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Development of a flood forecasting system using IFAS: a case study of scarcely gauged Jhelum and Chenab river basins

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Development of a well-calibrated, distributed hydrological model for flood forecasting based on rainfall and snowmelt is quite challenging, especially when in situ data is limited or unavailable. This paper presents… Click to show full abstract

Development of a well-calibrated, distributed hydrological model for flood forecasting based on rainfall and snowmelt is quite challenging, especially when in situ data is limited or unavailable. This paper presents the study carried out to parameterise the Integrated Flood Analysis System (IFAS) model for the trans-boundary, scarcely gauged catchments of Jhelum and Chenab rivers in Pakistan. Rainfall-runoff analysis was performed with a two-layered tank configuration, integrating snowmelt and dam and barrage operation from the very upstream in India to Trimmu Barrage in Pakistan. A grid size of 5 × 5 km was considered. Global map topography, land cover and soil data was utilised. The model was tested considering different magnitudes of floods of the years 2014, 2015 and 2017. The results showed that the satellite rainfall product, i.e. Global Satellite Mapping of Precipitation (GSMaP-NRT), underestimated the rainfall volume, compared to the ground-gauged rainfall. The GSMaP-IF correction method showed poor performance owing to the lack of ground observatory rainfall data for correcting the trans-boundary part of the basin. The GSMaP-Type1 correction method showed good results, except for the confluence point where complex flow conditions were not properly reproduced by the model. In addition, the incorporation of dam and barrages in the model improved the simulated flow results. It is concluded that the satellite rainfall estimates must be corrected to improve the results. Snowmelt module estimated the snowmelt contribution as 3 to 7% and 4 to 23% of the average daily discharge during the monsoon season at Mangla Dam and Marala Barrage, respectively, during 2014 and 2015. This study assessed various correction methods and concluded that the model and methodology used in the study functioned well with suitable precipitation.

Keywords: flood forecasting; scarcely gauged; study; model; rainfall; flood

Journal Title: Arabian Journal of Geosciences
Year Published: 2018

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