Ng, Pei Pei (2005) Estimating The R-Factor With Limited Rainfall Data In Peninsular Malaysia. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Awam. (Submitted)
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Abstract
Rainfall-runoff erosivity factor (R) of the revised universal soil loss equation (RUSLE) is one of the important indicators to predict erosion risks. However, lack of long term and continuous pluviograph data is becoming a problem to determine the R factor. This problem does not only exist in Malaysia but everywhere in the world as shown by researchers around the world. The purpose of this study is to develop models (equations) for calculating the R-factor with only daily and monthly data for Peninsular Malaysia (mainly for the northern part of Peninsular Malaysia). Hourly and daily data of six different stations were used to create these equations. One of the methods used was by using the Fournier index. A relationship between the rainfall erosivity and the Fournier index was determined. Another method was to get a relationship involving three parameters which are the monthly rainfall erosivity (EI30), monthly rainfall for days with ≥ 10mm and monthly number of days with rainfall ≥ 10mm. These two equations which are produced in this study can be used to determine the rainfall-runoff erosivity factor with just daily and monthly data. From this study, the annual rainfall erosivity calculated in northern Peninsular Malaysia ranged from 6576 to 9094 MJ mm ha-1 h-1 year-1. A geographic information system (GIS) was used to interpolate the values and generate a map to show spatial variations of the rainfall erosivity. Maps for monthly and annual rainfall erosivity factor distribution are developed.
| Item Type: | Monograph (Project Report) |
|---|---|
| Subjects: | T Technology T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Kampus Kejuruteraan (Engineering Campus) > Pusat Pengajian Kejuruteraan Awam (School of Civil Engineering) > Monograph |
| Depositing User: | Mr Engku Shahidil Engku Ab Rahman |
| Date Deposited: | 02 Mar 2023 08:19 |
| Last Modified: | 02 Mar 2023 08:19 |
| URI: | http://eprints.usm.my/id/eprint/57169 |
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