Determining the best rainfall erosivity index in a cold semi-arid region(Case study: Kaboudeh Oliya Soil Research Station, Kermanshah province, Iran)
2007
Hemmati, Mohammad | Nikkami, Davud | Ahmadi, Hasan | Zehtabian, Gholamreza | Jafari, Mohammad
Soil is one of the four elements of life and one of the most important agricultural and rangeland production factors. Soil erosion has impact on fertility of upstream lands and indirectly causes downstream damages. On a global scale, more than 50% of rangelands and about 80% of farmlands are significantly suffering from soil erosion and sedimentation phenomenon. In spite of agricultural importance of rainwater, its erosive energy in the primary stages of water erosion, detaches soil particles and makes surface runoff which has the most important impacts on soil erosion. The effective energy in this shape of erosion is called rainfall erosivity, which is rainfall erosion potential and depends on rainfall physical characteristics. Some different indices are developed for quantification of rainfall erosivity. Some indices emphasise on the amount of rainfall or rain intensity. Worldwide investigations show that applying a certain index, like EI60 in USLE equation has not sufficient credit and according to climatic condition the best rainfall erosivity index should be determined. In this research, after establishing 21 erosion plots in Kaboudeh Oliya village, Kermanshah city, on two land use types of dry farming on 6, 12, 16 and 17 percent of slope and rangelands on 25, 35 and 45 percent slopes with three repetitions, 15 rainfall events which produced surface runoff were monitored by a recording rain gauge and the amount of surface runoff and sediment were measured. According to the literature, 45 rainfall erosivity indices were chosen to be compared. For facilitating and increasing accuracy of calculations on rainfall erosivity indices, a computer program was developed to analyze and extract necessary factors from each storm. To choose the best rainfall erosivity index, SPSS software was used for statistical analysis between soil loss as dependent variable and rainfall erosivity index as independent variable. The result showed that in the study area, EI60 is the best rainfall erosivity index and has maximum correlation coefficient of 0.721 with soil loss.
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