Prediction of Streamflow at the Pemali catchment area using Shetran model
Author(s) -
Suroso Suroso,
Amaylia Dwi Wahyuni,
Purwanto Bekti Santoso
Publication year - 2021
Publication title -
iop conference series earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/698/1/012009
Subject(s) - streamflow , hydrology (agriculture) , flood myth , watershed , environmental science , flood forecasting , drainage basin , digital elevation model , land cover , flooding (psychology) , java , land use , geography , remote sensing , geology , cartography , psychology , civil engineering , geotechnical engineering , archaeology , machine learning , computer science , engineering , psychotherapist , programming language
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.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom