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在世界各国广泛的研究由暴雨引发的土沙灾害,应用土壤雨量指数制定预防土沙灾害对策,设定雨量警戒、避难的基准。但靠降雨资料获得的数据对土壤斜面滑坡构成的因素差异很大,不能反映各测试区域不同地形、土壤结构的实际情况。2011年日本宇都宫大学执印康裕等人围绕引起土壤滑坡发生的地形因子,应用程序模型对一定空间范围内适宜降雨特性的评价方法进行研究。通过模型中输出的数据对土壤潜在滑坡面积指数进行定义,并与土壤雨量指数进行比较。该研究明确了2个指数都能检测出致滑坡发生和非致滑坡发生的暴雨的差别;并能检测出滑坡发生和非发生的暴雨的不同。
In all countries in the world, it has conducted extensive research on soil and sand disasters caused by heavy rain, formulated measures for preventing earth and sand disasters using the soil rainfall index, and set the benchmark for rainfall alert and evacuation. However, the data obtained from the rainfall data have very different factors on the soil slope landslide, and can not reflect the actual situation of different topography and soil structure in each test area. In 2011, Ujiya University, Japan, such as print-Kang Yu and others around the cause of soil landslides caused by the topography factor and application model for a certain range of rainfall characteristics of appropriate evaluation methods. The potential landslide area index of soil is defined by the data output in the model and compared with the soil rainfall index. The study identified that both indices can detect the difference between rainstorms occurring in landslides and non-landslides; and that the difference between landslides and non-occurrence rainstorms can be detected.