Open AccessComparison of rainfall-runoff models for climate change projection – case study of Citarum River Basin, Indonesia
Author(s) -
Waluyo Hatmoko,
Levina,
Bocanegra Díaz
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/423/1/012045
Subject(s) - environmental science , surface runoff , hydrology (agriculture) , climate change , drainage basin , water resources , discharge , climate model , structural basin , climatology , geography , geology , ecology , paleontology , oceanography , geotechnical engineering , cartography , biology
Climate change affects temperature, rainfall and hydrological properties in the river basins. Projected rainfalls for several climate change models are widely available nowadays. However, in water resources planning and management, river discharges data is unfortunately more important. The information on climate change impact on river discharges is very limited. Conversion from the projected rainfall to the runoff in the rivers is needed. This study analyzes the performance of rainfall-runoff models: 1) Empirical Model that defines the discharge as a function of rainfall, evaporation, and temperature, widely applied by climate scientist; and 2) simple lump conceptual model of NRECA. These two rainfall-runoff models are applied during the control period in the year of 2006 to 2015 of the rainfall projections from the seven CMIP5 Global Circulation Models with the worst scenario, RCP 8.5. The ground station river discharge data selected is Nanjung river gauging station at Citarum River, situated just upstream of Saguling Reservoir, the uppermost of the cascade of three reservoirs Saguling-Cirata-Jatiluhur, with the catchment area of 1, 675 square kilometers. The results show that the simple conceptual model NRECA significantly gives better fitted to the observation data than the Empirical Model, especially during the dry season.