TY - GEN
T1 - Estimation of RUSLE EI30 based on 10 min interval rainfall data and GIS-based development of rainfall erosivity maps for Hitotsuse basin in Kyushu Japan
AU - Santosa, Purnama B.
AU - Mitani, Yasuhiro
AU - Ikemi, Hiro
PY - 2010/10/25
Y1 - 2010/10/25
N2 - Land erosion is regarded as one of the most important phenomenon causes land degradation. In revised universal soil loss equation (RUSLE) erosion model, rainfall erosivity factor (R) is one of the important parameters. Ideally, the calculation of EI30 (R factor) uses breakpoint rainfall intensity data which is calculated manually from graphical charts that are generated by continuously recording rain gauges. However, due to limited availability of breakpoint rainfall data, many simple methods for estimating EI30 have been developed by using yearly, monthly and daily rainfall data. In this research, due to limited data availability, pluviograph data at 10 minute interval from eight stations in Hitotsuse basin were used to compute EI 30 (R factor) for RUSLE. The approach used in this research is based on storm rainfall and duration data from 1990 to 2009. This method is based on the calculation of rainfall energy per unit depth of rainfall, total storm kinetic energy (E), rainfall intensity for a particular increment of a rainfall, and maximum 30 minute rainfall intensity. Furthermore, EI30 were computed, and then GIS method was used to create rainfall erosivity maps. The annual rainfall erosivity values prediction model was developed based on MFI values.
AB - Land erosion is regarded as one of the most important phenomenon causes land degradation. In revised universal soil loss equation (RUSLE) erosion model, rainfall erosivity factor (R) is one of the important parameters. Ideally, the calculation of EI30 (R factor) uses breakpoint rainfall intensity data which is calculated manually from graphical charts that are generated by continuously recording rain gauges. However, due to limited availability of breakpoint rainfall data, many simple methods for estimating EI30 have been developed by using yearly, monthly and daily rainfall data. In this research, due to limited data availability, pluviograph data at 10 minute interval from eight stations in Hitotsuse basin were used to compute EI 30 (R factor) for RUSLE. The approach used in this research is based on storm rainfall and duration data from 1990 to 2009. This method is based on the calculation of rainfall energy per unit depth of rainfall, total storm kinetic energy (E), rainfall intensity for a particular increment of a rainfall, and maximum 30 minute rainfall intensity. Furthermore, EI30 were computed, and then GIS method was used to create rainfall erosivity maps. The annual rainfall erosivity values prediction model was developed based on MFI values.
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U2 - 10.1109/GEOINFORMATICS.2010.5568195
DO - 10.1109/GEOINFORMATICS.2010.5568195
M3 - Conference contribution
AN - SCOPUS:77958038454
SN - 9781424473021
T3 - 2010 18th International Conference on Geoinformatics, Geoinformatics 2010
BT - 2010 18th International Conference on Geoinformatics, Geoinformatics 2010
T2 - 2010 18th International Conference on Geoinformatics, Geoinformatics 2010
Y2 - 18 June 2010 through 20 June 2010
ER -
