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Hydrological Modelling of Data-Scarce Catchments: A Case Study of Namal Valley

This paper considers the problem of modelling ungauged catchments with minimal sensing. We specifically consider the case of Namal lake catchment which either suffers from water scarcity or flooding and the lack of flow sensors makes their prediction a challenging problem. To this end, we perform the hydrological modelling of the catchment for determining the inflows from the streams to the reservoir using essentially rainfall data in the catchment, thereby circumventing the challenges posed by lack of flow sensors data. This is achieved by performing manual calibration of the SWAT model in ArcSWAT. The comparison of simulated water level with the observed water level demonstrates the efficacy of the our approach for modelling ungauged basins. The inflows generated by the proposed hydrological model can then be used in flood forecasting and effective management of reservoir operations.