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Rejoice Tsheko, PhD Faculty of Agriculture at B.C.A, Department of Agricultural Engineering and Land Planning, Private B

Comparison between the United States Soil Conservation Service (SCS) curve number, the Pitman and Monarch models for estimating rainfall-runoff in South-Eastern Botswana. Rejoice Tsheko, PhD

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Rejoice Tsheko, PhD Faculty of Agriculture at B.C.A, Department of Agricultural Engineering and Land Planning, Private B

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  1. Comparison between the United States Soil Conservation Service (SCS) curve number, the Pitman and Monarch models for estimating rainfall-runoff in South-Eastern Botswana Rejoice Tsheko, PhD Faculty of Agriculture at B.C.A, Department of Agricultural Engineering and Land Planning, Private Bag 0027, Gaborone, Botswana WMO/FAO Training Workshop, Gaborone 14 – 18 November 2005

  2. Structure of presentation • Introduction • Description of the study area • Research methodology • Data sources for the SCS model • Results • Observations

  3. Introduction • It is crucial that the watershed runoff or inflows, which are used as inputs for the modelling of water resources are accurate. • Erroneous values could have serious implications. • Because of the aridness of the country, the government of Botswana has invested heavily on studies to evaluate potential of water resources in the country (BWMP). • Two models namely Pitman and Monarch have been used extensively in the past to estimate potential reservoirs inflows in Botswana. • Deterministic models • Pitman model ->Lumped parameter model • Monash model -> Distributed model • SCS curve number model -> Empirical model • ->model parameters lacking in Botswana (BNWMP 1991)

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

  5. Research Methodology SCS model inputs Shuttle Radar Topography Mission (NASA) Digital Elevation Model (FAO-SDRN) Mean Annual Runoff Volumes Watershed delineation Basin characteristics Composite curve numbers Hydrologic soil group Land cover complex Landsat ETM+ Imagery Land use / Land cover Database Landsat MSS and TM Imagery Soil Types Database (FAO+Botswana Ministry of Agriculture) SCS 6-hour rainfall distributions Rainfall charts (Botswana Department of Meteorological Services) Rainfall intensity Digital Image processing<-> GIS environment

  6. Digital Elevation Models • The Shuttle Radar Topography Mission (SRTM) DEMs data was acquired from FAO-SDRN • Watershed was delineateded from the DEMs using the drainage module of WMS.

  7. NASA SRTM DEMs

  8. Soil data • Digital soil data was obtained from the Botswana Ministry of Agriculture. • This consisted of 1:100 000 shape and attribute data of the different soil types in Botswana (FAO/UNDP/Government of Botswana). • The hydrologic soil type attribute was created in ArcView. • This was based on the infiltration rates of the different soil types based on AG: BOT/85/011 Field Document Number 33 (Joshua, 1991)

  9. Soil types

  10. Land use / Land cover data • Landsat ETM+ data acquired from FAO-SDRN in Rome and the Regional Remote Sensing Unit (RRSU). • Channels 1, 3 and 4 of the Landsat ETM+ (Path172 Row 077 2002) image were used to create the land use/ land cover database. • Manual and semi-automatic classification was carried out using the GeoVIS software(Terra Nova)

  11. Land use / land cover

  12. Rainfall data • In this study, the procedure outlined in McCuen 1984 was used to form a design storm using Gaborone rainfall data from the department of Meteorological Services (DMS). • Actual and generated rainfall (BNWMP, 1991) data from 8 stations in the Notwane, 10 stations in the Metsimotlhabe and 9 stations in the Thagale river systems were used to calculate the average rainfall data input for the model. • From the long-term rainfall data (1925 – 1988), the average 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 model.These months were excluded from the calculations.

  13. SCS model • The land use and soil data was used to calculate composite curve number for the watersheds. • The shapefiles were mapped to WMS feature objects using the GIS module. • The soils coverage shapefile was mapped to HYDGRP (hydrologic soil group). • The land use coverage shapefile mapped to LUCODE (land use code). • The mapping table were prepared and saved earlier in text mode. • Finally the hydrologic modelling module was used to calculate the composite curve numbers. • The model was then used to calculate runoff for the three sub basins.

  14. Watershed delineation • Using the DEMs to delineate watersheds gave 4172.4 km2 for the Notwane river system, 3568 km2 for the Metsimotlhabe river system and 9686 km2 for the Thagale river system. This compares very well with already established figures of 3983 km2 and 3570 km2 for both the Notwane andMetsimotlhabe river systems

  15. Actual and predicted mean annual runoff

  16. Observations and recommendations • SCS model underestimate mean annual runoff for the Notwane drainage areas. • SCS model overestimate mean annual runoff for the Metsimotlhaba drainage areas. • City of Gaborone runoff contributes to the Metsimotlhaba drainage area runoff. • Is data available? • Only the land use / land cover data has to be developed (FAO GLCN) • Other data are available • Processing of MET rainfall data is required • This method is rapid, could be updated as required i.e. changes in land cover / land use.

  17. Mean monthly runoff volumes for the three watersheds

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