Open AccessEstimation of Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) Using GSSHA Model (Case Study Area Upper Citarum Watershed)
Author(s) -
Puji R A Sibuea,
Dewi Rahmah Agriamah,
Edi Riawan,
Rusmawan Suwarman,
Atika Lubis
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 - 10.1088/1755-1315/893/1/012023
Subject(s) - environmental science , watershed , precipitation , flood myth , hydrology (agriculture) , hydrograph , meteorology , climatology , geography , geology , geotechnical engineering , archaeology , machine learning , computer science
Probable Maximum Flood (PMF) used in the design of hydrological structures reliabilities and safety which its value is obtained from the Probable Maximum Precipitation (PMP). The objectives of this study are to estimate PMP and PMF value in Upper Citarum Watershed and understand the impact from different PMP value to PMF value with two scenarios those are Scenario A and B. Scenario A will calculate the PMP value from each Global Satellite Mapping of Precipitation (GSMaP) rainfall data grid and Scenario B calculate the PMP value from the mean area rainfall. PMP value will be obtained by the statistical Hershfield method, and the PMF will be obtained by employed the PMP value as the input data in Gridded Surface Subsurface Hydrologic Analysis (GSSHA) hydrologic model. Model simulation results for PMF hydrographs from both scenarios show that spatial distribution of rainfall in the Upper Citarum watershed will affect the calculated discharge and whether Scenario A or B can be applied in the study area for PMP duration equal or higher than 72 hours. PMF peak discharge for Scenario A is averagely 13,12% larger than Scenario B.