Comparison between the United States Soil Comparison between the United States Soil Conservation Service (SCS) curve number, Conservation Service (SCS) curve number,

the Pitman and Monarch models for the Pitman and Monarch models for estimating rainfall-runoff in South-Eastern estimating rainfall-runoff in South-Eastern

BotswanaBotswana

Rejoice Tsheko, PhDRejoice Tsheko, PhDFaculty of Agriculture at B.C.A, Department of Faculty of Agriculture at B.C.A, Department of

Agricultural Engineering and Land Planning, Private Agricultural Engineering and Land Planning, Private Bag 0027, Gaborone, BotswanaBag 0027, Gaborone, Botswana

WMO/FAO Training Workshop, Gaborone 14 – 18 November 2005

Structure of presentationStructure of presentation

• IntroductionIntroduction

• Description of the study areaDescription of the study area

• Research methodologyResearch methodology

• Data sources for the SCS modelData sources for the SCS model

• ResultsResults

• ObservationsObservations

IntroductionIntroduction

• It is crucial that the watershed runoff or inflows, which are used as It is crucial that the watershed runoff or inflows, which are used as inputs for the modelling of water resources are accurateinputs for the modelling of water resources are accurate..

• EErroneous values could have serious implications. rroneous values could have serious implications. • Because of the aridness of the country, the government of Botswana Because of the aridness of the country, the government of Botswana

has invested heavily on studies to evaluate potential of water resources has invested heavily on studies to evaluate potential of water resources in the countryin the country (BWMP). (BWMP).

• Two models namely Pitman and Monarch have been used Two models namely Pitman and Monarch have been used extensively extensively in in the past to estimate potential reservoirs inflows in Botswanathe past to estimate potential reservoirs inflows in Botswana..

• Deterministic modelsDeterministic models• Pitman model ->Lumped parameter modelPitman model ->Lumped parameter model• Monash model -> Distributed modelMonash model -> Distributed model• SCS curve number model -> Empirical modelSCS curve number model -> Empirical model• ->model parameters lacking in Botswana (BNWMP 1991)->model parameters lacking in Botswana (BNWMP 1991)

Source: Botswana Atlas (1:9,460,000)

Shuttle Radar Topography Mission

(NASA)

Landsat ETM+ Imagery

Landsat MSS and TM

Imagery

Rainfall charts(Botswana Department of Meteorological Services)

Digital Elevation Model

(FAO-SDRN)

Land use / Land cover Database

Soil Types Database(FAO+Botswana Ministry of Agriculture)

Rainfall intensity

Watershed delineation

Basin characteristics

Composite curve numbers

Hydrologic soil group

Land cover complex

SCS 6-hour rainfall distributions

Research MethodologyResearch Methodology SCS model inputs

Digital Image processing<-> GIS environment

Mean Annual Runoff

Volumes

Digital Elevation ModelsDigital Elevation Models

• The Shuttle Radar Topography The Shuttle Radar Topography Mission (SRTM) DEMs data was Mission (SRTM) DEMs data was

acquired from FAO-SDRNacquired from FAO-SDRN • Watershed Watershed was was delineateddelineatededed from from

the the DEMs using the drainage module DEMs using the drainage module of WMSof WMS..

NASA SRTM DEMs

Soil dataSoil data

• Digital soil data was obtained from the Botswana Ministry of Digital soil data was obtained from the Botswana Ministry of AgricultureAgriculture..

• TThis consisted of 1:100 000 shape and attribute data of the his consisted of 1:100 000 shape and attribute data of the different soil types in Botswana (FAO/UNDP/Government of different soil types in Botswana (FAO/UNDP/Government of Botswana). Botswana).

• The hydrologic soil type attribute was created The hydrologic soil type attribute was created in ArcView. in ArcView.

• This was This was based on the infiltration rates of the different soil types based on the infiltration rates of the different soil types based on AG: BOT/85/011 Field Document Number 33 (Joshua, based on AG: BOT/85/011 Field Document Number 33 (Joshua, 1991)1991)

Soil typesSoil types

Land use / Land cover dataLand use / Land cover data

• Landsat ETM+ data acquired from FAO-SDRN Landsat ETM+ data acquired from FAO-SDRN in Rome in Rome and the and the Regional Remote Sensing Unit (RRSU). Regional Remote Sensing Unit (RRSU).

• Channels 1, 3 and 4 of the Landsat ETM+ (Path172 Row 077 2002) Channels 1, 3 and 4 of the Landsat ETM+ (Path172 Row 077 2002)

image were used to create the land useimage were used to create the land use / land cover database/ land cover database.. • Manual and semi-automatic classification was carried out using Manual and semi-automatic classification was carried out using

the the GeoVIS softwareGeoVIS software ((Terra NovaTerra Nova))

Land use / land coverLand use / land cover

Rainfall dataRainfall data

• In this study, the procedure outlined in McCuen 1984 was used to In this study, the procedure outlined in McCuen 1984 was used to form a design storm using Gaborone rainfall data from the form a design storm using Gaborone rainfall data from the

department of Meteorological Services (DMS).department of Meteorological Services (DMS). • AActual and generated ctual and generated rainfall rainfall (BNWMP, 1991) data from 8 stations (BNWMP, 1991) data from 8 stations

in the Notwane, 10 stations in the Metsimotlhabe and 9 stations in in the Notwane, 10 stations in the Metsimotlhabe and 9 stations in the Thagale river systems wethe Thagale river systems were re used to calculate used to calculate the the average average rainfall data input rainfall data input forfor the model. the model.

• From the long-term rainfall data (1925 – 1988), the average From the long-term rainfall data (1925 – 1988), the average rainfall for the winter months (June, July and August) is less than 5 rainfall for the winter months (June, July and August) is less than 5 mm per month which is very little to produce any runoff in the SCS mm per month which is very little to produce any runoff in the SCS

model.model. These months were excluded from the calculations.These months were excluded from the calculations.

SCS 6-hour rainfall distribution for Gaborone

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Time (hr)

Fra

cti

on

of

6-h

r R

ain

fall

SCS modelSCS model

• The land use and soil data was used to calculate composite curve The land use and soil data was used to calculate composite curve number for the watersheds. number for the watersheds.

• The shapefiles were mapped to WMS feature objects using the GIS The shapefiles were mapped to WMS feature objects using the GIS module. module.

• The soils coverage shapefile was mapped to HYDGRP (hydrologic The soils coverage shapefile was mapped to HYDGRP (hydrologic soil group)soil group)..

• TThe land use coverage shapefile mapped to LUCODE (land use he land use coverage shapefile mapped to LUCODE (land use code).code).

• The mapping table were prepared and saved earlier in text mode. The mapping table were prepared and saved earlier in text mode. • Finally the hydrologic modelling module was used to calculate the Finally the hydrologic modelling module was used to calculate the

composite curve numbers. composite curve numbers. • The model was then used to calculate runoff for the three sub The model was then used to calculate runoff for the three sub

basinsbasins..

Watershed delineationWatershed delineation

• Using the DEMs to delineate watersheds gave 4172.4 kmUsing the DEMs to delineate watersheds gave 4172.4 km22 for the for the Notwane river system, 3568 km2 for the Metsimotlhabe river Notwane river system, 3568 km2 for the Metsimotlhabe river system and 9686 kmsystem and 9686 km2 2 for the Thagale river system. This compares for the Thagale river system. This compares very well with already established figures of 3983 kmvery well with already established figures of 3983 km22 and 3570 and 3570

kmkm22 for both the Notwane and for both the Notwane and Metsimotlhabe river systemsMetsimotlhabe river systems

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

Notwane Metsimotlhabe Thagale

Flo

w (

Mm

^3

) SCS

Pitman

Monash

Gauged flow

Actual and predicted mean annual runoff

Observations and recommendationsObservations and recommendations

• SCS model underestimate mean annual runoff for the SCS model underestimate mean annual runoff for the Notwane drainage areas.Notwane drainage areas.

• SCS model overestimate mean annual runoff for the SCS model overestimate mean annual runoff for the Metsimotlhaba drainage areas.Metsimotlhaba drainage areas.

• City of Gaborone runoff contributes to the Metsimotlhaba City of Gaborone runoff contributes to the Metsimotlhaba drainage area runoff.drainage area runoff.

• Is data available? Is data available? – Only the land use / land cover data has to be developed (FAO Only the land use / land cover data has to be developed (FAO

GLCN)GLCN)– Other data are availableOther data are available– Processing of MET rainfall data is requiredProcessing of MET rainfall data is required

• This method is rapid, could be updated as required i.e. This method is rapid, could be updated as required i.e. changes in land cover / land use.changes in land cover / land use.

Mean monthly runoff volumes for the three watersheds