Risk assessment of soil erosion in different rainfall scenarios by RUSLE model coupled with Information Diffusion Model: A case study of Bohai Rim, China

被引:123
作者
Xu, Lifen
Xu, Xuegong [1 ]
Meng, Xiangwei
机构
[1] Peking Univ, Coll Urban & Environm Sci, Beijing 100871, Peoples R China
关键词
Soil erosion risk; RUSLE; IDM; Exceeding probability; Geographically Weighted Regression; Bohai Sea Rim; LOSS EQUATION; WATER;
D O I
10.1016/j.catena.2012.08.012
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Risk assessment of soil erosion addresses the likelihood of the occurrence of erosion as well as its consequences. This in turn can provide precautionary and relevant suggestions to assist with disaster reduction. In light of the great threat of soil erosion to global soil resources, it is necessary to implement this type of risk assessment This study aims to appraise the risk of soil erosion caused by water along the Bohai Sea region during the rainy season. A new method, namely the RUSLE-IDM coupled model, which embeds the IDM (Information Diffusion Model) into the RUSLE(Revised Universal Soil Loss Equation)model, is applied to reveal soil erosion risk in different scenarios, with rainfall exceeding the probability of 0.1 and 0.02 respectively. From this case study, three conclusions can be drawn as follows: (i) This coupled method can effectively examine soil erosion risk and show comparable results of different scenarios, which cannot only calculate the erosion amount, but also identify the likelihood; (ii) Soil erosion caused by water is serious from July to September, but comparatively speaking, the greatest amount of attention should be paid to the prevention of soil erosion in July, as the erosion amount at this time is times larger than during September; (iii) Vegetation coverage and soil erosion control practices are controllable and important factors for the future soil conservation in this area. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:74 / 82
页数:9
相关论文
共 31 条
[1]   Soil erosion prediction using RUSLE for central Kenyan highland conditions [J].
Angima, SD ;
Stott, DE ;
O'Neill, MK ;
Ong, CK ;
Weesies, GA .
AGRICULTURE ECOSYSTEMS & ENVIRONMENT, 2003, 97 (1-3) :295-308
[2]  
[Anonymous], 1980, 26 DEP AGR WASH
[3]  
[Anonymous], 1978, AGR HDB
[4]  
Chen Z.F., 2006, FUZZY SYSTEMS MATH, P42
[5]   Empirical reformulation of the Universal Soil Loss Equation for erosion risk assessment in a tropical watershed [J].
Cohen, MJ ;
Shepherd, KD ;
Walsh, MG .
GEODERMA, 2005, 124 (3-4) :235-252
[6]  
Duan L.Y., 2011, 28 CHIN MET SOC ANN, P2106
[7]   The application of fuzzy risk in researching flood disasters [J].
Feng, Li-Hua ;
Hong, Wei-Hu ;
Wan, Zi .
NATURAL HAZARDS, 2010, 53 (03) :413-423
[8]   Indicators for pan-European assessment and monitoring of soil erosion by water [J].
Gobin, A ;
Jones, R ;
Kirkby, M ;
Campling, P ;
Govers, G ;
Kosmas, C ;
Gentile, AR .
ENVIRONMENTAL SCIENCE & POLICY, 2004, 7 (01) :25-38
[9]   The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models [J].
Gutman, G ;
Ignatov, A .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1998, 19 (08) :1533-1543
[10]  
Huang C.F., 1998, J NATURAL DISASTERS, P4