Research Article Estimation of Peak Flood Discharge for an ...downloads.hindawi.com/archive/2013/214140.pdf · village Kogram , about km from Burdwan Town on the Burdwan-Katwaroad(Figure

Hindawi Publishing CorporationGeography JournalVolume 2013 Article ID 214140 11 pageshttpdxdoiorg1011552013214140

Research ArticleEstimation of Peak Flood Discharge for an Ungauged RiverA Case Study of the Kunur River West Bengal

Suvendu Roy1 and Biswaranjan Mistri2

1 University of Kalyani Nadia West Bengal 741235 India2The University of Burdwan Burdwan West Bengal 713101 India

Correspondence should be addressed to Suvendu Roy suvenduroy7gmailcom

Received 10 September 2013 Revised 21 October 2013 Accepted 29 October 2013

Academic Editor Achim A Beylich

Copyright copy 2013 S Roy and B MistriThis is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Due to unavailability of sufficient discharge data for many rivers hydrologists have used indirect methods for deriving flooddischarge amount that is application of channel geometry and hydrological models for the estimation of peak discharge in theselected ungauged river basin(s) in their researchproject works This paper has studied the estimation of peak flood discharge ofthe Kunur River Basin amajor tributary of the Ajay River in the lower Gangetic plain To achieve this objective fieldmeasurementsGIS technique and several channel geometry equations are adopted Three important geomorphic based hydrological modelsmdashmanningrsquos equation kinematic wave parameter (KWP) and SCS curve number (CN)methodmdashhave been used for computing peakdischarge during the flood season based on daily rainfall data of September 2000 Peak discharges calculated by different givenmodels are 23944m3s 20408m3s and 14652m3s respectively The hydrograph has demonstrated the sudden increase withheavy rainfall from the 18th to the 22ndof September 2000As a result a havoc flood conditionwas generated in the confluence zoneof Ajay and Kunur Rivers This hydrograph might be not only successful application for flood forecasting but also for managementof the lower Ajay River Basin as well as the downstream area of Kunur Basin

1 Introduction

In India most of the watersheds up to 500 km2 geographicalarea can be categorized as ungauged catchments [1] Majorityof river basins are either sparsely gauged or not gauged at allwhere the lack of hydrological and catchment informationmakes obstruction for watershed planning [2] As per Singet al [1] hydrological response from each catchment assistsin flood routing vis-a-vis in flood modeling and floodforecasting Schumm [3] apprises that water and sedimentdischarge are the principal determinants of the dimensionsof a river channel (width depth meander wavelength andgradient) Physical characteristics of river channels such aswidthdepth ratio sinuosity and pattern (braided meander-ing and straight) are significantly affected by the flow rate andsediment discharge According to Bhatt and Tiwari [2] chan-nel geometry method is an alternative mode of estimatingflood discharge for regional flood frequency analysis Riverbed characteristicsmdashchannel width cross-section area riverbed gradient and bank side slopemdashare crucial parameters foralternative techniques of discharge estimation

In hydrology the term ldquopeak dischargerdquo stands for thehighest concentration of runoff from the basin areaThe con-centrated flow of the basin greatly exaggerated and overtopsthe natural or artificial bank and this might be called flood[4] In this paper local enquiries have played an importantrole to know actual depths of river water during the majorfloods On the contrary the accurate estimation of flood dis-charge remains one of themajor challenges tomany engineersand planners who are involved in project design Hencehydrological data and information are limited [2] In this casegeomorphic parameters have availed to discharge estimationGeomorphic parameters such as channel-pattern meanderwavelengths and palaeochannels dimensions were firstlyused in palaeohydrology by Dury [5 6] and Schumm [3] andwere modified subsequently depending upon the area ofapplication [7ndash11] In theUSA the relationship between flooddischarge and river channel dimensions was initially devel-oped after following the suggestion of Langbeinrsquos [12] researchin Nevada After achievement of studies including Hedmanet al [13 14] Scott and Kunkler [15] Riggs [16] Osterkamp

2 Geography Journal

andHedman [17]Webber andRoberts [18]Omang et al [19]Wahl [20 21] and Lawlor [22] the method was accepted bythe water resource division of the US Geological Survey asan operational technique In the central USA Williams [23]established relationships between bankfull discharge andchannel dimensions with sample data of 36 gauging stationsIn Indian context several researchers [2 24 25] have appliedindirect methodologies for estimation of discharge of severalungauged catchments

Flood is a natural phenomenon in the West Bengal Thestate with a geographical area of 88752 km2 occupies 27of Indiarsquos land and supports 802 (census 2011) of totalIndian population The flood prone area of West Bengal is37660 km2 4243of total geographical area ismore elevatedthan the average of 1217 [26] The downstream areas of 26river basins are frequently flood affected in the rainy seasonin all over theWest Bengal Enormouse flood has occurred inthis region from the end of September till the mid of October[27] The problem of flood is more difficult to control in thisstate because of two major aspects (i) the very small longi-tudinal gradient in general and (ii) the funnel-shaped basin(eg Damodar Ajay Dwarakeswar and Kasai River Basins)with a wide upper catchment and a narrow lower catchmentUnder these circumstances the basins generally have phe-nomenal increase of peak discharge [28 29] With this vul-nerability of West Bengal there is no availability of sufficienthydrological data to predict the nature of flooding behavior ofriver Correspondingly Kunur is also a notable river whichcauses flood in the Mangalkote and its adjoining Blocks ofBarddhaman District [30]

11 Purpose ofThis Research Themajor purpose of this studyis to estimate the peak discharge of the ungauged KunurRiver Basin during heavy flood using indirect methods withchannel geometry There are used numerical models insteadof modern instrument based velocity measurement (currentmeters) due to lack of departmental instrument financeand during flood the whole confluence zone is inundatedcompletely and there is no scope to reach to the outlet of theKunur River to measure the discharge In lean season therewas no flow for both rivers (Ajay and Kunur) and havoc floodcondition is a sudden scenario (mainly in September) foraccumulation of huge monsoonal runoff from upstream areaof these two basins On the basis of water input-output graphof the Kunur River Basin [31] it has been observed that floodcomes during September (Figure 1) Nevertheless Mitra [31]did not estimate the monthly discharge data of Kunur Riverduring floods this work has been an attempt to estimate itThis study also attends to understand regional hydrology forstudy area which provides a concept to design surface waterand flood management project

2 Materials and Method

21 Study Area The Kunur River Basin which covers a geo-graphical area of 92240 km2 is the second largest draininginland basin of north-east ward of Barddhaman District andamajor right bank tributary of theAjayRiver Geographically

0

50

100

150

200

250

300

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

Surplus water

Am

ount

of w

ater

(in

998400 00ha

middotm)

Water balance of Kunur River Basin

Input of water (in 99840000 hamiddotm)Output of water (in 99840000 hamiddotm)

Figure 1 Input-output situation of the Kunur River Basin (source[31])

it is located between 23∘251015840N to 23∘401015840N latitude and 87∘151015840Eto 87∘551015840E longitude and administratively divided into sev-eral police stationsmdashFaridpur Durgapur Kanksa AusgramBudbud Mangalkote and Bhatarmdashin the north-central partof Barddhaman The outlet of this watershed is near to thevillage ldquoKogramrdquo about 38 km from Burdwan Town on theBurdwan-Katwa road (Figure 2) The Kunur River representsa basin of 5th order with a drainage density that is equal to085 kmkm2 and the drainage pattern is more or less den-dritic with elongated shape [32] As per Mitra [31] the up-stream and central part of the Basin has a forest cover inter-spersed with paddy fields along watercourses 1380 of thebasin area is under forest while 5390 is cultivated 2620of the Basin area is not available for the cultivation and 610is culturable waste

Geographically this basin is tropical the Tropic of Cancer(23∘301015840E) is passing over the basin fromWest to EastThe seacoast is located at least 220 km away from the Bay of Bengaland somewhat extreme tropical climate is experienced here[34] The average annual rainfall is 1400mm of which themaximum occurs within the second week of June to Septem-ber

During summer months rainfall nearly exceeds 100mmand it is even over 1500mmduring rainymonths [32] Geohy-drologically the total basin is divided into three types of geo-hydrological characteristics First the upper catchment of theKunur River Basin is covered by hard rock mainly Archaeanformation with high grade metamorphic rocks of granitegneiss commonly referred as ldquoBengal Gneissrdquo Furthermoremiddle portion consists of semiconsolidated formation of theGondwana Sedimentaries and hard lateritic patches Finallythe lower catchment area is mainly un-consolidated with newalluvial of the Ajay and Kunur floodplains [35] As a resultmaximum rainfalls in the upper and middle catchment areaare turned into overland flow due to low infiltration capacityand make huge water pressure in the downstream channel ofthe Kunur River To generate floods in the lower Ajay River

Geography Journal 3

India

West BengalBirbhum

Barddhaman

Kunur River Basin Study area

Barddhaman

Chittranjan

Chakai

Jharkhand

(km)

Katoya

Source Sutapa Roy 2012

Birbhum

Ajay River

0 10 20 30

(a)

Ajay River

Kunur River

NatunhatConfluence Point

(b)

Figure 2 Location map of the study area

Basin discharge of the Kunur River Basin has played veryimportant role to make a devastative form of these floodsKunur River is an important tributary of the Ajay River and33 area of lower Ajay River Basin (Area of Lower AjayRiver Basin is 281625 km2 and 7965 areas are flood affectedentirely or partially [32]) is covered by this basinMukhopad-hyay [32] stated that the lower Ajay River Basin has beensuffering from floods since time immemorial The major

recorded flood years are 1956 1959 1970 1971 1973 19781984 1995 1999 2000 2005 and 2007 Unfortunately there isno availability of hydrological data apart from rainfall data ofthe Kunur Basin Even though there is no gauging station onthe Kunur so that there is a lack of discharge data [31] Figures3(a) and 3(b) have given a clear idea about spatial patternof floods in the lower Ajay River Basin and vulnerabilityof the Kunur River Basin There are several causes behind

4 Geography Journal

Ajay RiverKunur River

0 2 4(km)

1978198419961999

200020042007

Flood affected areasLower Ajay River Basin

during 1978 to 2007

23∘45998400N

23∘30998400N

87∘35998400E 87∘55998400E

(a)

Flood intensity map(Lower Ajay River Basin)Based on 1956 to 2007

flood affected area

0 2 4(km)

Flood intensity map(Lower Ajay River Basin)

y pyBased on 1956 to 2007

j yj yflood affected area

0 2 4(km)

Highly affected area (gt60)Moderately affected area (40ndash60)Least affected area (lt40)

23∘45998400N

23∘30998400N

87∘35998400E 87∘55998400E

(b)

Figure 3 Spatial pattern of floods in the lower Ajay River Basin (source [32])

Ajay

Kunur River

Premonsoon period

Basin boundaryGround water contour (m)

Direction of ground water flowPhreatic divide

0 4 8(km)

50

4035 30

20 15

60 50454035 30

2520

55

A

B

15B998400

A998400

River

(a)

Section showing the ground water surface and profile


Phreatic divide

45

25

65H

eigh

t (m

)H

eigh

t (m

)

Kunur Riverrrrrr

Ajay River Kunur River

45

25

65 Ajay River Kunur River

AA 998400

B B998400

(b)

Figure 4 Subsurface water flow in the confluence zone of the Ajay and Kunur Rivers (source [35])

generating havoc flood in the downstream area of the KunurRiver (i) gradual decreasing channel width of Kunur rivertowards the confluence point [30] (ii) huge sedimentation inthe confluence zone disturbed the longitudinal profileslopeof the Kunur river [30] (iii) effluent condition of Kunur Riverand very good ground water potentiality (150m3hr) [35](Figures 4(a) and 4(b)) (iv) high percentage of cumulativethickness of granular materials (8650 1600 meters within1850 metres bore hole) and high storage coefficient (52 times

10minus4) [35] and (v) topographically depression in the rightbank of the Ajay river [30] All these cause pace overlandflow of the Kunur Basin and high amount of discharge As perSing et al [1] knowledge of peak discharge is essential for safeand economical planning and design of hydraulic structuresTherefore to provide sustainable management of flood pronearea in the lower Ajay River Basin estimation of dischargedata of the Kunur River is extremely required

22 Method The entire research work has carried out withfour steps that is literature survey field measurement

graphical representation and discharge estimation usinghydrological models and their quantitative analysis Severaljournals books reports and thesis have been reviewedcarefully and different hydrological models have been chosenfrom there Among them three important models have beenselected for the estimation of peak discharge of the KunurRiver Basin All three models have been used for their geo-morphic perspective with GIS based calculation In the firstmodelmanning equation is applied for discharge estimationwhich works with in-stream channel geometry and textureof river bed In the Second model used model is KinematicWave Parameter (KWP) model is used in which rainfallintensity an important parameter for runoff generation ofbasin area has been taken into consideration for dischargeestimation Monsoonal rainfall amount is the basic input forgenerating peak discharge and therefore rainfall data for theentire month September (30 days) of the year 2000 was usedhere Year 2000 was a havoc flood year in the flood history ofWest Bengal Lastly SCS curve numbermethodhas beenusedfor deals with land use character and soil hydrology which

Geography Journal 5

Table 1 Calculation of hydraulic radius (119877ℎ) of the study reach

Site Cross-sectionline 119861 119887 119910 119897 119911119910 119860 119875 119877

ℎ

At outlet of Kunur River 119860119861 563m 344m 6m 144m 219m 2721m2 632m 431m

B

b

zy

120572

1

zy

985747

Figure 5 Trapezoidal open channel cross-section (source [41])

are the important factors for making variation of runoff gen-eration Here used rainfall data has been computed by RiverResearch Institute Kolkata at the Illambazar gauge stationwhich is situated in the outside of Kunur Basin But thedistance is only five kilometres from the northern edge of thisbasin (middle part) (Figure 7)

221 Manning Equation and Peak Discharge As per Chow[33] Barnes Jr [36] Benson and Dalrymple [37] Limerinos[38] Jarrett [39] and Summerfield [40] in case of limited fieldmeasurements and data availability for any river Manningrsquosmethod is considered to be an accurate and reliable methodfor river discharge estimation Hydraulic Radius is an impor-tant parameter in themanning equation It is varying with thecross-sectional shapes (rectangular circular semicirculartrapezoidal and triangular) of open channel For calculat-ing it also needs to use different mathematical equations orPythagorasrsquo theorem In the present study channel of theKunur River looks like a trapezoidal shape (Figure 6(a)Table 1) A trapezoidal open channel cross-section is shown inFigure 5 along with the parameters used to specify its size andshapeThose parameters are 119887 the bottomwidth119861 the widthof the liquid surface 119897 the wetted length measured along thesloped side 119910 the liquid depth and 120572 the angle of the slopedside from the vertical

The hydraulic radius for the trapezoidal cross-section isoften expressed in terms of liquid depth bottom width andside slope (119910 119887 and 119911) as followsThe cross-sectional area (119860)of flow = the area of the trapezoid =

119860 =

119910 (119887 + 119861)

2

= (

119910

2

) (119887 + 119861) (1)

The wetted perimeter for trapezoidal cross-section is 119875 = 119887 +

2119897Now hydraulic radius of a trapezoidal cross-section is cal-

culated by the following equation 119877ℎ= 119860119875

The velocity of stream flow is influenced by the gradientroughness and cross-section form of a channel [42] Themanning equation is a more widely applied estimator which

incorporates an index of channel bed roughness [40] TheManning equation (V) defines the mean flow velocity (V) as

V =119896 (11987723

ℎtimes 11990412

)

119899

(2)

where 119896 is a dimensionless constant (=1 in metric units and146 in English units) 119877

ℎis the hydraulic radius (defined as

the cross-section area divided by the wetted perimeter butcommonly approximated by mean channel depth) 119904 is thelongitudinal slope of channel and 119899 is theManning roughnesscoefficient another dimensionless number that defines theflow resistance of a unit of bed surface [43 44]ThisManningroughness coefficient (119899) is usually estimated from table valuesas given by Chow [33] or by comparison with photographsillustrating channels of known roughness [45] (Figure 6(b))The assignment of roughness coefficients calculation in natu-ral channels has been performed by different researchers [3646] comparing cross-sectional area sand river profiles withphotographs of typical river and creek cross-sections or bymeans of empirical equations [47 48] As per Chow [33] thevalue range ofManning roughness coefficient (119899) for the largechannel (widthgt 30m)with regular channel lacking bouldersor vegetation is from 0025 to 0060 Alternatively as perSimons and Richardson [45] if bedform is characterized withdunes it will be in the range of 0018ndash0035 In this river thechannel of both types of characteristics has been observedand thereforeManning roughness coefficient (119899) was taken as0035 for applying inManning equation

222 KinematicWave Parameter (KWP) for FlowVelocity andDischarge Estimation Runoff concentration for any riverbasin is dependent upon two interrelated systems that is thechannel network and the hill slopes The hill slopes controlthe production of stormwater runoff which is treated as peakdischarge when it reached at the basin outlet [49] With con-sidering these two systems Rodriguez-Iturbe et al [50] hadpresented a kinematics wave relation for the estimation offlow velocity with using the flowing equation

119881Ω= 0665120572

06

Ω(119894119903119860)04 120572

Ω=

11987805

Ω

11989911986123

(3)

where 119881Ωis flow velocity (ms) 119894

119903is rain intensity (cmh) 119860

is drainage basin area (km2) 119878Ωis slope of main river in

drainage basin outlet () 119899 is Manningrsquos roughness coeffi-cient and 119861 is mean flow width in outlet of drainage basin(m)

223 Effective Discharge Estimation To estimate the effectivedischarge of any watershed Rodriguez-Iturbe et al [50] hadused geomorphologic model and relations for preparing thisequation

119876119890= 119894119903lowast 119860 (4)

6 Geography Journal

B

b

zy

zyy

985747

(a)

PoolDuneSandy alluvialchannel bed

(b)

Figure 6 (a) Trapezoidal channel cross-section of the Kunur River (b) bed-form characteristic with dunes and pool

where 119876119890is effective discharge 119894

119903is rainfall intensity (cmh)

and 119860 is area of total basin It is treated as the equilibriumdischarge for any basin Therefore this equation is used hereto quantify basic discharge capacity of Kunur River and tomake a comparative analysis with the other three models toquantify their level of efficiency

224 SCS Curve Number Method for Direct Runoff Estima-tion The SCS curve number method is a simple widelyused and efficient method for determining the approximateamount of runoff depth from a rainfall event in a particulararea For drainage basins where no runoff has been mea-sured the curve number method can be used to estimate thedepth of direct runoff from a measured rainfall amount overthe study area The SCS Curve Number Method was origi-nally developed by the Soil Conservation Service [51 52] forthe management of water resource in the United States foragricultural development [33] In this method the followingequation is used to calculate the direct runoff from anyungauged basin

119876 =

(119875 minus 02119878)2

(119875 + 08119878)

(5)

where 119876 is estimated direct runoff (mm) 119875 is maximumstorm rainfall within a day (mm) and 119878 is the potential max-imum retention 119878 can be calculated from CN value by thisequation that is 119878 = (25400CN) minus 254 and CN value can beextracted from the table (see [33 Table 522 pp 150]) valuewith weight index value (Table 4) After calculating the directrunoff or excess runoff from any basin (119876) to estimate thepeak runoff rate (m3s) the following equation should beused [33]

119902119901

= 0208 lowast (

119860 lowast 119876

119879119901

) (6)

where 119860 is area of drainage basin (km2) 119876 is excess rainfall(mm) 119902

119901is peak runoff rate unit hydrograph (m3s) and 119879

119901

is time to peak runoff unit hydrograph (h) In that equationthe only unknown parameter is time to peak (119879

119901) This can

be estimated in terms of time of concentration (119879119888) Relation

between 119879119901and 119879

119888is shown in this equation

119879119901= 07119879

119888 (7)

To compute 119879119888value Kirpich [53] developed this empirical

equation

119879119888= 002119871

077119878minus0385

(8)

where119879119888is time of concentration (min)119871 ismaximum length

of travel (m) and 119878 is slope that is equal to119867119871 where119867 isthe difference in elevation between the most remote point inthe basin and the outlet The parameters to estimate the timeof concentration can be derived from the topographic mapsSo after estimating 119879

119888 we can easily calculate 119879

119901 and conse-

quently the peak runoff rate (119902119901)

225 Models Calibration To determine the level efficiencyof predicted discharge data by indirect methods it is veryimportant to compare them with observed discharged dataof the same river But due to lack of observed discharged dataof Kunur River all three predicted discharged data have beencompared with the estimated effective discharge which istaken as equilibrium discharged volume of the Kunur Basinusing the following methods

Relative Mean Error (RME) Relative mean error relationcould be used to determine the deviation between calculatedpeak discharge and observed peak discharge and the follow-ing equation is used for that

RME =

1

119899

sumRE119894 RE

119894=

[(119876op minus 119876cp) lowast 100]

119876op

(9)

where RE119894is relative error percent for each of events 119876op is

observed peak discharge and 119876cp is calculated peak dis-charge

Root of Mean Square Error (RMSE) Root of mean squareerror relevant to peak discharge is presented by

RMSE = [

1

119899

(sum SE119894)]

12

SE119894= (119876op minus 119876cp)

2

(10)

Geography Journal 7

Table 2 Estimation of bankfull discharge during flood of the Kunur River at the outlet using manning equation

Site Cross-sectionline

Hydraulicradius 119877 (m)

Slope-mm(119878)

Manningroughness

coefficient (119899)

Manningequation (Vms)

Cross-section area(CSA) = 119908 sdot 119889 (m2)

Discharge(119876 = 119908 sdot 119889 sdot V)

m3sAt outlet ofKunur River 119860119861 431 001 0035 088 2721 23944

Table 3 The required parameters for measurement flow velocity from kinematic wave parameter and discharge

Rain intensity(cmh)(119894119903)

Drainage basinarea (km2)

(119860)

Slope of mainriver in drainagebasin outlet ()

(119878Ω)

Manningrsquosroughness


Mean flowwidth in outletof drainagebasin (m) (119861)

Flow velocity (ms)(119881Ω)

119881Ω= 0665120572

06

Ω(119894119903119860)04

120572Ω= 11987805

Ω11989911986123

Cross-sectionarea (CSA) =119908 sdot 119889 (m2)


m3s

00024 92240 019 0035 563 075 27210 20408

Table 4 Compute the weighted curve number (CN) using table value (see Table 552 p150 in [33])

Hydrological soilgroup Major land use and soil characteristics Covering basin

area () CN Product

A Urban area with 50 to 75 impervious land 3 49 147

B Moderate infiltration rate with coarsetexture land pasture and open scrap area 7 79 553

C Low infiltration rate with fine sandy loamdense forest and degraded wood land 55 77 4235

D Fine clay to silt soil with agricultural land 35 72 2520Thus weighted CN = 7455100 = 7455 Σ100 Σ7455

where SE119894is relative error for each of events119876op is Observed

peak discharge and 119876cp is calculated peak dischargeThe field surveys were conducted along river course from

confluence towards upstream six river cross-sections weresurveyed to measure different parameters of channel geom-etry The region has sparse elevations which have been sur-veyed using GPS (Garmin eTrex 30)The river cross-sectionswere surveyed using Autolevel (Sokkia C4

10) with 25mm

standard deviation for one km double run leveling and 100metres tape and 4metres staff are also used for these surveysThe longitudinal slope and hydraulic radius have been cal-culated to determine flow velocity using manningrsquos equationand ASTER data has been also used to get slope factor usingGlobal Mapper v140 software

3 Result and Discussion

31 Calculation of Peak Bankfull Discharge Using ManningEquation To begin this study hydraulic radius has beencalculated based on model for a trapezoidal cross-sectionTable 1 indicates that hydraulic radius of Kunur outlet sectionis 431 metres ThenManningrsquos equation has been applied tocalculate the mean maximum bank discharge of the KunurRiver at its mouth (Figure 2 Table 2) Finally this manningequation based hydrological equation has estimated thatmaximum bank capacity of the Kunur River is 23944m3swhich might be the peak discharge volume of this river

32 Kinematic Wave Parameter (KWP) for Flow Velocity andDischarge Estimation After applying kinematic wave param-eter equation on the Kunur River the result is more likely

similar to the previous estimation Mean flow velocity ofKunur River at the outlet is 075ms and computed dischargeis 20408m3s (Table 3) Effective discharge of Kunur RiverBasin is 17935m3s which is themean equilibrium dischargefor this basin that is used here as observed discharge tocalculate the model wise efficiency

33 SCS Curve Number Method and Peak Discharge Basedon the hydrological soil group the maximum area of Kunurwatershed was observed to be under hydrological soil groupC (55) and followed by 35 of D 7 of B and 3 of groupA Similarly the study area was identified into fivemajor landuse classes namely agricultural land dense to degraded Salforest wasteland settlement and hard surface The majorportion of this watershed is under agricultural land Curvenumber table of the Soil Conservation Service was used todetermine the curve number of thewatershed By intersectingthe land usemap and soilmap the curve numberwas assignedto the each combination of land use and soil type Weightedvalue of CNwas found out to be 7455 for AMC II conditionsThe daily rainfall data for entire month September in the year2000 was collected and the weighted curve number of thewatershed has been used for the estimation of directs runoffThe calculated direct runoffwas found out to be 8873mm formonsoon season (19th September highest one day rainfall160mm) of the year 2000 which is approximately 1730percent of the total rainfall in the entiremonth September and5546 of that day (Table 8)

Now the potential maximum retention (119878) can be eas-ily calculated from the CN value 119878 = (25400CN) minus 254Therefore 119878 = 8671 and 119876 or accumulated runoff depth

8 Geography Journal

Table 5 Calculation of peak runoff using SCS curve number method

Potentialmaximumretention (119878)

Maximum oneday rainfallduring strom

(119875)

Direct runoffor excessrunoff (119876)

Area of thetotal basin (119860)

Time ofconcentration(min) (119879

119888)

Time to peak runoffunit hydrograph (h)

(119879119901)

Peak runoff rateunit hydrograph

(m3s) (119902119901)

8671mm 160mm 8873mm 92240 km2 16598 11618 14652

Table 6 Calculated peak discharge (m3s) from three models in Kunur River Basin

Event timelowastEffective discharge orobserved discharged

data (m3s)

Estimated bymanning equation

model (m3s)

Estimated bykinematic waveparameter (m3s)

Estimated by SCScurve numbermethod (m3s)

19th ofSeptember2000

17935 23944 20408 14652

lowastMaximum one day rainfall 160mm

Table 7 Comparison of study models in drainage basin with indexof relativemean error (RME) and root ofmean square error (RMSE)

Applied models RME RMSEManning equation 3350 6009Kinematic wave parameter 1379 2473SCS curve number 1830 3283

are 8873mm Now the runoff depth value can be used toestimate the peak runoff in cumec After calculation the valueis 14652m3s (Table 5)

As for as the factors of models are concerned these canbe applied and able to estimate discharge amount In thissection instead of results of eachmodel all the predicted datahas been compared with effective discharge data taking asobserved discharge to determine the level of efficiency bet-ween three models (Table 6) Error functions were calculatedto determine precision of each model Functions consideredin this section are relative mean error (RME) and root ofmean square error (RMSE) It is evident from the results thatthe kinematic wave parameter model has the minimum erroramong the study models with RME value of 1379 and RMSEvalue of 2473 (Table 7)

34 Preparation of Monthly Hydrograph for Kunur Riverduring Monsoon Period In general hydrograph of basins isa pictorial representation of water availability with temporalchange It is treated as basic component of river basin man-agement for better irrigation practices dam constructionflood damage control recreation and so forth To prepare themonthly hydrograph of the Kunur River SCS curve numbermethod has been used for its efficiency of runoff estimationSame methodology has been followed here for each day ofthe entire month September (Table 8) which was previouslyapplied to estimate the peak discharge of the Kunur Riverfor only the 19th of September for highest rainfall occurrence(160mm)

This hydrograph represents the relationship betweenrainfall occurrences and runoff generation In the same waybasin area has the correlation value of 093 during September

0

20

40

60

80

100

120

140

160

180

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Rain

fall

(mm

) and

disc

harg

e (cu

mec

)

Days of September 2000

Rainfall (mm)Discharge (cumec)

Figure 7 Monsoonal hydrograph (September) of Kunur RiverBasin

The correlation coefficient 093 indicates a relatively strongrelationship between the rainfall and runoff amounts for theselected episodes at the catchment scale The polynomial1198772 statistic indicates that the model explains 995 of the

variability in the runoff amount The major characteristic ofthis hydrograph is single extreme peak period the end ofSeptember generating highest discharge (14653m3s) withdirect runoff of 5546 rainfall (Figure 7 and Table 8) Thishydrograph peak is developed due to the sudden heavy andcontinuous rainfall during 18th to 22nd of September 2000As a result a havoc flood condition was generated in theconfluence zone of Ajay and Kunur Rivers [27 32] Thishydrograph proved very good application for flood forecast-ing andmanagement in the lower Ajay River Basin during themonsoon period as well as downstream area of Kunur BasinAs per Rudra and Mukhopadhyay [27 32] the lower AjayRiver Basin is frequently affected by havoc flood at the endof September to the mid of October month This hydrographalso proved its comment about flood characteristic of thestudy area

Geography Journal 9

Table 8 Monthly discharge estimation using SCS curve number method of Kunur River Basin

Days(Sep 2000) Rainfalllowast (mm) or 119875 119878 (mm) 119876 (mm) of rainfall 119879

119888119879119901

Discharge in m3s (119902119901)

1 16

8671

002 0125

16598 11618

0032 5 204 408 3373 0 433 7154 0 433 7155 0 433 7156 6 171 285 2827 0 433 7158 0 433 7159 47 756 1609 124810 3 284 9467 46911 0 433 71512 0 433 71513 0 433 71514 9 089 989 14715 5 204 408 33716 0 433 71517 0 433 71518 52 99 1904 163519 160 8873 5546 1465320 136 6856 5041 1132221 44 627 1425 103522 30 161 537 26623 0 433 71524 0 433 71525 0 433 71526 0 433 71527 0 433 71528 0 433 71529 0 433 71530 0 433 715lowastRainfall data computed by River Research Institute Kolkata in 2000

There are several other hydrological models andmethodsof runoff and discharge estimation form ungauged basinsBut in this study these three models have been applied fortheir geomorphic approach and worldwide acceptability fortheir easy and RS-GIS based application Although there aresome errors in these models but the major objective of thisstudy has been fulfilled This study helps to get an approx-imate idea about the hydrological behavior of Kunur Riverduring the heavy rainfall season This research work helps toestimate the maximum channel capacity of the Kunur RiverBasin and may be applicable for other ungauged river basinand also helps to prepares monthly hydrograph for theselected period The major findings of this work is that thisbasin has very good potentiality for water harvesting duringthe rainy seasons and it can reduced the flood probabilityof the month September by developing water bank for

cultivation in the lean season This research paper alsodemonstrates an approach to generate reliable discharge datafor different vulnerable ungauged river basins in sense ofdraught prone and flood prone areas in the developing coun-tries particularly for India where most of the middle andsmall sized watersheds have no discharge data But theseungauged watersheds may have chance to form havoc floodevent and economic losses for the surrounding settlementsOverall these applications obviously provide the benefits forcitations of hydrological information about this basin

4 Conclusion

Across the globe water resources and the water environmentare under threat like never before In this case in river basinseverywhere human activities have disrupted the natural

10 Geography Journal

hydrological and ecological regimes Water supplies are notsecured to billions of people worldwide Flood risk is increas-ing and biodiversity is steadily decreasing due to the ongoingdestruction of riparian ecosystems At that moment predic-tion of actuate amount of water resource for every small andlarge basins is absolutely essential for water planning Predic-tion in ungauged basin (PUB) is one of the recent develop-mental strategies by the International Association of Hydro-logical Sciences (IAHS) for proper hydrological planning inbasin-scale water and resource management The channelgeometry method is a simple and useful alternative methodof estimating flood discharge compared with methods basedupon catchment characteristics Recently application in-stream local level geomorphic study is an important and sig-nificant way for calculating hydrological behaviors of water-shed with least error and costThe study reveals that compar-ative study of alternative hydrological models provides floodestimates which are adequate for the planning and design ofvarious hydraulic structures and for flood frequency analysis

Acknowledgments

The authors would like to thank one of their friends Rat-anpriya Jaiswal Research Scholar of CSRD-JNU for herremarks on the paper writing and would also like to thankSadhan Mallik and Subhankar Bera Ex-Student of The Uni-versity of Burdwan for their contribution during data collec-tion

References

[1] A K Sing S Sharma and U Vakharia ldquoGIS remote sensingand field measurement for estimating hydrological parametersin ungauged catchmentrdquo in Proceedings of the 12th Esri IndiaUser Conference pp 1ndash8 2011

[2] V K Bhatt and A K Tiwari ldquoEstimation of peak streamflowsthrough channel geometryrdquo Hydrological Sciences Journal vol53 no 2 pp 401ndash408 2008

[3] S A Schumm ldquoRiver adjustment to altered hydro-logic regime-Murrumbidgee River and palaeochannels Australiardquo US Geo-logical Survey Professional Paper 598 1968

[4] J R Reddy A Textbook of Hydrology University Science PressNew Delhi India 2010

[5] G H Dury ldquoBed-width and wave-length in meandering val-leysrdquo Nature vol 176 no 4470 pp 31ndash32 1955

[6] G H Dury ldquoDischarge prediction present and former fromchannel dimensionsrdquo Journal of Hydrology vol 30 no 3 pp219ndash245 1976

[7] K J Tinkler ldquoActive valleymeanders in south-central Texas andtheir wider implicationsrdquoGeological Society of America Bulletinvol 82 pp 1783ndash1800 1971

[8] P C Patton and V R Baker ldquoGeomorphic response of centralTexas stream channels to catastrophic rainfall and runoffrdquo inGeomorphology in Arid Regions Proc 8th Binghamton Sympo-sium in Geomorphology 1977 D O Doehring Ed pp 189ndash217Publications inGeomorphology SUNY BinghamtonNYUSA1977

[9] J C Knox ldquoResponses of floods to Holocene climatic change inthe upper Mississippi Valleyrdquo Quaternary Research vol 23 no3 pp 287ndash300 1985

[10] J C Knox ldquoClimatic influence on upper Mississippi Valleyfloodsrdquo in Flood geomorphology V R Baker R C Kochel andP C Patton Eds pp 279ndash300 JohnWiley NewYork NY USA1988

[11] G P Williams ldquoPaleofluvial estimates from dimensions of for-mer channels and meandersrdquo in Flood Geomorphology V RBaker R C Kochel and P C Patton Eds pp 321ndash334 JohnWiley New York NY USA 1988

[12] W B Langbein ldquoHydrologic data networks and methods ofextrapolating or extending available hydrologic networksrdquoFlood Control Series 15 United Nations Economics Commis-sion for the Far East Bangkok Thailand 1960

[13] E R Hedman P O Moore and R K Livingstone ldquoSelectedstreamflow characteristics as related to channel geometry ofperennial streams of Coloradordquo US Geol Survey Open-FileReport (200) H358s 1972

[14] E R Hedman and W R Osterkamp ldquoStreamflow characteris-tics related to channel geometry of streams in western UnitedStatesrdquo US Geological Survey Water-Supply Paper 2193 1982

[15] A G Scott and J L Kunkler ldquoFlood discharges of streams inNew Mexico as related to channel geometryrdquo US Geol SurveyOpen File Report 76-414 Washington DC USA 1976

[16] H C Riggs ldquoStreamflow characteristics from channel sizerdquoJournal of the Hydraulics Division vol 104 no 1978 pp 87ndash961978

[17] W R Osterkamp and E R Hedman ldquoDischarge estimates insurface mine areas using channel geometry techniquesrdquo in Pro-ceedings of Symposium on Surface Mining Hydrology Sedimen-tology and Reclamation University of Kentucky Lexington KyUSA 1979

[18] E E Webber and J W Roberts ldquoFlood flow characteristicsrelated to channel geometry in Ohiordquo US Geol Survey OpenFile Report 81-1105 Washington DC USA 1981

[19] R J Omang C Parrett and J A Hull ldquoMean annual runoff andpeak flow estimates based on channel geometry of streams insoutheasternMontanardquo USGeol SurveyWater Resource Inves-tigations Report 82-4092 Washington DC USA 1983

[20] K L Wahl ldquoDetermining streamflow characteristics based onchannel cross section propertiesrdquo in Improving Estimates fromFlood Studies Transportation Research Record no 922 pp 1ndash10Transportation Research Board Washington DC USA 1983

[21] K L Wahl ldquoEvolution of the use of channel cross section char-acteristics for estimating streamflow characteristicsrdquo US GeolSurvey Water Supply Paper 2262 Washington DC USA 1984

[22] S M Lawlor ldquoDetermination of channel-morphology charac-teristics bankfull discharge and various design-peak dischar-ges in westernMontanardquo Scientific Investigations Report 2004-5263 US Geol Survey Reston Va USA 2004

[23] G P Williams ldquoBankfull discharge of riversrdquo Water ResourceResearch vol 14 no 6 pp 1141ndash1154 1978

[24] A Sridhar ldquoDischarge estimation from planform charactersof the Shedhi River Gujarat alluvial plain present and pastrdquoJournal of Earth System Science vol 116 no 4 pp 341ndash346 2007

[25] V S Kale V U Joshi and P S Hire ldquoPalaeohydrological recon-structions based on analysis of a Palaeochannel and Toba-AshAssociated alluvial sediments in the Deccan Trap region IndiardquoJournal of the Geological Society of India vol 64 no 4 pp 481ndash489 2004

[26] S C Mukhopadhyay and A Dasgupta River Dynamics of WestBengal (Vol II) Applied Aspect Prayas Publishers KolkataIndia 2010

Geography Journal 11

[27] K Rudra ldquoBanglar Nadikathardquo (in Bengali) Sahitya SamsadKolkata pp 11ndash19 58ndash69 and 78ndash92 2008

[28] S Mukherjee ldquoFloods inWest Bengalrdquo inGeographical Mosaic-Professor KG Bagechi Felicitation S P Chatterjee Ed pp 263ndash270 Manasi Press Calcutta India 1985

[29] P K Sen ldquoThe genesis of floods in the lower Damodar catch-mentrdquo inTheConcept andMethods in Geography P K Sen Edpp 71ndash85 The University of Burdwan Burdwan India 1985

[30] S Roy ldquoSpatial variation of floods in the lower Ajay River BasinWest Bengal a geo-hydrological analysisrdquo International Journalof Remote Sensing and GIS vol 1 no 2 pp 132ndash143 2012

[31] B Mitra ldquoExpediency of surrogate data in accounting hydro-logical balance of small River Basin a case study of the KunurBasinrdquo Indian Journal of Landscape System and EcologicalStudies vol 25 no 1 pp 38ndash48 2002

[32] S Mukhopadhyay ldquoA geo-environmental assessment of flooddynamics in lower Ajoy River including Sand Splay problem inEastern Indiardquo Ethiopian Journal of Environmental Studies andManagement vol 3 no 2 pp 99ndash110 2010

[33] V T ChowHandbook of Applied Hydrology McGraw-Hill NewYork NY USA 1964

[34] S Ghosh and S Ghosh ldquoLand degradation due to indiscrimi-nate ldquoMurrumrdquo extraction near Durgapur Town West Bengalrdquoin Land Degradation and Desertification V C Jha Ed pp 257ndash258 Rawat Publication New Delhi India 2003

[35] M Niyogi ldquoGround water resource of the Ajay Basinrdquo in Geo-graphical Mosaic- Professor KG Bagechi Felicitation S P Chat-terjee Ed pp 165ndash182 Manasi Press Calcutta India 1985

[36] H H Barnes Jr ldquoRoughness characteristic of natural channelsrdquoUS Geological Survey Water-Supply Paper 1849 1967

[37] M A Benson and T Dalrymple ldquoGeneral field and office pro-cedures for indirect discharge measurementsrdquo US GeologicalSurvey Techniques of Water-Resources Investigations Book 3Chapter A-1 1967

[38] J T Limerinos ldquoDetermination of themanning coefficient frommeasured bed roughness in natural channelsrdquo US GeologicalSurvey Water-Supply Paper 1898-B 1970

[39] R D Jarrett ldquoDetermination of roughness coefficients forstreams in Coloradordquo US Geological Survey Water ResourcesInvestigations Report 85-400 1985

[40] M A Summerfield Global Geomorphology An Introduction tothe Study of Landform Pearson Education Edinburgh UK 1stedition 1991

[41] H H Bengtson ldquoUniform open channel flow and manningequation (Course 501)rdquo Morrisville pp 1ndash26 2011 httpwwwpdhsitecom

[42] A D Knighton ldquoFluvial forms and processesrdquo Edward ArnoldSheffield North America Chapter 4 1984

[43] R Manning ldquoOn the flow of water in open channels and pipesrdquoTransactions of the Institution of Civil Engineers of Ireland vol20 pp 161ndash207 1891

[44] A L Bloom Geomorphology a Systematic Analysis of LateCenozoic Landforms PHI Learning Private New Delhi India3rd edition 2009

[45] D B Simons and E V Richardson ldquoForms of bed roughness inalluvial channelsrdquo Transactions of the American Society of CivilEngineers vol 128 p 289 1963

[46] G J Arcement Jr and V R Schneider ldquoGuide for selectingManningrsquos roughness coefficients for natural channels and floodplainsrdquo US Geological Survey Water-Supply Paper 2339 1989

[47] V T ChowOpen-Channel Hydraulics McGraw-Hill NewYorkNY USA 1959

[48] B C Yen ldquoOpen channel flow resistancerdquo Journal of HydraulicEngineering vol 128 no 1 pp 20ndash39 2002

[49] A Mohammadi H Ahmadi E Taghvaye Salimi Sh Khalighiand A Sallajegheh ldquoRegional model presentation for peakdischarge estimation in ungauged drainage basin using geomor-phologic Synyder SCS and triangular models (case study Kandrainage basin)rdquoCaspian Journal of Environmental Sciences vol10 no 1 pp 91ndash102 2012

[50] I Rodriguez-Iturbe G Devoto and J B Valdes ldquoDischargeresponse analysis and hydrologic similarity the interrelationbetween the geomorphologic IUH and the storm characteris-ticsrdquo Water Resources Research vol 15 no 6 pp 1435ndash14441979

[51] Soil Conservation Service ldquoNational engineering handbookrdquoSection 4 Hydrology Department of Agriculture Washingtonp 450 1964


[53] Z P Kirpich ldquoTime of concentration of small agriculturalwatershedsrdquo Civil Engineering vol 6 p 362 1940

Submit your manuscripts athttpwwwhindawicom

Child Development Research

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Education Research International


Biomedical EducationJournal of



Psychiatry Journal

ArchaeologyJournal of



AnthropologyJournal of


Research and TreatmentSchizophrenia


Urban Studies Research

Population ResearchInternational Journal of


CriminologyJournal of


Aging ResearchJournal of



NursingResearch and Practice

Current Gerontologyamp Geriatrics Research

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

Sleep DisordersHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

AddictionJournal of


Depression Research and TreatmentHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Geography Journal


Research and TreatmentAutism


Economics Research International

2 Geography Journal

andHedman [17]Webber andRoberts [18]Omang et al [19]Wahl [20 21] and Lawlor [22] the method was accepted bythe water resource division of the US Geological Survey asan operational technique In the central USA Williams [23]established relationships between bankfull discharge andchannel dimensions with sample data of 36 gauging stationsIn Indian context several researchers [2 24 25] have appliedindirect methodologies for estimation of discharge of severalungauged catchments

Flood is a natural phenomenon in the West Bengal Thestate with a geographical area of 88752 km2 occupies 27of Indiarsquos land and supports 802 (census 2011) of totalIndian population The flood prone area of West Bengal is37660 km2 4243of total geographical area ismore elevatedthan the average of 1217 [26] The downstream areas of 26river basins are frequently flood affected in the rainy seasonin all over theWest Bengal Enormouse flood has occurred inthis region from the end of September till the mid of October[27] The problem of flood is more difficult to control in thisstate because of two major aspects (i) the very small longi-tudinal gradient in general and (ii) the funnel-shaped basin(eg Damodar Ajay Dwarakeswar and Kasai River Basins)with a wide upper catchment and a narrow lower catchmentUnder these circumstances the basins generally have phe-nomenal increase of peak discharge [28 29] With this vul-nerability of West Bengal there is no availability of sufficienthydrological data to predict the nature of flooding behavior ofriver Correspondingly Kunur is also a notable river whichcauses flood in the Mangalkote and its adjoining Blocks ofBarddhaman District [30]

11 Purpose ofThis Research Themajor purpose of this studyis to estimate the peak discharge of the ungauged KunurRiver Basin during heavy flood using indirect methods withchannel geometry There are used numerical models insteadof modern instrument based velocity measurement (currentmeters) due to lack of departmental instrument financeand during flood the whole confluence zone is inundatedcompletely and there is no scope to reach to the outlet of theKunur River to measure the discharge In lean season therewas no flow for both rivers (Ajay and Kunur) and havoc floodcondition is a sudden scenario (mainly in September) foraccumulation of huge monsoonal runoff from upstream areaof these two basins On the basis of water input-output graphof the Kunur River Basin [31] it has been observed that floodcomes during September (Figure 1) Nevertheless Mitra [31]did not estimate the monthly discharge data of Kunur Riverduring floods this work has been an attempt to estimate itThis study also attends to understand regional hydrology forstudy area which provides a concept to design surface waterand flood management project

2 Materials and Method

21 Study Area The Kunur River Basin which covers a geo-graphical area of 92240 km2 is the second largest draininginland basin of north-east ward of Barddhaman District andamajor right bank tributary of theAjayRiver Geographically

0

50

100

150

200

250

300

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

Surplus water

Am

ount

of w

ater

(in

998400 00ha

middotm)

Water balance of Kunur River Basin

Input of water (in 99840000 hamiddotm)Output of water (in 99840000 hamiddotm)

Figure 1 Input-output situation of the Kunur River Basin (source[31])

it is located between 23∘251015840N to 23∘401015840N latitude and 87∘151015840Eto 87∘551015840E longitude and administratively divided into sev-eral police stationsmdashFaridpur Durgapur Kanksa AusgramBudbud Mangalkote and Bhatarmdashin the north-central partof Barddhaman The outlet of this watershed is near to thevillage ldquoKogramrdquo about 38 km from Burdwan Town on theBurdwan-Katwa road (Figure 2) The Kunur River representsa basin of 5th order with a drainage density that is equal to085 kmkm2 and the drainage pattern is more or less den-dritic with elongated shape [32] As per Mitra [31] the up-stream and central part of the Basin has a forest cover inter-spersed with paddy fields along watercourses 1380 of thebasin area is under forest while 5390 is cultivated 2620of the Basin area is not available for the cultivation and 610is culturable waste

Geographically this basin is tropical the Tropic of Cancer(23∘301015840E) is passing over the basin fromWest to EastThe seacoast is located at least 220 km away from the Bay of Bengaland somewhat extreme tropical climate is experienced here[34] The average annual rainfall is 1400mm of which themaximum occurs within the second week of June to Septem-ber

During summer months rainfall nearly exceeds 100mmand it is even over 1500mmduring rainymonths [32] Geohy-drologically the total basin is divided into three types of geo-hydrological characteristics First the upper catchment of theKunur River Basin is covered by hard rock mainly Archaeanformation with high grade metamorphic rocks of granitegneiss commonly referred as ldquoBengal Gneissrdquo Furthermoremiddle portion consists of semiconsolidated formation of theGondwana Sedimentaries and hard lateritic patches Finallythe lower catchment area is mainly un-consolidated with newalluvial of the Ajay and Kunur floodplains [35] As a resultmaximum rainfalls in the upper and middle catchment areaare turned into overland flow due to low infiltration capacityand make huge water pressure in the downstream channel ofthe Kunur River To generate floods in the lower Ajay River

Geography Journal 3

India

West BengalBirbhum

Barddhaman


Barddhaman

Chittranjan

Chakai

Jharkhand

(km)

Katoya


Birbhum

Ajay River

0 10 20 30

(a)

Ajay River

Kunur River


(b)




4 Geography Journal


0 2 4(km)

1978198419961999

200020042007


during 1978 to 2007

23∘45998400N

23∘30998400N

87∘35998400E 87∘55998400E

(a)


flood affected area

0 2 4(km)




0 2 4(km)


23∘45998400N

23∘30998400N

87∘35998400E 87∘55998400E

(b)


Ajay

Kunur River

Premonsoon period



0 4 8(km)

50

4035 30

20 15

60 50454035 30

2520

55

A

B

15B998400

A998400

River

(a)



Phreatic divide

45

25

65H

eigh

t (m

)H

eigh

t (m

)

Kunur Riverrrrrr


45

25


AA 998400

B B998400

(b)






Geography Journal 5



ℎ


B

b

zy

120572

1

zy

985747





119860 =

119910 (119887 + 119861)

2

= (

119910

2

) (119887 + 119861) (1)






V =119896 (11987723

ℎtimes 11990412

)

119899

(2)





119881Ω= 0665120572

06

Ω(119894119903119860)04 120572

Ω=

11987805

Ω

11989911986123

(3)






119876119890= 119894119903lowast 119860 (4)

6 Geography Journal

B

b

zy

zyy

985747

(a)


(b)






119876 =

(119875 minus 02119878)2

(119875 + 08119878)

(5)


119902119901

= 0208 lowast (

119860 lowast 119876

119879119901

) (6)



119901


119901) This can


between 119879119901and 119879


119879119901= 07119879

119888 (7)


equation

119879119888= 002119871

077119878minus0385

(8)




119901 and conse-




RME =

1

119899

sumRE119894 RE

119894=


119876op

(9)




RMSE = [

1

119899

(sum SE119894)]

12

SE119894= (119876op minus 119876cp)

2

(10)

Geography Journal 7




Slope-mm(119878)

Manningroughness









(119860)


(119878Ω)





119881Ω= 0665120572

06

Ω(119894119903119860)04

120572Ω= 11987805

Ω11989911986123



m3s

00024 92240 019 0035 563 075 27210 20408



area () CN Product








10) with 25mm








8 Geography Journal




(119875)




119888)


(119879119901)


(m3s) (119902119901)

8671mm 160mm 8873mm 92240 km2 16598 11618 14652



data (m3s)


model (m3s)




17935 23944 20408 14652








0

20

40

60

80

100

120

140

160

180

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Rain

fall

(mm

) and

disc

harg

e (cu

mec

)






Geography Journal 9



119888119879119901


1 16

8671

002 0125

16598 11618




4 Conclusion




Acknowledgments


References































































Psychiatry Journal



















Volume 2014


AddictionJournal of




Geography Journal





Geography Journal 3

India

West BengalBirbhum

Barddhaman


Barddhaman

Chittranjan

Chakai

Jharkhand

(km)

Katoya


Birbhum

Ajay River

0 10 20 30

(a)

Ajay River

Kunur River


(b)




4 Geography Journal


0 2 4(km)

1978198419961999

200020042007


during 1978 to 2007

23∘45998400N

23∘30998400N

87∘35998400E 87∘55998400E

(a)


flood affected area

0 2 4(km)




0 2 4(km)


23∘45998400N

23∘30998400N

87∘35998400E 87∘55998400E

(b)


Ajay

Kunur River

Premonsoon period



0 4 8(km)

50

4035 30

20 15

60 50454035 30

2520

55

A

B

15B998400

A998400

River

(a)



Phreatic divide

45

25

65H

eigh

t (m

)H

eigh

t (m

)

Kunur Riverrrrrr


45

25


AA 998400

B B998400

(b)






Geography Journal 5



ℎ


B

b

zy

120572

1

zy

985747





119860 =

119910 (119887 + 119861)

2

= (

119910

2

) (119887 + 119861) (1)






V =119896 (11987723

ℎtimes 11990412

)

119899

(2)





119881Ω= 0665120572

06

Ω(119894119903119860)04 120572

Ω=

11987805

Ω

11989911986123

(3)






119876119890= 119894119903lowast 119860 (4)

6 Geography Journal

B

b

zy

zyy

985747

(a)


(b)






119876 =

(119875 minus 02119878)2

(119875 + 08119878)

(5)


119902119901

= 0208 lowast (

119860 lowast 119876

119879119901

) (6)



119901


119901) This can


between 119879119901and 119879


119879119901= 07119879

119888 (7)


equation

119879119888= 002119871

077119878minus0385

(8)




119901 and conse-




RME =

1

119899

sumRE119894 RE

119894=


119876op

(9)




RMSE = [

1

119899

(sum SE119894)]

12

SE119894= (119876op minus 119876cp)

2

(10)

Geography Journal 7




Slope-mm(119878)

Manningroughness









(119860)


(119878Ω)





119881Ω= 0665120572

06

Ω(119894119903119860)04

120572Ω= 11987805

Ω11989911986123



m3s

00024 92240 019 0035 563 075 27210 20408



area () CN Product








10) with 25mm








8 Geography Journal




(119875)




119888)


(119879119901)


(m3s) (119902119901)

8671mm 160mm 8873mm 92240 km2 16598 11618 14652



data (m3s)


model (m3s)




17935 23944 20408 14652








0

20

40

60

80

100

120

140

160

180

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Rain

fall

(mm

) and

disc

harg

e (cu

mec

)






Geography Journal 9



119888119879119901


1 16

8671

002 0125

16598 11618




4 Conclusion




Acknowledgments


References































































Psychiatry Journal



















Volume 2014


AddictionJournal of




Geography Journal





4 Geography Journal


0 2 4(km)

1978198419961999

200020042007


during 1978 to 2007

23∘45998400N

23∘30998400N

87∘35998400E 87∘55998400E

(a)


flood affected area

0 2 4(km)




0 2 4(km)


23∘45998400N

23∘30998400N

87∘35998400E 87∘55998400E

(b)


Ajay

Kunur River

Premonsoon period



0 4 8(km)

50

4035 30

20 15

60 50454035 30

2520

55

A

B

15B998400

A998400

River

(a)



Phreatic divide

45

25

65H

eigh

t (m

)H

eigh

t (m

)

Kunur Riverrrrrr


45

25


AA 998400

B B998400

(b)






Geography Journal 5



ℎ


B

b

zy

120572

1

zy

985747





119860 =

119910 (119887 + 119861)

2

= (

119910

2

) (119887 + 119861) (1)






V =119896 (11987723

ℎtimes 11990412

)

119899

(2)





119881Ω= 0665120572

06

Ω(119894119903119860)04 120572

Ω=

11987805

Ω

11989911986123

(3)






119876119890= 119894119903lowast 119860 (4)

6 Geography Journal

B

b

zy

zyy

985747

(a)


(b)






119876 =

(119875 minus 02119878)2

(119875 + 08119878)

(5)


119902119901

= 0208 lowast (

119860 lowast 119876

119879119901

) (6)



119901


119901) This can


between 119879119901and 119879


119879119901= 07119879

119888 (7)


equation

119879119888= 002119871

077119878minus0385

(8)




119901 and conse-




RME =

1

119899

sumRE119894 RE

119894=


119876op

(9)




RMSE = [

1

119899

(sum SE119894)]

12

SE119894= (119876op minus 119876cp)

2

(10)

Geography Journal 7




Slope-mm(119878)

Manningroughness









(119860)


(119878Ω)





119881Ω= 0665120572

06

Ω(119894119903119860)04

120572Ω= 11987805

Ω11989911986123



m3s

00024 92240 019 0035 563 075 27210 20408



area () CN Product








10) with 25mm








8 Geography Journal




(119875)




119888)


(119879119901)


(m3s) (119902119901)

8671mm 160mm 8873mm 92240 km2 16598 11618 14652



data (m3s)


model (m3s)




17935 23944 20408 14652








0

20

40

60

80

100

120

140

160

180

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Rain

fall

(mm

) and

disc

harg

e (cu

mec

)






Geography Journal 9



119888119879119901


1 16

8671

002 0125

16598 11618




4 Conclusion




Acknowledgments


References































































Psychiatry Journal



















Volume 2014


AddictionJournal of




Geography Journal





Geography Journal 5



ℎ


B

b

zy

120572

1

zy

985747





119860 =

119910 (119887 + 119861)

2

= (

119910

2

) (119887 + 119861) (1)






V =119896 (11987723

ℎtimes 11990412

)

119899

(2)





119881Ω= 0665120572

06

Ω(119894119903119860)04 120572

Ω=

11987805

Ω

11989911986123

(3)






119876119890= 119894119903lowast 119860 (4)

6 Geography Journal

B

b

zy

zyy

985747

(a)


(b)






119876 =

(119875 minus 02119878)2

(119875 + 08119878)

(5)


119902119901

= 0208 lowast (

119860 lowast 119876

119879119901

) (6)



119901


119901) This can


between 119879119901and 119879


119879119901= 07119879

119888 (7)


equation

119879119888= 002119871

077119878minus0385

(8)




119901 and conse-




RME =

1

119899

sumRE119894 RE

119894=


119876op

(9)




RMSE = [

1

119899

(sum SE119894)]

12

SE119894= (119876op minus 119876cp)

2

(10)

Geography Journal 7




Slope-mm(119878)

Manningroughness









(119860)


(119878Ω)





119881Ω= 0665120572

06

Ω(119894119903119860)04

120572Ω= 11987805

Ω11989911986123



m3s

00024 92240 019 0035 563 075 27210 20408



area () CN Product








10) with 25mm








8 Geography Journal




(119875)




119888)


(119879119901)


(m3s) (119902119901)

8671mm 160mm 8873mm 92240 km2 16598 11618 14652



data (m3s)


model (m3s)




17935 23944 20408 14652








0

20

40

60

80

100

120

140

160

180

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Rain

fall

(mm

) and

disc

harg

e (cu

mec

)






Geography Journal 9



119888119879119901


1 16

8671

002 0125

16598 11618




4 Conclusion




Acknowledgments


References































































Psychiatry Journal



















Volume 2014


AddictionJournal of




Geography Journal





6 Geography Journal

B

b

zy

zyy

985747

(a)


(b)






119876 =

(119875 minus 02119878)2

(119875 + 08119878)

(5)


119902119901

= 0208 lowast (

119860 lowast 119876

119879119901

) (6)



119901


119901) This can


between 119879119901and 119879


119879119901= 07119879

119888 (7)


equation

119879119888= 002119871

077119878minus0385

(8)




119901 and conse-




RME =

1

119899

sumRE119894 RE

119894=


119876op

(9)




RMSE = [

1

119899

(sum SE119894)]

12

SE119894= (119876op minus 119876cp)

2

(10)

Geography Journal 7




Slope-mm(119878)

Manningroughness









(119860)


(119878Ω)





119881Ω= 0665120572

06

Ω(119894119903119860)04

120572Ω= 11987805

Ω11989911986123



m3s

00024 92240 019 0035 563 075 27210 20408



area () CN Product








10) with 25mm








8 Geography Journal




(119875)




119888)


(119879119901)


(m3s) (119902119901)

8671mm 160mm 8873mm 92240 km2 16598 11618 14652



data (m3s)


model (m3s)




17935 23944 20408 14652








0

20

40

60

80

100

120

140

160

180

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Rain

fall

(mm

) and

disc

harg

e (cu

mec

)






Geography Journal 9



119888119879119901


1 16

8671

002 0125

16598 11618




4 Conclusion




Acknowledgments


References































































Psychiatry Journal



















Volume 2014


AddictionJournal of




Geography Journal





Geography Journal 7




Slope-mm(119878)

Manningroughness









(119860)


(119878Ω)





119881Ω= 0665120572

06

Ω(119894119903119860)04

120572Ω= 11987805

Ω11989911986123



m3s

00024 92240 019 0035 563 075 27210 20408



area () CN Product








10) with 25mm








8 Geography Journal




(119875)




119888)


(119879119901)


(m3s) (119902119901)

8671mm 160mm 8873mm 92240 km2 16598 11618 14652



data (m3s)


model (m3s)




17935 23944 20408 14652








0

20

40

60

80

100

120

140

160

180

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Rain

fall

(mm

) and

disc

harg

e (cu

mec

)






Geography Journal 9



119888119879119901


1 16

8671

002 0125

16598 11618




4 Conclusion




Acknowledgments


References































































Psychiatry Journal



















Volume 2014


AddictionJournal of




Geography Journal





8 Geography Journal




(119875)




119888)


(119879119901)


(m3s) (119902119901)

8671mm 160mm 8873mm 92240 km2 16598 11618 14652



data (m3s)


model (m3s)




17935 23944 20408 14652








0

20

40

60

80

100

120

140

160

180

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Rain

fall

(mm

) and

disc

harg

e (cu

mec

)






Geography Journal 9



119888119879119901


1 16

8671

002 0125

16598 11618




4 Conclusion




Acknowledgments


References































































Psychiatry Journal



















Volume 2014


AddictionJournal of




Geography Journal





Geography Journal 9



119888119879119901


1 16

8671

002 0125

16598 11618




4 Conclusion




Acknowledgments


References































































Psychiatry Journal



















Volume 2014


AddictionJournal of




Geography Journal







Acknowledgments


References































































Psychiatry Journal



















Volume 2014


AddictionJournal of




Geography Journal









































Psychiatry Journal



















Volume 2014


AddictionJournal of




Geography Journal













Psychiatry Journal



















Volume 2014


AddictionJournal of




Geography Journal





Documents

Research Article Estimation of Peak Flood Discharge for an ...downloads.hindawi.com/archive/2013/214140.pdf · village Kogram , about km from Burdwan Town on the Burdwan-Katwaroad(Figure