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Floods are the most significant natural hazards worldwide, claim precious lives and cause serious damage to buildings,
infrastructure and agricultural crops. Pakistan is also frequently suffering huge agro-economic dents and life loss by floods in
Indus, Jhelum and Chenab rivers due to lack of budget, effective flood preparedness and flood forecasting. The flood
forecasting in the Chenab river is a major challenge due to lack of hydrometeorological data as most of its catchment is under
Indian control. In this study, three high spatiotemporal Global Satellite Mapping of Precipitation (GSMaP) products,
GSMaP_Near Real Time (NRT), GSMaP_now (NOW) and GSMaP_RIKEN Nowcast (RNC) were used along with the global
temperature, snow, landuse and soil datasets in Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS)
model for flood forecasting. The Soil Moisture Accounting (SMA) and temperature index methods were used for direct runoff
estimation and snowmelt runoff modeling, respectively. The results revealed that GSMaP_NRT, GSMaP_NOW and
GSMaP_RNC based simulated flow has Nash and Sutcliffe Efficiency (NSE) value of 0.58, 0.73 and 0.35, respectively, from
2017 to 2018. The GSMaP_NOW precipitation estimate has fair flow simulation results while the GSMaP_RNC product has
poor simulation results. It is concluded from the results that GSMaP_NRT is a reliable high spatiotemporal precipitation
estimate for hydrological studies and flood forecasting in data scarce Chenab river catchment.
Tasneem Khaliq, Sikandar Ali, Muhammad Jehanzeb Masud Cheema , Allah Bakhsh1. (2020) NEAR REAL TIME FLOOD FORECASTING IN THE TRANSBOUNDARY CHENAB RIVER USING GLOBAL SATELLITE MAPPING OF PRECIPITATION, Pakistan Journal of Agricultural Sciences, Volume 57, Issue 5.
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