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《Journal of Lanzhou University》 1999-01
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Research on the Estimation Methods of Precipitation Resource for Rain harvesting Agriculture

Dai Ruolan, Liang Tiangang, Xu Yuqing, Wang Xizhi (The State Key Laboratory of Arid Agroecology, Lanzhou University, Lanzhou, 730000, China)  
Based on the rainfall data and topographic maps at 25 observation stations around Dingxi County, the grid digital elevation models(DEM) in the related areas and the spatial database of annual average precipitation(AAP) and relative information in the late 34 years at each station were established. According to the statistics, spatial interpolations and comprehensive methods, the spatial distributions and changes of AAP for 34 years, AAP coefficients of variation, AAP under different rainfall probabilities, AAP in arid and humid years and average rainfall in rainy seasons and growing seasons for spring wheat were modelled. At the same time, simulated precision of each method was estimated by 5 test stations, and the AAP was calculated by using the above databases on different scales(i.e, villages and catchments in the related areas). Results indicated that the comprehensive method had the highest simulation precision in the 9 approaches(inverse distance weighted, trend, spline, ordinary Kriging, universal Kriging one, universal Kriging two, multi variable regression and comprehensive methods), its maximum relative error was 6.895%. The next was ordinary Kriging method, and its maximum error reached to 6.756%. As far as the 7 interpolation approaches were concerned, the precision of ordinary Kriging method was the best. The error of statistical model was relatively high, of which the maximum relative error was 9.041%. The AAP estimation system established by the measured and predicted rainfall spatial databases could quickly and timely calculate the spatial distributions and changes on any scales in the related areas, and it had an important influence in the agricultural engineering planning, development strategy and decision making as well as water management in rain harvesting agriculture.
【Fund】: 农业部和水利部联合资助项目
【CateGory Index】: S161.6
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