Chandra Sekhar Matli
Professor in Civil Engineering, Water & Environment Division, National Institute of Technology, Warangal – 506 004, INDIA.
E-mail: 380mcs@gmail.com
Vinay S. Hunashal
Former Post Graduate Student, National Institute of Technology, WARANGAL.
Received on April 23, 2021 Accepted on April 26, 2021
DOI:https://doi.org/10.47884/jweam.v2i1pp48-54
ABSTRACT
The Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) is designed to simulate thecomplete hydrologic processes of dendritic watershed systems. The software includes many traditionalhydrologic analysis procedures such as event infiltration, unit hydrographs, and hydrologic routing. The modelis applied to the Pravara River Basin, which is a tributary of the Godavari River in the Ahmednagar district ofMaharashtra (India). For the simulation of runoff, the daily precipitation data and daily observed streamflow datafrom 1999 to 2012 was collected and ten years of data from 1999 to 2008 was used for the calibration of the modeland 4 years of data from 2009 to 2012 was used for the validation of the model. The calibration of the HEC-HMS4.0 model for the study area is carried out by comparing the simulated daily streamflow with the observed flow atthe outlet of the basin. For this particular study, the deficit and constant loss model is used to compute the lossesfrom the watershed. Under prediction of high flows is an inherent problem seen in hydrological modeling of thebasin in the present study. This is due to the lack of extreme event modeling capability of the hydrological model.The daily flows except extreme flows are better simulated. The ability of HEC–HMS to simulate the magnitudeof the peaks in extreme floods in the river basin underscores the significance of the model application as a floodprediction tool. The HEC–HMS successfully reproduced low flows and thus the model is a useful tool to estimatelow flows in advance based on drought forecasts.
Keywords – Hydrological Modelling, HEC model, Streamflow analysis, watershed losses, flood prediction