A distributed monthly water balance model: formulation and application on Black Volta Basin

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作者
Khodayar Abdollahi
Imtiaz Bashir
Boud Verbeiren
Mahamane R. Harouna
Ann Van Griensven
Marijke Huysmans
Okke Batelaan
机构
[1] Shahrekord University,Faculty of Earth Science
[2] Vrije Universiteit Brussel (VUB),Department of Hydrology and Hydraulic Engineering
[3] KU Leuven,Faculty of Biosciences Engineering
[4] UNESCO-IHE Institute for Water Education,International Research and Education Institute
[5] Flinders University,School of the Environment
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关键词
Monthly water balance; Recharge; Runoff coefficient; Open-source software;
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摘要
Recharge assessment is of critical importance for groundwater resources evaluation in arid/semiarid areas, as these have typically limited surface water resources. There are several models for water balance evaluation. One of them is WetSpass, which has the ability to simulate spatially distributed recharge, surface runoff, and evapotranspiration for seasonally averaged conditions. This paper presents a modified methodology and model, WetSpass-M, in which the seasonal resolution is downscaled to a monthly scale. A generalized runoff coefficient was introduced, enabling runoff estimation for different land-use classes. WetSpass-M has been calibrated and validated with observed streamflow records from Black Volta. Base-flow from simulated recharge was compared with base-flow derived via a digital filter applied to the observed streamflow and has shown to be in agreement. Previous studies have concluded that for this basin, small changes in rainfall could cause a large change in surface runoff, and here a similar behavior is observed for recharge rates. An advantage of the new model is that it is applicable to medium- and large-sized catchments. It is useful as an assessment tool for evaluating the response of hydrological processes to the changes in associated hydrological variables. Since monthly data for streamflow and climatic variables are widely available, this new model has the potential to be used in regions where data availability at high temporal resolution is an issue. The spatial–temporal characteristics of the model allow distributed quantification of water balance components by taking advantage of remote sensing data.
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