Predicting Peak Flows in Real Time through Event Based Hydrologic Modeling for a Trans-Boundary River Catchment

Investigating the hydrological response of an area to adverse climate changes and extreme rainfall events is crucial for managing land and water resources and mitigating the natural hazards like floods. Limited availability of the in situ data, especially in case of Transboundary Rivers, further highlights the need to develop and evaluate decision support systems which may predict the flows in real time using open source rainfall data. This paper presents the study conducted in Chenab River catchment, Pakistan, to develop and evaluate a hydrologic model using HEC-HMS for predicting flows based on TRMM rainfall data. The catchment was analyzed for hydro-morphological properties using SRTM DEM in HEC-GeoHMS. To rely on open source data as much as possible, digital soil map of the world developed by FAO and global land cover map developed by European Space Agency were utilized to compute Curve Number grid data for the catchment. These preliminary data analyses were employed to set initial values of different parameters to be used for model calibration. The model was calibrated for five rainfall events occurred in the rainy seasons of 2006, 2010 and 2013. The calibrated model was then validated for four other rainfall events of similar type in the same years. Consistency in simulated and observed flows was found with percent difference in volume ranging from −6.17 % to 5.47 % and percent difference in peak flows to be in the range of 6.96 % to 7.28 %. Values of Nash-Sutcliffe Efficiency were ranging from 0.299 to 0.909 with an average value of 0.586 for all flow events. The model was found well capable of capturing the hydrologic response of the catchment due to rainfall events and can be helpful in providing alerts of peak flows in real time based on real time/forecasted rainfall data.