摘要
降雨侵蚀力空间插值的不确定性直接关系到土壤侵蚀的模拟结果和预测精度。利用浙江省金华市51个自动气象站近5年的逐日降雨资料,探讨了降雨侵蚀力空间插值过程中由插值方法、格网大小以及站网密度等因素所造成的降雨侵蚀力(R因子)不确定性,在此基础上,分析了R因子不确定性对土壤侵蚀量模拟结果的影响。研究表明:1)对于站网密度较高的自动站而言,插值方法和格网大小对R因子不确定性的影响不大,对R插值精度起决定作用的是站网密度;2)标准小区条件下,R因子不确定性可导致土壤侵蚀模拟结果的绝对误差在200t/(hm2·a)以上,因而很难在红黄壤区根据通用土壤流失方程的模拟结果准确区分无明显侵蚀区和轻度侵蚀区;3)土壤侵蚀模拟中需要考虑各因子误差的叠加和累积效应,在其他因子相对误差为10%条件下,使用研究区36个站点进行插值,侵蚀量模拟结果的最大相对误差可超过40%。
The uncertainty in interpolation of rainfall erosivity data can directly influence the results and predicting accuracy of soil erosion modeling. In this paper, the daily rainfall data of past five years obtained from 51 automatic weather stations in Jinhua, Zhejiang Province of eastern China was used to explore the uncertainty, which was caused by interpolation methods, output grid size, station density, etc. On this basis, the effects of uncertainty on soil erosion modeling were analyzed. The results showed that: 1)for the automatic weather stations which were densely distributed, station density was much more important to the interpolation of rainfall erosivity data than interpolation methods and output grid size; 2)the absolute error of soil erosion modeling result caused by the uncertainty of R-factor was more than 200 t/(hm2·a) under standard unit plot condition, which made it difficult to tell apart the non-eroded and light erosion area in red-yellow soil region; 3) the effects of error addition and accumulation should be considered in modeling soil erosion. On condition that the relative error for any of the other erosion factor was 10%, the maximum relative error for soil erosion modeling may reach more than 40% when 36 weather stations were used for interpolation.
出处
《北京林业大学学报》
CAS
CSCD
北大核心
2013年第1期30-35,共6页
Journal of Beijing Forestry University
基金
国家自然科学青年基金项目(40901062)