Development of seasonal flow outlook model for Ganges-Brahmaputra Basins in Bangladesh
Bangladesh is crisscrossed by the branches and tributaries of three main river systems, the Ganges, Bramaputra and Meghna (GBM). The temporal variation of water availability of those rivers has an impact on the different water usages such as irrigation, urban water supply, hydropower generation,...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-10-01
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| Series: | Proceedings of the International Association of Hydrological Sciences |
| Online Access: | https://www.proc-iahs.net/374/117/2016/piahs-374-117-2016.pdf |
| Summary: | Bangladesh is crisscrossed by the branches and tributaries of three main
river systems, the Ganges, Bramaputra and Meghna (GBM). The temporal
variation of water availability of those rivers has an impact on the
different water usages such as irrigation, urban water supply, hydropower
generation, navigation etc. Thus, seasonal flow outlook can play important
role in various aspects of water management. The Flood Forecasting and
Warning Center (FFWC) in Bangladesh provides short term and medium term flood
forecast, and there is a wide demand from end-users about seasonal flow
outlook for agricultural purposes. The objective of this study is to develop
a seasonal flow outlook model in Bangladesh based on rainfall forecast. It
uses European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal
precipitation, temperature forecast to simulate HYDROMAD hydrological model.
Present study is limited for Ganges and Brahmaputra River Basins. ARIMA
correction is applied to correct the model error. The performance of the
model is evaluated using coefficient of determination (<i>R</i><sup>2</sup>) and
Nash–Sutcliffe Efficiency (NSE). The model result shows good performance
with <i>R</i><sup>2</sup> value of 0.78 and NSE of 0.61 for the Brahmaputra River Basin,
and <i>R</i><sup>2</sup> value of 0.72 and NSE of 0.59 for the Ganges River Basin for the
period of May to July 2015. The result of the study indicates strong
potential to make seasonal outlook to be operationalized. |
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| ISSN: | 2199-8981 2199-899X |