Application of Web ERosivity Module (WERM) for estimation of annual and monthly R factor in Korea

作者：Risal Avay; Bhattarai Rabin; Kum Donghyuk; Park Youn Shik; Yang Jae E; Lim Kyoung Jae^*

来源：Catena, 2016, 147: 225-237.

DOI：10.1016/j.catena.2016.07.017

• Soil erosion
• USLE R
• Erosivity
• Rainfall
• Model
• Regression equation

Soil erosion is a very serious problem from agricultural as well as environmental point of view. Various computer models have been used to estimate soil erosion and assess erosion control practice. Universal Soil Loss Equation (USLE) is one of the most frequently used soil loss estimation models which have been used in many countries around the world. Erosivity (USLE R-factor) is one of the USLE input parameters to reflect impacts of rainfall in computing soil loss. R factor for a specific rainfall event depends upon maximum rainfall intensity of specific period and kinetic energy of that event Annual R factor is calculated as the sum of erosivities of such rainfall events that occurred. It is usually calculated from rainfall data having higher temporal resolution but the process of calculation is very tedious and also the higher temporal resolution data are not readily available in many parts of the world. Various regression models have been developed to estimate monthly R factor as well as annual R factor using monthly/yearly rainfall amount However, it is rarely allowed to estimate R factor with higher accuracy using these models since they were developed from obsolete dataset and also only the rainfall amount was used for an input parameter without rainfall intensity. In this study, a web-based Erosivity estimation system (Web ERosivity Module-WERM) was developed to compute R factor using 10 min interval rainfall data. The model was then tested for 75 different cities in Korea using the rainfall data of 15 to 18 years from 1997 to 2014 obtained from Korea Meteorological Administration (KMA). Using the monthly rainfall data and R factor values obtained from the model, regression equation for 25 cities was developed to estimate monthly R factor from the monthly rainfall with amount and intensity of rainfall considered. The coefficient of determination (R-2) of the regression equation ranged from 0.75 to 0.92. This indicated that these regression equations can be used to estimate the value of R-factor from the monthly rainfall data with more than 75% accuracy. The WERM is very simple to use and it can be a very effective tool to compute R factor using higher temporal resolution rainfall data. Along with this, it is possible to calculate R factor using local daily rainfall with the help of regression equations which are available for 25 cities in South Korea till now.

• 出版日期2016-12