A review of hydrologic models for flash floodwarning system in southwest Saudi Arabia.

Item Type Thesis-Reproduction (electronic); text

Authors Al-Haratani, Eisa Ramadan, 1958-

Publisher The University of Arizona.

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A REVIEW OF HYDROLOGIC MODELS FOR FLASH FLOODWARNING SYSTEM IN SOUTHWEST SAUDI ARABIA

by

Eisa R. Al-Haratani

A Professional Paper Submitted to the Faculty of the

SCHOOL OF RENEWABLE NATURAL RESOURCES

in Partial Fulfillment of the Requirements

For the Degree of

MASTER OF SCIENCE

WITH A MAJOR IN WATERSHED MANAGEMENT

in the Graduate College

THE UNIVERSITY OF ARIZONA

1988

This professional paper has been approved or the dateshown

/)(///7..).4i

Date

Pe r FfolliottProfessor of Watershed Management

STATEMENT BY AUTHOR

This professional paper has been submitted inpartial fulfillment of requirements for an advanceddegree at The University of Arizona and is deposited inthe University Library to be made available toborrowers under rules of the Library.

Brief quotations from this paper are allowablewithout special permission, provided that accurateacknowledgement of source is made. Requests forpermission for extended quotation from or reproductionof the manuscript in whole or in part may be granted bythe head of the major department or the Dean of theGraduate College when in his or her judgment theproposed use of the material is in the interests ofscholarship. In all other instances, however,permission must be obtained from the author.

ThSigned:

APPROVAL BY GRADUATE COMMITTEE

illip Guertin ateAsst. Prof. in Watershed Management

DEDICATION

Dedicated to my father Ramadan, mother, Naima, my

wife Hanan, and my children, Ramadan and Reham. To them

I reserve my deepest gratitude. This paper must seem a

modest Consolation for all the inconvenience and

hardships they all have gone through to make this

possible.

ACKNOWLEDGEMENTS

It gives me great pleasure to acknowledge those

who have assisted me in carrying out this work,

especially the constructive criticisms regarding the

content and organization of this paper.

First and foremost, I would like to express my

sincerest gratitude to my major professor, Dr. Martin

Fogel, Who was ever available in my time of academic

and intellectual needs, who persevered to guide me with

this modest accomplishment. My association with him

has been a most stimulating experience in life and has

made my stay here with the University of Arizona an

enjoyable one.

I would like to thank Dr. Peter Ffolliott for his

academic support, likewise to Dr. Phil Guertin for his

assistance.

Special thanks goes to Dr. Walid Abed Rabboh for

his assistance and advise.

am also thankful to all my colleagues with the

School of Renewable Natural Resources, who helped me in

the preparation of this professional paper; Khalid M.

Arkanji, Raja Zarif, Mary Ann Pollisco-Botengan and

Ahmed Bakhashwain.

iv

Finally, I would like to express my appreciation

for the government of Saudi Arabia, particularly the

Meteorological and Environmental Protection

Administration, especially Dr. Abdulbar A. Al-Gain and

Dr. Nizar Tawfiq for their support.

TABLE OF CONTENTS

LIST OF FIGURES

LIST OF TABLES

ABSTRACT

INTRODUCTION

vii

viii

ix

1

The Asir Highlands 2

The Runoff Process 10

WATERSHED MODELS: A BACKGROUND 14

Soil Conservation Service Model 20

SCS TR-20 Watershed Model 30

Stanford Watershed Model 34

USDAHL-74 Model 37

ANSWERS Model 40

HEC-1 Model 44

THE AL-BAHA EXPERIMENTAL WATERSHEDS 46

Description of the Experimental Sites • • • 46

Experimental Data 50

DISCUSSION AND CONCLUSIONS 53

Conclusions 56

REFERENCES 58

vi

LIST OP FIGURES

1. A Map of Southwestern Saudi Arabia 4

2. Isohyetal Map of the Study Area 5

3. Relationship Between Rainfall and Runoff . . . 25

4. Effect of Antecedent Moisture Condition

on Curve Number as Referenced on AMC II . . . . 29

5. General Structure of SCS TR-20 Watershed Model 31

6. General Form of Stanford Watershed Model IV,

Showing Principal Storages and Flows 35

7. General Structure of USDAHL-74 Watershed Model 39

8. A Map of the Two Study Sites:

USGS and HEMA 48

vii

LIST OF TABLES

1. Antecedent Moisture Class Limits 28

2. Observed Versus Calculated Rainfall-Runoff

Data From Two Watersheds 51

viii

ABSTRACT

Various models have been applied in the analysis

of hydrologic conditions in different watershed areas.

The whole spectrum of models available as tools for

natural resource managers is because the use of

modeling techniques are limited for specific areas

and/or purposes. Constraints and limitations have to

be realized in order to properly select a model that

answers the needs of a certain locality, for a stated

goal.

It is the purpose of this paper to review existing

hydrologic models, and in the process, select the most

promising for application in the southwestern part of

Saudi Arabia for the purpose of designing flood control

and warning systems. The six models under

investigation are the SCS Method, SCS TR-20, Stanford,

USDA HL-74, HEC-1 and ANSWERS.

Based on the scope and limitations of each model,

as well as certain restrictions found within the area

of study, it became evident that the SCS models are the

most appropriate. This became more apparent having

considered the type of data input the models require

that can be provided for in the study area, as well as

the simplicity of the models and scale of application.

ix

1

INTRODUCTION

Different modeling techniques have been developed

and applied to estimate runoff from rainfall. Each

model was developed to fit and serve certain cases and

locations. Due to the lack of resources, poor research

activities and infrastructures in developing countries,

little work has been done in this field. Whenever

models are needed to be used in these countries, models

are imported from developed countries. The only

criterion often considered in selecting a model is the

researcher's familiarity with such a model.

The appropriateness and suitability of six models

will be evaluated, and their applicability for the

southwestern region of Saudi Arabia will be examined

and analyzed. In so doing, a description of each of

the six models and the study areas will be included in

the study. Different criteria will be applied in

evaluating the six models, namely required model

inputs, simplicity and the scale of model application.

Finally, a model or models will be selected and

recommended for adoption in southwestern Saudi Arabia

for purposes of designing flash flood warning systems

and flood control structures.

2

The Asir Highlands

Government records reveal that the total area of

Saudi Arabia is about 2.2 million square miles.

Approximately 80 percent of the Arabian Penninsula

falls under Saudi Arabia.

The population of the Kingdom is distributed along

the eastern and western coasts especially in towns and

interior oases. The total population of the country is

around eight million, of which about 70 percent reside

in cities and towns.

The climate of Saudi Arabia is generally hot with

winds blowing from the east towards the Arabian Gulf.

Humidity is low, with the exception of the coastal

zones, where it reaches over 90 percent. During the

summer months, the average annual temperature is 35°C,

while in winter it is 25°C. There is a wide range in

maximum and minimum temperatures. Rainfall is scarce

in the northern two-thirds of Saudi Arabia. It is

unpredictable with great annual variations. Long

periods of drought are common. However, where there is

rainfall, it is stormy with occasional flash floods in

low land areas, especially in the southwestern part.

This part of Saudi Arabia experiences seasonal rainfall

that can be as high as 600 millimeters.

3

This study will focus on the southwestern part of

Saudi Arabia (Fig. 1), which has two distinct areas;

the western and eastern slopes, separated by the

escarpment ridge of the Asir mountains. The western

zone encompasses a coastal strip between the Red Sea

and the mountain range. The topography of the upstream

sections of the western slope wadis (valleys), are very

steep particularly near the escarpment. Consequently,

runoff is carried by incised wadis of limited capacity.

The surface material on the mountains is generally

impermeable, thus groundwater resources at the upstream

sections are negligible. As the drainage system enters

the foothills, the topography flattens, and the

alluvial wadi (valley) beds widen. The shallow

alluvial deposits begin to hold significant amounts of

groundwater. Figure 2 shows the isohyetal map of

annual precipitation for the area. The map indicates

the geographic variability over the western and eastern

slopes of the zone, as well as the location of

different wadis. This rainfall is stormy in nature and

bring flash floods to the area. Insofar as hydrologic

data are concerned, a few surface runoff stations are

located at the foothills side of the wadis. Most of

the runoff records vary from 1967 to the present, as

reported in Ministry of Agriculture and Water (1963-85)

4

BanOAftWir+

+J. Wavle

by +Al Ândah Ansg

Figure 1. A map of Southwestern Saudi Arabia.

AL LITH

KINGDOM OF SAU

RIS HAN

ESCARPMENTMETERS

2000-Re ANNUAL RUNOFF VOLUME

RN=NATURAL SURFACE RUNOFF

RG a ANNUAL GW RECHARGE

i-COASTALPLAIN

100Cs•

UPtANDS

LOCATION MAP OF THE STUDY AREA

Topography of the Southwest Zone

FIGURE (la) TOPOGRAPHIC SECTION OF THE— ZONE.

ESCARPMENT RIDGE

z

AL QUNPUDHAN

LEGEND:-

AL BIRK

•—•-n INTERNATIONAL BOUNDARY.

• WATERSHED REGION BOUNDARY.ISOHYET.

Al.

WESTERN DRAINAGE SYSTEM

JIZAN

5

Figure 2. Isohyetal map of the study area.

publications, with the exception of few stations which

have been in operation since 1953. In some wadis, it

is not possible to provide an accurate estimate of the

natural surface runoff because some amounts are

diverted for agricultural purposes. Furthermore, the

wadi runoff is measured in only one of the branches

(Sorman and Abdul Razzak, 1987).

Saudi Arabia is characterized to be arid and semi-

arid, generally having low and sporadic rainfall of

short duration and high intensity. The sharp reliefs

of the terrain induces extreme flood magnitudes.

The southwest region has a total area of about

250,000 square kilometers, of which 77 percent are

agricultural and 23 percent for nomadic stock raising.

The total population of the area is 502,000 and 84

percent are engaged in agricultural production with the

remaining 16 percent involved with handicrafts and

other commercial ventures.

The southeastern region of Saudi Arabia is within

a transitional meteorological zone that is invaded by

various air masses at different times of the year. In

winter, the area is observed to be under the influence

of westerly air masses from the Mediterranean Sea, and

is associated with depressions that settle over the

northern part of Saudi Arabia. During spring time, an

7

intertropical front moves northward, hence the area

comes under the influence of relatively moist southerly

airstreams that give rise to precipitation over the

escarpment. Southwestern Saudi Arabia, specifically

the study areas of HEMA and USGS watersheds, can be

classified into three climatic zones:

1. The mountains in terms of elevation are above

1500 meters having a mean annual temperature

of 16 to 21°C, with a relative humidity of

about 65 percent. Average annual rainfall is

about 300 to 400 millimeters. Above 2300

meters elevation, it had been noted that ice

and frost are present and the mean temperature

can go as low as below 0°C.2. The foothills region with elevation between

1000 to 1500 meters, has a mean annual

temperature of about 25°C. Average rainfall

ranges from 100 to 300 millimeters.

3. The desert zone has a mean annual temperature

above 250C. The maximum temperature reaches

48 to 50°C, with a relative humidity of lessthan 30 percent. Average annual rainfall is

less than 100 millimeters.

During the winter season, rainfall generally is

related to weak influxes of moist cold air of westerly

8

origin, when mixed with the localized effects of the

Red Sea and the escarpment, rainfall occurs along the

escarpment. In spring, a south-easterly monsoon flow

is generated, along with a consequent convergence,

giving rise to a relatively widespread rainfall over a

large part of the study area. During the summer

months, the south-westerly monsoon flow occurs and this

produces thunderstorms in the south and along the main

escarpment.

Based on records from the Ministry of Agriculture

and Water (MAW, 1985), evaporation ranges from 2.0 to

2.5 meters per year. Due to the different air masses

in the area, a steady decline of humidity occurs from a

mean annual value of 65 percent in the mountainous

region to less than 30 percent in the desert. Annual

gross solar radiation is on the average from 530 to 620

gram calories. Windspeed significantly affects

evaporation and transpiration. It has been observed

that along the escarpment, windspeed is consistent,

with the mean monthly speed of 12 to 18 kilometers per

hour. These speeds, however, go eastward, away from

the escarpment and mountain region with 60 to 70

percent of the speed. Average windspeed in the

escarpment and mountain region is between 7 and 13

kilometers per hour.

9

From a hydrologic standpoint, it appears that the

Asir highlands and the eastward and westward draining

wadis are significant. High rainfall coupled with

impervious underlying geological formations and steep

gradient, provides considerable volumes of direct

surface runoff (El Khatib, 1972).

Runoff over the large majority of the study area

has relevant implications in the hydrologic balance

especially in its role as the main source of recharge

for the alluvial filled valleys. This occurs when the

following conditions exist:

1. high rainfall

2. steep gradients

3. low permeability of the precambrian shield

areas

Runoff, however, is subject to a wide variation in

both quantity and frequency.

Areas that largely generate runoff are found in

the mountainous and steppe regions of the plateau. The

most significant runoff generating areas lie in the

median rainfall belt. In sedimentary and desert areas,

runoff tends to be localized and seldom occurs. Even

though individual storms can yield up to 8 percent as

runoff, it generally is less than 5 percent. The total

runoff volume is, by and large, insignificant compared

to the total rainfall input.

10

The Runoff Process

Runoff is largely dependent on the fact that the

rate of precipitation exceeds the rate at which water

infiltrates into the soil. When the soil is saturated

with water, excess water starts to fill in the

depressions on the soil surface. When the depressions

are filled up, overland flow occurs. Water depth

accumu1ates on the surface until it results in runoff

in equilibrium with the rate of precipitation, less

infiltration and interception. Surface detention is

the amount of water storage on the soil surface. As

channels are filled up by the flow, a similar build up

occurs in channel detentions. The amount of water

found in surface and channel detentions is returned as

in the form of runoff, as the runoff rate decreases.

The water found in surface storage is ultimately

involved in such processes as infiltration or

evaporation.

Factors have been identified to affect runoff and

can be categorized as associated with either

precipitation or watersheds. Runoff rate and volume

are affected by such variables as precipitation

duration, intensity, and areal distribution. The total

runoff for a storm is associated with the duration for

given intensity. Infiltration decreases with time

11

especially in the initial stages of the storm. Hence,

short duration storms may not emit runoff, while a

storm of the Same intensity, but of longer duration can

produce runoff.

Runoff rate and volume are affected by rainfall

intensity. An intense storm far exceeds the

infiltration capacity of the soil than does a gentle

rain. Therefore, the total volume of runoff in an

intense storm can be greater, even though the total

amount of precipitation for two rains may be the same.

Intense storms can disrupt the infiltration process by

its destructive action on the soil structure,

especially at the surface.

The rate and volume of runoff from a defined

watershed area are clearly affected by rainfall

distribution and intensity over that particular area.

The peak runoff rate and volume generally is achieved

when the whole watershed contributes to it. There are

times though that an intense storm on just one portion

of the watershed may emit greater runoff than a

relatively moderate storm over the entire watershed.

Identified watershed factors that influence runoff

are morphological in nature. These include watershed

size, shape, orientation, topography, geology, and

surface culture. There is observed to be a

12

corresponding increase in runoff volume and rates as

watershed size increases. However, runoff rate and

volume per watershed unit area decreases as the area in

which runoff occurs increases. The size of the

watershed determines the season where high runoff is

most likely to happen.

Watersheds that are long and narrow are more

likely to have lower runoff rates compared to those

that are more compact and are of the same size. Runoff

from long and narrow watersheds does not concentrate

quick enough as in compact watersheds. It is most

probable for long watersheds to be less uniformly

covered by intense storms. Storms moving upstream

cause lower peak runoff rates than storms downstream,

especially when the long axis of a watershed runs

parallel to the storm path. Storms moving upstream

have lessened runoff from the lower end of the

watershed before the peak contribution from headwaters

accumulate at the outlets. Furthermore, storms moving

downstream result into higher runoffs from the lower

part of the watershed, especially when it converges

with the high runoff from the headwaters.

Topographic characteristics of the watershed

likewise affect runoff rates and volume, i.e., slope

and gradients of channels, as well as the extent and

13

number of depressed areas. Watersheds possessing

extensive depressed areas without any surface outlets

have lower runoffs compared to watershed areas with

steep and well-defined drainage systems. To a large

extent, geologic factors influence rates of

infiltration thereby affecting runoff too. Other

factors that affect infiltration are cultural practices

in both agriculture and forestry, human activities, as

well as presence or absence of vegetation. Vegetation

impedes overland flow while increasing surface

detention hence reducing peak runoff rates (Schwab

et.al., 1981).

Based on the above discussions, it is evident that

the southwestern part of Saudi Arabia is in dire need

of flash flood warning systems and flood control

structures. The occurrence of floods in the region has

claimed lives and destroyed the livelihood of the

people. In the light of these facts, six models will

be reviewed and analyzed. A model will ultimately be

selected that can assist in the designing of flood

control structures and flash flood warning systems.

14

WATERSHED MODELS: A BACKGROUND

Modeling techniques are important aspects in

natural resource management. Models enable resource

managers to predict future productivity provided with

the necessary data, and from here, decisions can

rationally be made concerning resource management,

conservation and utilization. There are, however, some

considerations that have to be made before seriously

applying modeling techniques in resource management

especially watershed management.

In the selection of a proper model about the

hydrology of watersheds, an approximation of the

reality of the situation in watershed areas is

important, hence the following criteria followed for

model selection:

1. Model inputs - the type of data needed is an

important consideration in selecting a model

since it determines whether the required model

input is accessible in the study area. It

would be an exercise in futility to go through

the process of model selection and in the end

realize that model inputs are not available.

2. Simplicity - this criterion refers to the

number and nature of parameters involved in

making the model operational. Identified

15

model parameters have to be simple enough

such that users can understand and apply the

model with ease.

3. Scale of application - the model applied to

small watersheds should be flexible enough to

account for occurrences in larger watersheds.

It is not to say that the model has to be

universal, but that it should have the

capability to deal with larger watersheds.

It is likewise necessary to identify the watershed

components that comprise the system. Given the system

components, an overall theoretical framework can be

constructed that will define the interrelationships of

watershed components. Equipped with these conceptual

tools, decisions regarding any watershed component

models (i.e., surface runoff) can be made more

rationally and efficiently.

According to Huggins and Burney (1982), surface

runoff can be predicted granted that all possible

factors are predetermined and can be measured

quantitatively. This is so because more often than

not, the components are treated simply as abstractions

from precipitation inputs. Factors identified that

influence rates of water runoff over an elemental area

are (Huggins and Burney, 1982):

16

1. The hydraulic roughness of the surface as

influenced by the micro-relief;

2. The surface macro-slope; and

3. The depth of flow in that elemental area.

Attempts to consider modeling application should

consider three approaches, according to Larson, et.al.

(1982):

1. Using an existing model;

2. Modifying an existing model; and

3. Developing a new model.

As much as possible, these approaches should be

considered in the above order. In using an existing

model, the one best suited to conditions that surround

the system component should be considered. On the

other hand, if modifications are needed, then it should

be done accordingly, based on persistent local factors

affecting the system component. The development of a

new model is an enormous task in itself, possibly

requiring years of study. Whatever alternative is

selected, it is determined by the existing local

conditions. Expertise on modeling principles and

techniques are also imperative, as well as an awareness

about already existent models in the area of watershed

management.

17

This leads the discussion to how models are

structured. Below are elements of a deterministic

watershed model (Larson et. al., 1982):

1. Input parameters representing relevant

physical characteristics of the watershed;

2. Input of precipitation and other

meteorological data;

3. Calculation of water flows, both surface and

subsurface;

4. Calculation of water storages, both surface

and subsurface;

S. Calculation of water losses; and

6. Watershed outflow and other ouputs.

A deterministic watershed model is made up of

submodels that illustrate the various hydrologic

processes, i.e., infiltration, overland flow and the

like. Water flows, storages and losses are generally

inherent in these models. In most cases, the more

detailed a model is, the more numerous the flow

pathways and storages.

The development of a model therefore entails the

selection and linkage of a series of submodels. The

selection of operational submodels is dependent on the

purpose of the larger model in particular. Further,

appropriate submodels are usually the detailed ones.

18

If a submodel is not detailed enough, then it calls for

improvements to be made making it as encompassing as

can be. In general, the model must be sensitive to

identified factors and processes for it to be

operationally acceptable.

Based on the above discussion, it is evident that

watershed models are variable in terms of intent,

structure and hydrologic processes. It is up to the

individual to establish boundaries or limitations to

the model being developed based on the availability of

data and resources on hand.

There are various ways of classifying watershed

models. One way is by distinguishing between event and

continuous models. An event model considers only one

runoff event over a period of time, i.e., one hour to

several days. It attempts to simulate a short duration

thunderstorm type of rainfall where only a daily type

data are available (Fogel, et.al., 1976). On the other

hand, a continuous model functions better over a

lengthened period of time. It ascertains the flow

rates as well as establishes the conditions when runoff

exists or when it does not. In other words, the model

maintains a continuous record of the basin moisture

condition thereby defining initial conditions suitable

to runoff events. At the start of the run however,

19

initial conditions should be established or assumed.

There are three runoff conditions pertinent to

continuous watershed models (Larson et.al., 1982):

1. Direct runoff

2. Shallow subsurface flow (interflow)

3. Groundwater flow

An event model, on the other hand, may not include

one or both of the subsurface components along with

evapotranspiration.

It is worthwhile to classify watershed models into

fitted parameter models or measured parameter models

(Larson et.al, 1982). Fitted parameter models are

those that have one or more means of measurement that

enable it to be assessed by pairing computed

hydrographs with observed hydrographs. This often is

essential if the watershed model applies conceptual

component models. By and large, fitted parameter

models are used on gaged watersheds.

Measured parameter models possess all parameters

that are determined by either measuring or estimating

known watershed traits. For instance, areas of

watersheds as well as channel lengths can be found in

existing maps. Ungaged watersheds can be studied

utilizing measured parameter models.

20

Lastly, watershed models can further be

characterized as general or special purpose models.

That which is universal in nature to all watersheds of

varying types and sizes is a general model. This type

of model takes into account a wide array of watershed

characteristics that have measurable or fitted

parameters. A special purpose model however is more

explicit to watersheds of defined topography, geology

or landuse. This type of model is limited in its use,

although it can also be effective in studying

watersheds of differing sizes as long as these are

characteristically similar.

Provided with the above information, it is

possible to review and compare several frequently used

watershed models. The models to be assessed are all

complete and general watershed models. They do differ

in other aspects.

The Soil Conservation Service Method (SCSI

The SCS method was developed by the Soil

Conservation Service (1972) primarily for agricultural

lands, in order to predict runoff. However, it is

currently being applied to urban and wildland areas as

well. The SCS method is also used to estimate direct

runoff from storm rainfall for small watersheds.

This method is used mainly to calculate amounts of

21

runoff in flood hydrographs or in connection with flood

peak rates. There are four types of runoff that have

to be first recognized to ensure proper usage of the

SCS method (McCuen, 1982):

1. Channel runoff - this results when rain falls

on flowing streams or on impenetrable surfaces

of a stream flow-measuring installation.

2. Surface runoff - happens when rate of rainfall

is greater than the infiltration rate. Runoff

courses through the watershed surface to a

point of reference.

3. Subsurface flow - as rainfall infiltrates the

soil, it encounters an underground zone of low

transmission, flows above this zone downhill

to the soil surface and will emerge as a seep

or spring.

4. Base flow - When there is a fairly steady flow

from the natural storage, this is likely to

occur. There are numerous possible sources

for this type of runoff, such as bodies of

water and aquifers.

A reliable indicator of the type of runoff in an

area is climate, since not all types occur in all

watersheds. In the case of arid regions, the type of

flow is almost always surface runoff especially with

22

smaller watersheds. Humid regions, however, typically

have to consider subsurface flow as well as surface

runoff. A series of prolonged storms in dry climates

can produce either subsurface or base flow, although

the likelihood for this to occur is less, compared to

wet areas.

The most accessible data available in Saudi Arabia

are those found at non-recording gages. Provided with

such information, a rainfall-runoff relationship was

developed. The data were taken from storm totals that

occurred in a calendar year. Unfortunately, nothing is

known about the distribution. The relationship

therefore does not include time as an explicit

variable, indicating that rainfall intensity was

ignored. If data on natural rainfall and runoff for a

large storm over a small area were analyzed, it would

be possible to plot accumulated runoff against

accumulated rainfall. This will indicate the point

runoff starts after a certain amount of rainfall

accumulates. The double-mass line curves form an

asymptotic line that has a 45° slope. The relationshipbetween rainfall and runoff can better be illustrated

with such a plotting. However, a finer approach is to

study a storm where rainfall and runoff occurs

simultaneously, granted that an initial abstraction

23

does not happen. For a simple storm, the relationship

between rainfall, runoff and retention (where rain is

not converted to runoff) at any point on the mass

curve, can be expressed as:

(1)

where:

F = actual retention

S' = potential maximum retention (S > F)

Q = actual runoff

P = potential maximum runoff (P > Q)

Initial abstraction is excluded with S' in

equation 1 and differs totally from parameter S that is

to be used later on. Retention S' is constant with a

particular storm since it is at its maximum under

existing conditions with the persistent storm that has

no limits. Retention F varies and is dependent on the

difference between P and Q at any point on the mass

curve, or:

F = P - Q (2)

Therefore, equation 1 can be expressed as:

P - 0 = Q (3)S'

Solving for Q can result into the following equation:

Q =2P—P +

(4)

24

Equation 4 is a rainfall-runoff relation that ignores

initial abstractions but can be brought into the

equation by subtracting it from rainfall. The

equivalent of equation 1 therefore becomes:

= 0 (5)P - I a

where Ia is the initial abstraction F < S, and Q

(P-

Ia). The parameters S include Ia; meaning that S =

S' + Ia , and equation 4 can result to:

= (P - I a ) 2 (6)(P - I a ) + S

which is the rainfall-runoff relation accounting for

initial abstraction (Fig. 3). Initial abstraction

generally consist of interception, infiltration and

surface storage. All of these transpire before runoff

begins. To lessen difficulty in estimating for these

variables in equation 6, the relation between Ia and S

was determined through rainfall and runoff data from

small experimental watersheds. The empirical

relationship then is:

= 0.2S (7)

Substituting eqUation 7 in 6:

Q = (P - 0.2S) 2 (8)P + 0.8S

This is now the equation that states the relationship

between rainfall and runoff, as used in the SCS method

200 250

250

Rate

Infiltration curve200

G

Time

—Initial abstraction. la

With I ? la ; S ? + G;— and G = I —.la — Q

= 0.2S, so that0D (/—.0 2S) 2

I+0.8S

150

3e.

100

• 110111.11.1111/°111 I I I I

Figure 3. Relationship between rainfall and runoff (US

SCS, 1972).

25

26

in estimating direct runoff from storm rainfall where:

Q = storm runoff in inches

P = storm rainfall in inches

S = potential maximum retention in inches

The Curve Number

Potential maximum retention S is associated with a

curve number (CN) by the empirical equation:

CM = 1000 (9)10 + S

Curve numbers are dependent on the following factors:

L. Soil type;

2. General hydrologic condition of the watershed;

3. Landuse and treatment or practice; and

4. Antecedent moisture condition (AMC).

Curve numbers can be determined with the use of

tables found in NEH-4 (Soil Conservation Service, 1972)

or can be calculated from historical records of

precipitation and discharge. The maximum retention

value S, is calculated from the following equation and

then S is substituted into equation 9 to solve for CN:

S sp 4. 2Q _ (4Q2 5m1/2 (10)

This process of determining the curve number takes

into account the effects of all the hydrologic

processes operating within the watershed (Hawkins,

1977). Further, according to Hawkins (1975), the

27

greatest possible error in estimating runoff can occur

in the selection of the curve number and not in the

precipitation values. Curve numbers can also

dramatically change its values with a corresponding

variation in watershed characteristics, soil and

vegetation type, and cover and soil moisture. Of

these, soil moisture is the most variable. Other

watershed characteristics change when land conditions

are altered over a certain period of time except during

rare situations, which seldom happens.

There is a dearth of empirical information as

regards the relationship between soil moisture and

curve numbers. What little information there is can be

found in the SCS Handbook (USDA, 1972) which utilizes

the 5-day antecedent rainfall and season of the year

(Table 1). Classes of antecedent moisture conditions

(AMC) and curve number relationships are shown in

Figure 4. The reference point here is AMC II and

modifications are made either upward or downward from

AMC II depending on the antecedent rainfall and season

of the year.

28

Table 1. Antecedent moisture class limits (USDA,1972).

Five-day Antecedent Rainfall (inches)

AMC

Dormant Season Growing Season

< 0.5

< 1.4

II 0.5 - 1.1 1.4 - 2.1

III > 1.1 > 2.1

CNforAMCshown

40

29

20

40

60

80

100

CN for AMC II

Figure 4. Effect of antecedent moisture condition on

curve number as referenced on AMC II

(Hawkins, 1978).

3 0

The SCS TR-20 Watershed Model

This model ascertains the peak discharges, time of

occurrence and water surface elevations for individual

storm events. The TR-20 was developed by the Soil

Conservation Service, using the above SCS method as a

basis in 1964. It can produce complete hydrographs

when needed. Discharges at designated locations can be

established with or without various combinations of

reservoirs and channel modifications. This generally

is applied by the SCS and other interested

individuals/researchers in the planning and formulation

of small watershed projects, as well as in flood plains

studies.

The TR-20 can be characterized as a complete,

event, general and measured parameter model. It can

easily be utilized in most agricultural and urban

watersheds, and even with ungaged ones too, especially

with the use of estimated input parameters.

The structure of the TR-20 is shown in Figure 5 .

This model employs two distinct types of operations:

1. Hydrograph computations

2. Control operations

Control operations equip the model with the

possibility of obtaining outputs for as much

combinations as conceivable, of stormy rainfall and

[

INPUT WATERSHEDCHARACTERISTICS

I INPUT SEQUENTIALOPERATION STEPS

INPUT STORM IRAINFALL

HYDROGRAPHS —COMPUTE, COMBINE

PRINT RESULTS(ONE EVENT)

m00iFY

WATERSHED

CONDITIONS-

LAND USEMANAGEMENTRESERVOIRSCHANNELS, ETC.

CHANGESTORMRAINFALL

f

PRINT SUMMARY

TA8LES

ENO

Figure 5. General structure of the SCS TR-20 Watershed

Model (US SCS, 1985).

31

32

watershed conditions, even with just a single computer

run. The control aspect of the model is applicable to

whatever part of the watershed, including the entire

area itself.

Below is a summary of several steps involved in

hydrograph computations:

1. RUNOFF - A subarea flood hydrograph results

from rainfall data. This utilizes the curve

number method to calculate for rainfall

excess, which then is incrementally applied to

the hydrograph to arrive at the subarea

hydrograph (Soil Conservation Service, 1972).

The curve number per subarea is assessed based

on landuse, associated management and

persistent hydrologic conditions, as well as

hydrologic soil group.

2. RESVOR - This is a subroutine that routes a

flood hydrograph through a reservoir or any

other type of water storage area by the

storage-indication method (Soil Conservation

Service, 1972). Reservoirs can be found on

the main stem or any of the tributaries.

3. REACH - Routes flood hydrograph through stream

reaches by the convex method (Soil

Conservation Service, 1972).

33

Required input parameters are subwatershed

drainage areas, times of concentration, runoff curve

numbers, reach lengths for stream routing, routing

coefficient, baseflow or triangular interflow

hydrograph data and initial reservoir elevations.

As for the control instructions, the needed inputs

are the main time increment, storm rainfall depth,

duration and starting time and the antecedent moisture

condition. The following are the tabulated input data

for the program:

I. Storm rainfall distribution --- actual or

synthetic

2. Reservoir characteristic, including spillway

3. Channel and valley cross-sections

4. Dimensionless hydrograph

5. Observed flood hydrograph

Output options are available with the use of this

model, as well as a summary table to compare alternate

designs and input. The structure of the TR-20 model is

such that it allows for the inclusion of several

reservoirs and channel reaches. It can process as much

as nine rainfall distributions and several occurrences

of rainstorms.

AssuMing uniformity of rain depth distribution

over an area is possible with large watersheds,

34

especially if it varies by subwatersheds. The model

typically is utilized on watersheds ranging from 2-400

square miles, with subareas of 0.1 - 10 square miles.

The Stanford Watershed Model

One of the first comprehensive watershed models

developed was the Stanford model, by Crawford and

Linsley (1966). This model has been applied in

numerous water resource studies to construct continuous

hydrographs, assess runoff coefficients and the effects

of urbanization on flood peaks and volumes, and gauge

infrequent flood peaks on natural watersheds.

The Stanford model is both complete and general a

watershed model in that, it may be applied to

watersheds of various types and sizes. It also is

continuous and is normally used over a period of time.

The model employs an array of fitted parameters and

thus may require several years to record the flows.

Various hydrologic processes are mathematically

represented in the Stanford model as flows and storages

(Fig. 6). The overall model, therefore, is based on

biophysical factors although a considerable number of

flows and storages are simplified or presented

conceptually. The Stanford model has the advantage of

refraining from use of physical indicators and

35

HOURLYPRECIPITATION

POTENTIALEVAPOTRANSP.

SNOW 'PACK

I DAILY

TEMPERATURES

I ImPERv. AREAS)

ET

iiNFIL T RATION

IET LOWER ZONE

STORAGE

f SURFACE

DETENTION

IN TE RF LOWDETENTION

OVERLANDFLOw

INTER F LOW

UPPER ZONE

S TORAGE

CHANNELINFLOW

ETC H AN N EL CHANNE L

TRANSLATION

AND ROUTING

GROUND- WATERSTORAGE

GROUNDWATEROuTFLOw

INFLOW

SY THESIZED

STREAmFLow

Figure 6. General form of Stanford Watershed Model IV,

showing principal storages and flows

(Crawford and Linsley, 1966).

36

characteristics of the flow system, even if it utilizes

fitted parameters. This then lessens input requisites

and provides the model with more room for

generalizations.

The model makes use of various surface and

subsurface water storages which unfortunately, are not

explicitly defined in most cases. The Stanford model

highlights the variability of infiltration, interf low,

and evapotranspiration over the watershed area.

Different inflows to the channel system have been

defined by the Stanford model. In all three types of

inflow, the relative volume of the flow over a period

of time changes as demanded by a parameter that

regulates inflow to the respective storage. Another

parameter governs the outflow timing. There are two

steps involved in channel routing:

1. Time-area histogram is constructed depicting

the influence of transposing time from

different parts of the watershed and their

relative areas; and

Construction of a conceptual reservoir at the

watershed outlet illustrates the effects of

channel storage.

Significant contributions to the Stanford model

were made by Anderson and Crawford (1964) using a

37

snowmelt subroutine, and Negev's (1967) sediment model.

The snowmelt subroutine makes use of daily temperature

data as Well as other parameters.

The basic data inputs required by the Stanford

model are hourly and daily precipitation and the

maximum and minimum temperatures for snowmelt.

Potential evapotranspiration can be directly utilized,

or may be taken as lake evaporation. Whatever the case

may be, this is taken on a daily or semi-monthly basis,

Observed daily streamf low data, if accessible, are also

utilized to compare with calculated values. Other

input parameters are watershed characteristics and

trial fitted measures.

When employing the Stanford model, the watershed

is sectioned into subareas, especially so if it has

several rainfall stations. Each subarea is assigned a

recording rainfall station to improve accuracy and

precision for simulation (Crawford and Linsley, 1966).

As regards the span of data gathering of observed

runoff, four to five years is acceptable enough.

The USDAHL-74 Model of Watershed Hydrology

The United States Department of Agriculture

Hydrograph Laboratory (USDAHL) Watershed Model was

primarily developed with small agricultural watersheds

in mind (Holtan et.al., 1975). It however is, being

38

used for different types of watersheds. The model was

constructed sometime in the early 1960s with the

introduction of the Holtan (1961 and 1965) infiltration

function. This model is still being refined (Holtan

and Yaramanoglu, 1977).

The USDAHL-74 model can be classified as a

complete, continuous, and general model. Complete,

since it regards the entirety of the hydrologic cycle

for a watershed. The model is likewise continuous for

it attempts to predict the hydrologic processes that

occur in between storms as well as during storms. And,

it is also general in the sense that it calls for the

inclusion of the effects of agricultural practices or

activities on any of the hydrologic processes.

The model makes use of a lot of quantifiable

parameters. Fortunately, these are accessible. For

instance, routing coefficients are imperative to

evaluate channel flow and subsurface flow regimes.

Hence, existing flow records are indeed useful.

Regarding soil as a parameter, soils within the

watershed are classified by land capability classes in

order to establish hydrologic response zones which

serve as the basic units for all calculations.

The prevalent structure of the USDAHL-74 model is

shown in Figure 7. Precipitation inputs for the whole

ii___.r INFILTRATION SIONALDEPRES

STORAGE

PRECIPITATION

RAIN

SNOW

SNOW MELT

I EVAPO-TRANSPIRATION' I DRAINAGE

39

OVERLANDFLOW

SOILLAYER

2

DRAINAGE

SOILLAYER

a

GROUNDWATERRECHARGE

i LATERAL SUB- HoSURFACE FLOW

ROUTING

BASE FLOW

RUNOFF

Figure 7. General structure of USDAHL-74 Watershed

Model (Holtan et. al., 1975)

41

algorithms for channel flow, subsurface drainage,

sediment detachment and management reactions. A

revision of the model was attempted by Burney and is

generally more accepted since all the routines

necessary to run the model are internal and written in

FORTRAN.

The ANSWERS model can be characterized as an

event-oriented, distributed parameter and deterministic

model. It was developed to simulate the responses of

watersheds to agricultural activities during, and

immediately following a rainfall. ANSWERS is basically

a deterministic model and it revolves around the

hypothesis that:

"At every point within a watershed,functional relationships exist between water flowrates and those hydrologic parameters whichgovern them, e.g., rainfall intensity,infiltration, topography, soil type, etc...Furthermore, these flow rates can be utilized inconjunction with appropriate componentrelationships as the basis for modeling othertransport-related phenomena such as soil erosionand chemical movement within that watershed."(Beasley and Huggins, 1982).

The hypothesis highlights its applicability on a

"point" basis, which in its operational definition is

made flexible and refers instead to a watershed

element. An element can be defined as an area that

exhibits a uniformity in all hydrologically

significant parameters. Some concepts related to

40

watershed is comprised of a continuous record of

rainfall or snowfall. If there is more than one

weather station, then weighted values are used. The

amount of rainfall is managed at regular time intervals

or by breakpoint tabulations.

Excess pecipitation is routed downslope across

each soil zone enroute to the channel. It is possible

to estimate for the roughness coefficient from the

vegetative density, slope steepness and flow path

length as demonstrated by Holtan et.al. (1975).

Channel flows and subsurface return flows are

distributed using an outflow function for the

recession.

It is conceivable that the model output can range

from monthly values to an overland hydrograph for a

storm. An output subroutine was newly added to mark

the daily status of the soil moisture as well as

increments of water movement in each layer of the

watershed zone.

The ANSWERS Model

The Areal Nonpoint Source Watershed Environment

Response Simulation (ANSWERS) model originally was

based on the distributed parameter watershed hydrology

model (Beasley, 1977), constructed by Huggins and Monke

(1966). Model refinements have been on the addition of

42

ANSWERS input requirements have to be discussed in the

process of fully understanding the applicability of the

ANSWERS model:

Retention and Detention:

The volume of water required to build up, to

sustain overland flow is surface detention. The

detention depth can be calculated as the volume of

surface water within an element minus the retention

volume, divided by the area of the element. This

denotes that the total specified retention volume of an

element must be saturated before any water is made

available for surface detention and runoff (Beasley and

Huggins, 1982).

Baseflow:

Basef low is the advent of groundwater into the

channel system. Infiltrated water that moves past the

zone of tile drainage is presumed to enter a

groundwater storage reservoir.

Channel Flow:

Channel flow should be unregulated in terms of

direction as well as its magnitude of branching.

Further, each element of the watershed should

accommodate only one channel segment. This is so

because all overland flow from more than one element is

43

limited to enter a shadow channel segment. Slope

direction determines the course for the shadow channel

segment, hence, only 450 increments in slope direction

is permitted for dual elements.

Rainfall rate:

Net rainfall rate is that which reaches the ground

surface and is dependent on the user specified

pluviograph and the rate of vegetative interception.

Each watershed element is prescribed to have a rain

gage.

There are a host of other inputs reqired in using

the ANSWERS model: infiltration, interception,

sediment detachment, and movement.

The ANSWERS output is comprised of; data input

"echo", watershed characteristics summary and a

detailed listing of the hydrologic and water quality

simulation. The hydrologic output is made up of an

outlet hydrograph along with its associated sediment

concentration, as well as a record of total rainfall,

total flow and average sediment yield. It is likewise

possible to acquire outflow information from any

element within the watershed.

44

The HEC-1 Model

The Hydrological Engineering Center (HEC-1, 1973)

model was developed by the US Army Corps of Engineers.

This model is composed of the following components:

1. Stream network model

2. River routing

3. Combination of different sub-basin runoff

computation

4. Reservoirs

5. Diversions

6. Pumps

The HEC-1 model simulates the effect of

precipitation to surface runoff through a

representation of the basin as an interrelated and

interconnected system of hydrologic and hydraulic

components.

The model employs the following as inputs:

topographic maps, other geographic data, soil

characteristics, and other hydrologic data to

separately simulate runoff for every sub-basin. A

river routing element is utilized to represent flood

wave movement through a river channel. This demands

the use of upstream, individual or combined flood

hydrographs to predict losses through such processes as

infiltration and the like. Through the combination of

45

the various sub-basin runoffs, the HEC-1 model is then

capable of integrating the produced hydrographs from

all the sub-basins. Further, it can develop a new

flood hydrograph for routing in the main channel

downstream. The reservoir component is used to

represent storage outflow characteristics from a

reservoir, lake, or any similar standing body of water.

The diversion component represents channel diversion,

stream bifurcation or any other transfer of flow from

one point of a basin to another. Lastly, the pump

component is utilized to simulate the pumping action of

vegetation used to lift runoff from low ponds.

The HEC-1 model is appropriate for a single storm

and is sensitive to any amount of rainfall.

46

THE AL-BAI A EXPERIMENTAL WATERSHEDS

Experimental data for rainfall and runoff are

extremely lacking in the Kingdom of Saudi Arabia. The

only place where such data exists for small, relatively

homogeneous watersheds, for conditions that are

somewhat similar to the proposed site for the flash

flood early warning system, is located at Al-Baha in

the Asir Highlands in southwestern Saudi Arabia.

Description of the Experimental Site

In 1982, as part of a project in which the

University of Arizona provided technical assistance for

the development of a Faculty of Meteorology and

Environmental Studies at King Abdulaziz University in

Jeddah, Saudi Arabia, two experimental sites were

located to study hydrologic processes. The purpose of

these sites were to provide information for the design

of both water supply and flood control facilities. The

sites were selected with the following criteria in

mind:

1. Accuracy of observations - this allows for the

accurate computation of a real rainfall using

a single recording gauge.

2. Accurate measurements of the resulting runoff

- this required a catchment with a well-

defined water course and outlet, where it is

47

possible to construct a flume.

3. Site accessibility

4. Vegetative cover

5. Topography

In view of the enumerated criteria, and

considering the availability of data in the two micro-

catchment near Al-Baha were selected as the

experimental sites. The location of these sites are

shown in Figure 8. Two sites instead of one were

selected, purposely to cover a reasonable spectrum of

vegetation and topography.

The first site (USGS) is located about a half

kilometer off the Al-Baha-Abha Highway, close to the

village of Shibrigah. The drainage area is

approximately 1.3 square kilometers, and the mean

elevation is about 2250 meters above sea level.

Vegetative cover is mainly of grass and shrubs,

covering approximately 15 percent of the basin. The

rest of the basin consists of precambrian cericite and

chlorite schists with an outcrop of granite. First and

second order types of ephemeral streams are present.

The second site (HEMA) has a drainage area

covering approximately 5.6 square kilometers. Mean

elevation is about 2200 meters above sea level and the

watershed has a relatively moderate slope. Geology of

48

Figure 8. The Al-Baha Watershed.

49

the basin is primarily of precambrian cericite and

schist. The basin has more vegetative cover than the

surrounding area. This is due to grazing restrictions

that are enforced in the area.

A study of the rainfall intensity data in the

southwest region of Saudi Arabia indicated that the

areas surrounding the Al-Baha receive significant

rainfall with varying intensities. The Ministry of

Agriculture and Water (1973) identified the hydrologic

regime around the Al-Baha as being typical of runoff

producing physiological zones.

Another consideration in site selection is the

peculiarity of the hydrologic structure of the

watersheds in the Kingdom. The watersheds,

particularly in the hydrologically active

southwest region, can be divided into two distinct

zones:

1. High rainfall, low infiltration, steep,

highland rainfall-runoff zone.

2. Low rainfall, highly permeable, flat, alluvial

lowland runoff-recharge zone.

The Al-Baha watersheds can be considered as being

located within the first of these two zones.

50

Experimental Data

The only hydrologic data that were available for

the two experimental sites was for the period November

1985 to August 1986 (Abdulrazzak et. al., 1986).

Unfortunately, information for parameter estimates for

the various models were not available.

The rainfall-runoff data, a few events on each

watershed, was used to calculate a characteristic

watershed parameter, potential maximum retention value,

S, for each event using the Soil Conservation Service

formula previously described. The reason this method

was chosen is that it is simple, it requires the

estimation of only one parameter, and, in addition,

many of the hydrologic models use the SCS methodology

to calculate rainfall excess, or runoff volume. S was

calculated for each event using equation 10, and then,

an average S value for each watershed was determined.

Based on experimental information from the Tucson

area, Fogel and Duckstein (1970) suggested that a value

of 20 percent for estimating initial abstractions from

S was too high for semiarid conditions where the

vegetative covers are less dense than for the area

where the SCS method was originally developed. Thus,

for this study, initial abstractions were estimated at

51

15 percent of S and the SCS equation for calculating

runoff volume becomes:Q = (P - 0.15S) 2

P + 0.85S

Inasmuch as the watershed retention value S is not

expected to change other than for antecedent moisture

conditions, an average for S was used with equation 11

to estimate the runoff volume for each event. The

calculated values were then compared to the observed as

shown in Table 2. If more data were available, a more

accepted approach for making this comparison would be

to use part of the data to estimate the parameter S and

Table 2. Observed Versus Calculated Rainfall-RunoffData From Two Watersheds.

Rain-Date fall

depthin.

Obs. Peak Reten-runoff flow tionvol., rate, (S)in. cfs in.

Ave. Cal- MarginS culated of

runoff Errorvol., in.

USGS Watershed

11-19-85 1.3 0.25 10.2 2.15 0.660 +.4103-01-86 0.7 0.20 26.2 0.86 0.217 +.01703-02-86 0.65 0.26 17.6 0.59 0.187 -.073

04-03-86 0.31 0.06 6.03 0.54 0.028 -.03204-04-86 0.20 0.05 3.65 0.28 0.004 -.046

08-27-86 0.31 0.01 0.13 1.02 0.028 +.0180.90

HEMA Watershed

08-05-86 0.54 0.16 8.30 0.65 0.198 +.038

08-13-86 0.36 0.08 3.40 0.54 0.087 +.007

08-27-86 0.78 0.37 25.0 0.55 0.377 +.0070.58

52

the remainder of the data for comparing calculated to

observed runoff volumes.

While there is a large difference between observed

and calculated runoff values, even though the limited

8data was used to estimate the parameter S, there

appears to be some consistency. For example,

antecedent moisture content is known to affect S, that

is, the wetter the soil, the higher the curve number

and the lower the S. In observing the data from the

USGS watershed, it can be seen that there were two

times when there were two consecutive days of rainfall

and runoff. In each case, the second day produced a

lower value of S.

With reference to Table 2, it can be seen that the

runoff values in the HEMA watershed have a lower margin

of error than the runoff values from the USGS

watershed. It could be that the antecedent soil

moisture conditions were not properly estimated. The

first two events from the USGS watershed may have used

antecedent soil moisture conditions that were too high.

The remaining events may have used antecedent soil

moisture conditions that were too low. The HEMA

watershed, being more dry has less antecedent soil

moisture condition factors affecting the runoff betwen

the observed and calculated values.

53

DISCUSSION AND CONCLUSIONS

While much of the arid and semi-arid regions in

Saudi Arabia annually receive less than 300 millimeters

of rainfall, extreme precipitation events certainly

occur with significant frequency that result in

extensive damage to property and transportation

networks, and on occasion, loss of lives. In the

southwestern part of Saudi Arabia, which has relatively

high elevations, these events may record as much as 50

percent more of the total annual rainfall.

Many models have been developed in the last thirty

years to calculate runoff from rainfall. Many of these

models are site specific, and therefore, users are

faced with the problem of selecting the model which

will most efficiently provide the answers needed. The

selection of the most appropriate model depends to a

large extent, on the problem. Hence, the most

appropriate model changes as the problem changes.

There are no agreed upon criteria that can be used to

evaluate the different models. Some criteria may

differ according to technical knowledge of the user,

cost, availability of data required, accuracy,

simplicity of the model, and the time frame involved.

In this study, six models were chosen as

potentials for use in the southwestern part of Saudi

54

Arabia. These six were trimmed to the most appropriate

model/s selected on the following premises:

1. Model inputs needed - data available about the

study area is limited, therefore the model

that will be chosen should function within the

scope and limitations of the problem on hand.

2. Simplicity - refers to the number of

parameters that must be obtained and the ease

with which the model can be explained to users

and others who might be interested in it.

3. Scale of application - it is important that

the model to be applied on smaller units (like

small wadis and sub-basins) simultaneously

will manifest the same ability to deal with

big watersheds.

The models described in the previous chapter have

some similarities. They, however, do possess major

differences as well. The Stanford and USDAHL-74 models

are continuous watershed models. These were designed

purposely for operations over a long period of time,

with actual weather sequences and the like. The SCS

method and the SCS TR-20 models being event models in

themselves, are such that the initial conditions for

each event must clearly be defined. The main purpose

of these models is to evaluate systems of structural

55

measures. The ANSWERS model is distributal in nature,

intended for individual storm events. Its parameters

are all physically based. It is possible to measure or

estimate their values thus making the models applicable

to ungaged watersheds for present and future

conditions.

The Stanford, USDAHL-74 and HEC-1 need actual

weather sequences, further requiring available

streamf low data, infiltration, soil moisture storage,

interf low and groundwater flow on a daily basis. These

values are used in determining amounts of runoff. T h e

SCS method and the SCS TR-20 were developed for ungaged

watersheds. Accordingly, they employ parameters that

can be evaluated directly from observable watershed

characteristics. As regards model applicability to

various landuse forms, the Stanford, SCS, SCS TR-20 and

HEC-1 models can be utilized specifically on forest,

pasture and range, agriculture and urban lands. The

USDAHL-74 model can be applied to agriculture and urban

lands, and the ANSWERS model purely for agricultural

lands. For small watershed projects, the SCS and SCS

TR-20 models are suitable, while the ANSWERS, HEC-1 and

USDAHL-74 models were designed primarily for large

watershed, and lastly, the Stanford is applicable to

watersheds of varying sizes.

56

One of the requirements for designing flood

control structures and flood warning systems is an

estimate of their depths, especially the peak. All

models provide an estimate of flow rates which can be

translated to flow depths in specified channels. Since

little or no data exists in Saudi Arabia, these

estimates have to be made for ungaged watersheds.

Conclusions

Hydrological models can vary in structure, amount

of detail and emphasis on individual hydrologic

processes. Their basic nature also varies. In

choosing the most appropriate model for the designing

of flash flood warning systems and flood control

structures for application in the southwestern region

of Saudi Arabia, different criteria were used as a

basis for comparing six of the more promising models.

It is evident from the discussion that each model has

advantages and disadvantages in terms of the required

input data and simplicity of the model. The ANSWERS,

SCS and SCS TR-20 models are simple enough compared to

the others, because these can be applied on ungaged

watersheds. In terms of land use, the ANSWERS,

Stanford and USDAHL-74 models have certain limitations

on some land forms and landuses. When the models were

compared in terms of the size of the watershed, the SCS

57

and SCS Th-20 models turned out to be the most

applicable for smaller watersheds.

Further consideration of the availability of the

type of data, limits model selection. Thus,

considering the characteristics of the study area and

the available data required as inputs to the model, it

appears that, at this time, the SCS or SCS TR-20 is the

most appropriate model for the southwestern part of

Saudi Arabia, primarily because it requires less

parameter estimates, is simple to use and can route

flows downstream in ungaged watersheds. Flood warning

systems for semiarid regions require models that route

only surface flows; thus, the event-based SCS models

are suited for this purpose..

It is clear that additional data and research will

be required before the process of model comparison and

selection can take place. Thus when experimental or

representative watersheds are installed, it is

recommended that their instrumentation consider the

type of data to be collected in terms of inputs to a

given set of hydrologic models.

58

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