Hydrologic Estimationd in Nepal by KP Sharma & NR Adhikari

7/28/2019 Hydrologic Estimationd in Nepal by KP Sharma & NR Adhikari

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3 LOW-FLOW

Low-flowstatisticsare essential n water supply planning to determineallowablewater ransfersand withdrawals. Other applicationsof low-flows include waterqualitymanagementapplications, determination of minimum downstream releaserequirementsrom water resources rojectsetc.

A method for assessingow-flow characteristicsor l-day,7-day,30-day,and monthly duration was developed by the Department of Hydrology andMeteorology and Water and Energy Commission Secretariate in 1980s(WECS/DHM, 1990) published in 1990 as a report titled 'Methodologies

forEstimating ydrologic Characteristics f UngaugedLocations n Nepal.' This westhe irst attempt n Nepal for assessingow-flows of different recurrence ntervals.Thestudyuseddata for 44 stationswith a period covering the period from 1963to1985. hepresentstudy is an updateof the 1990study to include: additionaldataup o 1995,additional stations, and improved physiographic and hlpsometric dataderived rom GIS tools. The study used data from 309 precipitation-gauglngstationsFigure1.3) and51 hydrometricstations Figure 1.4).

3.1 Low-FlowCharacferisfics

Significantdecrease n low-flow on a stream leads to drought, reduction inreservoirevels,depletion in soil moisture, &d depletion of groundwater evels.

Suchconditions lead to scarcity in drinking water, ffid decline in agricultureproductionwittr high consequences on economy and social developmentsincluding uman miseries. Estimation of low-flow status on a river is important

for designing single purposeor multipurpose water resourcesproject considering

exteme onditions egarding the availability of adequatewater supply.

Rivers ure mainly recharged by groundwater during minimum flow

periods. ence, he flow pattern is highly influenced by the hydrology of a riverbasin. ecause f the drawdown of upper aquifers, a river is recharged from deep

aquifers ith lesswater storageduring extremely dry years.A potential frequency

distribution f low-flow series must, hence, be able to take such deviation into

acc0unt.

In a region affected by continental monsoons, winter and spring seasons

ue usuallydry causing the minimum flow occurring generally in spring season.

Theperiod s also highly dependent on the ice and snowmelt situation in the

headwater reas. Due to snowmelt in snow-fed rivers, lowest flow conditiongenerally ccurs earlier than in the rivers lacking snowmelt contribution to the

river lows Figure1.7).

As in the case of floodflow estimates, the assessmentof low-flow

dischargesn a river at any location primarily dependson three cases: adequate

data"nadequate ata and missing data. The well-known method of hydrological

analogys an appropriate tool in the case of inadequate hydrometric data. The

scopef thismethodmay be wider in respect of the estimation of low flows.

29



3.2 LiteratureReview

Compared o flood-flow studies, iterature on low-flow studies s limited. One ofthe earlierstudieson low fl ows by Riggs(1972)discusseshe natureof low-flowfrequencycurvespresentinga multiple regressionapproach n regionalization.Afew regional studieson low flows found in recent iterature nclude the Low-Flow'

Studies n the UK (IH, 1980), n Russia (Artemieva, 1997) and in South Africa(Smakhtin and Hughes, L997). Multivariate relationship of low flows to ciimatic

and basin characteristics re he basicapproachapplied n most of thesestudies o

developmethodologiesor ungauged asins.A methoddeveioped n 1982by SirMacDonald and Partners titled 'Medium lrrigation Project Design Manual' isbasedon the data of a single streamflow measurement uring a dry period to ger

long-termcharacteristicsf minimum flows (MacDonald1990).

A catchmentarea acts as a reservoir for precipitation.Hence a catchment

area s usually consideredas a universal parameterwhile computing low flows.

Besides the catchment area, other parametershave also been considered n the

regressionanalysis or arriving at the best equation or predicting low-fiow. Thepatternof equationconsidered n this study has he following iorm:

Iow-flow sminimum.

Liteliterature sT)p. II Idistrihurionprobability

Fouloula-G

Distr i:rrtiotn tnrs stuboundedat tl

Theprogram LOCanada. ThExtreme Valtpresentedn l

Q,=axix{ x1'--......,

whereQr : T- yearminimum flow

Xr, X:, X: : lndependent ariables nfluencing ow flows

&d,p,T... . regression oefficients

( J . I ]

3.3 Low-FIow Derivation

Daily dischargedataavailable at DHM were the sourceof data for the derivationof low-flow values for different durations. An EXCEL based macro was

developed to extract l-day minimum, 7-day minimum, 30-day minimum andmonthly minimum flows. The macro producedoutput in a format, which could

directly be used as nput for the low-flow frequencyanalysis.

One-day low-flow computed by the macro is the lowest value obtainedfrom eachyear'sdaily streamflow data.Seven-dayow-flow is the minimum value

obtained from the consecutive seven-day averages. The procedure used tocalculation 30-day ow-flow was similar to theprocedureused n 7-day low-flowcomputation.Monthly minimum flow is the minimum value obtained from the

seriesof twelve monthly values.One-day,7-day,30-day,and monthly minimumvalueswereobtained for eachyeardevelopinga series or eachduration..

3.4 Low-FIowFrequencyAnalysis

Estimation of low-flows from stream low records s generally done by fitting aprobability distribution to the annuai minirnurn average ou.,-flou''series"Tlrricai

J V



low-flowseriesconsidered n this study are: l-day, 7-day,30-day and monthlyminimum.

Literatureon low-flow frequencyanalysis s relatively sparse. Availableliterature hows that the three-parameterWeibull Distribution, the Log PearsonType III distribution, and two-parameter and three-parameter Lognormaldistribution re the widely useddistributions n severalpartsof the world for theprobability istribution analysis of low flows (Riggs, 1982; Stedinger,Vogel &Foufoula-Georgiou,992). The Extreme Value Type III distribution (Weibull

Distribution) sed n most of the regionsof the world, was selected or applicationin this study. This distribution is particularly suitable for discharge values

boundedt he ower end such as he casesof ephemeral ivers.

The low-flow frequency analysis was carried out using a computerprogram OFLOW developed by the Inland Water Directorate of Environment

Canada. he program computes low-flow values for a given duration using

Extreme alue Type III distribution. The resultsof the run for all the stationsarepresentedn Table3.1 for different durations.

J r





7-DAY 2.YEARLOW-FLOW

@

caE

3o

LLIV

ootC)

(g

q

Q o

95 % Cl

95 % Pl

'100 200

SquareRoot Area km2)below5000m]

-Year7 -daYow-flow'

ir 7-daYow-flow'

2O-YEAR OW-FLOW

ac)

E

3 r ooLL

oot e

o$

q

Q 0

95 % cl

- - 9 5 % P l

SquareRoot Area km2)below5000m]

) )



u)

(.,q)o)(g

oU'

l -

l c )

l oI ( )

1-daY 0-Yearow-Flow

1 0

Actual ischargem3/s)

Figure3.3.Plotofactualvscomputeddischarge:1-dayl0-yearylow-f low

7-daY10-Year ow'Flow

Figure3.4.Plotactualvscornputeddischarge:1.dayl0.yearlowflowi

al +

1 00

3.5 Resu

The correlati

significantlY

SimilarlY, th

hypsometric

areasbelow

by the Poorthe regional

aprlied for tthe reiations

and ungaug

for theseregi

Anall

multiPle reg

elevation an

improvemen

5000 m, ho

ease, onlY

recommend

frequencies

comPutatio

Present the

low flows r

periodT

T

presentmultiPlenumber(3.2) fo

resPecti

I

f

- t ,

' '--\I



3.5 Resulfsand Dfscussion

The correlation matrix (Annexure III) shows that the low-flow values are

significantlycorrelated with basin area, basin perimeter, and river length.

Similarly, the minimum flows are also significantly related to different

hypsometricnd land-useareas.Correlationmatrices also indicate that the basin

areaselow 5000 m are the most influencingarea or the low-flows. As indicated

by thepoor correlation between he low-flow and the geographicalcoordinates,

the egional spect s consideredess significant so that the sameequationmay be

appliedor the whole country. Caution should,however,be taken while applyng

the elationshipor an ungauged ocation above 1800 m in high mountain areas

andungaugedocations on streamsoriginating in the Siwalik or Terai as no data

for heseegionswere available or developing egressionequations.

Anaiysisof multiple regressionshowed hat the relationship based on the

multipleegression f areabelow 5000 m or 3000 m combinedwith averagebasin

elevation nd averagebasin slopeyieldedbest results avoiding co-linearities.The

improvementn goodnessof fi t by including additionalparametersn area below

5000m, howeverwas marginal. Consideringthe applicability of equation with

ease, nly the relationship of low-flow with area below 5000 m have been

recommendedor the estimation of low-flows for different durations and

frequencies. he following equation (Equation 3.2) may be used for thecomputationf low flows at an ungauged ocation. Figure 3.1 and Figure 3.2

presenthe best-fit plot presenting he sample of 7-day Z-year and 7-day Z}-year

low lows espectively.

W =Co., Fo.rJ-* , (3.2)

where,Qd,,: Discharge m3/s;

d: duration day)

T: Returnperiod (year)

Co.r: Constantcoefficient for a duration d andreturnperiod T

Fa,r : Coef. of independentvariable for duration d and return

periodT

A.5r: Area of the basinbelow 5000m

The values of C and F for different return periods and duration are

presentedn Table 3.2. The table also includes the statistics obtained from the

multiple egression nalysis of the data.Figure 3.3 and Figure 3.4 compares he

numbersbtained rom actualvalues with the numberscomputed from Equation

(3.2) or the two samplecasesof l-day lO-year and 7-day Z-year low flows

respectively.nnexure presents n exampleof the computation.

35



Table 3.2. Table for low-f l est imatit, Laote Ior tow-Ilow esLtmatton equauons

ReturnPeriod Day

Const.

C a r

Goef.

Farstd.Error f

2 1 0.2144 0.081t 0.0033 0.9257 0.2362 0.083c 0.0033 0.929

30 0.302€ 0.0854 0.0031 0.938[/onthly 0.339i 0.086c 0.003c 0.94C

1 0 1 0.085s 0.0729 0.0032 0.915

0.0920 0.0748 t.oogr 0.921

3C 0.1807 0.076€ 0.003c 0.93C

Monthly 0.2138 0.0777 0.0031 0.94C

201 0.0698 0.0703 0.0031 0.912

0.0662 0.0726 0.0031 0.91€

30 0.160€ 0.0742 0.003c 0.927

[/onthlv 0 .1 94 t 0.0754 0.0031 0.929

36



















5 CONCLUSIONSANIDRECOMMENDATIONS

Themethods or hydrologicalestimations t ungaugedocations n Nepal, suggested

in this eport,are he updates f the eariiersimilar studies WECSIDHM, 1990).The

updates se meteoroiogicaland hydroiogical data up 1995. Besides, he updateddatabasentegrated n a GIS systemwas the sourceof land-use,physiographic,and

hypsometric ata used n this study.

The mathematical ormulations developed or different hydrological designs

arebasedon easily derived basin and climatic information. Designerswith iimited

hydrological xpertise can use these methods.Drainage areaof the ungaugedbasin

below 000m is the only parameter equired or flood flow estimation.Similarly, low

flowsareestimatedon the basisof the drainageareabelow 5000 m. Average annual

hydrograph t an ungauged location is computed using. average basin elevation,

averagennuaiprecipitationand basin areabeiow 3000m. Flow-duration curve for an

hngaugedocation uses he samevariableas n averageannualhydrographbesides he

b.asinrea elow 5000 m.i

Aithough Nepal can be divided into three distinct physiographic zones,

nameiy he High Himalayas,Middle Mountains, and the Terai, attempts to derive

regional atternof the hydrological characteristics ver Nepal were not successful

primarilybecauseof the unavailability of representative nformation covering the

whole egion. The existing hydrometric network in Nepal covers only the Middle

Mountainegionwithin the eievation one rom 140m to 1800m abovesea evel.

Since the developedmethodologies are based on limited information and

averagedonditions, hey should be used only for the hydrological investigationsat

reconnaissancer pre-feasiblyevels.Estimated aluesshouldbe udged properlyon

thebasis f hydrological reasoning or the best results.The following precautionsare

particulariymportantwhile applyrng he methods.

. Reliability of the methodswill be low in the high Himalayan region

whereno regular hydrometryexists.Besides, he hydrology of the high

Himalayan region needs o address he complexprocessof snow and

glacier,which is not yet properlyassessed.

. The methodswill need special udgment in the Terai region where the

flows are highly influencedby surfacewater-Groundwater nteractions

and human impacts. In addition, the nature of floods in Terai is

different fronn /alleyfloods n the mountainousareas.The Terai fioods

aremore staticcompared o floods n themcuntainous ivers.

. Since the drainage areasused in this study ranged from 17 kmz54000 km2, precautionshould be taken in applying the methods

river basinssmaller han 20 km2.

45

toin

































































































































Stat ion number:

Locat ion:

R iver :

6 0 0 . 1

Uwa Gaon

Arun RiverLa t i t ude : 2 7 36 00

Longi tude: 87 20 06

EXTREME DISCHARGES

MAXIMI'M INSTAI.ITA}IEOUS

Year Discharge Gauge heighE DateMINIMI,M INSTAI{TAI\TEOUS

Discharge caugE height DaEe(m3/s ( m) {m3/s

6 9 . 3

6 7 5

5 2 . 9

5 3 . 0

6 1 . 0

5 5 . 4

5 9 4

5 3 0

5 L . B

, 5 L . 3

(m )

L . 8 7 L 8 / 0 2 / 8 6

L . 8 s t e / 0 2 / 8 7

1 . 6 7 2 7 / O L / 8 8

1 . 8 0 2 0 / 0 2 / 8 e

1 . 6 0 0 7 0 2 / e o

r . . 3 2 6 / o r / e t1 _ . s 8 2 7 / 0 2 / 9 2

1 . s 0 2 3 / 0 3 / e 3

1 . 4 8 2 2 / O L / g q

1 . 4 8 0 3 / O r / e 5

l - 9 8 5

1 _ 9 8 6

L 9 8 7

L 9 8 8

L 9 B 9

r .990

r_991_

1992

r .993

L 9 9 4

r_99s

t 4 2 0 5 . 6 0

L 2 7 0 6 . 3 0

05 / oe / 8s2 e / 0 6 / 8 6t2 / 08 /87t s / o 8 /8 82 e / 0 5 / 8 et 3 / 0 8 / e o76 / 06/ eL2s / o B /e 20 4 / 0 7 / e 30 8 / 0 8 / e 42 8 / 0 8 / e s

L 5 20j - 3 7 0

1270

L L 7 0

)-47

L270

6 . 8 0

6 . 5 0

6 . 3 0

6 . 1 0

6 . 7 0

5 . 3 0

t 4 7 0 6 . 7 0

9 5 7 5 . 6 0

1 4 5 0 . 6 . 5 0

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Hydrologic Estimationd in Nepal by KP Sharma & NR Adhikari