Predicting streamflow for land cover changes in the Upper Gilgel Abay River Basin, Ethiopia: A TOPMODEL based approach
•Runoff contributions from respective land cover types in Gilgel Abbay basin analysed.•Runoff simulated using TOPMODEL approach based on selected land cover types.•Simulation runs are performed for the specific land cover types and related parameters.•Annual peakflow and streamflow volume varied amo...
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Veröffentlicht in: | Physics and chemistry of the earth. Parts A/B/C 2014-01, Vol.76-78, p.3-15 |
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Sprache: | eng |
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Zusammenfassung: | •Runoff contributions from respective land cover types in Gilgel Abbay basin analysed.•Runoff simulated using TOPMODEL approach based on selected land cover types.•Simulation runs are performed for the specific land cover types and related parameters.•Annual peakflow and streamflow volume varied among agriculture, forest and grassland.•Findings relevant in African rural catchments experiencing rapid population increases.
Hydrological effects of land cover changes and runoff contributions from respective land cover types are analysed for the Upper Gilgel Abay basin in Ethiopia. Runoff production and streamflow are simulated by the TOPMODEL approach. For impact assessment of land cover changes, satellite based land covers for the years 1973, 1986 and 2001 are considered. Catchment topography as well as land cover and vegetation characteristics are derived from satellite images and serve to estimate model parameters. Land cover in TOPMODEL has been implemented by spatial units based on the actual size of each land cover type. The topographic index distribution function, which is an important input to the TOPMODEL, is prepared for each land cover type. Simulations are also performed for specific land cover types to allow inter comparison of hydrological responses. Results showed that the highest peak flow as well as the annual streamflow volume varied among the land cover types agriculture, forest and grassland which dominate land cover in the catchment. Results of this study show that in data poor basins, satellite images provide suitable land surface data for rainfall–runoff modelling and land surface parameterization. Findings are of relevance for many African rural catchments which experience rapid population increases and resource scarcity. |
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ISSN: | 1474-7065 1873-5193 |
DOI: | 10.1016/j.pce.2014.11.012 |