Land-use adjustment with a modified soil loss evaluation method supported by GIS

Land-use structure information is of significance in evaluation of soil loss owing to the contributions of various land-use patterns with different relative importance to soil and water conservation. In previous studies, a land-use structure characteristic index (SI), defined as the sum of products between each weighted land-use type and the percentage of the impacted area in the whole test region, was proposed to reflect the resulting impacts of human factors and serve as an indirect measure of soil loss variation. In this paper, the SI was modified with consideration of spatial distribution of land-use in terms of the minimal distance between a specific land patch and a river, either the main stem or one of the primary tributaries. A topographic factor was also introduced to correct the SI. Soil loss was evaluated with support of GIS through a case study at Zhifanggou, a small catchment in the Yanhe watershed in the middle part of the Loess plateau. Comparison was made between the soil losses before and after the adjustment of land-use types since 1987 according to the governmental ordinance aiming at ecological rehabilitation. It was found that the land-use adjustment in the last 12 years has been in a fight direction toward minimizing soil loss, but the difference of the actual SI in 1999 and the predicted SI corresponding to the potential optimal land-use structure implies that more efforts should be made in land-use conversion in the coming years.

[1]  A. D. Roo,et al.  LISEM: A SINGLE‐EVENT, PHYSICALLY BASED HYDROLOGICAL AND SOIL EROSION MODEL FOR DRAINAGE BASINS. II: SENSITIVITY ANALYSIS, VALIDATION AND APPLICATION , 1996 .

[2]  G. R. Foster,et al.  RUSLE: Revised universal soil loss equation , 1991 .

[3]  Graciela Metternicht,et al.  Evaluating the information content of JERS-1 SAR and Landsat TM data for discrimination of soil erosion features , 1998 .

[4]  D. Flanagan,et al.  The USDA Water Erosion Prediction Project (WEPP) , 1997 .

[5]  Liu Suhua EVOLUTION OF THE SOIL EROSION MODEL , 2002 .

[6]  S. M. de Jong,et al.  Regional assessment of soil erosion using the distributed model SEMMED and remotely sensed data , 1999 .

[7]  Rorke B. Bryan,et al.  The relationship of soil loss by interrill erosion to slope gradient. , 2000 .

[8]  M. C. Bronsveld,et al.  A knowledge-based approach for C-factor mapping in Spain using Landsat TM and GIS , 1996 .

[9]  H. D. Scott,et al.  Applications of fuzzy logic to the prediction of soil erosion in a large watershed , 1998 .

[10]  Approach to soil erosion assessment in terms of land-use structure changes , 2003 .

[11]  J. Lemunyon,et al.  Predicting soil erosion in conservation tillage cotton production systems using the revised universal soil loss equation (RUSLE) , 2001 .

[12]  T. Saaty How to Make a Decision: The Analytic Hierarchy Process , 1990 .

[13]  W. H. Wischmeier,et al.  Predicting rainfall erosion losses : a guide to conservation planning , 1978 .

[14]  W. G. Knisel,et al.  CREAMS: a field scale model for Chemicals, Runoff, and Erosion from Agricultural Management Systems [USA] , 1980 .