an on farm comparison of conservation agriculture ...€¦ · 2.2 conservation agriculture ......

Wrem MSc Thesis Clever Taurayi Dhliwayo June 2006

AN ON FARM COMPARISON OF CONSERVATION AGRICULTURE PRACTICES AND CONVENTIONAL FARMER PRACTICES ON SOIL HYDROLOGY AND

MAIZE YIELD

By

CLEVER TAURAYI DHLIWAYO

A dissertation submitted in partial fulfillment of the requirements for the degree of Master of Science in Water Resources Engineering and

Management

Department of Civil Engineering Faculty of Engineering

University of Zimbabwe June 2006

Wrem Msc Thesis Clever Taurayi Dhliwayo June 2006

iWrem MSc Thesis Clever Taurayi Dhliwayo June 2006

ABSTRACT

The negative impacts of mid season dry spells on the productivity of rain fed cropping in the smallholder sector of southern Africa is well documented. One way of mitigating these impacts is the promotion of conservation agriculture to enhance infiltration and soil water retention. This on farm study was carried out in ward 1 of Insiza District, Zimbabwe. A short season maize (Zea Mays L.) variety SC403 was grown under three tillage practices (farmer practice, planting basins and clean ripping), on two soil types: sandy silt loam soil (Soil A) and clay loam soil (Soil B). Cumulative infiltration, soil moisture retention and grain yield were determined for each treatment under the same climatic conditions. Seasonal rainfall during the season was 490 mm in Field A and 513 mm in Field B. For both soil types, cumulative infiltration was highest in planting pits and lowest in clean ripping. Soil A had the highest cumulative infiltration compared to Soil B, yet soil B retained the most moisture. Planting pits showed the highest moisture retention capacity in both soil types. However, clean ripping retained more moisture than farmer practice in soil A and less for soil B. Statistically, there was no significant difference in either the cumulative infiltration and the soil moisture retention in the three tillage practices for the same soil type. In the sandy silt loams, yields of 1648 kg ha-1, 1815 kg ha-1, 700 kg ha-1 for farmer practice, planting pits and clean ripping respectively, were observed. For clay loam the yield was 663 kg ha-1, 798 kg ha-1, 525 kg ha-1 for farmer practice, planting pits and clean ripping, respectively. There was no significant difference in the yields obtained in the three tillage practices for the same soil type but there was a significant difference in yield between the two soil types. Crops in sandy silt loams had higher yields. It was concluded that, planting pits enhance infiltration and produce the highest yields in both soil types and that the lack of statistical differences could be attributed to the above normal rainfall received and that only one season was observed. It was recommended that farmers adopt planting pits as a conservation agriculture technique and that additional weeding operations be carried out in the clean ripping practice in the first year as weeds outgrow the maize crop. Keywords: Conservation agriculture, infiltration rate, soil moisture, grain yield.


iiWrem MSc Thesis Clever Taurayi Dhliwayo June 2006

ACKNOWLEDGEMENTS

I would like to acknowledge the Department of Civil Engineering for offering me a place to

carry out my studies at the highest institute of learning in the country. In particular I am most

thankful to the wise guidance and supervision of this work by Eng H. Makurira of the

Department of Civil Engineering and Mr. D Love of Waternet.

The field work carried out in this research would not have been successful had it not been for

the measuring equipment supplied by ICRISAT. The expert advice availed by Dr. S. Twomlow

and Mr. W Mupangwa is greatly appreciated especially in the setting up of the field work.

The administration and staff of Tshazi Secondary School is acknowledged for offering

accommodation during the course of my field work. In particular I would like to thank the

School Head, Mrs. Ncube for her motherly concern to my welfare during my stay at Tshazi.

Finally I would like to express my sincere gratitude to my wife Kudzai for being there for me

all the way to the completion of this work. Your support both morally, financially and

spiritually was most welcome. I would like to thank my parents for the encouragement and the

faith they had in my ability, my son Tinashe, the sight of you spurred me on. You endured my

long absence. This work is dedicated to all of you.


iiiWrem MSc Thesis Clever Taurayi Dhliwayo June 2006

DECLARATION I, Clever Taurayi Dhliwayo, declare to the Senate of the University of Zimbabwe that this thesis is my original work and all other sources of material used are duly acknowledged. This work has not been submitted to any other university for any academic award. Name …………………………………………….. Signature…………………………. Clever. T. Dhliwayo University of Zimbabwe Department of Civil Engineering Zimbabwe

This research was funded by the Challenge Programme and the output is part of a large scale study of the Mzingwane catchment. Data analysis and interpretation of results in this thesis was done purely by the author.


ivWrem MSc Thesis Clever Taurayi Dhliwayo June 2006

TABLE OF CONTENTS ABSTRACT ………………………………………………………………………….…i ACKNOWLEDGEMENTS ……………………………………………………………iii TABLE OF CONTENTS………………………………………………………………iv LIST OF SYMBOLS AND ABBREVIATIONS………………………………….…..vi LIST OF TABLES………………………………………………………………..…...viii LIST OF FIGURES ……………………………………………………………………ix

CHAPTER 1: INTRODUCTION ..........................................................1

1.1 Food production in arid and semi arid countries ..................................... 1 1.2 Objectives ................................................................................................ 4

1.2.1 General Objective ............................................................................................. 4 1.2.2 Specific Objectives ........................................................................................... 4 1.2.3 Research hypothesis.......................................................................................... 4

CHAPTER 2: LITERATURE REVIEW ................................................. 6 2.1 Meteorological and Agricultural droughts .............................................. 6 2.2 Conservation agriculture.......................................................................... 8

2.2.1 No till tied ridging ............................................................................................. 9 2.2.2 Mulch ripping.................................................................................................... 9 2.3 Rainwater harvesting ......................................................................................... 10 2.3.1. Natural runoff................................................................................................. 11 2.3.2 Collected and Diverted Runoff ....................................................................... 11 2.3.3. Inundation methods ........................................................................................ 11 2.3.4 Flood Diversion .............................................................................................. 12

2.4 Constraints to adoption of conservation tillage ..................................... 12 2.4.1. Low Degree of Mechanization....................................................................... 12 2.4.2 Weed Control .................................................................................................. 14

2.5 The effects of crusting ........................................................................................... 15 2.6 Infiltration .............................................................................................. 16

2.6.1 Infiltration capacity of a soil ........................................................................... 16 2.6.2 Factors affecting infiltration rate .................................................................... 16 2.6.3 Measurement of Infiltration ............................................................................ 19 2.6.4 Tension infiltrometer versus double ring infiltrometer................................... 20 2.6.5 Tension infiltrometer theory ........................................................................... 21

2.7 Soil moisture measurements ................................................................................... 22 2.7.1 Theta Probes.................................................................................................... 24

2.8 Evaporation and Transpiration .............................................................. 24


vWrem MSc Thesis Clever Taurayi Dhliwayo June 2006

CHAPTER 3: STUDY AREA .............................................................. 26 3.1 Vegetation .............................................................................................. 28 3.2 Farming systems .................................................................................... 28

CHAPTER 4: METHODOLOGY ...................................................... 30 4.1 Treatments and experimental plot layout .............................................. 30 4.2 Crop establishment ................................................................................ 31 4.3 Fertilizer application .............................................................................. 32 4.4 Crop harvesting ...................................................................................... 32 4.5 Measurements ........................................................................................ 33

4.5.1 Rainfall............................................................................................................ 33 4.5.2 Infiltration ....................................................................................................... 34 4.5.3 Soil volumetric water content ......................................................................... 34 4.5.4 Water Partitioning ........................................................................................... 36 4.5.4.1 Evapotranspiration ....................................................................................... 38 4.5.4.2 Rainfall and other climatic data ................................................................... 38 4.5.4.3 Surface runoff and run on ............................................................................ 38 4.5.4.4 Deep drainage .............................................................................................. 39

CHAPTER 5: RESULTS .................................................................... 41

5.1 Rainfall ................................................................................................... 41 5.2 Infiltration .............................................................................................. 43 5.4 Evapotranspiration ............................................................................. 48 5.5 Change in storage................................................................................... 48 5.6 Runoff .................................................................................................... 50 5.7 Deep drainage ........................................................................................ 50 5.8 Yield ....................................................................................................... 51

CHAPTER 6: ANALYSIS AND DISCUSSION OF RESULTS ...... 52

6.1 Rainfall ................................................................................................... 52 6.2 Infiltration .............................................................................................. 53 6.3 Soil Moisture Content............................................................................ 56 6.4 Rainfall partitioning............................................................................... 59 6.5 Yield ....................................................................................................... 60 CHAPTER 7: CONCLUSIONS AND RECOMMENDATIONS ...... 62

CHAPTER 8 REFERENCES ............................................................... 64

CHAPTER 9 APPENDICES .................................................................68


viWrem MSc Thesis Clever Taurayi Dhliwayo June 2006

LIST OF SYMBOLS AND ABBREVIATIONS

AIDS Acquired immunodeficiency syndrome

AN Ammonium nitrate

ANOVA Analysis of variance

AREX Agricultural Research and Extension

CA Conservation agriculture

CR Clean ripping

CRA Clean ripping in Field A

CRB Clean ripping in Field B

D Deep drainage

DF Degrees of freedom

ET Evapotranspiration

FAO Food and Agriculture Organisation of the United Nations

FC Field capacity

FP Farmer practices

FPA Farmer practices in Field A

FPB Farmer practices in Field B

GDP Gross Domestic Product

ICRISAT International Crops Research Institute for the Semi Arid Tropics

NGO Non Governmental Organisation

PP Planting pits

PPA Planting pits in Field A

PPB Planting pits in Field B

PC Practical Solutions

R Rainfall

Roff Runoff

Ron Run on

∆S Change in soil moisture

Send Soil moisture content at the end of the time step


viiWrem MSc Thesis Clever Taurayi Dhliwayo June 2006

Sinitial Soil moisture available from previous time step

SADC Southern Africa Development Community

SIWI Stockholm International Water Institute

TI Tension Infiltrometer

TDR Time domain reflectrometer

WHC Water holding capacity

WP Wilting point

WVI World Vision International


viiiWrem MSc Thesis Clever Taurayi Dhliwayo June 2006

LIST OF TABLES

Table Page Table 1 Distinction between meteorological and human induced droughts and spell 7

Table 2 Sources of power for primary land preparation in 5 SADC countries 14

Table 3 Summary of planted variety, planting, weeding and fertilizer application dates 34

Table 4 Saturated hydraulic conductivities of different soil types 41

Table 5 Moisture content at the onset of the season 46

Table 6 Volume of water stored in the different treatments 50

Table 7 Deep drainage in the different treatments 51

Table 8 ANOVA for the cumulative infiltration of the different treatments 55

Table 9 Standard errors of differences of means and least significant difference 55

Table 10 Results of a 2 tailed, 2 sample paired, T- test of cumulative infiltration 56

Table 11 ANOVA for the moisture content of the different treatments 58

Table 12 Standard errors of differences of mean and least significant difference 58

Table 13 Results of a 2 tailed, 2 sample paired, T- test of moisture content 58

Table 14a Summary of rainfall partitioning in Field A 59 Table 14b Summary of rainfall partitioning in Field B 59 Table 15 ANOVA for the yield in different treatments 60


ixWrem MSc Thesis Clever Taurayi Dhliwayo June 2006

LIST OF FIGURES

Figure Page

Fig 1 The variation of infiltration capacity with time and slope 19

Fig 2 Components of tension infiltrometer 20

Fig 3 TDR for soil moisture measurements 24

Fig 4 Hydrological boundaries of Zimbabwe 27

Fig 5 Mzingwane Catchment, showing location of Zhulube field sites 28

Fig 6 Experimental plot layout 32

Fig 7 Soil moisture meter components 36

Fig 8 Summary of how rainfall was partitioned in the fields 38

Fig 9 Seasonal precipitation summary 43

Fig 10 daily rainfall figures 43

Fig 11 Infiltration rates at the start of the season 45

Fig 12 Infiltration rates at the flowering stage 45

Fig 13 Infiltration rates at maturity 46

Fig 14 Soil moisture distribution at the on set of the season 46

Fig 15 Soil moisture distribution 4 weeks after planting 47

Fig 16 Soil moisture distribution at grain filling stage 48

Fig 17 Soil moisture distribution at maturity 48

Fig 18 Change in storage for the different treatments 51

Fig 19 Summary of yield from different treatments. 52


1Wrem MSc Thesis Clever Taurayi Dhliwayo June 2006

CHAPTER 1: INTRODUCTION

1.1 Food production in arid and semi arid countries Water productivity in rain fed agriculture will have to increase dramatically over the next

generation if food production is to keep pace with population growth. Tropical developing

countries suffer from severe malnutrition. A large proportion of the population in these

countries depends on rain fed agriculture for their livelihoods (Rockström et al., 2002).

Ignoring the impact of HIV/AIDS, the population of the Southern Africa Development

Community region is in excess of 84 million people and growing at an estimated rate of two

million people per annum (SADC, 1995). Agriculture plays an important role in both

development and food security as 23% of the gross domestic product (GDP) for the region is

derived from agriculture (World Bank, 1997). Rain fed agriculture in Sub Saharan Africa is

practiced on approximately 95% of the agricultural land (the remaining is under irrigated

agriculture) and will remain the dominant source of food production during the foreseeable

future (Parr et al., 1990).

In general, yields from smallholder rain fed agriculture are low in many parts of the water

scarce tropical world oscillating around 1t ha-1 (Rockström, 2001). There is ample evidence to

suggest that the low productivity in rain fed agriculture is more due to sub optimal performance

related to management aspects than to low physical potential (Agarwal and Naram, 1997).

These management practices include timing of operations such as land preparation and planting

and management of weeds. This means that developing countries which are experiencing the

most rapid population growth depend on rain fed agriculture which is operating at sub optimal

level. Furthermore, it has been estimated that there is limited new land to put under agriculture

(McCalla, 1994), contrary to the last three decades in sub Saharan Africa where the bulk of



increases in food production originated from expansion of agricultural land. There is thus a

growing pressure to increase agricultural productivity through improved yields per unit of land

and per unit of water.

In Zimbabwe a number of malpractices have led to a communal farming sector performing far

below achievable yields. Obtained grain yields of below 1t ha-1 in areas which could produce 2-

3 times as much are not uncommon (Rockström, 2002). One of the reasons for this is poor land

management practices based on continuous grain cultivation and conventional tillage with hoe,

mouldboard plough or disk ploughs. The other is the excessive utilisation without

replenishment of soil nutrients and soil organic matter (Oldrieve, 1993). Mouldboard ploughs

and disk ploughs create a plough pan which inhibits infiltration and root proliferation

(Oldrieve, 1993).

The occurrence of dry spells during critical stages in the growth of a crop can also cause a

reduction in yields. Dry spells lasting 14 days or longer can lead to complete failure of a maize

crop if supplemental irrigation is not applied (SIWI, 2001). However, supplemental irrigation is

not always feasible for many rural communities due to the high cost associated with setting up

the necessary infrastructure.

Rural communities in semi arid areas will have to depend more on rain fed agriculture for a

long time to come, the cost of setting up an irrigation scheme being the prohibitive factor.

Conservation agriculture is one way of mitigating the impact of dry spell occurrences through

the enhancement of productive use of available water. It has proven to contribute to improved

use of rainfall, contribute to dry spell mitigation and help to increase farmers yield levels

(Rockström et al., 2001). Other benefits realized from conservation agriculture include the

following:



• Conservation tillage (especially ripping) reduce workload by half of that with the use of

mouldboard plough, which enable a farmer to go in line with the cropping seasonal

calendar (Rockström, 2003).

• Less soil compaction due to deep tilling.

• Less soil disturbance due to machinery use.

• Restriction of animal tramping the fields after crop harvest.

• Equal distribution of nutrients between the contour bunds (in sloppy areas)

resulting in having a homogenic crop stand (Rockström, 2003).

Recent research efforts in Zimbabwe, Kenya and Tanzania seem to promote conservation

tillage in low rainfall areas. In Matabeleland South province of Zimbabwe, a non-governmental

organization (NGO) World Vision International (WVI), together with a leading crop research

organization, International Crops Research Institute for the Semi Arid Topics, (ICRISAT) and

Practical Solutions (PS), is promoting different types of conservation tillage. Currently World

Vision International (WVI) and ICRISAT are promoting basin tillage in Gwanda, Insiza and

Beitbridge districts. In-field rainwater harvesting techniques being promoted by WVI are pot

holing and tied ridges between planting rows. PS and WVI are also promoting the use of dead

level contours with in-contour infiltration pits. Apart from promoting these practices, there is

not much evidence to suggest that sufficient research has been done to investigate the effects of

these practices to soil physical parameters such as infiltration and soil moisture retention. It is

only imperative that an on-farm research is carried out to determine the effectiveness of

promoted conservation tillage techniques which help mitigate agricultural droughts and ensure

livelihoods of these communities.



The purpose of this study is therefore to analyze the effectiveness of different conservation

agriculture techniques on the infiltration and soil moisture retention characteristics in two CA

tillage practices and two soil types. The conservation agriculture practices studied were

planting pits (PP) and clean ripping (CR) and compared against traditional farming practices.

1.2 Objectives

1.2.1 General Objective To investigate the effects of PP and CR as conservation agriculture practices on infiltration and

hence soil moisture availability with the aim of increasing yield due to increased soil moisture

availability within the root zone.

1.2.2 Specific Objectives i. To investigate the difference in infiltration capacity between conservation

agriculture practices and traditional farmer practices in Ward 1of Zhulube.

ii. To investigate the effects of farmer practices, planting pits and ripping on soil moisture

retention.

iii. To investigate the effect of conservation agriculture practices and traditional

farmer practices on yield.

1.2.3 Research hypothesis Specific objective 1 was achieved by testing the following hypothesis:

Null Hypothesis (Ho): There is no difference in infiltration between the three tillage practices.

Alternative Hypothesis (H1) There is a significant difference in infiltration between the three

tillage practices and two soil types.

A Test comparison was carried out between the control field (farmer practice) and the

experimental fields (planting pits and clean ripping).



Testing the hypothesis that soil moisture retention is the same in the three tillage practices

satisfied specific objective 2.

Specific objective 3 was achieved by testing the hypothesis that there is no significant

difference in the yields obtained from practicing conservation agriculture and traditional farmer

practices.



CHAPTER 2: LITERATURE REVIEW

2.1 Meteorological and Agricultural droughts Dry spells are generally understood as being related to drought occurrence during cropping

seasons. These droughts can be classified as follows: Meteorological droughts and agricultural

droughts.

A meteorological drought occurs when the amount of overall rainfall is below the minimum

required to generate fundamental ecosystem services from nature above all food production

(Rockström, 2000). This means that there is simply not enough rainfall to generate an edible

harvest of food crops. On the other hand an agricultural drought occurs when there is not

enough available soil moisture in the root zone. Crop water deficit generating an agricultural

drought can occur as a result of two major processes:

(i) Poor plant water availability related to low rainfall infiltration and poor soil moisture

holding capacity of the soil.

(ii) Poor plant water uptake capacity related to weak soil physical and chemical conditions and

poor crop management (soil fertility, timing of operations, crop varieties, etc.).

Often times the term drought is mainly associated with a meteorological drought. Rockström

(2003) suggests that this is not the usual case. Agricultural droughts are overwhelmingly more

common than meteorological droughts. Table 1 shows the types of water scarcity and

underlying causes.



Table 1: Distinction between meteorological and human induced droughts and spells, indicating impact and

causes as well as key resilience coping mechanisms.

Dry Spell Drought

Meteorological

Occurrence

Impact

Cause

Resilience options

Agricultural

Occurrence

Impact

Cause

Resilience options

Two out of three years (2/3 years)

Yield reduction

Rainfall deficit of 2-5 week periods during

crop growth

Build ecological and social resilience

Water harvesting

Two out of three years (>2/3 years)

Yield reduction/complete crop failure

Poor rainfall partitioning leads to low plant

water availability

Poor plant water uptake capacity


Soil and water conservation

Crop management

One year out of 10 (1/10 years)

Complete crop failure

Seasonal rainfall below minimum seasonal plant

water requirements

Resilient parachutes

Relief food, virtual water imports

One out of ten years (>1/10 years)

Complete crop failure

Poor rainfall partitioning leads to seasonal soil

moisture deficit to produce harvest


Resilience parachutes

Water harvesting

Soil and crop management

Source: Rockström 2003



2.2 Conservation agriculture This constitutes a wide set of integrated farming practices which focus on abandoning the

detrimental practice of conventional soil inversion through ploughing. Rockström (2000)

defined conservation tillage (one of the techniques of conservation agriculture) as any tillage

sequence having the objective to minimize the loss of soil and water and having an operational

threshold of leaving at least 30% mulch or crop residue cover on the surface through out the

year. However, with respect to small-scale farmers in semi arid savannah environment,

conservation tillage is defined as any tillage system that conserves water and soil while saving

labor and traction needs (Ngigi, 2003). It has been shown that conventional ploughing with

mouldboard and disk plough on tropical soils contribute to soil degradation and erosion of

ecological resilience in agricultural soils. Improved tillage where soil inversion is abandoned in

favor of sub soiling, manual pitting, ripping and zero tillage systems builds soil biology,

improves soil fertility and contributes to immediate productivity benefits and long term

resilience building (Rockström, 2003).

Mitigating dry spells is key to improved water productivity in rain fed agriculture in semi arid

and dry sub humid tropical environments. There are three major avenues to achieve this:

• Maximize plant water availability (maximize infiltration, minimize

unproductive water losses (evaporation), increase soil water holding capacity

and maximize root proliferation.

• Maximize plant water uptake capacity (timeliness of operations, crop management, soil

fertility management).

• Bridge crop water deficit during dry spells through supplemental irrigation and rain

water harvesting.



In situ systems, i.e. on farm cropland water conservation to enhance soil infiltration and water

holding capacity dominate while storage systems for supplemental irrigation are less common

especially in sub Saharan Africa (SIWI, 2001).

2.2.1 No till tied ridging This is a system of semi-permanent ridges with cross-ties along the furrows to trap run-off. The

ridges are laid across the main slope at a grade of 0.4-1%. Normally once constructed the ridges

are not destroyed for a period of six seasons depending on the crop rotations practiced by the

farmer (Nyagumbo, 1992). Planting is done on top of the ridges. In subsequent seasons land

preparation simply involves planting on top of the ridges. For good emergence, planting is

recommended only when the ridges are fully moist. In drier areas, planting may also be carried

out in the furrows where most of the run-off water collects. The shortcoming of this practice is

that planting is delayed until ridges fully wet up, which could be 50 to 60 mm of rain for a

sandy soil and more than 150 mm for a heavy soil (Ritches et al., 1997).

2.2.2 Mulch ripping This is a conservation tillage system involving the retention of stover on the surface and

use of a ripper to open up planting lines. Crop rows alternate between seasons. Planting is

carried out along the rip-lines. No ploughing takes place. This is not practiced at a large

scale in Zimbabwe because the stover is used to feed cattle in the drier months of the year

leaving nothing to act as mulch cover.



2.2.3 Clean ripping This system is the same as mulch ripping except that no stover is retained after

harvesting. An animal drawn ripper is used to open up rip lines into which planting is

done. Rip lines are repeated in the same line for successive seasons. This practice

requires less draught power and enables land preparation before the onset of the rains.

This is a critical opportunity in semi arid regions where 25% of the rains over a season

fall with the initial few rain storms (Rockström, 2003).

2.2.4 Hand hoeing (planting pits) Involves the use of hand hoes to open up planting holes to mimic situations where draft

power is not available. Weed control is achieved by hand weeding. This practice is

strongly promoted in Natural regions IV and V where 60% of households cannot put a

draught team together. Manual pitting is cheap, requires neither oxen nor implements,

and above all gives the farmer full control over the use of precious inputs such as seed,

manure and fertilizers (Rockström, 2003). This practice however, is labor intensive.

2.2.5 Infiltration pits These are deep trenches dug along the contour ridge to trap runoff and increase

infiltration. The pits are filled with grass or stover that is covered by a thin layer of soil so

that the organic material can decompose to form compost. The pits trap rain as it falls and

then the water infiltrates down slope thereby providing moisture to the crops in the field.

Infiltration pits improve water infiltration rate, water retention, reduce evaporation and

increase surface storage and the time available for infiltration to occur.

2.3 Rainwater harvesting This is the diversion and collection of runoff which will be used as supplemental

irrigation during dry spells. There are four well known methods of rainwater harvesting.

The soil type influences the method in several ways. Clay soils have low infiltration rates



and high moisture storage capacity, so they are suitable for deep flooding with

subsequent cropping. A deep soil can absorb larger amounts of water, while a shallow

soil may need the provision of overflow outlets to avoid drowning the crop.

2.3.1 Natural runoff There are many examples of traditional use of naturally occurring run-off to augment

rainfall in areas where the rain alone is not sufficient for growing crops. The Navajo in

Arizona use run-off from sandstone outcrops to water alluvial soil at the base of the hills

(Billy 1981). Good crops of maize, squash, and melons are produced where the annual

rainfall is only 300-400 mm a-1. .

2.3.2 Collected and Diverted Runoff This has to do with schemes where there is some element of manipulation or management

of the land or the run-off. Another example of carefully controlled water use in valley

bottoms comes from Colorado (Mickelson et al., 1965). Level pans of one to three

hectares are formed in broad valleys where slopes are less than 3 percent. The rainfall is

400 mm a-1, sufficient for some rather unreliable cropping of grain or forage sorghum.

The cropped land yields 5 to l0 percent of the rainfall as run-off from the heavy summer

storms. The run-off from 150 hectares of cropland is spread onto the first level pan, and

when the depth reaches more than 100 mm the surplus spills over to the second pan and

so on. During the season, an additional 200 mm of water results in good crops on the

pans, so that the installation costs can be repaid in three to five years.

2.3.3 Inundation methods This describes systems where floodwaters are impounded and retained long enough to

saturate the soil so that a crop can be grown on moisture stored in the soil. Simple



systems on a small scale are used in the Sudan (Pacey, 1986). On gently sloping land

embankments known as 'teras' collect and hold surface run-off, and after the water has

soaked into the soil, short duration millet is planted and matures in eighty days.

2.3.4 Flood Diversion This is the diversion and spreading of floods and spate flows. Diversion of floodwater

from its channel usually involves some form of structure, a barrage or weir to divert the

water. For small schemes, simple diversions may be constructed each year using stones

and boulders using wire netting or poles and brushwood where these are available (FAO,

1987).

2.4 Constraints to adoption of conservation tillage

2.4.1 Low Degree of Mechanization Most field operations particularly by small-holder farmers are performed manually thereby

limiting the area cultivated per person. In comparison with other developing countries Sub-

Saharan Africa ranks the lowest in terms of access to draught power sources such as oxen and

tractors (FAO., 1987 and Ellis-Jones, 1997). The fact that most operations are performed by

hand limits the extent to which farmers can adopt certain conservation tillage practices as

draught power or mechanization is almost always a requirement.

Table 2 highlights the distribution of sources of power for primary land preparation for some

SADC countries. In terms of development of mechanized power sources South Africa (70%),

Zimbabwe (55 %) and Botswana (40 %) are the most developed in this regard due largely to

the extent of commercialization of agriculture in these countries.

Thus the development of mechanical power has been associated with scales of production

associated with the colonial history of the respective countries. The use of draft animals is



confined to the small-holder farming sector with Botswana (40%) and Zimbabwe (30%)

ranking the highest. Mwinjilo (1992) states that virtually all cultivation is done by hand-hoes in

Malawi with only 4.9 % of the farmers owning draft animals.

Table 2: Sources of power for primary land preparation in 5 SADC countries

% of cultivated land

Country Manual Labour Draught Animal Power Mechanical Power

Botswana 20 40 40

Kenya 84 12 4

South Africa 10 20 70

Tanzania 80 14 6

Zimbabwe 15 30 55

Source: Ellis-Jones, 1997

The adoption of conservation tillage systems is related to the resource ownership of the

farmers, particularly draught power. In Zimbabwe, for instance, it is estimated that 5-10% of

the commercial farms are under conservation tillage whilst the use of conservation tillage in the

small-holder farming sector is estimated to be below 1%. Furthermore socio-economic surveys

in the small-holder farming sector in a high potential region of Zimbabwe revealed that farmers

participating in the development of a conservation tillage technique, no-till tied ridging, were

better resourced and owned more draft power than their non-participating counterparts

(Nyagumbo, 1992). The availability of implements in most countries in the region has also

contributed appreciably to the relatively low adoption of conservation tillage systems. This is



because farmers lack the means to acquire these implements or the institutional set-up has not

enabled farmers to access these implements. In most of the countries in the region the most

commonly available implement is the plough. Over 80% of the farmers in Zimbabwe own

single furrow mould board ploughs while ridgers are owned by 2-5% (Nyagumbo, 1992; Ellis -

Jones 1997). The ripper tine was also found to be owned by less than 5% of farmers in a high

potential region in Zimbabwe (Nyagumbo, 1992). The ridgers and ripper tines are key

implements for the type of conservation tillage systems promoted in Zimbabwe. Thus most of

the small-holder farmers in the region suffer from the problem of lack of appropriate

implements coupled with limited access to draught power.

2.4.2 Weed Control The control of weeds under conservation tillage systems also poses a major threat to the use of

conservation tillage systems in the region. Ellis-Jones and Mudhara (1997) found in Zimbabwe,

that the system used by farmers depends on resources that they have available to them and

established that households with 3 adult equivalents, working 6 hours a day have sufficient

labor for 1.1 hectares where operations were fully manual with no access to draught power; 4

hectares where the mould board plough was used as the basic implement but with some draught

power limitation and 7.4 hectares where a range of animal drawn implements were available

and access to draft power was unlimited.

Riches et al., (1997) working at Makoholi Experiment Station also found that the weeding

effort which accounted for more than 60 % of the labor used for maize production in semi-arid

Zimbabwe, was greatly eased while grain yields and return to weeding labor significantly

improved where animal drawn implements such as cultivators and ploughs were used to control

weeds. The efficiency of weed control was also found to greatly improve where farmers used



re-ridging with the plough as a weed control measure under no-till tied ridging in the sub-

humid north of Zimbabwe (Nyagumbo, 1993). Complimentary work by Shumba et al., (1992)

showed that the use of the ripper tine for primary land preparation allowed for timely planting

but resulted in earlier and heavier weed infestations. Thus unless effective weed control can be

achieved the benefits of timely planting accrued using the ripper tine are lost.

The relatively higher adoption of conservation tillage in the large scale commercial farming

sectors of Zimbabwe, Zambia and South Africa could therefore be attributed to the availability

of suitable machinery and the use of herbicides which have tended to be unaffordable to small-

holder farmers in Zimbabwe.

2.5 The effects of crusting Conservation tillage practices are used to modify the structural organization of a soil by

mechanically loosening the soil surface. This loosening results in a reduction of bulk density

and an associated increase in porosity and hydraulic conductivity. Water retention is enhanced

and root penetration is made easier hence exploiting available soil water and nutrients (Mellis

et al., 1996). These benefits are however temporary as the action of rainfall tends to modify

them. Successive rainfall events change the rate of permeability, porosity, and surface structure.

As degradation proceeds wetting and dry cycles a surface layer of reduced permeability

commonly develops on a range of temperate and tropical soils (Casenave and Valentin, 1992).

The resulting crust seal can range from 1 to 50mm in thickness (West et al., 1992). Weeding

operations however, ensure that this crust is broken increasing permeability temporarily.



2.6 Infiltration

2.6.1 Infiltration capacity of a soil When rain falls, it first wets the vegetation or the bare soil. When the surface cover is

completely wet, subsequent rain must either penetrate the surface layers if the surface is

permeable, or runoff the surface towards a stream channel if the surface is impermeable.

If the surface layers are porous and have minute passages available for the passage of water

droplets, the water infiltrates into the sub surface soil. Soil with vegetation (crops) on it is

always permeable to some extent. Once infiltrating water has passed through the surface layers

it percolates downwards under the influence of gravity until it reaches the zone of saturation at

the phreatic surface.

2.6.2 Factors affecting infiltration rate

Soil type Different types of soil allow water to infiltrate at different rates. Each soil type has a different

infiltration capacity, which is usually measured in mm/hr. Rain falling on a gravelly or sandy

soil rapidly infiltrates provided the phreatic surface is below the ground surface. Even heavy

rain will not produce surface runoff (Nassif, 1976). A clayey soil will resist infiltration and the

surface will become covered with water even in light rains.

Rainfall intensity The rainfall intensity also affects how much rain will infiltrate and how much will runoff.

Infiltration rate is largely controlled by the surface pores (Butler, 1957). Even quite a small

increase in the hydrostatic head over these pores results in an increase in the flow through the

soil surface. This head increases with rainfall intensity and so does infiltration rate until a

limiting value is reached where runoff prevents any further increase.



Vegetal cover Dense vegetal cover such as grass or forests tends to promote high values of infiltration rate in

a number of ways (Wilson, 1969).

• The dense root systems provide ingress to the subsoil.

• The layer of organic debris forms a sponge like surface preventing compaction.

• Burrowing animals and insects open up ways into the soil.

• The cover prevents compaction and.

• Transpiration from vegetations removes soil moisture. All this tends to help the

infiltration process.

Slope Slope affects infiltration rate to a limited extent. As slope percentage increases, infiltration rate

decreases. Slope variation is most sensitive between 16 % and 24 % (Nassif, 1976). A summary

of factors affecting infiltration capacity is shown in Fig 1.



Fig 1: The variation of infiltration rate (f = infiltration rate mm/hr) with time and slope

Source: Nassif (1976)

Turfed soil

f

Bare soil

Time

f

Low rainfall intensity

High rainfall intensity

Time

Slope %

f



2.6.3 Measurement of Infiltration Determining soil water characteristics in the field is costly, time-consuming, and relatively

cumbersome, but necessary for many soil management evaluations and for modeling purposes.

In the last decade, tension infiltrometers have become a valuable tool for understanding water

movement through macro pores and the soil matrix near saturation (Logsdon and Jaynes, 1993;

Reynolds et al., 2000; McKenzie et al., 2001; Ankeny et al., 1988). They work by measuring

infiltration rates at water pressures that are negative relative to the atmospheric pressure. The

tension infiltrometer (TI) method is applied in situ, with minimum disturbance of the

infiltration surface and establish a three-dimensional infiltration process controlled by the

pressure head (in this case negative) imposed at the soil surface. An illustration of the tension

infiltrometer is shown in Fig 2.

Fig2: Components of tension infiltrometer



Another way of measuring infiltration is by use of the double ring infiltrometer. It consists of

an inner and outer ring inserted into the ground. Each ring is supplied with a constant head of

water from a Mariotte bottle. Infiltration rate can be estimated for the topsoil when the water

flow rate in the inner ring is constant (Cook et al,. 1994).

Having the two rings eliminates the problem of overestimating the infiltration rate in the field

due to three dimensional flow (White et al,. 1992). The outer ring supplies water which

contributes to lateral flow as the inner ring is contributing to the downward flow.

Water moves from the Mariotte bottles into the rings via a tap at the base of the vessels until

the height equals that of the base of the bubble tube. When water moves into the soil, reducing

the height of ponded water to below that of the bubble tube, more water is fed into the ring.

Some draw-backs of the double ring are that it is very time consuming, requiring trial and error

when adjusting the bubble tubes to get the water levels in each ring equal. The practicality of

the instrument is reduced by the fact that rings are extremely heavy to move. It also requires a

flat undisturbed surface which sometimes is not available. During the experiment it is

sometimes necessary to refill the Mariotte bottles. To do this, the tap has to be turned off and

this disrupts the experiment.

2.6.4 Tension infiltrometer versus double ring infiltrometer Practical advantages of using a tension infiltrometer are:

• Easy construction with detachable and interchangeable components.

• Faster measurements.

• Less water requirements.

• Minimal disturbance of soil surface.



Obtaining data from these infiltrometer is a lot easier than the double ring infiltrometer,

although it is a lot more complicated to analyze due to the flow being in three dimensions.

When analyzing this data absorption and capillary forces, which act in all directions and the

geometry of the water source, have to be considered (White et al., 1992). When using the

tension infiltrometer, a good intimate contact between the disc and the soil surface needs to be

established. This is often achieved by using a contact material such as fine sand. A drawback of

using such a material is that it will interfere with the measurements especially in the early

stages of infiltration giving inaccurate sorptivity values (Bagarello et al., 2001).

2.6.5 Tension infiltrometer theory During infiltration events, the water enters the soil in response to potential gradients of water

potential and gravitational potential. The water potential term is governed by the dryness of the

soil and the pore structure of the soil. These two factors combine to form a sorptivity factor

which is made up of the combined influences of capillary action and adhesive forces to soil

solid surfaces (Cook, 1994). The gravity term is a constant for different soils and is due to the

impact of the pore size, continuity and distribution on the rate of water flow through soil under

the influence of gravity.

Infiltration from a circular disc into a homogeneous soil has a two-dimensional flow-pattern

with a radial symmetry. The cumulative infiltration is caused by a combined effect of

capillarity and gravity. Initially, for a very small period, the capillarity is predominant and the

gravity influence is negligible. As the soil wets up, the gravity term dominates and the

infiltration rate approaches a constant.



2.7 Soil moisture measurements Soil moisture content can be measured using the gravimetric method or a Time Domain

Reflectrometer (TDR). With the gravimetric method, soil samples are taken from the field. The

soil is preserved in a medium which does not allow water to escape. The sampled soil is then

weighed before placing it in an oven to dry for 24 hours. The sample is then weighed to get the

dry weight. The difference in weight of the soil sample before and after oven drying expressed

as a percentage of the initial weight gives the moisture content of the soil sample. This method

requires that a laboratory be near the experimental site to make sure that no water is lost

between sampling and measurement.

With a TDR, however, soil moisture content readings are available promptly. The moisture

meter applies power to the sensor and measures the output signal voltage returned. The voltage

is converted internally to moisture units. The meter converts the mV reading into soil moisture

units using conversion tables and soil specific parameters. (See Fig 3 for an illustration of the

TDR used in the field).



Fig 3 TDR for soil moisture measurement

Source Delta-T Devices 2004



2.7.1 Theta Probes Theta Probes measure volumetric soil moisture content, Өv by responding to changes in the

apparent dielectric constant of moist soil. These changes are converted into a dc voltage in mV,

which is then converted to soil moisture content in the HH2 using a linearization table and soil

type parameter (see Fig 8 for components of the moisture meter).

Volumetric soil moisture content is the ratio between the volume of water present and the total

volume of the sample. This is a dimensionless parameter, expressed either as a percentage (%

volume), or a ratio (m3/m3).

2.8 Evaporation and Transpiration Wallace and Batchellor (1997) indicated that soil evaporation in rain fed crops can be 30-35%

of rainfall for millet grown on research plots in Niger. Walker (2003) put this figure at 35-

40%. Rockström (1997) found that transpiration could be as low as 5% of rainfall in typical

farmer’s fields in West Africa. Thus irrespective of spatial and temporal rainfall variability

there is a high seasonal risk of soil water scarcity in crop production due to immense

evaporation.

Rockström (1997) established that an average of 10% of the rainfall in a Sahelian rain fed

cropping system with pearl millet could be used productively to generate a crop. If a crop is

grown under unlimiting conditions of water availability, substantial yields are realized provided

soil fertility and other management practices such as proper timing of operations are done

properly. This substantial increase in yields can be realized if the amount of water used for

transpiration could be increased.

When crop yields are increased from a low starting point (say from 1-2t ha-1), there is a

significant improvement of water productivity (in terms of green water, i.e. total transpiration).

Thus from the total precipitation received, the blue and white water components are reduced



due to an increase in the utilization of green water. The reason is that while transpiration

increases linearly with increased yields, evaporation losses will progressively decline. The

effect is a progressive improvement in water productivity (Rockström, 2003).

The majority of smallholder farmers have adopted intercropping to use the available soil water

in a semi arid environment more productively (Walker and Ogindo, 2003). Intercropping

results in a high leaf area than sole cropping. The soil surface is shaded and the canopy is

denser resulting in a lower soil surface evaporation. Evaporation losses account for more than

30 % of the rainfall whereas transpiration accounts for less than 10 % of the rainfall in a rainfed

cropping system (Rockström, 1997). This implies that increased canopy cover repartitions

transpiration and evaporation components by reduces the evaporation loss and increasing the

transpiration component. The water budget thus gives a higher value of transpiration for inter

cropping during the growing season.



CHAPTER 3: STUDY AREA

The research was conducted in ward 1 of Zhulube village, Insiza District of Matabeleland

South province in the Mzingwane catchment of the Limpopo basin in Zimbabwe (see Fig 4).

Fig 4: Hydrological boundaries of Zimbabwe

Mzingwane is located in the southwest region of Zimbabwe in a semi arid agro-climate. The

catchment has three major river systems; namely Shashe, Mwenezi and the Thuli river systems

which all drain into Mzingwane River. Mzingwane is divided into four sub catchments namely



Shashe, Mwenezi, Upper Mzingwane and Lower Mzingwane. All the river systems in

Mzingwane flow into the Limpopo River and form part of the larger Limpopo basin which cuts

across three countries; Zimbabwe, South Africa and Mozambique.

Fig 5: Mzingwane Catchment, showing location of Zhulube field sites.

The annual rainfall ranges from 250 mm a-1 in the South to 550 mm a-1 in the north of the

catchment with an average of 350 mm a-1 over the entire catchment area (Unganani, 1996). The

wet season starts any from November to mid December and normally ends in April. Values for

air temperature are closely related to altitude with mean annual temperatures ranging from

about 120C to 290C. The lowest temperatures (below 00C) are recorded in June and July during

the dry season and the highest temperatures (above 30oC) are recorded in October at the onset

of the wet season.



3.1 Vegetation In communal lands characterized by relatively high population densities, disturbance of

the vegetation by cultivation has greatly depleted the extent of climax woody cover. The

Miombo woodland, dominated by Brachystegia species and Julbernadia globiflora has

been the most affected by population pressure. The northern part of the Insiza sub-

catchment has low open woodland of Combretum-acarcia-terminalia associated with

granitic or gneissic derived sandy soils. On heavier textured soils, Colophospermum

mopane becomes dominant. Towards the south of the sub-catchment vegetation types and

species change with elevation from sparse low mopane woodland being gradually

replaced by Terminalia sericea open woodland.

3.2 Farming systems There are four major categories of farmers: the large scale commercial farmers, the small-scale

commercial farmers, smallholder communal farmers and smallholder irrigation schemes. Large

scale commercial farms were subdivided into two categories due to the land reform programme

embarked upon by the Government. These groups are A2 farms and A1 farms. A2 farms are

relatively big subdivisions of the original farms with one farmer owning between 20 and 400

hectares. A1 farms are relatively small with one farmer owning 6 hectares of arable land. Land

for grazing is shared amongst all the farmers.

Small scale commercial farmers own individual, relatively small pieces of land. Their

operations are mainly hindered by low degree of mechanization. Smallholder irrigation

schemes also suffer from low degree of mechanization. As a result the recommended area for

one farmer is 0.5 hectares (FAO, 2003). The farmers are able to grow wheat and vegetables in

the dry season. Communal farmers are the most vulnerable group should a drought occur as

they only rely on rain fed agriculture. Since the area receives very low rainfall and the soils are



of low fertility, the chances of getting a descent harvest are very low. Subsistence agriculture

takes place in the communal areas where vegetables and cereals are grown during the wet

months, in addition to livestock farming (Waternet CNN133, 2003).



CHAPTER 4: METHODOLOGY

4.1 Treatments and experimental plot layout The experiment was set up with two farmers (whose fields have different soil types: (red sandy

silt loam and red clay loam) practicing dry land farming. Resource constraints only allowed up

to two sites to be studied. The selection of these farmers was done together with a leading crop

research organization: International Crops Research Institute for the Semi Arid Tropics

(ICRISAT). Because the experiment involved some degree of mechanization in the clean

ripping treatment, farmers were selected taking into consideration available draught power. In

each field, three tillage practices were studied.

(a) Farmer practice. This is conventional ploughing with the single furrow mould

board plough during winter. This is what the farmer would normally practice without

the influence of research or donors.

(b) Planting pits. These are holes 20cm deep dug with a hand hoe. The in row

spacing was 60cm and the row spacing was 90cm.

(c) Clean ripping. A donkey drawn ripper was used to open up rip lines into

which planting was done. The rip lines were spaced 90cm apart. Plot layout was

as shown in Fig 6.



Farmer Practice

Planting Pits

Rip Lines

90cm

60cm

Fig 6: Experimental plot layout

4.2 Crop establishment A short season maize variety (SC403) was planted in each plot. In order to achieve a planting

rate of 2.5kg per acre which is the recommended planting population for the soil type by the

AREX officers in the district, the following planting methods were used for the different tillage

practices:

For farmer practice, seed was placed at a spacing of 30cm along a row following where the

mould board plough was ploughing. One seed was placed at each location. Planting was done

manually. A tape measure was used to mark 30 cm locations in each row where upon a seed

was dropped in the furrow at that particular location and covered to a depth of ten centimeters.

For planting pits, the pits were dug with an in row spacing of 60 cm and a row spacing of 90

cm. Seed was placed at each end of the planting pit and one in the middle. The weakest of the

10m

10 m



three plants was removed at first weeding. This ensured that the most thriving plants had the

chance to grow well.

For clean ripping, two maize seeds were placed at a spacing of 30 cm along the rip line. The

emerging plants were thinned removing the weakest plant at a location. The reason for placing

two seeds at a location was the anticipated low germination rate in clean ripping.

4.3 Fertilizer application According to the recommendations of the two organizations working in the area (World Vision

International and ICRISAT), ammonium nitrate fertilizer (AN) was applied using the micro

dosing technique. This involves applying AN directly to where the plant is. Each plant received

one capful of AN per application. The cap which was used was that of 300 ml carbonated soft

drinks and is equivalent to 10g. This amounted to 10 kg ha-1. Fertilizer was applied twice, first

when the crop was at knee height and second when the crop was flowering. To reduce on the

cost of fertilizer, cattle manure was used as basal fertilizer instead of compound D. This

fertilizer application was the same for all tillage practices.

4.4 Crop harvesting Each plot was harvested and the grain was weighed in the field using a pocket balance. For

each plot, a sample was taken for oven drying. Before oven drying, the sample was weighed

and then oven dried to 12.5% moisture content. 12.5 % was used as it is the marketing and

storage moisture content. The grain was then shelled after drying and the grain weight was

measured. The grain weight was then converted to the total field weight (i.e. the yield weight).

Below is a summary of planted variety, planting dates, weeding and AN application dates.



Table 3: Summary of planted variety, planting dates, weeding and fertilizer application dates.

Planting pits Clean ripping Farmer practice

Maize Variety SC403 SC403 SC403

Planting date 09-12-05 20-12-055 17-12-05

Germination date 14-12-05 25-12-05 22-12-05

First weeding 27-12-05 11-01-06 09-01-06

Second weeding 24-01-06 10-02-06 08-02-06

Fertiliser application 1 12-01-06 23-01-06 20-01-06

Fertiliser application 2 11-02-06 21-02-06 18-02-06

4.5 Measurements The following parameters were measured during the experiment; infiltration, rainfall, soil

volumetric moisture content, and yield. Components constituting the elements of rainfall

partitioning were estimated using a spread sheet model developed by Rockström (2001) for

supplemental irrigation in Same, Tanzania. These elements were: soil moisture storage, run off

and deep drainage. Evapotranspiration was estimated using the CROPWAT model.

4.5.1 Rainfall Two rain gauges were installed, one in each research site. Rainfall occurring in the study fields

was measured from these rain gauges. Readings were taken at eight o’clock in the morning

every day. The rain gauges used were of diameter 12cm, plastic and measuring rainfall in mm.

The rain gauges were placed in a clear place free from trees and shrubs at field edge.



4.5.2 Infiltration A tension infiltrometer (Model no. PMB-170, 20 cm-diameter. base plate: Soil Measurement

Systems, Tucson, AZ) was calibrated in November 2005, and a pressure head of 10mm of

water, was applied to the maize plots in the two fields (see figure 4 for diagram of tension

infiltrometer). Five readings were recorded for each treatment at weekly intervals for a plot

measuring 10m by 10m. The tension infiltrometer was placed at a spacing of 2.5m across each

treatment. In farmer practice treatments, the instrument was placed between the rows. For

planting pits the instrument was placed between the holes in a row and for clean ripping, the

instrument was placed between the riplines. Infiltration readings were taken for ten minutes at

thirty second intervals for each sampling site. A stop watch was used for timing.

To make sure that the base of the infiltrometer sat squarely on the ground, sites were carefully

chosen where the ground was relatively level. Where such ground was not available, an attempt

was made to level the ground. This however changed the original soil structure of the soil at

that particular site and tended to give infiltration rates which were higher than normal (Andreini

and Steenhuis, 1990).

4.5.3 Soil volumetric water content A Time Domain Reflectrometer (TDR) was used to measure soil volumetric water content. The

type used is the type HH2 moisture meter with an RS232 cable with 9 way to 25 way converter.

The sensor used for theta probes was the type ML2.



Fig 7: Components of moisture meter

Source: Delta T Devices 2004



For the purposes of this study, it was necessary to measure profile readings and get soil

volumetric moisture content for the different profiles. However, due to lack of the necessary

equipment, this was not possible. Instead Theta Probes were used in conjunction with a soil

auger. Profile readings were taken at three locations spaced at 3.3m. Moisture content was

taken at different depths, 0-10, 10-20, 20-30, 30-40 and 40-50cm at an interval of seven days.

For deeper profiles it was difficult to take readings especially in the clay loam soil because it

was gravelly. For the sandy loam soil, depths of up to 60cm could be reached without problems

but for comparison sake 40-50cm was the last profile for both soil types.

A soil auger was used to probe the different profiles. The ML2 sensor was then inserted inside

the augured soil to get the moisture content of that particular profile. The assumption here was

that the soil water content was uniform over the area for which it was being estimated. In

farmer practice treatments, augering was done in between the rows. For planting pits, augering

was done between the holes in a row and in clean ripping augering was done between rip lines.

4.5.4 Water Partitioning In an effort to partition rainfall occurring in the study fields, some assumptions were made to

simplify the otherwise complex dynamics of water flow processes at field scale through crop

and soil.

In this study rainfall partitioning was done on a weekly basis following the guidelines stated by

Rockström, (2001). Fig 9 is a conceptual diagram of how rainfall is partitioned in the farmer

fields. Rainfall (R) is partitioned into surface runoff (Roff), and soil infiltration (I). The water

that enters the soil is turned into soil moisture storage (S). The soil moisture is partitioned

between soil evaporation and plant transpiration which can be lumped into evapotranspiration

(ET), and deep drainage (D) downwards beyond the root zone.



`

Fig 8: Conceptual diagram of rainfall partitioning in the fields.

Thus the equation representing rainfall partitioning takes the form

ETDRRRS offon −−−+=∆ …………………………. (1)

Where R = rainfall, Roff = surface runoff, D = deep drainage (in this case below 50cm) and ET

= evapotranspiration.

The change in soil moisture is given as ∆S because it is a moisture change over the time step

used (7 days), that is, the soil moisture content at the end of the time step (Send) minus the soil

moisture available from the previous time step (Sinitial).

Thus,

ETDRRRSS offoninitialend −−−+=− …………………… (2)

Runoff (R0ff)

Deep drainage (D)

Precipitation (R) Evapotranspiration (ET)

Run on (Ron)

Infiltration (I)Storage (S)



Where,

∆S = Send – Sinitial …………………………………………. (3)

The soil moisture available at the end of one time step (Send) becomes the available initial soil

moisture (Sinitial) for the next time step. Thus,

ETDRSRRS offinitialonend −−−++= …………………….. (4)

This means that the soil moisture storage available to the crop in the root zone at the end of a

time step is equal to the input of water (infiltration +soil moisture) at the beginning of the time

step ( Sin) minus all losses (Roff, D and ET).

4.5.4.1 Evapotranspiration Evapotranspiration was estimated using the CROPWAT model developed by the United

Nations Food And Agriculture Organization (FAO).

4.5.4.2 Rainfall and other climatic data Rainfall data used was that which was recorded on site. These were preferred to that provided

in the CROPWAT model since site data is available as daily figures as opposed to CROPWAT

data which is available as predicted average values of the total monthly rainfall. Climatic data

was used from West Nicholson weather station.

4.5.4.3 Surface runoff and run on The actual surface runoff generated from a rainfall event depends on several factors like surface

crusting, plough pans, rainfall intensity, soil moisture content, soil texture and slope

(Rockström, 2001). In this study, a constant runoff coefficient for all rainfall events exceeding

15mm for field A and 20mm for field B was used. This estimate was based on observations in

the two fields. Average surface runoff in semi-arid areas, from gently sloping land (1-3%) on

soil with surface crusting will range from 15 to 30% of the rainfall (generally for rainfall events



exceeding 15mm (Rockström, 2001)). Run on was considered negligible as there was a contour

ridge which diverted runoff generated upstream away from the fields. Although this was done

as a soil conservation measure, this diverted runoff could be used to augment the meager

rainfall experienced in the area.

4.5.4.4 Deep drainage As mentioned in section 4.3.1 the soil profile considered was in the upper 50cm due to

difficulties faced in augering beyond this depth in the clay loam soils. Any soil water

accumulation beyond the 40-50 cm profile was regarded as deep drainage loss for this study.

Deep drainage was assumed to have occurred when the water content in the root zone exceeded

the field capacity (FC) of the soil for holding water. The field capacity is defined as the soil

water available to plants after the soil has drained rapidly, normally after twenty four hours. FC

is calculated from the water holding capacity (WHC) of the soil and the water content at wilting

point (WP). Thus FC = WHC – WP.

Deep drainage was assumed to have occurred when infiltration exceeded field capacity in the

soil. This field capacity gives the threshold moisture content beyond which deep drainage

occurs. To estimate how much deep drainage will occur during the 7 day time step, a simple

constant value was assumed, based on saturated hydraulic conductivity data for different soil

types (Table 4).



Table 4: Saturated hydraulic conductivities of different soil types

Source: FAO 1995

Soil type Organic matter Soil aggregate structure (permeability in mm/hr) None Weak Intermediate GoodSand Low 25-50 - - - Adequate 50-250 - - - Sandy loam Low 15-25 - - - Adequate - 25-120 - - Loam Low 10-20 20-60 - - Adequate - - 60-120 - Clay loam Low 2.5-5 5-20 0 - Adequate - - 20-60 - Light clay Low - <2.5 - - Adequate - - 2.5-5 5-20 Medium or heavy clay Low - <2.5 - - Adequate - - <2.5 5-20 Clay sodic <1 <2.5 8 -



CHAPTER 5: RESULTS

5.1 Rainfall The rainy season for the study fields started on the 26th of November 2005. The total rainfall

recorded from the start of the season on the 26th of November to the end of the season (Crop

declared mature) on the12th of March in the two fields was 490 mm and 513mm in Field A and

Field B respectively. February recorded the highest rainfall with Field A recording 167

mm/month and Field B recording 182 mm/month. This pattern was favorable as the maize crop

was in its flowering and grain filling stages. The monthly rainfall data is presented in Fig 9.

The daily precipitation figures show two periods of prolonged dry spells of two weeks and

more during the growing season. The first was observed between the 25th of December 2005

and the 9th of January 2006 i.e. 16 days (during the vegetative growth period). The second was

observed between the 25th of January and the 7th of February 2006 (during the flowering stage).

The last rainfall was recorded on the 7th of March.



0

20

40

60

80

100

120

140

160

180

200

Nov Dec Jan Feb Mar

Month

Pre

cipi

tatio

n (m

m)/m

onth

Field AField B

Fig 9: Seasonal precipitation summary

Fig 10 shows the daily rainfall figures. It can be observed from the graphs that there were two

periods where 14 day or more dry spells were experienced i.e., days 32 - 45 and days 61-74.

(a)

0

10

20

30

40

50

60

1 10 19 28 37 46 55 64 73 82 91 100 109

Days after germination

Pre

cipi

tatio

n (m

m/d

ay) Field A

Germination Vegetative Flow ering Maturity



(b)

0

10

20

30

40

50

60

1 10 19 28 37 46 55 64 73 82 91 100 109

Days after germination

Pre

cipi

tatio

n (m

m/d

ay)

Field B

Germination Vegetative Flow ering Maturity

Fig 10: Daily rainfall figures (a) Field A (b) Field B

5.2 Infiltration At the onset of the season, it took between 8 and 10 minutes at a negative suction head of

10mm) to reach the steady state infiltration rate for all the tillage practices in both soil types.

The order of time taken to reach the basic infiltration rate for the three tillage practices was 0.6

mm hr-1, 0.7 mm hr-1, and 0.2 mm hr-1 for FP, PP, and CR respectively in Field A. For field B

the order is PP (0.7 mm hr-1), CR (1 mm hr-1), and FP (0.8 mm hr-1).

As the season progressed however, the time taken to reach the basic infiltration rate continually

declined for FP and PP in both soil types. CR plots showed a constant time of reaching the

basic infiltration rate.

It was also observed that weeding operations increased the time of reaching the basic

infiltration rate but it was only temporary. The temporal variation of the time it took the

different treatments to reach the basic infiltration rate is shown in Fig 11 to13.



a

0.0

2.0

4.0

6.0

8.0

10.0

0.0000 0.0500 0.1000 0.1500 0.2000Time (hr)

Infil

tratio

n ra

te (m

m/h

r)

FPppCR

b

0.0

2.0

4.0

6.0

8.0

10.0

0.0000 0.0500 0.1000 0.1500 0.2000

time (hr)

Infilt

ratio

n ra

te (m

m/h

r)

FPPPCR

Fig11: Infiltration rates at the start of the season (19-12-2005), (a) Field A (b) Field B

a

0.0

2.0

4.0

6.0

8.0

10.0

0.0000 0.0500 0.1000 0.1500 0.2000

Time (hr)

Infilt

ratio

n ra

te (m

m/h

r)

FPPPCR

b

0.0

2.0

4.06.0

8.0

10.0

0.0000 0.0500 0.1000 0.1500 0.2000Time (hr)

Infilt

ratio

n (m

m/h

r) FPPPCR

Fig12: Infiltration rate at the flowering stage (14-02-2006), (a) Field A (b) Field B

a

0.0

2.0

4.0

6.0

8.0

0.0000 0.0500 0.1000 0.1500 0.2000

Time (hr)

Infilt

ratio

n ra

te (m

m/h

r)

FPPPCR

b

0.0

2.0

4.0

6.0

8.0

0.0000 0.0500 0.1000 0.1500 0.2000

Time (hr)

Infilt

ratio

n (m

m/h

r) FPPPCR

Fig 13 Infiltration rate at maturity (16-03-2006), (a) Field A (b) Field B



5.3 Soil Moisture Content The first soil moisture measurements were taken on the 19th of November 2005. The initial soil

moisture content for the first 20 cm was below the minimum rating of the TDR used for this

study hence it was regarded as negligible. The initial soil moisture distribution profiles for

Field A and Field B are shown in Fig 14a and 14b respectively.

(a)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

0 10 20 30 40 50Depth (cm)

Moi

stur

e co

nten

t (%

vol)

FPPPCR

(b)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

0 10 20 30 40 50 60

Depth (cm)

Moi

stur

e co

nten

t (%

vol)

FP

PP

CR

Fig 14: Soil moisture distribution at the on set of the season; (a) Field A, (b) Field B.



Table 5: Moisture content at the onset of the season

Tillage practice Moisture content Field A (% vol) Moisture content Field B (%vol

Farmer Practice 5.5 5.3

Planting Pits 6.3 5.4

Clean Ripping 4.8 4.9

Soil moisture measurements were also taken when the crop was knee high i.e. four weeks after

emergence. Field A had received 203 mm of rainfall and field B had received 214 mm of

rainfall. The results are shown in Fig 15a and 15b.

(a)

10.0

20.0

30.0

0 20 40 60Depth (cm)

Moi

stur

e co

nten

t (%

vol

)

FPPPCR

(b)

10.0

15.0

20.0

25.0

0 20 40 60

Depth (cm)

Moi

stur

e co

nten

t (%

vol

)

FPPPCR

Fig 15: Soil moisture distribution 4 weeks after planting; (a) Field A, (b) Field B.

The same trend prevailed for Field A as at the onset of the season. For field B Farmer practice

treatment showed the highest moisture retention capacity (15.4 %) followed by planting pits

(13.5 %) for soil depth of up to 20 cm. At flowering stage, after 390 mm of rainfall in Field A

and 416 mm of rainfall in Field B, the soil moisture distribution was as shown in Fig 16.



(a)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

0 20 40 60

Depth (cm)

Moi

stur

e co

nten

t (%

vol

)

FPPPCR

(b)

10.0

15.0

20.0

25.0

0 20 40 60

Depth (cm)

Moi

stur

e co

nten

t (%

vol

)

FPPPCR

Fig 16: Soil moisture distribution at grain filling stage, (a) Field A, (b) Field B.

For Field A, farmer practice showed the greatest soil retention capacity in the first 10 cm of the

profile (16 %) and the last 20 cm of the profile (28.2 %). Planting pits showed the greatest soil

moisture retention capacity in the middle 10 cm of the profile (21 %). For Field B, both

planting pits and clean ripping showed high soil moisture retention capacity (19.8 % and 20.2

%) while farmer practice had the lowest (18 %).

At Maturity, after 490 mm of rainfall in Field A and 513 mm of rainfall in Field B, the soil

moisture distribution was as shown in Fig 17.

(a)

0.0

5.0

10.0

15.0

20.0

0 20 40 60

Depth (cm)

Moi

stur

e co

nten

t (%

vol

) FPPPCR

b

0.0

5.0

10.0

15.0

20.0

25.0

0 20 40 60

Depth (cm)

Moi

stur

e co

nten

t (%

vol

)

FPPPCR

Fig 18: Soil moisture distribution at maturity (a) Field A, (b) Field B.



For the first 20 cm of the profile in Field A, clean ripping showed the highest soil moisture

retention capacity (12.3 %). Planting pits then showed the greatest capacity for deeper profiles.

As for Field B, there was no significant difference between the three tillage practices at the end

of the season from a statistical analysis.

For both soil types, FP and PP took long to drain as compared to CR. Soil moisture content

readings taken less than 24 hours after a rainfall event showed higher moisture content readings

in the first 20 cm for FP and PP. With CR, higher moisture content readings were recorded in

profiles deeper than 20 cm. Thus rip lines facilitate the infiltration of water vertically with little

lateral movement.

5.4 Evapotranspiration The output from the CROPWAT model is summarized in appendix 5. The total

evapotranspiration in Field A was estimated to be 174 mm. This is a low value compared to

potential evapotranspiration figures (203 mm) estimated using long term averages of the

nearest weather station. This is 36 % of the total rainfall received in this field. For Field B, The

total evapotranspiration was estimated to be 190 mm. This is 38 % of the total rainfall received

in the field.

5.5 Change in storage The soil moisture content of the two fields was measured at the start and at the end of the

growing season. Figure 18 shows the results of those measurements. The area bound between

the curve of moisture content against depth at the beginning and end of the season is the depth

of water stored in the root zone. This however does not close the water balance as parameters

such as run on, evapotranspiration and run off were not measured but empirically determined.

Table 5 shows the summary of the change in storage for the different treatments.



Table 6: Soil water storage in the different treatments

Treatment FPA PPA CRA FPB PPB CRB

Soil water storage (mm) 31 32 34 75 88 81

Overall Field B had the greatest change in storage. For Field A clean reaping had the biggest

change in storage followed by planting pits and lastly farmer practice. For Field B planting pits

had the largest change in storage, followed by farmer practice and lastly clean ripping. Fig 18 is

a graphical representation of the change in storage in the different treatments.

0.0

5.0

10.0

15.0

20.0

0 20 40 60

Depth (cm)

Moi

stur

e co

nten

t (%

vol) Initial FPA

Final FPA

0.0

5.0

10.0

15.0

20.0

25.0

0 10 20 30 40 50

Depth (cm)

Moi

stur

e co

nten

t (%

vol) initial FPB

Final FPB

(a) Moisture storage FPA (b) Moisture storage FPB

0.0

5.0

10.0

15.0

20.0

0 10 20 30 40 50Depth (cm)

Moi

stur

e co

nten

t (%

vol) Initial PPA

Final PPA

0.0

5.0

10.0

15.0

20.0

25.0

0 20 40 60

Depth (cm)

Moi

stur

e co

nten

t (%

vol) Initial PPAB

Final PPB

(c) Moisture storage PPA (d) Moisture storage PPB



0.0

5.0

10.0

15.0

20.0

0 20 40 60

Depth (cm)

Moi

stur

e co

nten

t (%

vol)

Initial RLA

Final RLA

0.0

5.0

10.0

15.0

20.0

0 10 20 30 40 50

Depth (cm)

Moi

stur

e co

nten

t (%

vol) Initial CRB

Final CRB

(c) Moisture storage CRA (d) Moisture storage CRB

Fig 18: Change in storage for the different treatments

5.6 Runoff From the water partitioning model, run off was found to be 98 mm for Field A and 103 mm for

Field B (Table 14a and 14b).

5.7 Deep drainage Deep drainage was evaluated as outlined in section 4.4.4.4. There was no deep drainage in clay

loam soils. In sandy silt loams planting pits recorded the highest deep drainage followed by

clean ripping and lastly farmer practice. A total of 27 mm was recorded as deep drainage in this

soil type. A summary of the results is presented in Table 6.

Table 7: Deep drainage in the different treatments.

Treatment FPA PPA CRA FPB PPB CRB

Deep drainage (m3) 4 15 8 0 0 0



5.8 Yield A summary of the yields produced in the different treatments is shown in Fig 19. For Field A,

Farmer practices produced a yield of 700 kg ha-1, planting pits produced 1816 kg ha-1 and clean

ripping produced 1649 kg ha-1. In Field B, Farmer practices produced 525 kg ha-1, planting pits

produced 798 kg ha-1 and clean ripping produced 662 kg ha-1.

Planting pits produced the greatest yield for both soil types followed by clean ripping and lastly

farmer practice. Comparing the two soil types, yields in the sandy silt loam soils were higher

than yields in the clay loam soils. There were two treatments for which the yield was more than

1 t ha-1. These were FPA and PPA. Yields were generally low (below 1 t ha-1) for the rest of the

treatments ranging between 500 kg ha-1 and 800 kg ha-1.

0200400600800

100012001400160018002000

FP PP CR

Treatment

Yie

ld (K

g /h

a)

Field A Field B

Fig 19: Summary of yield for the different treatments.



CHAPTER 6: ANALYSIS AND DISCUSSION OF RESULTS

6.1 Rainfall The rainy season for the study fields started on the 26th of November 2005. Rainfall records

show that the season started earlier than normal. The normal start of the season in the area is

mid December. The amount however was not sufficient for germination so it was not advisable

to plant then. The amount of rainfall which can sustain germination in the area is 30mm

according to the District Arex Office. Although dry planting is recommended in low rainfall

areas such as the study site, farmers were not willing to do this as they had experienced drought

for the past three years and could not afford to lose their seed should another drought occur.

The total rainfall of 490 mm in Field A and 513 mm in Field B recorded during the growing

season was above normal for the study area. The mean annual rainfall for the whole catchment

is only 350 mm a-1. Conservation agriculture techniques are normally employed in cases of low

rainfall to fully utilize the little rainfall received as well as sustain the crop during long periods

of dry spells (SIWI, 2001). February recorded the highest rainfall with Field A recording 167

mm m-1 and Field B recording 182 mm m-1. This scenario was favorable as the maize crop was

in its flowering and grain filling stages.

The daily as well as total rainfall figures show spatial variability in the distribution of rainfall in

the area. Although the two study fields lie in the same subcatchment and are only 800m apart,

there was never a time when the rain gauges recorded the same rainfall throughout the growing

season.

The daily precipitation figures show two periods of prolonged dry spells of more than two

weeks. The first was observed between the 25th of December 2005 and the 9th of January 2006



i.e. 16 days. The second was observed between the 25th of January and the 7th of February

2006. Reference is made here of 14 days and above because it has been shown that dry spells

lasting more than 14 days are detrimental to the growth of grain crops. Such prolonged dry

spells cause a severe depletion of the plant available moisture content causing an agricultural

drought (Rockström 2003). This agricultural drought is caused by poor plant water availability

related to low rainfall infiltration and poor soil moisture holding capacity of the soil.

In this study, it was observed that these prolonged dry spells did not have a severe effect in

both Planting pits and rip lines. With conventional farmer practices however, plant leaves

started showing signs of stress 12 days after the last rainfall event. This might have contributed

to the yields of planting pits being higher than farmer practice though farmer practice had the

highest infiltration.

6.2 Infiltration The basic infiltration rate for the two soil types was found to be 12 mm hr-1 for soil A and 7mm

hr-1 for soil B. An analysis of variance was carried out to find out whether there was a

difference between the means of the cumulative infiltration in the three treatments. Table 7

shows a summary of the results of the ANOVA.



Table 8: ANOVA for the cumulative infiltration of the different treatments.

Source of variation Df Ss Ms vr Fpr

Replica stratum

Treatment 2 15441 7720 3.05 0.247

Residual 2 5065 2533 0.94

Replica *units*

Treatment 2 23808 11904 4.4 0.017

Residual 53 143288 2704

Total 59 181331

Since Fpr <0.05 then at least one of the means is significantly different, thus the null hypothesis

was rejected.

Table 9: Standard errors of differences of means and least significant difference

Table Treatment

Replications 20

Df 53

Sed 16.76

LSD 33.62

To test whether there was a significant difference between the means of the cumulative

infiltration of the 2 soil types, a 2 tailed, 2 sample paired, T- test, was carried out and the results

are presented in Table 9



Table 10: Results of a 2 tailed, 2 sample, paired, T- test of cumulative infiltration

Sample Size Mean Variance Standard Standard error of

Deviation Mean

Cum_Inf_ A 60 59.57 3073 55.44 7.157

Cum_Inf_B 60 61.17 1647 40.48 5.239

95% confidence interval for difference in means: (-19.19, 15.97) Test of null hypothesis that mean of Cum_Inf_A is equal to mean of Cum_inf_B Test statistic t = -0.18 on approximately 108.12 d.f. Probability = 0.857 Since the probability is more that 0.5 the null hypothesis is accepted.

The basic infiltration rate of a given soil type does not change with tillage practice. What

changes is the time taken to reach that rate (Cook, 1994). As highlighted in section 2.6.5, the

sorptivity factor is the one that causes variation of the infiltration rate in the initial stages of

water application (Cook and Broeren, 1994). The gravity factor is constant for a given soil type.

At the onset of the season, it took long to reach the steady state infiltration rate for all the tillage

practices in both soil types. The sorptivity factor was predominant then. The order of time

taken to reach the basic infiltration rate for the three tillage practices is FP, PP, CR in

descending order. What this implies is that when a storm of high intensity occurs, plots with

soils which reach the basic infiltration rate quickly will generate more runoff than plots with

soils which reach the basic infiltration rate slowly. Such storms however were very rare in the

study area. This meant that low intensity storms were beneficial to PP and CR since water



which infiltrated into deeper layers was not prone to evaporation. This was due to the minimum

area of disturbed soil.

As the season progressed, the gravity factor became dominant reducing the time taken to reach

the basic infiltration rate for all treatments. The constant time taken by CR to reach the basic

infiltration rate is explained by the fact that there is minimum disturbance of a greater area of

the soil in these plots. The pore size of the soils in these plots remains the almost the same

throughout the growing season (Parr, 1990). From the onset, the soil in these plots display

constant infiltration characteristics (between 0.2 and 0.4 mm hr-1 at a negative suction head of

10 mm).

Ideally rip lines were not supposed to be weeded but as the season progressed it was observed

that weeds in these plots were outgrowing the maize crop. To ensure that the crop was

harvested at the end of the season, weeding was instituted.

6.3 Soil Moisture Content An analysis of variance was carried out to see whether there was a significant difference

between the means of the soil moisture content readings in the different treatments. The results

of the ANOVA and the standard error of the differences and least significant differences are

presented in Tables 10 and 11 respectively.



Table 11: ANOVA for the moisture content of the different treatments.


Replica stratum 2 100.72 50.36 0.76

Replica *units*stratum

Treatment 2 30.57 15.29 0.23 0.794

Residual 211 13967.53 66.2

Total 215 14098.81

The results show that there is no significant difference in the soil moisture retention in the three

treatments as Fpr = 0.794 (>0.005). Thus the null hypothesis is accepted.

Table 12: Standard errors of differences of mean and least significant difference.

Table Treatment

Replications 70

Df 211

Sed 1.356

LSD 2.673

To find out whether there was a difference between the means of the soil moisture retention

capacity of the two soil types a two tail, two sample, T-test was carried out. The results are

presented in Table 12



Table 13: Results of a 2 tailed, 2 sample paired, T- test of moisture content

Sample Size Mean Variance Standard Standard error of

Deviation Mean

Cum_Inf_ A 216 14.71 65.58 8.098 0.551

Cum_Inf_B 216 15.44 52.32 7.233 0.4922

Standard error for difference of means 0.7388 95% confidence interval for difference in means: (-2.179, 0.7252) Test of null hypothesis that mean of m_c_A is equal to mean of m_c_B Test statistic t = -0.98 on 430 d.f. Probability = 0.326 Since the probability of the test statistic is less than 0.5, the null hypothesis is rejected. This

means that there is a significant difference between the means of the moisture content retention

of the two soil types.

The initial soil moisture content for the first 20cm was found to be negligible. This must have

been due to successive droughts which occurred for the past four years. The last normal season

for the study area was in 2001.

The difference in moisture content observed in individual fields before the onset of the season

could be a result of soil evaporation after the different tillage techniques were applied to the

soil.

Planting pits showed high moisture retention capacity especially in the first 20cm of the soil

profile. This could be due to the storage effect of planting pits. The planting pits were 20cm

deep after planting and this might have contributed to them retaining more moisture content

than rip lines.



At the end of the season, planting pits showed the greatest soil moisture retention capacity more

in Field A than Field B. The farmer for Field A maintained the original condition of each and

every tillage practice e.g. for planting pits, he made sure that after weeding operations the holes

are maintained as they were originally. This could be the reason why there is a marked

difference in the soil moisture retention capacity in the conservation agriculture treatments in

the two fields.

6.4 Rainfall partitioning A summary of how rainfall was partitioned in each field is presented in tables 14 a and b

Table 14: Summary of rainfall partitioning.

Time step 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 105 days Growth stage

Germination stage Vegetative stage Flowering stage Maturity stage

Rain 37 98 7 10 6 0 26 54 22 0 26 108 37 30 29 490 mm R off 6 15 0 0 0 0 4 8 3 0 4 16 6 5 4 70 mm I 31 83 7 10 6 0 22 46 19 0 22 92 31 26 25 420 mm Sin 0 28 62 100 91 89 76 68 68 74 77 91 90 98 91 Soil moisture 31 66 106 101 102 93 87 87 93 95 108 103 107 96 87 WHC 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 Dp 0 0 6 1 2 0 0 0 0 0 8 3 7 0 0 27 mm ET 3 4 6 10 13 17 19 19 19 18 17 13 9 5 1 174 mm Sout 28 62 100 91 89 76 68 68 74 77 91 90 98 91 86

(a) Field A

Time step 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 105 days Growth stage

Germination stage Vegetative stage Flowering stage Maturity stage

Rain 46 95 10 10 6 0 29 60 5 0 25 115 49 27 21 498 mm R off 9 19 2 2 1 0 6 12 1 0 5 23 10 5 4 100 mm I 37 76 8 8 5 0 23 48 4 0 20 92 39 22 17 398 mm Sin 0 31 70 95 78 73 65 59 74 73 74 72 79 78 82 Soil moisture 34 73 100 89 87 83 78 93 92 92 90 97 91 91 72 WHC 120 120 120 120 120 120 120 120 120 120 120 120 120 120 120 Dp 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 mm ET 3 3 5 11 14 18 19 19 19 18 18 18 13 9 1 190 mm Sout 31 70 95 78 73 65 59 74 73 74 72 79 78 82 71

(b) Field B



Evapotranspiration values obtained from the CROPWATT model are in agreement with

experimental values obtained by Wallace (1997) and (Walker 2003). They estimate the figure

at between 30 and 40% of the total rainfall received. Deep drainage occurred in Field A only.

This could be a result of the soil texture in this field. The pore size distribution of sandy silt

loams promotes drainage. Whenever the field capacity of these soils is exceeded it is easy for

the excess water to percolate beyond the root zone. With clay loams however, adhesion forces

between soil and water particles promote storage rather than drainage. This could be the reason

why there was no deep drainage recorded in Field B. The strong adhesion forces could have

impacted negatively on plant water uptake as more energy is required by the roots to extract

this water from the soil.

6.5 Yield An analysis of variance was carried out to find out whether there was a significant difference

between the means of the different treatments. The analysis is presented in Table 13 below.

Table 15: ANOVA for the yield in different treatments


Block stratum 2 560050 280025 2.54

Block *units*stratum

Treatment 2 421973 210986 1.92 0,261

Residual 4 440627 110157

Total 8 1422650

Since Fpr >0.05 the null hypothesis is accepted.



The high yield from planting pits in both fields could be a result of the observed soil moisture

retention capacity of these planting pits. Comparing the two soil types, yields in the sandy silt

loam soils were higher than yields in the clay loam soils. The clay loam soils were shallow as

compared to the sandy silt loams. This might have hindered root development thus limiting the

depth to which the roots could tap water.

Yields were generally low (below 1t/ha). As regards rainfall, the area received above normal

rains so water could not be the limiting factor. The limiting factor during this study could

therefore be other factors than water, especially nutrients. However, the fertilizer application

rate used was found to be suitable for the low income communal farmers in the area.



CHAPTER 7: CONCLUSIONS AND RECOMMENDATIONS

From the study, and in relation to the objectives set, it can be concluded that:

1. Comparing the two soil types though, it can be concluded that there is a

significant difference between the cumulative infiltration in sandy silt loam soils and

clay loam soil. Sandy silt loams have higher infiltration capacity than clay loam

soils.

2. The cumulative infiltration is highest in planting pits followed by farmer practice

and lastly clean ripping. The above normal season could be the reason why farmer

practices recorded more infiltration than clean ripping. However, statistically, the

cumulative infiltration did not differ significantly with the type of tillage practiced.

3. Clean ripping displayed the highest soil moisture retention capacity followed by

planting pits and lastly farmer practices. However, statistically, there was no

significant difference in the soil moisture retention capacity of the three

tillage practices. There is a significant difference in the soil moisture retention

capacity of the two soil types. Clay loam soils exhibited higher soil moisture

retention capacity than sandy silt loam soils.

4. Highest yields were realized in planting pits followed by clean ripping and lastly

Farmer practice though statistically there is no difference in the yields realized in the

three treatments for the same soil type. Comparing the two soil types, the highest

yields were realized in the sandy silt loam soil.



Recommendations

From the study, the following recommendations are made

1. Although weeding is not encouraged in conservation agriculture, during the first year of

practicing it, weeding is inevitable. This has to be timeously to reduce competition for the little

available soil water. The first weeding should be done two weeks after emergence as this is the

period which showed the greatest weed infestation particularly in the clean ripping treatment.

2. Further studies in the methods of partitioning rainfall to be carried out in order to assess what

actually goes to transpiration. Furthermore, temporal variation of soil moisture is better

measured by tensiometers as these are placed permanently on a particular sampling site.

Augering introduces soil disturbance and accumulation of soil moisture in the resulting holes

which might distort soil moisture distribution in the field. Also, this type of study should be

carried over to subsequent seasons to find out how the weeding problem, yields, infiltration and

soil moisture retention improve over seasons.

3. Although clean ripping provides for timely planting, the heavy weed infestation in the early

stages of plant growth provides a challenge to farmers in the form of frequent weeding

operations. It is recommended that farmers in the study area adopt planting pits as a

conservation agriculture practice as it produced the highest yields. This technique however is

labor intensive especially if the farmer is to maintain the planting pits in their original state.

4. Further studies in an integrated approach to water and nutrient management to realize

the full potential of conservation agriculture is recommended. Conservation agriculture takes

care of soil water management but to realize a much beneficial yield, the level of fertilizer

application should be studied to find the optimum level. This should be done together with the

financial implications on the small holder farmer.



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Butler, S.S. 1957. Engineering Hydrology, Prentice Hall, Engle wood Cliffs. Casenave, A., and Valentin, C. 1992. A runoff capability classification based on surface features criteria in semi arid areas of West Africa. Journal of hydrology 130, 231-249 conservation agriculture, vol 1. Keynote contributions, 39. FAO, Rome, Italy pp363- 374.

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McKenzie, N. J., Cresswell, H. P., Rath, H., and Jacquier, D. 2001. Measurement of unsaturated hydraulic conductivity, using tension and drip infiltrometers. Australian Journal of Soil Research, 39:823-836.

Mickelson, R.H., Cox M.B. and Musick J. 1965. Runoff water spreading on levelled cropland. J. Soil and Water Cons. 20(2): 57-60.

Mwinjilo, M. L. 1992. Animal traction technology in Malawi: potential and constraints. In "Animal Traction Network for Eastern &Southern Africa (ATNESA)" (P. Starkey, E. Mwenya and J. Stares, eds.). 18-23 January 1992, CTA, GTZ, Lusaka, Zambia.

Nassif, S.H., and Wilson, B.M. 1976 The influence of slope and rain intensity on runoff and infiltration. International Association of hydrological Sciences, 20, No4. Ngigi, S.N. 2003. What is the limit of up scaling rainwater harvesting in a river basin? Physics and Chemistry of the Earth 28, 943-956. Nyagumbo, I. 1992. The influence of socio-economic factors on potential adoption of no-till tied ridging in four communal areas of Zimbabwe. In “Proceedings of the 3rd annual Scientific Conference" (M. Kronen, ed.), pp. 319-329. 5-7 th October 1992, SADC Land and Water Management Research Programme, Harare, Zimbabwe. Nyagumbo, I. 1993. Part II: Farmer Participatory Research in Conservation Tillage: Practical Experiences with no-till tied ridging in Communal Areas lying in the Sub-humid north of Zimbabwe. In "Proceedings. of the 4th.Annual. Scientific. Conference" (M. Kronen, ed.), pp. 236-249. 11-14 October 1993, Sadc Land and Water Management Research Programme, Saccar, P.Bag 00108, Gaborone, Botswana, Windhoek, Namibia. Oldrieve, B. 1993. Conservation farming for communal, small scale, resettlement and co- operative farmers of Zimbabwe. A farm management handbook. Mazongororo Paper Converters (Pvt) Ltd, Zimbabwe p76.



Pacey, A., and Cullis, A. 1986. Rainwater Harvesting - the Collection of Rainfall and Run-off in Rural Areas. Intermediate Technology Publications, London. Parr, J.F., Stewart, B.A., Hornic, S.B., and Singh, R.P. 1990. Improving the sustainability of dry land farming systems: A global perspective In: Singh, R.P., Parr, J.F., and Stewart, B.A. (Eds) Advances in soil science. Vol 13. Dryland agriculture strategies for sustainability New York USA pp 1-8.

Reynolds, W. D., Zebchuck, W. D. 1996. Use of contact material in tension infiltrometer measurements. Soil Technology, 9:141-159.

Riches, C.R., Twomlow, S.J., and Dhliwayo, H., 1997. Low-input weed management and conservation tillage in semi-arid Zimbabwe. Experimental Agriculture 33, 173-187.,

Rockström, J. 2003. Resilience building and water management for drought mitigation. Physics and Chemistry of the Earth 28, 869-877. Rockström, J., Barron, J., and Fox, P. 2002. Rainwater management for increased productivity among smallholder farmers In: drought prone environments. Physics and Chemistry of the Earth 27, 949-959. Rockström, J. 2001. Green water security for food makers of tomorrow: windows of opportunity in drought prone savannahs. Water Science Technology 43 (4), 71-78. Rockström, J. 2001. Water-Balance Accounting for designing and planning rainwater-harvesting systems for supplementary irrigation. Working Paper No. 14. Regional Land Management Unit, Sida. Rockström, J., Kambutho, P., Mwalley, P., Temesgen, M. 2001. Conservation farming among smallholder farmers in Eastern and Southern Africa: Adapting and adopting innovative land management options in: Conservation agriculture, a worldwide Rockström, J. 2000. Water resources management in smallholder farms in Eastern and Southern Africa: an overview. Physics and chemistry of the Earth. Part B: Hydrology, Oceans and atmosphere 25 (3), 279-288. Rockström, J. 1997. On Farm Agrohydrilogical Analysis of the Sahelian Yield crisis: Rainfall partitioning, soil nutrients and water use efficiency of Pearl Millet. PhD. Thesis, University of Stockholm, Sweden. SADC. 1995. Consultancy report on long-term strategy for regional Research Priorities on Food, Agriculture and Natural Resources in the Southern African Development Community (SADC). SIWI, 2001. Water harvesting for upgrading rain fed agriculture: Problem analysis and research needs SIWI report No 11. Stockholm International Water Institute (SIWI), Stockholm, Sweden. P97.



Shumba, E. M., Waddington, S. R., and Rukuni, M. 1992. Use of tine tillage with attrazine weed control to permit earlier planting of maize by small-holder farmers in Zimbabwe. Experimental Agriculture 28, 443-452. Unganani, L.S. 1996. Historic and future climatic changes in Zimbabwe. Climate Research 6, 137-145. Walker, S., and Ogindo, H.O. 2003. The water budget of rain fed maize and bean inter intercrop. Physics and Chemistry of the Earth 28, 919-926. Wallace, J.S., and Batchelor, C.H. 1997. Managing water resources for crop production. Philosophical transactions of the Royal Society of London 352 (13), 937-947). Wallace, J.S. 2000. Increasing agricultural water use efficiency to meet future food production. Agriculture, ecosystems and environment 82, 105-119. Waternet proposal (CN133), IWRM for Improved Rural Livelihoods, Limpopo Basin, Final proposal, 9 September 2003.

White, I., Sully, M.J. and Perroux, K.M. 1992. Measurement of Surface-Soil Hydraulic Properties: Disk Permeameters, Tension Infiltrometers and Other Techniques. In Topp, G.C., Reynolds, W.D. and Green, R.E.( Eds). Advances in Measurement of Soil Physical Properties: Bringing Theory into Practice. Soil Science Society of America. Special Publication Number 30. Madison: 69-105.

West, L.T., Chiang, S.C. and Norton, L.D. 1992. The morphology of surface crusts. In Soil crusting. Chemical and physical processes (Eds). Wilson, E.M. 1969. Engineering Hydrology Macmillan Education Ltd Houndmills, Basingstroke, Hampshire. World Bank, 1997. World Development report. World Bank, Washington, DC.



CHAPTER 9: APPENDICES Appendix 1. Collected rainfall data Field A Rainfall Field B Rainfall Precipitation (mm) Precipitation (mm) Day Oct Nov Dec Jan Feb Mar Day Oct Nov Dec Jan Feb Mar 1 14 30 1 19 27 2 19 2 21 3 31 3 30 4 13 22 4 12 21 5 21 5 18 6 10 6 9 7 7 8 4 15 8 5 17 9 7 9 8 10 4 11 32 10 6 13 38 11 3 15 52 11 4 16 55 12 6 12 7 7 13 4 7 13 3 14 3 14 2 15 16 11 15 18 10 16 3 16 5 17 17 18 18 18 19 19 17 19 18 20 10 4 20 10 21 13 20 21 15 23 22 17 22 19 23 23 24 9 24 5 25 25 26 4 6 26 6 6 27 27 28 28 29 29 30 19 30 21 31 31 Total 23 135 102 167 63 490 27 140 109 182 55 513


- 69 -Wrem MSc Thesis Clever Taurayi Dhliwayo June 2006

Appendix 2 Infiltration measurements

Site Identity Field A Site Identity Field A Site Identity Field ASoil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 12/19/2005 Date 12/19/2005 Date 12/19/2005

Time Level

(mm) Time Level (mm) Time Level

(mm) (min) Set 1 Set 2 Set

3 Set 4 Set 5 (min) Set 1 Set 2 Set 3 Set 4 Set 5 (min) Set 1 Set 2 Set 3 Set 4 Set 5

0 1 130 278 358 0 2 76 172 239 289 0 1 12 27 95 1340.5 10 150 287 376 0.5 13 102 181 251 310 0.5 1 19 39 146

1 24 167 295 392 1 21 115 188 258 325 1 1 21 46 105 1551.5 37 182 302 406 1.5 28 127 193 263 340 1.5 1 22 53 109 162

2 48 197 309 419 2 34 137 199 269 352 2 3 23 58 112 1762.5 57 210 315 431 2.5 40 147 204 274 364 2.5 4 24 63 116 182

3 67 222 320 440 3 46 157 209 279 376 3 5 25 68 120 1883.5 77 235 326 452 3.5 51 167 213 284 388 3.5 6 26 72 123 193

4 83 246 331 463 4 57 177 219 289 400 4 7 27 76 126 2004.5 92 257 336 472 4.5 63 187 224 294 412 4.5 8 27 81 129 205

5 100 268 340 482 5 70 197 229 299 424 5 9 28 85 132 2095.5 109 279 344 491 5.5 76 207 234 304 436 5.5 10 28 88 135 213

6 115 290 349 500 6 82 217 239 309 448 6 11 28 92 138 2166.5 121 301 353 509 6.5 88 227 244 314 460 6.5 12 29 95 141 219

7 127 312 357 518 7 94 237 249 319 472 7 13 29 98 144 2227.5 133 323 361 527 7.5 100 247 254 324 484 7.5 14 29 101 147 225

8 139 334 365 536 8 106 257 259 329 496 8 15 30 104 150 2288.5 145 345 369 545 8.5 112 267 264 334 508 8.5 16 30 107 153 231

9 151 356 373 554 9 118 277 269 339 520 9 17 30 110 156 2349.5 157 367 377 563 9.5 124 287 274 344 532 9.5 18 31 113 159 23710 163 378 381 572 10 130 297 279 349 544 10 19 31 116 162 240



Site Identity Field A Site Identity Field A Site Identity Field A profile profile profile precipitation precipitation precipitation Soil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 1/12/2006 Date 1/12/2006 Date 1/12/2006 Time Level (mm) Time Level (mm) Time Level (mm)

(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5

0 2 58 110 159 194 0 1 32 2 67 3 0 0 25 37 51 89 0.5 15 67 118 166 200 0.5 12 43 18 92 7 0.5 15 31 44 60 101

1 24 72 123 169 205 1 14 51 21 115 13 1 18 32 45 65 110 1.5 30 77 127 171 208 1.5 16 59 25 138 18 1.5 20 33 47 70 118

2 35 80 132 174 211 2 19 69 29 162 23 2 21 34 48 80 125 2.5 40 84 136 176 212 2.5 22 79 32 183 29 2.5 22 35 49 85 131

3 44 88 139 179 215 3 25 89 35 206 34 3 23 36 50 90 139 3.5 47 92 142 180 218 3.5 28 99 39 226 40 3.5 24 37 51 95 144

4 50 94 146 183 221 4 31 109 42 250 45 4 25 38 52 100 151 4.5 53 97 149 185 224 4.5 34 119 46 271 50 4.5 26 39 53 105 155

5 56 100 152 187 227 5 37 129 50 292 56 5 27 40 54 110 160 5.5 59 103 155 189 230 5.5 40 139 54 313 61 5.5 28 41 55 115 165

6 62 106 158 191 233 6 43 149 57 334 67 6 28 41 56 120 170 6.5 65 109 161 193 236 6.5 46 159 61 72 6.5 29 42 57 125 175

7 68 112 164 195 239 7 49 169 64 78 7 29 43 58 130 180 7.5 71 115 167 197 242 7.5 52 179 67 84 7.5 30 44 59 135 185

8 74 118 170 199 245 8 55 189 70 90 8 30 45 60 140 190 8.5 77 121 173 201 248 8.5 58 199 73 96 8.5 30 45 60 145 195

9 80 124 176 203 251 9 61 209 76 102 9 31 46 61 150 200 9.5 83 127 179 205 254 9.5 64 219 79 108 9.5 31 46 61 155 205 10 86 130 182 207 257 10 67 229 82 114 10 31 46 62 160 210




(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5

0 11 3 2 4 5 0 2 51 69 127 4 0 2 20 39 62 131 0.5 40 34 40 47 29 0.5 6 57 89 147 27 0.5 4 23 47 76 157

1 71 55 68 71 43 1 10 58 96 154 43 1 6 25 50 83 174 1.5 100 73 91 92 55 1.5 12 60 100 160 57 1.5 7 26 54 99 190

2 129 89 114 113 66 2 16 61 104 166 71 2 9 27 58 102 206 2.5 159 107 136 134 77 2.5 19 62 107 172 85 2.5 11 29 62 108 222

3 189 124 156 155 88 3 2 63 111 177 98 3 13 30 65 112 240 3.5 199 140 176 176 99 3.5 24 64 114 181 111 3.5 15 31 68 116 256

4 209 157 196 197 110 4 26 65 117 186 125 4 17 32 71 120 272 4.5 219 173 216 218 121 4.5 29 66 120 191 138 4.5 19 34 74 124

5 229 189 236 239 132 5 33 67 123 196 151 5 21 35 76 128 5.5 239 205 256 260 143 5.5 35 68 126 202 158 5.5 23 36 78 132

6 249 221 276 281 154 6 38 69 129 207 164 6 25 37 80 136 6.5 259 237 296 302 165 6.5 40 69 132 212 170 6.5 27 38 82 140

7 269 253 316 323 176 7 43 70 135 217 176 7 29 39 84 144 7.5 279 269 336 344 187 7.5 46 70 138 222 182 7.5 31 40 86 148

8 289 285 356 365 198 8 49 71 141 227 188 8 33 41 88 152 8.5 299 301 376 386 209 8.5 52 71 144 232 194 8.5 35 42 90 156

9 309 317 396 407 220 9 55 72 147 237 200 9 37 43 92 160 9.5 319 333 416 428 231 9.5 58 72 150 242 206 9.5 39 44 94 164 10 329 349 436 449 242 10 61 73 153 247 212 10 41 45 96 168




(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5

0 3 2 3 3 2 0 0 40 95 5 1 0 2 22 3 4 3 0.5 28 22 40 35 27 0.5 10 54 115 26 16 0.5 30 14 15 21

1 47 40 64 56 1 15 60 127 40 28 1 4 35 21 27 33 1.5 66 55 85 78 60 1.5 20 65 137 54 39 1.5 6 39 26 37 44

2 82 70 106 98 74 2 25 69 145 66 49 2 8 43 32 48 54 2.5 97 84 124 113 89 2.5 30 73 154 78 59 2.5 10 46 38 57 64

3 113 97 143 131 100 3 35 76 162 91 69 3 11 50 42 67 74 3.5 128 111 161 148 112 3.5 40 79 170 103 109 3.5 12 52 48 77 84

4 143 124 178 165 122 4 45 83 177 113 149 4 14 55 52 87 94 4.5 157 137 195 181 133 4.5 50 86 185 126 189 4.5 15 57 56 97 104

5 172 150 212 196 146 5 55 89 193 136 229 5 17 59 60 107 114 5.5 186 163 229 211 156 5.5 60 92 200 147 269 5.5 18 61 64 117 124

6 200 176 246 225 167 6 65 95 206 157 309 6 20 63 68 127 134 6.5 215 189 263 240 178 6.5 70 98 212 168 349 6.5 21 65 72 137 144

7 229 202 280 255 189 7 75 101 218 179 389 7 22 67 76 147 154 7.5 243 215 297 270 198 7.5 80 104 224 190 429 7.5 23 69 80 157 164

8 257 228 314 285 210 8 85 107 232 200 469 8 24 71 84 167 174 8.5 271 241 331 300 219 8.5 90 110 240 210 509 8.5 25 73 88 177 184

9 285 254 348 315 230 9 95 113 246 220 549 9 26 75 92 187 194 9.5 299 267 365 330 240 9.5 100 116 252 230 589 9.5 27 77 96 197 204 10 313 280 382 345 250 10 105 119 259 240 629 10 28 79 100 207 214



Site Identity Field A Site Identity Field A Site Identity Field A profile profile profile precipitation precipitation precipitation Soil type Soil type Soil type Sandy loam Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 1/23/2006 Date 1/23/2006 Date 1/23/2006 Time Level (mm) Time Level (mm) Time Level (mm)

(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5

0 3 4 4 3 4 0 5 30 82 4 2 0 0 9 92 9 6 0.5 26 46 38 74 38 0.5 7 39 99 36 35 0.5 3 28 109 46 52

1 40 79 45 131 56 1 11 41 105 60 62 1 4 38 118 60 75 1.5 54 110 61 187 70 1.5 14 45 111 83 81 1.5 5 46 124 71 89

2 66 140 77 228 83 2 17 48 116 104 100 2 5 54 128 79 102 2.5 79 170 93 274 94 2.5 21 51 122 124 118 2.5 6 62 132 86 13

3 91 200 109 315 104 3 24 54 127 142 133 3 6 68 136 93 122 3.5 102 230 125 355 114 3.5 27 56 132 160 148 3.5 7 74 140 100 133

4 115 260 142 395 123 4 30 59 136 177 164 4 7 80 144 106 143 4.5 127 290 158 335 132 4.5 33 61 140 195 178 4.5 7 86 148 110 151

5 138 320 175 345 141 5 36 64 144 210 192 5 7 92 152 116 159 5.5 150 350 182 355 149 5.5 39 66 149 227 204 5.5 7 98 156 121 167

6 161 380 189 365 158 6 42 69 152 243 218 6 7 104 160 127 175 6.5 173 410 196 375 166 6.5 45 71 156 259 231 6.5 7 110 164 132 183

7 184 440 203 385 174 7 48 73 160 273 243 7 8 116 168 138 191 7.5 195 470 210 395 182 7.5 51 76 164 289 256 7.5 8 122 172 141 199

8 206 500 217 405 190 8 54 78 168 304 268 8 8 128 176 147 207 8.5 217 530 224 415 198 8.5 57 80 172 319 274 8.5 8 134 180 152 215

9 228 560 231 425 206 9 60 82 176 333 280 9 8 140 184 157 223 9.5 239 590 238 435 214 9.5 63 84 180 347 286 9.5 8 146 188 162 231 10 250 620 245 445 222 10 66 86 184 361 292 10 8 152 192 167 239



Site Identity Field A Site Identity Field A Site Identity Field A profile profile profile precipitation precipitation precipitation Soil type Soil type Soil type Sandy loam Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 1/25/2006 Date 1/25/2006 Date 1/25/2006 Time Level (mm) Time Level (mm) Time Level (mm)

(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5

0 1 3 5 5 5 0 4 2 43 15 35 0 0 9 92 9 6 0.5 12 24 14 33 19 0.5 7 14 54 28 51 0.5 3 28 109 46 52

1 23 49 24 59 1 9 17 56 35 66 1 4 38 118 60 75 1.5 34 73 34 82 42 1.5 12 19 58 43 74 1.5 5 46 124 71 89

2 45 96 44 102 52 2 14 23 60 49 81 2 5 54 128 79 102 2.5 56 119 54 121 62 2.5 17 25 62 56 88 2.5 6 62 132 86 113

3 67 140 63 140 71 3 19 28 65 62 95 3 6 68 136 93 122 3.5 77 161 72 159 79 3.5 21 67 68 101 3.5 7 74 140 100 133

4 87 184 81 177 87 4 23 32 69 71 107 4 7 80 144 106 143 4.5 92 205 90 194 94 4.5 25 34 71 73 114 4.5 7 86 148 110 151

5 102 227 99 213 101 5 27 36 73 79 120 5 7 92 152 116 159 5.5 112 248 108 230 108 5.5 29 38 75 85 127 5.5 7 98 156 121 167

6 122 269 117 247 115 6 31 40 77 90 132 6 7 104 160 127 175 6.5 132 290 125 264 121 6.5 33 42 79 95 137 6.5 7 110 164 132 183

7 142 310 134 281 127 7 35 44 81 101 143 7 8 116 168 138 191 7.5 152 330 142 288 134 7.5 37 46 83 106 148 7.5 8 122 172 141 199

8 162 350 150 295 140 8 39 48 85 111 152 8 8 128 176 147 207 8.5 172 370 159 302 146 8.5 41 50 87 116 156 8.5 8 134 180 152 215

9 182 380 167 309 152 9 43 52 89 121 160 9 8 140 184 157 223 9.5 192 390 175 316 158 9.5 45 54 91 126 164 9.5 8 146 188 162 231 10 202 400 183 323 164 10 47 56 93 131 168 10 8 152 192 167 239



Site Identity Field A Site Identity Field A Site Identity Field A profile profile profile precipitation precipitation Weeding precipitation Soil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 1/29/2006 Date 1/29/2006 Date 1/29/2006 Time Level (mm) Time Level (mm) Time Level (mm)

(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5

0 6 5 5 4 3 0 1 3 9 6 0 0 9 27 8 6 4 0.5 14 34 17 27 22 0.5 18 22 22 23 29 0.5 17 35 21 23 29

1 25 58 31 51 41 1 34 35 39 41 50 1 20 40 29 34 45 1.5 35 79 45 75 58 1.5 59 42 50 59 70 1.5 21 45 36 44 56

2 45 101 58 92 72 2 76 50 59 75 89 2 22 50 42 53 66 2.5 55 123 71 116 87 2.5 92 59 69 90 106 2.5 24 55 48 60 75

3 64 145 84 135 100 3 109 69 78 106 121 3 25 60 52 68 83 3.5 73 165 96 154 114 3.5 125 78 8 121 138 3.5 26 65 58 74 91

4 82 186 107 171 127 4 141 87 95 136 154 4 27 70 62 81 99 4.5 91 206 119 188 140 4.5 155 95 103 154 170 4.5 28 75 68 87 107

5 100 227 133 204 153 5 169 103 111 166 185 5 29 80 72 93 114 5.5 108 247 144 20 166 5.5 183 111 117 174 199 5.5 30 85 76 99 120

6 116 267 155 237 179 6 197 119 129 182 23 6 31 90 81 105 128 6.5 124 287 167 252 192 6.5 210 129 138 190 227 6.5 32 95 85 111 133

7 132 297 178 268 205 7 223 139 147 198 241 7 33 100 89 115 141 7.5 140 307 189 283 218 7.5 236 149 156 206 254 7.5 34 105 93 119 147

8 148 317 201 299 231 8 249 159 165 214 267 8 35 110 97 123 153 8.5 156 327 212 314 244 8.5 262 169 174 222 280 8.5 36 115 101 127 159

9 164 337 223 328 257 9 275 179 183 230 293 9 37 120 105 131 165 9.5 172 347 234 342 270 9.5 288 189 192 238 306 9.5 38 125 109 135 171 10 180 357 245 356 283 10 301 199 201 246 319 10 39 130 113 139 177



Site Identity Field A Site Identity Field A Site Identity Field A profile profile profile Coordinates Coordinates Coordinates Soil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 14/02/06 Date 14/02/06 Date 14/02/06 Time Level (mm) Time Level (mm) Time Level (mm)

(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5

0 4 2 3 5 0 6 4 4 7 6 0 11 23 9 11 7 0.5 9 2 3 15 0.5 8 5 12 15 14 0.5 13 37 16 16 14

1 13 2 8 20 1 11 5 20 22 18 1 14 48 21 19 19 1.5 18 3 12 25 1.5 18 6 28 28 22 1.5 15 57 25 22 23

2 22 5 16 29 2 20 7 35 33 26 2 16 66 29 24 27 2.5 27 7 20 34 2.5 22 8 43 38 30 2.5 16 75 32 27 31

3 31 9 24 38 3 25 9 50 43 34 3 17 83 35 30 35 3.5 35 29 42 3.5 27 10 56 48 38 3.5 17 91 38 32 39

4 39 12 32 46 4 29 11 63 53 42 4 18 97 41 34 43 4.5 43 14 37 50 4.5 32 12 70 58 46 4.5 18 104 44 37 47

5 47 15 40 54 5 34 13 77 63 50 5 19 111 47 39 51 5.5 51 18 44 58 5.5 36 14 84 68 54 5.5 19 117 50 41 55

6 55 21 48 62 6 38 15 91 73 58 6 20 123 53 43 59 6.5 59 24 52 66 6.5 40 16 98 78 62 6.5 20 129 56 45 63

7 63 27 56 70 7 42 17 105 83 66 7 21 135 59 47 67 7.5 67 30 60 74 7.5 44 18 112 88 70 7.5 21 141 62 49 71

8 71 33 64 78 8 46 19 119 93 74 8 22 147 65 51 75 8.5 75 36 68 82 8.5 48 20 126 98 78 8.5 22 153 68 53 79

9 79 39 72 86 9 50 21 133 103 82 9 23 159 71 55 83 9.5 83 42 76 90 9.5 52 22 140 108 86 9.5 23 165 74 57 87 10 87 45 80 94 10 54 23 147 113 90 10 24 171 77 59 91



Site Identity Field A Site Identity Field A Site Identity Field A profile profile profile Coordinates Coordinates Coordinates Soil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 24/02/2006 Date 24/02/2006 Date 24/02/2006 Time Level (mm) Time Level (mm) Time Level (mm)

(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5

0 6 5 4 8 2 0 1 4 2 3 0 2 15 6 0 7 0.5 12 10 15 14 11 0.5 2 4 10 12 0.5 2 22 20 9 16

1 19 15 22 17 17 1 3 4 11 17 1 2 27 25 13 20 1.5 26 20 28 21 21 1.5 4 5 14 21 1.5 2 30 28 17 23

2 33 25 35 24 25 2 5 6 17 25 2 3 34 31 20 25 2.5 39 30 41 27 30 2.5 5 7 20 30 2.5 3 37 33 23 27

3 46 35 48 30 34 3 6 8 23 34 3 4 40 36 25 29 3.5 53 40 54 32 39 3.5 7 9 26 37 3.5 4 43 37 27 31

4 60 45 60 35 43 4 8 10 29 40 4 4 46 39 29 33 4.5 67 50 66 38 47 4.5 9 11 32 44 4.5 5 49 41 31 35

5 74 55 73 41 51 5 9 12 35 47 5 5 52 43 33 37 5.5 81 60 79 44 55 5.5 10 13 38 51 5.5 6 55 45 35 39

6 88 65 85 47 59 6 11 14 41 54 6 6 58 47 37 41 6.5 95 70 91 50 63 6.5 12 15 44 57 6.5 7 61 49 39 43

7 102 75 97 53 67 7 13 16 47 60 7 7 64 51 41 45 7.5 109 80 103 56 71 7.5 14 17 50 63 7.5 8 67 53 43 47

8 116 85 109 59 75 8 15 18 53 66 8 8 70 55 45 49 8.5 123 90 115 62 79 8.5 16 19 56 69 8.5 9 73 57 47 51

9 130 95 121 65 83 9 17 20 59 72 9 9 76 59 49 53 9.5 137 100 127 68 87 9.5 18 21 62 75 9.5 10 79 61 51 55 10 144 105 133 71 91 10 19 22 65 78 10 10 82 63 53 57




(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5

0 20 36 57 84 8 0 4 5 3 45 60 0 5 15 30 37 88 0.5 22 38 63 95 10 0.5 5 7 14 46 66 0.5 7 20 31 45 90

1 23 40 66 105 11 1 6 13 18 48 71 1 9 22 32 52 91 1.5 26 42 67 115 12 1.5 7 16 22 50 76 1.5 10 23 33 58 92

2 28 45 70 125 13 2 8 19 25 52 81 2 11 25 34 64 93 2.5 30 48 72 135 14 2.5 9 22 28 54 86 2.5 12 26 35 70 94

3 32 51 75 145 15 3 10 25 33 56 91 3 13 27 36 76 95 3.5 34 54 78 155 16 3.5 11 28 36 58 96 3.5 14 28 37 82 92

4 36 57 81 164 17 4 12 31 39 60 101 4 15 29 38 88 95 4.5 38 60 84 173 18 4.5 13 34 42 62 106 4.5 16 30 39 90 98

5 40 63 87 182 19 5 14 37 45 64 111 5 17 31 40 92 101 5.5 42 66 90 191 20 5.5 15 40 48 66 116 5.5 18 32 41 94 104

6 44 69 93 200 21 6 16 43 51 68 121 6 19 33 42 96 107 6.5 46 72 96 209 22 6.5 17 46 54 70 126 6.5 20 34 43 98 110

7 48 75 99 218 23 7 18 49 57 72 131 7 21 35 44 100 113 7.5 50 78 102 227 24 7.5 19 52 60 74 136 7.5 22 36 45 102 116

8 52 81 105 236 25 8 20 55 63 76 141 8 23 37 46 104 119 8.5 54 84 108 245 26 8.5 21 58 66 78 146 8.5 24 38 47 106 122

9 56 87 111 254 27 9 22 61 69 80 151 9 25 39 48 108 125 9.5 58 90 114 263 28 9.5 23 64 72 82 156 9.5 26 40 49 110 128 10 60 93 117 272 29 10 24 67 75 84 161 10 27 41 50 112 131



Site Identity Field A Site Identity Field A Site Identity Field A profile profile profile precipitation precipitation precipitation Soil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 14-03-2006 Date 14-03-2006 Date 14-03-2006 Time Level (mm) Time Level (mm) Time Level (mm)

(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5

0 45 63 0 40 71 0 75 4 22 49 0 0 2 19 35 87 2 0.5 48 75 8 49 73 0.5 77 6 28 61 1 0.5 4 25 42 89 10

1 50 85 14 52 77 1 79 10 32 69 3 1 7 37 50 94 12 1.5 51 95 19 56 79 1.5 81 13 35 76 6 1.5 11 29 56 99 14

2 52 105 23 59 83 2 83 17 38 84 10 2 14 31 63 102 16 2.5 54 115 27 62 86 2.5 85 21 41 91 14 2.5 17 33 69 105 18

3 55 125 31 65 89 3 87 25 44 99 18 3 20 35 75 108 20 3.5 57 135 35 68 92 3.5 89 29 47 105 22 3.5 23 37 81 111 22

4 59 145 39 71 95 4 91 33 50 111 26 4 26 39 87 114 24 4.5 61 155 43 74 98 4.5 93 37 53 117 30 4.5 29 41 93 117 26

5 63 165 47 77 101 5 95 41 56 123 34 5 32 43 99 120 28 5.5 65 175 51 80 104 5.5 97 45 59 129 38 5.5 35 45 105 123 30

6 67 185 55 83 107 6 99 49 62 135 42 6 38 47 111 126 32 6.5 69 195 59 86 110 6.5 101 53 65 141 46 6.5 41 49 117 129 34

7 71 205 63 89 113 7 103 57 68 147 50 7 44 51 123 132 36 7.5 73 215 67 92 116 7.5 105 61 71 153 54 7.5 47 53 129 135 38

8 75 225 71 95 119 8 107 65 74 159 58 8 50 55 135 138 40 8.5 77 235 75 98 122 8.5 109 69 77 165 62 8.5 53 57 141 141 42

9 79 245 79 101 125 9 111 73 80 171 66 9 56 59 147 144 44 9.5 81 255 83 104 128 9.5 113 77 83 177 70 9.5 59 61 153 147 46 10 83 265 87 107 131 10 115 81 86 183 74 10 62 63 159 150 48



Site Identity Field B Site Identity Field B Site Identity Field B profile profile profile Coordinates Coordinates Coordinates Soil type Clay loam Soil type Clay loam Soil type Clay loam Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 1/22/2006 Date 1/22/2006 Date 1/22/2006 Time Level (mm) Time Level (mm) Time Level (mm)

(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5

0 3 4 4 36 6 0 4 3 5 4 2 0 4 72 2 4 80.5 19 24 30 78 16 0.5 29 22 31 16 22 0.5 25 90 16 21 41

1 29 34 45 102 19 1 49 34 57 26 34 1 34 102 39 31 671.5 37 43 56 124 22 1.5 69 54 76 34 45 1.5 41 114 46 40 88

2 44 50 66 143 24 2 86 68 89 41 54 2 46 123 58 47 1052.5 51 56 76 162 26 2.5 105 82 101 49 64 2.5 52 134 70 55 121

3 58 62 85 180 28 3 123 95 112 57 72 3 56 143 81 62 1353.5 64 68 94 193 30 3.5 141 109 122 64 81 3.5 60 152 93 69 150

4 70 72 102 215 31 4 160 122 131 71 90 4 64 160 103 76 1624.5 76 79 109 232 32 4.5 177 135 140 77 97 4.5 68 169 113 83 175

5 82 84 118 249 34 5 195 148 148 83 105 5 72 178 123 90 1875.5 88 90 126 266 35 5.5 213 161 157 89 112 5.5 76 187 133 97 199

6 94 95 134 283 36 6 230 174 166 97 120 6 80 196 143 104 2116.5 100 100 141 300 37 6.5 249 187 175 103 127 6.5 84 205 153 111 223

7 106 105 148 317 38 7 265 200 184 109 134 7 88 214 163 118 2357.5 112 110 155 334 39 7.5 282 213 193 115 141 7.5 92 223 173 125 247

8 118 115 351 40 8 294 226 202 121 148 8 96 232 183 132 2598.5 124 120 171 368 41 8.5 316 239 211 127 155 8.5 100 241 193 139 271

9 130 125 177 385 42 9 332 252 220 133 162 9 104 250 203 146 2839.5 136 130 185 402 43 9.5 350 265 229 139 169 9.5 108 259 213 153 29510 142 135 192 419 44 10 366 278 238 145 176 10 112 268 223 160 307



Site identity Field B Site identity Field B Site identity Field B profile profile profile Coordinates Coordinates Coordinates Soil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 1/24/2006 Date 1/24/2006 Date 1/24/2006

Time Level (mm) Time Level (mm) Time Level (mm)

(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5

0 60 10 2 70 4 0 4 5 5 3 4 0 2 39 8 9 90.5 88 16 15 90 10 0.5 10 19 43 10 19 0.5 9 56 19 16 25

1 105 21 27 102 15 1 17 29 59 17 30 1 15 65 29 25 411.5 119 26 36 112 19 1.5 24 38 70 23 40 1.5 19 74 39 31 54

2 133 31 44 122 23 2 31 46 78 29 48 2 22 81 47 37 652.5 145 36 51 131 27 2.5 37 53 86 34 56 2.5 26 89 56 43 76

3 157 40 58 139 30 3 43 61 93 39 63 3 29 95 64 50 863.5 168 44 65 148 34 3.5 49 68 100 44 70 3.5 33 103 72 56 95

4 178 48 72 156 37 4 55 75 106 49 77 4 35 110 79 63 1044.5 189 52 79 164 40 4.5 60 82 112 54 83 4.5 38 117 87 69 113

5 199 56 85 172 44 5 66 88 118 58 89 5 41 124 95 74 1215.5 209 60 91 180 47 5.5 72 94 124 62 95 5.5 44 130 102 80 129

6 219 64 97 188 50 6 77 101 130 67 101 6 47 135 110 85 1376.5 229 68 103 196 53 6.5 82 107 136 71 107 6.5 50 142 117 90 145

7 239 72 110 204 56 7 88 113 142 75 113 7 53 149 124 95 1527.5 249 76 116 212 60 7.5 93 119 148 79 119 7.5 56 155 131 100 159

8 259 80 122 220 63 8 98 125 154 83 125 8 59 162 138 105 1668.5 269 84 128 228 66 8.5 103 131 160 87 131 8.5 62 168 145 110 173

9 279 88 134 236 69 9 108 137 166 91 137 9 65 174 152 115 1809.5 289 92 140 244 72 9.5 113 143 172 95 143 9.5 68 180 159 120 18610 299 96 146 252 75 10 118 149 178 99 149 10 71 186 166 125 192



Site Identity Field B Site Identity Field B Site Identity Field B profile profile profile Coordinates Coordinates Coordinates Soil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 1/27/2006 Date 1/27/2006 Date 1/27/2006


(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5

0 11 3 40 6 8 0 1 49 0 8 4 0 2 0 1 1 00.5 14 7 42 24 15 0.5 2 64 51 10 28 0.5 15 10 14 14 8

1 19 12 50 35 19 1 6 71 75 16 46 1 25 18 25 25 201.5 25 18 54 43 24 1.5 11 80 90 22 62 1.5 33 25 35 35 27

2 31 21 60 52 27 2 16 88 101 27 75 2 40 33 45 45 362.5 36 26 62 60 30 2.5 21 96 115 34 88 2.5 50 45 55 55 44

3 40 31 66 66 35 3 26 104 125 38 99 3 58 52 65 64 503.5 46 35 69 74 37 3.5 30 109 137 43 110 3.5 65 58 75 72 57

4 50 40 74 81 41 4 34 114 147 48 121 4 72 71 80 80 634.5 55 45 76 89 45 4.5 38 121 157 53 132 4.5 80 76 85 88 72

5 59 49 80 95 49 5 42 129 167 58 143 5 86 83 90 96 775.5 64 52 84 101 51 5.5 46 135 177 63 154 5.5 92 90 95 102 84

6 68 56 88 107 55 6 50 140 187 68 165 6 100 95 100 108 906.5 72 60 92 114 57 6.5 54 145 197 73 176 6.5 107 100 105 114 97

7 76 64 96 120 60 7 58 150 207 78 187 7 112 105 110 120 1037.5 80 68 100 126 63 7.5 62 155 217 83 198 7.5 119 110 115 126 109

8 84 72 104 132 67 8 66 160 227 88 209 8 124 115 120 132 1158.5 88 76 108 138 70 8.5 70 165 237 93 220 8.5 129 120 125 138 121

9 92 80 112 144 73 9 74 170 247 98 231 9 134 125 130 144 1279.5 96 84 116 150 76 9.5 78 175 257 103 242 9.5 139 130 135 150 13310 100 88 120 156 79 10 82 180 267 108 253 10 144 135 140 156 139





(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5

0 7 5 5 57 4 0 1 1 5 6 7 0 30 24 18 23 77 12 30 8 8 40 12 25 30 60 35 28 35 92 17 60 10 10 67 18 40 60 90 46 38 47 106 21 90 14 14 83 22 54 90

120 57 48 59 120 25 120 19 19 103 27 65 120 150 68 57 70 133 30 150 22 22 117 32 75 150 180 79 66 80 144 35 180 26 26 130 36 85 180 210 89 75 90 160 39 210 30 30 142 40 95 210 240 99 84 101 173 43 240 34 34 154 44 104 240 270 109 92 111 185 47 270 37 37 165 48 113 270 300 119 100 121 197 51 300 40 40 175 52 121 300 330 129 108 132 210 55 330 43 43 185 56 129 330 360 139 116 142 222 59 360 46 46 196 60 137 360 390 149 124 152 234 63 390 49 49 207 64 146 390 420 159 132 162 246 67 420 52 52 217 68 153 420 450 169 140 172 258 71 450 55 55 227 72 161 450 480 179 148 182 270 75 480 58 58 237 76 169 480 510 189 156 192 282 79 510 61 61 247 80 177 510 540 199 164 202 294 83 540 64 64 257 84 185 540 570 209 172 212 306 87 570 67 67 267 88 193 570 600 219 180 222 318 91 600 70 70 277 92 201 600





(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5

0 2 67 0 55 90 0 0 68 1 50 92 0 0 110 0 33 550.5 12 87 9 65 105 0.5 10 86 10 60 107 0.5 9 121 1 78 75

1 17 93 15 69 116 1 15 94 16 64 118 1 21 125 4 103 921.5 23 99 22 73 123 1.5 21 100 23 68 125 1.5 32 129 7 127 116

2 29 104 28 75 131 2 27 105 29 70 133 2 45 133 13 148 1202.5 33 111 34 79 138 2.5 31 112 35 74 140 2.5 56 141 17 167 130

3 38 116 40 81 147 3 36 117 41 76 149 3 66 145 21 185 1403.5 42 118 46 84 153 3.5 40 119 47 79 155 3.5 78 149 24 202 150

4 48 125 52 86 160 4 46 126 53 81 162 4 88 153 28 219 1604.5 53 132 58 89 168 4.5 51 133 59 84 170 4.5 98 157 32 236 170

5 58 139 64 92 176 5 56 136 65 87 178 5 108 161 36 252 1805.5 63 146 70 95 184 5.5 61 139 71 90 186 5.5 118 165 40 267 190

6 68 153 76 98 192 6 66 142 77 93 194 6 128 169 44 282 2006.5 73 160 82 101 200 6.5 71 145 83 96 202 6.5 138 173 48 297 210

7 78 167 88 104 208 7 76 148 89 99 210 7 148 177 52 312 2207.5 83 174 94 107 216 7.5 81 151 95 102 218 7.5 158 181 56 327 230

8 88 181 100 110 224 8 86 154 101 105 226 8 168 185 60 342 2408.5 93 188 106 113 232 8.5 91 157 107 108 234 8.5 178 189 64 357 250

9 98 195 112 116 240 9 96 160 113 111 242 9 188 193 68 372 2609.5 103 202 118 119 248 9.5 101 163 119 114 250 9.5 198 197 72 387 27010 108 209 124 122 256 10 106 166 125 117 258 10 208 201 76 402 280



Site Identity Field B Site Identity Field B Site Identity Field B profile profile profile Coordinates Coordinates Coordinates Soil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 25-02-2006 Date 25-02-2006 Date 25-02-2006


(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5

0 6 6 9 5 6 0 4 4 1 3 5 0 5 0 7 9 90.5 14 34 32 18 21 0.5 7 22 9 6 15 0.5 19 9 20 15 18

1 19 54 50 25 27 1 11 34 13 8 20 1 24 13 26 18 231.5 25 72 66 32 34 1.5 15 46 17 10 26 1.5 28 16 30 21 27

2 31 88 81 39 40 2 18 57 20 11 32 2 33 20 34 22 312.5 36 103 95 45 45 2.5 21 68 23 14 37 2.5 36 23 37 24 36

3 41 119 110 51 50 3 24 77 26 15 41 3 40 26 41 26 393.5 45 134 122 57 55 3.5 26 85 29 17 46 3.5 43 29 44 28 42

4 40 147 134 63 49 4 29 93 32 18 50 4 46 32 47 30 454.5 54 160 147 69 63 4.5 31 100 35 20 55 4.5 49 35 50 32 48

5 59 172 157 73 69 5 34 107 38 21 59 5 52 38 53 34 515.5 62 184 170 79 72 5.5 37 114 41 23 63 5.5 55 41 56 36 54

6 66 196 181 85 76 6 40 121 44 24 68 6 58 44 59 38 576.5 70 208 192 91 80 6.5 43 128 47 25 71 6.5 61 47 62 40 60

7 74 218 202 97 84 7 46 135 50 26 75 7 64 50 65 42 637.5 78 229 212 103 88 7.5 49 142 53 27 78 7.5 67 53 68 44 66

8 82 239 222 109 92 8 52 149 56 28 81 8 70 56 71 46 698.5 86 249 232 115 96 8.5 55 156 59 29 84 8.5 73 59 74 48 72

9 90 259 242 121 100 9 58 163 62 30 87 9 76 62 77 50 759.5 94 269 252 127 104 9.5 61 170 65 31 90 9.5 79 65 80 52 7810 98 279 262 133 108 10 64 177 68 32 93 10 82 68 83 54 81



Site Identity Field B Site Identity Field B Site Identity Field B profile profile profile Coordinates Coordinates Coordinates Soil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 28-02-06 Date 28-02-06 Date 28-02-06 Time Level (mm) Time Level (mm) Time Level (mm)

(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5

0 5 5 2 3 6 0 2 3 5 1 3 0 9 2 4 5 50.5 8 17 17 11 12 0.5 4 6 12 3 8 0.5 10 6 7 13 13

1 11 25 29 17 15 1 5 11 16 5 11 1 11 8 10 18 181.5 14 33 41 23 18 1.5 7 15 21 7 15 1.5 12 10 12 23 23

2 17 40 54 29 21 2 10 19 25 8 18 2 13 11 14 28 282.5 20 48 66 34 24 2.5 12 23 29 10 21 2.5 14 13 16 33 33

3 23 55 77 40 27 3 15 27 33 12 24 3 15 15 19 38 383.5 26 61 89 45 30 3.5 17 31 37 14 27 3.5 16 17 21 42 42

4 29 68 100 50 33 4 19 35 41 16 30 4 17 18 23 47 474.5 32 75 112 55 36 4.5 21 39 45 17 33 4.5 18 20 25 52 52

5 35 81 122 60 39 5 23 44 49 19 36 5 19 21 27 56 565.5 38 87 135 65 42 5.5 25 49 53 20 39 5.5 20 23 29 60 60

6 41 94 146 70 45 6 27 54 57 22 42 6 21 25 31 64 646.5 44 100 156 75 48 6.5 29 59 61 24 45 6.5 22 27 33 68 68

7 47 106 167 80 51 7 31 64 65 25 48 7 23 29 35 72 727.5 50 112 178 85 54 7.5 33 69 69 26 51 7.5 24 31 37 76 76

8 53 118 189 90 57 8 35 74 73 27 54 8 25 33 39 80 808.5 56 124 198 95 60 8.5 37 79 77 28 57 8.5 26 35 41 84 84

9 59 130 207 100 63 9 39 84 81 29 60 9 27 37 43 88 889.5 62 136 216 105 66 9.5 41 89 85 30 63 9.5 28 39 45 92 9210 65 142 225 110 69 10 43 94 89 31 66 10 29 41 47 96 96



Site Identity Field B Site Identity Field B Site Identity Field B profile profile profile Coordinates Coordinates Coordinates Soil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CR Date 14-03-2006 Date 14-03-2006 Date 14-03-2006


(min) Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4 Set 5 (min)

Set 1

Set 2

Set 3

Set 4

Set 5

0 34 58 83 5 42 0 65 0 32 41 0 0 54 60 7 20 00.5 41 63 87 10 43 0.5 72 3 36 43 7 0.5 55 71 8 21 6

1 46 68 96 19 45 1 74 12 37 45 16 1 56 79 10 23 101.5 49 73 104 27 49 1.5 77 20 38 48 23 1.5 57 86 12 25 12

2 52 78 112 30 54 2 80 28 39 51 29 2 58 91 14 27 142.5 55 83 120 33 67 2.5 83 36 40 54 32 2.5 59 99 16 29 16

3 58 88 128 36 70 3 86 44 41 57 38 3 60 106 18 31 183.5 61 93 136 39 73 3.5 89 52 42 60 40 3.5 61 113 20 33 20

4 64 98 142 42 76 4 92 60 43 63 42 4 62 120 22 35 224.5 67 103 148 45 79 4.5 95 72 44 126 44 4.5 63 127 24 37 24

5 70 108 154 48 82 5 98 84 45 189 46 5 64 134 26 39 265.5 73 113 160 51 85 5.5 101 96 46 252 48 5.5 65 141 28 41 28

6 76 118 166 54 88 6 104 108 47 315 50 6 66 148 30 43 306.5 79 123 172 57 91 6.5 107 120 48 378 52 6.5 67 155 32 45 32

7 82 128 178 60 94 7 110 132 49 441 54 7 68 162 34 47 347.5 85 133 184 63 97 7.5 113 144 50 504 56 7.5 69 169 36 49 36

8 88 138 190 66 100 8 116 156 51 567 58 8 70 176 38 51 388.5 91 143 196 69 103 8.5 119 168 52 630 60 8.5 71 183 40 53 40

9 94 148 202 72 106 9 122 180 53 693 62 9 72 190 42 55 429.5 97 153 208 75 109 9.5 125 192 54 756 64 9.5 73 197 44 57 4410 100 158 214 78 112 10 128 204 55 819 66 10 74 204 46 59 46



Appendix 3: Soil moisture content measurements Site Identity Filed A Site Identity Field A Site Identity Field Aprofile profile profile Coordinates Coordinates Coordinates Soil type Soil type Soil type Tillage practice Farmer practice Tillage practice Planting pits Tillage practice CRDate 20-11-2005 Date 20-11-2005 Date 20-11-2005

Depth (cm)

Profile m.c (%vol)

Depth (cm)

Profile m.c (%vol)

Depth (cm)

Profile m.c (%vol)

1.0 2.0 3.0 4.0 1.0 2.0 3.0 4.0 1.0 1.1 2.0 2.1 3.0 3.1 4.0 4.10-10 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.010-20 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.020-30 8.1 8.5 7.2 7.1 7.7 20-30 9.2 8.7 8.6 9.3 9.0 20-30 7.7 8.4 22.5 7.3 22.0 8.1 22.330-40 9.2 9.2 9.1 8.9 9.1 30-40 10.4 9.9 11.2 10.5 10.5 30-40 9.4 9.2 9.7 21.6 10.240-50 10.3 10.1 11.3 10.7 10.6 40-50 11.4 11.8 12.8 11.7 11.9 40-50 10.3 11.2 11.2 23.1 12.550-60 50-60 50-60

5.5 6.3 7.4Site Identity Site Identity Site Identity

Soil type Soil type Soil typeTillage practice Farmer practice Tillage practice Planting pits Tillage practice CRDate 1/21/2006 Date 1/21/2006 Date 1/21/2006

Depth (cm)

Profile m.c (%vol)

Depth (cm)

Profile m.c (%vol)

Depth (cm)

Profile m.c (%vol)

1.0 2.0 3.0 4.0 2.5 1.0 2.0 3.0 4.0 2.5 1.0 1.1 2.0 2.1 3.0 3.1 4.0 4.10-10 19.3 17.0 10.2 21.2 16.9 0-10 13.7 13.0 9.2 13.4 12.3 0-10 22.2 26.1 18.3 15.8 18.9 16.7 18.5 17.410-20 22.7 19.9 21.3 17.3 20.3 10-20 16.9 9.9 18.3 12.6 14.4 10-20 26.3 17.4 18.9 22.2 19.6 18.9 17.5 19.020-30 27.7 ## 24.4 28.2 26.3 20-30 25.5 17.6 18.6 16.9 19.7 20-30 27.1 18.9 20.1 22.5 21.3 22.0 21.9 22.330-40 25.2 21.4 27.2 34.0 27.0 30-40 26.7 23.3 21.8 22.8 23.7 30-40 27.8 21.9 22.8 21.6 22.140-50 24.4 25.7 27.3 31.4 27.2 40-50 27.1 22.5 22.1 23.1 23.7 40-50 27.9 23.7 23.9 23.1 23.550-60 50-60 50-60

23.5 18.8



Site Identity Site Identity Site Identityprofile profile profileCoordinates Coordinates CoordinatesSoil type Soil type Soil typeTillage practice Tillage practice Tillage practiceDate Date Date

Depth Profile m.c (%vol) Depth Profile m.c (%vol) Depth Profile m.c (%vol)(cm) (cm) (cm)

1.0 2.0 3.0 4.0 2.5 1.0 2.0 3.0 4.0 1.0 2.0 3.0 4.00-10 18.0 13.6 13.9 15.5 15.3 0-10 16.2 16.9 15.1 15.7 16.0 0-10 15.9 16.3 14.5 17.610-20 19.3 14.1 13.1 16.1 15.7 10-20 19.4 20.5 19.2 18.4 19.4 10-20 18.9 18.5 17.8 19.320-30 18.3 19.9 19.7 23.2 20.3 20-30 26.1 21.3 21.0 20.4 22.2 20-30 21.5 21.9 22.2 21.230-40 22.9 22.4 21.7 18.5 21.4 30-40 27.3 23.3 23.1 22.9 24.2 30-40 23.1 22.7 23.8 23.140-50 24.0 21.2 22.8 23.7 22.9 40-50 27.9 25.2 24.9 24.8 25.7 40-50 23.9 24.7 24.6 24.250-60 50-60 50-60 50-60

19.1 21.5Site Identity Site Identity Site Identityprofile profile profileCoordinates Coordinates CoordinatesSoil type Soil type Soil typeTillage practice Tillage practice Tillage practiceDate Date Date


1.0 2.0 3.0 4.0 2.5 1.0 2.0 3.0 4.0 1.0 1.1 2.0 2.1 3.0 3.1 4.0 4.10-10 13.7 10.6 12.6 12.9 12.5 0-10 15.2 9.7 9.2 12.2 11.6 0-10 11.5 10.5 10.6 12.2 7.1 9.5 10.6 10.910-20 14.6 14.5 16.2 19.0 16.1 10-20 16.2 14.8 10.6 13.5 13.8 10-20 17.8 13.3 15.3 16.4 16.3 15.8 16.0 17.320-30 15.9 16.8 19.1 24.0 19.0 20-30 19.9 18.9 16.7 17.9 18.4 20-30 18.2 14.5 17.9 16.2 18.5 18.3 18.1 19.730-40 18.6 21.4 20.3 22.8 20.8 30-40 21.7 20.4 18.9 20.3 20.3 30-40 20.1 19.2 21.1 20.940-50 18.1 20.4 22.3 24.2 21.3 40-50 23.8 22.9 20.3 22.1 22.3 40-50 22.3 21.8 22.3 22.750-60 50-60 50-60

17.9 17.3

Field A Field A Field A

Riplines1/26/2006

Farmer practice1/26/2006

Planting pits1/26/2006

Field A

1/28/2006Planting pits

Field AField A

Riplines1/28/2006

Farmer practice1/28/2006





1.0 2.0 3.0 4.0 2.5 1.0 2.0 3.0 4.0 1.0 1.1 2.0 2.1 3.0 3.1 4.0 4.10-10 13.9 15.8 18.8 17.6 16.5 0-10 18.3 18.5 18.8 18.4 18.5 0-10 18.0 18.4 12.2 18.4 9.5 17.1 10.910-20 18.7 15.0 18.9 18.6 17.8 10-20 16.2 12.8 18.4 18.6 16.5 10-20 20.6 18.4 16.4 18.3 15.8 18.4 17.320-30 18.8 18.8 22.6 18.0 19.6 20-30 19.9 13.2 18.4 18.6 17.5 20-30 21.1 18.4 16.2 18.3 18.3 18.0 19.730-40 25.3 20.2 20.7 17.0 20.8 30-40 21.4 17.3 18.2 19.4 19.1 30-40 22.3 18.0 18.0 19.340-50 26.0 18.8 19.8 15.0 19.9 40-50 23.3 20.1 18.3 21.9 20.9 40-50 22.5 20.0 18.6 20.850-60 50-60 50-60



1.0 2.0 3.0 4.0 1.0 2.0 3.0 4.0 1.0 1.1 2.0 2.1 3.0 3.1 4.0 4.10-10 14.6 13.6 14.3 14.2 0-10 16.7 13.7 19.4 16.6 0-10 15.0 15.2 12.2 13.2 17.1 10.910-20 15.1 14.3 15.9 15.1 10-20 21.2 19.0 18.4 19.5 10-20 19.1 19.3 16.4 16.8 18.4 17.320-30 16.9 19.4 17.2 17.8 20-30 25.3 25.6 20.1 23.7 20-30 21.0 20.6 16.2 19.0 18.0 19.730-40 18.7 20.3 20.9 20.0 30-40 25.6 25.9 2.4 18.0 30-40 22.5 21.9 21.8 20.340-50 20.9 21.8 21.0 21.2 40-50 25.7 24.8 24.1 24.9 40-50 24.1 23.5 24.9 22.950-60 50-60 50-60

17.7 20.5

Farmer practice Planting pits Riplines27-02-06 27-02-06 27-02-06


Riplines3/2/2006 3/2/2006 3/2/2006

Farmer practice Planting pits

Field AField A Field A





1.0 2.0 3.0 4.0 1.0 2.0 3.0 4.0 1.0 2.0 3.0 4.00-10 16.6 14.4 15.1 17.4 15.9 0-10 17.4 11.1 10.7 13.7 13.2 0-10 16.8 14.7 13.110-20 17.2 15.2 15.8 22.3 17.6 10-20 24.4 14.8 26.7 17.9 21.0 10-20 18.6 16.6 19.020-30 21.5 20.8 14.8 25.8 20.7 20-30 27.4 20.5 16.8 19.3 21.0 20-30 19.4 17.3 21.830-40 25.5 24.2 26.9 29.6 26.6 30-40 28.3 23.4 20.3 23.4 23.9 30-40 24.1 20.3 23.440-50 27.1 27.6 28.2 29.8 28.2 40-50 28.7 27.6 23.4 26.6 26.6 40-50 27.3 24.5 27.150-60 50-60 50-60



1.0 2.0 3.0 4.0 1.0 2.0 3.0 4.0 1.0 2.0 3.0 4.00-10 14.6 13.6 14.3 14.2 0-10 16.7 13.7 19.4 16.6 0-10 15.0 15.2 13.110-20 15.1 14.3 15.9 15.1 10-20 21.2 19.0 18.4 19.5 10-20 19.1 19.3 19.020-30 16.9 19.4 17.2 17.8 20-30 25.3 25.6 20.1 23.7 20-30 21.0 20.6 21.830-40 24.1 25.8 26.9 25.6 30-40 26.1 26.9 24.1 25.7 30-40 23.4 22.7 23.840-50 26.1 27.2 28.5 27.3 40-50 28.2 28.5 25.9 27.5 40-50 25.1 24.6 25.650-60 50-60 50-60

20.0 22.6



Farmer practice16-02-06

Planting pits16-02-06


16-02-06Riplines





1.0 2.0 3.0 4.0 1.0 2.0 3.0 4.0 1.0 2.0 3.0 4.00-10 15.7 15.1 15.3 15.4 0-10 18.5 15.0 17.1 16.9 0-10 18.0 15.4 15.710-20 18.7 13.4 16.8 16.3 10-20 20.4 14.5 19.0 18.0 10-20 16.8 14.4 16.220-30 18.7 18.0 14.4 17.0 20-30 21.1 23.0 16.4 20.2 20-30 20.4 18.4 14.830-40 18.0 16.6 15.2 16.6 30-40 21.6 23.8 14.8 20.1 30-40 19.6 18.0 18.640-50 15.2 16.0 15.1 15.4 40-50 18.2 20.0 18.6 18.9 40-50 18.0 16.050-60 50-60 50-60



1.0 2.0 3.0 4.0 1.0 2.0 3.0 4.0 1.0 2.0 3.0 4.00-10 7.3 8.7 7.9 8.0 0-10 7.7 9.0 10.8 9.2 0-10 13.7 12.0 11.310-20 13.1 13.4 13.3 13.3 10-20 12.6 12.2 11.8 12.2 10-20 12.2 12.5 11.720-30 11.1 12.3 14.4 12.6 20-30 14.1 14.3 14.2 14.2 20-30 10.6 11.4 16.130-40 16.6 16.1 11.4 14.7 30-40 15.6 16.6 16.7 16.3 30-40 14.9 15.2 13.640-50 12.1 11.6 11.0 11.6 40-50 17.1 18.6 19.1 18.3 40-50 14.0 14.6 13.950-60 50-60 50-60

12.0 14.0



Farmer practice Planting pits Riplines3/3/2006 3/3/2006 3/3/2006




Site Identity Site Identity Site Identityprofile profile profileCoordinates Coordinates CoordinatesSoil type Soil type Soil typeTillage practice Farmer practice Tillage practice Planting pits Tillage practice RiplinesDate Date Date


1 2 3 4 Avg 1 2 3 4 Avg 1 2 3 4 Avg0-10 21 20.5 16.4 20.4 19.65 0-10 20 17 18.8 19 18.7 0-10 19.7 17.2 16 9 15.3810-20 24 22.5 20.7 24.8 22.98 10-20 22.6 18 20.7 19 20.1 10-20 17 19.5 20 17 18.4020-30 27 25.3 26.3 29.4 27.1 20-30 24.1 20 23.2 22 22.2 20-30 12.4 25.5 17 14 17.0830-40 25 24.2 24.8 26.3 25.1 30-40 22.1 22 22.2 21 21.4 30-40 15.3 16.2 16 15 15.6040-50 23 21.3 20.4 22.1 21.68 40-50 20.2 20 20.1 21 20.8 40-50 14.7 15.1 15 15 14.6050-60 50-60 50-60

23.3 20.6 16.21Site Identity Site Identity Site Identityprofile profile profileCoordinates Coordinates CoordinatesSoil type Soil type Soil typeTillage practice Farmer practice Tillage practice Planting pits Tillage practice RiplinesDate Date Date

Depth Profile m.c (%vol) Depth Profile m.c (%vol) Depth Profile m.c (%vol)(cm) (cm) (cn)

1 2 3 4 Avg 1 2 3 4 Avg 1 2 3 4 Avg0-10 17 15.8 15 13.7 15.35 0-10 16.9 17 10.8 9.4 13.5 0-10 13.6 13.9 12 11 12.5010-20 20 17.2 16.2 15.2 17.05 10-20 18.1 17 12.3 12 14.9 10-20 15.2 16.7 16 15 15.6520-30 23 19.3 19.4 22.9 21.23 20-30 20.2 19 15.9 15 17.5 20-30 16.1 20.8 19 16 17.8530-40 22 21.1 20.9 21.9 21.53 30-40 21.5 21 16.8 17 18.9 30-40 18.3 21.3 21 18 19.5840-50 21 20.4 19.5 20.5 20.25 40-50 20.4 20 16.3 16 18.2 40-50 17.1 19.3 19 17 18.0050-60 50-60 50-60

19.08 16.6 16.72

Field B

1/21/20061/21/2006

Field B Field B

1/26/2006

1/21/2006

Field BField B

Field B

1/26/2006 1/26/2006





1 2 3 4 Avg 1 2 3 4 Avg 1 2 3 4 Avg0-10 14 12.8 11.1 12.9 12.7 0-10 8.4 11 9.1 9.4 9.35 0-10 9.2 12.9 12 8.4 10.5010-20 17 15.3 14.1 15.8 15.58 10-20 11.3 12 11 11 11.3 10-20 14.2 14.1 14 9.8 13.0820-30 20 17.8 16.8 19 18.35 20-30 13.5 16 13 14 14.1 20-30 15.9 16.8 17 13 15.6530-40 21 19.3 18.7 20.4 19.9 30-40 15.4 18 15.2 16 16.1 30-40 17.6 18.2 19 15 17.4340-50 23 20.4 19.9 22.3 21.38 40-50 17.2 20 17.1 18 18.2 40-50 19.3 21.4 21 18 19.8050-60 50-60 50-60

17.58 13.8 15.29Site Identity Site Identity Site Identityprofile profile profileCoordinates Coordinates CoordinatesSoil type Soil type Soil typeTillage practice Farmer practice Tillage practice Planting pits Tillage practice Clean rippingDate Date Date

Depth Profile m.c (%vol) Depth Profile m.c (%vol) Depth (Profile m.c (%vol)(cm) (cm) (cm)

1 2 3 4 1 2 3 4 1 2 3 40-10 21 22 21.5 21.47 0-10 20.6 19 18.5 19.2 0-10 18.4 18.2 19 18.4710-20 18 20.9 19.3 19.53 10-20 16.2 18 18.2 17.6 10-20 16.8 19.8 19 18.4020-30 17 19.8 18.6 18.57 20-30 16.1 18 18.3 17.6 20-30 20.2 21.1 18 19.9030-40 15 17.8 17.6 16.9 30-40 16.3 18 17.9 17.5 30-40 21.1 22.3 18 20.5340-50 15 17.3 16.4 16.27 40-50 16.2 17 17.2 16.9 40-50 22.4 21.1 18 20.5350-60 50-60 50-60

18.55 17.7 19.57

Field BField B Field B

1/28/2006 1/28/2006

3/2/2006

1/28/2006

Field B Field BField B

3/2/2006 3/2/2006





1 2 3 4 1 2 3 4 1 2 3 40-10 15 11.1 17.1 14.27 0-10 17.5 17 18.9 17.6 0-10 17.3 22.3 18 19.1710-20 22 17.9 16.9 18.8 10-20 17.5 19 16.4 17.8 10-20 17.6 16.3 17 16.9320-30 17 15.7 17.8 16.77 20-30 19.5 20 19.4 19.7 20-30 17.3 17.2 18 17.4330-40 17 16.9 18.6 17.63 30-40 20.1 22 21.7 21.3 30-40 18.4 19.3 19 18.8040-50 18 17.5 19.5 18.27 40-50 21.8 23 22.3 22.3 40-50 19.4 20.6 20 19.8750-60 50-60 50-60

17.15 19.7 18.44Site Identity Site Identity Site Identityprofile profile profileCoordinates Coordinates CoordinatesSoil type Soil type Soil typeTillage practice Farmer practice Tillage practice Planting pits Tillage practice Farmer practiceDate Date Date


1 2 3 4 1 2 3 4 1 2 3 40-10 11 16.5 13.3 13.63 0-10 12.2 13 12 12.2 0-10 11.3 13.8 15 13.3710-20 18 18.7 18.2 18.3 10-20 15.3 15 13.5 14.6 10-20 15.4 18 16.9020-30 21 22.7 21.5 21.63 20-30 17.1 18 17.2 17.3 20-30 17 17.0030-40 22 23.5 22.7 22.83 30-40 19.4 19 18.7 19.1 30-4040-50 23 24.8 22.1 23.33 40-50 20.8 20 20.3 20.5 40-5050-60 50-60 50-60

19.95 16.7

27-02-06 27-02-06 27-02-06

16-2-06 16-2-06 16-2-06

Field B Field B Field B






1 2 3 4 1 2 3 4 1 2 3 40-10 14 20.3 19.2 17.7 0-10 15.4 17 18.5 17 0-10 15.2 17.6 14 15.5010-20 13 20.7 18 17.23 10-20 14.9 17 17.6 16.6 10-20 17.1 18.3 19 17.9720-30 16 21.8 21.6 19.77 20-30 21.5 17 19 19.1 20-30 21.6 21.8 22 21.7730-40 18 22.9 22 20.9 30-40 20.6 15 22.8 19.5 30-40 20.7 21.2 22 21.2740-50 19 23.1 23.8 22.03 40-50 22.3 20 23.4 22 40-50 21.3 22.7 23 22.3050-60 50-60 50-60

19.53 18.8 19.76Site Identity Site Identity Site Identityprofile profile profileCoordinates Coordinates CoordinatesSoil type Soil type Soil typeTillage practice Farmer practice Tillage practice Planting pits Tillage practice RiplinesDate Date Date


1 2 3 4 1 2 3 4 1 2 3 40-10 16 15.9 15.1 15.77 0-10 15.4 15 17.4 16 0-10 15.2 17.6 14 15.5010-20 18 17.3 16.4 17.1 10-20 17.3 17 19.6 17.9 10-20 12.2 13.8 14 13.3720-30 19 19.1 18.5 18.7 20-30 19 18 20.1 19.1 20-30 21.6 16 13 16.9030-40 20 20.4 19.6 20.03 30-40 20.1 20 21.1 20.5 30-40 20.7 18.3 14 17.6740-50 21 21.3 20.2 20.87 40-50 21.2 22 22.3 21.9 40-5050-60 17.9 50-60 18.4 50-60 15.86

16-03-06 16-03-06 16-03-06

3/3/2006 3/3/2006 3/3/2006





Appendix 4: Output from Gensat ***** Analysis of variance ***** Variate: m_c_A Source of variation d.f. s.s. m.s. v.r. F pr. Replica stratum 2 100.72 50.36 0.76 Replica.*Units* stratum Treatment 2 30.57 15.29 0.23 0.794 Residual 211 13967.53 66.20 Total 215 14098.81 ***** Tables of means ***** Variate: m_c Grand mean 14.71 Treatment CR FP PP 14.82 15.10 14.20 *** Standard errors of means *** Table Treatment rep. 72 d.f. 211 e.s.e. 0.959 *** Standard errors of differences of means *** Table Treatment rep. 72 d.f. 211 s.e.d. 1.356 *** Least significant differences of means (5% level) *** Table Treatment rep. 72 d.f. 211 l.s.d. 2.673



***** Analysis of variance ***** Variate: cumm_infilt_B Source of variation d.f. s.s. m.s. v.r. F pr. Replica stratum 4 2874. 718. 0.40 Replica.*Units* stratum Treatment 2 230. 115. 0.06 0.937 Residual 53 94053. 1775. Total 59 97157. ***** Tables of means ***** Variate: cumm_infilt Grand mean 61.2 Treatment CR FP PP 59.0 63.7 60.8 *** Standard errors of means *** Table Treatment rep. 20 d.f. 53 e.s.e. 9.42 *** Standard errors of differences of means *** Table Treatment rep. 20 d.f. 53 s.e.d. 13.32 *** Least significant differences of means (5% level) *** Table Treatment rep. 20 d.f. 53 l.s.d. 26.72



***** Analysis of variance ***** Variate: cumm_infil_A Source of variation d.f. s.s. m.s. v.r. F pr. Replica stratum Treatment 2 15441. 7720. 3.05 0.247 Residual 2 5065. 2533. 0.94 Replica.*Units* stratum Treatment 2 23808. 11904. 4.40 0.017 Residual 53 143288. 2704. Total 59 181331. ***** Tables of means ***** Variate: cumm_infil Grand mean 59.6 Treatment CR FP PP 37.9 86.7 54.1 *** Standard errors of means *** Table Treatment rep. 20 d.f. 53 e.s.e. 11.85 *** Standard errors of differences of means *** Table Treatment rep. 20 d.f. 53 s.e.d. 16.76 *** Least significant differences of means (5% level) *** Table Treatment rep. 20 d.f. 53 l.s.d. 33.62



APPENDIX 4 ***** Two-sample T-test ***** Variates: m_c_A, m_c_B. *** Test for equality of sample variances *** Test statistic F = 68.52 on 215 and 65348 d.f. Probability (under null hypothesis of equal variances) < 0.001 Note: strong evidence of unequal sample variances - variances estimated separately for each group. *** Summary *** Sample Size Mean Variance Standard Standard error deviation of mean m_c_A 216 14.71 65.58 8.098 0.5510 m_c_B 65349 0.05102 0.9571 0.9783 0.003827 Standard error for difference of means 0.5510 95% confidence interval for difference in means: (13.57, 15.74) *** Test of null hypothesis that mean of m_c_A is equal to mean of m_c_B *** Test statistic t = 26.60 on approximately 215.02 d.f. Probability < 0.001



APPENDIX 4 ***** Two-sample T-test ***** Variates: CUM_INF_a, cumm_infilt_b. *** Test for equality of sample variances *** Test statistic F = 1.87 on 59 and 59 d.f. Probability (under null hypothesis of equal variances) = 0.02 Note: evidence of unequal sample variances - variances estimated separately for each group. *** Summary *** Sample Size Mean Variance Standard Standard error deviation of mean CUM_INF_a 60 59.57 3073 55.44 7.157 cumm_infilt_b 60 61.17 1647 40.58 5.239 Standard error for difference of means 8.870 95% confidence interval for difference in means: (-19.19, 15.97) *** Test of null hypothesis that mean of CUM_INF_a is equal to mean of cumm_infilt_b *** Test statistic t = -0.18 on approximately 108.12 d.f. Probability = 0.857



******************************************************************************Appendix 5: Crop Water Requirements Report ****************************************************************************** - Crop # 1 : MaizeSC403 - Block # : [Field A] - Planting date : 12/12 - Calculation time step = 7 Day(s) ------------------------------------------------------------------------------ Date ETo Planted Crop CWR Total Effect. Irr. FWS Area Kc (ETm) Rain Rain Req. (mm/period) (%) ---------- (mm/period) ---------- (l/s/ha) ------------------------------------------------------------------------------ 12/12 34.01 100.00 0.10 3.40 30.39 23.82 0.00 0.00 19/12 37.38 100.00 0.10 3.74 31.08 24.49 0.00 0.00 26/12 37.83 100.00 0.16 6.08 28.92 23.18 0.00 0.00 2/1 35.60 100.00 0.27 9.57 21.66 18.47 0.00 0.00 9/1 35.54 100.00 0.38 13.36 22.18 18.77 0.00 0.00 16/1 35.14 100.00 0.48 16.98 24.98 20.46 0.00 0.00 23/1 34.51 100.00 0.56 19.25 29.50 23.20 0.00 0.00 30/1 33.78 100.00 0.56 18.92 34.75 26.38 0.00 0.00 6/2 33.12 100.00 0.56 18.55 39.34 29.16 0.00 0.00 13/2 32.65 100.00 0.56 18.28 41.77 30.60 0.00 0.00 20/2 32.37 100.00 0.56 18.13 40.66 29.84 0.00 0.00 27/2 32.10 100.00 0.53 16.92 35.12 26.29 0.00 0.00 6/3 31.35 100.00 0.42 13.24 25.19 19.91 0.00 0.00 13/3 29.21 100.00 0.31 9.22 12.29 11.25 0.00 0.00 20/3 24.24 100.00 0.21 5.09 1.25 1.25 3.83 0.09 27/3 9.81 100.00 0.12 1.23 0.00 0.00 1.23 0.05 ------------------------------------------------------------------------------ Total 508.63 191.94 419.07 327.09 5.06 [0.01] ------------------------------------------------------------------------------ * ETo data is distributed using polynomial curve fitting. * Rainfall data is distributed using polynomial curve fitting. ****************************************************************************** C:\CROPWATW\REPORTS\FA.TXT8/17/2006 CropWat 4 Windows Ver 4.3



****************************************************************************** Crop Water Requirements Report ****************************************************************************** - Crop # 1 : MaizeSC403 - Block # : [Field B] - Planting date : 12/12 - Calculation time step = 7 Day(s) ------------------------------------------------------------------------------ Date ETo Planted Crop CWR Total Effect. Irr. FWS Area Kc (ETm) Rain Rain Req. (mm/period) (%) ---------- (mm/period) ---------- (l/s/ha) ------------------------------------------------------------------------------ 12/12 34.18 100.00 0.10 3.42 31.52 24.46 0.00 0.00 19/12 33.40 100.00 0.10 3.34 32.29 25.16 0.00 0.00 26/12 33.63 100.00 0.16 5.44 30.15 23.91 0.00 0.00 2/1 35.60 100.00 0.27 9.57 22.59 19.18 0.00 0.00 9/1 35.54 100.00 0.38 13.36 23.52 19.70 0.00 0.00 16/1 35.14 100.00 0.48 16.98 26.95 21.67 0.00 0.00 23/1 34.51 100.00 0.56 19.25 32.21 24.71 0.00 0.00 30/1 33.78 100.00 0.56 18.92 38.11 28.11 0.00 0.00 6/2 33.12 100.00 0.56 18.55 43.09 30.94 0.00 0.00 13/2 32.65 100.00 0.56 18.28 45.45 32.20 0.00 0.00 20/2 32.37 100.00 0.56 18.13 43.66 30.95 0.00 0.00 27/2 32.10 100.00 0.53 16.92 36.81 26.63 0.00 0.00 6/3 31.35 100.00 0.42 13.24 25.06 19.29 0.00 0.00 13/3 29.21 100.00 0.31 9.22 10.24 9.39 0.00 0.00 20/3 24.24 100.00 0.21 5.09 0.24 0.24 4.84 0.11 27/3 9.81 100.00 0.12 1.23 0.00 0.00 1.23 0.05 ------------------------------------------------------------------------------ Total 500.62 190.92 441.89 336.54 6.07 [0.01] ------------------------------------------------------------------------------ * ETo data is distributed using polynomial curve fitting. * Rainfall data is distributed using polynomial curve fitting. ****************************************************************************** C:\CROPWATW\REPORTS\FB.TXT



APPENDIX 6 :water partitioning in Field A Time step 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 105

Growth stage Germination stage Vegetative stage Flowering stage

Maturity stage

Date Rain 37 98 7 10 6 0 26 54 22 0 26 108 37 30 29 490 mm R off 6 15 0 0 0 0 4 8 3 0 4 16 6 5 4 70 mm I 31 83 7 10 6 0 22 46 19 0 22 92 31 26 25 420 mm Sin 0 28 62 100 91 89 76 68 68 74 77 91 90 98 91 Soil moisture 31 66 106 101 102 93 87 87 93 95 108 103 107 96 87 WHC 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 Dp 0 0 6 1 2 0 0 0 0 0 8 3 7 0 0 27 mm Dpmax 0 ET 3 4 6 10 13 17 19 19 19 18 17 13 9 5 1 174 mm Sout 28 62 100 91 89 76 68 68 74 77 91 90 98 91 86 Water partitioning in Field B Time step 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 105 days

Growth stage Germination stage Vegetative stage Flowering stage Maturity stage

Date Rain 46 95 10 10 6 0 29 60 5 0 25 115 49 27 21 498 mm R off 9 19 2 2 1 0 6 12 1 0 5 23 10 5 4 100 mm I 37 76 8 8 5 0 23 48 4 0 20 92 39 22 17 398 mm Sin 0 31 70 95 78 73 65 59 74 73 74 72 79 78 82 Soil moisture 34 73 100 89 87 83 78 93 92 92 90 97 91 91 72 WHC 120 120 120 120 120 120 120 120 120 120 120 120 120 140 140 Dp 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 mm Dpmax ET 3 3 5 11 14 18 19 19 19 18 18 18 13 9 1 190 mm Sout 31 70 95 78 73 65 59 74 73 74 72 79 78 82 71

an on farm comparison of conservation agriculture ...€¦ · 2.2 conservation agriculture ......

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