Prediction of Streamflow at the Pemali catchment area using Shetran model

Central Java is one of the provinces in Indonesia which has the most flood events, with a total of 1330 flood events in the span of 1819 to 2020. One of the watersheds in Central Java is the Pemali Watershed, most of which are in Brebes Regency. According to the National Disaster Management Agency (...

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Bibliographic Details
Published in:IOP conference series. Earth and environmental science 2021-03, Vol.698 (1), p.12009
Main Authors: Suroso, Wahyuni, Amaylia Dwi, Santoso, Purwanto Bekti
Format: Article
Language:English
Subjects:
Catchment areas
Digital Elevation Models
Disaster management
Disasters
Emergency preparedness
Evaporation
Evaporation rate
Flood control
Flood discharge
Flood management
Flood predictions
Floods
Flow rates
Flow velocity
Hydrologic data
Hydrologic models
Hydrology
Land cover
Land use
Rainfall
River flow
Rivers
Soils
Stream discharge
Stream flow
Watersheds
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Summary:Central Java is one of the provinces in Indonesia which has the most flood events, with a total of 1330 flood events in the span of 1819 to 2020. One of the watersheds in Central Java is the Pemali Watershed, most of which are in Brebes Regency. According to the National Disaster Management Agency (BNPB), there were 57 floods in Brebes Regency in 1994 - 2019. Therefore, to predict the occurrence of a flood disaster, it is necessary to know how much changes in river flow rates in the Pemali watershed. The purpose of this study was to determine the flood discharge at the Pemali river. The streamflow used is the maximum daily streamflow in a year from 2001 to 2017. The method used is the SHETRAN hydrological model. The data used in the SHETRAN model are the data derived from satellite measurements, namely digital elevation model data, MODIS land use land cover, soil type from the Harmonization World Soil Database, rainfall from the Tropical Rainfall Measuring Missions, and evaporation data. The results of this study indicate that river flow rates can be predicted by modeling using SHETRAN.
ISSN:1755-1307
1755-1315
DOI:10.1088/1755-1315/698/1/012009