Flood forecasting using HEC-HMS model for Sukkur district, Pakistan

Fatima Salman Awan

United Nations University Institute on Comparative Regional Integration Studies, Belgium.

https://orcid.org/0009-0004-6377-7033

Dhananjay Singh

Village Satheri Post Office Khatauli District Muzaffarnagar, Uttar Pradesh, India.

https://orcid.org/0000-0002-5941-2048

Nidhi Nagabhatla

United Nations University Institute on Comparative Regional Integration Studies, Belgium.

https://orcid.org/0009-0002-1906-9473

DOI: https://doi.org/10.20448/arees.v12i1.6936

Keywords: Early warning systems, Flood forecasting, Flood risk assessment, HEC-HMS, Hydrological modeling, Rainfall-runoff modeling.


Abstract

This study investigates the applicability of the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) for reliable flood forecasting in the Sukkur District, Pakistan, a lower Indus Basin region that suffers on average three major flood events per decade and experienced catastrophic inundation of over 1,200 km² of cropland during the 2022 monsoon. We delineated the 5,165 km² Sukkur watershed into eight sub-basins using a 30 m SRTM-derived DEM and applied HEC-HMS with locally calibrated parameters—initial and constant loss, SCS unit hydrograph, and constant monthly baseflow—driven by daily rainfall (2018–2022) from Guddu, Sukkur and Kotri stations and six-hourly discharge at the Sukkur gauge. Representing the first calibrated HEC-HMS application with an eight-subbasin configuration in the region, this approach provides improved spatial resolution over lumped models. Calibration on three flood peaks (July 2020, August 2021, August 2022) and validation against an independent September 2022 event yielded a Nash-Sutcliffe Efficiency of 0.92 and a Root Mean Square Error of 55 m³/s, while the model provided an 18-hour lead time for peak discharge forecasts. These results demonstrate HEC-HMS’s strong potential as an operational early-warning tool to enhance emergency preparedness and minimize flood impacts in Sukkur and underscore the value of integrating real-time telemetry networks, coupling with two-dimensional hydraulic models, and conducting comprehensive sensitivity analyses to further improve forecast accuracy and support decision-making.

Downloads

Download data is not yet available.