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Operationalizing a flood forecasting decision support system for Ayeyarwady river, Myanmar
Myanmar is one of the developing countries of South East Asia (SEA), wherein millions of people are exposed to risk of flooding every year. The Department of Meteorology and Hydrology (DMH), Myanmar is thus, bestowed with the responsibility of flood forecasting within the country for early warning. This study presents a new web-based Decision Support System (DSS), for DMH’s use in operational flood forecasting. The new DSS, that has a forecast lead time of 24–72 h, is a significant improvement over the existing forecasting systems used by DMH, which had a lead time of 4–24 h. Moreover, the new DSS couples Hydrological Engineering Centre Hydrological Modelling System (HEC-HMS) with Weather and Research (WRF) rainfall forecast for Ayeyarwady river basin (ARB), the principle river basin of the country. In addition to the hydro-meteorological coupling, core modules of the DSS include rainfall forecasting, bias correction and flow error correction. The hydrological model setup of the DSS was calibrated and validated for the periods 2008–2012 and 2013–2014 with observed rainfall. The DSS was then actively deployed and tested operationally by DMH using bias-corrected WRF rainfall forecasts for the period 2015–2017. Performance of the system is very good in forecasting flows and floods within ARB, and also provides additional lead time to DMH for issuing the flood advisories. Hence, the novel web-based flood forecasting DSS, is an important applied research contribution, that is being successfully used by the operational staff of DMH for short-term flood forecasting in Myanmar and has the potential to improve flood resiliency of similar agencies in the SEA region.
Operationalizing a flood forecasting decision support system for Ayeyarwady river, Myanmar
Myanmar is one of the developing countries of South East Asia (SEA), wherein millions of people are exposed to risk of flooding every year. The Department of Meteorology and Hydrology (DMH), Myanmar is thus, bestowed with the responsibility of flood forecasting within the country for early warning. This study presents a new web-based Decision Support System (DSS), for DMH’s use in operational flood forecasting. The new DSS, that has a forecast lead time of 24–72 h, is a significant improvement over the existing forecasting systems used by DMH, which had a lead time of 4–24 h. Moreover, the new DSS couples Hydrological Engineering Centre Hydrological Modelling System (HEC-HMS) with Weather and Research (WRF) rainfall forecast for Ayeyarwady river basin (ARB), the principle river basin of the country. In addition to the hydro-meteorological coupling, core modules of the DSS include rainfall forecasting, bias correction and flow error correction. The hydrological model setup of the DSS was calibrated and validated for the periods 2008–2012 and 2013–2014 with observed rainfall. The DSS was then actively deployed and tested operationally by DMH using bias-corrected WRF rainfall forecasts for the period 2015–2017. Performance of the system is very good in forecasting flows and floods within ARB, and also provides additional lead time to DMH for issuing the flood advisories. Hence, the novel web-based flood forecasting DSS, is an important applied research contribution, that is being successfully used by the operational staff of DMH for short-term flood forecasting in Myanmar and has the potential to improve flood resiliency of similar agencies in the SEA region.
Operationalizing a flood forecasting decision support system for Ayeyarwady river, Myanmar
Agarwal, Anshul (Autor:in) / Ghimire, Uttam (Autor:in) / Than, Htay Htay (Autor:in) / Srinivasan, Govindarajalu (Autor:in) / Dash, Itesh (Autor:in) / Shakya, Niraj (Autor:in) / Oo, Myo Tun (Autor:in)
International Journal of River Basin Management ; 19 ; 509-522
02.10.2021
14 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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