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UNIVERSITI PUTRA MALAYSIA

CURVE NUMBER METHOD RUNOFF ESTIMATION IN THE KARDEH WATERSHED, IRAN

MAHBOUBEH EBRAHIMIAN

T FH 2009 6


By


Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia, in Fulfilment of the requirements for the Degree of Master of Science

August 2009

Abstract of thesis presented to the Senate of University Putra Malaysia in fulfilment of the requirement for the degree of Master of Science


By


August 2009

Chairman: Associate Professor Lai Food See, PhD

Faculty: Forestry

The major problem in the assessment of the relationship between rainfall and runoff

occurs when a study is carried out in ungauged watersheds, in particular, the absence of

hydro-climatic data. This study aims to determine the runoff depth using NRCS-CN

method with GIS and the effect of slope on runoff generation in the Kardeh watershed,

located between 59º 26´ 3˝ to 59º 37´ 17˝ E longitude and 36º 37´ 17˝ to 36º 58´ 25˝ N

latitude, about 42 km north of Mashhad, Khorasan Razavi province, Iran. The US

Department of Agriculture, Natural Resources Conservation Service Curve Number

(USDA-NRCS-CN) method was applied for estimating the runoff depth in the semi-arid

Kardeh watershed. Hydrologic soil group, land use and slope maps were generated in

GIS environment. The curve number values from NRCS standard tables were assigned to

the intersected hydrologic soil groups and land use maps to generate CN values map. The

curve number method was followed to estimate runoff depth for selected storm events in

the watershed. Effect of slope on CN values and runoff depth was determined. Estimated

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runoff depth and slope-adjusted runoff depth were statistically compared with the

corresponding observed runoff data. Pair wise comparisons by the t-test, Pearson

correlation analysis and percent error were used to investigate the accuracy of estimated

data and relationship between estimated and observed runoff depth. The results showed

that there was no significant difference between the means of observed and estimated

runoff depths (P > 0.05). Fairly positive correlations were detected between observed

with estimated runoff and slope-adjusted runoff depth (r = 0.55; P < 0.01) and (r = 0.56;

P < 0.01), respectively. About 9 % and 6 % of the estimated and slope-adjusted runoff

values were within ±10% of the recorded values, respectively. In addition, about 43 and

37 percent of the estimated and slope-adjusted values were in error by more than ±50 %,

respectively. Statistical analysis indicated that percent error of estimated slope-adjusted

runoff depth was significantly (p < 0.01) lower than the percent error of estimated runoff

depth. This decline in percent error can be explained by the role of slope in runoff

generation in steep slope watershed. The results of study indicated that the CN is an

effective method for homogenous watersheds in terms of land use, soil, and climate

rather than heterogeneous ones like Kardeh watershed. In such watersheds it can be

employed with about 60 percent accuracy only for management and conservation

purposes however and probably not for computation of design floods.

Keywords: Curve Number, Geographic Information System, Kardeh watershed, Slope-

adjusted runoff depth

Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk ijazah Master Sains

LIMPASAN KAEDAH CURVE NUMBER ESTIMASI DI KARDEH TADAHAN, IRAN

Oleh


August 2009

Pengerusi: Professor Madya Lai Food See, PhD

Fakulti: Perhutanan

Penilaian keatas hubungkait diantara turunan hujan dan kelarian air permukaan adalah penting

and satu isu yang komplek dalam bidang haidrologi. Masalah utama berlaku apabila sesuatu

kajian dibuat keatas hubungankait diantara turunan hujan dan kelarian air permukaan didalam

tadahan air yang belum dicerap kerana terdapat banyak kawasan tadahan air tanpa data iklim

hairdo. Objektif kajian ini adalah untuk menentukan kedalaman kelarian air permukaan

menggunakan kaedah NRCS-CN bersama GIS serta mengkaji kesan kecerunan keatas kelarian

aliran air permukaan. Kajian ini dijalankan di Tadahan Air Kardeh, terletak 42 km keutara

Mashhad, Jajahan Khorasan, Iran. Kawasan kajian ini berkoordinat diantara 59º 26´ 3˝ ke 59º

37´ 17˝ T longitud dan 36º 37´ 17˝ ke 36º 58´ 25˝ U latitud. Sehubungan itu, Kardeh

“USDA_NRCS_CN” (US Department of Agriculture, Natural Resources Conservation Service

Curve Number) telah digunakan dalam kajian ini untuk menganggarkan kedalaman kelarian air

permukaan dalam satu tadahan air separa kering. Peta kumpulan tanah haidrologi, gunatanah dan

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kecerunan dijana dalam persekitaraan GIS. Nilai curve number telah diberikan kepada peta

kumpulan haidrologi tanah dan gunatanah yang telah dikhususkan untuk kawasan kajian. Kaedah

curve number seterusnya menganggarkan kedalaman kelarian air permukaan untuk “storm

events” yang terpilih dalam kawasan tadahan air dikaji. Kesan kecerunan keatas CN number dan

kedalaman aliran air permukaan juga telah ditentukan. Anggaran kedalaman aliran air

permukaan dan kedalaman air permukaan yang telah ubahsuai dengan nilai kecerunan telah

dibandingkan secara statistik dengan data aliran air permukaan sebenar untuk kawasan kajian.

Perbandingan “Pair wise” telah dilakukan melalui t-test dan “Pearson correlation analysis” dan

“Percent error” untuk mengetahui sebarang hubungkait antara kedalaman kelarian air permukaan

anggaran dan nilai sebenar. Keputusan kajian menunjukkan bahawa tidak ada perbezaan yang

signifikan antara cara mengamati dan limpasan dianggarkan kedalaman (P> 0.05). Cukup

korelasi positif dikesan antara diamati dengan anggaran limpasan dan lereng-disesuaikan

kedalaman limpasan (r = 0.5; P <0.01) dan (r = 0.56; P <0.01), masing-masing. Sekitar 9% dan

6% daripada anggaran dan lereng-nilai-nilai ±10% daripada nilai tercatat masing-masing.

Dilimpasan disesuaikan dalam samping itu, sekitar 43 dan 37 peratus daripada anggaran dan

lereng-nilai-nilai ±50%, masing-masing. Yang disesuaikan dalam kesalahan oleh lebih daripada

Analisis statistik menunjukkan bahawa percent error daripada anggaran lereng-kedalaman

limpasan disesuaikan secara signifikan (p <0.01) lebih rendah daripada percent error daripada

anggaran kedalaman limpasan. Penurunan kesalahan peratus boleh dijelaskan oleh peranan

generasi cerun limpasan daerah aliran sungai di cerun curam. Keputusan kajian menunjukkan

bahawa CN adalah kaedah yang berkesan untuk homogeneous tadahan

dalam hal penggunaan tanah, tanah, dan iklim daripada yang heterogenous seperti Kardeh

tadahan. Dalam tadahan itu boleh digunakan dengan akurasi sekitar 60 peratus hanya untuk

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tujuan pengurusan dan pemuliharaan namun dan mungkin bukan untuk perhitungan desain

banjir.

Keywords: Curve Number, Sistem Informasi Geografis, Kardeh tadahan, Cerun-disesuaikan

kedalaman limpasan

ACKNOWLEDGMENT

First and most my gratitude and gratefulness is to God, the most gracious and merciful

for his blessing. I gratefully acknowledge the continued guidance and support of my main

supervisor Assoc. Prof. Dr. Lai Food See for his guidance in scientific formation through

these years and his patience in reviewing all manuscripts and dealing with my

impatience. His time and energy for this study were unforgettable. I would also like to

thank my committee members Dr. Mohd Hasmadi Ismail and Mr. Ismail Adnan Abdul

Malek for their ideas and assistances that have enhanced the scope of this work.

Special gratitude goes towards the University Putra Malaysia for providing research

fellowship to make this research possible and the staff of Faculty of Forestry for their

kind guidance and help. I am also particularly grateful to Khorasan Razavi Regional

Water Authority, Department of Watershed Management and Abkhiz Gostar Shargh Co.

Ltd. for providing the data and maps of study watershed.

My deepest appreciation is to my special friends Mr. Akhoundi, Mr. Arabkhedri, Mrs.

Ostad who had shared me very useful views about GIS and hydrology.

Finally, I want to thank my husband for her love, support, sacrifices and patience and also

my blessed family for instilling me the importance of education and their financial,

encouragement, inspiration, concern and continuous moral support during doing this

work.

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This thesis was submitted to the Senate of Universiti Putra Malaysia and has been accepted as fulfilment of the requirement for the degree of Master of Science. The members of the Supervisory Committee were as follows: Lai Food See, PhD Associate Professor Faculty of Forestry Universiti Putra Malaysia (Chairman) Mohd Hasmadi Ismail, PhD Lecturer Faculty of Forestry Universiti Putra Malaysia (Member) Ismail Adnan Abd. Malek, MF Lecturer Faculty of Forestry Universiti Putra Malaysia (Member) HASANAH MOHD. GHAZALI, PhD Professor and Dean School of Graduate Studies Universiti Putra Malaysia Date: 16 November 2009

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DECLARATION

I hereby declare that the thesis is my original work except for quotations and citation,

which have been duly acknowledged. I also declare that it has not been previously, and is

not concurrently, submitted for any other degree at University Putra Malaysia or at any

other institutions.


Date:

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TABLE OF CONTENTS PageABSTRACT i ABSTRAK iii ACKNOWLEDGMENTS vi APPROVAL vii DECLARATION ix LIST OF TABLES xii LIST OF FIGURES xiv LIST OF ABBREVIATIONS xvi

CHAPTER

1 INTRODUCTION 1.1 General 1 1.2 Problem Statement 3 1.3 Objectives 4 2 LITERATURE REVIEW 2.1 Introduction 5 2.2 Surface runoff 5 2.2.1 Factors affecting runoff 6 2.2.2 Runoff depth estimation methods 7 2.3 Historical background of NRCS-CN method 10 2.4 Advantages of NRCS-CN Method 11 2.5 NRCS-CN method concept 13 2.6 Derivation of empirical relationship for NRCS-CN 17 2.6.1 Retention parameters 22 2.7 Factors affecting the curve number value 24 2.7.1 Antecedent Moisture Condition (AMC) 24 2.7.2 Land use or cover 28 2.7.3 Hydrologic soil group (HSG) 30 2.7.4 Hydrologic Condition in relation to land treatment 32 2.7.5 Importance of Slope 34 2.8 Description of GIS 38 2.8.1 Integration of NRCS-CN method and GIS 40 2.9 Application of the NRCS-CN method in Iran 44 2.10 Summary 44

3 MATERIALS AND METHODS 3.1 Introduction 46 3.2 Materials 46 3.2.1 Data sources 46 3.2.2 Software used for data processing 47 3.2.3 Study area 48

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3.3 Methodology 69 3.3.1 Generating hydrologic soil group map (HSGs) 69 3.3.2 Generating CN map with GIS 73 3.3.3 Generating slope map with GIS 75 3.3.4 Antecedent moisture condition (AMC) 78 3.3.5 Estimating runoff depth 80 3.3.6 Determining runoff depth for observed data 88 3.3.7 Statistical analysis 89 3.3.8 Summary

89

4 RESULTS AND DISCUSSION 4.1 Introduction 91 4.2 Hydrologic soil groups 91 4.3 CN values map 95 4.4 Runoff depth 98 4.5 Slope-adjusted runoff depths 100 4.5.1 Slope-adjusted CN values 102 4.5.2 Estimated slope-adjusted runoff depth 104 4.6 Runoff depth for observed data 107 4.7 Comparison of estimated and observed runoff 108 4.7.1 Data comparison 112 4.7.2 Statistical analysis 113 5 CONCLUSIONS AND RECOMMENDATIONS 5.1 Conclusions 119 5.2 Recommendations 121 REFERENCES 123 APPENDICES 130 BIODATA OF STUDENT

LIST OF TABLES

Table Page

2.1 Methods used for estimating runoff depth at watershed scale

8

2.2 Instances of conducted research on the application of NRCS-CN 14

2.3 Available methods for computing CN value in NRCS-CN method

21

2.4 Seasonal rainfall limits for AMC classes

25

2.5 Hydrologic soil groups definitions

32

2.6 Hydrologic condition with respect to infiltration and runoff

33

2.7 Slope classes in relation to terrain

35

2.8

Curve Numbers for Hydrological Soil-Cover Complexes for Antecedent Moisture Condition Class II and Ia= 0.2 S

36

2.9 Selected studies on the integration of GIS with NRCS-CN

42

3.1 Physiographic characteristics of the study site

51

3.2 Average monthly precipitation of the Kardeh watershed (over 25 years)

54

3.3 Average monthly temperature of the Kardeh watershed (over 25 years)

55

3.4 Hydrological equipments installed in the Kardeh watershed

58

3.5 Area of geological structures of the watershed 60

3.6 Infiltration rates of soils in Kardeh watershed 62

3.7 Vegetation types of rangelands in Kardeh watershed 66

3.8 Land use/ cover classes present in the Kardeh catchment 67

3.9 Soil characteristics of Kardeh Watershed 71

3.10 Conversion Table for curve numbers (CNs) from Antecedent Moisture Condition class II to AMC class I and AMC class III

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3.11 Conversion table for curve numbers (CN) from Antecedent Moisture Condition Class II to AMC Class I or Class III (Soil Conservation Service 1972)

79

3.12 Calculation of maximum potential retention (s) leading to runoff depth estimation (for example CN=35)

83

3.13 Calculation of weighted runoff depth for one storm event in entire watershed (for example storm dated on 14/05/91)

84

3.14 Calculation of slope-adjusted runoff depth (for example CN = 35; slope = 17 %)

87

4.1 Hydrologic soil groups in Kardeh catchment 91

4.2 Curve number of various land use and hydrologic soil groups in the Kardeh watershed

93

4.3 CN values for Antecedent Moisture Condition II (AMC II) 96

4.4 Estimated runoff depth (for example CN=35) for all events 98

4.5 Estimated runoff depths for rainfall events using NRCS-CN method 99

4.6 Slope of the study watershed 100

4.7 Slope-adjusted CN values for the study watershed 103

4.8 Slope-adjusted runoff depth (for example CN = 35; slope = 17 %) 105

4.9 Estimated slope-adjusted runoff depths for rainfall events using NRCS-CN method

106

4.10 Direct runoff depth for selected storm events in the study watershed 107

4.11 Comparison of runoff generated by NRCS-CN in the Kardeh watershed

110

4.12 Details of percent error between estimated and observed runoff depth 111

4.13 Checking the normality distribution of the data 114

4.14 Means comparison of estimated and observed runoff depth for the Kardeh watershed

115

LIST OF FIGURES

Figure Page

2.1 Graphical solution of equation 3 showing runoff depth as a function of rainfall depth and CN ( Soil Conservation Service 1972)

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3.1 Flow diagram of the research method 47

3.2 Location of the study area in Iran 50

3.3 Counter map of the study area 52

3.4 Ombrothermic diagram of mean monthly temperature and mean monthly precipitation at Kardeh watershed

55

3.5 Hydroclimatological gauging stations in the Kardeh watershed 57

3.6 Land use/cover map of the study watershed 68

3.7 Flow diagram for generating of hydrologic soil group map 70

3.8 Soil unit map of the study watershed 72

3.9 Flow diagram for generating of CN map 74

3.10 Flow diagram for generating of slope map 75

3.11 TIN map for the study watershed 76

3.12 DEM for the study watershed 77

4.1 Hydrologic soil groups of Kardeh catchment 94

4.2 Map of Curve Number values for Kardeh watershed 97

4.3 Slope map of the Kardeh watershed 101

4.4 Relationship between the calculated CN from SCS standard tables and Slope-adjusted CN ration and land slope

103

4.5 Comparison of estimated, slope-adjusted and observed runoff depths

112

4.6 Correlation between observed and estimated runoff depth 117

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4.7 Correlation between observed and slope-estimated runoff depth 118

LIST OF ABBREVIATIONS

3D Three Dimensional

AMC Antecedent Moisture Condition

ANN Artificial Neural Network

ARC Antecedent Runoff Condition

CN Curve Number

DEM Digital Elevation Model

ESRI Environmental Systems Research Institute

FHWA Federal High Way of America

GIS Geographic Information System

GIUH Geomorphological Instantaneous Unit Hydrograph

ha Hectare

hr Hour

ILWIS Integrated Land and Water Information System

ICAR Indian Council of Agricultural Research

LULC Land Use/Land Cover

mm Millimeter

min Minute

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NDVI Normalized Difference Vegetation Index

NCC National Cartography Centre

NEH-4 National Engineering Hand book Section 4

NRCS Natural Resource Conservation Service

RS Remote Sensing

SCS Soil Conservation Service

SPSS Statistical Program for Social Science

TIN Triangular Irregular Network

U.B.C University of British Columbia

UH Unit Hydrograph

USDA United States Department of Agriculture

WHAT Web-based Hydrograph Analysis Tool

Chapter 1

Introduction

1.1 General

The annual average precipitation of Iran ranges from less than 50 mm in the deserts to

more than 1500 mm along the coast of Caspian Sea. The average annual rainfall is 252

mm and approximately 90% of the country is arid or semiarid. Periodic droughts are a

normal phenomenon and water shortage is a frequent problem in the arid regions. As

such, water is a priority issue at national and individual levels in Iran.

In spite of water deficiency in arid and semiarid areas, there are many flash floods every

year in such areas. That is because of high rainfall intensity although unevenly distributed

in these areas. In some arid and semi arid regions what causes flood is lack of water

resources management. Thus appropriate planning for water resources management is

imperative in water deficiency regions. Lack of adequate consideration to watershed

management in most areas in Iran not only cause water deficiency in parts of watersheds

but also generate sever floods downstream. It has been reported in the past that changes

to the upstream portion of watersheds affected hydrologic and hydraulic characteristics of

the downstream portion of the basin.

A detail analysis of surface runoff is highly important for flood control, stream flow

forecasting and reservoir design. Large amount of precipitation are lost as surface runoff

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due to lack of watershed management practices, poor vegetation cover, and continuation

of inappropriate land use and land degradation.

In addition to the above problems, most basins in Iran do not have sufficient numbers of

gauges to record rainfall and runoff volume. Scarcity of reliable recorded data therefore is

another serious problem which planners and researchers face for the analysis of the

hydrology of the arid regions.

While having runoff data is essential in all watershed development and management

plans, very little work has been previously done in the watersheds of Iran in estimating

runoff volume from rainfall in ungauged watersheds. Estimating basin runoff in

ungauged watersheds is of tremendous importance in Iran.

There are several approaches to estimate ungauged basin runoff. Examples are the

University of British Columbia Watershed Model (UBCWM), Artificial Neural Network

(ANN), Soil Conservation Service Curve Number model (SCS-CN), and

Geomorphological Instantaneous Unit Hydrograph (GIUH). Among these methods, the

SCS method (now called Natural Resources Conservation Service Curve Number method

(NRCS-CN)) is widely used because of its flexibility and simplicity. In this method, the

runoff volume estimation takes into consideration some of the watershed parameters

including land use, discharge, soil characteristics; and climatic parameters as rainfall

quantity. The method combines the watershed parameters and climatic factors in one

factor called the Curve Number (CN).

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Conventional methods for runoff measurement are difficult, time consuming and error-

prone because of the vastness of basins and inaccessible terrain in many places. Thus, we

need to use new tools such as Geographic Information System (GIS), to generate reliable

runoff records for conserving soil and water resources in watershed planning.

This study emphasizes the use of GIS technique to develop a data base containing all the

information of the study watershed for direct runoff volume estimation using the NRCS-

CN model. GIS is used in hydrologic modeling to facilitate processing, management and

interpretation of hydrologic data. The ability of GIS to combine different types of data

such as land use, land cover, soil and slope has led it to significant increase in

hydrological applications. GIS provides efficient tools for data input into database,

retrieval of selected data for further processing and software modules which can analyze

and manipulate the data in order to generate desired information on specific forms.

Integration of GIS and curve number increases the accuracy and provide quick estimation

of runoff values. The essence of this study is the application of GIS and NRCS-CN as a

simple model to estimate runoff values in the Kardeh basin, Iran.

1.2 Problem statement

Due to serious soil erosion and water deficiency problems in most areas of Iran, natural

resources conservation is a vital issue. Despite this pressing issue, few studies have been

carried out in rainfall-runoff modeling in Iran. While accurate data is necessary for

appropriate management and planning of watershed resources, few drainage basins in

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Iran have well-established hydrometric stations. Conventional methods of runoff

measurement are costly, time consuming and difficult because of inaccessible terrain in

many of the watersheds in Iran. Thus, the use of new tools, for instance GIS, to generate

supporting land-based data for conserving soil and water resources in watershed planning

is very much needed.

1.3 Objectives

The aim of this study is to evaluate the use of NRCS curve number method for estimating

runoff depth in the Kardeh watershed in Iran. The specific objectives include:

i. To determine the ranges of probable CN values for the study watershed.

ii. To determine the effect of slope of watershed on CN values and runoff

generation.

Finally the accuracy between estimated and observed runoff data will be tested

statistically. If the study finds accurate estimated runoff depth compared with observed

runoff, then the result can be applied for adjacent watersheds.

Chapter 2

Literature Review

2.1 Introduction

This chapter is a review of the literature on runoff estimation, with particular reference to

the NRCS-CN method. The various factors influencing runoff generation and spatial

distribution are discussed in sub sections in an attempt to synthesize key findings of

studies with regard to the intent of this study.

2.2 Surface runoff

Surface runoff is the water running over land resulting from the infiltration excess during

a rainfall (or snow melt) event. Horton (1933) was the first to study this process, and

proposed an infiltration-capacity-based model referred to as the Hortonian overland flow.

Later, Dunne (1970, 1978) proposed a saturation-based (saturation excess) runoff

generation process and outlined the importance of a rising water table in initiating and

sustaining surface runoff (cited by Ajayi, 2004).

Plot-based measurement and the measurement of rainfall intensity with appropriate rain

gauges were the basis for better insight into the process of surface runoff and

understanding of the factors influencing that process at a small scale.

2.2.1 Factors affecting runoff

The most important factors affecting direct runoff are the rainfall depth and duration, and

although climatic, physiographic conditions and land use are also important influences at

the catchment scale (Kovář, 2006). The combined effect of rainfall intensity and the

physical properties of the soil surface have significance role in surface runoff generation

process. These factors interact at the same time and the extent of each of them depends

on the conditions of the study area.

2.2.1.1 Climatic factors

There are various factors of climate influencing runoff in a watershed. Some of these

factors are:

• Type of precipitation (rain, snow, sleet, etc.);

• Rainfall intensity;

• Rainfall amount;

• Rainfall duration;

• Distribution of rainfall over the drainage basin;

• Direction of storm movement;

• Precipitation that occurred earlier and resulting soil moisture;

• Other meteorological and climatic conditions that affect evapotranspiration, such

as temperature, wind, relative humidity, and season.

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2.2.1.2 Watershed characteristics affecting runoff

Runoff generation process in a watershed can be affected by different characteristics of

the catchment including:

• Land use;

• Vegetation;

• Soil type;

• Drainage area;

• Basin shape;

• Elevation;

• Topography, especially the slope of the land ;

• Drainage network patterns;

• Ponds, lakes, reservoirs, sink, etc. in the basin, which prevent or delay runoff

from continuing downstream.

2.2.2 Runoff depth estimation methods

The assessment of relationship between rainfall and runoff is an important and complex

issue in hydrology. In this respect, much research has been carried out and different

methods have been presented to estimate runoff depth at watershed scale (Table 2.1).

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