Namwade, Gangadhar and Trivedi, M. M. and Tiwari, Mukesh Kumar and Patel, G. R. (2023) Rainfall-Runoff Modelling Using HEC-HMS Model, Remote Sensing and GIS in Middle Gujarat, India. International Journal of Environment and Climate Change, 13 (9). pp. 952-962. ISSN 2581-8627
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Abstract
Hydrological modeling is a widely used approach for estimating the hydrological response of a basin to precipitation. Floods are among the most catastrophic natural disasters in small urban watersheds, inflicting loss of life, massive property destruction, and a severe danger to the economy. As a result, appropriate modeling can be a useful tool in preventing and mitigating such flood hazards. Despite this, flash flood prediction remains one of the challenges of hydrological modeling in ungauged basins due to a lack of runoff observations. This study aims to calibrate and validate the rainfall-runoff transformation model for Hathmati river sub watershed in the Sabarmati River basin using HEC-HMS (Hydrologic Engineering Centre Hydrology Modeling System). For the loss rate, SCS Curve Number method was selected while Clark Unit Hydrograph and SCS unit hydrograph was used for the transform method. The model is calibrated and verified using two rainfall-runoff events from 2006 and 2007 year The model calibration and validation efficiency were verified for both methods using the Nash-Sutcliffe efficiency (NSE), The coefficient of determination (R2), and the Percent Bias (PBIAS) As a result, the model calibration and validation were found to be satisfactory with the acceptable value of NSE between 0.869 to 0.914, with R2 0.901 to 0.947 and PBIAS from 9.76 to 14.8. it is observed that the model shows a very good correlation between simulated flow and observed flow. As a result, the model can be used to forecast river flow and aid in flood mitigation efforts to lessen their effects and associated costs. Additionally, the findings of this study can serve as guidelines for future assessments of the flood risk in the study area.
Item Type: | Article |
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Subjects: | AP Academic Press > Agricultural and Food Science |
Depositing User: | Unnamed user with email support@apacademicpress.com |
Date Deposited: | 13 Jul 2023 06:39 |
Last Modified: | 14 Sep 2024 03:54 |
URI: | http://info.openarchivespress.com/id/eprint/1812 |