Uncertainty assessment of soil erodibility factor for revised universal soil loss equation

被引:89
作者
Wang, GX
Gertner, G
Liu, XZ
Anderson, A
机构
[1] Univ Illinois, Dept Nat Resources & Environm Sci, Urbana, IL 61801 USA
[2] USACERL, Champaign, IL 61820 USA
关键词
uncertainty assessment; spatial prediction; soil erodibility; simulation;
D O I
10.1016/S0341-8162(01)00158-8
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Soil erodibility accounts for the influence of the intrinsic soil properties on soil erosion and is one of six factors in the Revised Universal Soil Loss Equation (RUSLE), a most widely used model to predict long-term average annual soil loss. In a traditional soil survey, each of the soil types (classes) is assigned with a soil erodibility value that is assumed to be constant over time. However, heterogeneity of soil in time and in space tends to support the concept that soil erodibility depends dynamically and spatially on the set of properties of a specific soil. This study statistically compared the published soil erodibility values with those from a set of soil samples in terms of their differences. The published values tend to underestimate soil erodibility. This feature is also supported by the uncertainty assessment in difference maps of the published K values versus those from soil samples. Spatial prediction and uncertainty analysis of the soil erodibility from the set of soil samples was carried out using a sequential Gaussian simulation. The results show that the simulation produces a reliable prediction map of soil erodibility and can be recommended as a monitoring strategy to spatially update soil erodibility.
引用
收藏
页码:1 / 14
页数:14
相关论文
共 24 条
[1]  
[Anonymous], 1995, SOIL CONSERV
[2]   SAMPLING STRATEGIES FOR FERTILITY ON A STOY SILT LOAM SOIL [J].
CHUNG, CK ;
CHONG, SK ;
VARSA, EC .
COMMUNICATIONS IN SOIL SCIENCE AND PLANT ANALYSIS, 1995, 26 (5-6) :741-763
[3]  
DEMARAIS S, 1999, ECOSYSTEMS WORLD, V16, P385
[4]  
Deutsch C.V., 1998, GSLIB Geostatistical Software Library and User's Guide., VSecond, P369
[5]  
Goovaerts P., 1997, GEOSTATISTICS NATURA
[6]   Comparison of kriging and inverse-distance methods for mapping soil parameters [J].
Gotway, CA ;
Ferguson, RB ;
Hergert, GW ;
Peterson, TA .
SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 1996, 60 (04) :1237-1247
[7]  
HOSSEINI E, 1994, T ASAE, V37, P1799, DOI 10.13031/2013.28269
[8]   Probabilistic assessment of ground-water contamination .2. Results of case study [J].
Istok, JD ;
Rautman, CA .
GROUND WATER, 1996, 34 (06) :1050-1064
[9]  
Jenny H., 1941, FACTORS SOIL FORMATI, P281, DOI DOI 10.2307/211491
[10]   Propagating uncertainty through spatial estimation processes for old-growth subalpine forests using sequential Gaussian simulation in GIS [J].
Mowrer, HT .
ECOLOGICAL MODELLING, 1997, 98 (01) :73-86