A comparative study of flow forecasting in the Humber River Basin using a deterministic hydrologic model and a dynamic regression statistical model

A Comparative Study of Flow Forecasting in the Humber River

Basin using a Deterministic Hydrologic

Model and a Dynamic

Regression Statistical Model

by RobertC.Picco

Athesissubmittedto the School of GraduateStudies

inpartial fulfilmentofthe requirementsfor the degree of

Masterof Engineering

FacultyofEngineeringandAppliedScience University of Newfoundlan d

August1997

.+.

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0-612-34219-0

Abstract

Since 1995theWater Resources ManagementDivision of the Depanmentof

Environmentand Labourhasgenerated flow forecastsforthe Humber River Basin.These forecastsare required to providea flood warning for residents livinginthedownstream sections ofthe basin.Informatio nis also usefultotheDeerLake PowerCompany for the safeandefficientoperationofthehydroelectricdevelopme nt that contro lsovertwothirds of thebasin

Flow forecasts forriversystems can be generatedusingtwo approaches. One approach isto use adeterministic modelthat tries10 constructamath ematical modelby

accountingforsome.orallof,hydro logicfactors responsible forrunoff in the basin.The second approachis to developa statisticallybased modelthatusesthe historic flows and

climatedatafromthe basinto generatea forecast. For anymodel to beeffective in an

operational environment,itmustbecompatiblewith hydrometeor ologic input datacollected

in nearreal time.

The current methodof generatingforecastsuses theSSARR (StreamflowSynthesis

andReservoir Regulation) hydrologicmodel a continuoussimulation modelthathasreservoir

rout ingcapabilities.plusthe ability to accountfor the areal distributionof meteorologic

inputs.includingsnowmelt. This modeldefines the water budg etusing hydrometeorological

In thisstudya forecastmethod based onthedynamic; regression techniqu e was developedtoproduceone,twoardthreedayforecastsfor the five gaugedsub basins results. Also.forecastsforthesame time periods wereproducedusing the SSARR modd.The

results

of bothmethodswerecompared using the mean absolut e percentag e error (MAPEl criterio n.

Tberesultsofthecomparison showed that the dynamic;regression perfonned better thanthe SSARRmod el forall basins.particularlyfor thelargerbasins.

Acknowledgements

Iwould liketo take thisopportunitytothankaoomberof peoplewhoprovided advice..assistanceandsupportduringmypursuitofaMaslers of Engineeringdegr ee.First orall.Iwouldliketothank theNewfoundlandDepartmentofEnvironrnent andlabourfor providingaccesstothedatausedintheanalysis.Inparticular,I wouldtiketothankDr.Wasi UUah(nowretired)for hisencouragementtostarttheprogram.

My sincere thanksare alsoextendedtoDr.LeonardLye,mysupervisor,forhis acade mic guidance andsuggestionsduringthe program.

Last.but not least,Isincerelythankmy wifeBrendaforher patience andmoral support.

2.

3.

Table of Contents

lNTRODUCTION. 1.1 Background. 1.2 Objectivesof theStudy. 1.3 Outlineof Thcsis

DESCRIPTIONOF THE STUDY AREA.

2.1 General. 2.2 Physiography 23 SurficialGeology... 2.4 Climate. 2.5 ForestCover DATAPREPARATION.. 3.1 AvailableData.

3.1.1AESClimateData. 3.1.2WSCFlow/Sta ge . 3.1.3NcarRealTimeData(NDOEL.)._ 3.2 DataReview. . ...1 .2 ....3

.

.

.. ..4 .7 ...10 .11 ..14 . ..14

I'

.I. ..16 . 16

4. METHODOLOGY.

4.I Deterministic Model(SSARR ). 4.1.1ModelDescriptio n

4.1.1,(History. 26 26 26 26 4.1.1.2Generaldescription. .28

4.1.1.3HydrologicPrinciplesUtilizedintheSSARR Model 29

4.1.1.4Structure 32

4.1.1.5MethodologyforCalibrationand Validation 39 4.1. 1.6ModelSetupfortheHumberRiverBasin .43 4.1.1.7CalibrationandVerification. 51

4.1.1.8Data Format 56

4.1.2ForecastsforSpecificEvents 4.2 Statistical Model(DynamicRegression)

4.2.1 ModelBackground . 4.2.2ForecastModelDevelopment 4.2.3ModelDiagnostics.

4.2.3.1DynamicsSpecifications 4.2.3.2 Variable Specification 4.2.3.3 Custom excludedvariabletests 4.2.3.4 Standard diagnostics.. 56 .59 59 61 66 66 67 67 .67

4.2.4Model Results. 4.2.5 Generation of Forecast s.

5. COMPARISON OFMODELUNG RESULTS

5.1 AnalysisofResults. 5.2 Discussion ofResults

6. CONCLUSIONSANDRECo MMENDAnONS.

6.I Conclusions

6.2 Recommendations

7, REFERENCES.

APPENDICES

Appendix A-InitialPlots -FlowandClimate Data AppendixB . Comparison Plots- WSCandNDOELData AppendixC - SSARRInput andOutput FilesSample Appendix0 - DynamicRegressionModelOutputExample

iii ..71 ... . . .71 77 ..77 81 80 .80 88 88

List of Tables

TableI-Long TermClimateData-Humber River Basin Table2·Summaryof Hydrometri cData-Humber RiverBasin TableJ DescriptiveStatistics- Flow and Climate Data Table 4- DescriptiveStatistics - Clima te Stations Table5-Desc riptiv eStatisticsClimateStations . Table6•Descripti veStatistics- FlowOnlyStations Table7 - ClimateStation Locations-Humber RiverBasin Table8 - SubbasinCharacteristics.

Table 9-PrecipitationGaugeWeights Applied toSub-basins. Table 10 - Snowmel t Coefficients

Table11-RoutingCoefficients. Table12 - SSARRInput Data. Table 13_ SSARR ControlCard Organization

Table 14-SampleDiagnosticsfromDynamic Regr essionMod el Table15 - Form of DynamicRegressi onModels Ta bl e16_MAPE Dynamic Regression Model Table .7-MAPE ResultsforSSARR Model

iv 11 .15 22 23 . ....24 25 45 49 ..53 54 55 56 58 ..68 .72 79 80

Li

st of F

igures

Figure I- General Location of Study Area Figure2~Physiographyand Surficial Geology. Figure3 - Forest Cover&Vegetation. Figure 4 - SampleFlow Data fromDCP Station Figu re 5 - SampleTemperature and Precipitation data Figu .-c 6 - WSC and DCP Data Comparison Figu re 7 - SSARR SchematicwithSnowband Option. Figure8 - Watershed Discretization -Humber River Basin. Figure 9 - HydrometricStation Locations - SSARR Model Figure 10 -BasinSchematic-SSARR Model. Figu r e 1t-Altitude-Ar eaRelationship.. Figure 12 - Sample SSARR Calibration Run FigureIJ-SampleSSARR FlowForecast Output Figure 14- BasinSchematic- Dynamic Regression Model Figu re 15 - Dynamic RegressionModel BuildingCycle. Figu re 16-Sample ACF Changes

Figure .7-Basin Map - Dynamic Regress ionModel. Figu re18 - Dynamic Regression Model Resultsvs RecordedFlows.

13 I. ..20 .21 31 46 47 48 50 51 57 63 64 .65 73 75

Figure 19- SampleOnedayForecast. Figure20- SampleTwodayForecast. Figure21-SampleThreeDayForecast. Figure22- SSARR Resu lts1996Data.

Figure2l- ResultsofManitoba Mood Comparison

vi . 76

.

7.

. ..76 . 82 ...83

ACF AES ARJMA BII DCP ETI NDOEL

SMI

SSARR S-SS WSC

Abbrevia

tions

Autocorrelation Function

AtmosphericEnvironmentServiceof Environment Canada

Autoregressiveintegratedmovingaverage

BaseflowInfiltrationIndex

Data CoUectionPlatform

EvapotranspirationIndex

NewfoundlandDepanment of EnvironmentandLabour

SoilMoistureIndex

StreamflowSynthesis and ReservoirRegulationModel Sub SurfaceInfiltration

WaterSurveyof Canada, branchof EnvironmentCanada

1

.

INTRODUCTION

1.

1

B

ackground

The HumberRiver Basinisthesecondlar gest riversystem ontheislandof

Newfoundlan dwithadrainageareaof over 80001on1

.Overhalfthe basinisregulatedfor bydrodcctricpowergenera tionbytheDeerLake PowerCompany(DLPC).Sincethe early

1900's,thecommuniti~.includingDeerLake and SteadyBroo k. havedevelo ped alongthe

HumberRiver.Aspanofthisdeve lop mentmany residents were drawntothescenicareas and flatlands alongthefloodplain areasof theHumberRiver and Deer Lake.Eachyear some flooding occursatSteadyBroo kandDeerLake.Whilethefloodingis usuallymino r.

thepot ential forflooding that

affects

largeareasofthecommunitiesexists,as OCCUlTedin

1969and1981.

Inanefforttoreduceflooddamagecausedbythisannualpro blem.these areaswer e includedinthe Canada-Newfound land FloodDamageReduction Program.Ahydrotechnica1 study completedin 1984(Cumming Cockburn, 1984) identified the floodrisk areas correspondingtotheI:20andI:100year intervalfloods.Thehydrologicmodelling was carriedoutusing theStreamflowSynthesisand ReservoirRegulation(SSARR)model. Additionalstudies (CunvningCoclcbum,1985&1986)recommendedthata flood forecasting

systembedevelo pedto warnresiden ts of impendi ngfloodeventsanddidapreliminary evaluatio n of afor ecastingsystem.Thiswouldallowreside nts totake preventativeaction 10 movevaluablesortake othe rapp ropria te actio ns.Suc hasystemwou ld also providethe

Deer Lake Power Companywithinformationto operate the hydroel ect ric genera ting stat ion withadditionalefficiencyandsafety

Even beforethecompletio nof thesestudies,theneedfo ranaccurate 'near real time' flo w forecasting and floodwarnin g system forthisbasin wasrec ogniz edbytheDepart ment ofEnviro nment and Labour(NOOEL)and thePow er Company.The Department's goalis topro videa flood warni ngsystemwith upto 72hoursadvancewarning ofan impending flood.ThePower Company requires accura te flowfo recast s forsafeandefficientope rati o n of thehydroelectricdevelopmentat Deer Lake. Based on this commo n interest,the Departmemof Envirorunentand Labour and thePowerCompanycostshared theexp ansio n of thedatacollectio n network required to implement theflowforecast ing andfloodwarni ng system for the basin.

1.2

Objectives of tbe Study

Theprimaryobjectiveofthisstudy is to develop and evaluat eanalternate method of fo recas ting base d on dynami c regression modell ingto forecast flows forthe Humbe rRiver Basin inweste rnNewfoundland.Thismodelwill be compared, us ing a statisticallysound meth od,with the deterministic modelcurrently in use. As well,descriptive andot he r ba c kgrou nd informatio non the basin andthedevelopmentof the SSARRmetho dwillbe present ed

1.3

O

utline

of Thesis

This thesis documentiscompo sed of six chapters.The firstchapter providesthe

backgroundandexplainstheneedforflowforecastinginthestudy area.Chapter 2 describes thestudyareaintennsofthephysiographicand hydrologicparametersrelevant tothestudy

objec tives and liststhehydrometri candclimate dataavailableforthestudyarea. The

proced ureused todescribe.analyseandprepare the datafordevelopment ofthetwo

forecasting methodsusedinthe studyispresented inChapter3.Thefirst sectio nofChapter

4 discusses the detenninistichydrologicmodelpresentlyusedbyNDO EL whilethe second

partdiscussesthebackgroundand developmentof thedynamicregression model.InChapter 5, the forecastedflowscalculatedbyeach of the modellingmethodsare presented and compared.Theconclusionsand recommendati onsare presentedinChapter6.

2

.

DESCRIPT

ION

OF T

HE

STUDY AREA

2

.1

Genera

l

TheHumberRiver-Basinislocatedon thewesternsideoftheislandof Newfou ndland

as showninFigure I."Thetotal drainage area measuredatthehydrometric stationonthe HWIlberRiveratHumber VillageBridgeis7860km!.Thewatershedisdrainedbytwomain

branches -theUpperHwnberRiverandGrandLake.bothofwhichdraininto Deer Lakeand

then into theBay ofIslandsviatheHumber River. TheUpper Humber Riverbasin, witha drainage areaof2 110km2measuredat thehyd rometri cstationnearReidville,originatesin GrasMome NationalPark and flowsin a sout herlydirection.This sectionofthe basinis in

arelativelynatu ral stateandflowsuncontrolled.The Grand Lake sectionof the basinhasa drainageareaof over 5000kID!. This sectionofthe basin is regulatedto produce hydroelect ricitywithitgeneratingplantthatoperatesatDeerLake Asecond, smaller hydroelectricdevelopment operates withinthebasinatHindsLake.

Theareasinthebasinwithc:ooccmrations of residentialdevelopment arelocated near tbe confluenceofthe two maiosubbasinsatDeerLake.or downstream alongthe Humber Rivet"betweenDeerLakeandComerBrook1bepresenceofresidential areaswitha history of floodinginwlnerabledownstream

reaches.

coupled with thepresenceof' the bydroelectric developments,providesthebasis forthenecessity of accurateflowforecastingin thebasin.

Gu

l

f of

S

t.

La

wrence

Corn

er

o

==-S

te

ph

e

nvi

ll

e

P

ort - oLlx-B osques

G

ra nd

Bonk

Figure 1-GeneralLocation of StudyArea

A

tlant

ic

Ocean

Bay

B

oy

2.2

Physiography

TheHumberRiverBasin is. for the most part, situatedina physiographic region called the Newfoundland Highlands (Bostock, 1970).This areais further broken down into four sub-regions called the Great Northern Highlands,Blow Me Down Mountains. Atlantic Upland of Newfoundland and the Grand lake lowlands.These areas are shown on Figure 2. (Sanford et al,1976)

The Great Northern Highlands form a barren mountainousplateau that extends northward along the Great Northern Peninsula from BOMe Bay and the lomond River Valley with elevations ranging to 180 to 800 m. Theinland surface of the highlands slopesgently

ina southeasterly direction towards theHumber Valley and White Bay.The Upper Humber River and the Main River flow along this slope flowing in a southeastwardlydirection.

The Blow Me DownHighlandsfonn an area of dissected plateaus and mountains that riseabruptly from the coast alongthe Gulf of 51. lawrence in the Bay of Islands to Trout River area The elevationsinthearea range from 550 m to 700 m Drainage from this area flows in a westerlydirection to the Gulf of S1. Lawrence.

TheAtlantic Upland of Newfoundland is a barren to sparselyforested plateau located between Grand Lake and Red Indian lake and extending northward to theBurlington Peninsula. Elevations in this area range from 400 m to 600 m.Thearea forms the drainage dividefor the two largest drainagebasins on the island- the HumberRiver to the westand the ExploitsRiverto the east.

TheGrandLakeLowlandsare locatedtowardsthecentreofthe Humber Riverbasin. Theselowlandsincludethe largestwater bodiesinthebasin:GrandLake. Sandy Lakeand DeerLake.

2.3

Surficia

l

Geology

Thesurficial geology within theHumber River watershedrangesfrombedrock outcrop ping,areasofglacialtills,and areas of sandsandgravelsto areas of organic soils.

Base don theavailableinformation, (Golder.1983) bedroc kisthemost commonsurficial geologyclassification type.Exposed bedrock formsextensive rockplains.knolls and ridges throughoutmuch ofthewatershed.Therock.in most cases, is covered by athinveneerof tillsoilsorconcealed by vegetationof either forest, scrubor peatbog. The areathat comprises the highlands of the LongRangeMountains, TopsailUplands and Burlington Peninsulaismostly exposedwith rocktalus or alluvium occurringonthe mountainslopes. Thesoil typesin the watershed.withsomeexceptionsalongtheHumberRivernearDeer Lake and alongtheHumberRiver, are generally not suitableforagriculturalusesdue 10 excessive soil moisture,andadverserelief because of steepnessor patternof slopes,stoniness and shallownessto bedrock.

Theglacialtills are found throughoutthe watershedwithlarge variabilityinthickness from one area toanother.The soils maybe foundas a thinveneeror extensivemoraine deposit overlying the bedrock.The compositionofthetills varyfrom grey siltysandor sand silt withintheLongRangeMount ains and Topsail Uplands,toredclayeysiltwithinthe

Humber RiverValley.There are variouslocal areasofliUcoverwhichare comprisedof unsubdividcddepositsofice contactsandandgravel.Ingeneral. thecompositionofalltiUs closdy resemblethelithologyof meunderlyingbedrock.

Thesandandgraveldepo sits foundwithinthestudyarea are outwash andfluvial in originandare generally confined tostream and river valleys.Themajorsandandgravel depositsarefoundintheDeerLake, Upper HUIIIberRiverValley,and theSandyLake-Birch y

Lakeareas. Additionalburieddeposits of sand andgravel occur at variouspoints interstratified within the till deposits.

Peat depositsarefoundcommonly throughout the watershedin areas with poor

surfacedrainage.These deposits occur extensivelyon the barrenTop sailUplands justsouth

of Grand Lake.Peat accumulationsinthefonnofhighmoorbogsandstring bogs arefou nd onthehighlandplateausoftheLong RAngeMountains.Peat depositscanattainthicknesses of several metresoverlyingbedrockortilldepo sits.Figure 2 shows the surficial geologyand

2

.4

C

limate

TheHumberRiverBasinhas atemperate,marineclimatethatis influencedbytheGulf of St. LawrencetothewestandtheLongRangeMountainsto theeast.Based ondatafrom the long tennclimatestations in thebasin (Atmospheric Environment Service,1981&1991) the averageannualtemperaturesrangefrom alowof2.9· C atBaieVerteto ahigh of5.I·C atCome r Brook. Asummaryof the averagedaily temperatu resandaverage annual precipitat ionfor thelong tenn stationsinand around thebasinareshowninTableI.

The annual precipitationranges from alowof943.5romatBadger,to ahigh of 1470 nun at Woody Point.Wood yPointislocated on the westerncoastwhileBadger islocated farinlandaway from the coastal influence.Theuplandareas ofthe LongRangeMountains andthe Topsailshave greaterprecipitation due to orographic effects. Theamountof precipitati ondecreasesinthe northeastern directionas indicated by Badge randSpringdale with 94].5 and967.1 nun respectively.For allstations,precipitation islowest duringthe months of April and May while thehighestamountsare recordedin the fall.

Table1-LoegTerm ClimateData - HumberRiverBasin

Station AnnualPrecipitation AverageDailyTempera tur e

(mm) ("C) 1951-1980 1961·1990 1951·1980 1961-1990 Badger 943.5 nI. 3.9 nI. Baieverte 1064.7 1100.8 2.9 3.0 Buchans 101 1.5 1128.8 3.5 34 Comer Brook 1133.5 1186.0 5.1 5.2 0""lake 1033.1 106 1.5 4.1 4.1

Deer LakeAirpo rt 1023.2 1034.3 3.3 3.4

ExploitsDam 1099.0 1099.5 3.2 3.2

RockyHarbour 1199.1 nI. 42 nI.

Springdale 967.1 1010.3 3.9 3.8

StephenviUe 1166.5 1272.1 4.8 4.7

WoodyPoint 1410.0 nI. 4. nI.

(StationlocationsareshownonFiguresIor9)

2

.5

F

orest C

over

TheHumber River Basiniswithinaclassificati onbandcalledtheBoreal Forest Region of Canada (Ro we,1972 ).Thisgeneralregionis subdividedintotwosubregions. Predominantl yFo rest BorealRegionandFo rest andBarren BorealRegion.TheHumber River watershedcontains areaswithinboth ofthesesubregions.Figure3illustratestheforest andvegetativeco verwithin thebasin.

ThedominanttreespeciesincludeWhiteSpruce.Black Spruce, Balsam Fir withareas ofTamarack,. WhitePine.WhiteBirch.Yellowbirch,Tremb lingAspenandBalsam Poplar. TheforestcoverintheHumberBasinisdividedimo fourmajorclasses:mature forest. scrub

land.

barrenandpeatbog.Matureforestisthe most common forest cove!"class within the study area.This forest classification generally occursinthe areas thathavethethic kest glacial till layer above the bedrock.However.mostoftbe tree coverisfairly sparsedueto thethinveneertillsoilsandexposedbedrock.Thedomin ant tree species within this classare Balsam FirandBlac kSpruce, with White Birc h.Trembling Aspen and Balsam Po plaralso beingfound.Overall, sparse, matur eforest cover isfoundin all subwate rsheds. Themost denselytreedarea withinthewatershedisloc ateddo wnstr eam ofDeer Lake to the Community ofSteadyBroo k whereBalsamFirand Black Spruce dominatewith softwood scrubland. WhiteBircb and peat bogalsobeingfou nd.Extensive logginghas beencarried out. and continues to becarriedout.inthe basin to supportthe paper millin Comer Brook. Theremainder ofthestudy area contains softwood and hardwood saub lands, rock barrensand peatbogs.Ascan be expected, the vegetationclassesare c10sdy related tothe soiltype,soildepthandmoisture regime.Well vegetated areas are usually smallin area and scattered. Peatbogs are commonin the highland plateaus,&long river valleys and around lakes withi nthelo wlands

13

I

.

'

!

~

:

"

••

~

_:

:

3

.

DA

TA

PREPARATION

3

.1

Availa

ble

Da

ta

3.1.1 AESOimateData

Thelo ng term climate stationsin andnear the basin arelistedinTabl e1in Chapter 2.4.ThesestationsareoperatedbyEnvironmentCanada'sAtmosphericEnvironmentService (AES),andforthe mostpart.acelocated outsidethe boundariesofthebasinand consequ ently are notsuitablylocat edforshorttermflow forecasting.Also.the data available from these stations is notavailablein nearrealtimesince the gaug es.except the Airportsites. areread manuallybyobservers.Arrang ement scanbe mad e with AES to obt ain thedatabut theda tamust be manually enter ed intothecomputer.

3.1.2 WSCFlowlStage

Environmen t Canada.,throughitsWat er Survey of Canada

(Wsq

branchopera tes a series ofbydromctricstatio nsinandaround the basin under acost sharing agreementwith NOOEL.The80 w dataispublished yearlyinCD-ROM forma tfnDowing a comprehensive qualitycontrolreview.Thedata isnotread ily availablethroughWSCinnearreaJ time.A summaryofthelongtenn stationsinthebasinispresentedinTable2. One important observationfrom this dataisthatall afthemaximuminstan taneous flo ws occu rred du ring the springsno wm elt runoff period.

Table Z -Summary ofHydrometricData - HwnberRiverBasin SlationName wsccee

,...

""""'

'''

... AmuoI

...

_-('on')

...

"""""""

(m '/s)

...

,F1ow (m'lsl

Lewascecbjeech 02YK002 470 1952·1967 176 175

Brook(LEWA) 1912-prcsc:nt (04 f9l)

HindsUkeatOutlet 02YK004 630 1956-1979 16.5

'36

(HIND) (04nl)

Sbcffieid Brookal 02YKOOli

r

eo

1955-1966 99 934

SheflicldLake (0 SJ60)

(SHEf)

ShcflIc ldBrookneu 02YKOO5 )91 1972 -preocn1 12.0 121

TCH(SHU') (05187)

""""'-

02YMOO2 238 1961· I978 '.7 '6.7 DiWfSion lOBarclty (QSn5) Uko(1NDn IndianBrook~ 02YM<JO< 238

'

--

6.' Sl4

Bircbyl.ake(IND 1) (OSI9l)

Upper Humba River 02YUlOI '108

_'

_{- " -}

12.2 1060

natReid\.ille IllMW)

(IlE1D)

Uppcl'"Humba River O'YlOOlI

'"

'

...

"

.

J02

aboYeBlac:kBrook (06J'95)

(BLAC)

Humber RiveraI 02Y1.OOl 7860 198 2-pn:scm

'"

'87

HumbaViUage (06J95)

(VlLL)

(See Figure9forstation locations)

3.1.3 NcarRealTimeDa1a

Ncarrealtimedata are collected at the stations usingDataCollectio nPlatfonns (OCP)'s_Thedau.aretelemeteredviasatellite toanearth receivi ng stationwheretheyare retrieved byNDOEL via modem. These stationsareoperatedandmaintai nedby Environment Canadaunderacostsharingagreementbetween Environm entCanada,NDOEL andtheDeerLakePowerCompany.The data retrieval, processi ng, and dissemination of the nearreal timedataiscarriedout byNOOEL.

Theraw data fromthesitesare given only a brief quality controlreviewprior to archivingin databasefiles

3.2

D

ata

R

eview

Asnoted above.the dataavailable fortheHumber RrverBasinorigina te fromthree

soon:es.

namelyAES forlo ng term climatedata.,WSC for longterm hydrometricdata. and NDOELfornearrealtimeclimateandhydromeuic data,TheAESdataisnotreadily acces5lble onarealtimebasisandWSCdoesnotpublishthedatauntil aboutsixmonths after the dataarecollected

Sinceanyflow forecasti ngsystem forthebasin will requirenear real time data.,the data from NDOEL wasselectedasthebasisforthe modeldev elopment.The maincause for concernin usingthis data isthatit is not subjecttotheextens ivequalitycontrol reviewand

correction like the AESandWSC data. For thisreason,thedata review forthe NDOEL data willconcentra te onidentifying anyproblemswith the data

Thelintstepinreviewinganydatasetistoplotthedata.Asample plot ofthe data

fortheUpperHumberRivernearReidvilleisshowninFigure:4andaplotof theprecipitat ion and temperature data for Grand Lakeon Glover bland isshown in FigureS.Thisinitial reviewaidedin thetaskofidentifying incorrectdata duetoinstrument error.outliers or the presenceof missing datL Anyproblemsnotedwere correctedinthedata files.Figures 4and 5areillustrative ofthenatureof the data. Thedatareviewwas doneprimarilyusing the computerdisplayscreen Plotsfor the remainder of thestationsusedin thisstudyare presentedinAppendixA

The nextstepinthedatareviewwastocalculatethedescriptive statistics forthedata SYSTATsoftware(SYSTATInc,1991) was usedfor this purpose The results of this analysis is given inTables 3-6

The next step inthereview of the data

was

to comparethe quality controlled data from the WSC with Noaa 'snearreal time data.Asshownintheexample in Figure 6. thereisa definitedifferencein the two datasets that occursduring the winterseason. The apparenthigherflows during thewinterseasonwere believed. andwerelater confirmed, (Baker.1996) tobearcsuItofan icetxJVa"inthesream The instrument at the site measures waterlevelwhichisconvenedtoa flowbased on a ratingcurvedevelopedusing openwater conditions.Thiscausesanerroneous ly high waterlevel and consequentlyanerro neo usly higherflow.Theeffectwasnot ed atallof the gauges.withthe exceptionoftwo.the

LewaseccbjcechBrookandHunV:lerRMratHumber Vl1lageBridge The comparisonpiau

fortheremainderof the stationsispresentedinAppendix B.

At thispointthepossibilityof correctin g for theicecoverwas investigated.The

procedureusedbyEnvironmentCanada to correctforthis backwater effect involves a graphicaltec hniquesupportedbyonsite reconnaissance and knowledgeofDeUby basi nsto adjustfOl" theiceeffect.Sincethistypeof correctioncannotbecarriedout on real timedata

due to the unavailability of fieldinfonnationandtimeconstrai nts.the only cho ice was to

proceedwiththe analysisusing therealtimedata, with the knowledge thatther e isan

inaccura cyin the data.

(SI£ W) MOI.:::l

rtgW'e4·Sample Flow Dillfrom OCP Station 19

Grand Lake on Glover Island

f ..

J

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01-~"'*"2:llUl...-a

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ZU_:rt..., 11.1'_1 ~12.1'_n ...IJ1-f_

~ ~ ~ C ~ ~ ~ ~ ' ~ ~ l ~ ~ ~ ' ~ ~ l ~ ~ ~ . ~ a

.-Fi

gure

5 - S

ample

T

emperature a

nd Pr

ecipitation

D

ata

Upper Humber River at Reidville Flow Data

-_

....

, _....-..

...

,...,-

_

..

_

_

..

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Year

1

_

OCP0." _INSC0... . INSC-DCP

I

Figure 6-WSC and DCP Data Comparison

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4

.

METHODOLOGY

This sectionwilldiscussthetwomethods used inthis studyto forecastflowsfor one, two and three days ahead forthe HumberRiverBasin. Part onewillfocus on the deterministicmodel (SSARR),its history,application[0the studybasinand the flow forecasts for specificevents.. Thesecondsectionwill pro vide similarinfonna tionforthedynamic regression method

4.1

Deterministi

c

Model (

SSARR)

4.1.1 Model Description 4.1.1. 1 History

TheSSARR modelwasdevelopedin1956bythe USCorpsof Engineers to analyse and forecast flows for thenaturalhydrologicand contro lled reservoir systems intheNorth

PacificDivision area. Thisarea included the Columbia River Systemin theUS andCanada. coastal rivers in WesternOregonandWashingt on, and the Stateof AJaska.Since thattime, theSSARRModelhasbeen updatedandmadecompatibleforPC use andhas beenwidely appliedthroughout the world.

Oneapplicationthatis similartothe Humber Basinin terms ofgeogr aphic. climatic andoperational characteristics isthe St. John River Basin inNew Brunswick.SSARRwas selectedfor this basin in 1973 because itwasbeliev ed tobe the bestavailableat that time

(fang&Lockhart,1983) .Themodelcontinuestobeused for flow forecasti ng forthat basin up tothe presentday.

Themodel

was

selected for theHumberRiverbasinforthe followi ngreasons: (Cumming Cock burn,1984)

The modelis simpleinstructureanduses readily availabledatacompared with many othercontinuoussimulation mod els;

The relati velyfastsimulatio ntimewhichallows forlow computational time compared with other models;

The benefit of transferringmodelparametersandexperie ncefromother Cana dian application s such

as

the St.John Rivernoted above; The excellentreservoir routing capabilities;

Variablecomputatio naltimestepsare possible , ie.a mixtur e ofweek.lyand/or daily;

Thecapabilitytoaccount forthearealdistribution ofsno wm e lt; The modelisnon-proprietaryandhasbeen well pro ven ina number of practicalapplicati ons;

Themodelis wide ly usedinfloodfor ecasting;and An interactivevers ionofthe modelisavailable

4.1.1.2 GeneralDescription

The SSARR modelhas beendevelopedtodescribe themaincomponents of the hydrologiccycle.Itwasconceived as a closed hydrologicsystemin whichthe waterbudget is definedbymeteorolo gicinputs(rainfall and/orsnowmelt)and hydrologicoutputs suchas runoff. soilstorage and evapouanspirati onlosses.Themodel is derivedsothatthemain

co mponentsof thehydrologiccycle arerepresentedin asimplified but rigorouslyapplied

manner. The parameters used in the modelallowfor an extremelyflexible meansof

representing the varioushydrologic components.Thisunique featur eallowsthe SSARR model to be appliedto virtuallyanydrainage basinor hydrologic system. Adetailed

discussion ofthe algorithms and data processing techniquesutilized in theSSARR model is foundin theUsers Manual (Davis,1991)

A schematicrepresentation of the basic elementsof the SSARR watershedmodel is

presentedin Figure 7.

TheSSARR programcarriesout thefollowingthree distinctfunctions: Itcalculates thenatural dischargesfor each ofthe elementary sub-basins

withinasubwatershed that isselectedbytheuserfor itsrelatively

homogeneoushydrologicalcharacteristics

It calculates the naturaldischarges as wellas routing and addinghydrographs

through riverreachesand natural lakes. up totheexit pointofthe entire

watershed.

It calculates the variations in discharge caused by the regulationofartificial

reservoirs forhydroelectricgeneration orflood controloperations

4.1.1.3 Hydrologic PrinciplesUtilizedin the SSARRModel Therepresentationof hydrologicrunoff processesin a watershed modelishighly

subjective.No twohydrologistslook at watershed nmoffprocessesin exactlythe same light. Nevertheless,there are some underlying principlesthatmust bepreserved in the formulation

of a deterministic hydrologicwatershedmodel.Theseincludethelogical accountingof each

of the basicelementsin the hydrologiccycle.includingrainfall,snowmelt,interceptio n. soil

moistu re.intertlow.groundwaterrecharge.evapotranspiration, andthevarious time delay processes.These elements must be accounted for while includingthe abilityto maintain co ntinuity of each of theprocessesandto represent each by objective functions that relate

them to observedhydrometeorologicalparameters.Themain differencebetween the ways

variousmodels accountforthese processesliesinthe level of complexitythat each model

uses to representaparticular process.

Thestreamflow routingfunctionscontainedin the SSARR modelprovidea

generalizedsystem forsolvingthe unsteadyflow conditionsinriver channelswhere

streamflowand channel storageeffects are related.eitheratone pointor at a series of points

along ariver system.In principle.themethod involvesadirect solutionof a storage-flow relationship involvedinmaintaining continuityof streamflow and storage in eachelementof

the river,using a procedure that solves therelationshipsinfiniteelementsoft ime and river 29

reach.This involves a completelygeneral and flexiblemethodforsolvingthe flow routing

equationswhichcanbeappliedinmany waysdepending uponthetype ofbasic dataavailable, and the conditionsof the riversystemwith respect to backwatereffects from variablestage

dischargeeffects. suchas tidal fluctuations or reservoir fluctuations

The SSARR model

wasdesigned

to includetheeffectsof reservoirs or other water

control eJements withinthe streamflow simulation process.Reservoirsmaybedescribed for

anylocationinariversystem. whereby inflows are definedfromsingleormultipletributaries, derived either from wate rshedsimulationfor river basinsupstream, or fromspecifiedflows

as a timeseries.or a combinationof thetwo.

Outflowsfrom reservoirs are detennined onthe basis of specifiedoperating

conditions.In order to provide a once-throughprocessforthesystem as a whole.including

allnatural effects and thosereJatedto humanintervention.theprocessing ofhydrau lic

conditio nsatreservoirs is performedsequentially with all otherelementsin the riverbasin

simulation.

~

-

-

---

-~

---

-

_ ._

~

'rE3

.. __ - - CIJr_

Figure7-SSARRSchematicwithSnowbandOption

4.1.1.4 Structure

Thissection defines and discusses hydrologicinput parametersingeneral terms.

Thespecific data input and parameter values used for various sub-watershedsof the

Humber River in this study are presented and discussed inChapter4.1.2

Net precipitati on inpul(WP) -Theaverage net precipitation value for a drainage basin or hydrologicunit is derived as a weighteddaily or period amount from a series of individuallyreponed or observed values.The weightingisgeneralized,andeachstation

maybeassigned its individualweighting value.The station weights may he determined onthebasis of previously derived relationshipsbetween station and basin normal annual or normal seasonal precipitation;or the weighting values may be derived onan areal basis using the Thiessen Polygonor other similartechnique.

The total precipitation ona watershed is computedfrom period precipitation

amountsat one ormore stations by:

Where

Pl.. W1+... .•• •• •.P~..W~

(I)

Period precipitationamounts at Stations1, 2,

respectively,in inches

Weights applied to the station precipitation 32

Total numberof stations. amaximumofJ O stations

Wp_ weightedperiodNetWatenhed Precipitationinches

Basically.there aretwogenen..loptionsfortheofsnowmelt.namely: the temperature indexmethod;and

theuseof generalizedequations of snowmdtasdetermined bythethermal budgetofheallossand gaintothesnowp ack.

The temp eratureindex methodisusuallyusedfordaily forecastingapplications,

whereasthedetailedenergybudgetapproachismore appropriate for design floodcalculations

whenextensivewatersheddataisavailable.By eithe r method.dailyor periodvaluesof effective snowmeltrunoffvalues are computedas a timeseries,as afunction of appro priate

meteorologicalvalues

Thesecond option hastheadvantage ofbeingmorepreciseand detailed,but alsohas the disadvantageof requiringsomedatawhichis availableat only a very limited numberof stations.Examplesofsuch data are:

Differencebetweenairtemperature measuredet]metresabovethesnow surfaceandsnow surface temperaturein degreesCelsius(-C).Thesnow surfacetemperature is assumedto be O-C;

Difference betwee nthe dewpointtemperature measured ]metres above the

surface ofthesnowandthetemperatureof thesnowsurface(O-C); Above thesurfaceof thesnow and the temperatureof the snowsurface

(O"C);

Wandvelocity at ISmetres abovethe snow,in kilometr esper hour, Solarradiationona horizontalsurface.inI~

Average snow surfacealbedo;

Basin sbortwaveradiation mdt factor; Averag eforest canopy cover,and Convectio n-eo ndensatio n meltfacto r.

In additiontothetwo optio ns of snowmelt equationsavailabletotheuser.two additional options forthesimulationof snow cover arealsoavailable.These are:

SnowCoverDepletion;and Snow Band Option

WIth thesnowcoverdeplet ion option, snow coverisdiminished in thickness.andin swfaceareaduringthesnowmeltseason.However.two disadvantagesofthisoptio narethat snowfallduringthe cakul atio nperiodisnotaddedto the existingsnow coverandsecondly.

itisnecessaryto enterat thebeginning oftheperiod of calculation. thequantity of snow whichwill effectivelyrun off after the melt.However.thisoptionhas been showntobe usefulinthefloodforecasti ngmode.The snow band option allowsthe userto separatethe subwatersh edinto different"bands" acco rding to elevation with thetempera tures being loweredsystematicallywithincreased elevation s, as illustratedinFigure 7 SoilMoistureIndcs: (SM I)- Thesoil moisture indexused in theSSARR model represents a weightedmean basinvalueof thewater storedinthe soilmantlethat can beremoved by plantroots throughtranspinl.tionand naturalevapo ratio n.It doesnot includethe pan. ofthe

soil moisture content that exists at the permanent wilting point.The computationofthe changes in soil moisture indexvalues are based on the increasesresultingfrom rainfall snowmelt,andthe decreasesbythe evapotranspirationprocess.Increasesinthe soil moisture index values result ina"permanent"lossto runoffin thewater balance forthe basin asa whole.The upperlimitof thesoil moisture index is consideredtobeitsfieldcapacity,which is equivalent tothe capillarymoistureholding capacity,or thetotal amountof water which canbeheld undertheforce ofgravityundernaturalconditions. Thus,thesoil moisture index isacontinuouslyvarying parameterthat mayrange from avalueof zero when the soil moistur ehas been reduced tothe"wilting point"bythe evapotranspiration process,to a maximumvalue representedbythe field capacityof the soilfor thebasinasawhole. Evapotranspiration Index(Ell)-Theevapotran spirationindex (Ell)usedin the SSARR modelisaweighted basin mean daily value ofthe waterlost to theatmos phere bythe evapotranspiratio n process.Transpiration, soilevaporation andevaporationoffree water from thepiantorforest coverare consideredtoacttogethertoproduce thelossesby evapotrans piration. Sincethe evapotranspiration lossisphysicallytheresu ltofchangeof sta teof water fromthe liquidto vapour phase,theprocess of evapo transpiration requires energyforthetransformation,andis,therefore,dependentupon asourceofenergy,fromthe atmosphere.

Inthemodelthepotentialevapotranspiration maybe computed byeither oftwobasic methods,namely:

meandaily amountsbased onmeaDmonthlyvalues whicharetypicalfor a given hydrologicregime;or

meandailyairtemperatureor dewpointtemperatures, ordailysolar radiation amounts.

Thedailycomputed amounts are adjusted in either casebya functionto account for dailyor theselectedperiodrainfaII thatwouldreducethe potential rate ofevapotranspiration. Intheapplicati on of the SSARR

model.

themean daily amounts computedthrough use of meanmonthlyamountseremost commo nly used.

Rannow(nmt ratioDIndex (BII) - The BaseflowInfiltrationIndex usedin the SSARR waters hed mod elprovides ameansfor computing therelative proportio nof thewater availableinthesurfacelayers of the soilmantlethat entersthe ground wateraquifersas deep percolation- Underthe principleof"generated runoff",as defined above, all water whichis

not lostto the atmosphereby evapotranspiration. or the pennanentloss by soil moisture increase,isavailable to runoffwrth atimedelayfunction. ConceptuaUy,themodel considers the timedelay to occur inthreezoces, namdy surface, sub-surface and basetlow.Tbelong time delay caused by base flow infiltration rep resents that portionofthewater which is in transitory storage forseven1 months (orpossibly years undercertaincircumstances). Su rine-S ub-Su rfaceFlow lodes(S-SS)- In the model,thesurfacesub-surface (5- 55) flowseparationindex deals with the water excess which is genera tedfromthe residual after soil moisture andtranspiration lossesand base 80w infiltrationhavebeensatisfied. Nonn ally, the"direct"runoff is considered tobetheresultoftbepercolation or-free-waterthroughthe

uppcrlayersofthesoilmantJe.Thiscouldbeinthezoneup to a maximum of depth of SOem belowtheground!Wfac:etermed as~flow.Whenthe waterinput rate exceedsthe capacity of the sub-surface zone to transmit waterundergravitationalforce.theresidual

waterexcess amountisconsidered to occurdirectlyon the ground surfaceor the upper few

centimetresof the soil marnle.1be surfitce..-sub-surface (S-55) flow separation is a means for definingthe rdativeportionofthe direct ruootfthatcontributes to each portion,as afunction of input rate

1beS-S5functionisusuallyspecifiedasa nonlinearfunctionwhereby thelowerrates of input pro vide waterexcessprimarily insub-surfacezoneswhilehighinputrates are predominantlyon thesurfacerunoff.The time delayfunctionsfor routingsurfaceandsu b-surface flo w are specifiedto representthe difference instoragetimes foreach of the two

Waltnhtd outflo",InInsfonnarioobypolyphaseroutin gfor eachRowcompone ntinput (NP.1'5)-Thewater excessvalues computed for each timeperiodineachof thethreeflow components (surfi1ce,sub-swface and bascflow) mustbetransformed from values computed as inputrates to time-distributedvalues of streamflow_ In the SSARR model, this transformationisaccomplishedbypolyphase routing, whereby the inputratesexpressedas anperperiodare converted to equivalentvaluesof steady-state outflow,expressed as cubic metrespersecondforthe particulardrainage area.The routingis performed throu ghtheuse of the flowcontin uity equat ionssetfonh intheSSARRusersmanual (Davis,1991).

Theuse ofpolyphaserou tingfoc thistypeoftransfocmationhasseveraladvantages for computerizedsimulatiooofstreamflowfromwatersheds.Theseinclude:

simplicityof computation;

ease of applicatiooin trialand error reconstitution studiesfor determining basinrunoffcharacteristics;

therelativelysmallamountofinfonnation requiredto storeinthecomputer, inorder torepr esentthe basinrunoffcharact eristics;

thecompletely flexiblemeansfor representin gtimedelaystorunoffeither for short termfloodrunoffon relativelysmalltributaries.or for long-termbase flow on groundwater dischargefor largeriversystem;

the convenient means for preservi ngthecontinuityof flow at any specified pointintime.for"stepaction-or-instantreplay-capabilities. panicularlyin its use forday-t o-da y streamflow forecasting;

thef1e.d>ilityof providingWtuallyanydesiredshapeof runoff characteristics suchas aunit distributionof known clw"acteristics;

theassum:lpres.crvation ofc:ont:im.rityof fJow foranycomputed.runoffexcess,

and;

the abilityto representnon-linear response forrunoff from awate rshed

4.1.1.5 MethodologyforCalibration and Validation

When usingthe snow band option inthe SSARR model a typical subbasin requiresup to68 parameterstodescribeitshydrologiccharacteristics.Of these parameters.,up to47 are pennanent characteristics of the modelandincludethestation nameand other parametersthat canbemeasured, such as the drainage

area.

Theremai ning parametersmust be calibratedor the defaults in themodelaccepted.

Ingeneral ,the optimization of the variousparameters isnormal1yaccomplishedby trial-and-errorreco nstitution studiesof historicalstreamflow data. These studies are generally performed usingseveralyears of histori caldata.Thevario us parametersaretested to achieve thebestfitof computedandobserved streamflow.Itisnormally assumed thatthe physicalfactorsaffecting runoff aceno nchanging overa periodofyears ,sothat the paramete rsandfunctionsused in themodel are fixed as agiven setof values for the entire studyperiod.Thedegreeof fit betweencomputed and historicalstreamflowisdetermined eit hervisually byinspectionof graphical plots of the dataorby graphicalorstatistic al methods.Theprincipalobjectiveis to achieveco nsistencyover a widerangeof hydrologic conditionsto eliminatebias between high and low periodsofstreamflow andto achieve relativelyuniform consistencyfortheyears being studied.

Theove rall waterbalance for particular study areas shouldrepresentas closelyas possiblethe knownorexpectedvalues ofprecipitation,evapotranspiratio n. soil moisture and groundwaterconditio nthatarecharacteristic for the climatologicaland hydrolo gicalregime

of the area. The main objecti ve of reconstitu tionstudiesisfirUtoachieve awaterbalance byadjusting thefollowing parameters:

precipitationweightingforestimatingbasinprecipitationfrom indexstation values;

S~function,intermsoftotal soilmoistureindexvaluesandtheshapeofthe SMI function;

En

values.basedonobserved orestimated amountswhich pro pertyreflect

theseaso nal ordaily variation;and

a

u

function. representing theportion

crwerer

inputwhich contributestobase flow.

Whentheoverallwaterbalanceisachieved, therefinementsintiming can betaken intoaccountbyadjustingthepolyphase routing parameters foreachcomponen t (surface. subsurface andbaseflow),andbyadjustingthe S-SS flow separation function.

OnceasirrulatedBowseriesisobtainedusingthisproced ureit iscomparedwiththe actual hydrograph forthebasin.This comparisonisthenreviewedandtheparameters are adjusted usingthe following guidelines

Ifthesimulated hydrographis consisten tly higher (or lower)thantheactual andthedifferenceismorepronounced over time, then the estimation for evaporationmaybetoohigh(or low) .Theslopeof the SMl curveshouldbe

increased(ordecreased).

lfthe slopeof the simulated ttydrographrecessioncurve ishigher (orlo we r) thantheactual hydrograph, thenthebaseflowistoo low (orhigh) The slope

of the GIl curvesho uldbereduced (orincreased)

If thesimulated maximum dischargeis higher(orlo wer) than the recorded

maximum dischargesand, if the runol'fvo lumesare close (indicatingthat the SMI curveis good),thensurface runoff is toolarge (ortoo small) with resp ectto the subsurfaceflow.Theslo pe of the SS-S curve shouldbe

reduced(or increased).

Ifthe simulatedhydrographis obviouslyhigherthan the recorded hydrograph foUowing a light rainfallin thesimulationperiod,then theinitialSMIsho uld

bereduced.

Ifthe shapeof the simulatedhydrograp h is sharper thanthe record ed

hydrographfollowinga light rainfall inthesimulation period.then the

maximum for the BII curve shouldbe increased

Once the model has been calibrate dfor rainfallonlyevents,the snowmeltparam eters

areadjustedusingthefollowingadditionalguidelines

If theupward slope of thesimulated hydrographistooflat (ortoo sharp), then the meltra te shouldbeincreased(or decreased).

If the simulatedflood startslater than the recordedflow s,thenthe base temperatureshouldbe increased.

lfthevotume of thesimulatedbydrograpb is toolarge (ortoo small),then the

weigh tingof thesnowcourseorprecipitationstations mayneed tobe

decreased(or increased)

Thisdescrip tionisabriefdescriptionoftbe stepsnecessary to calibrate the SSARR

model.However,itisotMousthatan adequate calibrationofthemoddrequiresa great deal

of know ledgeabout themod elandaboutthe watershed.Itshould also be noted that the

calibrationisuser driven andrequ iresfrequent adjustmentstobe used effectivelyin an

operationalforecastingmode

4.1.1.6 ModelSetu pfortheHumberRiverBasin

TheinitialsetupfortheSSARRmodel

was

carriedout as partof the studytodevelop

800driskareas(Cumming Cockburn,1984).Further development wascarriedoutto assess

thepcssibilityof usingtheSSARR model.toforecastDows onthe Humber Riverusingthe

highfloweventthatOCCUlTedinJune 19&4(CummingCockburn., 1985).Bothofthese studies recommended that the datacollectionnetWOrkrequiredimprovementifthe model.was

toproduceaccurateflowforecast s.In1990under a costsharingagreement between

Environment Canada,Newfou ndland Department of Environmentand Landsand the Deer

LakePower Companythe datacollectionnetw ork was improved.These improve ments

included theinstallatio nof additional stations, the additio noftemp erature andprecipitation

sensorsto existingsta tionsand the installationof transmittersfornearreal time data

acquisition.Oncedatacollection networkexpansionwasco mpleted,additional work was

carriedoutto developthe proceduresto implementthe SSARR model for flow forecasting

(Cumming Cockburn,1995).The studyalsoused the April 1991 version of the SSARR

model.'Thechangesin thisversionincludedmicrocomputerprocessingand theuse of metric

units.Alsoincluded

was

a recalibration oflhe modeltoutilise the new data providedby the

expandeddatacollectionnetwork.Thefollowingparagraphs summarize thesetu p procedure s

carried out through all of these studies

Thefirststep in applyingtheSSARR modelto the basinwas to identifyand isolat e the various subwatersbeds , reservoirs and channelreaches required to facilitate model calibrationandvalida tion usingobserveddischargedata.Subwatershed swere selected by

separating the total watershed intorelatively homogeneoushydrologicunits. Consideration

was

also given tothemeteorologicand hydrometric data availablefora givensubwatershed

to aid inthe calibrationandvalidationof themodel.In additiontotheselection of the

sub-watersheds,the reservoirsand river reacheswhichhave asignificantimpacton the flows to

down streamhydrometricgaugeswerealsoidentified and modelledinorder to give an

accuraterepresentation ofthehydrologicand hydraulicresponseof thesystem Figure8 is the basin map with the SSARRsubbasin discretization

The main elementsof the HumberRiver watershedarerepresentedin the SSARR

modelby11 subbasins,two reservoirsand one lake. Figure10shows aschematic

representation ofthebasin .

Meteo ro logiclopa l Data

Oneof theusefulfeaturesoftheSSARRmodel isthatItallowsthedistnbutionof data from a number ofmeteo rologic stationsto the subbasinsdefined in themodel.This capabilityispartic:uIartybd.pfulmrepresc:atiogthe hydrologicregimesofl arge basins. likethe HumberRiver.sinceit accountsfor thespatial variationsofme meteorologicparameters

Theinitial hydrot echni calstudyforthebasinfoundthatthere was"amarginally sufficient amount of meteor ologicdata availablefortheHumberRiverwatersh edwhichis conside red tobe suitable for hydrologicmod elling viathe SSARR model." (Cumming Cockburn,1984 ) At that timenoneofthe data wasrelemereredtoace ntr allo ca tionrequiring theupgrading of thesystem topermit usingthe SSARR model foroperational flow forecasting.Theclimate station locati onsare listedinTable7andshown on Figure 9. Hydro logi c Inpu t Data

Many of thehydrologic param eters inthe SSARR mod elare determined duringthe initialmodel setup.Someof thcie parameters areconsidered permanentcharacteristic ofthe model.includingsuchthingsasthe drainagearea, andthe altitu de-area relati o nship asshown inTable 8.Thesnowb andmodeloption

wasu

sed ratherthanthedepletio n optionused in the 1984 study.Thesnowbandoption betterrepresentsthesnowpackaccumulation-depletion char acteri sticsof the HumberBasinandwas recommendedbythemodel develop er. (Cumming Cockburn.1995)

Table7-Climate Station Locations - Humbe rRiverBasin

Atmosp he ricEnv ironm en tService Departm ent ofEnvironment and Labo u r

Station AES 10 No SSARR Station Name DCP

_S~~

N"",

Cod, Platfo nn ID

Deer Lake 8401500 1500 Upper Humber 4812C702 BLAC

above Black Brook

Buchans 8400698 0698 Grand

"

ok,

o

n

480FC3FA GLGI Glover Island

Comer Brook Lake 48001066 CDRN at Outlet

Burgee Road near 480FB56A BURG Buchan'sAccess

Grand

"ok,

at 48128192 GLSW

Southwest End

Indian Brook 480CFl6E lND!

Diversion

Sandy

"ok,

at 4812A2E4 SAND HowleyRoad

Themean dailyevaporation amounts werebased on the mean monthly values.The mean monthlyamounts wereobtainedfrom isohyetal maps.(Environment Canada, 1970).

The values ranged from 0.25mm1day to 3.3mm1day with an average of1.4 mm/day.These values wereadjustedas recommendedinthe SSARR manualusing a function to accountfor daily rainfallwhich wouldtend to reduce potential evaporation amounts

Figure

to-

Basin Sc:hematic - SSARR Model 48

NodeSlnvnatIonPoint

LaKe

Table

a

.

Subbasin Cban cteristics

s..~Codoo-.dN_

....

...

"'""

ll.ouIet (_ '

WIIOO-I...-ueocb;<a:hBnd

".

IAS·700 WIIOI-HinohLaU

""

198-liSO WI 102 . ShclTJdd.RiYer

""

99_S40 WI 10).lndianBroo lt;Divcnion ass lU.)90 WII04 - Upper Hum berRiYeraboveReid...dle 2108 lS.li8S

W2IOC1.GfandLaUWc:a:

_'

_'''

n

./i4C)

W2101.GnndLaUCCftCnll sse

n

.640

W2102 •GnDd LaUEaa

"

..

1S.S68

W2104.I..oaIlInllowOawnstJa,m a(GnndlAU

,,,

so

.

101 W210S.I..oaIlInflow ~DccrLaU

...

.1S.,tSS W2106 ·lDCIIl fDt"'* ~ Conlel'Bmok

_'

_"

2.S46

Area -Eleva lion Relati onship

Thearea elevationrelationshi pisinput to theSSARRmodelto allowadjustmentsin themodelforchangesinthe temperature as elevationsinthe basin change relativeto climate stations.TherelationshipisshowninFigure II.

Att

ttude -

Area Re

lationship

283 325 475 650 1000 1500 2000 2250

2SO 284 400 500 750 1250 1750 2100

Albtude(Feetabove sealevllll)

[

_l.B"OA o-l-IrOS .SH:F aN) ..RED ·-tJ.·GRANJV

I

• GRA.'C ...GRAN:: ...GRAN:YS(7ca:R ....COf,N

Figure11-Altitude-AreaRelation ship 50

4.1.1.7 Calibration and Verification

Thecalibntted paramctendevelopedbyCumming Cockburn (CummingCockburn. 19(5)weecsedas a basisforthisstudy.Tbecalibrationprecedcreuseddata for theperiod fromAugust1991 to August 1992 using the available climate and hydrometric data.The model wasverified usingdatafromtheperiodAugust1992 toJune 1993. Due to the problem with the data related to the ice effect on winterflows discussed in Chapter 3.no further calibrationwasundertaken for this study.However.a simulatio nrun using the first two yearsofthedata was carried out to visuallyevaluate the calibration. Asampleof the resultsispresentedinFigure12.

IUIBEIllutll FUllFORECASTI'"rlJEln IJI'1"EIIlUIBEJll IUE:l ll lLUJDUJ L1.E

loll1(14 CflLO /UlTED

!

,

;~

~

tJ;

,,

)'I\J

'

~

J

J

,

,);.

,

m

"

...

"

,

'lZ 28 OCT

"

28

""

'.1 zs DEC

"

Figure 12- SampleSSARR Calibratio n Run

Weighting of Meteorologic Stations

TheSSARRmodelallowstheuserthe optionof assigningdataavailable for several

met eor ol ogicstations toany oftbe subbasins defined inthe model.Also, the userhasthe

optionofweightingmeteorologic stationsapplied toeachsubbasin.Theinitialweightswere

determinedbythe consultant fortheinitialstudy(CummingCockburn, 1984) usingTheissen

polygons.Inthisprocessthe temperatureand precipitation datawerefirst given thesame

weights.Theweightings usedin thisstudy arebased on the (Cumming Cockburn, 1995)

study and are showninTable9.

SnowmeltCoefficients

Once themodel yieldsgood results for rainfallonly eventsthecalibration springsnowmelt

eventscanbe initiated.The paramet ersthatrequireinitial estimatesare:

rain freeze temperature;

basetemperature;

lapserate;and

meltrate(fordegreedaymethod only).

The snowmeltcoefficientsused in this studyare givenin Table10

Routing Coefficien ts

Theroutingparamet erswere determinedforthe gaugedwatershedsthen these valueswere

transferred totheungaugedbasins. Theinitial valuesweredetennined usingrunoff

conditionsthatwer e independent ofsnowmelt.Therout ing coefficientsare given inTable

II.

~

Table9 - PrecipitationGaugeWeighlSApplied10 Sub-basins (CummingCockburn,1995)

SIlb-b. olIlC....ItdN. _ CIlnwokSI....

'LAc CLSW BURG CLe' SAND INDI

....

OOR N '500

WI100·l~wum:hj=hIlrunk

..

rso

u

c

I1S

_,

_"

_".

".

_".

_"

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TableII-Routing Coefficients(Cummin8 Cockburn,1995)

Sub-basinCode andName Surface Subsurface Baseflow

NP TS NP TS NP TS

WII00-LewaseecbjeechBrook 3 IS 2 40 2 300

WIIOI-HindsLake 3 20 5 SO 2 400

WII02- SheffieldRiver 3 20 5 SO 2 450

WII03 - IndianBrookDiversion 4 IS 3 20 2 200

WII04-UpperHumber RiveraboveReidville 4 IS 3 20 2 200

W2100- GrandLakeWest 3 IS 3 20 2 200

W2101-Grand lakeCentral 3 IS 3 20 2 200

W2102-Grand LakeEast 3 IS 3 20 2 200

W2104·LocalInflowDownstreamof GrandLake 3 10 2 20 2 200

W2105·LocalInflow toDeerLake 3 IS 3 20 2 200

W2\06·LocalInflowtoComerBrook 3 10 3 IS 2 100

4.1.1.8 Data Format

Theinput data files for theSSARRmodel use a"cardimage"format.Theformatis based on the punch cardsused whenthe modelwas developed in the 1950's .The cardis divided intogroupsofcolumnsspecific to the typeof card.For example,precipitationdata isentered on a"Z4K

card.In the example,inTable 12the"Z4 "identifies the cardtype,

"BLAe"identifies thestation, thenextsixcolumnsthe data, the"3~thetimeperiodfor the data (dailyin this case) and the remainingcolumns the actual data.

With thePCversion of the program thecontrolcards are placedinaseparate data file in card format. Theorganizationof thecontrol card fileisshown in Table13. Table12- SSARRInput Data

Z4BLAC OlCl19 5 3 0.054 0.324 0.31 8 0.3 24 0.000 0.10 8 0.054 0. 00 0

Z4 BLAC 09C11953 O.ClOO 1.40 3 0.000 O.OClO 0.054 2.483 0.000 0.270 14BLAC 1707 953 CI.I08 0.054 0.593 0.648 0.000 1.349 0.108 O.2 a

%4 BLAC 2507953 0.432 0. 000 0.324 0.000 0.054 0.378 0.215

4.l.2 Forecast.'!forSpeci ficEvents

Theselectionof events was basedontheperiod of recordavailablefor theDCPstatio ns and thepresence of suitableevents to forecast. Thespringsnowmelt season wasselectedfor the three years with data records outside of thecalibrationperiod.

The input files for each daywerepreparedandthe model wasrun.Each of the inputfiles was structuredto providea forecast three daysbeyondthe forecastdateforeach of the five gauged subbasins The results foronestation are presentedgraphicallyin Figure13.

Appendix

c

containssamplewpU:andoutputfiles fortheSSARRmodelaswellas sample plotsof theforecasts for-eachof thebasins

I

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'7

Tabl e13- SSARRControl CardOrganiza tion

Card Description

J Run characteristics

CP Charac te risticsofmeteorologic stations

CT Tablesof variations of basinparameters

Permanent characteristics CB Basincharacteristics of themod el _{C3 Altitude-Arearelationship}

CR Reach characteristics CL Lake and river charac te ristics

CI Reservoir storagecurves CC Node characteris tics

P Networkconfiguration T Duration of the simulation 2B Initialconditionsof thebasins Initialconditions and _{2R Initial conditions of the reaches} inputdata

3B Revision of initialbasin conditions

4

0

meteorologic data (observed and

forecast)

5 Temporaldistribution ofrainand

tempera ture

6 Hydrometric data

ControlofOutput PR Printingform at fornumeric output

PQ Printing format for graphic output

E

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4

.1

Statisti

ca l Mod

el

(Dynamic R

egressi on)

Dynamic regression models denote single equation regression models thatcombine

time series orienteddynamic featureswiththeeffectsof explanatoryvariables (Goodrich, 198 9).The ARIMA typeof modelispurdy dynamic.Itsforecasts depend sold y onthe propagation of random shocks forwardsintime.In additiontomodelling thispropagatio n

proc ess.adynamicregress ion mod el must also accountforthe casual influencesofthe explanatoryvaria bles.

Dynamicregressionmaybeused when:

thedatasetsarelongeno ugh andstableenoughto suppo rta correlational

model.and

theexplanato ryvariablesincreasetheaccuracyof fitin a meani ngfu l way

4.1. 1 ModelBa ckg ro und

Muchofthe current theoryand development oftime series modelling goesbackto BoxandJenIrins(BoxandJenIcins,1976 ).Inthistext,Bo xandJenkinsreferred a technique calledthe"combinedtransfer function-disturbance"model.Pankratz (Pankratz. 1991 )used Box-JenkinsmodeUingtechnique callingit"dynami cregression".

The ordinaryleast squares dynamic regressionmodeltakes thefonnshown in

Equati o n2:

<!>(b)Y, •~Z,•

e

59

where~(b)

y,

auto regressive polynomial dependantvariableattime , coefficientofi'th exogenousvariableZ/fJ

Z, vector of exogenous variablesattime '

E, errorswhere the errorsareNlD(O,ri),le.no rmally and independently distributed with varianceri Often theresiduals fromEq(I) are correlated.contrary to the assumption of independence. Asignificantcorrelationinthe residuals indicates that the historical data are relatedto current dataand may be useful in predicting futurevalues.With streamflows,it is quiteconceivable thattomorrowsflowsarerelatedtoflowsand precipitation that occurred one,two orthree days ago. For this reason,errorautocorre lationmust be seriously consideredin modelconstruction

Errorautocorrelationcan be detected by examining lite autocorrelationfunction (ACF) results.using the Ljung-BoxQ-test,theDurbin-Wa tsontest, or byusing othertests. The ACF determines theIfautocorrelations arefound this mayindicate that oneor more lags should beadded tothemodel or thatadditional exogenous variablesshouldbe added.In the modellingprocess exogenousvariablesare variables,suchas temperatureor precipitation that may not beinitially included inthe model.In some cases, both maybe required

One method to improve themodeldynamicsisto use the Cochrane-Orcutt (Goodrich, 1989) model to addnew parameters With this method.Equation Iisrep laced by the following pair of equations: