CMORPH数据在吉林省降雨侵蚀力计算中的应用
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摘要
基于气象站点降雨数据,对30 min时间分辨率的CMORPH遥感反演降雨数据进行精度分析,并采用CMORPH数据计算吉林省2016年降雨侵蚀力,得到了以下结论:①CMORPH数据与气象站点数据相比较,整体相关系数大于0.6,日降雨量和月降雨量平均误差较小,可以较为准确地反映吉林省降雨状况;②通过高时相的CMORPH数据计算得到降雨侵蚀力,既可以满足空间上的精确性,又可以排除非侵蚀性降雨的干扰,计算结果较为精确;③吉林省2016年平均降雨侵蚀力为537.48 MJ·mm/(hm~2·h·a),其中松原市平均降雨侵蚀力最高,延边朝鲜族自治州最低。
The paper made accuracy analysis on CMORPH remote sensing inversion rainfall data with time resolution of 30 minutes based on the rainfall data of meteorological stations and sites. It calculated the rainfall erosivity of Jilin Province in 2016 by using CMORPH data and obtained the following conclusions. a) Comparing the data of CMORPH and meteorological stations and sites,the overall correlation coefficient is greater than 0.6 and the average error of daily rainfall and monthly rainfall is smaller which can comparatively reflect the rainfall in Jilin Province; b) the rainfall erosivity obtained through the calculation of CMORPH data of high temporal phase can not only satisfy the spatial accuracy,but also eliminate the interference of non-erosive rainfall and satisfy the accuracy of the calculation results and; c) The average rainfall erosivity of Jilin Province in 2016 was 537.48 MJ·mm/( hm~2·h·a),of which,the average rainfall erosivity of Songyuan City was the highest and Yanbian Korean Autonomous Prefecture was the lowest.
The paper made accuracy analysis on CMORPH remote sensing inversion rainfall data with time resolution of 30 minutes based on the rainfall data of meteorological stations and sites. It calculated the rainfall erosivity of Jilin Province in 2016 by using CMORPH data and obtained the following conclusions. a) Comparing the data of CMORPH and meteorological stations and sites,the overall correlation coefficient is greater than 0.6 and the average error of daily rainfall and monthly rainfall is smaller which can comparatively reflect the rainfall in Jilin Province; b) the rainfall erosivity obtained through the calculation of CMORPH data of high temporal phase can not only satisfy the spatial accuracy,but also eliminate the interference of non-erosive rainfall and satisfy the accuracy of the calculation results and; c) The average rainfall erosivity of Jilin Province in 2016 was 537.48 MJ·mm/( hm~2·h·a),of which,the average rainfall erosivity of Songyuan City was the highest and Yanbian Korean Autonomous Prefecture was the lowest.
引文
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[12] 许时光,牛铮,沈艳,等.CMORPH卫星降水数据在中国区域的误差特征研究[J].遥感技术与应用,2014,29(2):189-194.
[13] 成璐,沈润平,师春香,等.CMORPH和TRMM 3B42降水估计产品的评估检验[J].气象,2014,40(11):1372-1379.
[14] 张宪奎,许靖华,卢秀琴,等.黑龙江省土壤流失方程的研究[J].水土保持通报,1992,12(4):1-9,18.
[2] WISCHMEIER W H,SMITH D D.Rainfall energy and its relationship to soil loss[J].Eos,Transactions American Geophysical Union,1958(39):285-291.
[3] FOSTER G R,LOMBARDI F,MOLDENHAUER W C.Evaluation of Rainfall-Runoff Erosivity factors for individual storms[J].Transactions of the ASABE,1982,25(1):124-129.
[4] 小高和则,远藤治郎.关于林地内外雨滴侵蚀的研究[J].洪双旌,译.中国水土保持,1986(4):58-61.
[5] 张宪奎,卢秀琴,詹敏,等.土壤流失预报方程中R指标的研究[J].水土保持科技情报,1991(4):49,48.
[6] 吴素业.安徽大别山区降雨侵蚀力指标的研究[J].中国水土保持,1992(2):32-33.
[7] 黄炎和,卢程隆,郑添发,等.闽东南降雨侵蚀力指标R值的研究[J].水土保持学报,1992(4):1-5.
[8] 郭子萍,王乃昂,屈志勇.基于RUSLE的引黄入晋北干线沿线地区土壤侵蚀定量研究[J].水土保持通报,2018,38(3):180-186,192,封2.
[9] 秦志佳.基于遥感调查和RUSLE模型的贵州省土壤侵蚀对比研究[D].贵阳:贵州师范大学,2017:38-40.
[10] 朱强,陈秀万,樊启祥,等.基于TRMM的降雨侵蚀力计算方法[J].中国科学:技术科学,2011,41(11):1483-1492.
[11] 王凯,陈璐,马金辉,等.TRMM数据在中国降雨侵蚀力计算中的应用[J].干旱区地理,2015,38(5):948-959.
[12] 许时光,牛铮,沈艳,等.CMORPH卫星降水数据在中国区域的误差特征研究[J].遥感技术与应用,2014,29(2):189-194.
[13] 成璐,沈润平,师春香,等.CMORPH和TRMM 3B42降水估计产品的评估检验[J].气象,2014,40(11):1372-1379.
[14] 张宪奎,许靖华,卢秀琴,等.黑龙江省土壤流失方程的研究[J].水土保持通报,1992,12(4):1-9,18.