Despite being in arid and semi-arid areas,erosion is largely a result of infrequent but heavy rainfall events; therefore,rainfall erosivity data can be used as an indicator of potential erosion risks.The purpose of th...Despite being in arid and semi-arid areas,erosion is largely a result of infrequent but heavy rainfall events; therefore,rainfall erosivity data can be used as an indicator of potential erosion risks.The purpose of this study was to investigate the spatial distribution of annual rainfall erosivity in North Jordan.A simplified procedure was used to correlate erosivity factor R values in both the universal soil loss equation (USLE) and the revised universal soil loss equation (RUSLE) with annual rainfall amount or modified Fournier index (F mod ).Pluviometric data recorded at 18 weather stations covering North Jordan were used to predict R values.The annual values of erosivity ranged between 86-779 MJ mm ha ?1 h ?1 year ?1 .The northwest regions of Jordan showed the highest annual erosivity values,while the northeastern regions showed the lowest annual erosivity values.展开更多
Soil erosion by water is the most important land degradation problem worldwide. In this paper a new procedure was developed to estimate the rainfall-runoff erosivity factor （R） based on Tropical Rainfall Measuring M...Soil erosion by water is the most important land degradation problem worldwide. In this paper a new procedure was developed to estimate the rainfall-runoff erosivity factor （R） based on Tropical Rainfall Measuring Mission （TRMM） satellite-estimated precipitation data, which consists of 3-h rainfall intensity data. In this method, R was calculated as the product of the maximum 180-min rainfall intensity and the rainfall energy. This procedure was applied to the Daling River basin in Liaoning Province, China, R in terms of yearly, monthly and event-based rainfall in 2005 was computed separately using TRMM 3B42 data. The TRMM data showed a significant correlation with the interpolated rain-gauge data. Furthermore, because the TRMM data are based on rainfall intensity, they can represent the impact on erosion more accurately. It reflects both the spatial distribution and the intensity of rainfall. The procedure is a new approach to estimate the rainfall erosivity for soil water erosion modeling, especially in areas lacking rain-gange stations.展开更多
基金Supported by the Deanship of Research, Jordan University of Science and Technology (No. 91/2004)
文摘Despite being in arid and semi-arid areas,erosion is largely a result of infrequent but heavy rainfall events; therefore,rainfall erosivity data can be used as an indicator of potential erosion risks.The purpose of this study was to investigate the spatial distribution of annual rainfall erosivity in North Jordan.A simplified procedure was used to correlate erosivity factor R values in both the universal soil loss equation (USLE) and the revised universal soil loss equation (RUSLE) with annual rainfall amount or modified Fournier index (F mod ).Pluviometric data recorded at 18 weather stations covering North Jordan were used to predict R values.The annual values of erosivity ranged between 86-779 MJ mm ha ?1 h ?1 year ?1 .The northwest regions of Jordan showed the highest annual erosivity values,while the northeastern regions showed the lowest annual erosivity values.
基金supported by the National High Technology Research and Development Program of China("863"Program)(Grant No. 2008AA12Z112)
文摘Soil erosion by water is the most important land degradation problem worldwide. In this paper a new procedure was developed to estimate the rainfall-runoff erosivity factor （R） based on Tropical Rainfall Measuring Mission （TRMM） satellite-estimated precipitation data, which consists of 3-h rainfall intensity data. In this method, R was calculated as the product of the maximum 180-min rainfall intensity and the rainfall energy. This procedure was applied to the Daling River basin in Liaoning Province, China, R in terms of yearly, monthly and event-based rainfall in 2005 was computed separately using TRMM 3B42 data. The TRMM data showed a significant correlation with the interpolated rain-gauge data. Furthermore, because the TRMM data are based on rainfall intensity, they can represent the impact on erosion more accurately. It reflects both the spatial distribution and the intensity of rainfall. The procedure is a new approach to estimate the rainfall erosivity for soil water erosion modeling, especially in areas lacking rain-gange stations.
