USLE和RUSLE估算草地土壤流失量的评价。

K. Spaeth, F. Pierson, M. Weltz, W. H. Blackburn
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引用次数: 69

摘要

利用8个州、22个站点、132个样地不同植被类型的降雨模拟数据,对通用土壤流失方程(USLE)和修正通用土壤流失方程(RUSLE 1.06)进行了评估。在2天的时间内,对研究地块进行干、湿和极湿降雨模拟处理。干湿模拟处理的降雨模拟速率为65mm/hr,极湿模拟处理的降雨模拟速率为65 ~ 130 mm/hr。在具有代表性的模拟运行中,所有地块的平均土壤流失量分别为:干、湿和极湿模拟处理的0.011 kg/m2、0.007 kg/m2和0.035 kg/m2。干、湿、极湿模拟处理下USLE的Nash-Sutcliffe模型效率(R2eff)和三种复合模拟处理(汇总数据)测量的所有土壤流失量之和均为负。这表明,从田间降雨模拟中观测到的平均土壤流失量优于USLE预测的土壤流失量。USLE在所有3个降雨模拟处理中都倾向于一致地高估土壤流失量。随着USLE预测值的增大,预测值与实测值之间的误差方差增大。Nash-Sutcliffe模型对RUSLE的效率也为负,除了使用RUSLE手册(C(表))中的RUSLE覆盖管理子因子参数(R2eff = 0.16)、NRCS土壤可蚀性因子(K)的干流模拟处理[R2eff = 0.16];R2eff = 0.17,其中C(表)和K由土壤可蚀性nomograph估算]。与USLE相比,土壤流失量观测值与RUSLE预测值误差较小。RUSLE误差方差表明,3个降雨模拟处理的土壤流失量偏低趋势一致。采用实际田间实测根系生物量、植物产量和土壤随机粗糙度值计算RUSLE C子因子时,干、湿、极湿降雨模拟处理和汇总数据的R2eff值均为负值。DOI: 10.2458 / azu_jrm_v56i3_spaeth
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of USLE and RUSLE estimated soil loss on rangeland.
The Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE 1.06) were evaluated with rainfall simulation data from a diverse set of rangeland vegetation types (8 states, 22 sites, 132 plots). Dry, wet, and very-wet rainfall simulation treatments were applied to the study plots within a 2-day period. The rainfall simulation rate was 65mm/hr for the dry and wet simulation treatments and alternated between 65-130 mm/hr for the very-wet treatment. Average soil loss for all plots for the representative simulation runs were: 0.011 kg/m2, 0.007 kg/m2, and 0.035 kg/m2 for the dry, wet, and very-wet simulation treatments, respectively. The Nash-Sutcliffe Model efficiencies (R2eff) of the USLE for the dry, wet, very-wet simulation treatments and sum of all soil loss measured in the three composite simulation treatments (pooled data) were negative. This indicates that the observed mean measured soil loss from the field rainfall simulations is better than predicted USLE soil loss. The USLE tended to consistently overpredict soil loss for all 3 rainfall simulation treatments. As the USLE predicted values increased in magnitude, the error variance between predicted and observed soil loss increased. Nash-Sutcliffe model efficiency for the RUSLE was also negative, except for the dry run simulation treatment [R2eff = 0.16 using RUSLE cover management (C) subfactor parameters from the RUSLE manual (C(table)), NRCS soil erodibility factor (K); and R2eff = 0.17 with C(table) and K estimated from the soil-erodibility nomograph]. In comparison to the USLE, there was less error between observed and RUSLE predicted soil loss. The RUSLE error variances showed a consistent trend of underpredicted soil loss among the 3 rainfall simulation treatments. When actual field measured root biomass, plant production and soil random roughness values were used in calculating the RUSLE C subfactors: the R2eff values for the dry, wet, very-wet rainfall simulation treatments and the pooled data were all negative. DOI:10.2458/azu_jrm_v56i3_spaeth
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