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Assessment of gridded precipitation products in the hydrological modeling of a flood-prone mesoscale basin

Authors :
Salman Khan
Farhan Khan
Yiqing Guan
Source :
Hydrology Research, Vol 53, Iss 1, Pp 85-106 (2022)
Publication Year :
2022
Publisher :
IWA Publishing, 2022.

Abstract

Precipitation plays a critical role in hydrometeorological studies. A predictive analysis of gridded rainfall datasets may provide a cost-effective alternative to conventional rain gauge observations. Here, our objective is to evaluate the performance of satellite and reanalysis precipitation products in the hydrological modeling of a mesoscale watershed. The research also examines the accuracy of hydrological simulations in a sizeable flood-prone watershed in the absence of observed data associated with the myriad water retaining structures present in the catchment. We use three precipitation products, namely Tropical Rainfall Measurement Missions (TRMM) 3B42 Version 7, Climate Forecast System Reanalysis (CFSR), and daily precipitation data recorded at multiple rain gauges in the upper Huai River Basin to simulate streamflow. The Soil & Water Assessment Tool (SWAT) is utilized for runoff modeling, while SWAT-CUP is used to perform sensitivity analysis and to calibrate and validate the simulation results. Nash–Sutcliffe efficiency, percent bias, and Kling-Gupta efficiency (KGE) are employed to evaluate modeling efficiency for three precipitation datasets on different temporal scales. The results indicate that TRMM and CFSR datasets provide satisfactory results on both daily and monthly scales. Specifically, the SWAT model performs better at monthly simulations than daily simulations for all precipitation datasets used. HIGHLIGHTS Examining the applicability of TRMM and CFSR daily precipitation products in simulating runoff from a large watershed.; Calibrating a hydrological model in the absence of data associated with extensive anthropogenic activities for flood prevention and diversion.; Performing streamflow simulations using a SWAT model and parameter calibration and sensitivity analysis using a SUFI-2 algorithm.;

Details

Language :
English
ISSN :
19989563 and 22247955
Volume :
53
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Hydrology Research
Publication Type :
Academic Journal
Accession number :
edsdoj.b6a2d73cc37a4a6dacf9cc4a78eb4c70
Document Type :
article
Full Text :
https://doi.org/10.2166/nh.2021.073