Estimating rainfall and water balance over the Okavango River Basin for hydrological applications
- Wilk, J, Kniveton, D, Andersson, L, Layberry, R, Todd, M C, Hughes, Denis A
- Authors: Wilk, J , Kniveton, D , Andersson, L , Layberry, R , Todd, M C , Hughes, Denis A
- Date: 2006
- Language: English
- Type: Article
- Identifier: vital:7084 , http://hdl.handle.net/10962/d1012343 , http://dx.doi.org/10.1016/j.jhydrol.2006.04.049
- Description: A historical database for use in rainfall-runoff modeling of the Okavango River Basin in Southwest Africa is presented. The work has relevance for similar data-sparse regions. The parameters of main concern are rainfall and catchment water balance, which are key variables for subsequent studies of the hydrological impacts of development and climate change. Rainfall estimates are based on a combination of in situ gauges and satellite sources. Rain gauge measurements are most extensive from 1955 to 1972, after which they are drastically reduced due to the Angolan civil war. The sensitivity of the rainfall fields to spatial interpolation techniques and the density of gauges were evaluated. Satellite based rainfall estimates for the basin are developed for the period from 1991 onwards, based on the Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave Imager (SSM/I) datasets. The consistency between the gauges and satellite estimates was considered. A methodology was developed to allow calibration of the rainfall-runoff hydrological model against rain gauge data from 1960 to 1972, with the prerequisite that the model should be driven by satellite derived rainfall products from 1990 onwards. With the rain gauge data, addition of a single rainfall station (Longa) in regions where stations earlier were lacking was more important than the chosen interpolation method. Comparison of satellite and gauge rainfall outside the basin indicated that the satellite overestimates rainfall by 20%. A non-linear correction was derived by fitting the rainfall frequency characteristics to those of the historical rainfall data. This satellite rainfall dataset was found satisfactory when using the Pitman rainfall-runoff model (Hughes, D., Andersson, L., Wilk, J., Savenije, H.H.G., this issue. Regional calibration of the Pitman model for the Okavango River. Journal of Hydrology). Intensive monitoring in the region is recommended to increase accuracy of the comprehensive satellite rainfall estimate calibration procedure.
- Full Text:
- Date Issued: 2006
- Authors: Wilk, J , Kniveton, D , Andersson, L , Layberry, R , Todd, M C , Hughes, Denis A
- Date: 2006
- Language: English
- Type: Article
- Identifier: vital:7084 , http://hdl.handle.net/10962/d1012343 , http://dx.doi.org/10.1016/j.jhydrol.2006.04.049
- Description: A historical database for use in rainfall-runoff modeling of the Okavango River Basin in Southwest Africa is presented. The work has relevance for similar data-sparse regions. The parameters of main concern are rainfall and catchment water balance, which are key variables for subsequent studies of the hydrological impacts of development and climate change. Rainfall estimates are based on a combination of in situ gauges and satellite sources. Rain gauge measurements are most extensive from 1955 to 1972, after which they are drastically reduced due to the Angolan civil war. The sensitivity of the rainfall fields to spatial interpolation techniques and the density of gauges were evaluated. Satellite based rainfall estimates for the basin are developed for the period from 1991 onwards, based on the Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave Imager (SSM/I) datasets. The consistency between the gauges and satellite estimates was considered. A methodology was developed to allow calibration of the rainfall-runoff hydrological model against rain gauge data from 1960 to 1972, with the prerequisite that the model should be driven by satellite derived rainfall products from 1990 onwards. With the rain gauge data, addition of a single rainfall station (Longa) in regions where stations earlier were lacking was more important than the chosen interpolation method. Comparison of satellite and gauge rainfall outside the basin indicated that the satellite overestimates rainfall by 20%. A non-linear correction was derived by fitting the rainfall frequency characteristics to those of the historical rainfall data. This satellite rainfall dataset was found satisfactory when using the Pitman rainfall-runoff model (Hughes, D., Andersson, L., Wilk, J., Savenije, H.H.G., this issue. Regional calibration of the Pitman model for the Okavango River. Journal of Hydrology). Intensive monitoring in the region is recommended to increase accuracy of the comprehensive satellite rainfall estimate calibration procedure.
- Full Text:
- Date Issued: 2006
Impact of climate change and development scenarios on flow patterns in the Okavango River
- Andersson, L, Wilk, J, Todd, M C, Hughes, Denis A, Earle, A, Kniveton, D, Layberry, R, Savenije, H H G
- Authors: Andersson, L , Wilk, J , Todd, M C , Hughes, Denis A , Earle, A , Kniveton, D , Layberry, R , Savenije, H H G
- Date: 2006
- Language: English
- Type: Article
- Identifier: vital:7086 , http://hdl.handle.net/10962/d1012346
- Description: This paper lays the foundation for the use of scenario modelling as a tool for integrated water resource management in the Okavango River basin. The Pitman hydrological model is used to assess the impact of various development and climate change scenarios on downstream river flow. The simulated impact on modelled river discharge of increased water use for domestic use, livestock, and informal irrigation (proportional to expected population increase) is very limited. Implementation of all likely potential formal irrigation schemes mentioned in available reports is expected to decrease the annual flow by 2% and the minimum monthly flow by 5%. The maximum possible impact of irrigation on annual average flow is estimated as 8%, with a reduction of minimum monthly flow by 17%. Deforestation of all areas within a 1 km buffer around the rivers is estimated to increase the flow by 6%. However, construction of all potential hydropower reservoirs in the basin may change the monthly mean flow distribution dramatically, although under the assumed operational rules, the impact of the dams is only substantial during wet years. The simulated impacts of climate change are considerable larger that those of the development scenarios (with exception of the high development scenario of hydropower schemes) although the results are sensitive to the choice of GCM and the IPCC SRES greenhouse gas (GHG) emission scenarios. The annual mean water flow predictions for the period 2020–2050 averaged over scenarios from all the four GCMs used in this study are close to the present situation for both the A2 and B2 GHG scenarios. For the 2050–2080 and 2070–2099 periods the all-GCM mean shows a flow decrease of 20% (14%) and 26% (17%), respectively, for the A2 (B2) GHG scenarios. However, the uncertainty in the magnitude of simulated future changes remains high. The simulated effect of climate change on minimum monthly flow is proportionally higher than the impact on the annual mean flow.
- Full Text:
- Date Issued: 2006
- Authors: Andersson, L , Wilk, J , Todd, M C , Hughes, Denis A , Earle, A , Kniveton, D , Layberry, R , Savenije, H H G
- Date: 2006
- Language: English
- Type: Article
- Identifier: vital:7086 , http://hdl.handle.net/10962/d1012346
- Description: This paper lays the foundation for the use of scenario modelling as a tool for integrated water resource management in the Okavango River basin. The Pitman hydrological model is used to assess the impact of various development and climate change scenarios on downstream river flow. The simulated impact on modelled river discharge of increased water use for domestic use, livestock, and informal irrigation (proportional to expected population increase) is very limited. Implementation of all likely potential formal irrigation schemes mentioned in available reports is expected to decrease the annual flow by 2% and the minimum monthly flow by 5%. The maximum possible impact of irrigation on annual average flow is estimated as 8%, with a reduction of minimum monthly flow by 17%. Deforestation of all areas within a 1 km buffer around the rivers is estimated to increase the flow by 6%. However, construction of all potential hydropower reservoirs in the basin may change the monthly mean flow distribution dramatically, although under the assumed operational rules, the impact of the dams is only substantial during wet years. The simulated impacts of climate change are considerable larger that those of the development scenarios (with exception of the high development scenario of hydropower schemes) although the results are sensitive to the choice of GCM and the IPCC SRES greenhouse gas (GHG) emission scenarios. The annual mean water flow predictions for the period 2020–2050 averaged over scenarios from all the four GCMs used in this study are close to the present situation for both the A2 and B2 GHG scenarios. For the 2050–2080 and 2070–2099 periods the all-GCM mean shows a flow decrease of 20% (14%) and 26% (17%), respectively, for the A2 (B2) GHG scenarios. However, the uncertainty in the magnitude of simulated future changes remains high. The simulated effect of climate change on minimum monthly flow is proportionally higher than the impact on the annual mean flow.
- Full Text:
- Date Issued: 2006
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