JOURNAL ARTICLE

CALIBRATION ANALYSIS OF RAIN DISCHARGE MODELING IN THE KALIBODO WATERSHED USING HEC-HMS

Danayanti Azmi Dewi NusantaraBelia Tatika Arno Dianeka

Year: 2023 Journal:   Jurnal Teknik Sipil Vol: 23 (3)Pages: 446-446   Publisher: Tanjungpura University

Abstract

The Kalibodo sub-watershed is among the Brantas sub-watersheds. The sub-watershed under consideration is situated within the administrative boundaries of Malang Regency. A recurring issue of flooding afflicts the area in question. Floods are influenced by alterations in land utilization, insufficiency of water catchment regions, and elevated precipitation levels. Efforts can be made to address the flooding issue by implementing a hydrological analysis in rain-discharge modeling. The modeling process is conducted using the Hec-HMS software tool. This modeling endeavor aims to acquire hydrological values that closely resemble the observed data. This parameter is a metric for assessing the volume of water flowing through a river. The methodology employed in Soil Conservation Service (SCS) is based on the Curve Number (CN) approach. The method encompasses several parameters: CN, Tlag, Ia, and impervious values. The model calibration process utilizes an input CN value of 77.66 and an impenetrable value of 16.77.Moreover, the analysis of rainfall is conducted using the Thiessen Polygon approach, which considers the influence of rain stations located in Singosari, Sumbergondo, and Karangploso. The present analysis yielded weighting values of 0.457, 0.096, and 0.447 for the Singosari, Sumbergondo, and Karangploso rain stations. The calibration process lost a Nash-Sutcliffe Efficiency (NSE) value of 0.994. Simultaneously, the root mean square error (RMSE) exhibits a value of 0.4. The matter in question is classified as outstanding due to its proximity to an NSE value of 1 and an RMSE value close to 0, indicating a minimal error rate

Keywords:
Watershed Hydrology (agriculture) Environmental science Calibration Impervious surface Flooding (psychology) Mean squared error Precipitation Meteorology Statistics Mathematics Geography Computer science Geology

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Topics

Water and Land Management
Physical Sciences →  Environmental Science →  Management, Monitoring, Policy and Law
Data Mining and Machine Learning Applications
Physical Sciences →  Computer Science →  Information Systems

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