w ater-saving agriculture and sustainable use of water and...

Water-Saving Agriculture and Sustainable Use of Water and Land Resources

Edited by Shaozhong Kang, Ph. D., Professor

Bill Davies, Ph. D., Professor Lun Shan, Ph. D., Professor

Huanjie Cai, Ph. D., Professor

Shaanxi Science and Technology Press

Xi��

Foreword Shortage of water resources and deterioration in the quality and availability of agricultural

land are worldwide problems. Water and land are critical resources and cannot be regarded as

available in abundance. Degradation of land, reduction of river flow and the increasing

frequency of severe dust storms have seriously damaged the natural environment and retarded

economic development. These problems have reached dangerous levels in many countries. It

is widely believed that an increase the efficiency with which water is used in agriculture is

one key way to reduce many of these problems. For many countries, agriculture is the largest

water user and to improve water use efficiency in agriculture would have a significant impact

on sustainable development. It is not only important to ensure availability of water in the right

quantity at the right time, but also important to ensure that water of an appropriate quality is

used in agriculture. Therefore, research on water efficient agriculture, and on sustainable use

of water and land resources in arid and semiarid areas has a high international priority.

Water shortage in China, particularly in Northwest China is very serious. This region

(including Shaanxi, Gansu, Ningxia, Qinghai, Xingjiang and Western Inner Mongolia)

accounts for 1/3 of the area of China, but has only 8.3% of total national available water

resources. While the water shortage in this region is serious, the waste of water resources and

water pollution remain as major issues. Overall irrigation water use efficiency is

approximately 40%, with atypical irrigation water productivity around 0.46 kg/m3. Excessive

irrigation in Ningxia and Inner Mongolia have had a significant influence on Yellow River

downstream water users. The frequency and severity of dust storms, sourced from the

Northwestern China, have been increased every year. This is accompanied by an increase in

the desertification of large areas of land.

The importance of water-saving agriculture and sustainable use of water and land resources

are increasingly being recognized by public and government authorities. To address many of

the important issues raised above, the ��

��

plant improvement for water-saving in water-limited areas and dryland, irrigation technology

and water management, sustainable use of water resources in arid and semiarid areas,

agricultural water and land environment. The secretariat received more than 240 abstracts, all

of them were edited, they and with the selected some full papers will be published in the

special issue of Journal of Experimental Botany, and the other full papers, which the

secretariat received, are published in this proceedings. We thank Du Taisheng, Martin Parkes,

Jeff Gale, Rupert Knowles, Rachel Caiger,Wang Zhinong, Hu Xiaotao, Ma Xiaoyi and the

anonymous reviewers who helped in checking papers and in preparing the conference.

Shaozhong Kang, Bill Davies, Lun Shan and Huanjie Cai

August 16, 2003

CONTENTS Section IV Sustainable Use of Water Resources

Methodology and models of ecological water amount estimation in the arid zone: the case in the no runoff areas in the lower reaches of Tarim River, China⋯⋯⋯⋯⋯ 4020 Ranghui Wang, Yingjie Ma, Huizhi Zhang, Hongbo Sun and Junfang Huang

Applying fuzzy synthetic clustering method to Hotan groundwater quality evaluation⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯4021 Yongfeng Fu, Bing Shen, Donghai Guan and Guangming Luo

Calculating phreatic water evaporation from bare soil for the Tarim River basin, Xinjiang⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯4022 Shunjun Hu, Shaozhong Kang, Yudong Song 1and Xiaobing Ceng

Groundwater issues in irrigated areas of North China⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ 4023 Xiaomei Wei, Duoduo Ba, Jianhuang Chen

Derivation of hydraulic functions of Gypsiferous soils using Pedo-transfer functions⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ 4024 M. Homaee and A. Farrokhian Firouzi

Developments in eco-hydrology⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ 4025 Huaien Li

Water reforms -need of the hour⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ 4026 Kiran Soni Gupta

Estimation of soil water retention curve with the derived Point and Parametric Pedo-transfer functions⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ 4027 M.Homaee and Sh. Ghorbani Dashtaki

Social values of water use and their economic impact in Jakham irrigation project of Rajasthan - India⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯4028 A.S.Solanki

Sustainable development and reasonable allocation of water resources⋯⋯⋯⋯⋯ 4029 Zhanyu Zhang and Baoping Feng

Model and application for fuzzy relation optimal decision⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ 4030 Shouyu Chen, Honglan Ji

Water rights allocation of Yellow River replacement water⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ 4031 Yuansheng Pei , Yunling Li and Fuliang Yu

Improvement of 10 large seasonal rivers feeding the Yellow River in Dalat Banner of Inner Mongolia⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ 4032 Baolin Ji, Zhiyuan Lu, Xiangdong Shen, Xianyou Mu and Dong Suo

Sewage purification investigations in Shandong⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ 4033 Jigang Ma, Zhenghe Xu, Juan Xie, Tianyou Li and Rong Cong

A new water resources appraisal system in water-saving irrigation⋯⋯⋯⋯⋯⋯⋯ 4034 Wei Chen, Lianheng Zheng and Wenjuan Liu

Conversion of Four Waters in wet and low-lying farmland in Sanjiang Plain⋯⋯⋯4035 Yongxia Wei, Baiying Kang, Daben Guo, Yanling Zhao and Qiang Fu

Causes of changes in run-off and sedimentation in the Weihe River Basin⋯⋯⋯⋯ 4036 Guoqing Wang and Haobing Li

Eco-environmental water demands and utilization limit for sustainable use of water resources of Northwest China⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯ 4037 Yu Wang

Model to optimize rainwater-harvesting system for irrigation⋯⋯⋯⋯⋯⋯⋯⋯⋯ 4038 Xinyan Zhang and Huanjie Cai

Analysis and strategic measures on the drought problems in Songnen Plain⋯⋯⋯ 4039 Hailin Yu

�

�� Ⅳ��

��

Methodology and models of ecological water amount estimation in the Arid Zone: the case in the no runoff areas in the lower reaches of

Tarim River, China

Ranghui Wang, Yingjie Ma, Huizhi Zhang, Hongbo Sun and Junfang Huang

Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang,830011,

China.

Abstract Ecological water use are new concept for management and research departments. The principle and

methodology of which is also an advanced field in Eco-hydrology. It is a key issues to protect natural

vegetation by means of ensuring ecological water use in arid zone. The ecological water use is mainly

consists off two parts in no runoff area in the lower reaches of Tarim River Basin. That is, total water

amount for restoration groundwater table and total stand water amount of the all river courses. The

former is including water amount for restoration of groundwater table, laterad discharge and evaporation

of water surface. They are estimated by model I, model II and model III respectively. The estimated

results are 8.99x108m3, 0.68x108m3/a and 0.132 x108m3/a respectively. Based on the groundwater depth

rising 4 meter requiring 5 years, the total water amount for restoration groundwater table is 2.61

x108m3/a by the model IV. The latter, i.e., total stand water amount is 1.992 x108m3/a estimated by model

V.

Key words: Arid zone, no runoff area, ecological water use, natural vegetation, ground water table,

estimation; model. e-mail: [email protected]

l Instruction

Water resource is the most precious resource in the life support system in the arid zone. The quantity and quality of water decide the ecological environment and social and economy development. In the 21st century, water resource and ecological environment protection is becoming a worldwide issues. At present, some new concepts which are on the ecology and environment to water resource utilization are turned up( Xu, 2003; Wang 2001). For instance, ecological water demand, ecological water use, consumption of ecological water, water demand for environment, water demand for ecosystem，water distribution for ecosystem，and so on．They are all the advanced fields in Eco-Hydrology (Zhao 2002). Ecological water use is the water amount that used In a kind of ecological level condition(Xu, 2003)．Some countries including Israel and Australia and America engaged In several researches In the field. The research of relation between natural vegetation and water, it has significance not only in the theory, but also in

the practice. Tarim River Basin, which is the important areas of global research and biodiversity conservation in China. The ecological construction In the Basin, is directly having close relations with ecosafty in the west China.

Ecological environment is quite fragile in the lower reaches of the Trim River Basin. Affected by human activities; there is no runoff below the Daxihaizi nearly 30 years. Great changes have taken place in the lower reaches of the Tarim River including terrain and geomorphology, soil, hydrology and organism, etc. Especially, during the evolution In the long term，natural vegetation formed physiologic mechanism and construction for adaptting to the drought habitat. Furthermore, some plants can store water moisture in their bodies relaying on special function. Not only Populous euphratica, but also Tamarix spp., Halimodendron halodndron, Lycium ruthenicum, Nitraria, Alhagi, Phragmites, Calmagrostis, Glycyrrhiza, Apocynum, they all have certain survival ability In the desert environment. So far, some researches based on SPAC have revealed the

laws and patterns of water moisture movement and plant adaptation in the desert environment (Daneil et al.,1981; Alvaro et al., 1994 ).

Most natural vegetation has dry-resistance characteristics in the arid zone. Meanwhile, some of them often could not have enough water supplies. The consumption of water is relatively little in per unit area. Meanwhile, Natural vegetation is not seriousness for water quantity and water quality. Ecological water use is mainly supply for natural vegetation growth. Apart from river course evaporation. the water is still used for sustaining ecological groundwater level and vegetation transpiration. Most of surface water is converted to groundwater by seepage for vegetation use. The availability of water resource is relatively high. 2 Methods

Quantitative estimation of ecological water use is an important basis for reasonable dispatching and distribution of water resource. So far, there are some methods for estimation of ecological water use by natural vegetation, such as, Transpiration method, Dry matter method, Soil evaporation- infiltration meter method, Hydro-thermo coefficient method, etc. In this research, some methodologies are used for estimating ecological water use (Song,2000; Wang, 1990).

Firstly, the estimation of total water amount of restoration of groundwater tables, which includes water amount of groundwater table restoration, lateral discharge and evaporation from water surface of river course. Water amount of groundwater table restoration is estimated by model I, i.e., △W=δ△hAn. Laterad discharge is estimated by model II, i.e., Qs=KIA1T.

According to the model III, Qe=ε. L. B. E0, the

evaporation from water surface of river course can be estimated. Based on model I, II and III, total water amount of restoration of groundwater table is estimated by model IV. If the duration lasts 5 years while the groundwater depth reaches 4m, the total water amount is calculated as follows, Q5=△W+5Qs+5Qe.

In addition, the total water amount for ecological stand is estimated by model V, i.e., Qk=Qs+Qe+Qv.

3 Quantitative estimation of ecological

water use in no runoff areas The ecological water use between Daxihaizi

and Tetema as mentioned above, among the calculation process below, a, b and c meaning is as follows, i.e., a: from Daxihaizi to Yingsu river course, b: from Yingsu to Alagan river course, c: from Alangan to Tetema river course. 3.1 The restoration water amount of ground water table in no runoff areas

Based on model I, among them, △Q is the water amount (108m3) while groundwater table rises △ h(m), △ h is the rising amplitude of groundwater table, δ is the saturation difference in variation belt of groundwater table, A is the calculating area, n is the dry soil capacity(g/cm3). Among them, L is the length of river course, the calculation of A based on banks that 1 km band width of vegetation protection along the river course. Soil moisture (n1) based on the experiment formula, n1=35.72exp(-0.185h). h is the depth of groundwater, the saturation difference of water bearing layer is 25.8%.

Restoration water amount for groundwater table in the no runoff area is showed in table 1.

Table 1. Restoration water amount in the no runoff area in the lower reaches of Tarim River

River course δ n △h(m) L(km) A(104hm2) △Q(108m3)

a 0.1403 1.36 4.00 54.0 1.08 0.82

b 0.1724 1.36 7.07 91.0 1.82 3.02

c 0.2018 1.36 5.37 175.0 3.50 5.15

total 320.0 8.99

3.2 Laterad discharge in the no runoff area

Based on model II, among them, Qs is annual laterad discharge, K is hydraulic conductivity of phreatic water(m/d), I is hydraulic gradient, A1 is the area of sectional area(m2), The width of sectional area is 30m, The length of sectional area is the total length of river course(m), T is the days(d). The annual lateral discharge water amount in the no runoff area is showed on table 2.

3.3 Annual evaporation of water surface in the no runoff area

Based on model III, among them, Qe is annual evaporation of water surface of the river course(108m3), Le is the length of river course(m). B is the average of river course(m). E0 is the annual evaporation of evaporation pan with 20cm diameter, ε is convert coefficient.

Taking into consideration of water delivery

condition, the length of the no runoff river course is 320km, so, Le=320×103(m), Qe=0.5×320×103

×30×2754×10-3=0.132×108m3/a.

Evaporation amount from water surface amount in the no runoff area is showed as table 3.

Table 2. Annual lateral discharge water amount in the no runoff area in the lower reaches of Tarim River

River course K(m/d) I A1(108m2) Qs(108m3/a)

a 2.4285 0.004 0.0324 0.12

b 2.4285 0.004 0.0546 0.19

c 2.4285 0.004 0.1050 0.37

total 0.3082 0.68

Table 3. Evaporation amount from water surface amount in the no runoff area

in the lower reaches of Tarim River

River course ε L(m) B(m) E0 Qe(108m3/a)

a 0.5 54000 30 2.754 0.022

b 0.5 91000 30 2.754 0.038

c 0.5 175000 30 2.754 0.072

total 0.132

3.4 The restoration water amount base on 5

years duration Based on model IV, among them, the meanings

of some parameters are similar to the former mentioned. In addition, W5 is the total water amount according to the duration of 5 years (108m3). Wa5 annual average restoration water amount depending on the duration of 5 years (108m3/a). Q5=Q+5Qs+5Qe=8.99+5×0.68+5×0.132=13.05×108m3

Wa5=W5/5=13.05/5=2.61×108m3/a

3.5 The total stand water amount of the all river courses

Among the model V, Qk is the annual stand water amount (108m3). Qv=A×E, E=Emax(1-e�E�20

/Emax), Qv is the annual water consumption of in protection area. A is the ecological protection area. E is the evaporation of phreatic water. Qs and Qe is lateral discharge and evaporation of water surface of river course. The calculation results are showed on table 4.

Table 4. The result of ecological stand water amount of the river course in the no runoff area

in the lower reaches of Tarim River

River course E A(106m2) Wv(108m3/a) Qs(108m3/a) Qe(108m3/a) Qk(108m3/a)

a 114.9 252 0.290 0.12 0.022 0.432

b 114.9 425 0.488 0.19 0.038 0.716

c 114.9 350 0.402 0.37 0.072 0.844

total 1027 1.180 0.68 0.132 1.992

4 Conclusions Ecological water use is a new field for

management department and research department. Many issues of theoretic and methodologies have to be studied gradually. The preliminary conclusions are as follows.

(1)Based on quantitative calculation, the quantitative values of ecological water use is made in the no runoff area in the lower reaches of Tarim River.

(2)On the basis of estimation of total restoration groundwater table and total stand amount, the former includes water amount of restoration

groundwater table, lateral discharge and evaporation amount from water surface amount, the later is that while the phreatic water depth rises 4m, water amount demand for vegetation transpiration, which includes average annual surface amount. According to target of ecological construction, plan should be reasonable made. The water amount of ecological water use in Daxihaizi sectional area is 4.602X108m3/a in 2005.

(3) Some issues should be emphasized. Such as, water demand features in different ecosystems including temporal and spatial distribution and transpiration patterns in natural oasis ecosystem,

water absorbability of root system of main vegetation types, water quality of ecological water use and ecological water standard, etc. meanwhile, some problems, which include the quota of ecological water use and using patterns for sustainable ecology and the rate of natural vegetation protection to production, are all should be solved as soon as possible. Acknowledge

This project is under the auspices of the National Key Project for Basic Research on Western Chinese Arid Areas (G1999043509) and also supported by Knowledge Innovation Project of CAS (KZCX-XJ02-02). It is also supported by Resource and Ecological Environment Project of CAS (KZ951-213-02). Professor Fan Zili and other researchers took part in discussing work. We are very appreciated for them. References Alvaro Brenes Vargas Victor F. Saborio Trejos.

Atmospheric circulation variation and its influences on precipitation tendency in Central America. AMBIO, 1994,23(1):87-90.

[Britain] Edited by Andrew J. Baird, Robert L. Wilby, Translated by Zhao Wenzhi, Wang Genxu., 2002. Eco-hydrology. Beijing: China Ocean Press.

Daneil D. Evans, John L. Thames, 1981.Water in Desert Ecosystems, Academic Press, America.

Lei Zhidong, Yang Shixiu, Xie Senchuan. 1984, Analysis and experiential formula of stable evaporation of phreatic water. Water Conservancy Journal, (8):60-64

Song Yudong. 2000, Research on Water Resources and Ecology of Tarim River, China. Urumqi: Xinjiang People��

��

��

��

�

Applying fuzzy synthetic clustering method to Hotan groundwater quality evaluation

Yongfeng Fu 1, Bing Shen 1, Donghai Guan 2 and Guangming Luo 3

1Xi��2��3��Abstract A fuzzy clustering method is combined with a fuzzy appraisal method where the former is adopted to sub-divide a water area and the latter is used to evaluate water quality. The groundwater quality in Hotan Prefecture of Xinjiang Autonomous Region is classified and evaluated in this way. A case study illustrates that this method is simple, practical and suitable for poor data. Key words: Fuzzy clustering; fuzzy synthetic appraisal; groundwater; water quality evaluation. E-mail: [email protected]

1 Introduction

Pollution of the water environment is an extensive environmental problem in our country, and evaluation of pollution status is a prerequisite to environmental protection. At present, there are several kinds of environmental evaluation approaches to use, such as a mixed weighting method, an appraisal index method or a gray clustering method (Deng , 1985). Although each appraisal method has its own strong points, there may be limitations over use of a specific method. For example, sometimes the appraisal index approach cannot truly reflect the environmental state being appraised. A mixed weighting approach might produce a result which is contrary to actual conditions at the time of appraising an environmental conditions (Li, 1991). Obviously, each method has its particular applications so it is important to perfect a range of appraisal approaches.

Both environmental pollution and its extent are both fuzzy concepts (Chen, 1992), so environmental evaluation can be made by the methods of fuzzy mathematics using environmental standards. In cluster analysis, the border of clusters should be clear enough and the membership between each cluster and its elements should be unambiguous. But in practice, some problems have ill-defined borders or an unidentified membership function. For example, the defining values for extents of water pollution are fuzzy. To solve these fuzzy classification problems, a fuzzy clustering approach can be used.

To evaluate water quality of a certain area, two main problems should be solved. Firstly, the area should be divided into a number of sub-areas, to get the equivalent fuzzy relationship for every water quality index of each sampled sub-area using

��

2 Fuzzy clustering of sub-areas 2.1 Data treatment

��n��xi ��i�� x1,x2, ⋯ xn�� xi�� m� �� xi1�� xi2�� ⋯� xim�� m×n��X��

�X��xi,j�n�m.��

)}min{}max{()}min{(1

,1

,1

,,’,

niji

niji

injijiji xxxxx

?????

??? �

� �� i,j�� i,j�� rij��xi��xj

��},,,,{ ’

,’,

’1, mikiii xxxx ???

},,,,{ ’,

’,

’1, mjkjjj xxxx ??? , then

??

???n

kkjkiji xx

nr

1

2’,

’,, )(

11 (3)

If ri,j is equal to 1, then xi and xj are completely different. If ri,j is equal to 0, then xi is completely the same as xj . Thus the similar relationship matrix R is formed by similar coefficients ri,j , which is denoted by

R= mnjir ?)( , (4)

2.2 Transitive closure approach

The fuzzy equivalent matrix, can be derived from the similar matrix using a Transitive Closure approach. Assume that R*(k powers of R) is the minimum fuzzy equivalent matrix which contains R, then R* is termed the Transitive Closure of R. It is generally obtained by the square method.

R2=R*R= )( 2, jir , (5)

where

),,2,1,(),( ,,1

2, njirrr jkki

n

kji ???? ?

?

.

(6) So, the matrix R* satisfies the relationship:

R* =��2222 *��

??��

RRRR , (7) When R* is derived, a different λ interceptive matrix can be obtained according to different levels of belief λ. The approach is given by

)( *,

*jirR ?? ， ]1,0[

0

1

,

,*, ?

???

??

? ???

ji

ji

ji r

rr (8)

Obviously, *?R is a Boolean matrix, when λ

varies from 1 to 0, so different *?R can be obtained

and corresponding clustering kinds also vary from n to 1. The upper process is fuzzy dynamic clustering analysis using Transitive Closure approach, and then fuzzy dynamic clustering graph can be drawn. 3 Fuzzy appraisal of water quality 3.1 Appraisal matrix

Using fuzzy dynamic clustering analysis, a water area can be divided into sub-areas of different water qualities. Then evaluation of water quality of every sub-area can be determined using fuzzy appraisal. Assume that there are m indices of water quality and their set is given as

},,{ 21 mi uuuuU ??? . Also there are c

grades of water quality evaluation, then the set of

appraisal criteria is given as: },,{ 21 cvvvV ?? .

So the single factor appraisal vector of the ith factor is denoted by:

},,,{ ,2,1, ciiii qqqQ ?? i = 1,2,? ,m) (9)

This is also a fuzzy subset in the appraisal set V, where qi, j stands for the membership degree of the

ith factor in the jth grade, so ijvu

qQ ��?),(? .

Thus a general appraisal matrix of m factors is

formed. The membership function ijq is derived

by an approach presented in (Zhang and Zeng, 1995).

For the first grade:

???

???

?

?

????

?

?

?

??

?

1,

1,,1,,

1,

,

0)(

)(1

jii

jiijijiji

jii

jii

ij

sx

sxssssx

sx

q (10)

For grades between 2 and c-1:

??

?

??

?

?

????

?

????

?

??

?

??

?

1,,1,,

1,

,

,1,1,,

1,

)()(1

)()(

jiijijiji

jii

jii

jiijijiji

jii

ij

sxssssx

sx

sxssssx

q (11)

For the cth grade:

???

???

?

?

????

?

?

?

??

?

1,

,1,1,,

1,

,

0)(

)(1

jii

jiijijiji

jii

jii

ij

sx

sxssssx

sx

q (12)

where xi is the surveyed concentration of the ith factor, sij is the standard concentration of the ith factor regulated in the jth grade water quality criterion.

3.2 Weighting of factors

Importance of every factor making up a water quality assessment, or weighting, must be taken

into account in an appraisal. The weight of every factor constitutes a fuzzy subset in the factor set U, which is given as

mm uauaA ??? ?11 (13)

where ia is the membership degree of factor iu

to set A, which is calculated by

i

ii s

xa ? , (14)

where ix is the surveyed concentration of the ith

factor and si is the base value of different water quality criteria corresponding to an index, which is usually derived from its legally-defined value.

When constituting matrix, ia needs to be

standardized. 3.3 Appraisal

When matrices Q and A are known then an appraisal can be obtained from

B = QA? = ( cbbb ,,, 21 ? ). (15)

If the elements of matrix B are standardized, the element bj represents an appraisal of a sub-area against jth grade when taking every factor into account. Zhu (1982) presents four evaluation

models, namely the main determining factor, main distinctive factor, weighted average and unequally averaged models. The main distinctive factor model is often used in water quality evaluation, since it makes full use of all the information and identifies the effect of the main factor as well. The model is described by

M（ ? ，V）， ?c

iijij qab

1

)*(?

?

}*,,*,*max{ 2211 cjcjj qaqaqa ?? (16)

4 Case study

Hotan lies to the south of Xinjiang Uygur Autonomous Region at the southern edge of the Takla Makan Desert. This arid district is mainly supplied by melt snow from the southern Kunlun Mountain and has a typical inland arid climate. The second phase project of the World Bank project in the Tarim Basin surveyed groundwater quality. Using the 1999 survey data, 60 samples are used, which may be grouped into 12 water quality indices. Each water quality index is considered as a clustering factor and part of the data is shown in Table 1.

Table 1. Cluster factors

Sample

pH

Conduct -ivity

Total

hardness Ca

Mg

K and Na

CL��

SO��

CO��

HCO��

Total alkalinity

Mineralization degree

1 7.4 2360 604 98.1 87 272 364 247 0 460 378 1400

2 7.3 3100 698 70.3 127 408 523 337 0 519 425 1830

3 7.4 4820 82.7 818 151 791 925 598 0 588 482 2990

4 7.7 1500 396 57.2 62 175 191 153 0 387 318 838

5 7.5 2250 606 124 72 224 345 249 0 374 307 1410

��

��

��

��

��

��

Suppose 0.81<λ<0.84, then the 60 samples are divided into 6 sets, namely, ｛3｝，｛18，33，35，44｝，｛42｝，｛43｝，｛49｝and the set composed of all the other samples. Thus, the whole area is divided into 6 sub-areas, which are denoted as S1，S2，S3，S4，S5 and S6. Five characteristic indices were selected namely pH, mineralization, total

hardness, ?Cl and ?24SO . Through fuzzy clustering analysis of these indices the results obtained are approximately the same as the above category. So the categorized results mentioned above are still used in the following discussion. To

evaluate the state of water quality of every sub-area, mean values of every index of all samples in each of the 6 sub-areas are used. These are presented in Table 2.

Based on the national water standard GB/T14848-93, the boundary value of the 4th and the 5th groundwater water qualities is the same. For samples with lesser concentrations it takes the 4th water quality, otherwise it belongs to 5th. Generally a range of concentrations specifies a specific quality. Xia (1999) recommends a procedure for identifying such ranges. Once the boundary value

Table 2. Average pollution factors of sub-area

Sub-area

PH

Conductivity

Total hardness

Ca

Mg

K and Na

CL��

SO��

CO��

HCO��

Total alkalinity

Mineralization degree

S1 7.4 4820 82.7 818 151 791 925 598 0 588 482 2990

S2 7.8 5890 754 77 137 1017 1152 567 0 699.8 574 3728

S3 8.5 7210 327 42.9 53.3 1400 1590 314 32 605 550 4160

S4 7.8 9220 1400 129 261 1520 1610 816 0 1610 1320 6020

S5 7.4 1660 1030 89.9 196 180 156 752 0 473 388 892

S6 7.5 2281 531.8 77 191 286 313 256 0 482.5 395.8 1318

Table 3. Water quality standards

Evaluation factor Grade 1 Grade 2 Grade 3 Grade 4 Grade 5

pH 7 7.8 8.2 8.6 9

Mineralization degree 300 400 750 1500 2000

CL� 50 100 200 300 350

SO�� 50 100 200 300 350

Total hardness 150 225 375 500 550

Note: Concerning pH, the value of the first grade is 7.0; if it varies over the range [5.5, 9], then water quality belongs to the fifth grade. A classification criteria for pH values is less than 7.0 is not presented in this table.

of the first grade standard is established, then the average of the first and second grade boundary values identifies a second grade representative value. Based on the national groundwater quality

criteria and the classification principle mentioned above, so grade representation values of the indices being examined are presented in Table 3.

It can be seen from Tables 2 and 3 that except for pH, most of the other four indices for each sub-area

exceed the water quality criteria. Mineralization degree is the most serious and there are four out of six sub-areas where the ore degree is beyond the 5th grade water quality criteria. Water quality is worst in sub-area B4, where there are four indices rated below the 5th grade water quality criteria. The water quality is the best in sub-area B6. The main distinction factor model is used to evaluate the general state of water quality. Results are presented in Table 4.

Table 4. Results of fuzzy synthetic evaluation

Sub-area Grade 1 Grade 2 Grade 3 Grade 4 Grade 5

B1 0.028158 0.026996 0 0 0.944846

B2 0 0.046142 0 0 0.953858

B3 0 0.018119 0.038502 0.117439 0.82594

B4 0 0.033448 0 0 0.966552

B5 0.026542 0.068934 0.121035 0.028268 0.755221

B6 0.039151 0.065251 0.219771 0.456057 0.219771

From this, the water quality is worst in the

sub-area B4, where the membership degree of the 5th grade water is up to 96%. Water quality is also regarded as the 5th grade in the B1, B2, B3 and B5, sub-areas, since the membership degree there is between 75% and 95%. For; as to the sub-area B6, it can be regarded as that the water quality there belongs to the 4th grade since the membership degree of 4th grade there is the biggest among the five membership grades. Since there are 52 samples in the sub-area B6, which is a majority of the collectivity, it can be concluded that the water quality of the whole area belongs to the 4th grade.

5 Conclusions Both environmental pollution and its extent are

fuzzy problems, which is usually neglected in traditional water quality evaluation. Adopting fuzzy appraisal, this paper evaluates the water quality of Hotan and gets a relatively objective evaluation. References Chen Shouyu. 1992. Fuzzy hydrology and the

fuzzy optimal principle of water resources. Dalian: The publishing house of Dalian University of technology, pp.51~54.

Deng Julong. 1985. Gray system. Beijing: The publishing house of national defense industry, 1985.

Li Renxie. 1991. The regional environmental quality synthetic appraisal formula. Environmental Science, (1): 75~79.

Xia Jun. 1999. Regional water environment and ecological environmental quality evaluation ��

��

��

�� 2��

�

1

Calculating phreatic water evaporation from bare soil for the Tarim River basin, Xinjiang

Shunjun Hu 1,2, Shaozhong Kang 2, Yudong Song 1and Xiaobing Ceng 1

1Xingjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China. 2Key Laboratory for Agricultural Soil and Water Engineering in Arid Areas. Ministry of Education, Yangling, 712100, China.

Abstract Data for 1984-1987 has been used to develop empirical formulae to calculate phreatic water evaporation from bare soil. Results show that the main factors are phreatic water depth (H, m) and atmospheric evaporation capacity or demand（E20, mm/d）applied to sandy loam soils of the Tarim River Basin. The smaller the phreatic water depth is, the greater the influence of atmospheric demand is. When the phreatic water depth is larger than a critical value, phreatic water evaporation becomes close to zero. For a given phreatic water depth, when atmospheric demand is small, then phreatic water evaporation increases with demand up to a critical value, the limited phreatic water evaporation Emax. When atmospheric demand is small, a power type formula is suitable to estimate phreatic water evaporation for regional sandy loam soils, using either the phreatic evaporation coefficient C = E/E20 = 0.1045H-0.669 �� 20��-1.8456�� max ��E20

/Emax�� η�� -0.5215� �� max� �� 10.302H ��

��max��mE20��1.0528H��

�Key words: ��

��

E-mail: ��

1 Introduction 1.1 Previous studies

��

��

��

�� 2 �� 1.2 Groundwater evaporation data

��20��

2

by a 20 cm diameter evaporation pan, denoting atmospheric evaporative demand. Figure 1 shows that the change of monthly groundwater evaporation from June, 1984, to October, 1987. It demonstrates that atmospheric evaporation

demand is strongest in June, July and August, and variation of groundwater evaporation matches the variation of atmospheric demand, especially for a groundwater depth of 0.25 m.

0

2

4

6

8

10

12

14

Dec-83 Dec-84 Dec-85 Dec-86 Dec-87

time T

E(mm

/d),

E20(

mm/d

)

E20 0. 25m 0. 75m 1. 25m 1. 75m 2. 25m

Figure 1. Monthly average groundwater evaporation rate E and evaporation pan data (E20)

Figure 2 is a graph of accumulated groundwater

evaporation as a function of groundwater depth during the frost-free period from April to October

in 1985. The general trend is that cumulative phreatic water evaporation decreases as water depth increases.

0

100

200

300

400

500

600

0. 0 0. 5 1. 0 1. 5 2. 0 2. 5Phreat ic water depth ( m)

Acc

umul

ativ

e ph

reat

ic w

ater

evap

orat

ion(mm)

Figure 2. Cumulative phreatic water evaporation vs phreatic water depth during frost-free period (1985)

1.3 Influence of atmospheric evaporative demand on phreatic water evaporation The relationship between phreatic water

evaporation, atmospheric evaporative demand and groundwater depth is shown in Figure 3. Phreatic water evaporation increases linearly with increasing E20. For a given groundwater depth, when the atmospheric evaporative demand reaches a critical value, Eoc, the phreatic water evaporation approaches a limiting evaporative flux. The deeper the groundwater depth, the

smaller is the critical atmospheric evaporative demand and the limited evaporative flux. Correlation analysis was carried out to determine relationships between monthly average phreatic water evaporation and monthly average atmospheric evaporative demand for 0.25, 0.75, 1,25, 1.75 and 2.25 m groundwater depths with the 1984 to 1987 data from Aksu water balance experimental station. Results are shown in Table 1.

3

Figure 3. Relationship between phreatic water evaporation, atmospheric evaporation demand and groundwater depth

Table 1. Correlation coefficient and slope for pan evaporation and the phreatic water evaporation

phreatic water depth

correlation coefficient

slope

0.25 0.8129 0.7110 0.75 0.4906 0.6254 1.25 0.4815 0.6043 1.75 0 0.5764 2.25 0.2522 0.5625

The table shows that a correlation exists

between phreatic water evaporation and pan evaporation data when the ground water depth is small, the correlation degree is close, with the phreatic water depth increase, the correlation decrease. It shows that the phreatic evaporation is related not only to the water surface evaporation E20, but also to the water transportation characteristics of soil.

2 Fitting empirical formula to phreatic

water evaporation data 2.1 Ratio of phreatic water evaporation and

evaporative demand Empirical formulae are more frequently used,

either relating phreatic water evaporation and groundwater depth, or also including evaporative demand. The ratio of phreatic water evaporation

and evaporative demand is called the phreatic water evaporation coefficient C. This is plotted as a function of groundwater depth (H) in Figure 4. Variation of phreatic water evaporation coefficient C with depth shows an inflection at point M. To the right of M, change of phreatic water evaporation coefficient C is small. To the left, change of coefficient C with water depth is sharp. So M can be called a characteristic point of phreatic water evaporation with a corresponding phreatic water depth is 0.5 m, determined by an optimal partitioning method of clustering. 2.2 Existing empirical relationships

Data in Figure 4 was fitted to existing regression equations to determine the corresponding regression coefficients. The results were:

(i) power function ： C=0.1045H-0.669 (n=5, R2=0.9563 ) (1)

(ii) exponential ： C=0.2522e-0.6964H (n=5, R2=0.8567) (2)

(iii) logarithmic ： C=-0.0967ln(H)+0.1223 (n=5, R2=0.9155) (3)

(iv) Zhang Chaoxin��：��-1.8456��2��

�� Ав� � � � � � �� еръянов：��2.4949��2��

��

��

0

1

2

3

4

5

0 5 10 15 20

Atmospheric evaporative demand (mm/ d)

Phre

atic

wat

erev

apor

atio

n(m

m/d) 0. 25m

0. 75m1. 25m1. 75m2. 25m

Figure 4. Relationship between evaporation coefficient and water depth

0. 0

0. 1

0. 2

0. 3

0. 4

0. 5

0. 0 1. 0 2. 0 3. 0

Phreatic water depth( m)

Phre

atic

wat

er

eva

pora

tion

coef

fici

ent

��

4

2.3 Improved relationships Lei Zhidong (1988) considered the influence of

atmospheric evaporative demand and groundwater depth on phreatic water evaporation and proposed the following formula:

)6()/

1(maxmax20 EE

eEE??

??

where Emax is the limited rate of phreatic water evaporation (mm/d), η is an empirical constant, which is related to soil texture and phreatic water depth.

Lei (1988) and Mao (1998) let η = 0.85. Re-arranging equation (1) gives:

ln(1-E/Emax)=-ηE20/Emax (7) Then Table 2 gives values of ηfor the Figure 4

data.

Table 2 Value ofηcorresponding to different groundwater depths

Groundwater depth H(m)

η

0.25 0.3163 0.75 0.1132 1.25 0.1112 1.75 0.0982 2.25 0.1024

The fitted regression equation is η=0.1309H-0.5215 (n=5, R2=0.849) (8)

On the basis of previous analysis of the

relationships between E and E20 and H, a new empirical formula is proposed as follows:

)9()1(max20mE

eEE?

??

assuming that E20→0， E→0; E20→∞，E→Emax.; then m = 0.0102e1.0525H . 2.4 The new empirical formula II

All the C ～ H empirical formula mentioned above think the relationship between phreatic water evaporation rate and atmospheric evaporation capacity is linear, but this doesn�� max��20�� ～ �� Аверъянов� ��

��E=a E20 p (1-H/Hmax)

n ��

��E=0.5696 E200.5523 (1-H/5)2.7184 ��

2.5 The new empirical formula III

�� μΔ��μ�20�q ��-��μ�� ，�� β��

E =k E20 q H-� ��（��）��

�� ln(E)=ln(k)+qln(E20)-ln(H)��

��β��20

0.5481 �-0.7390��

3 Analysis of accuracy of empirical formula

�� ～�� -b ��，��，�� Аверъянов� �� ～�20～��

4 Conclusions

��

�� （�20，��）��

5

becomes close to a constant, limited phreatic evaporation Emax. The phreatic evaporation decreases with the increase of phreatic water depth.

(2) When the atmosphere evaporation capacity is small, the Power Type Formula, the phreatic evaporation coefficient C=E/E20= 0.1045H-0.669 and Zhang C�� 20��-1.8456�� max��E20

/Emax�� η��-0.5215� ��

��10.302H �� max��- mE

20�� 1.0528H�� 20

0.5484�-0.7390��

References ��

�� （�）：��

��

�� ， �� （�）��

��

��

��，��

�� 21��

�� 8��

�� 3��

��

��

��，�� 18��：��

��

��

��

��

��

��，�� ：��

��

��

��

��，�� 21��

�� 6��

�� 14��：��

1

Groundwater issues in irrigated areas of North China

Xiaomei Wei, Duoduo Ba, Jianhuang Chen

College of Water Conservancy and Architectural Engineering, Northwest Sci-Tech University of Agriculture and Forestry, Yangling, Shaanxi, 712100, China.

Abstract

Trends in groundwater use in irrigated areas of North China identify negative effects of human activities. Reduction of groundwater resources has affected the eco-environment and prospect of sustainable use of groundwater resources. To counter those problems, making full use of the storage and adjustment functions of subsurface aquifers is proposed. Controlling groundwater resources through combined use of surface water and groundwater are the effective ways to realize the sustainable development of irrigation agriculture. Key words: Irrigation area of North China; groundwater issues; eco-environment of agriculture;

adjusting and controlling means. E-mail: weixiaomei57 @163.net

1 Introduction

North China is very dry. So, sustainable development of agriculture heavily relies on its water resources. The irrigated area of North China is 252.4 million ha or 50.4% of the national irrigation area. In North China, the crop yield of irrigated land is 2.5 times more than that of dryland farming. Sometimes it can even be more than 4 times when the year is extremely dry. Development of an irrigation area not only provides basic conditions for grain production and agricultural by-production but also ensures safety of the eco-environment and promotes sustainable development of social economy.

Groundwater is clean, widely dispersed and can be accessed as a local reservoir, making it an important component of water resources. Water resources are scarce in North China, but its groundwater resources in the plain area cover 78% of national groundwater resources. The ratio of groundwater to surface water resources is also higher than South China. So, the rational exploitation of groundwater is especially important to North China. Currently, there are 2 million motor-pumped wells for agriculture in 17 provinces and municipalities directly under the central government, with an annual exploitation 40 billion m3 of groundwater to irrigate 11.33 million ��

�� 2 Evolution of groundwater resource

use of IANC 2.1 Historical perspective

��

��

2

Yellow River irrigation area, leading to reduced groundwater resources. 2.2 Necessary and efficient practices

Groundwater recharge by irrigation infiltration is reduced due to application of efficient water-saving irrigation techniques. Canal water seepage and deep percolation from farmland are reduced while irrigation application efficiency is raised. With the spread of high yielding and superior quality crops and more fertilizer, so crop yield has markedly increased. With the increased farmland activity so groundwater infiltration from precipitation and irrigation water is decreased also.

Comprehensive measures of water and soil conservation can intercept precipitation efficiently and increase soil water storage. This enhances drought resistance. However, these measures change both the timing and amount of surface runoff and groundwater flow. In some extent, surface runoff and groundwater flow has decreased. 2.3 Groundwater over-exploitation

Groundwater exploitation is the main way of groundwater drainage in IANC. In last 20 years, with accelerating economic development of use of groundwater as a proportion of total water resources has increased remarkably. Especially in the Yellow River, Huihe River and Haihe River-Luanhe River Plain, rates of groundwater exploitation are 92%, 65% to 77% and 105% to 143% respectively. 3 Main groundwater issues in IANC 3.1 Water-logging and soil salinization

Water-logging and soil salinization disasters were a common problem during the 1950s to 1980s in IANC. This resulted from irrigation with large amounts of surface water and a consequent rapid increase of groundwater resources. Groundwater evaporation intensified and salt accumulated in surface soils. Salinized soil areas increased from 30,000 ha2 to 210,000 ha in the 24 years from 1949 to 1973 in Hetao Irrigation Area of Inner Mongolia. The groundwater table also rose 10-30 m during 1971 to 1980 in Baojixia Irrigation Area of Shaanxi Province, which led to some ponds appeared in lower location and salinized soil areas totalled 2000 ha. These consequences seriously imperiled agricultural production. Similar problems also appeared in the Yellow River Diversion Irrigation Area of Ningxia Hui AR, Jingtai Irrigation Area of Gansu Province and Jinghuiqu Irrigation Area of Shaanxi Province. Lately, waterlogging disasters have been treated by digging wells and constructing drainage canals. However, if groundwater recharge and drainage problems are not properly resolved, some irrigation areas are still threatened by potential secondary salinization. These locations mainly depend on surface water irrigation such as the

Yinbei Irrigation Area of Ningxia Hui Nationality AR, Yellow River Diversion Irrigation Area of Nei Menggu AR, Yeerqiang River and Akesu River Irrigation Area of Xinjiang Uygur AR. 3.2 Reduction of groundwater resources? 3.2.1 Effects of drought and increased usage

At present, the groundwater exploitation area totals 658,000 km2 and in 160,000 km2 of this a groundwater depression funnel has formed. Continuous decline of the groundwater table brings consequences for well irrigated or well-canal irrigated areas. Consequent problems include the drying up of motor-pumped wells and increasing energy consumption per unit of pumped water. In Shijiazhuang district, because of the large fall of groundwater table, costs of pumping water increased from 120 Yuan/ha.a in the early 1970s to 742.51 Yuan/ha.a. This is a 6 fold increase based on tripled energy consumption. Rates of pumped wells drying up is 3-10% per annum, and the speed of machine replacement becomes faster and faster. It is estimated groundwater resources of this city will be depleted within the next 15 years if the groundwater is not scientifically and efficiently and managed. While Jinghuiqu Irrigation Area of Shaanxi Province is an example conjunction management of both surface and groundwater, its groundwater table has dropped 10-20 m because of decreased river diversion and increased exploitation of groundwater. This has influenced the sustainable development of irrigated agriculture. 3.2.2Vegetation destroyed and land desertification

The sharp drop in groundwater table in arid IANC threatens the vegetation that depends on groundwater. The result is receding vegetation, land desertification and decreased crop yields. Over the last 20 years, there has been undue exploitation of groundwater resources in the Lower Reaches of the Shiyanghe River, since surface water resources flowing into the Minqin Basin have decreased. This was caused by development of industry and agriculture in the upper reaches. Over-exploitation of groundwater has reached about 0.3 billion m3 per annum to maintain development of Minqin Oasis. The groundwater table has dropped sharply, farmland is seriously scarce of water, and in most of the farmland beside canals and irrigated areas the vegetation is withering and receding. Desertification becomes worse. 33,300 ha of natural bush that has withered, and 20,000 ha farmland has become desert. These events seriously threaten the survival of Minqin Oasis. 3.2.3 Groundwater quality deteriorated and insecure groundwater use

Decline of the groundwater table in the coastal plain leads to a change in the balance between fresh water and seawater, resulting in seawater intrusion. As a result large groups of motor-

3

pumped wells are unused, farmland has no fresh irrigation water, and the population and livestock have no water to drink. In Liaoning, Hebei and Shandong Provinces, annual exploitation of non-renewed groundwater is 130 million m3, so large areas are salinized by the seawater intrusion and the reduced irrigation area exceeds 40,000 ha. The sharp drop of groundwater table also changes the original groundwater conditions leading to accelerated groundwater pollution by polluted rivers, waste water seepage, fertilizer, pesticide and improper irrigation by waste water. These actions not only pollute the farmland but also represent insecure groundwater use. Groundwater monitoring data of Hebei Province during 1995 to 1997 indicated that that quite a proportion of the groundwater in the plain located south of Beijing �� 3.2.4 Land subsidence and land cracking

�� 4 Means of groundwater control 4.1 Conjunctive surface and groundwater use

to control salt ��

��

4.2 Conjunctive surface and groundwater use to conserve groundwater sources

�� . References ��

��

��

��

��

��

��18��

�� 19��

��

� �1

Derivation of hydraulic functions of Gypsiferous soils using Pedo-transfer functions

M. Homaee and A. Farrokhian Firouzi� �

Department of Soil Science, University of Tarbiat Modarres, Tehran 14155-4838, Iran .

Abstract The objective of this study was to derive some Pedotransfer functions to predict the retention curve, the van Genuchten and the Mualem-van Genuchten parameters of some Gypsiferous soils. Consequently, 35 gypsiferous soil samples from different part of a semi-arid area were collected. The gypsum content was measured by acetone method, bulk density by volumetric method and the soil water retention curve was obtained using pressure plates apparatus. The gypsum of the soil samples was then removed by distilled water. Particle size distribution was determined into two steps: (i) with gypsum, by covering the particles with Barium Sulfate (ii) without gypsum, using hydrometery method. The easily obtainable variables were grouped into two groups (1) particle size distribution, bulk density and gypsum content, (2) bulk density, gypsum content, geometric mean and geometric standard deviation of particle diameter. The stepwise multiple linear regression method was used to derive the PTFs. Two types of parametric functions and two types of point functions are derived using of these variables. Comparison of the results indicated that the first group of variables had better prediction of water retention, the van Genucthen and the Mualem-van Genuchten parameters than the second group. The gypsum content appeared to be the second dominant parameter to predict the water retention at 0, -33, -100, -300, -500 and ��

�Keywords: ��

�� E-mail: ��

�1. Introduction

��

��

��

��

?h��* ��*��* ��*��* ��

��?h ��h��a��b��c��d��x�� X� �� ?� ��

� �2

The second, the parametric PTF, presumes that the ? - h relation can be described adequently by any parametric hydraulic model e.g. Van Genuchten (1980), Campbell (1974) and Brooks and Corey (1964). This approach is more stratighforward than the point prediction procedures, becaused the predicted parameters are directly applicable in the numerical ��

��

�? ? m]nah[1

r?s?r??

?

??? ��

��?r��?s�� ? �� n�� m� ��

�� m=1-n

1, ��

��

? ? ? ?

2Se

o

1

o

xdxh

1 / xd

xh

1eSK(h)

???

?

?

???

?

?? ? ?l

sk � ��

�� l� �� x� �� Se ��

��

? ?

2m

m

1

eS-1-1 leSeSK

????

?

?

????

?

?

????

?

?

????

?

?

? sK ��

��

�� 2. Materials and Methods

�� Typic Haplopypsids and Typic Cacigypsids�� ? ��? �� ? ��?� �� ?��

��

��

��(?b)��-3

��(%)��(dg) ��(? g). �dg� �� ? g� ��

��

dg=exp (�� iMlnn

1iif?

?) ��

? g�� ? ? ?n

1i aMlnif01.0 ��

�� n��if ��

��

��

�� ?r�� ? � �� n� �� l��Ks��

��

��

��

�� l, K0 and ? ��

)Gypsumln(*Gypsum ? �5.0)lexp(*l ? �

)0Klog1log(*0K ?? �

)ln(* ?? ? �

�� *Gypsum � *l �� *0K � �� *? ��

��0�� ? ��

��

� �3

because the silt and clay particles showed strong linear relation. Table 1. Mean, Maximum, Minimum and SD of soil properties with gypsum

Variable Bulk density (Mm-3)

Sand (%)

Silt (%)

Clay (%)

Gypsum content (%)

dg (mm) ? g (mm)

Mean 1.29 53.37 24.43 22.20 12.00 0.1254

14.548

Maximum 1.65 77.00 44.00 56.00 32.70 0.2929 19.754 Minimum 0.90 5.00 8.00 8.00 3.78 0.0050 7.255

SD 0.18 18.16 10.06 10.14 8.04 0.0854 2.611

Table 2. Mean, Maximum, Minimum and SD of soil properties without gypsum Variables Bulk density (Mm-3) Sand (%) Silt (%) Clay (%) dg (mm) ? g (mm)

Mean 1.35 49.03 22.79 28.17 0.1031 15.952 Maximum 1.59 85.00 40.00 59.00 0.4264 20.808 Minimum 1.11 8.00 5.00 10.00 0.0051 8.723

SD 0.1266 20.69 10.89 12.14 0.0986 3.265

Table 3. Mean, minimum and maximum values of vav Genuchten and Mualem van Genuchten parameters before gypsum removal from samples

Paramater Mean Minimum Maximum )kpa( 1?? 0.2461 0.0041 0.0892

n (-) 1.4608 1.0948 1.8300

)cmcm(s��? 0.3836 0.2402 0.5043

)cmcm(r��? 0.0933 0.0003 0.2765

l (-) -2.091 -12.733 0.062 log K0 05227 -0.4760 1.8300

Table 4. Mean, minimum and maximum values of van Genuchten and Mualem-van Genuchten parameters

after gypsum removal from samples Paramater Mean Minimum Maximum

)kpa( 1?? 0.2461 0.0041 0.0892

n (-) 1.4608 1.0948 1.8300 )cmcm(s ��? 0.3836 0.2402 0.5043

)cmcm(r ��? 0.0933 0.0003 0.2765

l (-) -2.091 -12.733 0.062 log K0 05227 -0.4760 1.8300

3. Results and discussion

Development of Pedotransfer Functions The easily obtainable variables were grouped

into two groups (1) Particle-size distribution, bulk density and gypsum content (2) bulk density, gypsum content, geometric mean and geometric standard deviation of particle diameter. The stepwise multiple linear regression method was used to derive the PTFs. Two types of parametric functions and two types of point functions are derived of these variables.

3.1. Point PTFs

The point Pedotransfer Functions predict water retention content at ��

(1) First type Point PTFs ��

��

��

��

�� ?s��

(2) Second type of point PTFs ��

��

� �4

gypsum content). The derived PTFs for this group are listed in Table 6.

As can be seen in this table, in most of the derived functions, gypsum content and dg are the dominant variables for the predicted water content.

Comparison of 2adjR for first and second type

of point PTFs indicated that the first group of variables can better predict the water retention at the range of interest.

Table 5. The derived first type Point PTFs NO.

Function� � Pedotransfer Function�Derived� � R2adj��

1� � 10-2???

????

?ClaySilt

��3.409��BD�0.149��Sand�102�� 3.81��0.290�� ?10kpa� � 0.77� �

2� � BD�0.123��Gypsum*�10-2�� 3.148��Sand��?��-3�0.214�� ?33kp� � 0.69� �3� � Gypsum*�10-2�� 2.877��Sand�10-3�� 2.43��0.262�� ?100kpa� � 0.54� �4� � Gypsum*�10-2�� 3.245��Sand�10-3�� 2.18��0.214��?300kpa� � 0.57� �5� � Gypsum*�10-2��3.681��Sand�10-3�� 1.98��0.181��?500kpa� � 0.56� �6� � Gypsum*�10-2�� 3.039��Sand�10-2��0.171��0.156�� ?1500kpa� � 0.47� �7� � Sand�10-3�� 1.83��0.210�� AWC� � 0.42� �

Table 6. The derived second type of Point PTFs

NO. Function� �

Derived Pedotransfer Function� � R2adj��

1� � -3s g �10�7.97��10-2 Gypsum*�0.271-1.009dg+0.160 BD + 3.659� ?10kp� � 0.760� �2� � � 0.139 BD+ 4.098 Gypsum*�� dg�-0.676�10-2�� 5.91� �?33kpa� � 0.64� �3� � BD�10-2�9.352�Gypsum*�10-2�3.317��dg0.477�10-2�� 5.87� �?100kpa� � 0.52� �4� � BD�10-2�8.023�Gypsum*�10-2�3.562��0.392 dg�10-2�� 5.574�� ?300kpa� � 0.50� �5� � 10-2 BD�7.198�Gypsum*�10-2�3.938��0.352 dg�10-2��2.068�� ?500kpa� � 0.50� �6� � 10-3 s g �4.97�Gypsum*�10-2�3.083��0.380 dg�0.148�� ?1500kpa� � 0.38� �7� � BD�10-2�7.927�dg10-2�0.346��10-2�� 5.411�� AWC� � 0.48� �

Fig.1.Comparison between the measured and estimated water retention at: (a) s? , (b) FC, (c) PWP and (d) AWC

��

��

��

��

��? measured (m3 m-3)

? measured (m3 m-3)

? pr

edic

ated

(m

3 m

-3)

��?

pred

icat

ed (

m3 a

b

c d

� �5

3.2 Parametric PTFs (1) First type parametric functions These functions predict the van Genuchten and

Mualem-van Genuchten parameter from first group of variables. The obtained functions for this group is given in Table 7.

The strong negative correlation between sand content and r? shows that the residual water

content reduce due to decreasing particle surface area.

(2) Second type parametric functions

These functions predict the soil hydraulic parameters parameter from the first and second group of variables. The results obtained are listed in Table 8.

The comparison between first and the second

type parametric PTFs indicated that the second group of variables ( BD,g,gd ? and gypsum

content) could provide better prediction for the hydraulic parameters.

Table7. The derived first type parametric PTFs

NO. Function� �

Derived Pedotransfer Functions� � R2adj��

1� � BD�10-2�9.116�????

??

Clay

Silt�10-2�3.748�Gypsum*�10-2�3.45� 10-3 Sand�3.3�0.325�?s� � 0.73� �

2� � Sand�10-3�1.94�0.197�?r� � 0.25� �

3� � ????

??

Clay

Silt�0.716�10-2 Sand�3.425�-5.07�a*�� 0.66� �

4� � Sand�10-3�6.38�1.81�n�� 0.22� �

5� � ????

??

Clay

Silt�0.108�Sand�10-3��6.197�10-2�-5.68� �K0

*� � 0.48� �

6� � 0.367 BD�????

??

Clay

Silt�0.278�Sand�10-3�8.10�0.153�l*� � 0.59� �

Table 8. The derived second type of Parametric PTFs

NO. Function� � Derived Pedotransfer Functions� � R2adj��

1� � 10-3 s g�7.48�BD�0.101�Gypsum*�10-2� 4.338� 0.822dg ��0.367�?s� � 0.68� �2� � 0.315 dg�0.133� ?r� � 0.13� �3� � 0.121 s g��dg�8.345�-6.897�a*� � 0.53� �4� � 1.056 dg�1.602�n� � 0.12� �5� � 10-2 s g �3.245�1.492 dg�0.513��K0*� � 0.44� �6� � BD�0.432�1.89 dg�0.189�l*� � 0.41� �

23 % gypsum

0

20

40

60

80

100

1 E - 04 0 .001 0 .01 0 .1 1 10

Particle diamater ( mm )

Part

icle

s cu

mul

ativ

e fr

eque

ncy

(%)

With gypsum

Withoutgypsum

8.5% gypsum

0

20

4060

80

100

0 0 0.01 0.1 1 10

P at ricle diamater (mm)

Part

icle

s cu

mm

ulat

ive

freq

uenc

y (

%)

W ith gypsum

W ithoutgypsum

Fig. 2. Particle size curve of the clay loam sample with and without gypsum

� �6

3.3. Effect of gypsum on particle size distribution

The paired t test was performed to compare the particle-size distribution of soils with and without gypsum. The results indicated that the removal

gypsum tend to increase the clay percentage and reduces sand and silt percentage. (p?0.01).

This Figure shows that gypsum removal reduces the sand particles and increases the clay percentage.

3.4 Effect of gypsum on soil water retention The paired t test was performed to compare the

water retention for the soil samples with and without gypsum. The results indicated that water retention increased at matric potential of 0, -10, -33, -100, -300, -500 and ��

��

��

21% gypsum

0

400

800

1200

1600

0 10 20 30 40 50

Moisture volume percentage

Mat

ric

pote

ntia

l (kp

a)

With gypsum

Without gypsum

15% gypsum

0

400

800

1200

1600

0 10 20 30 40 50


Mat

ric

pote

ntia

l

With gypsum

Withoutgypsum

4.2% gypsum

��


Mat

ric

pote

ntia

l (kp

a)

With gypsum

Without gypsum

Fig.3. Soil water retention curves loamy texture with and without gypsum for different gypsum content

� �7

3.5 Effect of gypsum on soil hydraulic parameters

Effect of gypsum on these parameters was investigated with paired t test. The results of paired t test indicated a significant difference between n and s? parameters for the samples

with and without gypsum (p?0.01). The removal gypsum from the soil samples did not significantly increase the mean values of �K,r? ��l ��

�4 Conclusions

�� g,gd ? ��

��

��

��

��

��

��

�References ��

��

��

��

��

��

��

��

��

��

��

��

��

��

��

��

��

� �8

Mashali, A. M., 1996. Soil management practies for gypsiferous soils. In: Poch, R. M. (Ed.), Proceeding of the International Symposium on Soils With Gypsum, 15-21 September 1996. Edicion Universitat de Lieda, Catalonia, Spain. Pp. 34-52.

Mousli, O. F. 1980. Methods of evaluation and classification of gypsiferous soils and suitability for irrigated agriculture. In: 3rd soil class. Workshop. (ed. Beinroth F. H. and Osman) ACSAD. Syria. 278-307.

Mualem, Y. 1976. A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res. 12(3): 513-522.

Poch, R. M., W. D. Coster, and G. Stoops. 1998. Pore space characteristic an indicators of soil behaviour in gypsiferous soils. Geoderma. 87: 87-109.

Porta, J. 1998. Methodologies for the analysis and characterization of gypsum in soils. Areview. Geoderma. 87: 31-46.

Rawls, W. J. and D. L. Brakensiek. 1982. Estimating soil water retention from soil�water properties. Trans. ASAE.108(IR2): 166-171.

Rawls, W. J.and D. L. Brakensiek. 1985. Prediction of soil water properties for hydraulic modeling. In: Jones, E.B. and T.J. Ward (Eds.). 1985. Watershed management in the eighties. Proc. Irrig. Drain. Div, ASCE., Denver, Co. pp: 293-299.

Schaap, M. G. and F. J. Leij. 1999. Improved prediction of unsaturated hydraulic conductivity with the Mualem-van Genuchten model. submitted to Soil Sci. Am. J.

Shirazi, M. A. and L. Boersma. 1984. A unifying quantitative analysis of soil texture. Soil Sci. Soc. Am. J. 48: 142-147.

Tomasella, J., M. G. Hodnett and L. Rossato. 2000. Pedotransfer function for the estimation of soil water retention in Brazilian soils. Soil Sci. Soc. Am. J., 64: 327-338.

Van Genuchten, M. Th. 1980. A closed-form equation for predicting the hydraulic conductivity of soils. Soil Sci. Soc. Am. J. 44: 892- 898.

Van Genuchten, M. Th., F. J. Leij. and S. R. Yates. 1991. The RETC code for quantifying the hydraulic� functions of unsaturated soils. EPA/600/2-91/065, US Salinity laboratory, USDA-ARS, Riverside, CA. 85 pp.�

Vereecken, H., J. Maes., J. Feyen and P. Darius. 1989. Estimating the soil moisture retention characteristics from texture, bulk density and carbon content. Soil Sci. Soc. Am. J. 148(6): 389-403.��

Vereecken, H., J. Maes and J. Feyen. 1989. Estimating unsturated hydraulic conductivity from easily measured soil properties. Soil Sci. 149: 1-12.

Vielliefon, J., ��

��

��

��

��

��

��

�

Developments in Eco-hydrology

Huaien Li

��

Abstract Developments in eco-hydrology are reviewed, especially studies of impacts on aquatic ecosystems associated with watershed development or land use change. Important aspects include watershed determinants of ecosystem functioning, indicators of aquatic ecosystems as time varying systems, impacts of development and urbanization on ecosystems, and water resources and bio-diversity. Habitat modeling, studies of fish species, populations and communities are also included. At the same time, some important quantitative studies of eco-hydrology are presented, including different aspects of terrestrial and aquatic ecosystems. Key words: Eco-hydrology; developments; ecosystem; quantitative relations. Email: [email protected] 1 Introduction

In recent years, there have been more and more symposia and workshops held on topics of eco-hydrology, or links between hydrology and ecology. Published work includes Barendregt (1993), Chalise, et al. (1998), Edmonds, et al. (1998), Kovar, et al. (1998), Roesner, (1996) Tenhunen and Kabat, eds, (1999), US EPA, (1999), Baird and Wilby, (1999), Rodriguez-Iturbe, 2000 and Zalewski, et al. (1997). In 2000, two journals published their special issues on this topic, a special issue on Ecological Engineering (Vol.16, Issue 1, Oct. 2000; Zalewski, 2000) and special issue (Linking Hydrology and Ecology; Gurnell, et al. 2000) in Hydrological Processes (Vol.14, Issue 16-17, Nov.-Dec., 2000). From this wealth of publications, it is apparent that ecohydrology concepts are very topical. Now there is increasing confidence in mathematical models to suggest effects of changes, such as urbanization, on hydrology and stream water quality. Studies that focus on quantitative relationships between watershed development, hydrological regime, water quality, stream habitat, and aquatic ecosystem are just at their beginning. This paper summarizes the developments in ecohydrology, mainly concerned with impacts of development or land use change on aquatic ecosystems. 2 Eco-system functions and adverse

influences on bio-diversity 2.1 Freshwater eco-systems

It is well known that a large number of species worldwide depend either directly or indirectly on freshwater habitats. However, the ongoing degradation of freshwater ecosystems, due to human impact, not only disturbs habitats, but all

life connected with them. The main problem is that the speed of change is too rapid for species to be able to adapt to the different circumstances; and the omnipresent human impacts result in the creation of new ecological conditions and totally destroy some habitats.

Karr and Schlosser (1978) analyzed impacts of near-stream vegetation and channel morphology on water quality, including effects of vegetation on nutrient and sediment transport, effects of streamside vegetation on water temperature and nutrient dynamics, channel morphology and sediment loads. Then they discussed impacts of near-stream vegetation and channel morphology on stream biota, including effects of sediment, effects of temperature on biota, effects on stream energetics and effects of stream channelization. They also pointed out that many channel management activities degraded rather than improved water quality and thereby decreased the effectiveness of non-point control programs as well as stream biota.

Karr (1991) restated the definition of biological integrity and ecological health, then considered the IBI measure of biological integrity, including its development, application, and adaptability. Invertebrate data from rivers in the Tennessee Valley was used to evaluate the utility of 18 characteristics of invertebrate attributes to assess the biological condition of the streams. From this a comprehensive benthic invertebrate index of biotic integrity (B-IBI) was developed that reflects important aspects of stream biology and responds to effects of human society in detectable ways. The B-IBI has potential as an assessment tool for streams.

2.2 Vegetation cover and soil depth

Rivers are important determinants of natural streamside vegetation but there are more basic influences over the diversity of vegetation. In one study to define areas prone to desertification, 106 soil sites were selected in fields that had been either cultivated or remained fallow for 40-45 years. Measurements were intended to identify protection from land degradation after abandonment, such as fertility status, water storage capacity, and vegetation characteristics (Kosmas et al., 2000). The selected sites were located on a variety of parent materials such as volcanic lava, pyroclastics, ignimbrite, schist-marble, and shale. The data obtained indicated that physical characteristics of the parent materials and soil depth greatly influenced establishment of the natural vegetation. A critical minimum soil depth of 25-30 cm was measured. On more shallow soils, the associated natural perennial vegetation cover was rapidly reduced, under the prevailing climatic conditions. Percentage vegetation cover (Y) of Sarcopoterium sp. shrubs is related to soil depth (X, in cm) for soils formed on pyroclastics and schist-marble, respectively, as follows, (Kosmas et al., 2000): XYp ln6.392.86 ??? (n = 24, R = 0.91)

XYs ln9.450.58 ??? (n = 24, R = 0.93)

2.3 Eco-system changes

Over a three-year period, Horner et al. (1996) monitored watershed and riparian zone conditions, flow, physical habitat characteristics, water quality, benthic macroinvertebrates and fish in 31 reaches of 19 low-order streams, representing a gradient of urbanization. Measurements were also carried out in 19 palustrine wetlands over an eight-year period, when urbanization began or increased in about half of the watersheds while the remainder were essentially unchanged. Quite a number of relationships were established: between Benthic Index of Biotic Integrity (B-IBI) and Total Impervious Area in % (TIA); between zinc concentration and TIA; between ratio of Coho Salmon to Cutthroat and TIA; between amphibian species richness and TIA; etc. They also identified relationships linking: B-IBI and cumulative upstream riparian zone width; mean stream B-IBI and qualitative habitat index; and amphibian species richness and mean annual water level fluctuation.

Research in representative sets of Puget Sound lowland streams and wetlands has shown that a host of physical habitat and biological characteristics change with increasing urbanization, in a continuous rather than threshold fashion. While patterns of change differ among the attributes studied and some are more evident than others, physical and biological measures were generally seen to change most rapidly from levels of slight urbanization, as total impervious

area increased above 5-8%. With greater urbanization, rates of alteration of habitat and biology usually increased (Horner et al., 1996).

Water quality measures and metal sediment concentrations did not follow this pattern. They did not change much with increased urbanization until the level of impervious cover approached 50%. While some physical and biological changes are seen to start almost immediately in the urbanization process (Horner et al., 1996), chemical pollutants have not exhibited such a role in these early stages. As urbanization increases above the 60% impervious level and pollutant concentrations rise rapidly, it is likely that the role of water and sediment chemistry becomes more important from a biological perspective.

Hicks and Larson (1996) also presented a correlation between impervious surface and habitat assessment score. Relationships between community index, sensitive species index and impervious cover were presented (Maxted and Shaver, 1996). They analyzed the relationship between biological quality and habitat quality but found no clear trend. Schueler and Claytor (1996) examined relationships between impervious watershed cover and level of stream quality, between annual P load and impervious cover and between sub-catchment development criteria based on impervious cover. Benthic invertebrate communities at 15 sites in a single drainage basin were examined over a 2-year period to relate streamflow to community structure (Rabeni and Wallace, 1998).

2.4 Fish species, populations and communities

Most studies of aquatic ecosystems concentrate on fish species, populations or communities, for ecological and economic reasons (Gowan and Fausch, 1996; Jessup, 1998; Mankin, 2000; Milner et al., 1998; Rose, 2000; Wang et al., ��

��

watersheds, but neither agriculture (65-59%) nor urban (4.4-4.8%) land-uses changed significantly in those watersheds during the study period. From the 1970s to the 1990s mean number of fish species for test stream sites decreased 15%, fish density decreased 41%, and the index of biotic integrity (IBI) score dropped 32%. Fish community attributes of the 4 reference sites did not change significantly during the same period. For both the 1970s and 1990s test sites, numbers of fish species and IBI scores were positively correlated with % watershed coverage by agricultural land and negatively correlated with watershed urban land uses, as determined by % effectively-connected impervious surfaces. Numbers of fish species per site and IBI scores were highly variable below 10% impervious cover, but consistently low above 10%. Sites that had less than 10% impervious cover and fewer than 10 fish species in the 1970s experienced the greatest relative increase in impervious cover and decline in species number, over the study period. The findings are consistent with previous studies that found strong negative effects of urban land uses on stream ecosystems and a threshold of environmental damage at about 10% impervious cover, though Horner et al. (1996) came to the opposite conclusion. This study showed that while agricultural land uses often degrade fish stream communities, agricultural land impacts are generally less severe than those from urbanization on a per-unit-area basis.

2.5 Ecosystem changes due to urbanization

Urban development has heavy impacts on terrestrial and aquatic ecosystems (Blair and Launer, 1997; Finkenbine et al., 2000; Grimm et al., 1997; Jessup, 1998; Kahn, 2000; McDonnell et al. 1993; Ormerod, 1999; Rottenborn, 1999; Theobald et al., 1997). To measure some environmental consequences of sub-urbanization, Kahn (2000) analysed the increase in household driving, home fuel consumption, and land consumption brought about by population dispersion. Although suburban households drive 31 % more than their urban counterparts, local air quality has not been degraded in sprawling areas, thanks to emissions controls.

Theobald et al. (1997) presented a general approach to estimating cumulative effects of land use change on wildlife habitat using Summit County, CO, USA, as a case study. The approach was based on a functional relationship between effect on habitat and distance from development. Two factors were important in understanding how development potentially degrades habitat. These were alteration of habitat near buildings or roads and landscape fragmentation (Theobald et al., 1997). Grimm et al. (1997) focused on sensitivity to potential climate change of rivers, streams,

springs, wetlands, and lakes of the largely dryland region that encompasses the American Southwest and western Mexico. They were especially concerned with changes in hydrological patterns such as amount, timing and predictability of stream flow. Finkenbine et al. (2000) also examined the long-term impacts of urbanization on stream health. Blair and Launer (1997) examined the distribution and abundance of butterfly species across an urban gradient and concomitant changes in community structure. They estimated butterfly and skipper populations at 48 points within 6 sites near Palo Alto, California. Similarly, in 1995, birds were surveyed in riparian woodlands along a gradient of urbanization in the Santa Clara Valley, CA, to determine relationships between riparian bird communities and urbanization (Rottenborn, 1999). The richness and density of bird species decreased at a location as the number of bridges near that location increased and as the extent of native vegetation decreased. Possible ecological consequences for water resources arising from population growth and increased urbanization in the less-developed world have also been addressed (Ormerod, 1999). Jessup (1998) applied an integrating simulation model to relate dynamic trout population and habitat quality in an urbanizing watershed.

Habitat alteration, in the form of land-use development, is a leading cause of biodiversity loss in the U.S. and elsewhere (Crist et al., 2000). Although statutes in the U.S. may require consideration of biodiversity in local land-use planning and regulation, local governments lack the data, resources, and expertise to routinely consider biotic impacts that result from permitted land uses. Crist et al. (2000) hypothesized that decision support systems could aid solutions to this problem. They developed a pilot biodiversity expert systems tool to test the hypothesis and learn what additional scientific and technological advancements are required for broad implementation of such a system.

2.6 Habitat modeling

Watershed development changes the attributes of habitats first, and then the fauna is affected. So there are many studies focused on habitat modeling, especially for riverine habitats (Armitage and Cannan, 2000; Garner, 1997; Hardy, 1998; Kemp et al., 1999; Milner et al., 1998; Ortigosa et al., 2000; Stevens, 1996; Tickner et al. 2000). Discharge-habitat relationships were calculated using a modified version of the Physical Habitat Simulation (PHABSIM) computer package, and the results show that as discharge increased habitat availability decreased, primarily as a result of increased velocity and depth (Garner, 1997).

Kemp et al. (1999) examined the influence of channel morphology and hydraulics on occurrence and diversity of functional habitats (or meso-habitats) in semi-natural and physically degraded rivers. HABSCORE is a system of salmonid habitat measurement and evaluation based on empirical models of fish density against combinations of sites and catchment features. An outline is provided of the derivation, performance and applications of HANSCORE (Milner et al., 1998). Habitat evaluation methods based only on catchment features explain significant proportions of spatial variance, demonstrating their potential in catchment-scale evaluation (Milner et al., 1998).

A computer program, VVF, was developed to assess suitability of a territory as habitat for a species, and it integrated several types of Habitat Suitability models into a GIS (Ortigosa et al., 2000). The summer distribution of distinct meso-habitats for four 100-m sections along the length of a lowland river was studied over 3 years, together with their associated faunal assemblages (Armitage and Cannan, 2000). Multivariate analysis of the faunal/site matrix showed that the principal source of variation was the meso-habitat composition. Tickner et al. (2000) pointed out that heavy modification of the channel banks suggested significant habitat impoverishment. Stream width, bar height, channel bed variation and thalweg depth were habitat parameters analyzed at different cross sections in a reach representing rural, suburban and urban areas of the South Platte River in the Denver metropolitan area (Stevens, 1996).

Hardy (1998) presented an abbreviated review of habitat modeling approaches. Data collection, multi-dimensional hydraulic simulations, species and habitat modeling were considered important aspects of future of habitat modeling. In conclusion, Hardy (1998) pointed out that ��

��

��

��

�2.7 Integrated modeling approaches

��

�� 2

��

�2.8 Indicators of aquatic ecosystems as time

varying systems

A set of 9 measures has been used to yield two quality indicators, one for habitat and one for water quality (Bain and Loucks, 1999). The five habitat measures use a long-term series of hydrologic data to yield a single integrity value, so flow regime is assessed on the basis of one flow stability value. Thus, stream habitat integrity was modeled as a fixed property under a single land use and environmental setting, assuming that habitat quality is a product of long-term processes. Contrariwise, water quality often changes rapidly in response to short-term activities like construction, farming practices, and climatic events. For this dimension of ecosystem integrity, the assessment uses integrated suitability values based on time series data to compute water quality reliability, resilience, and vulnerability (Bain and Loucks, 1999). The final assessment of integrity requires an interpreted synthesis of summarized habitat and water quality values, rather than using a common approach of a single quantitative score. The primary advance with this analysis is treatment of ecosystems as time varying systems, where overall environmental quality is a product of the pattern of variation over time. A reasonable framework has been established, but determining the relationships between water quality suitability and habitat factors, as well as between the suitability and water quality factors, still needs to be studied and tested further.

2.9 Dutch polder landscape case study

In Netherlands, relationships between hydrology and vegetation in manmade aquatic ecosystems have been investigated at two levels (Barendregt, 1993). At the first level there are the direct habitat relationships and at the second level it is the ecology of landscape processes which change these habitats. At the habitat scale, extensive measurements were carried out in the summers of 1984-1990. Some 2064 observations of aquatic systems were collected in diverse polder areas. Sampling of each location included soil structure, drainage and dimensions of the aquatic system, surface water chemistry and the presence of plant species. The dominating variation in major ions and vegetation was caused by salinity, while calcium concentration, precipitation and nutrient concentrations arising from human pollution were secondary factors. The influence of chemical and hydrological variables on the response of plant Species (ICHORS) model was developed to link non-biotic characteristics and plant species. It is a multiple factor regression model based on a large dataset. This model has been used to assess the environmental impact of water management options. At the level of landscape processes, three case studies in wetland areas were provided. The changed hydrology

influences the conditions in the habitat that cause the changes in vegetation.

2.10 U.S. National Park case study

Studies of watershed ecosystems collect long-term baseline data on the ecosystem health of park and equivalent resources. Research and monitoring since 1980 at the watershed level by the U.S. Geological Survey and National Park Service has contributed to the accumulation of important baseline information on deposition, meteorology, hydrology, ecosystem functioning, and biology in selected parks and biosphere reserves. Important information on biological diversity and biogeochemical processes has also been obtained. Edmonds et al. (1998) presented results of the first 13 years of watershed research in Olympic National Park, Washington, an environment with little apparent anthropogenic disturbance. Using the small watershed approach, they examined vegetation patterns, biomass distribution, streamflow, soil and stream, and long-term trends in precipitation and chemistry.

This kind of research provides important data on ecosystem processes and interactions to help detect spatial and temporal changes in environmental conditions. These data collections allow the apportioning of cause-and-effect relationships for ecological changes in a watershed. They also serve to meet reference and early warning objectives linked with natural ecosystem change. So the scientific and public policy communities can employ watershed ecosystem information as one means of obtaining early indicators of potential effects of anthropogenic stress, along with an improved assessment of its magnitude. Acknowledgements

This paper was partially supported by the Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of MOE, P.R.C. References Aber J.D. 1993. Modification of nitrogen cycling

at the regional scale: the subtle effects of atmospheric deposition. In: Mc Donnell M.J. and Pickett S.T.A. (editors), Humans as components of ecosystems: the ecology of subtle human effects and populated areas. Springer-Verlag New Youk, Inc., 163-174.

Armitage P.D. and Cannan C.E. 2000. Annual changes in summer patterns of meso-habitat distribution and associated macroinvertebrate assemblages. Hydrological Processes 14: 3161-3179.

Bain M.B. and Loucks D.P. 1999. Linking hydrology and ecology in simulations for impact assessments. Proceedings of the 26th

Water Resources Planning and Management Conference, ASCE, Phoenix, Arizona.

Baird A.J. and R.L. Wilby, 1999. Eco-hydrology: Plants and water in terrestrial and aquatic environments. Routledge.

Baker P.D., Brookes J.D., Burch M.D., Maier H.R. and Ganf G.G. 2000. Advection, growth and nutrient status of phytoplankton populations in the lower River Murray, South Australia. Regulated Rivers: Research and Management 16: 327-344.

Barendregt A. 1993. Hydro-ecology of the Dutch Polder Landscape. Netherlands Geographical Studies 162, Utrecht.

Blair R.B. and A.E. Launer, 1997. Butterfly diversity and human land use: species assemblages along an urban gradient. Biological Conservation 80: 113-125.

Chalise S.R. 1998. Ecohydrology of High Mountain Areas. Proceedings of the International Conference on Ecohydrology of High Mountain Areas, Kathmandu, Nepal. March 1996.

Crist P.J., Kohley T.W. and Oakleaf J. 2000. Assessing land-use impacts on biodiversity using an expert systems tool. Landscape Ecology 15: 47-62.

Edmonds R.L., et al. 1998. Vegetation Patterns, Hydrology, and Water chemistry in Small Watersheds in the Hoh River Valley, Olympic National Park. Scientific Monograph NPSD/NRUSGS/NRSM-98/02, National Park Service.

Extence C.A., Balbi D.M. and Chadd R.P. 1999. River flow indexing using British benthic macroinvertebrates: a framework for setting hydrological objectives. Regulated Rivers: research and Management 15: 543-574.

Finkenbine J.K. 2000. Stream health after urbanization. Journal of the American Water Resources Association 36: 1149-1160.

Garner P. 1997. Seasonal variation in the habitat available for 0+Rutilus rutilus (L.) in a regulated river. Aquatic Conservation: Marine and Freshwater Ecosystem 7: 199-210.

Gowan C. and K.D. Fausch, 1996. Long-term demographic responses of trout populations to habitat manipulation in six Colorado streams. Ecological Applications 6: 931-946.

Grimm N.B., Chacon A., Dahm C.N., et al. 1997. Sensitivity of aquatic ecosystems to climatic and anthropogenic changes: the basin and range, American Southwest and Mexico. Hydrological Processes 11: 1023-1041.

Gurnell A.M., Hupp C.R. and Gregory S.V. 2000. Preface: Linking hydrology and ecology. Hydrological Processes 14: 2813-2815.

Hardy T.B. 1998. The future of habitat modeling and instream flow assessment techniques.

Regulated Rivers: Research and Management 14: 405-420.

Harris N.M., Gurnell A.M., Hannah D.M. and Petts G.E. 2000. Classification of river regimes: a context for hydroecology. Hydrological Processes 14: 2831-2848.

Hicks A.L. and Larson .S. 1996. The impact of urban stormwater runoff on freshwater wetlands and the role of aquatic invertebrate bioassessment. In: Roesner L.A.(ed), Effects of Watershed Development and Management on Aquatic Ecosystems. Proceedings of an Engineering Foundation Conference, ASCE, New York; 386-397.

Horner R.R., Booth D.B., Azous A. and May C.W. 1996. Watershed determinants of ecosystem functioning. In: Roesner L.A.(ed), Effects of Watershed Development and Management on Aquatic Ecosystems. Proceedings of an Engineering Foundation Conference, ASCE, New York; 251-274.

Jessup B.K. 1998. A strategy for simulation brown trout population dynamic and habitat quality in an urbanizing watershed. Ecological modeling 112: 151-167.

Kahn M.E. 2000. The environmental impact of suburbanization. Journal of Policy Analysis and Management 19(4): 569-586.

Karr J.R. 1991. Biological integrity: a long-neglected aspect of water resource management. Ecological Applications 1: 66-84.

Karr J.R. and Schlosser I.J. 1978. Water resources and the land-water interface. Science 201 (Jul.): 220-234.

Kemp J.L., Harper D.M. and Crosa G.A. 1999. �� 9��

�� 40��

��

�� 133��

��

��

urban effects. In: Mc Donnell M.J. and Pickett S.T.A. (editors), Humans as components of ecosystems: the ecology of subtle human effects and populated areas. Springer-Verlag New York, Inc., 175-189.

Milner N.J., Wyatt R.J. and Broad K. 1998. HABSCORE�� 8��

�� 9��

�� 15��

��

�� 14��

��

��

�� 10��

�� 88��

��

��

��

�� 39��

�� 10��

��

�� 36��

��

��? �� 16��

�

Water reforms -need of the hour

Kiran Soni Gupta

Command Area Development & Colonisation Bikaner, India. Abstract: Water being the mean stay of human existence has been harvest incrementally in the past few years. However looking into the needs and requirement of water of the present and future, it is now dawning that with the limited resources of water needs to be rationed and budgetted. As the competition for water increases to achieve the greatest community benefit there is a need to have sensible sharing arrangements and to encourage all users to employee water for its highest value use. The paper highlights that we need to address issues of enhancing environmental health, secure clear water rights ensure flexibility and proper trading of water use, long term planning for water management with the highest water efficiency and reclying. There is a need to evolve area specific and location specific water management plans with clear strategies for use of surface and ground water. In fact as a measure for optimum utilization of water and best conservation policies the paper proposes water legislation and creation of water markets. These water markets should operate in consistent with the river flow and water quality objectives and other ecological considerations. Key words: Water management plan; water legislation ; creation of water markets. E-mail: [email protected]

Water has played a vital role in supporting communities and developing our economy. The building of the major rural dams and the productive use of our available water resources promoted economic growth. An assured supply of good quality water fostered regional development. New industries emerged and communities expanded. Landholders, industries, transport, towns and cities have benefited from using water, and water use has continued to expand to the present time. Food and fiber production, mining, manufacturing, electricity and service industries all depend on water in one way or another. Water is essential to our daily lives ��

��

��

��

��

��

aur Sab Ko Padao". Even otherwise for a desert State with arid to semi arid condition water is vital. Drought prone areas should be made less vulnerable to drought associated problems through soil moisture retention, conservation measures- water harvesting practices, the minimization to evaporation losses, development of ground water potential including recharging & transfer of surface water from surplus areas to feasible area.

Water has always played a very critical role in the economy of Sriganganer, which is the granary of Rajasthan it is presently catered to by the Gang canal, Bhakra Canal & Indira Gandhi Canal. The sharing of water with bordering states of Punjab, Haryana and the issues of erratic flows & management of water, which are often raised in the regulation committee have always left administrative environment surcharged with questions that have entailed law & order problems. Indira Gandhi Canal project is one of the largest efforts in the world at introducing water into desert environment leading not only to issues of desert irrigation but also occupational & population shift in the area alongwith the higher agricultural production.. Since drinking water is a problem in desert areas, the Canal waters are often used for drinking purposes. Introduction of large scale irrigation in this arid region has brought in the positive environmental changes i.e. improvement of micro-climate, changes in flocel elements, micro relief variation, revolution in economy & urbanization along with the adverse effects like soil salinity, water logging & marshy land. Due to excessive seepage & mismanagement of water resources, water level is rising continuously at an alarming rate resulting in rejuvenation of the palaeco fluvial setup. With these adverse effects, intensive agricultural lands are again transforming into poor agricultural areas and ultimately to saline deserts. The ill effects are clearly seen in the depressional area of Baropal Suratgarh sector. The appearance of water logging conditions began from Baropal areas after the commissioning of Bhakra Canal System due to its topographic setup and extended all along the Drishadwats had after the introduction of IGNP Canal (1963) and impounding of flood waters in natural depressions(1968).

While we have certainly benefited from the productive use of water, we have reached a stage that if we continue to use more water, advancing degradation of the environment will seriously reduce our capacity to produce. As competition for water increases, to achieve the greatest community benefit there is a need to have sensible sharing arrangements& encourage users to employ water for its highest value use. We now have to appreciate

that our water resources are limited and that human activity has an impact on the environment. Over time, some land & water use activities have led to problems such as:

? land degradation; ? increasing salinity; ? blooms of toxic algae in our waterways; ? increasing conflict over access to water; and

water supply restrictions. We are reaching the limits of our available water

resources, with the result that our natural ecosystems are being affected. Existing investment in food & fiber production, and other industries, is threatened by growth in water use. We cannot simply blame what happened in the past, nor ’turn things back to the way they were’. We must recognise that we have economic & social systems that will need to continue depending on a robust, functioning environment. There is increasing community concern about providing a better environment and sustainable industries for future generations. Community-based programs such as River care, Land care, Water watch-and others- are examples of programs repairing environmental damage, and we have begun the process of managing some river flows to protect river health. We have learned from history and must use the lessons to create a better future. Today’s water users need to address issues of : ? Maintaining and enhancing environmental health: ? Lack of clear and secure water rights; ? Limits on access to water; ? Lack of flexibility for water use and trading; ? Long-term planning for water management; ? Improving water use efficiency, and water re-use;

and Community involvement.

These issues must be addressed now if there is to be secure future for tomorrow’s generations. There will be many challenges for us all on the road to achieving this. The Government’s water policy is a major step towards achieving that goal. We tend to take for granted that we share water with the natural ecosystems of our planet ��

environments ��

��

��

��

��

��

��

��

significant, and in some areas of the country. The effects of degradation are beginning to translate into economic & environmental losses.

Policy implementation tools should include: the development of local Groundwater Management Plans, where appropriate; the development of guidelines for industries; education and community awareness activities; more effective licensing measures; better integration of groundwater management with land use planning activities, and; the establishment and refinement of transfer markets where appropriate.

One of the major vehicles for policy implem��

��

��

��

Estimation of soil water retention curve with the derived point and parametric Pedotransfer functions

M.Homaee and Sh. Ghorbani Dashtaki

Department of Soil Science, University of Tarbiat Modarres, Tehran 14155-4838, Iran. Abstract Some point and parametric pedotransfer functions (PTFs) were developed to predict the water status in the root zone. Also, the possibility of using geometric mean and geometric standard deviation of particle diameters instead of soil particle size distribution was investigated. Consequently, 34 soil samples were collected randomly from a cropped soils. The particle-size distributions and bulk densities of the soil samples were determined with the hydrometry and core method, respectively. The retention curve was obtained using pressure plate apparatus. The parameters of van Genuchten and Mualem �� i��ii�� ii��? ��?s �� n� �� l �� Key words:��

�E-mail:��

1 Introduction ��

��

Jarvis, 1999; Minasny and McBratney, 2000; Wosten, 1997; Vereecken et al., 1989). Some reviews of pedotransfer functions are given by Tietje and Tapkenhinrich (1993), Wosten (1997),Cornelis et al. (2001) and Wosten et al. (2001). One more systematic classification method, classifies the PTFs into the following (McBratney et al., 2002): Mechanistic-empirical approach This approach converts a physical model to the predicted properties. For example, Arya and Paris (1981) translated particle-size distribution data into a water retention curve, using the fundamental capillary equation. Empirical approach This method correlates the basic soil properties to the more difficult-to-measure soil properties, using multiple linear regression (e.g. Wosten et al., 1999) or artificial neural networks (e.g. Schaap et al., 1998). PTFs can also be classified as single point regressions, parametric and physico-empirical functions. Single point PTFs predict a soil property at a special point of the water retention curve. The parametric PTFs aim to predict the parameters of a model, e.g. van Genuchten model (van Genuchten, 1980), as independent variables (y) and readily/easily obtainable soil properties as dependent variables (x). �� )h1(S �??

??

? ????? � � ��

�� Se� �� ? r� �� ?s� �� ? ��-1��n ��m�� ])S1(1[SKK ??? � � ��K0��-1��l��

2 Materials and methods �� Torriorthents �� Haplocambids �� ? , n, ?r �� ?s� �� k0�� l� �� dg��? g� �� dg = exp a ��? g = exp b� � � � ��

??��Mlnf01.0a � � � ��aMlnf01.0b ??? � � � ��

��

?? 1?�� KloglogK ?��

l1logl ??�� dd ?�� ? *�� *

0K ��l*�� *gd ��? ��

K0��l ��dg�� dg� �� ? g� �� ? , n, ? r,?s��k0��l��

��

Table 1. Minimun and maximum values of sand, silt, clay and bulk density SiCL N=10

Min-Max

CL N=3

Min-Max

SiL N=3

Min-Max

L N=17

Min-Max

SL N=1

Min-Max

All N=34

Min-Max Variable

11.0-20.0 26.0-43.0 20.5-27.0 24.5-56.0 54.0 11.0-56.0 Sand%

41.0-53.5 28.0-45.0 50.0-53.5 24.0-53.5 32.0 24.0-53.5 Silt%

32.0-40.0 29.0-29.0 22.0-26.0 16.0-26 14.0 14.0-40.0 Clay%

1.30-1.55 1.41-1.45 1.20-1.46 1.35-1.61 1.44 1.20-1.61 Bulk�Dnsity

(g.cm��) silt ratio C/Si was used instead of their absolute values when clay and silt were simultaneously incorporated in the model. The stepwise procedure was used to derive the regression models. To develop point and parametric PTFs, the independent variables were classified into two groups. The sand, silt and clay percents and bulk densities were used as independent variables of group (a). The group (b) was consisted of dg, ? g and bulk densy. Thus, four types of PTFs were obtained: Type 1: The point PTFs based on group (a) variables. Type 2: The point PTFs based on group (b) variables. Type 3: The parametric PTFs based on group (a) variables. Type 4: The parametric PTFs based on group (b) variables. 3 Results and discussion The soil samples were classified into five textural classes i.e Sandy Loam (SL), Loam (L), Silty Loam (SiL), Clay Loam (CL) and Silty Clay Loam (SiCL) textures. The value ranges of sand, silt, clay and bulk density (BD) of these textures are given in Table 1. The van Genuchten parameters of these textures are given in Table 2, indicating that ?r and ?s varied from 0.0028 to 0.2016 cm3.cm-3 and 0.3939 to 0.5481 cm3.cm-3, respectively. The variation of n and ? is 1.2473 to 1.8482 (-) and 0.0032 to 0.0608 cm-1, respectively. The parameters k0 and l varied from 0.299 to 41.1434 and �� k0��l��k0��l ��Drivation of PTFs ��

��

Table 2. The calculated mean, minimum and maximum of the van Genuchten parameters Parameter Mean Minimum Maximum

?�(cm�.cm��) 0.1224 0.3939 0.5481

?�(cm�.cm��) 0.4466 0.0028 0.2016

? (1.cm��) 0.0122 0.0032 0.0608

n(-) 1.5071 1.2473 1.8482

�� R

2adj��

�� dg�� ? g �� dg ��? g ��

Rsq=0.688

4035302520

40

35

30

25

20

Rsq=0.768

2015105

20

15

10

5

Table 3. The derived type 1 PTFs

Parameter PTFs R��??��35.9-0.423*S+12.2*Bd 81.1

??��15.6-0.323*S+16.9*Bd 66.8

??��11.35-0.287*S+15.09*Bd 68.9

??�� 11.9-0.219*S+8.39*Bd+ 4.25 * C/Si

76.3

??��9.291+0.343*C 66.2

??��6.627+0.315*C 76.0

Bd=Bulk Density(g.cm �); C=Clay percent; S=Sand percent; C/Si= Clay to Silt ratio.

Table 4. The derived type 2 PTFs Parameter PTFs R��

??��54.982-74.377*d�� 80.3

??��23.9-61.6*d�� +12.5*Bd 71.3

??��18.7-55.5*d�� +11.3*Bd 75.6

??��17.645-45.918*d�� +7.794*Bd 80.7

??��15.864-46.987*d�� +3.278*s�� 73.5

??��12.647-41.894*d�� +2.944*s�� 79.8

Type 3 are the derived parametric PTFs with group (a) variables (Table 5). The results given in Table 5 indicate that the bulk density is the main dominant predicting variable, predict ?s covering 94.6 percent of the total variability. Also, the clay content appeared to be the most important input to predict ?r parameter. Since ?r has an important effect on the shape of the retention curve at high pressure heads, it was expected that this parameter be depend upon to the soil specific surface and consequently on clay percent. Type 4 PTFs estimate ? , n, ? r, ?s, k0 and l parameters from the given dg, ? g and bulk density. A comparison between the adjusted coefficients of determination of this PTFs type with type 3 indicated that the predicted ?s, ?r and ? with both types is almost identical. However, type 4 provided a better prediction for n and l than type 3. This can be related to the fact that dg and ? g regard the effect of all soil particles simultaneously without providing any multicolinearity.

Table 5. The derived type 3 PTFs

Parameter PTFs R��? r

0.0192+0.00375*C� � 32.1

?s 0.933-0.000707*S-0.311*Bd� � 94.6

? * -531-4.67*S+550*Bd 69.0

N 1.668-0.00522*S 13.2

l* 0.291-1.174*C/Si� � 16.1

K0* 0.199-0.006*S� � 12.9

(a) r2=0.688

measured ? (%) (b) r2=0.768

measured ? (%)

Fig. 1. The measured and predicted water contents, using type 1 point PTFs at Field Capacity (a) and Permanent Wilting Point (b)

pred

icte

d ?

(%)

pred

icte

d ?

(%)

� �

� �

�� Rsq=0.81

20 15 10 5

20

15

10

5

�� Rsq=0.73

35 25 15

35

25

15

Table 6. The derived type 4 PTFs Parameter PTFs R��

? r 0.197-0.392*d�� 30.8

?s 0.954-0.324*Bd-0.124* d�� 94.1

? * -448-684* d�� +568*Bd-9.18 *?�� 68.2

N 8.539-3.673 *?�� +0.474 *?�� 23.2

l* -25.2-1.92*?�+13.7*?��+1.92*d�� 27.2

K0* -1.162+3 *d�� 14.5

(c) r2=0.73

measured ? (%) (d) r2=0.81

measured ? (%) Fig. 2. The measured and predicted water contents, using type 2 point PTFs at Field Capacity (c) and Permanent Wilting Point (d) 4 Conclusion

Information of the soil hydraulic properties is often lacking and the direct measurements of this characteristics are time-consuming and costly. It is therefore necessary to develop indirect methods such as PTFs to estimate these properties. Since a

given pedotransfer function should not be extrapolated beyond the geomorphic region or soil type from which it was developed, some point and parametric PTFs were developed, using dg and ? g. The results indicated that the geometric mean and standard deviation of the soil particle diameter can better explain the variations of hydraulic properties than the traditional particle-size distribution. Because the influence of all soil particle-sizes are simultaneously presented by dg and ? g.

This reflects the fact that the particle-size distributions and the pore-size distributions are approximately congruent. The soil particles with large dg produce larger interparticle voids than smaller particles and vice versa. Furthermore, the standard deviation of the soil particle diameter determine the homogeneity of the soil particles. The soil samples with small ? g produce voids of homogeneous diameter and vice versa. Consequently, the dg can be regarded as a quantitative index for describing the geometric mean of the pore sizes and the ? g quantifies the ��References ��

��

��

�� nd��

��

��

��

��

pred

icte

d ?

(%)

pred

icte

d ?

(%)

Klute, A. 1986. Ed. Methods of soil analysis, Part 1: Physical and mineralogical methods, Second Edition. Monogr. 9. ASA. and SSSA, Madison,WI. 1188pp.

Kosugi, K. 1999. General model for for unsaturated hydraulic conductivity for soils with lognormal pore-size distribution. Soil Sci. Soc. Am. J. 63: 270-277.

Mayer, T. and N.J. Jarvis. 1999. Pedotransfer functions to estimate soil water retention parameters for modified Brooks-Corey type model. Geoderma. 91: 1-9.

McBratney, A.B., B. Minasny, S.R. Cattle and R. Willem Vervoort. 2002. From pedotransfer functions to soil inference systems. Geoderma, 109: 41��

��

��

��

��

��

��

��

��

��

��

��

�� functions of unsaturated soils. EPA/600/2-91/065, US Salinity laboratory, USDA-ARS, Riverside, CA. 85 pp.

Vereecken, H., J. Maes., J. Feyen and P. Darius. 1989. Estimating the soil moisture retention characteristics from texture, bulk density and carbon content. Soil Sci. Soc. Am. J. 148(6): 389-403.

Wosten, J.H.M. 1997. Pedotransfer functions to evaluation soil quality. In: Gregorich, E.G. and M.R. Carter (Eds). 1997. Soil quality for crop production and ecosystem health. Soil Sci. 25.

Wosten, J.H.M., P.A. Finke and M.J.W. Janes. 1995. Comparison of class and Continuous pedotransfer functions to generate soil hydraulic characteristics. Geoderma. 66: 227-237.

Wosten, J.H.M., A. Lilly, A. Nemes and C. Le Bas. 1999. Development and use of a database of hydraulic properties of European soils. Geoderma, 90: 169-185.

Wosten, J.H.M., Ya.A. Pachepsky and W.J. Rawls. 2001. Pedotransfer functions: bridging the gap between available basic soil data and missing soil hydraulic characteristics. J. Hydrol. 251:123-150.

Social values of water use and their economic impact in Jakham irrigation project of Rajasthan - India

A. S. Solanki

Department of Soil and Water Engineering, College of Technology and Engineering, Maharana Pratap University of Agriculture and Technology, Udaipur (Raj.), India. Abstract A sample of 50 farmers was used from two different communities to assess their social values and the economic impact of related irrigation development. The studies were conducted in the Jakham irrigation project where more than 79.2% of the farmers are tribal people The cropping patterns showed that the first community were more interested in taking more remunerative crops than the second. The first community had introduced several new crops such as rice and mustard in their cropping pattern. The difference in cropping intensity was 96.3% between two communities. The second community was more interested in providing services and hiring out labour. Values of farm and family assets were also found to be greater in first community. The difference between average household income was found to be Rs.19266 for the two communities. The first community was socially more strong, in resource base and also enriched in socio-economic conditions. Whereas, the second community was more in the grip of social evils, being poor in their resource base. The first community even did not like to marry their wards into the second community. The first community used water rationally, recognizing that water has social value for them. For some water is a God. This suggests that social values are an impotent tool in improving efficiencies in irrigation projects. So in the Indian context, misuse of water by farmers in command areas is due more to social rather than technical factors. Key words: Social values, gainful employment, irrigation. E-mail: [email protected] 1 Introduction 1.1 General

Water is an essential natural resource for the survival of human beings. As a promoter of new technologies, irrigation not only improves crop yield but also helps in improving the socio-economic conditions of farmers. In India, irrigation water becomes more important because of its scarcity. To overcome the problem, the Government of India constructed several irrigation projects after independence. While irrigation potential has increased several-fold, the question of efficient use of irrigation water remains unresolved. The issue is particularly important when, irrigation projects are constructed in the vicinity of areas dominated by tribal people.

1.2 Tribal people of Southern Rajasthan

The southern Rajasthan State of India is mainly dominated by tribal people, especially Bhills, Garasia, Meena and Lumbi. In many areas, they represent 82% of the population. In spite of this, they are socially backward and generally work in the fields of powerful non-tribal farmers. The Government of Rajasthan has spent several millions Rupees in construction of irrigation projects to improve the socio-economic conditions

of tribal people but they still remain under-developed.

With irrigation being a lifeline for tribal farmers, so some tribal communities worship water. A peculiar characteristic was observed in the Jakham irrigation project. A particular community of tribal people worshiped water and treated it as a "God". Social values were important for the first community and they understand that water is a God for them, leading to socio-economic development. The name of water God was �� 1.3 Research project

��

2 Materials and methods The study was located within the Jakham

irrigation project. One parallel minor out of 14 minors on Left Main canal was selected for in-depth study. A samples of 50 farmers was chosen from Bhil and Garasia tribal community, who worship water, and 50 farmers were selected from a second community who have no such beliefs. A special questionnaire was developed and data was collected by personal interview. A detailed analysis was done to assess the impact of community social values on changes in their socio-economic conditions. 3 Results 3.1 Change in cropping pattern and cropping

intensity Changes in cropping pattern and intensity

(Table 1), in farm and family assets (Table 2) and in total household income (Table 3) were identified. Table 1. Changes in cropping pattern and cropping

intensity (% gross cropped area)

S. No.

Crops First Community

Second Community

(A) Cereals 1 Paddy 5.8 - 2 Jawar 2.1 3.1 3 Maize 13.1 33.2 4 Wheat 40.2 13.1 5 Barley 4.1 2.0 Sub total - A 65.3 51.5

(B) Pulses 1 Kharif pulses 6.2 1.1 2 Gram 4.1 0.2 Sub total - B 10.3 1.2

(C) Oil seeds 1 Ground nut 5.1 2.0 2 Sesame 2.1 0.2 3 Rape seed and

mustard 13.1 3.2

Sub total - C 20.4 5.5 (D) Other crops 4.0 41.8

Gross crop area 100 100 Cropping

intensity 232.4 136.1

The above table reveals that wheat is the most

important crop for the first community followed by maize. Maize is a staple and an important khanif crop of the area so every farmer grows this. Paddy was introduced to the area and occupies 5.8% but no area was found under this crop for the second community. Maize was also the most important crop for the second community. Growing of pulses was also reported, with 10.3% for first community, compared with only 1.3% in the second community. Growing of rapeseed and mustard was also found to be quite prevalent in first community (13.1%). Greater diversity of

cropping was evident relative to the second community.

The data also revealed that the first community chose more remunerative crops whereas, the other community showed little interested in crop farming. The latter depend more on other sources of income. Cropping intensity was 232.4% in the case of first community.

3.2 Change in farm and family assets

Table-2 reveals that the first community was in a better condition in the terms of possession of farm and family assets. Both farm and family assets were found greater for the first community, with Rs.42134 of farm assets and Rs.21026 of family assets.

Table 2. Change in farm and family assets (per ha) S.

No. Assets 1st community 2nd community

1 Farm assets

(Rs.) 42134 29282

2 Family

assets (Rs.) 21026 7282

3 Share of

farm assets (%)

66.7 80.1

4 Share of family

assets (%) 32.3 19.9

3.3 Change in total household income

The above table shows that crop farming income was higher for the first community, with Rs.30,229 per household compared with only Rs.10212 in the second community. The total household income was reported to be Rs.49,583 and Rs.30,317 for first and second communities respectively. The dairy income was also reported to be high in the case of first community, compared to the second. Wages, salaries and income from other sources were reportedly high for the second community. The data shows that the first community was more interested in crop farming while the second was more dependent on activities other than farm activities for their livelihood.

Table 3. Changes in total household income (Rs.) S.

No. Particulars First

Community Second

Community 1 Crop farming 30229 10212 2 Dairy farming 15126 11229

3 Hiring out machines

1086 208

4 Other farm income

1422 406

5 Wages 212 2021 6 Salary 1082 4212

7 Other sources (trade, business)

426 2028

8 Total income 49583 30317

Acknowledgements

The author is grateful to the irrigation office, Jakham irrigation project, Udaipur and the staff of the Soil and Water Engineering Department, College of Technology and Engineering, Udaipur, India for their valuable guidance timely help. References Kumar, Asun, 2002.Participatory irrigation

management in Hariyana, Indian Water Resource Society, Journal, Jan. pp 9-17

Punia, SS et al.. 1998. Farmers perception of the problem and acceptance of SSD. In Proceeding of National Seminar on Socio-economic Aspects of Sub Surface Drainage and Water Management, pp22.

Statistics Abstract of Rajasthan, 2000. Directorate of Economics and Statistics, Govt. of Rajasthan.

.

1

Sustainable development and reasonable allocation of water resources

Zhanyu Zhang and Baoping Feng

Hohai University, Nanjing, 210098, China. Abstract A regional water allocation plan is proposed which is based on multi-objective decision- making. To minimize water shortages, all sources of precipitation, surface water, groundwater and imported water are considered as a whole, whilst the demands of industry, agriculture, human life and ecosystems are treated separately and assigned differing weightings. This is in keeping with both domestic and international views of integrated water resource management. Key words: Water resources; sustainable development; reasonable allocation. E-mail: [email protected] 1 Introduction

According to the Integrated Evaluation Report of the World��

�� 3�� 3� �� 3��

��

��

��2 Theory of sustainable water resource

use ��

��

��

��

2

development of water resources should not affect availability of water in other regions.

According to the theory of sustainable According to the theory of sustainable the core aims of sustainable water resource use are to develop and use water resources, to protect the environment, to develop the economy, and to satisfy the water demands of both the present and future generations. Sustainable development of both water resources and society influence each other. On the one hand, society will not develop steadily without sustainable development of water resources; on the other hand, development of society will impact on water resources, and even spoil water resources without the support of a water management system. 3 Reasonable allocation of water

resources in a region It is scarcity, lack of a substitute and uneven

space-time distributions that control natural allocation of water resources. So every kind of measure for water conservancy must be adopted to reallocate water. How to deal with the relationship between water resources and social-economic development and environment to reach the maximum economic benefit? Social and environmental benefits identify the basis for carrying out water resource allocation. Considering water supply, through mediating the contradiction of users the situation of natural water distribution is changed; while considering demand, through regulating the industry and demand structures so a saving-water system is founded, based on the national economy.

Reasonable allocation of water resources is that with the general principle that every kind of water is distributed to every user through water conservancy and non-structural measures (Li, 2000). On the one hand, precipitation, surface water, groundwater, imported water and recycled sewage are planned as a whole. On the other hand, every type of user is treated differently and fulfillment of the demands of important users is ensured. According to the fundamental principle of sustainable development, water is allocated to several subsections and users, and the allocation scenarios are compared for some typical year, which can assist decision-making.

3.1Objective function

Water allocation is a multi-objective decision problem guided by sustainable development concepts. The indicators are as follows: (a) compatible development among several subsections, (b) equal allocation of water among several subsections and users, (c) compatible development of economy, environment and society and (d) compatible development in the near and distant future. The degree of water resource

shortage (S) is defined as the difference between water demand (D) and water supply (Q) divided by water demand (D). The objective function is calculated by:

???

???

?

???

???

?

????

?

?

????

?

? ?????

???

??????

??

?

??

??

?

h

kj

ikj

T

ikj

kj

N

jk

M

k

kjkj

N

jk

M

k

kk

M

k

D

QD

s

SZ

��1

11

11

1

min

min

min

??

??

?

(1) ? ?WiNjMk k ,,2,1;,,2,1;,,2,1 ??? ???

where Z is the extent of integrated water resources shortage, k the subsection number, M the subsection total, j the user number, Nk the user total of the kth subsection, i the water resource number, T the total water resource, �? the weighing of the

kth subsection, ��? the weighing of the jth user in

the kth subsection, Dkj the water demand of the jth user in the kth subsection, Qikj the water supply of the jth user in the kth subsection from the ith water resource, Sk the integrated shortage degree of water resources of the kth subsection, skj the shortage degree of the jth user and h the power, which implies the allocation equity. 3.2 Constraints

(1) The constraint of supply capability of water sources ��WQ�

???�� (2)

where Wi is the maximum supply of the ith water resource.

(2) The constraint of the supply capability of water resources in every subsection

ikikj

N

jWQ�

???1

(3)

where Wik is the maximum supply of the ith water source for the kth subsection.

(3) The constraints of water demand of every subsection of the kth subsection

kjikj

T

ikj HQL ???

?1 (4)

where Hkj and Lkj are the maximum and the minimum water demand of the jth user of the kth subsection respectively.

(4) The constraints of ecosystem water demand

EikE

T

iWQ ??

?1 (5)

where ��Q is the ecosystem demand of the ith

water resource and WE the minimum water demand to maintain the environment. For a water basin, the ecosystem water demand includes water demand

3

of rivers and that of the exterior of rivers (Zheng et al, 2000). To calculate the water demand of the exterior of rivers, vegetation should first be divided according to its natural circumstances, and then the vegetative water demand is calculated according to the data of annual precipitation, air temperature and heat balance. The water demand of rivers includes the use of water for such purposes as the generation of power, shipping, sediment ejection, flushing sediment, protecting the environment and ��

��0?ikjQ ��

3.3 Solution

��

��

��

��k��

h

kj

ikj

T

ikj

kj

N

jk D

QDZ�

????

?

?

????

?

? ???? ?

?

1

1min ? ��

��k��k��

????

?

????

?

?

?

??

???

??��0

..��

Q

WQ

HQL

WQ

ts

� (8)

(2) The overall model of water allocation The overall model, which is to solve the water allocation among the subsections, is

kk

M

kSZ ?

1min

??? (9)

s.t.

iikj

N

j

M

kWQ�

????? 11

(10)

Figure 1. Decomposition and harmonization of water resources allocation

Whole harmony system

Agriculture

demand

Domestic

Environmental

demand

Xingfu

subsection

Agriculture

demand

Domestic

Environmental

demand

Wangjin

subsection Industry

Agriculture

demand

Domestic

Environmental

demand

Huandong

subsection

Agriculture

demand

Domestic

Environmental

demand

Huannan

subsection

Agriculture

demand

Domestic

Environmental

demand

Tanghe subsection

4

4 Example applications The study was conducted at the Zhangnan

Irrigation Area, Henan Province, People’s Republic of China. The area, located in the most northern part of Henan Province, includes five subsections, namely Xingfu, Wanji, Huandong, Huannan and Tanghe. The water needs include domestic, agriculture, ecotope and industry (Figure 1). The water sources include groundwater, imported water, local surface runoff, and industrial drainage. Imported water includes the Yuecheng, Zhangwu, and Tanghe Reservoirs. The industrial drainage is the cooling water from the electric power plant and steelworks.

The allocation rules of water sources are as follows:

(a) Local surface runoff and industrial drainage is distributed first. The industrial drainage can basically be used directly without treatment. The local water sources can be distributed to agricultural users.

(b) Secondly, imported water is distributed, and the distance of supply channels should be a minimum.

(c) Finally, the groundwater is distributed in every subsection. Because of previous over-consumption of the groundwater, it should be used as little as possible. At the same time, the groundwater in different subsections should be kept in balance.

According to the above allocation rules, the low and the high allocation scenarios under different years (2005, 2015, 2030) and under different guarantee rates (50％, 75％, 95％) are obtained. Table 1 gives the allocation scenarios under P = 75% in the year of 2015.

5 Conclusions

The water resource crisis is a global problem that is growing in seriousness. The sustainable development of water resources is a new pattern of water resource use and is an important component of sustainable development.

It is important to approach sustainable development of water resources on the basis of natural distribution situation of water. Water is reallocated by all kinds of water conservancy and non-structural measures. A proper relationship between socio-economic development and the environment is achieved by felicitous use of water resources, and water achieves its maximum benefits.

Water allocation within a region is a multi

objective problem. In order to minimize the integrated water shortage degree, all the water sources are considered as a whole; different users should be treated differently by weighing their importance. References Chen Ning, Zhan Yanjun. 1998. Concept,

connotations and index system of water resources sustainable development. Areal Research and Development 17(4), 37-39.

Fang Ziyun. 1998. The status quo and prospect about water resources sustainable development. Wall Bulletin of Water Conservancy and Water Power 19(6), 1-6.

ICWE, 1992. The Dublin Statement and Report of the Conference, International Conference on Water and the Environment Development Issues for the 21st Century. Dublin.

Liu Changming，Fu Guobin. 2000. Water world today. Guangzhou: Jinan Univ. Press, Beijing :Beijing Univ. Press,. pp168-194.

Li Lingyue, Gan Hong. 2000. Remark on the Relationship between Water Resources Rational Allocation, Carrying Capacity and Sustainable Development. Advances in Water Resources 11(3), 307-313.

Mou Haisheng. 1995. Zero increase mode for water resources sustainable development in China. Geographical Research.14(1), 80-84.

Rijsberman M.A., van de Ven F.H.M. 2000. Different approaches to assessment of design and management of sustainable urban water systems. Environmental Impact Assessment Review 20, 333-345.

Tang Huajun, Luo Qiyou, Bi Yuyun, et al. 1990. Sustainable use strategy of China agricultural water and land resources. China Agricultural Resources and Regional Planning 20(1), 5-10.

Xie Junan, Zhu Jun. 1998. Global water resources crisis and sustainable development. Journal of Shijiazhuang Economic College 21(2), 125-135.

Zhang Guoxiang. 2000. Preliminary Study of a Mode for Sustainable Development of the Qingjiang River Valley Water Resources. International Journal Hydroelectric Energy 18(3), 57-59.

Zheng Dongyan, Xia Jun, Huang Youbo. 2002. Discussion on Research of Ecological Water Demand. Journal of Hydroelectric Energy Science 20(3), 3-6.

5

Tabl

e 1

Allo

cati

on s

cena

rios

of

wat

er r

esou

rces

wit

h P

=75%

in t

he y

ear

of 2

030

(un

it:

Mm

3 )

Scen

ario

Su

bsec

tion

Use

r D

eman

d vo

lum

e Su

pplie

d by

Y

uech

eng

Res

ervo

ir

Supp

lied

by

Zha

ngw

u R

eser

voir

Su

pplie

d by

Ta

nghe

Res

ervo

ir

Supp

lied

by

grou

ndw

ater

Su

pply

of

runo

ff

Use

of

indu

stri

al

was

tew

ater

Wat

er

defi

cit

Dom

estic

11

0

0

11

0

Agr

icul

ture

71

19

0

45

2

5

Eco

tope

3

0 0

0

3

0

Xin

gfu

Irri

gatio

n A

rea

Tota

l 85

19

0

56

6

5

Dom

estic

16

0

0

16

0

Agr

icul

ture

91

0

0

0 5

86

0

Indu

stry

24

9 8

143

86

12

Eco

tope

14

0

0

0 14

1

Wan

gjin

Ir

riga

tion

Are

a

Tota

l 37

0 8

143

10

1 19

85

13

Dom

estic

6

0 0

6

0

Agr

icul

ture

63

11

0

38

2

12

Eco

tope

3

0 0

0

2

0

Hua

ndon

g Ir

igat

ion

Are

a To

tal

72

11

0

44

5

12

Dom

estic

4

0 0

4

0

Agr

icul

ture

38

0

0

37

1

0

Eco

tope

2

0 0

0

2

0

Hua

nnan

Ir

igat

ion

Are

a To

tal

43

0 0

40

3

0

Dom

estic

8

0 0

8 0

0

Agr

icul

ture

26

0

0 25

0

1

0

Eco

tope

1

0 0

0 0

1

0

Low

sc

enar

io

Tang

he

Irig

atio

n A

rea

Tota

l 35

0

0 33

0

2

0

6

Dom

estic

15

0

0

15

1

Agr

icul

ture

77

17

0

41

3

16

Eco

tope

5

0 0

0

4

1

Xin

gfu

Irri

gatio

n A

rea

Tota

l 97

17

0

56

7

18

Dom

estic

22

0

0

21

1

Agr

icul

ture

99

0

0

0 5

94

0

Indu

stry

29

1 21

14

3

81

47

Eco

tope

22

0

0

0 20

2

Wan

gjin

Ir

riga

tion

Are

a

Tota

l 43

2 21

14

3

101

25

94

50

Dom

estic

9

0 0

8

1

Agr

icul

ture

64

0

0

36

2

26

Eco

tope

4

0 0

0

3

1

Hua

ndon

g Ir

igat

ion

Are

a To

tal

77

0 0

44

5

28

Dom

estic

5

0 0

5

0

Agr

icul

ture

39

0

0

38

1

0

Eco

tope

2

0 0

0

2

0

Hua

nnan

Ir

igat

ion

Are

a To

tal

46

0 0

43

4

0

Dom

estic

10

0

0 10

0

0

Agr

icul

ture

28

0

0 27

0

1

0

Eco

tope

2

0 0

0 0

2

0

Hig

h

scen

ario

Tang

he

Irig

atio

n A

rea

Tota

l 40

0

0 37

0

3

0

(Rem

ark:

Bla

nk s

how

s th

at w

ater

��

��

��

��

��

��

��

��

��

1

Model and application for fuzzy relation optimal decision

Shouyu Chen and Honglan Ji

College of Civil Engineering and Water Conservancy, DaLian University of Science and Engineering, LiaoNing, DaLian, 116024, China.

Abstract Water resources shortage and water-soil environment aggravation in China restrict seriously the sustainable development of agriculture, even the whole national economy. This paper puts forward fuzzy relation optimal decision model for multi-objective system, applies it to crop plant structure which is closely related to the agricultural water resources optimal allocation, fully considers economy, ecology, society, environment etc., provides theory guide for the sustainable development of regional agriculture. The theory is strict. The solution is simple. The model is universal. Key words: Relative superiority; multi-objective system; fuzzy relation optimal decision model; crop

plant structure. E-mail: [email protected]

1 Introduction

Water resources in China are not abundant. Agriculture consumes the largest amount of water in all water use departments. Every year the drought fields are about 25%~30% of the whole arable lands. Irrigation districts are short of water about 30 billion m3. The reduced grain yields come to several thousand million kilos due to drought. Shortage of water has bad effect on agriculture particularly. In order to improve the situation, we must strengthen water resources management, make crop plant structure optimal, promote water resources optimal allocation, improve water resources availability, and then we can release the contradictory in water resources supply and demand, obtain the sustainable development of agriculture.

At present, research of multi-objective model for crop plant structure is few at home and abroad. Furthermore, people often focus on economic benefit in the previous research, neglect social benefit and ecological benefit, lead to the aggravation of ecological environment, influence the agricultural sustainable development. Therefore, when irrigation districts are short of water, we should coordinate the growth of economy, ecology, society and environment, make crop plant structure optimal, and allocate the limited water resources rationally to obtain the optimal comprehensive benefit for the agricultural sustainable development. 2 Model for fuzzy relation optimal

decision Fuzzy relation expresses the universal relations

between things, but it is only used in the single

objective system. Based on the relative superiority, we combine fuzzy relation with fuzzy optimization, found fuzzy relation optimal decision model. We will compound fuzzy relations of some single objectives to express the relations between things in the multi-objective system.

U and V are two finite domains in the multi-objective system. To objective i, the pair (g, h) composed by arbitrary elements in the U and V constitutes Cartesian product set. Its characteristic value is expressed by the following matrix.

)(�� x

xxx

xxx

xxx

X ?

????

?

?

????

?

?

?�?

?????

(1)

ghi x -to the objective i in the multi-objective

system, the characteristic value of the pair (g, h) composed by element g in the U and element h in the V; i=1, 2,��

��

��

ghihg

ghighi

ghihg

ghihg

ghighi

ghihg

ghihg

ghihg

ghi

ghi

x

xror

xx

xror

xx

xxr

,

,,

,,

,

??

????

???

???

� � � � ��

2

To the objective which is the smaller the superior

ghihg

ghighi

ghihg

ghihg

ghighi

ghihg

ghihg

ghighihg

ghi

x

xror

xx

xror

xx

xxr

,

,,

,,

,

1

1

???

?????

???

???

(3)

ghi r -the relative subordination of the

characteristic value ghi x to superiority, namely

objective relative superiority ghihg

ghihg

xx,,

?? � -the

maximum value and the minimum value of all characteristic values.

To the objective i, the characteristic value

matrix cbi X ? is changed into the relative

superiority matrix cbi R ? , namely fuzzy relation

matrix to superiority.

)(�� r

rrr

rrr

rrr

R ?

????

?

?

????

?

?

?�?

?????

(4)

Two poles in the reference continuum are 0 and 1. If

11 12 1

21 22 2

1 2

1 1 1

1 1 1( )

1 1 1

i i i c

i i i ci b c

i b i b i bc

i gh

g g g

g g gG

g g g

g

?

? ?? ?? ??? ?? ?? ?

? ?? ?? ?? ?? ?? ?? ?

L

L

M M M

L

L

L

M M M

L

(5)

call matrix cbi G ? as superior fuzzy relation

matrix.

If

11 12 1

21 22 2

1 2

0 0 0

0 0 0( )

0 0 0

i i i c

i i i ci b c

i b i b i bc

i gh

b b b

b b bB

b b b

b

?

? ?? ?? ??? ?? ?? ?

? ?? ?? ?? ?? ?? ?? ?

L

L

M M M

L

L

L

M M M

L

(6)

call matrix cbi B ? as inferior fuzzy relation

matrix. Weight vectors of m objectives in the system

are the following.

1,),...,,(1

21 ?? ??

m

iim ????? (7)

?i -weight of objective i

There are cb ? pairs in the finite domains U and V. The pair (g, h) subordinates to superiority

through the relative subordination ghu ,

subordinates to inferiority through the relative

subordination cghu .

ghcgh uu ?? 1 (8)

In order to solve the optimal value of relative

subordination ghu of the pair (g, h) in the finite

domains U and V, we found the objective function.

? ? ? ?? ? ? ? ? ?? ???

??

?

??

??

?

???

??? ?????

???? ?? ?? �� brurguuF

��1min ??

(9)

Let ,0)(

?gh

gh

du

udF obtain the following:

? ?? ?? ?? ?

p

m

i

pghighii

m

i

pghighii

gh

br

rg

u 2

1

11

1

???

???

?

???

???

?

?

??

?

?

?

?

?

?

?

(10)

According to the matrix (5), (6), the formula (10) is expressed by the following.

? ?? ?? ?

p

m

i

pghii

m

i

pghii

gh

r

r

u 2

1

1

11

1

???

???

?

???

???

? ??

?

?

?

?

?

?

?

(11)

ghu -the relative superiority of the pair (g, h) in

the finite domains U and V, namely decision relative superiority

To m fuzzy relation matrixes cbi R ? ，

��

3

)(

21

22221

11211

gh

bcbb

c

c

cb u

uuu

uuu

uuu

U ?

?????

?

?

?????

?

?

??

????

??

(12)

��

�� 3 Example and application - the

optimal decision for cultural practice in agricultural system ��

��

��

��

��? ? ?? 321 ,, uuuU ��

? ? ?? 4321 ,,, vvvvV ��

��

)(

10020080150

350350400400

50150200300

1431 ghxX ????

?

?

???

?

??? �

)(

40803260

25.3325.333838

25.1775.51695.103

2432 ghxX ????

?

?

???

?

???

�

)(

10020080150

245245280280

2575100150

3433 ghxX ????

?

?

???

?

???

�

��

��

)(

25.050.020.0375.0

875.0875.00.10.1

125.0375.050.075.0 �� rR ????

?

?

???

?

??�

)(

386.0773.0309.058.0

321.0321.0367.0367.0

167.050.067.00.1 �� rR ????

?

?

???

?

??�

)(

357.0714.0286.0536.0

875.0875.00.10.1

089.0268.0357.0536.0 �� rR ????

?

?

???

?

??�

Three objectives have the same importance to crop cultural practice, namely objective weight vector is equal.

? ? ????

????

31

,31

,31

,, 321 ????

Let p=1, we apply the model (11), compound the three fuzzy relation matrixes, obtain fuzzy relation composite matrix or fuzzy relation optimal decision matrix.

? ?��uU ????

?

?

???

?

??�

197.0794.0115.0494.0

832.0832.0933.0933.0

021.0275.0518.0911.0��

According to fuzzy relation composite matrix

? ?ghu , we draw the following conclusions.

Analyze in row: (1) If we plant soybean, ordinary black soil

three-year rotation is optimal. (2) If we plant maize, ordinary black soil

three-year rotation or non-rotation is optimal. (3) If we plant sunflower, carbonate meadow

soil three-year rotation is optimal. Analyze in column:

(1) If we adopt ordinary black soil three-year rotation, planting maize is optimal.

(2) If we adopt ordinary black soil three-year non-rotation, planting maize is optimal.

(3) If we adopt carbonate meadow soil three-year rotation, planting maize is optimal.

(4) If we adopt carbonate meadow soil three-year non-rotation, planting maize is optimal.

In a word, the choice that is planting maize and adopting ordinary black soil three-year rotation or non-�� 4 Conclusions

��

4

Reference Chen Shouyu. 1994. Theory and Application for System

Fuzzy Decision. Dalian: Dalian University of Science and Engineering Press.

Chen Shouyu. 2002. Theory and Application for Complex Water Resource System Optimal Fuzzy Recognition. Changchun: Jiling University Press.

Water rights allocation of Yellow River replacement water

Yuansheng Pei 1, Yunling Li 2 and Fuliang Yu 1

1China Institute of Water Resources and Hydropower Research, Beijing, 100044,China. 2Hohai University, Nanjing, 210098, China. Abstract Principles of efficiency, equity and sustainability were used to establish a system of water rights and define a complete set of indicators for water allocation. This is necessary since a part of the water diverted from the Yellow River, to areas served by the east and mid-route of the South-North Water Transfer Project, may be reallocated to upstream and midstream areas of the Yellow River. To promote development of the west, reallocation will take place after commissioning of the east and mid-routes and before commissioning of the west-route of the Transfer Project. Allocation of the replaced water is regarded as a special issue of not only distribution of water rights but also of multi-regional and multi-objective decision-making. To resolve the problems of multi-regional and multi-objective decision-making, the analytical hierarchy process was combined with fuzzy decision-making analysis to define a distribution of water rights based on indicators. The resulting decisions regarding reallocation of replaced water from the Yellow River appear reasonable and satisfactory. Key words: Yellow River; water right; water allocation; analytical hierarchy process; Fuzzy decision-making. E-mail: [email protected] 1 Introduction

In 1987, the State Planning Commission, in consultation with the provinces and departments concerned, formulated a plan for allocating available water of the Yellow River before commissioning of the South-North Water Transfer Project (Table 1). This plan was the first to allocate water of the large rivers in the PRC and is

considered as an outcome of the competitive use of deficient water resources of the Yellow River. The plan has played an important role in macro adjustments and controls of water allocation, helping to alleviate the imbalance between supply and demand. But the shortage of water supply from the Yellow River still exists.

Table1. Scheme for allocating available water of Yellow River (in 108m3)

Area Qinghai Sichuan Gansu Ningxia Inner

Mongolia Shaanxi Shanxi Henan Shandong

Hebei &

Tianjin

Total

Water allocated

14.1 0.4 30.4 40.0 58.6 38.0 43.1 55.4 70.0 20.0 370

The west route of the South-North Water

Transfer Project is the only one of the three routes to directly supply water for the Yellow River basin. Difficulties with the west route suggest that it is likely to begin only ten years after the east and the middle routes are commissioned in ten years. Before commissioning the western route, effective countermeasure are necessary to supply the upstream and midstream areas to alleviate water shortages. Additional access might be given to the upstream users to allow for benefits to lower Yellow River users, who would receive supplies from the east and middle transfer routes. Water withdrawn from the lower Yellow River is that for the provinces and cities in Huaihe and Haihe river basins along the lower Yellow River. Since these

provinces and cities all belong to areas served by the east and middle routes of the South-North Water Transfer Project, a part of water usually withdrawn from the Yellow River may be replaced and reallocated to the upstream and midstream areas of the Yellow River. The water quantity to be replaced is 3.04 109 m3 per annum.

2 Water rights allocation of the replaced

water 2.1 Fundamental theory of water rights Water rights, or water resource property rights, is the general name of a group of rights relating to ownership of water resources. They concern the right to use or to provide products and deliver services resulting from water resources, which are

expressed as a set of standards for regulating activities of individuals, regions and departments of water resource development and use. The Water Law of the PRC stipulates that� �� 2.2 Defining the right to use water

��

�2.3 Method of water rights allocation

��

��

3 Mathematical model of water allocation 3.1 Indicator system for water allocation

��

��

��

��

��

��

��

��

��

��

concern sustainability in water right allocations.

3.2 Construction of hierarchy process framework In the hierarchy framework, a target layer is set

as the top level, constraints, criteria for evaluation or strategies to attain a general target are set at the

middle level and important measures to attain the general target make up the bottom level. Straight lines connect interrelated factors between levels. The established hierarchy process framework is shown in Figure 1.

Figure 1. Hierarchy process frame of water allocation

3.3 Calculating indicator weights from AHP-

based discriminatory matrix analysis Firstly, a discriminatory matrix, [��u ]k�k,

indicating relative importance of each indicator, is derived by comparing each two indicators. The method of quantifying the discriminating values, ��,��ff , is shown in Table 2, where ��f

is the importance of indicator i compared with indicator j and ��f and vice verse

)(ujuif = )(1

ujuif ?

By comparing each two indicators, the following discriminatory matrix is derived:

???

?

???

?

????

??��bb

bbB��

Then, the coefficient of importance of each

indicator, ia , is determined. According to the

discriminatory matrix B, maximum characteristic

value max? is calculated by applying the power

method (through the mathematical software Matlab). The characteristic vector corresponding

to the maximum characteristic value max? is the

coefficient of importance, ia to be determined,

Table 2. Levels of importance of discriminatory indicators ��u 1 3 5 7 9 2 4 6 8 ��f Equal

importance Slightly

more important

Significantly more important

Strongly important

Most important

In-between importance

Level of object Level of criterion Level of indicator category Level of indicator Level of plan

Qinghai

Shanxi

Inner Mongolia

Sichuan

Gansu

Ningxia

Henan

Shaanxi

Waterallocation

Efficiency

Sustainability

Equity

Efficiency of water resourcesutilization

Economic development

Economic benefit

Water use efficiency

Proportion of GDP

Proportion of gross industrial outputvalue

Proportion of grain yield

GDP per unit water use

Water shortage s

Equal water allocation

Water yield

Proportion of water deficit

Rate of water deficit

Per ha water use

Per ha water use plus rainfall

Per capita water use

Per capita water use plus rainfall

Water yield

Secondary soil alinization

Water pollution

Groundwater drawdown cone

Drying-up of riverEcology/environment

Social developmentPopulation growth

Rate of change in industrial structure

Contribution of sci-tec advancement

Condition of medical treatment andsanitation

expressed as ），，，（ naaaA ??? 21

.

Finally, the consistency of the discriminatory matrix B is tested.

1max 1 ????? ）（）（）（ nnBC ?

where: ）（BC �� ）（BC �� —�� iw —��—�� ia —��

�� ijb —� ��

�—�� ijr —��

�� ijf —��71�� 3.4 Construction of fuzzy matrix at level of plan

��

?V �� ， �� ， ⋯ ， ��m � },,,{ 21 mvvv ?? �� }{ 21 nfffu ，，， ?? ��

Tnjjjj fffv ），，，（ ?? 21 � 1?j ，�，⋯，n ��

�� ijf ��

???

?

?

???

?

?

?????

??

?

nmnn

m

m

fff

ffffff

F

21

22221

11211

�

�� ijf ��

)()(1.0

)()(1.01

min

1max

bdff

adffr

iij

ijiij ，

，?

?

??????

? ijf ��

��

��

ijf ��

�� ijr ��

�� ijf ��

��

???

?

???

?

????

??

nmn

m

rr

rrR

1

111

~�

3.5 Fuzzy comprehensive decision-making for multi-area and multi-objective water allocation

��

???

?

?

???

?

?

????

?

???

?

?

???

?

???

?

nmn

m

T

n rr

rr

a

a

RAC

1

1111

~??? ��

�� ? ? ?nccc ,,, 21 ? �� — � �� “ ? �� ），（ ??M ��

? ?mwwwWCw ,,, 21 ??? ��

4 Allocating Yellow River water after

initiating South-North Water Transfer Project

4.1 Ranking the relative importance of each indicator

��

Table 3. Criteria of evaluation value assignment

Grade Maximum Very high high Slightly high

Middle Slightly small

Small Very small

Minimum

Value assigned

0.9~1.0 0.8~0.9 0.7~0.8 0.6~0.7 0.5~0.6 0.4~0.5 0.3~0.4 0.2~0.3 0~0.2

every two indicators. From the discriminatory matrix, the weights of the fuzzy indicator set are derived as follows:

?A （ 2021 ,,, aaa ? ）

=0.0943,0.1152,0.0500,0.0522,0.0984,0.0957,0.0957,0.0281,0.0281,0.0281,0.0281,0.0264,0.0221,0.0221,0.0221,0.0221,0.0429,0.0429,0.0429,0.0429 4.2 Plan level evaluation matrix 4.2.1 Values of quantitative indicators1)

Water allocation indicator values need be ranked

in accordance with socioeconomic conditions of each area in the upper and the middle Yellow River (Table 4). Then, by applying equation (1), the quantitative indicators can be calculated for each area. 4.2.2 Values of qualitative indicators

The qualitative indicators for water allocation are determined by applying fuzzy decision-making theory. The outcome of �� 20�8��

Table 4. Ranking of quantitative water allocation indices

Efficiency of water resources use

Economic development Economic

benefit Water Shortage Equal water allocation

Region Water use

efficiency

Proportion of GDP

(%)

Proportion of grossindustrial output value

(%)

Proportion of grain yield

(%)

GDP per unit water

use (yuan/m�) Proportion

of water deficit

(%)

Rate of water deficit

(%)

Per ha water use

(m�/ ha)

Per ha water use plus rainfall (m�/ ha)


(m�/person)


plus rainfall (m�/person)

Qinghai 0.38 3.9 2.4 2.5 10.1 0 0.01 7671 8742 310.9 389.8

Gansu 0.46 13 13.5 13.7 15.3 7.5 7.02 6809 7487 169.2 227.5

Ningxia 0.32 4.7 4 10 2.7 0.9 0.41 9987 9075 736.3 867.7

Inner Mongolia

0.37 12.2 12.8 11 7 1.1 0.54 6006 7043 722.8 932.4

Shanxi 0.46 20.8 25.7 18.4 29.5 31 26.7 5265 5841 206 333

Shaanxi 0.48 26.8 21.2 30 24.6 49.5 27.8 3486 4586 137.1 264.8

Henan 0.46 18.6 20.5 13.4 39.8 10 13.6 5316 5685 155.7 274.8

�Table 5. Ranking of water qualitative allocation indices

Region

Water yield

Non-secondary soil salinization

Drying-up of rivers

Groundwater drawdown

cone

Extent of non-polluted

water

Contribution of science and technology

advancement

Rate of change of Industrial Structure

Population growth

Improvement of condition of medical

treatment & sanitation

Qinghai 0.9 0.8 0 0 0.8 0.1 0.1 0.3 0.8

Gansu 0.8 0.8 0 0 0.85 0.25 0.25 0.35 0.8

Ningxia 0.25 0.2 0.25 0.6 0.55 0.35 0.35 0.3 0.75 Inner

Mongolia 0.2 0.8 0.65 0.5 0.75 0.4 0.4 0.5 0.75

Shanxi 0.65 0.9 0.85 0.75 0.6 0.7 0.9 0.85 0.95

Shaanxi 0.3 0.95 0.95 0.95 0.85 0.9 0.85 0.9 0.95

Henan 0.1 0.5 0.75 0.7 0.2 0.8 0.5 0.10 0.10

4.3 Proportions of water allocation

��

? ?251.0,439.0,397.0,209.0,142.0,224.0,158.0

21

?

??????

），，（ mcccCRA?�

��? ?138.0,241.0,218.0,115.0,078.0,123.0,087.0?C

�� 3��

? ?20.4,34.7,63.6,48.3,37.2,74.3,64.2?? ii WCW �

�� 3�� 3�� 3�� 3�� 3�� 3��3��References ��

��

��

Management in China, Beijing, China Water Resources and Hydropower Press, pp5~6

Xie Jijian and Liu Chengping. 2000, Measure and

Application of Fuzzy Mathematics, Wuhan, Huazhong University of Science and Technology Press.

Improvement of 10 large seasonal rivers feeding the Yellow River in Dalat Banner of Inner Mongolia

Baolin Ji 1, Zhiyuan Lu 1, Xiangdong Shen 1, Xianyou Mu 1 and Dong Suo2

1Inner Mongolia Agricultural University, Huhhot, China. 2Water and Soil Conservation Bureau of Dalat Banner, Erduosi , Inner Mongolia ,China.

Abstract Key elements of a comprehensive improvement programme are proposed for 10 large seasonal rivers. Measures include water and soil conservation, tree planting and recovering grassland and forestry through abandoning farmland in the upper hilly reaches. Restoration of vegetation to prevent desertification should be combined with projects to change the desert into farmland and to charge an aquifer beneath the Kubuqi desert. Floodwaters should be diverted to warp land for irrigation and to improve salt and alkali soil. Key words: Yellow River; flood disaster; comprehensive improvement.

E-mail: [email protected] 1 Introduction

Kongdui is the Mongolia pronunciation for the valley of ten big seasonal rivers in the first branch of Yellow River at DaLat Banner of Inner Mongolia. According to the National Construction Programme for Ecology and Environment, it belongs to the upper and middle reaches of the Yellow River, while at the same time, it is a sand blown area in the middle of the Kubuqi desert and Erduosi grassland. It is major area of national ecological construction over the last 5-10 years. How to control water and soil erosion, to protect the safety of people and belongings in the lower reaches and to reduce the huge sediment flow into Yellow River are the most important problems of this comprehensive improvement program. 2 Basic conditions in the valley 2.1 Geomorphology

The ten big seasonal rivers originate from the Erduosi terrace then flow into the Yellow River. Within Dalat banner its upper reaches are made up of loess hills, with the Kubuqi desert in the middle reaches and an alluvial plain makes up the lower reaches. It lies at longitude 108°47��°��°��°�� 2�� 2��

��

�� 2�� 0��0��

��2��

�� 2� ��

�2.2 Soil and vegetation�

��

organic matter content only is 0.61%. The vegetation is short and sparse. The cover rate is 7%~30%. Shifting sands make up a large part of the soils in the Kubuqi Desert. Average organic matter content is 0.36%. The vegetation mostly is oil wormwood growing to a height of 45~60 cm and with only 30% ground cover. The alluvial plain is mostly made up irrigated, saltly, alkali and meadow soils. Grass flourishes so organic matter of such meadow soils is 0.79- 0.82%. The soil organic content is 0.31-1.14%. The height of vegetation is 10~150 cm with ground cover extending up 50%.

2.3 Weather conditions

Dalat banner has a continental climate, which is cold and long in winter and short and hot in summer. The mean annual temperature is about to 6oC, with and range of 40.2 to -34.5oC. Average annual rainfall is 240-360mm, reducing from east to west. Around 71% of the annual precipitation falls in July, August and September. The annual evaporative demand is 2200 mm, some seven times the rainfall. It is highest in May and June when monthly totals can exceed 375mm. Annual sunshine hours total 3159.4 hours, with only an average of 130~140 frost-free days.

2.4 Water resources

In the banner, the long-term average annual surface flow is 1.36×108 m3, equivalent to a runoff depth of 20 mm. Flow in the flood season accounts for 90% of annual flow. The annual flow variation is significant, especially between wet and dry years. The annual Yellow River flow passing through the area has a long-term average of 247.5×108 m3. Sources of ground water amount to 3.15×108 m3 in the banner. Ground water yields are 4.4 × 104

m3/km2 in the north plain region and Kubuqi desert while it is 2.9×104 m3/km2 in the southern hills region. The daily storage capacity of groundwater yield is 89.3×104 m3 in the banner. The single well yield can achieve 100-800m3/day in the north plain area, 100 ～ 500 m3/day in the Kubuqi desert (middle region) and 10-100 m3/day in the south hills region. The gross water resources reserves in the area are 4.51×108 m3. The per capita water resources are 1400m3, or 2890 m3/ha, expressed as an agricultural water supply.

2.5 Social economy

The Dalat banner is made up of 9 towns, 1 Sumu (similar to town) and 13 Xiang (similar to town). The total population is 324 thousand, including 262 thousand rural inhabitants, with a population density of 40-people/ km2. The rural labor force is 150 thousand. Agricultural land amounts to about 90 thousand ha, with equal proportions of food and economic crops. The food crops are mostly wheat,

corn and potato. Economic crops include sunflower, sugar beet, oil plants, vegetables and quality grass. Total yield of foodstuff is about 5×108 kg while livestock numbers are of the order 800 thousand.

2.6 Threats to seasonal rivers (Kongdui)

The most immediate danger is that floods carry then deposit large amounts of sand, which raise the bed of lower, and middle reaches, thereby reducing flood carrying capacity. Since 1961, the bed level of lower reaches of Dongliu fosse has risen 4 m. ��

�3 Comprehensive improvements 3.1 Guidance thoughts

��

�3.2 Hill lands

��

bare rocks outcrops, then scale pits are adopted for improving the land. Oil pines are planted in these pits with purple medic planted between the pits.

Since slopes are normally steep, so improvement through mechanisation is difficult. Broadcast sowing is sometimes possible for Elaeagnus

rhannoides L., Caragana Korshinskii Kom, so these plants can take root on slopes and increase

the vegetation.

Table 1. Hydrology and sediment characteristics of the ten seasonal rivers (1960-1989)

Maximum in past years Long-term average

River name River basin area (km2)

Length of river

(km) Flow rate

(m3/s)

Silt content (kg/m3)

Run-off amount (104m3)

Silt discharge

(104t)

Sediment runoff

modulus (t/ km2)

Maobula Kongdui 1261 111 5600 1500 901 330 2620 Burigasetai fosse 545 74 3670 430 158 2890

Heilai fosse 944 89 4040 998 367 3890 Xiliu fosse 1194 106 6940 1550 3220 481 4030 Hantai river 880 90 3090 1350 1880 275 3130

Hashila fosse 1089 92 4070 3510 524 4810 Muhaer river 407 77 1610 708 177 4350 Dongliu river 451 75 1500 669 167 3700 Haoqing river 213 29 435 335 84 3940 Husitai River. 406 65 2350 590 148 3650

Total 7390 13241 2711

Note: 1. The basin area of each Kongdui does not include the plain area. 2. The data for Maobula kongdui, Xiliu fosse and Husitai River are observed data and others are flood survey estimates.

Valleys are normally quite broad in the hilly area. Land in the middle, bottom and along sides of main valley can be developed into basic farmland through regulating small scale flooding and deposition of silt. Lateral ditches and rill channels are built to create warped valley dams and pool dams. This method will create a system of dams for improving valleys, then irrigation of land will be possible in the near future. In some regions where there is difficulty to develop ditch dam, it may be possible to adopt terracing as a means of collecting

rains, or to create drought wells for use with water saving irrigation technology.

3.3 Control of wind erosion

In the worst affected areas, protection barriers are required to stop soil wind erosion, created using sand willow and Hedysarear scoparium fisch. et Meg. ��

Figure 1. Project locations of flood diversion, silting and irrigation project

planting sand willow, which is arranged in either belt and diamond arrangements combined with broadcast sowing of grass seeds. In the bottomlands that are relatively flat, with better moisture supplies, then sand willow and Caragana Korshinskii Kom can be planted to build a protection forest.

There are broad bottomlands to the north of the Kubuqi desert where it connects with the plain. Through local investigations, we plan to build flood diversion works and divert floods so as to reclaim farmland. Floodwater will be better used for groundwater recharge. This should reduce the flood protection burden in the lower reaches and reduce the amounts of sand added to the Yellow River. 3.4 The plain region

Flood protection mostly depends on embankments but with riverbeds constantly rising so the level of flood-control is obviously reduced. Then reinforcing the protection embankments is one of the main measures in the plain regions. In addition, diversion projects are needed to alleviate protection flood pressure of the lower reaches.

With the rising bed level of all rivers in the plain, the land elevation in many districts is already below these levels. This leads to stalinization and drainage problems with adverse effects on crop yield. There are almost 10×104 hm2 of bottomland, salt land and meadow in the middle and lower reaches of the ten rivers that need reclaiming. We plan to build warped land through diverted floods, to improve lower yield farmland and to develop lower salt land. For example, nine projects have been approved for development of warped land through diversion of Hashila River floods.

Plain regions in the lower reaches of the ten rivers depend on groundwater irrigation at all times. A significant cone of depression has been observed. However, the ten rivers usually have flow and not only is the temperature of floodwater higher, but it has also abundant nutrients. So, water projects can divert floodwater for irrigation.

4 Significant problems The policy of changing farmland to grass and

trees and forbidding grazing is very important. Only by sticking to this policy can farmland be effectively used in the plain. Forbidding grazing is equally important in the Kubuqi desert region. Land use needs to be adjusted. Regulated areas might grow quality grass seeds, Chinese medicinal materials, sand willow, Caragana and liquorice. This will improve income of the local farmers. Flooding of the ten rivers has some unique features. So when we design diversion flood projects, these peculiarities should be noted and lessons learnt from the failure of diversion flood projects on the Hashila River. References Ground Weather Data of Yikezhao League Inner

Mongolia, Inner Mongolia Observatory. Ji Baolin, Shen Xiangdong, Mou Xianyou. ????

Engineering Feasibility Study for Controlling Sand Floods and Warping Ground Tributaries of Yellow River in Inner Mongolia, The International Conference on Optimum Allocation of Water Resources in Ecological Environment Construction and the Sustainable Development of Arid Zones, Inner Mongolia University Publishing Company. China.

Ji Baolin, 2002, Symposium of 2002 annual academic conference of China Water Resources Society. Haidian zone, Beijing, Three Gorges Publishing Company, China, pp284-289.

Ji Baolin, Shen Xiangdong, Dong Suo et al., 2002, Accelerating construction of ecological environment of West regions, promoting concordant development of regional economy, Sichuan scientific and technological publishing company, pp185-189.

Zhu Junfeng, Zhu Zhengda et al., 1999, The Prevention and Cure of Desertification of China, Forest Publishing Company of China, Beijing. pp98-127.

Sewage purification investigations in Shandong

Jigang Ma1, Zhenghe Xu 2, Juan Xie3, Tianyou Li 4 and Rong Cong2

1 Wuhan University, Wuhan, 430072, China. 2 Institute of Water Science of Shandong Province, Jinan, 250013, China. 3 Water Conservancy Department of Shandong Province, Jinan, 250013, China. 4 Xiaoqing River Administration of Weifang City, Shouguang, Shandong, 262700, China. Abstract A sewage purification investigation was carried out in Shouguang, Shandong. A sewage marsh disposal system is described for which treatment is achieved, while at the same time having an environmental benefit. Treatment was combined with reclaiming a saline area. Overall treatment combines anaerobic treatment, the reed marsh treatment and aerobic treatment, prior to final re-use by irrigation. Now a natural ecological reserve has been established including the reed marsh, a protected forest and a fishing pond. All these are combined with some farmland to create a bird and animal sanctuary. The demonstration area helps popularize such ecological engineering approaches to sewage re-use. Key words: Sewage purification, sewage marsh, environmental benefits, ecological engineering. E-mail: [email protected]

1 Problems of wastewater use in Shandong Shandong is a developed province in China. In

the last 20 years, with quick economic development so the population has greatly increased. As a result, large amounts of sewage discharge into rivers directly or indirectly, without any treatment. Most of the rivers, which are near the cities and towns, are now changing into blow down river, with the result of damaging the headwater as well as polluting the living and ecological environment of human being.

From water quality monitoring data, there is neither a river stretch nor a reservoir whose water quality meets the 1st standard and the river stretch whose water quality is over the fifth standard occupies 78%, and the reservoir whose water quality is over the third standard occupies 60%. The Huai and Hai Rivers are especially serious because the two river catchments have an advanced cultivation industry.

Shandong has a shortage of water resources, and pollution of headwaters becomes more and more serious, aggravating difficulties of developing water resource and sharpening the contradiction between water supply and demand. So, as the largest user of water resources and needing a relatively low standard of water quality, agricultural users have no choice but to purify sewage to make it a viable resource. There is a long history of sewage irrigation in Shandong. As early as 1958, the Construction and Industry, Agriculture and Sanitary Ministries together held the 1st meeting of sewage irrigation in Jinan, capital of Shandong Province. Incomplete records suggest that by the 1980��

��

��

��

2

purification process. 2 Demonstration area for sewage

purification in Shouguang Shouguang lies in the downstream area of the

Mi River, to the east of the Mid-Shandong Plain and south of Jiaoji Railway. Shouguang industry is mainly concerns organic agriculture for vegetables and fresh flowers with exquisite oceanographic chemistry. T�� 3�� 3��

��

��

�� 3 Sewage treatment operations 3.1 Introduction

��

Table 1. Water quality monitoring of sewage Ttreatment in Shouguang unit: mg/l

Time Item PH SS COD BOD AH3,

N As Chloride Oil Alkoxide Lead Tin

Inlet 7.33 192 365 225 28.2 0.016 0.014 9.2 --- --- --- Apr.5th

Outlet 7.28 26 112 28 2.98 --- --- 0.43 --- --- ---

Inlet 7.31 186 368 210 29.6 0.017 0.012 9.0 --- --- --- Jul. 5th

Outlet 7.15 20 110 20 2.74 --- --- 0.32 --- --- ---

Inlet 7.29 188 350 245 25.6 0.014 0.013 8.6 --- --- --- Oct.5th

Outlet 7.07 20 102 30 2.52 --- --- 0.22 --- --- ---

Inlet 7.41 202 388 275 30.8 0.022 0.016 9.8 --- --- --- Jan.5th

Outlet 7.32 38 158 65 7.9 --- --- 2.35 --- --- ---

Note: the results of 2001

3

3.2 High yield and high quality of crop demonstration area

After treatment, effluent is used for crop irrigation. Results for 2001 show that winter wheat yielded 5.35 tons/ha and summer corn 5.94

tons/ha. Yields were increased by over 60%, with an increase of annual income of RMB 3 million Yuan. Uptake of metals was within the required standard (Table 2).

Table 2. The results of crops in the demonstration area by sewage irrigation mg/l

Elements As Hg Cr+6 Pb Cd S (/%) Rough protein

(/%)

Winter wheat 0.067 0.055 0.74 0.72 0.16 0.863 14.7

Summer corn 0.056 0.019 0.45 0.68 0.061 0.59 8.2

Standard ≤0.7 ≤0. 2 ≤1. 0 ≤0. 4 ≤10

Note: the results of 2001 3.3 Natural environment is improved

The reed marsh is helpful to the sewage treatment. We selected one place for sewage purification, and after a period, the environment is better than before, then we selected another place for treatment. Reeds form a small ecological system, transferring solar into biological energy. The extensive growth attracts many birds, creating a varied ecological environment. Over 50 kinds of bird are now observed, and an estimated total breeding weight of 2900 tons. Water infiltrating into groundwater after sewage treatment, helps prevent encroachment of seawater and generally improves the water environment in the area.

Before amelioration of the demonstration area, soil pH value was about 8.5 with over 83% bare land or solonchak. Previously there were only 15 bird species, with a total breeding weight of about 1400 tons. After amelioration, soil conditions were greatly improved. Plant, animal, and wheat straw residues together with sewage sludge are full of organisms, which improve soil fertility. Soil microbial organisms have improved soil structure and now pH value is 7.0-7.5, with high fertility and fine structure. Restored land is suitable to grow soybean, sorghum, and corn.

Since a large amount of organic manure is transferred so the forest industry is benefiting. The aquaculture area also creates its ecological system, which plays a key role in balancing the whole system. Lotus roots have high economic returns, and leaves of Fengyan lotus can be converted to animal food. Fish, also have high

economic returns and act as a consumer in the system, which helps stabilize the ecological system. A dynamic equilibrium is created of green plant producer, fish, animal, or other natural consumers and microorganism decomposers. By using sewage irrigation, the ecological system can remain stable. 4 Problems

There are still some problems although we achieved great success. (a) In the reed marsh treatment, only a single species of microorganism is treating the sewage, which is a disadvantage. In the long run, the aquatic microorganism community may be vulnerable. So more aquatic plants and animals are required in the ecological system. (b) The cold weather performance is less good, so if we want to popularize the project in north China, then a key step is developing the disposal technique for continuous operation in cold conditions. (c) As the project develops, sewage must meet discharge standards then treatment sections can be put into the project. But we found that some plants discharged wastewater with little or no treatment, water quality easily deteriorated and emergency measures were lacking. We should pay more attention to this. (d) We gave little consideration to storing water in winter and using it in the summer or busy time. We need a detailed plan of annual water use.

A new water resources appraisal system in water-saving irrigation

Wei Chen, Lianheng Zheng and Wenjuan Liu

Hebei Water Resources Scientific Research Institute, Shijiazhuang, 050051, China. Abstract Water-saving irrigation is a long-term strategy and a focus of water resource management in areas with shortage of water. Great potential exists in Water-saving irrigation because rural water takes more than 70% of available water resources. However, existing indicatives of water-saving efficiency only comprises water-saving amount or water-saving efficiency in irrigation without considering water amount in repetitives; this incurs error in calculating water-saving amount. In this paper, firstly, the concept of water-saving irrigation was identified in the perspective of water resources, then new indicative system was established to evaluate water-saving irrigation, i.e. Coefficient of irrigation water resources was used including once water use percentage and repetitive percentage, multiple water use coefficient in channel and multiple water use coefficient in the field, on which was based to deduce water resources coefficient transporting in channel, coefficient of irrigation water resources in wells and channels, coefficient of irrigation water resources in base land. These help calculation of actual water-saving amount and better understanding the actual potentialities of water-saving in local area. Key words: Water-saving irrigation; coefficient of irrigation water resources; appraisal in water-saving

irrigation. E-mail: [email protected] 1 Introduction

21 century is an age with historic rapid development. It is also an age with difficulty in balancing water supply and demand. Water shortage in China, particularly in Northern China is very serious. So, water-saving agriculture is necessary in future. Hebei province belongs to arid and semiarid areas with serious shortage of surface water. Most part of region over exploited ground water. Agriculture irrigation takes 74% of water in Hebei province. Therefore, research on indicatives of water-saving efficient in irrigation and its potentialities of water-saving is necessary. Evaluating method has been a high international priority. 2 The limitation of existing indicatives of water-saving irrigation The technology of water-saving irrigation have been used for more tha��

�� 3 Establishment of water resources appraisal system in water-saving irrigation � � ��

is used for supplying ground water which is subdivided into two parts, one part is used once more, the other part is wasted through undercurrent evaporation. Therefore, activities of water-saving can not increase water amount, but it can minimize loss of channel leakage. Irrigation water amount is increased while sum of surface water and ground water does not change. In this way, the concept of water-saving irrigation can be defined as �� 4 Formula of coefficient of irrigation water resources use � � �� ..?water? � �� channel? ��

� � channelheadQ , �� ? �� 1? �� 2? ��

� � � ? �� field? �� ?? ??? ）（ channelchannelheadQ 1, �� ??? ???? ）（ channelchannelheadQ 1, �� 1, 1 ???? ????? ）（ channelchannelheadQ ��

21, 1 ????? ?????? ）（ channelchannelheadQ ��

��

?channelrepetitive,? ��

�� 211 ????? ????? ）（ channel ��

��

� � ?fieldrepetitive,? �� ? （��

��）× 1? × 2? ��

�� channelrepetitivechannelchannelwater ,, ??? ?? � �

�� ?irrigationwater,? ��

fieldrepetitivechannelchannelrepetitiveirrigation ,, ???? ????

� � �� ?fieldwater,? ��

�� fieldrepetitivefield ,?? ?? �

�5 Actual water-saving of irrigation

district base on water resources Usually, when we calculated water-saving amount of adopted measure fore-and-behind. Quantity of water was calculated by the irrigation ration of water-saving before minus water-saving behind multiply irrigation area. But, in the perspective of water resources, the actual water saving amount deduction from leakage effective quantity of water. Thus, in average years, supposed supply of rainrall leakage of water-saving fore-and-behind and side is sameness, and ignored quantity of water inflow and outflow, the actual water-saving amount in Hebei plain irrigation area equal to water amount difference of irrigation deduction from quantity of water of supply of irrigation leakage utilization. Water-saving amount is objectified appraisal in coefficient of canal water utilization and coefficient of field water utilization replaced by coefficient of irrigation water resources use. 5.1 Actual water-saving amount in irrigation area Q? )( rIrI ???

APcETPcET ???

??? ??????? ?? 水水）（ ?? //)( 00

where： Q? —actual water-saving amount，m3;

rIrI ?、 - irrigation water amount fore-and-behind

considering repetitive water use ， m3;

cTEcET ?、 — water requirement by crop of

water-saving fore-and-behind ， m3/hm2;

00 PP ?、 — effective quantity of rainfall

fore-and-behind， 00 PaPaPP ????? 、，m3/hm2;

?? waterwater ?? 、? — coefficient of irrigation

water resources use fore-and-behind; A —area. hm2. 5.2 Actual water-saving amount in channel Water amount at head of channel considering channel leakage in repetitive once.

channelwaterfieldchannelhead AQQ ,, /???

coefficient of canal water utilization

from channel? raise to channel? ? ， formula of

water-saving amount is：

channelwaterAQQ field ,/????

channelwaterfield AQ ,/? ???

? ?? 21)1(/1 ??? ??? channelchannelfield AQ ????? ? ?21)1(/1 ??? ??? channelchannel ?????

where： fieldQ —irrigation ration in field.

6 Water resources appraisal system with water-saving irrigation

In the process of defining multiple water use coefficient in channel and multiple water use coefficient in the field, water resources use coefficient in channel, coefficient of irrigation water resources use in wells and channels, coefficient of irrigation water resources use in base land. Actual water-saving amount is clarified and better understanding of actual potentialities of water saving in local area is obtained.

In order to get the actual water-saving amount in one irrigation area, crop water demand was calculated with the help of referenced crop evapotranspiration and net water amount of irrigation area is obtained by effective precipitation and water amount taken in groundwater. The introduction of coefficient of irrigation water resources use helps consideration of multiple water use factor with reference of irrigation water use in one calculated year, we are able to objectively appraise the water-saving amount in one irrigation area. This lays a foundation of optimal allocation of water resources, so as to provide stable water for irrigation. 7 Conclusion

In the process of clarifying the definition of irrigation water efficiency and deduce its equation, repetitive use of leaked water was considered. This work establishes theoretical foundation for calculation of actual water-saving amount and better understanding the actual potentialities of water-saving in local area in a wider range of view. References Ministry of water resources rural water

department. 1998. Water-saving Irrigation Technology Standard Edit. Beijing: China Water Power Press.

Rural Water Department of Ministry of Water Resources. 1998. Water-saving Irrigation. Beijing: China Agricultural Press.

Sheng Zhengrong. 2000. New Concept of Water Saving Study and Application of Real Water Saving. Beijing: China Water Resources Press.

Zhao Jingcheng.1999.Recognition once again on water saving irrigation-study on generalized water saving irrigation. China Rural Water and Hydropower. (7).4-8.

1

Conversion of Four Waters in wet and low-lying farmland in Sanjiang Plain

Yongxia Wei 1, Baiying Kang 2, Daben Guo 3, Yanling Zhao4 and Qiang Fu1

1Water and Construction College of Northeast Agricultural University, Harbin, 150030, China. 2 Heilongjiang Land Reclamation Bureau, Harbin, 150090, China. 3 Survey & Design & Research Institute of Heilongjiang Land Reclamation, Jiamusi, 154002, China. 4 South Florida Water Management District, West Palm Beach, FL33406, U.S.A. Abstract Arterial drainage, field drainage and appropriate sub-soil treatments have been developed in China’s ��4�� Key words:� ��

��E-mail:�� 1 Introduction

�� ×��4�� ×��4� ��

�2 Relation between plant product industry and four waters distribution

��

��

��

��

2

of wet and low-lying land, therefore improve the agricultural production gradually. The framed diagram of the four waters conversion before the wet and low-lying land control is shown in Figure 1.

3 Main measures of four waters conversion in low-lying farmland

It is impossible to change the temporal and spatial distributions of rainfall under the power of science and technology at present. The percentages of other Three Waters can be regulated by the measures of field water engineering and tillage. Here water-engineering measures include open ditches, closed drains, concealed pipes, mole drains, soil fissures and absorbing wells, etc. Tillage measures include deep plowing, deep soil loosening, and so on. The scheme of the field engineering arrangement is various with the natural conditions of the wet and low-lying farmland. Practically, 3 main types of the schemes in Sanjiang Plain are as follows:

- In case of complex micro land feature, more low ��

��

��

��

��

��

��

�4 Analysis of four waters converting mechanism 4.1 Four aspects of four water conversion

��

��

��

�� 4.2 Changes to converting parameters

��

3

Four Waters conversion.. On the basis of field data, the relation curves between the burying depth of ground water and evaporation coefficient in rainy days, surface runoff coefficient, ground water recharge coefficient by rainfall, total water resources coefficient have been drawn respectively (see fig. 4 ). The formulas are as follows: k=h/t as=R/P

ar=H/P aT= as+ ar μ= Vs/Vt C= Eq/E601 Cr= Ey/P

Where: k is hydraulic conductivity (m/d); h is constant infiltration amount (m); t is the duration of constant infiltration (d); as is surface runoff coefficient; R is runoff (mm); P is rainfall per time (mm); ar is the ground water recharge coefficient by rainfall; H is the amount of ground water

recharge by rainfall (mm); aT is total water resources coefficient; μ is storage capacity; Vs is the volume of water drained out from soil (m3); Vt is the volume of soil from which the water is drained out (m3); C is the ground water evaporation coefficient; Eq is the amount of ground water evaporation (mm); E601 is the water surface evaporation (mm), it can measured by E601 pan; Cr is the evaporation coefficient in rainy days; Ey is the amount of evaporation in rainy days (mm).

From the relation curves, the Four Waters converting coefficients before and after wet and low-lying land control can be obtained (see table which is obtained from the experiment area with meadow Baijiang soil in the 14 team of 850 state farm).

Table 1. Comparison of the four waters converting coefficient before and after the measures

implementation Soil Depth（cm） k( km/d) a�� μ a� C

before after before after before after before after before after Meadow 0-30 0.25 0.35 0.12 0.20 baijiang 30-50 0.06 0.25 0.13 0.42 0.06 0.10 0.06 0.20 0.45 0.30 soil 50-100 0.05 0.10 0.04 0.05

The figures and the table show that: - Above the mole drains and closed pipes, the

hydraulic conductivity and the storage capacity in the soil are much more affected by deep loosening, deep plowing and fissures, and the biggest change happened in middle layer, but below them the soil remains as before.

- The surface runoff coefficient is more than 2 times as it was, the reason is that the surface accumulating water after rain and the water exceeding field capacity are all converted into runoff.

- The ground water recharge coefficient by rainfall and the ground water evaporation coefficient are all reduced greatly, because the depth of ground water table burying is controlled lower than 0.7-1.0 m due to the mole drains and closed pipes application.

- The evaporation coefficient in rainy days almost has nothing to do with underlying condition.

- Because of the increase of soil storage capacity, the total water resources coefficient decrease.

- The relation between the ground water recharge coefficient by rainfall and ground water table burying depth is shown as skew curve, the reason is that when the ground water table burying depth is lower, the coefficient is almost affected by under ground storage capacity, and it has very close relation with the soil moisture content in unsaturated zone when the depth is bigger.

- With the ground water table burying depth increasing, the actions of the under ground

storage capacity and moisture content in unsaturated zone are diminished gradually. So, as, ar, aT are all tend to a stable value respectively.

It must be mentioned here, that because Sanjing Plain is located in the seasonal freezing region and the laws above were derived in rainy seasons, so the laws would be different in the long wintertime and periods of thawing. 5 Estimation of the four waters converting amount

The amount and the percentage of converted water are relative with the natural conditions. Now take 14 team of 850 state farm as an example to estimate them as follows:

- The distributions in natural conditions: the mean annual rainfall is 550mm, of which 80%(440mm) is concentrated in June to October. Take the 440mm of rainfall as 100%, 57.2mm of surface runoff is 13% of the total, 242mm ground water recharge is 55%, 30.8mm of evaporation in rainy days is 7% and 110mm of soil water is 25%.

- The distribution after wet and low-lying land control

Supposing 440mm of the mean annual �� References

4

Guo Daben, 1988. Method of farmland drainage modulus calculation in plain region, Journal of

Heilongjiang Hydraulic Engineering College, (2), 1-7.

Causes of changes in run-off and sedimentation in the Weihe River Basin

Guoqing Wang 1,2 and Haobing Li 2

1Department of Hydrology and Water Resources, Hohai University, Nanjing 290098, China. 2Institute of Hydraulic Research of YRCC, Zhengzhou, 450003, China. Abstract From a simulation of surface flow and a monthly water balance model, a formula for sedimentation was established. First, background levels of run-off and sedimentation were derived from historic meteorological and hydrological data for the Weihe basin. Next, values were extrapolated for the period 1970~1995 by hydrological simulation. Then, the causes of variations in water and sediment volumes were analyzed. Results showed that, in the period 1970~1995, annual runoff and sedimentation at Huaxian station decreased ��8�3��8�� Key words: �� E-mail�� 1 Introduction

��

�� ? � ��? ��? � ��? �� 2� ��

��

��

�� ? ��8��8�3��? �� 2� �� ? �� 2� �� ? ��

��

been developed in more than 80 places with an effective irrigation area of 9 million mu, and about 222 large and medium sized reservoirs have been built with a total storage capacity of up to 2.1 billion m3. These human activities have had a significant effect on runoff and sedimentation.

2 Runoff and sedimentation models 2.1 General Model

Using hydrological simulation to analyze the causes of water and sediment variation, a model should be able to simulate long-term water and sedimentation processes. If the calculation interval is too short, such as one hour or one day, it not only needs too much hydrological data, but also needs over-elaborate calculation methods: currently available data is insufficient. Therefore, one month was chosen as a suitable calculation period.

A monthly water balance model has been established according to water conservation principles (Wang et al., 2000), which has good physical interpretation of parameters. Discharge was simplified into two components: surface flow and ground flow. Rainfall and surface flow are the driving forces of sedimentation, but there is no actual data recorded for surface flow. So, the model used a simulation of surface flow together with the monthly water balance. A formula for sedimentation was established by analyzing the relationship between sediment, rainfall and surface flow. As a one month period is relatively long, and most runoff and sediment during this time flow through the gauging station, any accumulation of water and sediment was not included in the model. Compared with other hydrological models, the model has the merits of a simpler structure, fewer parameters and being easy to

calibrate. The equations controlling the model are as follows:

iiiii EQPWW ???? ?1 (1)

max

1

W

WEE i

wi??? (2)

ii

ssi PW

WKQ ??? ?

max

1 (3)

1??? iggi WKQ (4)

gisii QQQ ?? (5)

Csi

Bii QPAS ??? (6)

Where Wi, Wi-1 are soil moisture in this period and the previous interval respectively, Pi, Ei and Qi are monthly precipitation, actual basin evaporation and calculated discharge, Qsi, Qgi are surface flow and ground flow, Ew is potential evaporation and usually measured by a E601 type evaporator, Si is sediment amount; Wmax, Ks, Kg, A, B and C are parameters.

Monthly mean basin precipitation and potential evaporation are input variables. Nash efficiency coefficient R2, and average relative error Re were chosen as objective functions to calibrate the model parameters. The best simulation result will have values for R2 close to 1 and Re close to 0. The calculation formulae are as follows:

? ?

? ?R

q q

q q

ri cii

n

ri rii

n2

2

1

2

1

1? ??

?

?

?

?

? (7)

Figure 1. Sketch map of Weihe river basin

Huaxian

R

q q

qe

ci rii

n

rii

n?

??

?

?

?

( )1

1

(8)

Where qri and qci are recorded and simulated

values respectively, and qri is the average value

recorded and n is the sample number. Soil moisture is an intermediate variable to

describe the state of the basin: it is closely related to the two flow components and the actual calculated evaporation. To run the model, an initial value for the intermediate variable must be taken and then the two flow components, actual evaporation, and root soil moisture calculated for the next period according to water conservation principles. Usually, initial soil moisture is taken to be half of Wmax. To mitigate the effect of such assumptions and to validate the model, the first two years of the data series is usually taken as a lead-in period, and the last 3~5 years data are used to validate the model. Only data from the middle of the series is used to calibrate model parameters. If R2 and Re in the calibration and validation periods can meet the required standards, the model is acceptable.

2.2 Natural run-off simulation

Before 1970, the Weihe river basin can be treated ��

��

��

�3 Causes of variation

��

�

Table 1. Parameters and simulation results from three regions of the Weihe river basin

Parameter Runoff simulation Sediment simulation Gauging station

Wmax Ks Kg A B C Re R12 R2

2 Re R12 R2

2

Xianyang 182 0.32 0.009 6.89 0.251 1.991 1.8 84.3 81.0 -4.9 73.8 75.6

Zhangjiashan 170 0.105 0.003 6.93 0.327 2.173 -1.0 75.6 80.3 -2.7 75.2 70.5

Huaxian 178 0.21 0.009 6.84 0.279 2.091 0.5 84.2 82.7 -3.8 79.1 72.3

Note: R12 and R2

2 are efficiency coefficients in the calibration and validation periods.

��

��

��

Table 2. The impact of climate change and human activities on runoff and sediment Caused by

climatic factors Caused by

human activities Region Item Time

Recorded value ⑵

Simulated value ⑶

Reduction ⑷=⑴-⑵ ⑸= ⑴

-⑶ ⑸ / ⑷ (%)

⑹= ⑷-⑸

⑹ /⑷ (%)

background ⑴ 57.9

1970～1979 36.7 49.4 21.2 8.5 40.1 12.7 59.9

1980～1989 47.2 54.1 10.7 3.8 35.5 6.9 64.5

Runoff

(10��m )

1990～1995 28.7 44.3 29.2 13.6 46.6 15.6 53.4

background ⑴ 17280

1970～1979 14023 14975 3257 2305 70.8 952 29.2

1980～1989 9003 15175 8277 2105 25.4 6172 74.6

Xianyang station

Sediment

( t�10 )

1990～1995 6067 12720 11213 4560 40.7 6653 59.3

background ⑴ 19.6

1970～1979 12.5 18 7.1 1.6 22.5 5.5 77.5

1980～1989 13.3 17.1 6.3 2.5 39.7 3.8 60.3

Runoff

(10��m )

1990～1995 11.6 16.2 8 3.4 42.5 4.6 57.5


1970～1979 24946 26757 2644 833 31.5 1811 68.5

1980～1989 17039 24703 10551 2887 27.4 7664 72.6

Zhang jiashan station Sediment

( t�10 )

1990～1994 19264 24084 8326 3506 42.1 4820 57.9

background ⑴ 90.9

1970～1979 59.4 78.7 31.5 12.2 38.7 19.3 61.3

1980～1989 79.2 87.8 11.7 3.1 26.5 8.6 73.5

1990～1995 50.5 73.2 40.4 17.7 43.8 22.7 56.2

Runoff (��10 m )

1970～1995 65.0 80.1 25.9 10.8 41.7 15.1 58.3


1970～1979 38397 40165 4873 3105 63.7 1768 36.3

1980～1989 27572 38549 15698 4721 30.1 10977 69.9

1990～1995 29436 35014 13834 8256 59.7 5578 40.3

Huaxian station

Sediment

( t�10 )

1970～1995 32166 38355 11104 4915 44.3 6189 55.7

Analysis indicates that this is mainly due to the

abundance of water in the area above Xianyang station, but that more sediment comes from the district above Zhangjiashan station. During the overall period from 1970~1995, annual runoff and sediment in the Weihe river basin has decreased ��8 �3��8 ��

�4 Conclusions

��

��

��

measures on flood and sediment should be researched in further detail.

References Wang Guoqing, Li Jian, Wang Yunzhang, 2000.

Monthly-distributed hydrological model and its application in Yellow River, Advances in Water

Science. 11( supplement). Zhang Shengli, 1994. Calculation methods for water

and sediment reduction benefit of soil and water conservation, Beijing: China Environment Scientific Press.

Zhao Runjun. 1984. Watershed hydrologic simulation. Beijing: Water Conservancy and Electricity Press.

1

Eco-environmental water demands and utilization limit for sustainable use of water resources of Northwest China

Yu Wang 1，2

1. Survey, Design and Research Institute of Yellow River, Zhengzhou, Henan, 450003,China. 2. Xian University of Technology，Xi��

Abstract Eco-environmental water demands are defined for the northwest regions in China and its minimum levels are analyzed. The utilization limits for sustainable use of water resources through human activity are determined on the basis of satisfying eco-environmental needs first. This study is of great importance for the water resources exploration, eco-environment protection and sustainable development of society for the northwest regions of China. Key words: northwest of China; water resources; carrying capacity; eco-environmental water

demand. E-mail: [email protected] 1 Introduction

The northwest regions of China are defined herewith as the vast land belonging to the inland river basins, international river basins and the yellow river basin in the northwest of china, covering from the borderline in Pamirs in the west to Yellow River main stem in the east, from the borderline with Mongolia in the north to the watershed of Yangtze Rive in the south. The total area reaches 3.12 million km2, accounting for 33% of China, covers the whole of Xinjiang, Qinhai, Gansu, Ningxia and Shanxi provinces and part of Inner Mongolia.

The northwest regions of China are characteristic of indigence of water resources and frangibility of eco-environment. As the northwest regions locate in the heart of inland with arid weather and exiguity of precipitation, the precipitation in most areas is not more than 400 mm annually, while the evaporation capacity is more than 2000 mm annually. The annual average runoff is only 47 mm, accounting for only 16.5% of national average. While part of the water resources existing in the remote and deserted area is almost impossible to utilize, the water resources available for oasis are very limited. Due to the arid weather, the eco-environment in the area relies greatly on the water and is very water-sensitive. Generally speaking, in the northwest regions, water is the essential factor of the sustainable development of society and eco-environment.

Since the last decade, with increase of economy and extension of population, the limited water resources is overused by human activities in some regions, which leads to destroying of

eco-environment, such as dry-off of rivers and lakes, dying out of forests, hungriness salinization and alkalinization of agricultural lands, etc. This paper presents the eco-environmental water demand and utilization limit of sustainable use of water resources. This study is of great importance for the water resources exploration, eco-environment protection and sustainable development of society for the northwest regions of China. 2 Eco-environmental water demand

The eco-environmental water demand varies on river basins and depends on various local conditions. Lots of studies have been accomplished on the Yellow River Basin; however only the soil conservation water-use in the middle reaches belonging to the northwest regions is concerned in this paper. The eco-environmental water demands of the inland river basins consisting of Xinjiang, Hexi inland river basins, Chaidamu basin, Qinhai Lake areas are mainly concentrated.

2.1 Definition

The eco-environment in this paper is defined herewith as the rivers, lakes and vegetation, and consists of artificial eco-environment and natural eco-environment. The artificial eco-environment is generated by the human activities, e.g. irrigation land, pasturage and economic plantings and etc; however, the natural eco-environment is formed by natural precipitation and underground water, e.g. lowland meadow, desert planting, riverbank forest, natural lakes, and etc. The eco-environmental water demand in this paper is

2

defined as the water necessary to maintain the definite eco-environment protection objectives of natural eco-environment.

2.2 Eco-environmental protection objectives and its water demands

(a) Xinjiang. The natural eco-environment, consisting of lowland meadow, desert planting, riverbank and river-valley forests, natural lakes, mountainous vegetation, utilize the precipitation and underground water to reserve. Each kind of water demand is estimated separately.

The water demand of river channel: with consideration of the importance and the difficulties, only the eco-environmental water demand of Talimu River channel is concerned, which basic eco-environment protection objective is to avoid dry-off in the river channel above Daxihazi and to transfer water to Alaer as possible. The water consumption in the Talimu river channel includes evaporation, diversion and infiltration. The evaporation capacity for the up-, middle- and lower-reaches of Talimu River channel are measured to be 1116 mm, 1190 mm and 1264 mm separately. After considering the water surface area, the evaporations for the up-, middle- and lower-reaches are 0.084 billion m3, 0.057 billion m3 and 0.009 billion m3, totally 0.15 billion m3. In the year of 2010 and 2020, the water demand remains as that in current year.

The water demand of lakes: the water demand of Bositeng lake, Wulungu lake and Aibi lake are considered. In the current year, the water demands are estimated as 1.4 billion m3, 0.84 billion m3 and 0.5 billion m3 separately (totally 2.74 billion m3) to reserve the current water levers. In the year of 2010 and 2020, as to rise the water levels of Aibi lake to the level in 1970s, the water demand of Aibi lake is raised to 0.7 billion m3, the total water demand of the lakes reaches 2.94 billion m3.

The water demand of natural vegetation: the water demand of the remote riverbank and river-valley forests, shrub and etc. is estimated to be 2.78 billion m3 in the current year, and remains the same in the year of 2010 and 2020. The water demand of lowland meadow is 15.14 billion m3 in current and year of 2010 and 2020.

By summation of the above results, the total eco-environmental water demands of Xinjiang are 20.8 billion m3, 21.0 billion m3 and 21.0 billion m3 in year of current, 2010 and 2020 separately.

(b) Hexi Inland river basins. The occurring eco-environmental problems nowadays in Hexi inland river basins include disertation of land, degeneration of meadow, salinization of soil, soil and water loss, pollution of partial river segments and towns, destroy of biology diversity. In this study, only the water demands of natural vegetation, including remote desert riverbank, river-valley forests and lowland meadow locating

on the riverbank or near lakes and fountains and surviving on groundwater and surface water, are studied, other water demands are not concerned yet. Calculating by the vegetation area and its evaporation intensity, the water demands are 1.187 billion m3, 1.617 billion m3, and 1.619 billion m3 separately in year of current, 2010 and 2020.

(c) Chaidamu basin. The frangibility of eco-environment is determined by the specific weather and geological conditions of Chaidamu basin. The local remote desert eco-environment nowadays is facing disturbing and being destroyed. The major eco-environment problems nowadays are observed as the reducing of natural arbor and frutex, degeneration of meadow, desertification of land, decreasing of water sources, atrophy of rivers and lakes, environmental pollution of cities and towns, among them the desertification of land is the most essential problem. The natural arbor and frutex, always allocating in the mountainous areas, is remained by the natural rainfall and groundwater. Its water use is already concerned in the determination of the natural runoff measured at the mountain mouth. Thus only the water demand of rivers and lakes is concerned with the estimate of 2.007 billion m3 in the year of current, 2010 and 2020.

(d) Qinghai Lake areas. The actual observed data shows the lake water level is decreasing with a wave-like variation in the past hundred years, for instance of the past 30 years, from 3196.55 m in 1959 drop to 3193.59 m in 1988, 2.96 m down in total and 10.2 cm in annual average. As the present local water consumption by irrigation and life is estimated only 0.1 billion m3, it shows the human activity around the lake is not the prominent factor, and however, the change of weather condition is the dominant factor for the variation of lake water level. The atrophy of lake water area intensifies the desertification and desertness of the lake area and affects the habitat of birds and multiplying of plant community as a result, therefore, water demand of Qinghai Lake must be considered in the water resources planning and local economy development. As the decreasing of lake water level is a long-term natural process and water transfer from other basin is not considered before 2020, hence water demand of Qinghai Lake area is not considered in this study.

Besides the above eco-environmental water demand of the inland river basins and international river basins, the soil conservation water use in the middle reaches of YRB, which belongs to the northwest regions as well, is studied to be 1.0, 2.0 and 2.5 billion m3 for the year of current, 2010 and 2020 year. Thus, the eco-environmental water demand of the northwest regions for year of current, 2010 and 2020 of the

3

northwest regions are estimated to be 25.0 billion m3, 26.63 billion m3 and 27.13 billion m3 separately. 3 Utilization limit of sustainable use of water resources

The northwest regions are the most arid area in China. Its total amount of natural water resources reaches 156.3 billion m3, in which surface water accounts for 142.8 billion m3, the ground water accounts for 9.7 billion m3 and the overlap of them is 85.2 billion m3. The average natural runoff depth 47mm accounts for only 16.5% of the national average. Despite of the large amount of water resources, its area average is rather low comparatively.

The utilization limit concept herewith is defined as the water resources available for utilization of human activities and eco-environment, which is evaluated in different way for Yellow River basin, the inland basins and the international river basins. Firstly for the yellow river basin, with accordance to the water allocation plan approved in 1987 by the central government, the utilization limit of surface water is determined, the utilization limit of ground water is determined to be natural replenishment of ground water, thus the total utilization limit of Yellow River basin accounts for 17.173 billion m3. Secondly for the inland river basins, the unusable amount in the deserts and other desolate areas must be deducted. Thirdly for the international river basins in Xinjiang, the international water

allocation treaty is to obey and to apply to determine the utilization limit. As evaluated in the above methods, the total of utilization limit of the northwest regions of China accounts for 107.1 billion m3, 69% of the total water resources of 156.3 billion m3. It must be mentioned that this utilization limit is rather than the amount of delivery or water available; however, it is the limit of water resources for development and utilization. Due to necessity, difficulty, economic feasibility and invest, the actual utilization will be less than the limit.

After the utilization limit is determined, its allocation between human activity and eco-environment must be studied as well. In the arid northwest regions of China, the natural water resources are the most decisive factor to maintain the eco-environment and human activity as well. It is realized by the history of water resources development that the water demand by the eco-environment in the arid regions ought to be satisfied at the first priority, otherwise the degeneration and damages of the local eco-environment will inevitable destroy the whole environment at the end. Based on the above thoughts, the utilization limit is determined under the condition that the water demand of eco-environment is met firstly. As analyzed, the water demands of natural eco-environment are estimated to be 25.0~27.1 billion m3 for 2000 and 2020, therefore, the utilization limit for artificial eco-environment and human activity is estimated to be 80~82 billion m3.

Table 1. The utilization limit and the eco-environmental water demand of the Northwest Regions (billion m3)

Eco-environmental water demand

Utilization limit for artificial eco-environment and human

activities Regions Utilization

limit Current 2010 2020 Current 2010 2020

Total 107.09 25.00 26.63 27.13 82.09 80.46 79.96 Yellow River Basin 17.17 1.00 2.00 2.50 16.17 14.67 14.67

Xinjiang 75.82 20.81 21.01 21.01 55.01 54.81 54.81 Chaidamu Basin 4.61 2.01 2.01 2.01 2.60 2.60 2.60 Qinhai Lake Area 2.42 0.00 0.00 0.00 2.42 2.42 2.42

Hexi Inland River Basin 7.07 1.19 1.62 1.62 5.89 5.46 5.46

4 Summaries

The eco-environmental water demands of Xinjiang, Hexi inland river basins, Chaidamu basin and Qinghai Lake area are studied separately, the total eco-environmental water demand is estimated to be 25.0 billion m3, 27.1 billion m3 and 27.1 billion m3 for year of current, 2010 and 2020. The utilization limits for sustainable use of water resources is 107.1 billion m3, in which the utilization limit for artificial eco-environment and human activity is estimated to be 80~82 billion m3.

Reference Wang Xiqin, Liu Changmin, Yang Zhifeng, 2002,

Research advance in ecological water demand and environmental water demand [J], advances in water resources, 13(4), 507-514.

Zhang Xinhai, Yang Libin, Wang Yu, 2002, Preliminary analysis on water requirement of ecological environment in the inland river ��

1

Model to optimize rainwater-harvesting system for irrigation

Xinyan Zhang and Huanjie Cai

Northwest Sci-Tech University of Agriculture and Forestry, Yangling, 712100,China. Abstract Rainwater-harvesting systems for irrigation have been studied from technical and economic points of view to optimize a system. Rainwater-collecting, storing, and using subsystems are considered separately. Four physical and ecological sub-models were used, namely a model of rainfall, an estimating model for amount of harvested rainwater, a model to optimize the distribution of irrigation water and a model to optimize the design of water-storing facilities. The hilly region of Liquan County was chosen for the case study for rainwater harvesting and use for the irrigation of wheat and corn. The model was developed on the basis of reliable theories and methods, being adaptable and practicable.

Key words: Rainwater-harvesting; irrigation; system optimization; model.

E-mail: [email protected] 1 Introduction

Water shortage is the key factor limiting the development of agricultural production and rural economy in arid and semi-arid regions. In most arid and semi-arid regions, natural rainfall is an important water resource due to limited surface runoff, and shortage of underground water. But in these regions the rainfall is low and mainly concentrates in several months of the year so water shortage occurs during crop growth. The model for the rainwater-harvesting system for irrigation rarely under study at home and abroad, and the cases reported were mainly conducted in accordance with the features of specified regions, the achievements of which do not have wide adaptability[1-3]. We optimized the design of the rainwater-harvesting system for irrigation of field crops according to different rainwater-collecting surfaces. 2 Design simulation and optimizing

model 2.1 Basic principles

Irrigation with harvested rainwater is the process in which rainfall and runoff, occurring in the specifically treated locations, is collected and stored, then used for irrigation. In specified regions, the rainfall and the total area of rainwater-collection and irrigation do not vary much, but the rainwater-collecting and irrigation areas affect the input and output. The arrangement of rainwater-storing facilities and final benefits of the system are also affected. Output depends upon the irrigation area and the yield per unit area. A larger rainwater-collecting area leads to reduction of the irrigation area, but it is favorable to increase the yield per unit of the irrigation area. While, a smaller rainwater-collecting area leads to an

increased irrigation area and reduced yield per unit of irrigated land. So the key issues are determining the proportions of rainwater-collecting area to irrigated area and optimal rainwater-storing facilities and associated irrigation system.

2.2 Techniques and economic parameters 2.2.1 Technical conditions

A balance of harvested water and water consumption is required.

CA�Rf ��CM�Ir �� CA �� Rf� ��

�� CM ��Ir��

�� WT��P� �� I�� CA�� Ec�� V�� WT-1

�� EO� �� Sr� �� WI ��

WT ��f��P��I��CA��EC��V��WT-1��EO��Sr��WI��2.2.2 Economic parameters

��

2

3.1 System model design

Rainfall data is the basic input to optimize the system as a whole. Data on annual, monthly and daily rainfalls for specified rainfall frequency can be achieved by statistical analysis of data accumulated over many years. The amount of harvested rainwater is determined through analysis of its various affecting factors according to rainfall data and the water balance principle. With limited irrigation, the effects of shortages are predicted using crop water-production function based on water balance calculations and a model to optimize distribution of irrigation water is set up using double-layer dynamic programming[4]. The first level of the model optimizes the irrigation system for individual crops using dynamic programming of balance of the soil water balance and the crop production function. A second level optimizes the multi-crop distribution of irrigation water, based on the water balance and water production function during full growing period. The overall model includes four sub-models and its operational chart is shown in Figure 1.The ideal combination of number, capacity and storing frequency of storage facilities for given retained water is determined through optimization. Using models developed for rainwater harvesting and decision-making in irrigation, the balance of water retained in storing facilities and control principles for retained water help optimize water-storing facilities.

3.2 System model use

Basic parameters include essential costs and service life of various facilities, costs of human labor attributed to the maintenance, management and operation. Costs of one-off inputs to the system should be averagely over the service life. In Equation 1, ratio of actual yield to potential yield is used in a model to work out optimal plans for irrigation area based on maximum production values for different amounts of collection water. Production values are calculated with and without irrigation as well as the production value per unit �� 4 Typical system analysis 4.1 Overview

��

Basic meteorological data

Rainfall analysis

Water production

function of crops

Balance of

soil water

Estimating model

for amount of

harvested water

Model to optimize irrigation system of individual crops

Balance of water retained in water-storing facilities

Model to optimize multi-crops distribution of irrigation water

Model to optimize design of water-storing facilities

Economic model to optimize rainwater-harvesting system for irrigation

Figure 1 Operational chart for simulation and optimization of rainwater-harvesting system for irrigation

3

continental monsoon climate. Annual rainfall is 573 mm, mainly distributed between June and September. Rainfall between June and September accounts for 65% and is mainly rainstorms. Northern Liquan County belongs to the hilly and gullied area of the loess plateau and mainly relies on agriculture. Average annual income is less than 300 Yuan (RMB) per capita with annual per capita water supplies of about 43 m3 on average. Available land for irrigation only covers 0.74% of the total land area so the major land use type is dryland farming.

4.2 System-optimizing design

There are two basic assumptions. Firstly, irrigation area per underground water-storing cellar should be 0.33 ha based on financial return, convenience,ease of management and irrigation operation. Secondly local experience suggests that capacity of underground water-storing cellars should be 100 m3.

Let ?T represent cost of rainwater collection. Costs, service life and operational costs differ for the different rainwater collecting locations surfaced with different materials (Table 1). In practice, the rainwater-collecting cost is negligible with sloping lands being used as rainwater-collection locations.

Let ? T represent cost attributed to water storage. Costs depend on surface areas of corresponding components. 《 The technical standards for rainwater-collecting facilities of Gansu province》was adopted to describe cellars plastered with cement mortar. Storage facilities are comprised of a major and auxiliary body. From the Chinese national budget standards for engineering, total cost of the major body depends on cellar capacity V, so ? T ��V＋��

�� f T� �� T ��

�� Y��Ya� － Ya��Pr�� Y� �� Ya� represents irrigated yield calculated with the model to optimize distribution of

irrigation water. Then Ya�� =Ym�F; where Ym represents potential yield and F is ratio of actual to potential yield; Ya represents yield without irrigation and Pr stands for crop price.

Then�� = MAX�Y－(?T＋? T＋f T)�� (5)

��Table 2 shows that for given materials used to

surface rainwater-collection facilities, the net returns differ for different amounts of water collected. As collected water increases the net return initially increases and then declines. Amounts collected water corresponding to maximum net returns are the optimal for the water-collecting location in question.

Table 3 gives net returns and detailed technical specifications of materials used to surface water-collecting locations for optimal amounts of collected water. So construction type can be chosen accordingly. Surfaced with machine-made �tiles results in the highest net return followed by cement tile, concrete, small blue baked tile, cement earth, rammed earth, film and sand mulching and

Table 1. Costs and efficiencies of rainwater-collection locations surfaced with different materials

Materials used to surface

rainwater-collecting locations

Rainwater -collecting efficiencies

Construction costs

(Yuan/m2)

Service life (a)

% of operational cost in total construction cost

(%)

Construction costs + operational costs

(Yuan, RMB)

Machine-made tile 0.90 3.98 25 2 5.97

Cement tile 0.90 4.96 25 2 7.44

Concrete 0.95 4.82 20 3 7.71

Small blue baked tile 0.75 3.00 20 3 4.80

Cement earth 0.85 3.64 15 4 5.82

Rammed earth 0.65 0.25 4 20 0.45

Film and sand mulching

0.80 1.94 10 8 3.49

Natural slope lands 0.40 - - - -

Notes: Calculated according to the research paper by Zhang Guanghui and Chen Zhihan[5] (1997).

4

natural slope lands. Table 2. Net returns of systems for different amounts of collected irrigation water (m3)

Net returns (Yuan/ha) for different amounts of collected-irrigation water Materials used to surface rainwater-collecting

locations 10 20 30 40 50 60 70 80 90 100

Machine-made tile 2168 2351 2598 2867 3125 3320 3437 3473 3467 3445

Cement tile 2146 2308 2536 2787 3029 3208 3311 3332 3314 3280

Concrete 2135 2287 2507 2752 2988 3162 3260 3277 3252 3213

Small blue baked tile 2095 2208 2387 2590 2784 2918 2981 2967 2917 2855

Cement earth 2087 2194 2370 2572 2766 2901 2964 2948 2894 2828

Rammed earth 2094 2205 2380 2576 2762 2888 2945 2928 2877 2815

Film and sand mulching 2076 2172 2337 2528 2712 2836 2889 2865 2806 2734

Natural slope lands 1924 1884 1918 1981 2041 2056 2019 1927 1815 1702 �

The optimal material surfacing material can be

used to further optimize each sub-system. For the rainwater-collecting subsystem, if collecting locations are surfaced with machine made tiles, collecting efficiency, annual collected water and rainwater-collecting area per irrigated ha become 90%, 343.9 mm and 0.31 ha, respectively. For the rainwater-storing sub-system, if cellars are plastered with cement mortar, the capacity per cellar, irrigation area per cellar and water-storing frequency are 100 m3, 0.0953 ha and 1.26, respectively. For the rainwater-use sub-system, if trickle irrigation is adopted, the optimal supply of water is 1200 m3/ha. Annual net production value, the average annual cost and the average annual net return of the rainwater-harvesting system are RMB 5440 Yuan/ha, RMB 1967 Yuan/ha and RMB 3473 Yuan/ha, respectively References Chen Zhihan, Ran Dachuan and Yan Xiaoling.

1998. Optimized techniques to harvest and store the runoff in the mountain slope lands of the Loess Plateau. (in Chinese). Research on water and soil conservatory, 1998, (12): 23-28.

Guan Hua. 1998. Study of the design of the rainwater-collecting system for agricultural irrigation in the mountain lands of Western Henan province. (in Chinese). Resource science, 1998, (5):26-31.

Liu Zhaowei. 1997. Methods to optimize the irrigation-drainage system (in Chinese). Beijing: China water resource and electricity press, pp1-26.

Sushil and Pandel. 1991. The economy of water harvesting and supplemental irrigation in the semi-arid tropical of India. Agricultural Systems. 36(2):61-70

Zhang Guanghui and Chen Zhihan. 1997. Types and benefits of the cellars used for rainwater collecting.[in Chinese]. Report of water and soil conservatory, 17(6):57-61.

Table 3. Optimal amounts of collected irrigation water

Materials used to surface

rainwater-collecting locations

Amounts of collection -irrigation water (m3)

Ratio of water-collecting

area to irrigation area

Total net production

value (yuan/ha)

Capacity per cellar

(m3)

Irrigation area

per cellar (ha)

Annual system

cost (yuan/ha)

Net returns (yuan/ha)

Machine-made tile 80 0.31 5440 100 0.0953 1967 3473

Cement tile 80 0.31 5440 100 0.0953 2108 3332

Concrete 80 0.30 5575 100 0.0953 2298 3277

Small blue baked tile 70 0.33 4846 100 0.1093 1865 2981

Cement earth 70 0.29 5146 100 0.1093 2184 2963

Rammed earth 70 0.38 4478 100 0.1093 1533 2945

Film and sand mulching 70 0.31 5003 100 0.1093 2114 2889

Natural slope lands 60 0.53 3064 100 0.1273 1008 2056

Analysis and strategic measures on the drought problems in Songnen Plain

Hailin Yu

Nenjiang Agricultural Science Institute, Heilongjiang Academy of Agriculture Sciences, Qiqhar ，Heilongjiang, 161041, China.

Abstract The developing tendency, the damaging extent, the occurring reason and the capability of drought-relief have been understood and analyzed on Songnen plain strategically. The drought-relief was divided into two links scientifically, they are the preventing dry in region and the resisting dry in part. Moreover, the drought-relief measure was provided, which was strategic, prescient, guiding and regional control, strengthening the research and the demonstration of new technology for drought resistant.

Key words: Songnen plain; dry problem; strategic measures. E-mail: [email protected]

Songnen plain is low plain by alluviation and

deposit in modern times, it is situated in the eastern part of the Daxinanling Mountain, the southern part of the Xiaoxinanling Mountain and the northern part of watershed between the Changbaishan Mountain and Songliao. The elevation is from 120 to 220 maters. It stretched over Heilongjiang, Jilin provinces and Inner Mongolia Autonomous Region, the area is 200 thousand square kilometers. ��

��

1 Getting a clear understanding of developing tendency of dry damage

�� th�� th�� st��

�� 2 Endangering range by dry damage

��

was high, the dry damage has been happened in western part consecutively except 1998. The endangering range of dry damage is expanding to the middle, northern and eastern parts of the main producing area of grain, so that the Sanjiang Plain with liable to water-logging happened dry damage consecutively. In 2000, the area of dry damage was 3368 thousand hm2, which made up 37% of the cultivated area. Among of them, seriously disaster area reached to 2035 thousand hm2, which direct economic loss surpassed 6 billions yuan, invested cost for drought-resistant was 0.456 billions yuan. In 2001, the area of dry damage was 5007 thousand hm2, which made up 55% of the cultivated area. Among of them, seriously disaster area reached to 2348 thousand hm2, the lacking water area of paddy field was 4580 thousand hm2, the population of lacking water was 4580 thousand people, which direct economic loss was 10 billions yuan, invested cost for drought-resistant was 0.515 billions yuan. In Qiqihar region in 2000, the area of dry damage was 1553 thousand hm2, which made up 91.7% of the cultivated area. Among of them, seriously disaster area reached to 1166 thousand hm2, the area that not yield was 132 thousand hm2, the lacking water area of paddy field was 90 thousand hm2, the yield reduced 2 billion kilograms, which direct economic loss was 2.42

billions yuan. In 2001, the area of dry damage was 1548 thousand hm2, which made up 91% of the cultivated area. The area that not yield was 782 thousand hm2, the lacking water area of paddy field was 96 thousand hm2, the population of lacking water was 3110 thousand people, it made up 89% of total population in the countryside, which direct economic loss was 4 billions yuan.

3 Reason of happening dry damage

It is the most important reason to destroy the ecological environment by mankind. For example, in 1949, there are 6529 thousand hm2 of grassland in the western part of Heilongjiang and Jilin provinces, as bringing under cultivation, so far there are only 3262 thousand hm2 of grassland area, which reduced 50.1%. According to the statistic, the cultivated area increased from 4020 to 567 thousand hm2, but the forest area, the grassland area and the wet land area have reduced from 4070 to 315 thousand hm2 within 20 (from 1960s to 1980s) years, these areas reduced 23%. The soil erosion area reached to 1990 thousand hm2. Up to 2000, the cultivated area increased to 9104 thousand hm2, and the grassland area reduced to 1867 thousand hm2.

Table 1. Grassland area in Songnen Plain (Unit: thousand hm2)

Explanation of Picture from Satellite Statistics Regions Grassland Area Unused Soil Area Grassland Area Unused Soil Area

The western of Heilongjiang 1438.3 559.7 1867.0 1480.0

The western of Jilin 729.0 704.9 1395.0 1177.0

The western of Songnen Plain 2169.3 1264.6 3262.0 2657.0

As bringing under cultivation, making the grassland become alkali, desert and degenerate seriously. The ecological environment has been destroyed with cutting trees down. The resisting power to natural calamity is descending constantly. So the dry damage will be serious year by year.

4 Capability of resisting dry damage

The resources of Songnen Plain are limited. From the situation of Heilongjiang province, the total water resource has only 77.22 billions m3, which makes up 2.8% of whole country, among of them, every person has 2058 m3 of water, it is �� 3��3��3�� 3��3��

�� 3�� 3� �� 3��

��

�5 Strategic measures of drought-resistant 5.1 Understanding the relation of the preventing dry in region and the resisting dry in part ��

maximally reduce damage of drought with applying ecology, systems analysis, technical economy principle, biological, engineering and agronomic measures, this way is long-term, strategic and initiative. The later is to relax dry spell and maximally reduce the loss with applying technical economy principle and irrigating effectively, this one is short-term, passive and adaptable. From the actual situation, preventing dry in region is a main and effective measure, resisting dry in part is an assistant method. Organically combining the both measures is the crux. Only by this key can it increase the synthetic capability of drought-resistant.

5.2 Scientifically planning and actively applying strategic measures

According to natural ecology, distribution of water resources and conservancy facilities, Scientifically planning and Actively applying strategic measures for preventing dry. Increasing the capability of drought-resistant.

5.2.1Improving the ecological environment thoroughly

Well ecological environment can adjust and improve climate conditions, which can reduce wind speed, increase air humidity and decrease evaporation, control soil erosion, prevent wind, enhance land utilization rate and reduce loss. The Baiquan county has an experience, applying the land scientifically, setting up some different ecological models with local conditions. So they have improved ecological environment thoroughly.

5.2.2 Setting up large water conservancy facilities

In He��

��

�5.2.3 Improving soil and increasing fertility

��

�5.3 Strengthening the research and the demonstration

of new technology for drought-resistant ��

��

��

w ater-saving agriculture and sustainable use of water and...

Documents