An-Najah National University 
Faculty of Graduate Studies 

 
 
 
 
 
 
 
 
 
 
 
 
 

GIS-Based Hydrological Modeling 
of Semiarid Catchments 

(The Case of Faria Catchment) 
 
 
 
 
 
 
 
 
 
 

By 
 

Sameer ‘Mohammad Khairi’ Shhadi Abedel-Kareem 
 
 
 

Supervisors 
 

Dr. Hafez Q. Shaheen 
Dr. Anan F. Jayyousi 

 
 
 
 
 
 
 
 
 
 
 

Submitted in Partial Fulfillment of the Requirements for the Degree of 
Master of Science in Water and Environmental Engineering, Faculty of 
Graduate Studies, at An-Najah National University, Nablus, Palestine 

2005 





 III

 
 
 
 
 
 
 

 بسم هللا الرحمن الرحيم

 

َأنَْزَل ِمَن السََّماِء َماًء فََسالَتْ َأْوِدَيةٌ بِقََدرَِها فَاْحتََمَل السَّْيُل 

)16(ألرعد .........َزَبًدا َرابًِيا  

 

 صدق اهللا العظيم

 

 
 
 
 
 
 
 
 
 
 
 
 
 



 IV

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 

… Dedicated to 
My parents, wife and my daughter (Muna) 



 V

Acknowledgments 

First of all, praise is to Allah for making this thesis possible. I would like to 

express my sincere gratitude to Dr. Hafez Shaheen and Dr. Anan Jayyousi 

for their supervision, guidance and constructive advice. Special thanks go 

also to the defense committee members.   

Thanks also go to those who helped in providing the data used in this study. 

Water and Environmental Studies Institute or giving me the chance to work 

on GLOWA project, Palestinian Water Authority (PWA) for producing of 

water data used in this study. 

My parents, brothers and sisters, thank you for being a great source of 

support and encouragement. All my friends and fellow graduate students, 

thank you. 

Special thanks to my friend Eng. Rami Qashou’ who’s support will never 

be forgotten. 

Finally, thanks to my dear wife Heba for her love, moral support and 

patience. 



 VI

Table of Contents        
 
ACKNOWLEDGMENTS ........................................................................................................ V 
TABLE OF CONTENTS ........................................................................................................ VI 
LIST OF ABBREVIATIONS .......................................................................................... VIII 
LIST OF TABLES ....................................................................................................................... IX 
LIST OF FIGURES ...................................................................................................................... X 
ABSTRACT .................................................................................................................................... XII 
 
CHAPTER ONE INTRODUCTION .................................................................................... 1 

1.1 BACKGROUND ............................................................................................................................ 2 
1.2 OBJECTIVES ................................................................................................................................. 3 
1.3 RESEARCH NEEDS AND MOTIVATIONS ....................................................................... 4 
1.4 METHODOLOGY ........................................................................................................................ 7 
1.5 DATA COLLECTION ................................................................................................................. 9 

 
CHAPTER TWO LITERATURE REVIEW ............................................................... 11 

2.1 HYDROLOGY OF SEMIARID REGIONS ........................................................................ 12 
2.1.1 Climate and Rainfall ................................................................................................ 13 
2.1.2 Runoff Generation and Channel Flow .......................................................... 16 
2.1.3 Storages ............................................................................................................................ 17 

2.2 RAINFALL-RUNOFF MODELING .................................................................................... 18 
2.2.1 Historical Overview ................................................................................................. 19 
2.2.2 Classification of Models and Basic Definitions ..................................... 21 

2.3 USE OF GIS IN HYDROLOGY .......................................................................................... 23 
2.4 PREVIOUS WORK IN THE STUDY AREA .................................................................... 26 

 
CHAPTER THREE DESCRIPTION OF THE STUDY AREA ...................... 28 

3.1 LOCATION AND TOPOGRAPHY ....................................................................................... 29 
3.2 CLIMATE .................................................................................................................................... 33 

3.2.1 Wind ................................................................................................................................... 33 
3.2.2 Temperature ................................................................................................................... 34 
3.2.3 Relative Humidity ..................................................................................................... 36 
3.2.4 Rainfall ............................................................................................................................. 36 
3.2.5 Evaporation .................................................................................................................... 38 
3.2.6 Aridity of the Catchment ....................................................................................... 40 

3.3 WATER RESOURCES ............................................................................................................ 41 
3.3.1 Groundwater Wells ................................................................................................... 41 
3.3.2 Springs .............................................................................................................................. 42 
3.3.3 Analysis of Springs Discharge .......................................................................... 43 

3.4 SURFACE WATER .................................................................................................................. 45 
3.4.1 Flow Measurements ................................................................................................. 45 
3.4.2 Quality Considerations ........................................................................................... 47 



 VII

3.5 SOIL .............................................................................................................................................. 49 
3.6 GEOLOGY ................................................................................................................................... 51 
3.7 LAND USE ................................................................................................................................. 53 

 
CHAPTER FOUR RAINFALL ANALYSIS ................................................................ 58 

4.1 RAINFALL STATIONS ........................................................................................................... 59 
4.2 CATCHMENT RAINFALL .................................................................................................... 60 

4.2.1 Density of Rain Gauges ......................................................................................... 60 
4.2.2 Consistency of Rainfall Data .............................................................................. 62 
4.2.3 Monthly Rainfall ........................................................................................................ 63 
4.2.4 Annual Rainfall ........................................................................................................... 66 
4.2.5 Trend Analysis ............................................................................................................. 68 

4.3 EXTREME VALUE DISTRIBUTION ................................................................................. 71 
4.3.1 Gumbel Distribution ................................................................................................ 72 

4.4 AREAL RAINFALL ................................................................................................................. 75 
4.5 CORRELATION ANALYSIS BETWEEN STATIONS ................................................... 77 

 
CHAPTER FIVE RUNOFF MODELING ..................................................................... 79 

5.1 INTRODUCTION ....................................................................................................................... 80 
5.2 GIUH MODEL ......................................................................................................................... 81 
5.3 TRAVEL TIME ESTIMATION OF THE KW-GIUH MODEL ............................... 83 
5.4 STRUCTURE OF THE KW-GIUH MODEL ................................................................. 87 
5.5 KW-GIUH MODEL INPUT PARAMETERS ............................................................... 91 

5.5.1 Hydraulic parameters .............................................................................................. 91 
5.5.2 Geomorphic parameters ......................................................................................... 91 
5.5.3 Parameter Estimation Using GIS ..................................................................... 92 

5.6 KW-GIUH UNIT HYDROGRAPH DERIVATION .................................................... 97 
5.7 SENSITIVITY ANALYSIS ..................................................................................................... 99 
5.8 MODEL APPLICATION FOR HYDROGRAPH SIMULATION ............................. 102 

5.8.1 Event 1, 14-2-2004................................................................................................. 103 
5.8.2 Event 2, 5-2-2005 ................................................................................................... 106 

5.9 ANALYSIS AND DISCUSSION ........................................................................................ 108 
 
CHAPTER SIX CONCLUSIONS AND RECOMMENDATIONS .............. 111 

6.1 CONCLUSIONS ...................................................................................................................... 112 
6.2 RECOMMENDATIONS ........................................................................................................ 114 

 
REFERENCES ............................................................................................................................. 117 
APPENDIX A (TABLES) ..................................................................................................... 125 
APPENDIX B (FIGURES) .................................................................................................. 162 
APPENDIX C (KW-GIUH OUTPUTS) .................................................................... 171 
APPENDIX D (PICTURES) .............................................................................................. 179 
  ب ......................................................................................................................................................... الملخص



 VIII

List of Abbreviations 
Symbol The meaning 

KW-GIUH Kinematic Wave based Geomorphological Instantaneous Unit 
Hydrograph

GIS Geographical Information System 
DEM Digital Elevation Model 
EAB Eastern Aquifer Basin  
PHG Palestinian Hydrology Group  
PWA Palestinian Water Authority 
IDF Intensity Duration Frequency Curves 
MOT Meteorological Office of Transport  
WESI Water and Environmental Studies Institute 
N  Optimal number of stations 
Ep  Allowable percentage of error 
Cv  Coefficient of variation 

avP  Mean of rainfall 
1−nσ  Standard deviation 

P(x) Probability of exceedance 
oixT  Time for the flow to reach equilibrium 
ioq  ith-order overland flow discharge per unit width 

Lq  Lateral flow rate 
iosh  ith-order water depth at equilibrium 
icsQ  ith-order channel discharge at equilibrium 

rkxT  Travel time for the channel storage component  

ckxT  Travel time for the channel translation component 
iOAP  Ratio of the ith-order overland area to the catchment area 

A Total area of the catchment 
iN  ith-order stream number 
icL  ith-order stream length 

on  Overland flow roughness 
cn  Channel flow roughness 

 Ai  ith-order sub catchment contributing area 
 S io  ith-order overland slope 
 S ic  ith-order channel slope 

ji xxP  Stream network transitional probability 
ΩB  Channel width at catchment outlet 

Ω  Stream network order 
 



 IX

List of Tables 
Table 1: Abstraction from Wells in the Faria Catchment ........................... 42 
Table 2: Spring Groups and Spring Information within Faria catchment .. 43 
Table 3: Surface Water Quality Parameters for Badan and Faria Streams . 49 
Table 4: Major Soil Types and Characteristics in Faria Catchment ........... 50 
Table 5: Total Land use Cover of the Faria Catchment .............................. 56 
Table 6: Available Rainfall Stations within the Faria Catchment .............. 60 
Table 7: Monthly Rainfall Totals of Nablus Station (mm) ......................... 65 
Table 8: Statistical Measurements of the Annual Rainfall of the Six 

Stations of Faria Catchment .......................................................... 67 
Table 9: Trend Equations for the 5-years Moving Average of the Six 

Stations .......................................................................................... 69 
Table 10: t  and  

1 , 2
2

n
t α
− −

with 90% and 95% Confidence Intervals .............. 71 

Table 11: Parameters of Gumbel Distribution for the Six Stations of the 
Faria Catchment .......................................................................... 74 

Table 12: Areal Rainfall Using the Thiessen Polygon Method .................. 76 
Table 13: Coordinates, Elevations, Rainfall Averages and Estimated 

Averages for the Six Stations ...................................................... 79 
Table 14: ji xxP  For the Three Sub-catchments ............................................ 95 
Table 15: KW-GIUH Input Parameters for Al-Badan Sub-catchment ....... 96 
Table 16: KW-GIUH Input Parameters for Al-Faria Sub-catchment ......... 96 
Table 17: KW-GIUH Input Parameters for Al-Malaqi Sub-catchment ...... 98 
 

 

 

 

 

 



 X

List of Figures 
Figure 1: A flow Chart Depicting the General Methodology Followed in 

this Study ....................................................................................... 9 
Figure 2: Arid Regions around the World (UNESCO, 1984) ..................... 12 
Figure 3: Hydrologic Cycle with Global Annual Average Water Balance 

(Chow et al., 1988) ...................................................................... 15 
Figure 4: Classification of Hydrological Models (Lange, 1999) ................ 23 
Figure 5: Location of the Faria Catchment within the West Bank ............. 30 
Figure 6: Springs and Wells within the Faria Catchment ........................... 31 
Figure 7: Topographic Map of the Faria Catchment .................................. 32 
Figure 8:  Mean Monthly Temperatures in Nablus and Al-Jiftlik .............. 35 
Figure 9: Spatial Distribution of the Mean Annual Temperature in the Faria 

Catchment .................................................................................... 35 
Figure 10: Rainfall Stations and Rainfall Distribution within the Faria 

Catchment .................................................................................. 37 
Figure 11:  Monthly Rainfall and Potential Evapotranspiration Rates (ETo) 

in   Nablus and Al-Jiftlik ........................................................... 39 
Figure 12: Potential Annual Evapotranspiration Rates in the Faria   

Catchment ................................................................................. 40 
Figure 13: Average, Maximum and Minimum Monthly Discharge of Total 

Springs within Al-Badan Sub-catchment.................................. 44 
Figure 14: Average, Maximum and Minimum Monthly Discharge of Total     

Springs within Al-Faria Sub-catchment .................................... 45 
Figure 15: Soil Types of the Faria Catchment ............................................ 51 
Figure 16: Geology Map of the Faria Catchment ....................................... 52 
Figure 17: Part of the airphotos of Faria Catchment ................................... 53 
Figure 18: The New Land use Map of the Faria Catchment ....................... 57 
Figure 19: Double Mass Curve for the Stations of Faria Catchment .......... 63 
Figure 20: Mean Monthly Rainfall of the Six Stations of the Faria 

Catchment ................................................................................. 64 
Figure 21: Monthly Average Rainfall of Nablus Station Plotted As 

Averages of Five Years Intervals.............................................. 66 
Figure 22: Yearly Rainfall of Nablus Station ............................................. 67 
Figure 23: The 5-year Moving Average of Nablus, Beit Dajan and Al-Faria 

Stations ...................................................................................... 69 
Figure 24: The 5-year Moving Average of Tubas, Taluza and Tammun    

Stations ...................................................................................... 69 
Figure 25: Gumbel Plots of Annual Rainfall for Nablus Station ................ 74 
Figure 26: Gumbel Plots of the Standardized Variable of the Six Stations of 

Faria Catchment ........................................................................ 75 
Figure 27: Thiessen Polygon Map for the Faria Catchment ....................... 77 



 XI

Figure 28: Runoff Structure for a second-Order Catchment (Lee and Chang, 
2005) ......................................................................................... 84 

Figure 29: Surface Flow Paths of A third-Order Catchment (Lee and 
Chang, 2005) ............................................................................. 90 

Figure 30: Digital Elevations Model (DEM) for the Faria Catchment ....... 93 
Figure 31: The Three Sub-catchments of the Faria Catchment .................. 94 
Figure 32: The Stream Order Networks for the Three Sub-catchments of 

the Faria Catchment .................................................................. 95 
Figure 33: 1mm-GIUH for Al-Faria and Al-Badan Sub-catchments ......... 99 
Figure 34: 1mm-GIUH for Al-Malaqi Sub-catchment ............................... 99 
Figure 35: Variation of GIUH with Excess Rainfall ................................... 99 
Figure 36: Sensitivity Analysis of Channel Width on GIUH ................... 100 
Figure 37: Sensitivity Analysis of Overland Roughness Coefficient on 

GIUH ....................................................................................... 101 
Figure 38: Sensitivity Analysis of Channel Roughness Coefficient on 

GIUH ....................................................................................... 102 
Figure 39: Al-Badan Sub-catchment and its Drainage Network .............. 103 
Figure 40: Rainfall Depth and Infiltration Capacity Curve of 14/2/2004 

Event ........................................................................................ 105 
Figure 41: Recorded and Estimated Direct Runoff Hydrograph for Al-

Badan Sub-catchment, Event of 14/2/2004 ............................. 106 
Figure 42: Rainfall Depth and the Phi-Index of Event of 5/2/2005 .......... 107 
Figure 43: Recorded and Estimated Direct Runoff Hydrograph for Al-

Badan Sub-catchment, Event of 5/2/2005 ............................... 108 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 



 XII

 GIS-Based Hydrological Modeling 
of Semiarid Catchments 

(The Case of Faria Catchment) 
By 

Sameer ‘Mohammad Khairi’ Shhadi Abedel-Kareem 
Supervisors 

Dr. Hafez Q. Shaheen 
Dr. Anan F. Jayyousi 

Abstract 
Extreme events, such as severe storms, floods, and droughts are the main 

features characterizing the hydrological system of a region. In the West 

Bank, which is characterized as semiarid; little work has been carried out 

about hydrological modeling. This thesis is an attempt to model the 

rainfall-runoff process in Faria catchment, which is considered as one of 

the most important catchments of the West Bank. Faria catchment 

dominating the north eastern slopes of the West Bank is a catchment of 

about 334 km2 and has the semiarid characteristics of the region. The 

catchment is gauged by six rainfall stations and two runoff flumes.  

Statistical analysis including annual average, standard deviation, maximum 

and minimum rainfall was carried out for the rainfall stations. The internal 

consistency of rainfall measurements of the six stations was examined by 

using the double mass curve technique. The results show that all station 

measurements are internally consistent.  

Gumbel distribution fits well the annual rainfall and can be used for future 

estimations. It provides means to understand and evaluate the distribution 

characteristics of the rainfall in the Faria catchment. Trend analysis of the 

rainfall has shows an increasing trend for the stations with high elevations 

and a decreasing trend for low elevated ones. The multiple regression 

analysis applied to the six rainfall stations proved to be strongly correlated. 



 XIII

GIS-based KW-GIUH hydrological model was used to simulate the 

rainfall-runoff process in the Faria catchment. GIUH unit hydrographs 

were derived for the three sub-catchments of Faria namely Al-Badan, Al-

Faria and Al-Malaqi. The KW-GIUH model is tested by comparing the 

simulated and observed hydrographs of Al-Badan sub-catchment for two 

rainstorms with good results. Sensitivity of the KW-GIUH model 

parameters was also investigated. The simulated runoff hydrographs proved 

that the GIS-based KW-GIUH model is applicable to semiarid regions and 

can be used to estimate the unit hydrographs in the West Bank catchments.  



 1

 

 

 

 

 

 

CHAPTER ONE 

INTRODUCTION 
 
 
 
 
 
 
 
 
 
 
 



 2

1.1 Background 

Water is the chief ingredient of life and all ancient civilizations flourished 

only near the water sources and then probably collapsed when the water 

supply failed. Water is a finite resource, essential for agriculture, industry 

and human existence. Without water of adequate quantity and quality, 

sustainable development is impossible. Water resources management is 

essential to ensure the availability of water, when and where it is needed, 

and to safeguard its quality.  

Hydrologists and water engineers are always concerned with discharge 

rates resulting from rainfall. Not only measuring rainfall and the resulting 

runoff are of interest, but also the process of transforming the rainfall 

hyetograph into runoff hydrograph. Peak flow rate and time to peak are the 

two important hydrograph characteristics that need to be estimated for any 

catchment. Unfortunately, the classic problem of predicting these 

parameters is usually difficult to resolve because many rivers and streams 

are ungauged, especially those in developing regions or isolated areas. 

Even in cases where catchments are gauged, the period of record is often 

too short to allow accurate estimates of the different hydraulic parameters.  

Flood frequency analysis enables the user to predict flow rates with certain 

return periods. Historical flow data is necessary to conduct such analysis. 

Hydrological models that incorporate catchment characteristics to predict 

flow rates at a given location in the catchment is another tool to be utilized 

in cases where historical flow records are not available.  

Hydrological simulation models can take the form of theoretical linkage 

between the geomorphology and hydrology. The geomorphological 

instantaneous unit hydrograph (GIUH) is one approach of this kind of 



 3

model. The GIUH focuses on finding the catchment response given its 

geomorphological features. The GIUH model is applied in this study to 

Faria catchment in the northern West Bank. The model uses catchment 

characteristics to predict flow rates. 

West Bank is a semiarid region. In arid and semiarid regions storm water 

drainage and hydrological modeling is important as in humid regions 

because it is not only a drainage problem but also a water resources 

management and planning problem. Hydrological modeling in the West 

Bank has not been given enough care and no intensive studies have been 

done. 

In characterizing the catchment, GIS has been applied. Using GIS in 

hydrology has become an important issue since the beginning of 1980 and 

up to the present. It enables the user to handle and analyze the hydrological 

data more efficiently.  

This thesis concentrates on modeling the rainfall-runoff process in the 

upper part of the Faria catchment in the northern West Bank. GIS-based 

KW-GIUH hydrological model was applied as it is available and can model 

ungauged catchments. The KW-GIUH model can be applied to any excess 

rainfall through convolution to produce the direct runoff hydrograph.  

1.2 Objectives 

Modeling the runoff in the Faria catchment will provide basic information 

for the managers to understand runoff generation within the catchment and 

thus support the decision-making process about future development of the 

water resources in the area. This will enhance the development of the 



 4

agricultural sector. It will also support the studies of the Jordan River Basin 

as Wadi Faria catchment is a major contribution to the Jordan River. 

The main objective of this research is to model the rainfall runoff process 

of the Faria catchment and to derive the unit hydrograph for the catchment. 

The KW-GIUH model that was developed for ungauged catchments is to 

be used in this research. The geomorphological and topographic 

characteristics were provided using the GIS system.  

The other objectives of this study are: 

1. Analysis of rainfall data of the Faria catchment. 

2. Investigate the rainfall runoff process in semiarid regions. 

1.3 Research Needs and Motivations  

Faria catchment is predominantly arid and semiarid characterized by its 

natural water resources scarcity, low per capita water allocation and 

conflicting demands as well as shared water resources.  This scarcity leads 

to the limited availability of water resources and the dire need to manage 

these resources.  

Faria catchment, located in the northeastern part of the West Bank, 

Palestine, is one of the most important agricultural areas in the West Bank. 

The predominantly rural population in the catchment is growing rapidly, 

which results in increasing demand for natural water resources.  

The prolonged drought periods in the catchment and the high population 

growth rate in addition to other artificial constraints have negatively 

affected the existing obtainable surface water and groundwater resources. 



 5

Due to the fact that the available water resources in the Faria catchment are 

limited and are not sufficient to fulfill the agricultural and residential water 

demand, reliability assessment of water availability in the Faria catchment 

is of great importance in order to optimally manage the local water 

resources.  

Rural population in the Faria catchment faces a series of problems. These 

problems are related to different causes including inefficient management, 

water shortages, environmental pollution, and Israeli occupation. The key 

problems of the Faria catchment relevant to the water resources can be 

summarized as follows: 

1. Lack of proper management of water resources causes over 

utilization of the scarce water resources.  

2. The water is not properly allocated between upstream and 

downstream communities and thus water use rights need to be well 

established and institutionalized. 

3. More than 40% of the people in the catchment lacks water supply for 

drinking purposes. 

4. The estimated annual water gap between water needs and obtainable 

water supply is about 20 millions cubic meters. This gap is 

increasing rapidly with time. 

5. Lack of storage capacity and non existence of small dams to capture 

the rain floods during the rainy season in order to be used later (As to 

peace agreements, permits for such projects are required from Israeli 

occupation authorities, which are almost impossible to obtain). 



 6

6. Unbalanced utilization of groundwater causes increasing salinity 

especially in the south eastern part of the catchment in the proximity 

of the Jordan River. 

7. Water losses through evaporation and infiltration from the 

agricultural canals are high and thus large quantities of water are not 

fully utilized. 

8. Soil erosion in the lower part of the catchment is of great concern.   

9. Water pollution is an ongoing problem. For instances surface water 

originating from the springs mixes with wastewater coming from 

Nablus City and Faria refugee camp. 

10. There is no treatment plant in the catchment.  

11. Cesspools are major threats to pollute the groundwater aquifers and 

springs. 

12. The unbalanced use of fertilizers and pesticides has led to the 

pollution of the scarce water resources. 

13. Unmanaged solid waste dumping in some areas adds additional 

complexity to the pollution problems. 

14. Lack of permits to rehabilitate and remediate the deteriorated wells. 

15. In contrast to the shallow Palestinian wells, Israeli wells are pumping 

largely from deep aquifers and thus lowering the water table.  

From the above it can be inferred that Faria catchment is under a severe 

problematic conditions that need to be investigated in order to set up proper 



 7

strategies and management alternatives to address these problems 

efficiently indemnify.   

For the aforementioned discussion, this study is of great importance. Due to 

the fact that the available water resources in the Faria catchment are limited 

and cannot suffice for increasing water demand to fulfill the agricultural 

and residential requirements, reliability assessment of water availability in 

the Faria catchment is of great importance in order to optimally manage the 

local water resources. This situation has compelled the motivation for 

conducting a hydrological modeling to better understand and to evaluate 

the water resources availability in the Faria catchment. This modeling is 

essential to provide input data for a management system and to enable the 

development of optimal water allocation policies and management 

alternatives to bridge the gap between water needs and obtainable water 

supply under drought conditions. 

1.4 Methodology 

To achieve the above objectives, the available topographic maps of the 

region were scanned and the catchment was subdivided into sub-

catchments. Drainage lines and divides were digitized. The stream paths, 

possible flow directions and slopes have been determined using the 

available Digital Elevation Model (DEM) and the base map of the Faria 

catchment has been prepared. All the information including topography, 

land use, drainage lines, water divides, soil and geology have been 

processed using the GIS ArcView 3.2 software.  

The rainfall data recorded by the different stations of the Faria catchment 

were analyzed for typical and maximum rainfall intensities and amounts. 



 8

These were used as a tool to describe the spatial structure of the rain events 

and to regionalize point station data to catchment rainfall. Rainfall and 

runoff were measured continuously during the rainstorms of the last two 

rainy seasons of the hydrological years 2003-2004 and 2004-2005. 

Accordingly the input parameters to the KW-GIUH model have been 

estimated. 

The following summarizes the main steps that were followed: 

1. Collect all data and information from national and local institutions. 

2. Hydrological measurements and sampling of rainfall-runoff events 

completed for the two rainy seasons. 

3. Analysis of rainfall and runoff data. 

4. Set up GIS-based data as input for the model. 

5. Model application to the available different rainfall events. 

6. Model verification and sensitivity analysis. 

7. The final results of the modeling have been formulated. 

The overall methodology followed in this study is illustrated in Figure 1. 



 9
 

Figure 1: A flow Chart Depicting the General Methodology Followed in 
this Study 

1.5 Data Collection 

Hydrological data in the West Bank is very limited. Difficulties have been 

faced in collecting the necessary data for this study due to continuous 

closure of the West Bank cities. Nevertheless the catchment was visited 

several times to collect further data. Most of the data have been collected 

from the following sources: 

KW-GIUH 
Rainfall Runoff model 

Geography  
Topography 
Geomorphology 
Climate 
Geology  
Soil 
Springs 
Wells 
Rainfall 
Runoff 
Quality monitoring 
Land use development Runoff data 

GIS 
Excel 

Database 
formatting 

Characterization of the study area 
Data collection 
Flumes construction 
Site visits 
Ground truthing

Statistics analysis 
Time series analysis 
Trend analysis 
Probability analysis 
Correlation analysis 

Unit hydrograph 
derivation 

Rainfall analysis 
Geomorphological 

data 

Rainfall data 

Sensitivity 
analysis 

Model application 



 10

1. Contour Map. The available 1:50000 scale topographic maps have 

been used to collect elevation data. The maps have been scanned and 

used within the GIS environment to delineate the catchment and sub-

catchments boundaries and divides. The stream paths, possible flow 

directions and slopes have been determined using the available 

Digital Elevation Model (DEM).  

2. Water resources (springs and wells) data were obtained from the 

Palestinian Water Authority (PWA) databank. The data included 

monthly and annual measurements of the abstraction of the wells and 

yield of springs in addition to the name and coordinates of these 

resources. The information obtained was in MS Excel format. 

3. Rainfall data necessary for the analysis of the rainfall-runoff process 

have been collected from the PWA and from Nablus Meteorological 

Station for five different stations (Taluza, Tammun, Tubas, Beit 

Dajan and Al-Faria). 

4. The climatic data for this study was obtained from the Palestine 

Climate Data Handbook published by the Metrological Office of the 

Ministry of Transport (MOT), 1998.  Climatic data included average 

monthly values for maximum and minimum temperature, hourly 

mean wind speed, daily mean sunshine duration, mean relative 

humidity, pan evaporation and mean monthly rainfall for Nablus and 

Al-Faria stations.   



 11

 

 

 

 

 
 
 

 

CHAPTER TWO 

LITERATURE REVIEW 



 12

2.1 Hydrology of Semiarid Regions 

One way to define aridity is the moisture deficit, or the aridity index, which 

is the ratio of mean annual precipitation (P) to mean annual potential 

evapotranspiration (PET). This index is then reclassified into four main 

aridity zones and one humid zone and one cold tundra mountains zone, 

according to the ranges defined by UNESCO (1984). These zones are: 

hyper-arid (P/PET < 0.05), arid (0.05 <= P/ PET < 0.20), semiarid (0.20 <= 

P/ PET < 0.50), dry sub-humid (0.50 <= P/ PET < 0.65), humid (P/ PET 

>=0.65) and cold, which area that have more than six months of an average 

temperature below 0 degrees and not more than three months where the 

temperatures  reach above 6 degree centigrade. The six arid regions around 

the world are shown in Figure 2.  

 

Figure 2: Arid Regions around the World (UNESCO, 1984) 



 13

The main hydrological difference between humid areas and arid zones is a 

high variability in both space and time of all hydrologic parameters (e.g. 

rainfall intensity, infiltration rates, runoff rates). Floods, although 

infrequent and rare, appear in arid areas and often cause loss of life and 

property (Schick et al, 1997, cited by Thormählen, 2003). Many semiarid 

regions are particularly affected by flash floods, caused mainly by 

convective storm systems. The main processes that dominate during flashy 

floods are the generation of Hortonian overland flow on dryland terrain and 

transmission losses into the dry alluvial beds of ephemeral channels. In dry 

environments, the hydrological regime is governed by missing baseflow 

and single episodic flood events traveling on dry river beds, induced by 

localized, high intensity rainfall (Thormählen, 2003). 

2.1.1 Climate and Rainfall 

The main climatological feature of arid regions is the ephemeral and often 

localized nature of precipitation usually associated with immense variations 

in space and time (Thormählen, 2003). The arid zone is characterized by 

excessive heat and inadequate variable precipitation; however, contrasts in 

climate occur. In general, these climatic contrasts result from differences in 

temperature, the season in which rain falls, and in the degree of aridity. 

Three major types of climate are distinguished when describing the arid 

zone: the Mediterranean climate, the tropical climate and the continental 

climate (FAO, 1989). 

In the Mediterranean climate, the rainy season is during autumn and winter. 

Summers are hot with no rains; winter temperatures are mild, with a wet 

season starting in October and ending in April or May, followed by 5 to 6 

months of dry season.  



 14

In the tropical climate, rainfall occurs during the summer. Winters are long 

and dry. In Sennar, Sudan, an area that is typical of the tropical climate, the 

wet season extends from the middle of June until the end of September, 

followed by a dry season of almost 9 months. 

In the continental climate, the rainfall is distributed evenly throughout the 

year, although there is a tendency toward greater summer precipitation. In 

Alice Springs, Australia, each monthly precipitation is less than twice 

corresponding mean monthly temperature; hence, the dry season extends 

over the whole year. 

The rainfall that falls is either intercepted by trees, shrubs, and other 

vegetation, or it strikes the ground surface and becomes overland flow, 

subsurface flow, and groundwater flow. Regardless of its deposition, much 

of the rainfall eventually is returned to the atmosphere by 

evapotranspiration processes from the vegetation and soil or by evaporation 

from streams and other bodies of water into which overland, subsurface, 

and groundwater flow move. These processes are as illustrated by the 

hydrologic cycle in Figure 3, in which global annual average water 

balances are given in units relative to a value of 100 for the rate of 

precipitation on land.  

Rainfall intensity is another parameter which must be considered when 

evaluating the rainfall runoff process. Because the soil may not be able to 

absorb all the water during a heavy rainfall, water may be lost by runoff. 

Likewise, the water from a rain of low intensity can be lost due to 

evaporation, particularly if it falls on a dry surface.  



 15

 

Figure 3: Hydrologic Cycle with Global Annual Average Water Balance 
(Chow et al., 1988) 

A semiarid region is subject to seasonal precipitation, with little or no 

precipitation in other parts of the years. Rainfall patterns vary widely from 

region to region and, within a certain region. Temperature is high and 

annual precipitation amounts are moderate (Ponce, 1989).  

Evaporation is affected by several climatic elements (e.g. air temperature, 

relative humidity, net radiation). It is necessary to distinguish between 

actual rates of evaporation and potential rates. The concept of the potential 

evaporation assumes that water is not limited and is at all times sufficient to 

supply the requirements of the dry air and the transpiring cover. Clearly, in 

semiarid regions, the value for actual evaporation seldom equals the 

potential evaporation, but is much lower. Generally in semiarid farm lands 

there is large gap between potential Evapotranspiration and rain depth.  



 16

2.1.2 Runoff Generation and Channel Flow 

The high variability of rainfall both in time and space, leads to very high 

variability of runoff. In humid regions different runoff generation processes 

(e.g. runoff from saturated areas and slow outflow of large groundwater 

bodies) deliver more or less permanently water to perennial rivers. In 

contrast, in arid regions Hortonian overland flow, generated as infiltration 

excess runoff, is generally assumed to be the dominant mechanism of 

runoff generation (Abrahams et. al, 1994). The overland flow is described 

as water that flows over the ground surface heading for the next stream 

channel and as the initial phase of surface runoff in arid environments 

(Lange et al., 2003). On plane surfaces a quasi laminar sheet flow may 

develop, but, more usually, flow is concentrated by topographic 

irregularities and water flows anatomizing in small gullies and minor 

rivulets downhill. The main cause of overland flow is the inability of water 

to infiltrate the surface as a result of high intensity of rainfall or a low value 

of infiltration capacity or both phenomena (Thormählen, 2003). The 

difference between rainfall rate and infiltration rate is the concept of 

calculation the runoff of Hortonian overland flow. Water accumulates on 

the top of the ground surface, if the infiltration capacity of the soil is 

exceeded.  Surface depressions have to be filled with water, after that 

runoff generation start to runs down slope. Arid areas with moderate to 

steep slopes and sparse vegetation cover form the ideal conditions for 

Hortonian runoff.  

Streams in the arid and semiarid areas are usually ephemeral, since rainfall 

events are seldom occurred. Arid and semiarid ephemeral streams flowing 

only occasionally as a direct response to runoff generating rainstorms and 

remaining dry for most of the year. Flow in the large streams with their 



 17

origin outside the arid zone (e.g. Nile River, Indus River or Colorado 

River) and small spring fed streams are the only exceptions (Thormählen, 

2003). Floods in small dryland basins are usually of the flash flood type, 

either single peak floods or multiple peak events. Flash floods are almost 

produced by convective rain storm cells and are typical for small scale 

catchments (<100km²), because most thunderstorm cells are relatively 

small in diameter. Flash floods are defined as stream flows that increase 

from zero to a maximum within a few minutes or at most few hours (Graf, 

1988). 

Surface runoff in the eastern slopes of the West Bank where the Faria 

catchment is located is mostly intermittent and occurs when rainfall 

exceeds 50 mm in one day or 70 mm in two consecutive days (Forward, 

1998, cited by Takruri, 2003).  Rofe and Raffety (1965) studied runoff in 

the West Bank through monitoring and studying runoff data from 

seventeen flow gauging stations within the boundaries of the West Bank. 

They concluded that surface runoff constitute nearly 2.2% of its total 

equivalent rainfall. 

2.1.3 Storages  

Two types of surface flow losses occur in the arid lands, which fill 

temporal storages (Lange, 1999): 

1. Infiltration is a direct loss with Hortonian runoff that governs the 

volume of storm runoff. Further direct losses occur when water is 

temporarily stored on route or in the stream system as detention loss 

or when depression storages retain water in depressions on the 

surface. 



 18

2. Linear transmission losses into the riverbed alluvium of the stream 

channels reduce flood volume as indirect losses, after surface flow 

has been generated and flows spatially concentrated. 

The main water storage in dry environments is formed by coarse river bed 

alluvium. With rainfall events broadly separated in time, the alluvial fill has 

a large available volume for flood water infiltration practically at all times. 

The alluvial storages form an infiltration trap for water that flows into them 

either through the orderly tributary system or directly from adjoining slopes. 

The alluvial bodies, filled by indirect losses may be relatively permanent 

and quite deep, serving as important water storage for vegetation or local 

population. Compared to alluvial fills, the second type of storage is 

shallower. It is recharged by direct losses and is quickly emptied by 

evaporation within a few days after the rainfall event. Percolation from 

rainfall to deep aquifers is generally very small. 

2.2 Rainfall-Runoff Modeling 

The selection, analysis and use of recorded hydrographs for direct 

simulation purposes are reflected in variation of the unit hydrograph 

technique. This technique, which assumes a linearity of the transfer 

function, is computationally attractive and often sufficiently accurate. Unit 

hydrograph techniques may be applied to synthesize hydrographs either 

from recorded rainfall events or from specific return period storms 

extracted from intensity-duration-return period curves and hypothetical 

time duration patterns (Chow et al., 1988). Hydrological modeling is 

concerned with the accurate prediction of the partitioning of water among 

the various pathways of the hydrological cycle (Dooge, 1992 cited by 

Lange, 1999). Hydrological systems are generally analyzed by using 



 19

mathematical models. These models may be empirical or statistical, or 

founded on known physical laws. They may be used for such simple 

purposes as determining the rate of flow that roadway grate must be 

designed to handle, or they may be used to guide decisions about the best 

way to develop a river basin for a multiplicity of objectives. The choice of 

the model should be tailored to the purpose for which it is to be used. In 

general, the simplest model capable of producing information adequate to 

deal with the issue should be chosen (Viessman et al., 2003). 

Hydrological models are used for several practical purposes. Imagine a 

flood disaster; during the flood event a model may help to predict when and 

where there is a risk of flooding (e.g., which areas should be evacuated). 

After the flood, models may be used to quantify the risk that a flood of 

similar or larger magnitude will occur during the coming years and to 

decide what measures of flood protection may be needed for the future. 

Furthermore, models may help to understand the reasons for the magnitude 

of flood (e.g., if the flood was enlarged by human activities in the 

catchment) (Lundin et al., 1998). 

2.2.1 Historical Overview   

The development and application of hydrological models have gone 

through a long time period. The origins of rainfall-runoff modeling in the 

broad sense can be found in the middle of the 19th century, when 

Mulvaney, an Irish engineer who used in the first time the rational equation 

to give the peak flow from rainfall intensity data and catchment 

characteristics. A major step forward in hydrological analysis was the 

concept of the unit hydrograph introduced by Sherman in 1932 on the basis 

of superposition principle. The use of unit hydrograph made it possible to 



 20

calculate not only the flood peak discharge (as the rational method does) 

but also the whole hydrograph (the volume of surface runoff produced by 

the rainfall event). The real breakthrough came in the 1950s when 

hydrologists became aware of system engineering approaches used for the 

analysis of complex dynamic systems (Todini, 1988). This was the period 

when conceptual linear models originated (Nash, 1958). Many other 

approaches to rainfall-runoff modeling were considered in the 1960s. A 

large number of conceptual, lumped, rainfall-runoff models appeared 

thereafter including the famous Stanford Watershed Model (SWM-IV) 

(Crawford and Linsley, 1966) and the HBV model (Bergström and 

Forsman, 1973). A great variety of these conceptual hydrological models 

has appeared up to the present date. TOPMODEL is one remarkable model 

developed in the late 1970s (Beven and Kirkby, 1979) that is based on the 

idea that topography exerts a dominant control on flow routing through 

upland catchments.  

To meet the need of forecasting (1) the effects of land use changes, (2) the 

effects of spatially variable inputs and outputs, (3) the movements of 

pollutants and sediments, and (4) the hydrological response of ungauged 

catchments where no data are available for calibration of a lumped model, 

the physically based distributed parameter models were developed. SHE 

model is an excellent example of such models (Lange, 1999).  

Geomorphological Instantaneous Unit Hydrograph (GIUH) (Rodriguez-

Iturbe and Valdes 1979) is a recently developed physically based rainfall-

runoff approach for the simulation of runoff hydrograph, especially 

appropriate for ungauged catchments. Lange 1999 mentioned that GIUH 

model has been used by Allam (1990), Nouh (1990) and Al-Turbak (1996) 

to develop unit hydrograph for several catchments in the Kingdom of Saudi 



 21

Arabia. In the semiarid experimental catchment of Walnut Gulch, Arizona, 

USA, the long history of research provides good runoff records, which 

facilitated the successful application of calibrated models (Goodrich et al. 

1997 and Renard et al.1993 cited by Thormählen, 2003). The long history 

of research also allowed a non-calibrated model run of KINEROS, a 

complex distributed model developed for semiarid catchments 

(Thormählen, 2003). Lange et al. (1999) develop a model not depending on 

calibration but accounting for the dominant processes of arid zone flood 

generation. This has been done for the 1400 km² Zin catchment in the 

Nagab Desert. The ZIN-Model has been developed especially for large arid 

catchments and has been tested successfully for 250 km² in the semiarid 

Wadi Natuf (Lange et al. 2001). 

2.2.2 Classification of Models and Basic Definitions 

Two types of mathematical models can be used in hydrology; stochastic 

and deterministic models. In the stochastic models, the chance of 

occurrence of the variable is considered thus introducing the concept of 

probability. In the deterministic models, the chance of occurrence of the 

variables involved is ignored and the model is considered to follow a 

definite law of certainty but not any law of probability (Raghunath, 1985). 

Different classification schemes have been proposed (e.g. Chow et al., 

1988, Todini 1988). Figure 4 provide a general overview of the 

hydrological model using the classification criteria randomness, spatial 

discretization and model structure. To find the desired hydrological model 

one should ask the following questions (Lange, 1999): 

1- Is there a need to consider randomness? 



 22

2- Is there a need to consider spatial variations of model input or 

parameter? 

3- To what extent the governing physical laws have to be considered? 

Randomness is not considered in a deterministic model; a given input 

rainfall always produces the same output runoff. The outputs of a stochastic 

model are at least partially random. A deterministic distributed model 

considers the hydrological process taking place at various points in space. 

It may either be physically based, i.e. reproducing the rainfall-runoff 

process only by physical principals on the conservation of mass and 

momentum, or conceptual reflecting these principals in a simplified 

approximate manner. In deterministic lumped models hydrological systems 

are spatially averaged or regarded as a single point in scale without 

dimensions. Since hydrological processes generally are space dependent, 

spatial lumping always includes crude conceptualization. Empirical models 

do not explicitly consider the governing physical laws of the processes 

involved. They only relate input through some empirical transformed 

function. Stochastic models are termed space-independent or space-

correlated according to whether or not random variables at different points 

in space influence each other. 



 23

 

 

 

 

 

 

 

Figure 4: Classification of Hydrological Models (Lange, 1999) 

2.3 Use of GIS in Hydrology 

Geographic Information Systems (GIS) can be defined as computer based 

tools that display, store, analyze, retrieve, and process spatial data. GIS is 

being more and more involved in hydrology and water resources and 

showing promising results. GIS provides representations of the spatial 

features of the earth, while hydrological models are concerned with the 

flow of water and its constituents over the land surface and in the 

subsurface environment.  

GIS with its upcoming advanced technology has been a great advantage to 

hydrological modeling. Hydrological modeling using GIS has been great 

developed during the last decade when people realized the utility of 

incorporating GIS with hydrologic modeling. The use of digital terrain 

models have showed there potential to a number of analysis in hydrology. 

Lee (1985) cited by Al-Smadi (1998) concluded that GIS is an efficient 

tool for compiling input data for use in hydrological investigations and best 

suited distributed hydrologic models. Al-Smadi (1998) mentioned that; 

Conceptual

Deterministic 

Hydrological  
Models

Stochastic 

Space 
-independent

Space 
-correlated Distributed 

Physically based 

Lumped

Empirical 



 24

Berry and Sailor (1987) noted some of the advantages of GIS in hydrology 

and water resources. According to them, GIS provides a powerful tool for 

expressing complex spatial relationships. It provides an opportunity to fully 

incorporate spatial conditions into hydrologic inquiries. Different proposed 

levels of development can be made rapidly and the resulting hydrologic 

effects easily communicated to decision makers. 

GIS are highly specialized database management systems for spatially 

distributed data. GIS provides a digital representation of the catchment 

characterization used in hydrological modeling. Maidment (1996) 

summarized the different levels of hydrological modeling in association 

with GIS as follows: hydrologic assessment; hydrologic parameter 

determinations; hydrologic modeling inside GIS; and linking GIS and 

hydrologic models. GIS integrates different elements like automated 

mapping, facilities management, remote sensing, land information systems 

and spatial statistics. GIS serves as an input to the management information 

systems in the corporate domain and modeling. Maidment (1996) tries to 

focus on the data model which is the key to the GIS modeling in hydrology 

concluding that “It is probably true that the factor most limiting 

hydrological modeling is not the ability to characterize hydrological 

processes mathematically, or to solve the resulting equations, but rather the 

ability to specify values of the model parameters representing the flow 

environment accurately”. GIS will help overcome that limitation. Bhaskar 

et al. (1992) simulated watershed runoff using the Geomorphological 

Instantaneous Unit Hydrograph (GIUH) with the Arc-Info GIS to compile 

the required data.  

In this study GIS has been employed as a tool to determine the hydrologic 

parameter for the Faria catchment needed to compile the KW-GIUH model. 



 25

Digital Elevation Model (DEM) is used in number of sub-domains in 

hydrology. Varied hydrological applications can be driven by different 

users accessing the same pool of information. As a result, the structure of 

the database that supports the GIS, quality of the data and the way in which 

the database is managed lie at the heart of development of many GIS 

applications. The DEM have proved to be very efficient in extracting the 

hydrological data from the DEM by analyzing different topographical 

attributes (elevation, slope, aspect, relief, curvatures) for modeling 

purposes. DEM has potentially proved to be a valuable tool for the 

topographic parameterization of hydrological models especially for 

drainage analysis, hill slope hydrology, watersheds, groundwater flow and 

contaminant transport etc. The reason of adopting GIS technology in 

hydrological models is because it allows the spatial information to be 

displaced in integrative ways that are readily comprehensible and visual. 

The spatial information collected is further subjected to continuous GIS 

analysis. The GIS techniques have the potential for widespread application 

to resource evaluation, planning and management (Grover, 2003). Several 

of the most popular computer models such as HEC-RAS, HEC-HMS, and 

Mike SWMM have GIS capabilities that are seldom used. GIS technology 

has not been used more widely because:  

• Lack of suitable data. 

• The technology is too expensive. 

• The engineering community lack training and education in GIS.  



 26

2.4 Previous Work in the Study Area 

Few reports appear in the literature concerning the runoff estimatation and 

analysis of rainfall data in the West Bank. Rofe and Raffety (1965) have 

installed special gauging networks which was designed and illustrated for 

ten wadis. The data were recorded for the year 1962/63 only. The results of 

this study show that the overall percentage of the rainfall-runoff was 2.2%. 

Rofe and Raffety (1965) also concluded that runoff was negligible in North 

West Bank. After the occupation of the West Bank in 1967, the runoff has 

cautioned to be measured by Israelis from many gauging stations located 

outside the boundaries of the West Bank. There are some stations located 

near the Green line (the 1967 cease fire agreement between the Palestinians 

and Israelis) which may provide reliable historic records on surface runoff.  

Husary et al., (1995) analyze the rainfall data for the northern west bank. 

They presented the relationship between rainfall and runoff in Hadera 

catchment. They found that the ratio of runoff to rainfall ranges from 0.1% 

to 16.2% with an average of 4.5% for the period of 1982/83-1991/92.  

Ghanem (1999) conducted a hydrological and hydrochemical investigation 

of the Faria drainage basin using GIS. According to Ghanem runoff is 2% 

of rainfall for the upper Faria and about 1% for the lower Faria. Al-Nubani 

(2000) studied the temporal characteristics of the rainfall data of Nablus 

meteorological station. By correlating the occurrences of runoff in Rujeeb 

watershed east of Nablus to the total rainfall values, he concluded that 

runoff occurs when total rainfall exceeds 48 mm distributed over less that 

15 hours duration. As a result of Al-Nubani the runoff is 13.5% of rainfall. 

Barakat (2000) studied the rainfall runoff process of the upper Soreq 

catchment in Jerusalem district and developed the unit hydrograph related 



 27

to four recorded events. Shaheen (2002) has studied the storm water 

drainage in arid and semiarid regions. He evaluated several rainfall-runoff 

processes of Soreq watershed. He has also evaluated the application of 

KW-GIUH model on semiarid watershed. Shadeed and Wahsh (2002) 

studied the runoff generation in the upper part of the Faria catchment using 

synthetic models, KW-GIUH model was also used in their study. The 

annual rainfall recorded at Nablus station for the period 1946-2002 was 

analyzed including frequency and trend analysis. Intensity-duration-

frequency relationships were constructed. Takruri (2003) studied rainfall 

data in Faria catchment and developed approximate IDF curves for Beit 

Dajan station. She developed the unit hydrograph for the Faria catchment 

using traditional methods.  

From the above it is clear that the ratio of rainfall to runoff in West Bank 

catchments has a wide range indicating that individual events of different 

characteristics dominate the rainfall-runoff process. Therefore there is a 

need for further investigations including detailed and accurate data 

acquisition of single events and proper modeling in the West Bank 

catchments. However, the outcomes of the previous studies indicate that 

the Faria catchment has not been modeled using appropriate rainfall-runoff 

models. Therefore the obtained results are weak and doubtful. This 

motivates the study of surface runoff in Faria catchment. This study is an 

attempt to hydrologically investigate and analyze the Faria catchment as 

one of the most important catchments of the West Bank, since the 

catchment has not been modeled using appropriate rainfall runoff models 

so far. 

 



 28
 

 

 

 

 

 

 

 

CHAPTER THREE 

DESCRIPTION OF THE STUDY AREA 
 

 

 

 

 

 

 

 



 29

3.1 Location and Topography  

The area under consideration is the Faria catchment which is located in the 

northeastern part of the West Bank and extends from the ridges of Nablus 

Mountains down the eastern slopes to the Jordan River and the Dead Sea as 

shown in Figure 5.  Faria catchment overlies three districts of the West 

Bank. Those are:  Nablus, Tubas and Jericho district and has a catchment 

area of about 334 km2  which accounts for about 6% of the total area of the 

West Bank (5650 km2) (see Figure 5). The Faria catchment lies within the 

Eastern Aquifer Basin (EAB), which is one of the three major groundwater 

aquifers forming the West Bank groundwater resources.  

The Faria catchment borders are: North Jordan and Fassayel-Auja drainage 

basins from the north and south respectively, Alexander, Yarkon and Al-

Khidera drainage basins from the west and Jordan River from the east. The 

western boundary of the study area lies at the main catchment between the 

Mediterranean Sea and the Jordan River.  

The Faria wadi extends from the upper part of the catchment to the Jordan 

River.  Al-Faria and Al-Badan wadis are the two main streams contributing 

to the Faria catchment. These wadis meet at Al-Malaqi Bridge located 25 

km east of Nablus city. The Faria wadi is the major water supply system in 

the catchment.  Springs are located around the stream and discharge water 

to the stream, through which water is conveyed to irrigation ditches and 

pipelines that distribute irrigation water to the farms along both sides of the 

stream.   

 



 30

West Bank Districts
Salfit
Jenin
Tubas
Nablus
Jericho
Hebron
Tulkarm
Qalqiliya
Jerusalem
Bethlehem
Ramallah and Al-Bireh

Dead Sea
Faria Catchment 
West Bank Boundary

N

Prepared by
Eng. Sameer Shadeed

0 40 Kilometers

$T
Nablus

#

Jordan River

 

Figure 5: Location of the Faria Catchment within the West Bank 

Irrigation wells are available in the Faria catchment to supply additional 

water. Within the Faria catchment there exist 13 fresh water springs and 70 

groundwater wells as presented in Figure 6. The fertile alluvial soils, the 

availability of water through a number of springs and the meteorological 

conditions of the catchment made the catchment one of the most important 

irrigated agricultural areas in the West Bank. 



 31

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$Z$Z

$Z
$Z$Z$Z$Z$Z

$Z
$Z

$Z

$Z$Z

N

Layout preparer
Eng. Sameer Shadeed

0 3 6 9 Kilometers

#Y Wells
$Z Springs

Catchment Boundary

 

Figure 6: Springs and Wells within the Faria Catchment 

Topography is a unique factor in the Faria catchment which starts at an 

elevation of about 900 meters above mean sea level in Nablus Mountains 

and descends drastically to about 350 meters below mean sea level at the 

point where the Faria wadi meets the Jordan River.  This means that 

topographic relief changes significantly throughout the catchment. In less 

than 30 km there is a 1.25 km change in elevation. Such an elevation 

decline in a relatively short distance has considerable effects on the 



 32

prevailing meteorological conditions in the area as a whole and, in fact, 

adds to its importance and uniqueness.   

Topographic map of the Faria catchment (Figure 7), uploaded into the GIS 

ArcView system and used in the delineation of flow paths and divides as 

discussed in section 5.6 of this study.  

Faria catchment includes about twenty communities within its borders.  

Most of these communities are rural communities except the eastern part of 

the city of Nablus, the refugee camps and parts of the town of Tubas and 

other villages in the upper part of the catchment. 

N

Layou t p re pa re r
Eng . S am e er Shadeed

Ca tchm ent B oundary

To po graph ic  M ap  o f 
the  Faria  C atch m ent

0 3 6 Kilom ete rs

 

Figure 7: Topographic Map of the Faria Catchment 



 33

3.2 Climate  

In the West Bank, climatic stations are mainly concentrated in the principal 

towns and villages. Since the Faria catchment does not contain significantly 

large built up areas, therefore only two climatic stations are located within 

the Faria catchment. One of the stations is located in Nablus (570 m 

elevation) and the other is located in Al-Jiftlik (-237 m elevation).  

Climatic data for these stations were obtained from the Palestine Climate 

Data Handbook published by the Meteorological Office of the Ministry of 

Transport (MOT) (1998).  Climatic data included average monthly values 

for maximum and minimum temperature, mean wind speed, mean sunshine 

duration, mean relative humidity and pan evaporation. The average values 

for the climatic conditions prevailing in the catchment area are presented in 

Appendix A1. The information has been spatially delineated using the GIS 

ArcView 3.2 software based on data input of temperature and 

evapotranspiration. 

3.2.1 Wind 

The main wind direction is from west, southwest and northwest. Variation 

during winter is associated with the pattern of depressions passing from 

west to east over the Mediterranean (Ghanem, 1999).  The prevailing winds 

in the area are the southwest and northwest winds with an annual average 

wind speed of 237 km per day in Nablus at a height of 10 meters from 

ground surface.  When this value is adjusted for 2 meters height (the 2 

meters height value is used in most of the potential evapotranspiration 

estimates), average wind velocity drops to 185 km per day. During 

summer, wind moves with relatively cooler air from the Mediterranean 

towards the north, with an average wind speed of 288 km per day in June in 



 34

Nablus at a height of 10 meters. At night the land areas become cooler, 

causing diurnal fluctuations in wind speed, due to the reduction of the 

pressure gradient.  In winter, the wind moves from west to east over the 

Mediterranean, bringing westerly rain bearing winds of average wind speed 

209 km per day in January.  The Khamaseen, desert storm, may occur 

during the period from April to June.  During the Khamaseen, the 

temperature increases, the humidity decreases and the atmosphere becomes 

hazy with dust of desert origin. Wind velocities decrease with elevation, 

thus wind velocities in Al-Jiftlik in the lower part of the catchment are 

significantly lower than those in Nablus located in the upper part of the 

catchment.  Existing wind data showed that measurements of wind 

velocities were recorded at a height of 10 meters in Nablus and at a height 

of 2 meters in Al-Jiftlik.  Due to the elevation of Al-Jiftlik which is 237 

meters below sea level and the existing mountains surrounding Al-Jiftlik, 

wind velocities are much lower than those at Nablus.  Annual average wind 

velocity in Al-Jiftlik was estimated at 106 km/day at a height of 2 meters 

which is much less than the 185 Km/day estimated in Nablus at the same 

height from ground surface. 

3.2.2 Temperature 

Faria catchment is characterized by high temperature variations over space 

and over time. Temperatures reduce with increasing elevation in the 

catchment.  The average temperature variation between Nablus and Al-

Jiftlik is about 5 oC.  The mean annual temperature changes from 18 oC in 

the western side of the catchment in Nablus to 24 oC in the eastern side of 

the catchment at Al-Jiftlik. Figure 8 shows the variation in average 

monthly temperatures in Nablus and Al-Faria stations. Spatial 



 35

representation of the mean annual temperature in the catchment is 

presented in Figure 9. 

0

5

10

15

20

25

30

35

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Months

M
ea

n 
T

em
p.

 (o C
)

Nablus Al-Jiftlik

 

Figure 8:  Mean Monthly Temperatures in Nablus and Al-Jiftlik 
19.0

19.5

18.5

23
.0

21
.5

20
.0

21
.0

20
.5 22

.0

22
.5

18.0

23
.5

23.0

N

Prepared by
Eng. Sameer Shadeed

Mean Annual Temperature (Celsius)
Catchment Boundary

0 3 6 9 Kilometers

 

Figure 9: Spatial Distribution of the Mean Annual Temperature in the Faria 
Catchment 



 36

3.2.3 Relative Humidity 

The mean annual relative humidity of Nablus area is 61%. The minimum 

value of relative humidity is 51% which occurs in May during the 

Khamaseen weather, while the maximum relative humidity of 67% is 

usually registered in December, January and February.  Relative humidity 

is in general low in the entire catchment especially in summer months 

because the catchment is located on the eastern side of the West Bank 

Mountains.  The source of humidity in the region is the Mediterranean Sea, 

where the western winds bring humidity to the catchment.  Eastern winds 

coming from the desert are usually dry. 

3.2.4 Rainfall  

The West Bank is considered semiarid and has the Mediterranean type 

climate. Regionally, the winter rainy season is from October to April in the 

catchment. Rainfall events predominantly occur in autumn and winter and 

account for 90% of the total annual precipitation events. Although the 

summer months are dry, some rain events occur occasionally and a high-

pressure area governs the weather over the Mediterranean. The continental 

low-pressure area to the east and south creates a strong pressure gradient 

across the country, which results in eastward moving sea breezes of 

relatively cooler air. In winter, the predominately low-pressure area of the 

Mediterranean centered between two air masses, the north Atlantic high on 

North Africa and the Euro-Asian winter high located over Russia, is the 

primary cause of winter weather in the area. The presence of hills in the 

west of Palestine affects the behavior of the low-pressure area, resulting in 

westernlies, which force moist air upwards, causing precipitation on the hill 

ridges. The steep gradient of Jordan Valley produces a lee effect, which 



 37

greatly reduces the quantity of the rainfall in the Jordan Valley rift area 

(Husary et al., 1995).  The rainfall distribution within the Faria catchment 

ranges from 640 mm at the headwater to 150 mm at the outlet to the Jordan 

River. Figure 10 presents the spatial presentation of the rainfall data within 

the Faria catchment.     

#Y

#Y

#Y

#Y

#Y

#Y

450
500

550

400

30
0

25
0

35
0

20
0

150

600

200

600

350
 Tubas

 Nablus

 Tammun

Al-Faria

 Talluza

Beit Dajan

N

Prepared by
Eng. Sameer Shadeed

Isohyetal Rainfall Map (mm)
#Y Rainfall Stations

Catchment Boundary

0 3 6 9 Kilometers

 

     Figure 10: Rainfall Stations and Rainfall Distribution within the Faria 
Catchment 



 38

3.2.5 Evaporation 

The Mediterranean climate (hot and dry in the summer, mild and wet in the 

winter) has six to seven months of dryness in the year. Winter months 

where moisture is available from rain have low evapotranspiration rates.  

Summer months with high potential evapotranspiration rates have no rain 

and thus actual evapotranspiration is limited by the availability of moisture.   

Evaporation rates in Faria regions are measured from a US Class A pan at 

Nablus station as shown in the table of Appendix A1. From the table it is 

noticed that the average annual evaporation measured at Nablus station is 

about 1682 mm. Evapotranspiration is usually smaller than pan evaporation.  

Evaporation rates should be multiplied by a pan coefficient (less than 1) to 

estimate evapotranspiration rates. A more accurate way to estimate 

evapotranspiration is from climatic data.   

Monthly potential evapotranspiration rates were estimated according to 

Penman-Monteith method as modified by FAO using CROPWAT 4 

Windows version 4.2 model (FAO, 1998). The maximum potential rate of 

Evapotranspiration was estimated at 1540 mm/year at Al-Jiftlik and 1408 

mm/year in Nablus. Although the temperature variability between Nablus 

and Al-Jiftlik might indicate a larger difference in evapotranspiration, this 

difference was reduced as a result of higher wind velocities in dry summer 

months in Nablus.   

In the upper part of the Faria catchment, at Nablus, precipitation exceeds 

potential evapotranspiration in five months of the year (November through 

March).  However, in the lower part of the catchment, at Al-Jiftlik, 

precipitation exceeds potential evapotranspiration in two months of the 

year only (December and January).  Therefore, irrigation is required during 



 39

most months of the year in the lower part of the catchment in comparison 

to the upper part. Figure 11 shows the relation between potential 

evapotranspiration and rainfall for Nablus and Al-Jiftlik stations. The 

spatiality of the potential annual evapotranspiration rates in the Faria 

catchment is presented in Figure 12 as computed using CROPWAT 4 

model. From the figure it is noticed that the spatiality of the potential 

annual evapotranspiration rates is roughly coincide to the spatiality of the 

mean annual temperature (Figure 9). CROPWAT 4 output results for 

Nablus and Al-Faria stations are presented in Appendix A2. 

0

50

100

150

200

250

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Months

V
al

ue
 (m

m
)

ETo-Al-Jiftlik
ETo-Nablus
Rainfall-Al-Jiftlik
Rainfall-Nablus

 

Figure 11:  Monthly Rainfall and Potential Evapotranspiration Rates (ETo) 
in   Nablus and Al-Jiftlik    



 40

1440

1430

145 0

1420

1530

1520

14
90

14
60

14
80

14
70

15
00

15
101410

1530

1460
14

40

N

Prepared By
Eng. Sameer Shadeed

Potential Evapotranspiration Rates (mm/year)
Catchment Boundary

0 3 6 9 Kilometers

 

        Figure 12: Potential Annual Evapotranspiration Rates in the Faria   
Catchment 

3.2.6 Aridity of the Catchment 

As to UNESCO (1984), aridity can be defined in several different ways and 

most simply it is a moisture deficit. The moisture deficit, or an aridity 

index, is determined by the ratio of mean annual precipitation (P) to mean 

annual potential evapotranspiration (PET). The index ranges for defining 

arid and semiarid regions are: arid (0.05 <= P/PET < 0.20), semiarid (0.20 

<= P/PET < 0.50).                     



 41

Monthly potential evapotranspiration rates were estimated according to 

Penman-Monteith method as modified by FAO (1998) using CROPWAT 4 

Windows version 4.2 model. The results of applying CROPWAT 4 model 

are presented in the previous section and Appendix A2. It was estimated 

that the annual potential rate of Evapotranspiration is 1540 mm and 1408 

mm at Al-Jiftlik and Nablus stations respectively.  For these stations, the 

long term average annual rainfall is 198 mm and 642 mm respectively. 

Therefore, the aridity index is 0.13 for Al-Jiftlik and 0.46 for Nablus. This 

means that arid conditions prevail in Al-Jiftlik, whereas semiarid 

conditions prevail in Nablus.  

3.3 Water Resources                

3.3.1 Groundwater Wells 

There are 69 wells in the Faria catchment; of which 61 are agricultural 

wells, 3 are domestic and 5 are Israeli wells. These wells are drilled in four 

sub-aquifers. These sub-aquifers are Eocene, Cenomanian, Neogene and 

Pleistocene sub-aquifers. All these wells are located in the study area 

mainly in the areas of Ras Al-Faria, Al-Aqrabanieh, Al-Nasaria, Froush 

Beit Dajan and Jiftlik along the flexure of wadi Faria.  

Based on the available data (Table 1), the total utilization of the Palestinian 

wells ranges from 4.4 to 11.5 MCM/year.  Data on the pumping rates from 

the Israeli wells is available for four wells for only four years from 1997-

2000. The average total abstraction from these four wells was found to be 

about 8 MCM/year. Average well abstraction from Israeli wells is about 2 

MCM/year.  Thus, considering the fifth Israeli well without data available, 

the total abstraction from the five Israeli wells in the Faria catchment is 

estimated at 10 MCM/year, which is more than the 61 Palestinian 



 42

agricultural wells combined. Table 1 presents the total annual abstraction 

from wells in the Faria catchment from 1984 -2003.   

Wells basic data includes coordinates, well name, location, district, usage, 

basin, and well depth were obtained from the Palestinian Water Authority 

(PWA). Appendix A3 gives a summary of these basic data for all wells 

within the Faria catchment.  

Table 1:  Abstraction from Wells in the Faria Catchment 

Year 
Abstraction MCM 

Agricultural Domestic Total Israeli  
1984 4.7 * 4.7 * 
1985 5.7 * 5.7 * 
1986 5.7 2.2 7.9 * 
1987 7.0 2.3 9.2 * 
1988 6.8 2.9 9.7 * 
1989 6.6 3.3 9.9 * 
1990 6.7 3.3 10.0 * 
1991 6.3 3.0 9.3 * 
1992 4.1 * 4.1 * 
1993 5.0 * 5.0 * 
1994 5.9 3.0 8.9 * 
1995 6.4 3.1 9.5 * 
1996 6.6 2.6 9.2 * 
1997 5.8 2.8 8.6 6.7 
1998 7.6 2.5 10.2 8.3 
1999 8.2 3.3 11.5 8.4 
2000 7.4 3.9 11.3 8.2 
2001 6.1 2.5 8.6 * 
2002 6.6 2.7 9.3 * 
2003 5.1 2.8 7.9 * 

                * Missing Data 

3.3.2 Springs 

Within the Faria catchment there exists 13 fresh water springs that are 

divided into four groups. These groups are Faria, Badan, Miska and Nablus. 



 43

The basic data available on these springs include group name, spring name, 

coordinates, average annual discharge, minimum annual discharge and 

maximum annual discharge. Table 2 presents a summary of these basic 

data. Monthly spring discharge measurements for more than 30 years are 

available for these springs as presented in Appendix A4. Discharge data of 

the springs show high spring discharge variability.  Annual discharge from 

these springs varies from 3.8 to 38.3 MCM/year with an average amount of 

14.4 MCM/year. 

The location of the springs and wells within the Faria catchment are shown 

in Figure 6.   

Table 2: Spring Groups and Spring Information within Faria catchment 

Group Spring 
Name 

Coordinates Ave. 
Annual 

Discharge
MCM 

Min.  
Annual 

Discharge 
MCM 

Max. 
Annual 

Discharge
MCM 

X 
(km) 

Y 
(km) 

Elevation 
(m) 

Faria El Faria 
El Duleb 

182.40 
182.00

188.40 
187.95

160 
155 

5.23 
1.27 

1.71 
0.06 

10.53 
8.60 

Badan Asubian 
Beida & 
Hammad 
Sidreh 
Tabban 
Qudeira 
Jiser 

180.52 
180.12 

 
179.95 
180.42 
180.13 
180.37

184.56 
185.32 

 
185.58 
184.82 
185.28 
185.10

130 
215 

 
240 
160 
215 
170 

0.19 
0.81 

 
1.34 
1.38 
1.33 
0.14 

0.14 
0.10 

 
0.00 
0.98 
0.00 
0.03 

0.23 
1.75 

 
8.12 
1.63 
2.33 
0.23 

Miska Miska 
Shibli 
Abu Saleh 

187.03 
189.90 
186.26

182.90 
181.28 
183.57

-38 
-80 
-19 

1.32 
0.95 
0.19 

0.02 
0.71 
0.00 

2.21 
1.15 
0.50 

Nablus Balata 
Dafna 

176.20 
176.20

179.77 
179.90

510 
560

0.17 
0.13

0.05 
0.02 

0.55 
0.49

Total 14.44 3.81 38.31 

3.3.3 Analysis of Springs Discharge 

There are sex springs within Al-Badan sub-catchment, in addition to other 

two springs that are entirely utilized by the city of Nablus, whereas Al 



 44

Faria sub-catchment contained two springs in its area. Preliminary analysis 

on the available monthly discharge measurements including minimum, 

maximum and average discharge was performed. From the analysis it is 

concluded that the average annual volume of Al-Badan springs for the 30 

years monthly data is about 4 MCM, while the minimum and maximum 

volumes are about 1.1 MCM and 16 MCM respectively. On the other hand, 

the average annual volume of Al-Faria springs is about 7 MCM, while the 

minimum and maximum volumes are 1.4 MCM and 24 MCM. Figures 13 

and 14 illustrate the sum of the minimum, maximum and average values of 

Al-Badan and Al-Faria springs respectively. From figures it is clear that 

high variability in the spring discharge exists. Results also suggest that the 

data do not follow a normal distribution and the average value is much 

closer to the minimum rather than the maximum. 

0

200

400

600

800

1000

O
ct

N
ov D
ec Ja
n

Fe
b

M
ar

A
pr

M
ay Ju
n Ju
l

A
ug Se

p

Time (Months)

D
isc

ha
rg

e 
(L

/S
)

Maximum
Average
Minimum

 

Figure 13: Average, Maximum and Minimum Monthly Discharge of Total 
Springs within Al-Badan Sub-catchment 



 45

0

200

400

600

800

1000

1200

1400

O
ct

N
ov D
ec Ja
n

Fe
b

M
ar

A
pr

M
ay Ju
n Ju
l

A
ug Se

p

Time (Months)

D
isc

ha
rg

e 
(L

/S
)

Maximum
Average
Minimum

 

Figure 14: Average, Maximum and Minimum Monthly Discharge of Total     
Springs within Al-Faria Sub-catchment 

3.4 Surface Water 

3.4.1 Flow Measurements 

No detailed runoff data were available for Faria catchment. The only 

hydraulic structure which was constructed in the early 70’s for measuring 

surface runoff in the Faria catchment is located next to Ein Shibli in the 

lower central part of the catchment.  This hydraulic structure is a wide 

crested weir which is used as a diversion structure to Al-Faria Irrigation 

Project. The structure has an upstream stage gage which could be 

monitored to estimate runoff flows.  However, the structure does not have 

an automatic recorder to register water stage continuously. Therefore, only 

few sporadic measurements are available for runoff rates from structure. 

These measurements are not sufficient to estimate the volume of annual 

runoff through the structure. In August 2003, An-Najah National 

University in coordination with GLOWA JR project established two 



 46

Venturi Flumes at Jiser Al-Malaqi to measure runoff rates from both Al-

Faria and Al-Badan wadis. GLOWA JR project is an interdisciplinary 

project that studies the "Impacts of Global Changes on Water Resources in 

Wadis Contributing to the Lower Jordan Basin". GLOWA project is a 

German funded project by the German Ministry of Education and Research 

and is managed by German, Jordanian and Palestinian institutes.  Water 

and Environmental Studies Institute (WESI) of An-Najah University is a 

counterpartner for Package 2 of GLOWA project researching the water 

resources in Jordan River.  

The Flume of Al-Badan wadi was designed to measure 25 m3/s and 0.23 

m3/s of maximum and minimum flows respectively. Maximum and 

minimum flows that can be measured by Al-Faria wadi Flume are 15 m3/s 

and 0.19 m3/s respectively. In case of low flows the Parshall Flumes are not 

significantly accurate.  

There are two reading gauges at each Flume to measure the flow depths at 

the critical sections, which are converted into flow rates using the designed 

empirical formulas. The constructed Flumes are still working and the 

records are available for the two years (2003-2005) since their construction. 

The Flumes did not have automatic recorders during the first year. The 

automatic recorders were constructed later and are available since the 

second year. Photos of the two Flumes are presented in Appendix D1. The 

recorded runoff data are tabulated as in Appendix A5. 

Surface runoff of the Faria catchment is considered high compared to other 

catchments in the West Bank. Within the catchment the runoff decreases 

from west to east as the slope becomes relatively gentile eastwards down 

the main stream where rainfall rates reduce also. 



 47

The city of Nablus discharges untreated industrial and domestic wastewater 

effluents to Al-Badan wadi while Al-Faria camp discharges untreated 

domestic wastewater to Al-Faria wadi. Therefore, the stream flow of the 

Faria catchment is a mix of: 

1. Runoff generated from winter storms.  This includes urban runoff from 

the eastern side of the city of Nablus and other built up areas in the 

catchment.    

2. Untreated wastewater of the eastern part of Nablus and of Al-Faria 

camp.  

3. Fresh water from springs which provides the baseflow for the wadi 

preventing it from drying up during hot summers. 

Farmers use part of the flowing water for irrigation while the rest discharge 

into the lower Jordan valley or lost through evaporation. 

3.4.2 Quality Considerations 

No considerable measurements for surface water quality are available for 

the Faria streams. All the quality measurements conducted in the area are 

performed for the springs and wells. Since the source of water for the Faria 

wadi are mostly from springs, then the water quality is dependent on the 

water quality of these springs. Measurements for spring water quality 

showed that these springs are generally of good water quality especially 

chemical quality. The chemical quality data of water from all the springs of 

the Faria catchment show low concentrations of salts. Therefore, the 

chemical quality of the Faria streams is good and water is suitable for 

irrigation (EQA, 2004). A major source of pollution comes from the Nablus 



 48

municipality. Nablus dumps untreated effluent from its sewage network 

directly into the Al-Badan wadi, a tributary of the mean wadi of the Faria 

catchment. The Faria refugee camp disposes of some of its solid waste in 

pits and the rest by trucking it to a site 1.5 km from the camp to be burned. 

The effluent is drained into the wadi a few hundred meters away from the 

camp and wastewater from homes is often dumped directly into the streams 

or into open ditches.  

Another source of water contamination is the livestock that use wadis and 

springs as a drinking water source, and pollute the water with fecal matter. 

Moreover, local herders bring their sheep and goats to the streams to wash 

them and to shear the sheep, thereby polluting the surface waters. Finally, 

an extremely significant pollution factor is the waste disposal and use of 

agricultural chemicals by the Israeli colonies. However, no information or 

data are currently available to be considered in this study. 

However, due to the discharge of untreated wastewater into the wadi its 

quality has deteriorated significantly. An eye inspection of the wadi and the 

wastewater entering into it gives an indication of the high deterioration in 

its quality. Historical data and measurements are not available to quantify 

such deterioration. Accordingly, samples from the outlet streams (Flumes) 

of the upper two sub-catchments were collected and analyzed in the context 

of GLOWA JR project. Samples were taken during different times to study 

the seasonal variation of the surface water quality. Table 3 shows a 

summary of the results for the samples collected during the years 2004 and 

2005.  

 
 



 49
Table 3: Surface Water Quality Parameters for Badan and Faria Streams 

Results of the wadi water quality analysis show that runoff during winter as 

well as peak discharge periods improve the quality of the water in the 

stream. This is mainly due to the mixing factor. In addition, the 

microbiological analysis shows that contamination of the water is caused 

by the untreated wastewater that is flowing from Nablus city and Faria 

Village and Camp. In general, it is concluded that effluent of untreated 

wastewater is the main threat to surface water quality of the catchment. 

This wastewater disposal is causing a major threat not only to the quality of 

surface water but also to land and soil resources within the catchment.  

3.5 Soil 

The major soil types found in the Faria catchment are as follows (Orthor et 

al., 2001):  

1. Grumusols 

2. Loessial Seozems 

3. Calcareous Serozems  

Date 
Parameters 

EC 
μs/cm

PO4 
Ppm 

NO3 
ppm 

COD
Ppm 

Turbidity
Unit 

Total.C
/100ml 

Fecal.C
/100ml 

May, 2004 Badan 844 0.30 39.1 32 1.1 1200 700 
Faria 571 0.00 15.9 0 5.7 900 600 

Aug, 2004 Badan 790 0.40 16.3 120 3.1 3500 2500 
Faria 494 0.00 13.6 0.0 3.5 2600 1500 

Dec, 2004 Badan 806 0.03 19.8 46.5 5.5 3000 2100 
Faria 610 6.00 17.1 0.0 4.1 500 300 

Jan, 2005 Badan 732 3.00 16.7 0.0 3.5 2300 1900 
Faria 630 0.27 14.0 0.0 18.7 1400 1000 

Feb, 2005 Badan 616 0.30 19.8 0.0 3.1 10000 8000 
Faria 636 0.22 19.4 0.0 10.5 1000 800 

Mar, 2005 Badan 695 0.20 22.4 0.0 1.2 9000 7000 
Faria 697 0.01 25.0 0.0 5.4 8000 6500 



 50

4. Terra Rossas Brown Rendzinas  

Characteristics of these types are adopted from the document entitled, 

Environmental Profile for The West Bank, Volume 5, Nablus Profile, ARIJ, 

1996. Table 4 shows the characteristics and the areas of the major soil 

types in Faria catchment. These soil types are spatially distributed over the 

catchment as illustrated in Figure 15.  

From the table and the figure it is noticed that Terra Rossas Brown 

Rendzinas soil and Loessial Seozems cover most of the catchment. These 

two types; taking up not more less than 70% of the total area. In addition, 

Loessial Seozems is concentrated in the middle part of the catchment, 

where Grumusols is distributed over the catchment.  

Table 4: Major Soil Types and Characteristics in Faria Catchment 
Soil Type General Characteristics Area (%)

Grumusols Parent materials are fine textural 
alluvial or Aeolian sediments 13 

Loessial Seozems Parent rocks are conglomerate and chalk 25

Calcareous 
Serozems 

The soil is highly calcareous with 
grayish-brown color. The texture is 
medium to fine. Parent rocks are 
limestone, chalk and marl

19 

Terra Rossas 
Brown Rendzinas 

The parent materials for this type of soil 
are originated from mainly dolomite and 
hard limestone.  Soil depth varies from 
shallow to deep (0.5 to 2 m)

44 

Total 100 

 



 51

N

Layout preparer
Eng. Sameer Shadeed

Soil Map
Grumusols
Loessial Seozems
Calcareous Serozems
Terra Rossas Brown Rendzinas

Catchment Boundary

0 3 6 9 Kilometers

 

Figure 15: Soil Types of the Faria Catchment 

3.6 Geology  

Faria catchment is a structurally complex system with Al-Faria Anticline 

that trends northeast to southwest acting as the primary controlling feature. 

Additionally, a series of smaller faults and joints perpendicular to this 

anticline have a significant effect on the surface water drainage area. The 

geological structure of the Faria catchment is composed form limestone, 

dolomite and marl. The rocks vary in its thickness, some of them are more 

than two meters and some of them are intermediate thickness of about 40-

100cm. The rock formations were deposited at the second time Mezosy and 



 52

mostly refer to the geological Era of Mezosy. The rocks have much 

intensity of fissures, because of the geological history that the area had 

faced. The faults and fissures reflect the geological conditions of the area 

passed and affected the hydrology by a huge infiltration quantity and the 

appearance of many springs as Badan, Faria, and Miska (Ghanem, 1999).   

Figure 16 illustrates the geology map of the Faria catchment. Figures 16 

and 15 were taken and modified from the data base of the study entitled, A 

Harmonized Water Data Base for the Lower Jordan Valley (Orthor et al., 

2001). 

N

Layout preparer
Eng. Sameer Shadeed

Geology Map
Dead Sea
Landslides, Fans
Basalt (Lower Cretaceous)
Chalk, Limestone, Chert (Ecocene)
Calcar. Sandstones, Dolomites, Limestones, Marls
Limestone, Dolomite,Marl (Cenomanian, Turonian)
Marls, Clays, Gypsum, Sulfur, Clastic Intercalations
Marl, Limestone, Sandstone,Conglomerate (Late Ecocene-Miocene)

Catchment Boundary

0 3 6 9 Kilometers

 

Figure 16: Geology Map of the Faria Catchment 



 53

3.7 Land Use 

The catchment area which has an area of about 334 km2 includes Al-Faria 

Valley which is one of the most important agricultural areas in the West 

Bank.  A new land use map of the Faria catchment has been developed in 

the context of GLOWA JR project. The land use images, which are 

available by Environmental Quality Authority, PHG and Birzeit University, 

were used in addition to the topographic map and airphotos to shape the 

new land use map. Part of the airphotos that were used is illustrated in 

Figure 17.  

 
Figure 17: Part of the airphotos of Faria Catchment 

Ground truthing has been conducted to investigate the actual ground cover. 

For that purpose, the catchment was visited several times and several 



 54

photos were snapped that cover the natures of the catchment as presented in 

Appendix D2.  

The land use map of the Faria catchment was classified into four classes. 

These classes are artificial surfaces, agricultural areas, forests and semi 

natural areas and water bodies. Table 5 presents these classes, the area of 

each class, its categories and its percent from the whole catchment. The 

following is a description of these land use classes.  

1. Artificial Surfaces 

The artificial surfaces in the catchment are composed of refugee camps, 

urban fabrics, Israeli colonies and military camps. The military camps and 

colonies are used by the Israeli occupation authorities and settlers. The total 

area of the artificial surfaces is 18047 dunum presenting about 5.5 % of the 

total area of the catchment. The actual figure is higher due to the fact that 

most of the roads and associated land were kept out of the scope of the 

study because of the unit limitations. This percentage is less than that of 

artificial surfaces in the West Bank (8%) which indicates that the area is 

not densely populated due to the harsh topography of the nonagricultural 

area in addition to the political restrictions (EQA, 2004).   

2. Agricultural Areas 

The agricultural land in the catchment is composed of an arable land and 

heterogeneous agricultural areas. Arable land involves non-irrigated arable 

land, drip-irrigated arable land, olive groves, palm groves and citrus 

plantations. The heterogeneous agricultural areas involve irrigated and non-

irrigated complex cultivated pattern and land principally occupied by 



 55

agriculture with significant areas of natural vegetation. The area of the 

agricultural part of Faria catchment is 115447 dunum which represents 

about 34.4%. This percentage is lower than that of the West Bank of about 

39% (EQA, 2004).  

3. Forests and Semi Natural Bodies 

This group of land use cover is composed of coniferous forests, natural 

grassland, bare rocks, sparsely vegetated area and halophytes. The forests 

and semi natural bodies in the Faria catchment occupy an area of about 

201087 dunum representing 60% from the total area. It is worth mentioning 

that most of the Israeli colonies were built at the expense of forests and 

semi natural areas under the cover of many military laws that consider the 

forests and vast natural areas as state owned land. 

4. Water Bodies 

No perennial rivers are available in West Bank other than the Jordan River 

that represents the eastern border of West Bank and Faria wadi. Most of the 

water courses are seasonal and could be added to the land use maps as 

linear features of a width less than the threshold of the smallest unit 

mapped.  

There are no water bodies controlled by the Palestinians that are large 

enough to be drawn on the maps of this study. On the other hand there are 

few water bodies on the Jordan Valley and Faria stream near the Jordan 

River that are controlled by the Israeli occupation and are utilized for 

irrigation and fishing (EQA, 2004). One of the artificial water surfaces 



 56

constructed by the Israeli Authorities is the Tirza reservoir, which has an 

area of about 250 dunum.  

Table 5 displays the total land use cover of the Faria catchment.  From the 

table, it is clear that the nonagricultural area is dominant and above the 

average of the nonagricultural area in the West Bank. The modified land 

use map is shown in Figure 18. 

Table 5:  Total Land use Cover of the Faria Catchment 

Land use Cover Area 
(Dunum) (%) 

Artificial Surfaces 
Urban fabrics 13300 4 
Refugee camps 972 0.3 
Israeli colonies 3107 0.9 
Military camps 668 0.2 
Sub Total 18047 5.5 
Agricultural Areas 
Olive groves 26506 7.9 
Palm groves 394 0.1 
Citrus plantations 4650 1.4 
Non-irrigated arable land 37289 11.1 
Drip-irrigated arable land 6978 2.1 
Land principally occupied by agriculture 20458 6.1 
Irrigated and non-irrigated complex cultivated patterns 19172 5.7 
Sub Total 115447 34.4 
Forests and Semi Natural Vegetation 
Bare rocks 12523 3.7 
Halophytes 8757 2.6 
Natural grassland 111205 33.2 
Coniferous forests 4716 1.4 
Sparsely vegetated area 63886 19.1 
Sub Total 201087 60 
Water bodies/ Artificial surfaces 250 0.1 
Total 334831 
 



 57

N

Modified by
Eng. Sameer Shadeed

Land Use Map
Bare rocks
Halophytes
Palm groves
Olive groves
Urban fabrics
Military camps
Israeli colonies
Refugee camps
Citrus plantation
Natural grassland
Coniferous forests
Sparsely vegetated area
Non-irrigated arable land
Drip-irrigated arable land
Water bodies/Artificial surfaces
Land principally occupied by agriculture
Irrigated and non-irrigated complex cultivated patterns

Catchment Boundary

0 3 Kilometers

 

Figure 18: The New Land use Map of the Faria Catchment 



 58
 

 

 

 

 

 

CHAPTER FOUR 

RAINFALL ANALYSIS 



 59

4.1 Rainfall Stations 

The Faria catchment is gauged by six rainfall stations that record rainfall. 

These stations are: Nablus, Taluza, Tammon, Tubas, Beit Dajan and Al-

Faria stations. Before 1994, these stations were controlled by the Israeli 

Authorities. After the establishment of the Palestinian Authority, the 

stations except one became under the control of the Palestinians. The 

Nablus station is a regular weather station in which most climatic data are 

measured. Monthly and annual precipitation for this station is available for 

more than 55 years.   

Al-Faria station is located in Al-Jiftlik village in the lower part of the 

catchment and is still under Israeli control. This station was established by 

the Jordanian government as an agricultural experimental station similar to 

the Deir Alla station on the eastern side of the Jordan River. The station 

was taken over by the Israeli Occupation Authorities in 1967. The Israeli 

Authorities neglected the station and therefore its role in serving the 

Palestinian farmers became insignificant. In 1994, when the Palestinian 

Authority was established, the Israeli Authorities refused to hand it over to 

the Palestinians. Therefore, data available from this station is limited to 

only few years.   

The other four rainfall stations are located in the schools of Taluza, Tubas, 

Tammon and Beit Dajan (see Figure 10). These stations are simple rain 

gages which measure daily precipitation. Data from these stations cover 

also monthly and annual precipitation for 30 to 40 years. No rainfall 

intensity charts are available in the catchment except from Nablus station 

where few years are covered and are available. This is due to lack of 

continuous measuring instruments for precip