Open AccessComparisons of distributed and lumped rainfall-runoff model for soil moisture estimation
Author(s) -
Ratih Indri Hapsari,
Magfira Syarifuddin,
Ratna Ika Putri,
Dandung Novianto
Publication year - 2021
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 - 10.1088/1755-1315/930/1/012071
Subject(s) - water content , environmental science , surface runoff , landslide , hydrology (agriculture) , distributed element model , soil science , drainage basin , calibration , hydrological modelling , geotechnical engineering , geology , climatology , engineering , ecology , statistics , cartography , mathematics , geography , electrical engineering , biology
Soil moisture is an important parameter in landslides because of increased pore pressure and decreased shear strength. This research aims to derive soil moisture indicators from two hydrological models: the physically-based distributed hydrological model and the lumped model. Rainfall-Runoff-Inundation (RRI) Model is used to simulate the hydrological response of catchments to the rainfall-induced landslide in a distributed manner. Tank Model as a lumped hydrological model is also used in this study to simulate the dynamic of soil moisture. The study area is the upper Brantas River Basin, prone to landslides due to heavy rainfall and steep slope. Calibration of the model is conducted by tuning the model according to the river discharge data. The simulation indicates that acceptable performance is confirmed. Tank Model can provide the dynamic of the soil moisture. However, by using this approach, the spatial variation of the soil moisture cannot be presented. Regarding the quantitative amount of soil water content, RRI Model could make a reasonable simulation though the temporal variation is not adequately reproduced. Validation of this method with satellite soil moisture as well as ground measurement is also presented. The challenges of using these approaches to develop landslide hazard assessment are discussed.