Application of Remote Sensing and GIS in Flash Flood Hazard Mapping and

Hydraulic Modeling(case study of Wadi Dahdah, Saudi Arabia)

ABSTRACTFlash floods are considered as catastrophic phenomena possessing majorhazardous threat to many of infrastructure facilities, especially new constructionprojects in Saudi Arabia. This study deals with the evaluation of flash flood hazardin the ungauged Wadi Dahdah basin depending on its detailed morphometriccharacteristics, hydrological studies, meteorological Analysis, and hydraulicmodeling. For this study, ASTER data were used for preparing digital elevationmodel (DEM), geographical information system (GIS) was used in the evaluationof linear, areal and relief aspects of morphometric parameters, Remote sensingdata (Landsat8) to analysis and preparing Digital Land Use/ Land cover mapping,using some special software for rainfall analysis and estimating IDF curves andfinally using WMS and HES-RAS for Hydrological analysis and hydraulic modeling.Thus can predict the probability occurrence of floods at various frequency timesand determine the intensity of the flood (depth and velocity of flood water) insidethe stream of the Wadi, and in case of important construction exposed to the riskof floods must to develop optimal solutions that control of flood waters andthrough the establishment of different protection works such as dams and storagelakes and drainage channels and culvert ... and other. So it was important to makesufficient hydrological studies to safety this sites of the Probabilities dangers offlooding.

IntroductionFlash floods often occur in arid regions as a consequence of excessive rainfall andoccasionally cause major losses of property and life (Subyani 2009). Flood hazardmapping is a component needed for appropriate land use in the flooded areas. Itcreates easily read, rapidly accessible charts and maps which mitigate the effectsof floods (Bapalu and Sinha 2005). Flood hazard mapping in arid regions is anextremely important but difficult task; the main reason is the scarcity of data inarid regions. Flood hazard mapping is very important for catchment management(i.e. for sustainable development of the water resources and for protection fromthe flood hazard and drought). Rainfall and runoff data are the essentialhydrological elements in the flood mapping of basin systems. So, because thestudy area is suffering from scarcity of data andthe flood inundation maps are dependent on the topographicand geomorphic features of the Wadi ( et al. 2012), this study is based on theintegration between physiographic features of the study area and GIS techniques.The integration of GIS to create flood hazard maps and disaster decision supporthas been continually upgraded and widespread since the beginning of thetwenty-first century, as a result of the increased availability of spatial databasesand GIS software (Zerger and Smith 2003). Several studies are cited in theliterature, relating to flood hazard mapping and zonation using GIS (Sui andMaggio 1999; Merzi and Aktas 2000; Guzzetti, and Tonelli 2004; Sanyal and Lu2006; He et al. 2003; Fernandez and Lutz 2010). Drainage basin characteristics inmany areas of the world have been studied using conventional geomorphologicapproaches (Horton 1945; Strahler 1964; Rudriaih et al. 2008; Nageswararao etal. 2010; Al Saud 2009). Gardiner (1990) indicated that in some studies, themorphometric characteristics of basins have been used to predict and describeflood peaks and estimation of erosion rate, underlying the importance of suchstudies. The application of geomorphological principles to flood potential orflood risk has led to a noteworthy amount of researches, attempting to identify therelationships between basin morphometric and flooding impact (Patton 1988).Identification of drainage networks within basins or subbasins can be achievedusing traditional methods such as field observations and topographic maps, oralternatively with advanced methods using remote sensing and digital elevationmodel (Macka 2001; Maidment 2002).

Al Quassim

Al Madinah

Ar Riyad

Ash SharqiyahMakkah

Al Bahah

`Asir

Najran

Jizan

Ha'il

Tabuk

Al Hudud ash ShamaliyahAl Jawf

`Asir

43°0'0"E

43°0'0"E

44°0'0"E

42°0'0"E

42°0'0"E

20°0'0"N 20°0'0"N

19°0'0"N 19°0'0"N

18°0'0"N 18°0'0"N

44°0'0"E

42°0'0"E

44°0'0"E

Degital Elevation Values

High : 961.765

Low : 288

!.

Stream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

!.

4

1

1

1

1

1

21

2

2

2

*The Digital Elevation Model Obtained fromAsterGDEM v2 30 m Resolution and Manupulatedby (IDW) Technique to 15 m Resolution*.

0 0.5 1 2 3 4

Kilometers

DiGital EleVation MoDel ofthe Study BaSin

Digital ElevationModel of Saudi Arabia

Digital ElevationModel of Aser

Location and geological characteristics of Wadi DahdahThe Wadi Dahdah is located in the western part of the Kingdom of Saudi Arabia at Aser Region. It lies between 41.8 and 41.92 longitudesand 18.9 and 19 latitudes with an area about 104 km2 and length about 14 km. Geologically, Wadi Dahdah is underlain by lateProterozoic plutonic, and volcanic rocks in the north and east of the Wadi with an area about 35.3 % of the total area, by volcanic andplutonic rocks, and by Tertiary oceanic crust of the Red Sea offshore. The contact between continental and oceanic crust is probably 10 15km onshore. The coastal plain is blanketed by Quaternary sediments of Aeolian sand, silt and pediment deposits with area of about 64.6% of the total area with thickness that ranges from 2 to 10 m.

K.Amin

Gis and Remote Sensing Sector,

Egyptian Mineral Resource and

Geological Survey Authority.

Cairo, Egypt.e-mail: kareemamin2001@hotmail.com

Digital Elevation Modeling

Morphometric Analysis

Relative Slope Position

Terrain Ruggedness Index

Hypsometric Curve

Aspect

Basic Terrain Analysis

Relative Relief PositionDownslope

Distance Gradient

Topographic Position Index

Slope

Hydrological Analysis

Stream Power Index

Topographic Wetness Index

Melton Ruggedness Number

LS Factor

Hydro-Morphometric Parameters

Remote Sensing Data

Geometric Correction &

Georeferencing

Digital image processing

Image classification

NADVI

Land-use/Land Cover Map

MeteorologicAnalysis

Rainfall data

Hydrological Modeling

Soil data

SCS Curve Number

Floodplain and Hydraulic Model

Methodology

1

Drainage Pattern Analysis

Stream Order

!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

19°0'0"N

18°58'30"N18°58'30"N

18°57'0"N

Aspect Map

Flat (-1)

North (0-22.5)

Northeast (22.5-67.5)

East (67.5-112.5)

Southeast (112.5-157.5)

South (157.5-202.5)

Southwest (202.5-247.5)

West (247.5-292.5)

Northwest (292.5-337.5)

North (337.5-360)

0 0.450.9 1.8 2.7 3.6

Kilometers

¥

LegendStream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

!.

AspectGenerally refers to the direction to which a mountainslope faces. The aspect of a slope can make verysignificant influences on its local climate because thesun s rays are in the west at the hottest time of day inthe afternoon, and so in most cases a west-facing slopewill be warmer than sheltered east-facing slope. Thiscan have major effects on the distribution of vegetationin the watershed area. The aspect map of W.Dahdahbasin is shown. It is clearly seen that west-facing slopesmainly occur in the basin. Therefore, these slopes havea lower moisture content and higher evaporation ratealthough and some parts are falling towards eastfacing which a higher moisture content and have alower evaporation rate.

Slope-Drainage Basin Map

Slope

<5

5 - 9.8

9.8 - 16.4

16.4 – 24

24 - 34

34- 45

45 – 56

56 – 70

>70

¥!. Project Site (Pour Point)

Legend

Stream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Watershed

!

SlopeSlope analysis is an important parameter in geomor-phological studies for watershed development andimportant for morphometric analysis. The slopeelements, in turn, are controlled by theclimatomorphogenic processes in areas having rock ofvarying resistance (Magesh et al. 2011; Gayen et al.2013). A slope map of the study area is calculatedbased on ASTER GDEMv2 data using the spatialanalysis tool in ARC GIS-10.3. Slope grid is identifiedas the maximum rate of change in value from eachcell to its neighbors (Burrough 1986). The degree ofslope in W.Dahdah watershed varies from <5 to>70.The slope map is shown in Fig. 2b. Has higher slopedegree results in rapid runoff and increased erosionrate (potential soil loss) with less ground waterrecharge potential. Higher slope is identified in North-eastern part of the basin where it originates.

0 0.450.9 1.8 2.7 3.6

Kilometers

It affects where structures

or trails can be built,

crops can be planted, the

speed of flowing water

and consequent erosion,

landslide potential.

!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

19°0'0"N

18°58'30"N18°58'30"N

18°57'0"N

0 0.450.9 1.8 2.7 3.6

Kilometers

Relative Relief Map

LegendStream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

!.

Relative Relief

VALUE

2 - 23

23 - 29

29 - 43

43 - 74

74 - 334

Relative relief Relative relief is difference between summit level, thehighest altitude for a given area, and base level, lowestaltitude for a given area (Dury, 1962, p. 174). It plays animportant morphometric variable used for theassessment of morphological characteristics of anytopography (Gayen et al. 2013. The highest relativerelief is calculated as 334 m, while the lowest value isrecorded as 2 m Fig. 3a. The low relief indicates that thenorthern and central Southern area under W.Dahdahbasin is flat to gentle slope type. Therefore, the areacould be basically used for agricultural activities aroundstream sides due to being flat in nature and also a wateraccessibility.

Relative Slope Positionlandscapes can be classified into discrete slope positionclasses, Jones, K. Bruce et al 2000.

The major of the Basin AreaIs middle slope and upperSlope delineated at East andWest of the basin.There relationships between soil moisture content and arelative slope position (upslope, midslope, anddownslope) were qualitatively understandable even inthe early twentieth century (Zakharov, 1913).Quantitatively, the dependence of soil moisture contenton catchment area (which, in fact, describes the relativeposition of a point on the topographic surface) wasprobably first described by Zakharov (1940, p. 384) asfollows: water amount per unit area increases fromupslope to downslope due to additional water supply.Thus, as CA increases, soil moisture content alsoincreases.

Zero, low slope

Slope position

Moderately positive

0

depression cliff

valley bottom base slope valleys

Very negative (valley)

Very positive

(ridge)

Zero, low slope

(flat)

Zero, high slope (open cliff)

Negative

(cliff base)

Positive

(cliff edge)(flat)

(upper slope)

Zero, moderate slope

(open slope)

Moderately negative

(lower slope)

hill top

ridge top

cliff

ridges slope edge

lower lateralconstant slope lateral upper

gentle plains

saddles

More negative More positive

gentle

1 ridge > + 1 2 upper slope > 0.5 =< 1 3 middle slope> -0.5, < 0.5, slope > 5 deg4 flats slope >= -0.5, =< 0.5 , slope <= 5 deg5 lower slopes >= -1.0, < 0.5 6 valleys < -1.0

!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

19°0'0"N

18°58'30"N18°58'30"N

18°57'0"N

Relative Slope Position

Legend

Stream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

!.

0 0.450.9 1.8 2.7 3.6

Kilometers

VALUE

0 - 0.06

6. - 0.2

0.2 - 0.4

0.4 - 0.73

7. - 1

2

Part I : T

he B

asic

Terra

in A

naly

sis

Downslope Distance Gradient

]1[ This index has become widely used inhydrology, but it utilizes a relatively small portion ofthe information contained in a digital elevationmodel (DEM). One potentially important featurenot considered in the implementation of theln(a/tanß) index is the enhancement or impedanceof local drainage by downslope topography. Thiseffect could be important in some terrain forcontrolling hydraulic gradients.Applied this index to our study Area shows highvalues at the Western and Eastern part of the basinand minor sites in the Northern and Southern partswhich refer to high local drainage areas thatfeeding the main stream of the Basin.

TRI (Nellemann’s Terrain Roughness Index)is a somewhat antiquated contour density

(transect-and-contour map) approach with applicationsto arctic wildlife. See Nelleman et al. (2007), Nellemannand Fry (1995), Nelleman and Thomsen (1994) papersfor methods. Nelleman et al. (2007), a paper on brownbears, classified TRI values for a study on Scandinavianbrown bears into . They used a1:100,000 scale DEM with a 10m contour interval, 4kmtransects within 4km x 4km grid cells: = TRI >2.5, = TRI < 2.5.

Topographic Position Index (TPI)Topographic Position Index (TPI) calculation as proposedby Guisan et al. (1999). This is literally the same as thedifference to the mean calculation (residual analysis)proposed by Wilson & Gallant (2000).The bandwidth parameter for distance weighting isgiven as percentage of the (outer) radius. Positive TPIvalues represent locations that are higher than theaverage of their surroundings, as defined by theneighborhood (ridges). Negative TPI values representlocations that are lower than their surroundings (valleys).TPI values near zero are either flat areas (where theslope is near zero) or areas of constant slope (where theslope of the point is significantly greater than zero).

Hypsometric curve Hypsometric curves are non-dimensional measure of the proportion of the catchment area above a given elevation. According to Schumm (1956), Strahler (1964), Leopold et al. (1964) and Hurtrez et al. (1999), hypsometric curves are related to geomorphic and tectonic evolution of drainage basins in terms of their forms and processes. Strahler(1952, 1957, and 1964) identified three types of landforms, namely, young, mature and monadnock on the basis of hypsometric curve shape.

!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

19°0'0"N

18°58'30"N18°58'30"N

18°57'0"N

Gradient

LegendStream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

!.

Downslope Distance

¥

ValueHigh : 0.40

Low : 0.040

0 0.450.9 1.8 2.7 3.6

Kilometers

!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

19°0'0"N

18°58'30"N18°58'30"N

18°57'0"N

Terrain Ruggedness Index

LegendStream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

!.

0 0.450.9 1.8 2.7 3.6

Kilometers

VALUE

<2.5 Flat

>2.5 Rugged

pt < µ = tpi < 0 (valley)Mean

Elevation neighborhood µElevation at point pt

orad irad pt > µ = tpi > 0 (ridge)

Elevation at point pt

Mean Elevation neighborhood µ

SlopeMean Elevation in

Neighborhood µ

Elevation at point pt

Mean Elevation in neighborhood µ

Elevation at point pt

pt ~ µ = tpi ~ 0 (constant slope, flat area, or saddle)Check slope of the point

Flat

scalefactor = outer radius in map units

irad = inner radius of annulus in cellsorad = outer radius of annulus in cells

!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

19°0'0"N

18°58'30"N18°58'30"N

18°57'0"N

Topographic Position Index

LegendStream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

!.

0 0.450.9 1.8 2.7 3.6

Kilometers

Value

High : 4.8

Low : -4.8

0

0

10

20

30

40

50

60

70

0

20

40

60

80

100

120

1 3 5 7 9 111315171921232527293133353739414345474951

Hypsometric Curve

Relative Height 80.239521

Hypsometric Curve Interpretation

Elevation

00

max

Pe

rce

nta

ge o

fb

asin

po

ints

ab

ove

agi

ven

ele

vaio

n

100

00

max

Pe

rcen

tage

of

bas

inp

oin

ts a

bo

ve a

give

nel

eva

&o

n

100Young Basin Old Basin

Elevation

Hypsometric Integral = Maximum Elevation – Minimum Elevation

Mean Elevation – Minimum Elevation

3

Part II : T

he M

orp

ho

metric

Analy

sis

The Topographic Wetness Index (TWI)The topographic wetness index (TWI) wasdeveloped by Beven and Kirkby (1979) within therunoff model TOPMODEL. It is defined as ln(a/tanß)where a is the local upslope area draining through acertain point per unit contour length and tanß is thelocal slope. It Also called Compound TopographicIndex (CTI). Higher CTI values represent drainagedepressions, lower values represent crests andridges. And it is related with soil moisture. Itindicates the tendency of a cell to produce runoff,since areas with high moisture are more prone tobecome saturated. The higher the value of thisindex in a cell, the higher soil moisture that can befound in it. Compound Topographic Indexdescribes the tendency of terrain to accumulatewater. Stream Power and Sediment TransportIndices describe tendency of flow and can be usedto depict locations of potential erosion.

The stream power indexStream power index (SI) takes into account both alocal slope geometry and site location in thelandscape combining data on slope gradient andcatchment area (SCA):

SPI = SCA * tan(Slope)Stream power index can be used to describepotential flow erosion at the given point of thetopographic surface. As catchment area and slopegradient increase, the amount of water contributedby upslope areas and the velocity of water flowincrease, hence stream power index and erosionrisk increase. It controls potential erosive power ofoverland flows, thickness of soil horizons, organicmatter, pH, silt and sand content, plant coverdistribution.Ref. I.V. Florinsky, Digital Terrain Analsis in Soil Scienceand Geology.

Slope Length and Steepness factor (LS-factor)]2[The Universal Soil Loss Equation (USLE)model is the most frequently used model for soilerosion risk estimation. Among the six inputlayers, the combined slope length and slopeangle (LS-factor) has the greatest influence onsoil loss at the European scale. The S-factormeasures the effect of slope steepness, and theL-factor defines the impact of slope length. Thecombined LS-factor describes the effect oftopography on soil erosion.

Melton Ruggedness NumberMelton ruggedness number (MNR) is a simpleflow accumulation related index, calculated asdifference between maximum and minimumelevation in catchment area divided by squareroot of catchment area size. The calculation isperformed for each grid cell, therefore minimumelevation is same as elevation at cell's position.Due to the discrete character of a single maximumelevation, flow calculation is simply done withDeterministic 8. (Zmax-Zmin) / Sqrt(A)

References:Marchi, L. & Fontana, G.D. (2005): GIS morphometric indicators for theanalysis of sediment dynamics in mountain basins. Environ. Geol.48:218-228, DOI 10.1007/s00254-005-1292-4.

I. hydrological indices

!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

18°58'30"N18°58'30"N

18°57'0"N

Topographic Wetness

Index (TWI)

LegendStream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

0 0.450.9

19°0'0"N

!.

Value

High : 10

Low : 1!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

19°0'0"N

18°58'30"N18°58'30"N

18°57'0"N

Stream Power Index

¥

Value

High : 32000

Low : 00 0.450.9 1.8 2.7 3.6

Kilometers

!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

19°0'0"N

18°58'30"N18°58'30"N

18°57'0"N

¥LS Factor for the Basin

LegendStream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

!.

0 0.450.9 1.8 2.7 3.6

Kilometers

Value

High : 38.9349

Low : 0!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

19°0'0"N

18°58'30"N18°58'30"N

18°57'0"N

0 0.450.9 1.8 2.7 3.6

Kilometers

Melton Ruggedness Number

LegendStream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

!.

Value

2.8

Low : 0

¥ ¥

¥ ¥

4

Part III : T

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yd

rolo

gic

al A

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sis

¥

Stream order (U)The ranking of streams has been carried out based on the methodproposed by Strahler (1964). stream orders are classified up to fourorders in the W.Dahdah Basin. The maximum stream order frequencyis observed in case of first-order streams and then for second order.Hence, it is noticed that there is a decrease in stream frequency as thestream order increases and vice versa.

Stream Length (Lu)According to Horton (1945), streams lengths delineate the total lengths of streamsegment of each of the successive orders in a basin tend to approximate a directgeometric series in which the first term is the average length of the stream of thefirst order. The stream length is a measure of the hydrological characteristics of thebedrock and the drainage extent. Wherever the bedrock and formation ispermeable, only a small number of relatively longer streams are formed in a well-drained watershed, a large number of streams of smaller length are developedwhere the bedrocks and formations are less permeable (Sethupathi et al. 2011).The result of order stream length in Wadi Dahdah basin is shown in the Table . It isclearly identified that the cumulative stream length is higher in first-order streamsand decreases as the stream order increases.

Mean stream length (Lsm)Mean stream length (Lsm) reveals the characteristic size of components of adrainage network and its contributing surfaces (Strahler 1964). It has beencomputed by dividing the total stream length of order u by the number of streamin the same order u. It is noted that Lsm value of any stream order is greater thanthat of the lower order and less than that of its next higher order in the basin. TheLsm values differ with respect to different basins, as it is directly proportional to thesize and topography of the basin.

II. Hydro-Morphometric Paramters

18°57'0"N

Low : 1!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

Catchment19°0'0"N

18°58'30"N18°58'30"N

Catchment Drainage Map

Value

High : 241

0 0.450.9 1.8 2.7 3.6

Kilometers

¥LegendStream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

!.

40%

30%

20%

10%

Stream Order/ Total Length

1

2

3

4

Stream number (Nu)Number of streams of different orders and the total number of streamsin the basin are counted and calculated in GIS platforms. Duringcalculation it is identified that the number of streams graduallydecreases as the stream order increases; the variation in stream orderand size of tributary basins is largely depends on physiographical,geomorphological and geological condition of the region. 157 streamline is recognized in the whole basin, out of which 40 % (121) is 1storder, 30 % (29) 2nd order, 20 % (6) 3rd order, 10 % (1) 4th order.

Stream Order

Nu Stream Order

Stream Order Length

Stream Length Ratio

Mean Stream Lenght

bifurcation ratio (Rb).

4 1 10.52 0.056 10.52 6

3 6 30.25 0.16 5.04 4.8

2 29 40.72 0.21 1.40 4.1

1 121 105.61 0.56 0.87

10 157 187.11553 Total

Bifurcation ratio (Rb)Horton (1945) considered Rb as an index of relief and dissection while Strahler (1957) opined that Rb shows only a small variation for different regionswith different environments except where powerful geological control dominates. According to Schumn (1956), the term bifurcation ratio (Rb) may bedefined as the ratio of the number of the stream segments of given order to the number of segments of the next higher orders. It is a dimensionlessproperty and shows the degree of integration prevailing between streams of various orders in a drainage basin. 1st Order/2nd Order ..etc. Thebifurcation ratio was introduced by Horton (1945) and modified by Strahler (1952). It characteristically ranges between 3 and 5 in homogeneousbedrock (Chorley 1969 and Waugh 1996). Chorley (1969) had noted that the lower the bifurcation ratio, the higher the risk of flooding, particularly ofparts and not the entire basin. The lower values of Rb are characteristics that the basin has suffered less structural disturbances [1] and the drainagepatterns has not been distorted because of the structural disturbances [6]..The higher value of Rb indicated strong structural control on the drainagepattern and also streams that have a higher average flood potential due to numerous tributary segments drain into relatively few trunk transportingstream segments. The bifurcation ratios of the study area vary from 4.1 to 6, which fall under High basin category [10]. The mean bifurcation ratio (Rbm)may be defined as the average of bifurcation ratios of all order and it s 4.96 in case of W.dahdah Basin.

II.1 The linear network properties:

Relief ratio (Rh)Schumm (1956) states that the maximum relief to horizontal distance along thelongest dimension of the basin parallel to the principal drainage line is termed asrelief ratio. The high value of relief ratio is characteristics of hilly areas with highrunoff production and soil erosion. Low value of relief ratios is mainly due to theresistant basement rocks of the basin and low degree of slope (Mahadevaswamy etal. 2011). The Rh normally increases with decreasing drainage area and size of agiven drainage basin (Gottschalk 1964). The relief ratio of the basin is 0.042.

II.2 Aerial Aspects of the Drainage Basin: Elongation ratio (Re)The elongation ratio (Re) is the ratio between the diameter of the circle of the same area as the drainage basin and the maximum length of the basin[16]. A circular basin is more efficient in the discharge of runoff than an elongated basin [20]. Higher values of elongation ratio show high infiltrationcapacity and low runoff, whereas lower Re values which are characterized by high susceptibility to erosion and sediment load (Reddy et al. 2004).Thevalues of Re vary from 0.6 to 1.0 over a wide variety of climatic and geologic type. Values close to 1.0 are typical of region of very low relief, whereasvalues in the range 0.6 to 0.8 are usually associated with high relief and steep ground slope [1]. It can be grouped into three class namely Circular(>0.9), Oval (0.9-0.8), and Less elongated (<0.7). The Basin shows Re value of 0.72 which falls in the oval class. This reveals that the majority of the areahas high relief and steep sloped.

Circularity Ratio (Rc)Miller (1953) stated that The circularity ratio Rc of the basin is the area of a circlehaving the same circumference as the perimeter of the basin. It is influenced by thelength and frequency of stream, geological structures, landuse/ landcover, climate,relief and slope of the basin. It is a significant ratio that indicates the dendritic stageof a watershed. Low, medium and high values of Rc indicate the young, mature, andold stages of the life cycle of the tributary watershed (John Wilson et al. 2012).TheCircularity Ratio is 3.1 which indicates strongly elongated and extremely permeablehomogenous geologic materials.

Form Factor (Rf)Horton (1932) stated that the form factor Rf is the ratio of the basin area to the square of the basin length [9]. This factor indicates the flow intensity of abasin of a defined area. The form factor value should be always less than 0.7854 (the value corresponding to a perfectly circular basin). The smaller thevalue of the Rf, the more elongated will be the basin. The elongated watershed with low form factor indicates that the basin will have a flatter peak offlow for longer duration and conducive for more groundwater recharge. Watersheds with high form factors experience larger peak flows of shorterduration, indicating less contact time and less infiltration. Rf value of the W.Dahdah basin is 0.41 which is more or less elongated basin with lower peakflows of longer duration than the average.

Slopew.Bifurcati

on ratio

Constant Channel Maintenance (C)

Topographic Texture

Stream frequency

Drainage Density

Stream Order Length

Nu Stream Order Hypsometric

integrationRuggedness

valueRelative

ReliefRelief Ratio

Length/Width Ratio

sinuosity ratio

Buckling Factor

Integrating Factor

Form Factor

Elongation ratio

Circularity ratio

Relief

Width

Length Premiter Square Premiter

Root Area/pi Area*pi Area/pi Area Basin

0.42 4.69 0.56 2.42 1.51 1.79 187.11553 157 0.15 1.21 0.01 0.042 2.46 40.26 0.61 3.21 0.41 0.72 0.31 673 6.5216.0

0 4197.74 64.79 5.76 327.38 33.20 104.26Main Basin

Constant Channel Maintenance (C)Schumm (1956) used the inverse of drainage density as a property termed constant of stream maintenance C. This constant, in units of square feet perfoot, has the dimension of length and therefore increases in magnitude as the scale of the land-form unit increases. Specifically, the constant C providesinformation of the number of square feet of watershed surface required to sustain one linear foot of stream. The value C of basin is 0.56.It means that onan average 0.56 sq.ft surface is needed in basin for creation of one linear foot of the stream channel.

Slope Average (S)Slope average (S) is computed by dividing basin length (Lb) by basin relief (H) in thesame unit (meters) for expressing changes of the slope between the upstream areaand the pour point. Generally, the slope plays an important vital role for estimatingflood hazardous where steep slopes could lead to severe flash floods. Velocity ofwater increases with increasing slopes, this means time required for water decrease.So hazard increases with increasing slope.

Flow Length (Lo)The flow length is the distance from any point in the watershed to the watershed outlet. Lo = ½ D. D is the Density. Lo= 0.89.

Drainage PatternThe drainage pattern in the study area exhibits dendritic to sub dendritic in nature ,The most common form, It develops in regions underlain byhomogeneous material (the subsurface geology has a similar resistance to weathering so there is no apparent control over the direction the tributariestake).

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The stream frequency (Fs)Stream frequency (Fs) is the total number of stream segments of all orders per unit area (Horton 1932). Reddy et al. (2004)) statedthat low values of stream frequency (Fs) indicate presence of a permeable subsurface material and low relief. The channelsegment numbers for unit areas are difficult to be enumerated (Singh 1980). Fs mainly depend on the lithology of the basin andthe texture of the drainage network. The stream frequency value of the W.dahdah basin is 1.51 km/ km2. The low streamfrequencies value indicates sparse drainage network favoring groundwater recharge. Stream frequency mainly depends on thelithology of the basin and reflects the texture of the drainage network. The value of stream frequency (Fs) for the basin exhibitspositive correlation with the drainage density value of the area indicating the increase in stream population with respect toincrease in drainage density. Channel frequency density serves as a tool in establishing the erosional processes operating over anarea; to be more specific, the same in relation to the stream orders and their characteristics provides data which can throw lighteven on the sequences of relief developments and the degree of ruggedness in the area (Singh 1980).

Drainage Density (D)Drainage density (Dd) is a measure the total stream length in a given basin to the total area of the basin (Strahler 1964). Thedrainage density is affected by the factors that control characteristic length of the watershed. Drainage density is related tovarious features of landscape dissection such as valley density, channel head source area, relief, climate and vegetation (Moglenet al. 1998), soil and rock properties (Kelson and Wells 1989) and landscape evolution processes. The significances of D as afactor determining the time of travel by water in a terrain and it also suggests that the D value vary between 0.55 and 2.09km/km2 in a humid region with an average of 1.03 km/km2. (W.B. Langbein, 1947), The drainage density of the W.dahdah basinis 1.79 km/km2, which indicates that basin area has a highly resistant permeable subsurface material with intermediate drainageand low to moderate relief. Higher drainage density is associated with the basin of weak and impermeable subsurface material,sparse vegetation and high relief. Low drainage density leads to coarse drainage texture while high drainage density leads to finedrainage texture, high runoff and erosion potential of the basin area. (Strahler 1964).

Waterflow NetworkThe main streams flow directions of W.dahdah basin takeNorth East South West direction which feeding the mainstream channel, and about 30% the rest directed from thewest bank of the main stream as shown.

Interpretation of Sf and DDThese low values of drainage density, stream frequency and drainage intensity also imply that surface runoff is not quicklyremoved from the basin, making it susceptible to flooding, gully erosion and landslides, particularly in the lower part of the basin.It is therefore recommended that human activities that could impact negatively on stream network in the basin should bediscouraged.Drainage Texture (T)Drainage texture is the total number of stream segments of all orders per perimeter of that area (R.E. Horton,1945). The drainage texture dependsupon a number of natural factors such as rainfall, vegetation, climate, rock and soil type, infiltration capacity, relief and stage of development (K.G.Smith,1950). The drainage texture is classified into five class such as very coarse (<2), coarse (2-4), moderate (4-6), fine (6-8), very fine (>8). The basinhas a drainage texture of 2.89 which indicates the moderate drainage texture. Similarly, the moderate drainage texture and medium value of drainagedensity indicates the presence of moderately resistant semi-permeable material with moderate relief.

Relief ®Basin relief is the difference in elevation between the highest and lowest points in the basin. It controls the stream gradient andtherefore influences flood patterns and the amount of sediment that can be transported. Hadley and Schumm (1961) showedthat sediment load increases exponentially with basin relief. The high relief value indicates high gravity of water flow, lowpermeable and high runoff conditions. The highest point of the studied basin is 961 and the lowest point is 288 meters abovesea level (ASL). Thus the basin relief interval for the studied area is 673 meters.

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19°3'0"N

19°0'0"N

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Terrain Surface Texture

LegendStream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

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0 0.450.9 1.8 2.7 3.6

Kilometers

Value

High : 5.2

Low : 0

41°52'30"E

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Stream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Pour point

Watershed

Drainage Network Flow

Legend

0 0.450.9 1.8 2.7 3.6

Kilometers

Flow Direction

Drainage Point

ConclusionThe morphometric parameters is an immense tools used inevaluating river basin and the watershed preference for soil,conservation of water and resource management at micro level. Theanalysis carried out for the W.dahdah catchment basin depicts thatthe basin is tending towards elongated shape. The morphometricanalysis is of great importance in hydrological behavior of basin forwater quality project, engineering works, public policies applicationsand flood forecasting, erosion control and environmentalmanagement, it is also essential for accurate modeling analysis.

The Evaluation of Flash Flood HazardEstimation of flooding and feeding probabilities for drainage sub-basins within the present area were studied according to EI-Shamy'smethod (1992a) established two relation graphs to classify the riskbasins assessment based on the relations between weighted meanbifurcation ratio and both of the drainage density and the drainagefrequency. The location of any basin on the two relations designatesits runoff/infiltration potentiality.The most affecting factor in risk calculation is the density andfrequency of drainage segments. Increasing both density andfrequency lead to increasing total runoff and total infiltration. Sohazard is directly proportional to density and frequency.According to these parameters, the sub-basins in the study area canbe classified into three classes. Class A: Basins of high Rb and low Fand D may represent ideal areas for feeding the pervious units withthe least chance for flash flooding; which may reflect appropriategeologic and geomorphologic setting with good chances ofdownward recharge to the existing shallow aquifers that may formimportant water resource in remote areas.

0 1 2 3 4 5 6 7

1

10

B C

A

Frequency

Fre

qu

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mRb

Basin

Rb: mBifurcation ratio,

F: Stream frequency,

A: Low flood possibilities,

B: High flood possibilities, C: Intermediate flood possibilities

0 1 2 3 4 5 6 7

1

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A

Frequency

De

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mRb

Basin

mRb: Mean Bifurcation ratio,

D: Stream density,

A: Low flood possibilities,

B: High flood possibilities, C: Intermediate flood possibilities

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41°52'30"E

41°51'0"E 41°54'0"E

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0 0.75 1.5 3Kilometers

TM B ands

RGB

Red: Layer 4

Green: Layer 3

Blue: Layer 2

Legend

Dam Site

Watershed

TM Landsat 8 Natural Color Interpreting The Landsat TM Color CompositesTo create a true color composite, the three visible bands available on Landsat are coupled with the primary colors in thecomputer monitor (R = visible red, G = visible green, and B = visible blue). Other names for this composite are normalor natural color. This composite image will have similar color to true or normal color aerial photos and the wayhumans see color. Healthy vegetation is green, dark brownish-blue is Hills of basement rocks, Brown to light brown clayand sediments, gray line is a railroad, green scattered spots are vegetation, dark gray network is a drainage pattern andsmall white scattered areas are Urban. In TM False color 7.6.4 Vegetation types are variations of green ; urban featuresand bare field are light grey. Infrared composite image This composite simulates the color of a color infrared aerialphoto and can be interpreted using the same logic. Vegetation types are variations of magenta.

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Landsat 8 TM False Color

Urban

Legend

!. Dam Site

Watershed

0 0.75 1.5 3Kilometers

TM Bands

RGB

Red: Layer 7

Green: Layer 6

Blue: Layer 4

Urban Areas

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TM Bands

RGB

Red: Layer 5

Green: Layer 4

Blue: Layer 3

Color Infrared (vegetation)

0 0.75 1.5 3Kilometers

Legend

!. Dam Site

Watershed

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Value

Normalized Difference

Vegetation Index (NDVI)

0 0.75 1.5 3Kilometers

Legend

!. Dam Site

Watershed

High : 0.700028

Low : -0.0739723

Normalized difference vegetation index – NDVINormalized Difference Vegetation Index (NDVI) was employed as the basis forLand Use / Land Cover classification. Interpretation: NDVI values varydepending on the radiation absorption by chlorophyll in the red spectralreflectance in the near infrared region. These values are between -1 and +1,expressing consistency of green vegetation. The closer to 1 (light colors) is ahigh consistency of specific vegetation and hardwood. Values close to -1 (darktones) are barren land, with soil, or rock to date. A value of 0 (midtones) isassociated lands meadows. It is useful in areas with vegetation mapping,vegetation typology, health of vegetation, land use patterns. It is given by: NDVI= ( NIR R )/( NIR + R ) = ( B5 B4 ) / ( B5 + B4 ) Research Journal of AgriculturalScience, 45 (4), 2013

Unsupervised classification provides more comprehensive information onthe spectral characteristics of the area, presents spectrally pure clusters forthe labelling step, and gives the opportunity to the analyst to group similarclusters into a smaller number of land cover classes, (Hansen et al., 2000).The Basin has been classified for land use/land cover into six classes asshown.

LULC mapping!.

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Land Use / Land CoverUnsupervised Classification

0 0.75 1.5 3Kilometers

Legend

Dam Site

Watershed

Stream Order 1

Stream Order 2

Stream Order 3

Stream Order 4

Railroad

!.

11 Residential

24 Other agricultural land

62 Nonforested wetland

73 Sandy areas other than beaches

74 Bare exposed rock

77 Mixed barren land

Value

Residential16%

Other agricultural

land16%

Nonforested wetland22%

Sandy areas other than beaches15%

Bare exposed rock11%

Mixed barren land20%

Area km

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Rainfall is a crucial agro climatological factor. It is important to analyze therainfall data for estimating the probability of flash flooding and its durationfrequency, in addition for cropping and agriculture. Rainfall intensities ofvarious frequencies and durations are the basic inputs in hydrologic design,and they are the main effective factor on flood formation. They are used, forexample, in the design of storm sewers, culverts and many other structuresas well as inputs to rainfall-runoff models. Precipitation frequency analysis isused to estimate rainfall depth at a point for a specified exceedanceprobability and duration.

In poorly gauged regions, rainfall data are often short or even absent. Theavailability rainfall data are collected from the nearest metrological station(Khosh Area). Which the annual rain over the area for a period extendingfrom 1966 to 2011.

Frequency Analysis of the Maximum Annual Daily Rainfall

Six methods of frequency distribution widely used in metrological analysishave been used to represent The maximum annual series.To choose between distributions, the visual fitting comparison, althoughnecessary, is highly subjective and misleading. To overcome this subjectivity,several methods are available for the choice between distributions. One canuse the moment ratio diagrams whether the ordinary or the linear moments.Another methodology is the one proposed by El-Adlouni et al.

Rainfall Data Analysis

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Khosh Metrological

Station Location

0 0.75 1.5 3Kilometers

Legend!. Dam Site

Watershed

Khosh Metrological Station

0

10

20

30

40

50

60

70

80

90

19

66

19

71

19

73

19

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Annual Rainfall data record

Basic statisticsNumber of observations 43Minimum 6Maximum 85Mean 33.3Standard deviation 16.7Median 30.1Coefficient of variation (Cv) 0.501Skewness coefficient (Cs) 0.986Kurtosis coefficient (Ck) 4.29

To choose between tested distributions, the AkaikeInformation Criterion (AIC) ([1] and [2]) and BayesianInformation Criterion (BIC) [3] can be used. Both criteriaare based on the deviation between the fitteddistribution and the empirical probability with apenalization that is function of the number of parametersof the distribution and the sample size. The distributionhaving the smallest BIC and AIC is the one that best fitsthe data. The Gumble distribution has shown to be thestrongest fitting distribution as shown in the table.

W.dahdah BasinNumber of observations: 43Return period : T= 100Model Nb param. XT P(Mi) P(Mi | x) BIC AICGumbel(Maximm Likelihood) 2 88.262 16.67 59.47 365.253 361.730Lognormal (Maximum Likelihood) 2 106.183 16.67 14.94 368.015 364.493Pearson type 3 (Maximum Likelihood) 3 82.715 16.67 11.52 368.536 363.253Log-Pearson type 3 =310) 82.618 16.67 10.10 368.799 363.515Normal (Maximum Likelihood) 2 72.167 16.67 3.93 370.688 367.165Exponential (Maximum Likelihood) 2 134.086 16.67 0.04 379.953 376.431P(Mi) : A priori probabilityP(Mi | x) : A posteriori probability (Method of Schwartz) BIC : Bayesian information criterionAIC : Akaike information criterion

[1] H. Akaike, “Information Theory and Extension of the Maximum Likelihood Principle,” In: B. N. Petrov and F. Csaki, Eds., 2nd

International Symposium on Information Theory, Akadémiai Kiado, Budapest, 1973, pp. 267-281.

[2] H. Akaike, “Markovian Representation of Stochastic Pro- cesses and Its Application to the Analysis of Autore- gressive Moving Average

Processes,” Annals of the Insti- tute of Statistical Mathematics, Vol. 26, 1974, pp. 363- 387. doi:10.1007/BF02479833

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The purpose of fitting data to statistical distributions is to be able to estimate the probabilityof extreme precipitation intensities for a given return period (T). Firstly, the maximumamount of precipitation for a given storm duration is calculated (Pt), and is then convertedinto an intensity (commonly with units of mm/hour). This intensity value is needed for manydesign calculations, most commonly for determining peak flow or peak runoff. Theestimated return values are needed to construct Intensity Duration Frequency curves (IDFcurves), which are widely used in engineering applications. These curves show therelationship between the intensity of the precipitation and the duration of the storm for agiven return period. The IDF curves are developed for a specific location, with a specificreturn period.

Intensity-Duration-Frequency (IDF) Curves

Return period Rainfall (mm) Standard deviation (mm) Confidence interval (95%) (mm)

200 97.7 9.62 78.9 - 117

100 88.3 8.51 71.6 - 105

50 78.8 7.39 64.3 - 93.3

20 66.1 5.93 54.4 - 77.7

10 56.3 4.84 46.8 - 65.8

5 46 3.76 38.7 - 53.4

3 37.9 2.99 32.1 - 43.8

2 30.6 2.43 25.8 - 35.4

Frequency analysis results for the Gumble distribution.

Storm Durations

Determining precipitation intensities for various storm lengths is an important aspect forsafely designing structures and infrastructure to manage flooding. Often short stormdurations are desired as they can give high intensities (mm/hr). A theoretical ratio of 1.13 to1.14 is adopted to transform the daily rainfall values and 24-hr values [4]. In the absence ofshort duration records or any similar information, sub-daily rainfall duration ratios could beassumed between rainfall intensities of 24-hr and those of the 12-, 6-, 3-, 2-, 1-hr, 30-, 15-,and 5-min ratios.

(XTxB)XT = 1.14 (HYFRAN XT)

B = Bell Ratio as per below tableIt is well known that ratios for durations from 2 hours to 5 minutes are fairly constant in different climates because of the similarity of convective storms patterns [5,6].

(I)= (XT * B) / (T / 60)WhereI = Rain Fall Intensity (mm/hr)XT = 1.14 (HYFRAN XT)B = Bell Ratio as per below tableT = Duration (min).

After constructing the IDF Curve then the estimation of rainfall depth values from the belowequation.

D = (I*T)/60WhereD = Rain Fall Depth (mm)I = Rain Fall Intensity (mm/hr)T = Duration (min)

Storm Duration (min) 5 10 15 20 30 60 120 180 360 720 1440

0.139 0.2 0.239 0.279 0.343 0.435 0.565 0.626 0.75 0.877 1

0

20

40

60

80

100

120

140

160

5 10 15 20 30 60 120 180 360 720 1440

100y 147.28 105.96 84.415 73.907 60.574 43.5 28.25 18.425 11.038 6.4533 3.6792

50y 131.44 94.56 75.333 65.956 54.057 34.278 22.261 16.443 9.85 5.759 3.2833

20y 110.25 79.32 63.192 55.326 45.345 28.754 18.673 13.793 8.2625 4.8308 2.7542

10y 93.908 67.56 53.823 47.123 38.622 24.491 15.905 11.748 7.0375 4.1146 2.3458

5y 76.728 55.2 43.976 38.502 31.556 20.01 12.995 9.5987 5.75 3.3618 1.9167

3y 63.217 45.48 36.232 31.722 25.999 16.487 10.707 7.9085 4.7375 2.7699 1.5792

2y 51.041 36.72 29.254 25.612 20.992 13.311 8.6445 6.3852 3.825 2.2364 1.275

Inte

nsi

ty (

mm

/hr)

Duration (min)

Intensity-Duration Frequency Curve

100y 50y 20y 10y 5y 3y 2y

Ret

urn

Per

iod

(Yea

r)

Distribution 100 12.2737 17.66 21.1037 24.6357 30.2869 43.5 56.5 55.2758 66.225 77.4391 88.3

50 10.9532 15.76 18.8332 21.9852 27.0284 34.278 44.522 49.3288 59.1 69.1076 78.8

20 9.1879 13.22 15.7979 18.4419 22.6723 28.7535 37.3465 41.3786 49.575 57.9697 66.1

10 7.8257 11.26 13.4557 15.7077 19.3109 24.4905 31.8095 35.2438 42.225 49.3751 56.3

5 6.394 9.2 10.994 12.834 15.778 20.01 25.99 28.796 34.5 40.342 46

3 5.2681 7.58 9.0581 10.5741 12.9997 16.4865 21.4135 23.7254 28.425 33.2383 37.9

2 4.2534 6.12 7.3134 8.5374 10.4958 13.311 17.289 19.1556 22.95 26.8362 30.6

[3] G. Schwarz, “Estimating the Dimension of a Model,” The Annals of Statistics, Vol. 6, No. 2, 1978, pp. 461-464. doi:10.1214/aos/1176344136

D. M. Hershfield, “Rainfall Frequency Atlas of the United States for Durations from 30 Minutes to 24 Hours and Return Periods from 1 to

100 Years,” Weather Bureau Technical Paper, No. 40, 1961, p. 115.[4]

F. C. Bell, “Generalized Rainfall-Duration-Frequency Re- lationship,” Journal of Hydraulic

Division, Vol. 95, No. 1, 1969, pp. 311-327. [5]

[6] Soil Conservation Service, “Urban Hydrology for Small Watersheds, Technical Release 55,”

United States Depart- ment of Agriculture, Washington DC, 1986.

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Hydrological Analysis and Mathematical Modeling Using WMS

A computer program called the Watershed Modeling System (WMS) is available tohydraulic engineers to automatically delineate drainage basins and determine nearly all ofthe key parameters necessary to computer a peak flow or hydrograph. By Using the DigitalElevation Model (DEM) In addition, land use and soil type maps makes it possible todevelop the supporting data for virtually all industry standard hydrologic models.These data can be directly transferred to WMS where the hydrologic computations areperformed and the results analyzed.

There are two primary classes of hydrologic simulation models: statistical and deterministic.Statistical models use an analysis of historical records such as stream flow or precipitation toinfer design values for different return periods (e.g. 10 year or 100 year). A deterministicmodel on the other hand uses a series of input parameters such as rainfall depth, watershedinfiltration parameters and unit hydrographs to determine runoff from physical processes.The SCS methodologies will be used here to illustrate the kinds of hydrologic parameterstypically required of deterministic models. Some of these parameters include rainfall depth(and an included temporal distribution), losses from a runoff coefficient or CN value, and atime of concentration or lag time used in conjunction with a unit hydrograph.

Land use

Soil

DEM

Runoff Curve Number Report for Basin W.dahdah

HSG Land Use Description CN Area Productkm^2 CN x A

D Other Agricultural Land 86 7.679 660.354D Residential 86 4.448 382.561D Mixed Barren Land 94 2.473 232.497D Bare Exposed Rock 98 10.447 1023.829D Nonforested Wetland 78 3.378 263.470D Sandy Areas other than Beaches 88 0.849 74.718B Residential 72 12.588 906.362B Nonforested Wetland 58 19.584 1135.869B Other Agricultural Land 74 8.786 650.165B Sandy Areas other than Beaches 77 15.006 1155.490B Bare Exposed Rock 98 0.664 65.120B Mixed Barren Land 86 18.993 1633.423

CN (Weighted) = Total Product \ Total Area==========================================

78.0181

Database Processing for SCS Curve Number.

[1] The curve number method was developed by the USDA Natural Resources Conservation Service, which wasformerly called the Soil Conservation Service or SCS the number is still popularly known as a "SCS runoff curvenumber" in the literature. The runoff curve number was developed from an empirical analysis of runoff from smallcatchments and hillslope plots monitored by the USDA. It is widely used and is an efficient method for determining theapproximate amount of direct runoff from a rainfall event in a particular area.The runoff curve number is based on the area's hydrologic soil group, land use, treatment and hydrologic condition.References, such as from USDA [1] indicate the runoff curve numbers for characteristic land cover descriptions and ahydrologic soil group. CN has a range from 30 to 100; lower numbers indicate low runoff potential while largernumbers are for increasing runoff potential. The lower the curve number, the more permeable the soil is. As can beseen in the curve number equation, runoff cannot begin until the initial abstraction has been met. It is important tonote that the curve number methodology is an event-based calculation, and should not be used for a single annualrainfall value, as this will incorrectly miss the effects of antecedent moisture and the necessity of an initial abstractionthreshold.

[1] United States Department of Agriculture (1986). Urban hydrology for small watersheds (PDF). Technical Release 55 (TR-55) (Second ed.). Natural Resources Conservation Service, Conservation Engineering Division.

Using Arc-map for mapping the land use of the basin generated from the unsupervised classification method ofLandsat 8 image according to a GIS table of Anderson land use codes was used along with the hydrologic soil groupfor the map unit, then importing and mapped in WMS for automatically computing the CN for the Basin.

Computation Travel Time, Lag time and Time of Concentration.

Rain clouds

Cloud formation

Precipitation

Evaporation

Ocean

Ground water

Rock

Deep percolation

SoilPercolation

Infiltration

Travel time (Tt) is the time it takes water to travel from one location to another. Travel time between two points is

determined using the following relationship: [2] Tt= l/3600Vwhere: Tt = travel time, hl= distance between the two points under consideration, ftV = average velocity of flow between the two points, ft/s3,600 = conversion factor, s to hThe Travel Time automatically computed in WMS for the basin equals 3.530 hrs.Lag time and Time of Concentration. Lag time and time of concentration are variables often used when computingsurface runoff using unit hydrograph methods available in the hydrologic models supported in WMS. These variablesindicate the response time at the outlet of a watershed for a rainfall event, and are primarily a function of the geometryof the watershed. WMS provides two powerful methods of computing travel times for lag time and time ofconcentration from the geometric data being used for basin delineation and parameter estimation.Lag Time ComputationLag is the delay between the time runoff from a rainfall event over a watershed begins until runoff reaches itsmaximum peak.

BASIN W.dahdah AREA 104.897 km^2Equations: SCS Method

Lag Time L^0.8 * ((((1000/CN)-10) + 1)^0.7)/(1900*sqrt(Y)) = 5.896 hrsVariables:L Watershed length 78153.3 ftCN SCS curve number 78.0181 Y Watershed slope in percent 9.76906 %

Time of Concentration (Tc) Time of concentration is the time required for runoff to travel from the hydraulically most distant point in thewatershed to the outlet. The hydraulically most distant point is the point with the longest travel time to thewatershed outlet, and not necessarily the point with the longest flow distance to the outlet. Time ofconcentration is generally applied only to surface runoff and may be computed using many different methods.Time of concentration will vary depending upon slope and character of the watershed and the flow path. [2]

Equations: Kirpich Method for overland flow on bare earthTime of Concentration m * 0.00013 * (L^0.77/S^0.385) = 3.47613 hrsVariables:m Earth type coefficient 1 L Length of overland flow 78153.3 ftS average overland slope 0.0193552

Conceptual watershed illustrating

travel time from the centroid (gray dot)

of each band of area to the watershed

outlet (National Engineering Handbook2010)

[2] National Engineering Handbook 2010 Chapter 15 Part 630.

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HEC-1 Hydrologic Simulation Model

[3] Hydrological simulation includes study of the return period estimation of rainfall of given precipitation, i.e. the 100 year storm or the100 year flood, 50 year, 30 ..3years etc. 100 year flood, 50 year storm, or 200 year flood, as a description of the magnitude of a storm orflood. We understand that the larger the number before 'year flood', the greater will be the effect on river levels and on anything out onthe river's flood plain. Return Period (T) - The average length of time in years for an event (e.g. flood or river level) of given magnitude tobe equaled or exceeded. The design storm was often developed from frequency-duration-intensity curves based on rainfall records. Earlydiscussed in Part V and estimated for the basin.The HEC series of software is produced by the U.S. Army Corps of Engineers Hydrologic Engineering Center. Keeping the Curve Numberand the time of concentration constant, 7 different design storms were run in the model.

[3] written by: Harlan Bengtson • edited by: Lamar Stonecypher • updated: 10/18/2013

Unite Time (min) Distribution (100y) Distribution (50y) Distribution (20y) Distribution (10y) Distribution (5y) Distribution (3y) Distribution (2y)5 12.2737 10.9532 9.18 7.82 6.39 5.26 4.25

10 17.66 15.76 13.22 11.26 9.2 7.58 6.1215 21.1037 18.83 15.79 13.45 11 9.05 7.3120 24.6357 21.98 18.44 15.7 12.83 10.57 8.5430 30.2869 27.02 22.67 19.31 15.77 12.99 10.4960 43.5 34.27 28.75 24.49 20.01 16.48 13.31

120 56.5 44.52 37.34 31.8 25.99 21.41 17.28180 55.2758 49.32 41.37 35.24 28.79 23.72 19.15360 66.225 59.16 49.57 42.22 34.5 28.42 22.95720 77.4391 69.1 57.96 49.37 40.34 33.23 26.83

1440 88.3 78.8 66.1 56.3 46 37.9 30.6

WMS result

Parameters &

HEC-1 Hydrographs

A range of curve numbers were run in HEC1 using a 7 Return distributiondesign storm of 24 hour duration. The following hydrographs resulted. Thehigher curve numbers result in a larger amount of runoff and therefore ahigher peak flow and flow volume.

The Analysis of Hydrograph curves, indicated that the food volume through 2-

100 year Return Duration range from 3968844.3 m3 to 310951.9 m3 while

the peak flow of flood ranges from 234.31 Cms to 18.43 Cms.

[4] This type of hydrograph is known as a storm or flood hydrograph and it isgenerally drawn with two vertical axes. One is used to plot a line graphshowing the discharge of a river in cumecs (cubic meters per second) at agiven point over a period of time. The second is used to plot a bar graph ofthe rainfall event which precedes the changes in discharge.The scale on the horizontal axis is usually in hours/days and this allows boththe rain event to be recorded and the subsequent changes in river dischargeto be plotted. The shape of the hydrograph varies according to a number ofcontrolling factors in the drainage basin but it will generally include thefollowing features.

The base flow of the river represents the normal day to day discharge of the riverand is the consequence of groundwater seeping into the river channel. The risinglimb of the hydrograph represents the rapid increase in resulting from rainfallcausing surface runoff and then later through flow. Peak discharge occurs when theriver reaches its highest level. The time difference between the peak of the rainevent and the peak discharge is known as the lag time or basin lag. The falling limb(or recession limb as it is sometimes known) is when discharge decreases and theriver s level falls. It has a gentler gradient than the rising limb as most overland flowhas now been discharged and it is mainly through flow which is making up the riverwater. A number of factors (known as drainage basin controls) influence the way inwhich a river responds to precipitation and have an effect on the shape of thehydrograph. The size, shape and relief of the basin are important controls. Watertakes longer to reach the trunk stream in a large, round basin than in does in asmall, narrow one. Where gradients are steep, water runs off faster, reaches theriver more quickly and causes a steep rising limb. Prolonged heavy rain causesmore overland flow than light drizzly rain. Areas of permeable rocks and soil allowmore infiltration and so less surface run off. The way in which the land is used willalso have an influence on the hydrograph vegetation intercepts precipitation andallows evaporation to take place directly into the atmosphere so reducing theamount of water available for overland flow while the large number ofimpermeable surfaces in urban areas encourages run off into gutters and drainscarrying water quickly to the nearest river.

Hydrograph interpretation

[4] http://www.bbc.co.uk/scotland/education/int/geog/rivers/hydrographs/

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Type of catchment soil Value of CRocky and impermeable soil 1-0.8

Slightly permeable , bare soil 0.8-0.6Cultivated soil covered with vegetation 0.6-0.4

Cultivated absorbent soil 0.4-0.3Sandy soil 0.3-0.2

Heavy forest 0.2-0.1

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Flo

w (

cm

s)

Time

HEC-HMS Simulation Model of W.dahdah Basin

flow 100yDR (M3/S) flow 50yDR (M3/S) flow 20yDR (M3/S)

flow 10yDR (M3/S) flow 5yDR (M3/S) flow 2yDR (M3/S)

Duration Return Peak Discharge (M3/S) Volume (mm) Duration Return Peak Discharge (M3/S) Volume (mm)

100yDR 229.6 36.96 10yDR 94.9 15.350yDR 186.6 30.03 5yDR 59.5 9.5520yDR 132.8 21.36 2yDR 18.5 2.97

HEC-HMS Hydrologic Simulation Model

The Hydrologic Modeling System (HEC-HMS) is designed to simulate the complete hydrologic processes of dendritic watershed systems.The software includes many traditional hydrologic analysis procedures such as event infiltration, unit hydrographs, and hydrologicrouting. Geometric attributes such as areas, lengths, and slopes are computed automatically from the digital watershed. Parameters suchas loss rates, base flow, unit hydrograph method, and routing data are entered through a series of interactive dialog boxes. Once theparameters needed to define an HMS model have been entered, an input file with the proper format for HMS can be writtenautomatically.The results and hydrographs obtained by using Hyetograph precipitation method.

Computed Results at W.dahdah BasinPeak Discharge: 229.6 (M3/S) Precipitation Volume: 88.30 (MM) Direct Runoff Volume: 36.96 (MM)Loss Volume: 50.67 (MM) Baseflow Volume: 0.00 (MM)Excess Volume: 37.63 (MM) Discharge Volume: 36.96 (MM)

Subbasin – Used for rainfall-runoff computation on a watershed.

Junction – Used to combine flows from upstream reaches and sub-basins.

Watershed Modeling By Rational Method

The Rational Method is one of the simplest and best known methods routinely applied in urban hydrology. Peak flowsare computed from the simple equation:Q = kCiAwhere:Q - Peak flowk - Conversion factorC - Runoff coefficienti - Rainfall intensityA - Area

Runoff coefficient for different soil types-Richard 1988

1- Rainfall Intensity (i) and Basin Peak Flows

As part of the WMS interface to the Rational Method, you can compute IDF curves using either HYDRO-35, NOAA, or userdefined data. By Using the estimated IDF curve early in Part V resulted from the rainfall frequency analysis.

Time min./y 100y 50y 20y 10y 5y 2y5 147.2844 131.4384 110.2548 93.9084 76.728 51.0408

10 105.96 94.56 79.32 67.56 55.2 36.7215 84.4148 75.3328 63.1916 53.8228 43.976 29.253630 60.5738 54.0568 45.3446 38.6218 31.556 20.991660 43.5 34.278 28.7535 24.4905 20.01 13.311

18.66 12.084 10.155 8.639 7.011 4.695 Intensity

As the data entry for each basin is completed, a peak flow (Q) is computed and listed in theFlowrate (Q) row. The Rational Method equation does not produce a hydrograph. However,one of several unit-dimensionless hydrographs can be used to distribute the peak flow throughtime to create a runoff hydrograph. The resulted Flowrate (Q) = 8286.348 cfs. = 234.64 cms.Flow Velocity (V) = Q/A = 2.23 m/s.

2- Rational Method Traditional Basin Hydrograph

Application Of Mathematical Model hydrology:Specialized the application of the model to follow the movement of flood waters from the different drainagebasins, Where the study take the link between the results of geological, morphological and metrologicalanalyzes to gain access to high-accuracy calculations in flood water volumes , flow rates and the time of runoffinto force and the time of arrival the floods to the maximum value at return period. These studies useful forpropose the necessary actions for the protection of industrial design hydraulically, structurally and determinethe extent of efficiency to face the flood water. Accordingly upon has been selected a advanced hydrologicalprograms which model (WMS). Where this model helps to checking account hydrograph curve in multipleways according to drainage basins easy and complex, with natural or artificial methods through theapplication of HEC-HMS program and HEC-I .

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0 50 100 150 200 250292

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River = W.dahdah Reach = Main RS = 99 BR

Station (m)

Ele

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Legend

EG 100y

WS 100y

Crit 100y

0.0 m/s

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1.0 m/s

Ground

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.03

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The profile displays the water surface level ovar W .dahdah from the outlet

Main Channel Distance (m )

Ele

vatio

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Legend

EG 100y

WS 100y

Crit 100y

Ground

W.dahdah Main

0 50 100 150 200

0.6

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Main Channel Distance (m)

Vel

Left

(m/s

), V

el C

hnl (

m/s

), V

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ight (m

/s)

Legend

Vel Chnl 100y

W.dahdah Main

0 50 100 150 2001.0

1.5

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Main Channel Distance (m)

Hyd

r D

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L (

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h R

(m

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Hydr Depth C 100y

W.dahdah Main

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River = W.dahdah Reach = Main RS = 99 BR

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EG 100y

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Crit 100y

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Floodplain delineation and hydraulic model

Using the RAS Mapping tool to generate both a raster (grid of pixels or "cells")and polygon of the flooding extents, by intersecting the water-surfaceelevations at each cross-section with the digital terrain surface. Post-processingin the form of creating Flood Extent, Flood Depth, and Flood Impact mapsimproves defining the hydraulic model and the determination of the bridge site.

!.

41°52'30"E

41°51'0"E 41°54'0"E

41°49'30"E

19°3'0"N

19°0'0"N

18°58'30"N18°58'30"N

18°57'0"N

Flood depth at the

outlet of Wadi

dahdah

0 0.75 1.5 3Kilometers

Legend!. Outlet

Watershed

Khosh Metrological Station

Geomorphologists define the floodplain as a flat valley flooradjacent a stream or river made by alluvial unconsolidatedsediments transported and deposited by the river and usuallyexperiences flooding when the river floods (Demek, 1988).Hydrologists and engineers define the floodplain as thesurface next to the channel that is inundated once during agiven return period regardless of whether this surface isalluvial or not (Ward, 1978).

Geographical representations of floodplain depths, velocities, and extentsprovide great insight into the model response, and ideally the behavior of thenatural system under analysis.

Floodplain depth gridThe output Flood depth grid of 100y probability flooding period at the outlet of Wadi DahdahBasin represents the water surface elevation level grid (WSEL) Minus the grid representing theground elevation and the floodplain extent. The Flood Coverage divide the flooded area intozones, each with a depth range.Ranges from 0 - 1.15 represent the Flood Stage.Ranges from 1.15 2.3 represent the minor flooding.Ranges from 2.3 3.46 represent moderate flooding.Ranges from 3.46 4.61 represent major flooding.

HEC-RAS Hydraulic Model and Bridge Design

34 Cross-sections were plotted along 172m on the mainstream of Wadi dahdah starting at the outlet with averagedistance 5 m between them. According to the topographicarea and the cross-sections the bridge site was determinedat the station 99 with length 150m to cross the wadi. TheHEC-RAS model included inputting a bridge deck of 15mwidth, and the contraction/expansion coefficients for thebounding cross-sections set to 0.1/0.3, respectively. 6 pierswith 2.5 m width were designed. The 100y Flood durationreturned of 234.8 cms flow rate used to estimate the steadyflow rate and hydraulic design analysis.

Up Stream Bridge Down Stream Bridge

Cross Sections, Profiles and Rating CurvesAfter the model has finished the steady flowcomputations. The output is available in agraphical and tabular format. Graphicaldisplays are often the most effective methodof presenting input data and computedresults. Graphics allow the user to easily spoterrors in the input data, as well as providingan overview of the results in a way thattables of numbers cannot. The profile plotshows that the water surface of 100y flooddistribution return at 297.1m elevation.

The flood severity grid represents the combined effect of depth and velocity, most oftencommunicated in categories of Low, Medium, High, Very High and Extreme Hazard. Studies havebeen performed in multiple countries to categorize the depth x velocity result into various floodhazard or flood severity classifications. Based on studies in Australia and published in the 2006Designing Safer Subdivisions - Guidance on Subdivision Design in Flood Prone Areas(http://www.ses.nsw.gov.au/content/documents/pdf/ resources/Subdivision_Guidelines.pdf)manual, which was derived from earlier work from the New South Wales Floodplain DevelopmentManual (2005).

Flood Severity Category Depth * Velocity Range (m2/sec)

Low < 0.2

Medium 0.2 – 0.5

High 0.5 – 1.5

Very High 1.5 – 2.5

Extreme > 2.50

0.5

1

1.5

2

2.5

0 20 40 60 80 100 120 140 160 180 200

De

pth

* V

elo

city

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m2

/se

c)

Distance

Wadi Dahdah flood severity

Combined Scour Depths =Pier Scour (2.12) + Contraction Scour (m) (0.25): = 2.37 m.Critical Velocity (m/s): 0.74Equation: LiveThe Peak flow rate of 100y Duration Return (Q): 235 cms.The peak water level : 297.1mThe Peak flow velocity inside the bridge: 0.9 m/sThe Bridge top width : 104 m

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Part V

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