Impact of Land Use/Cover Changes on Soil Erosion in Western Kenya

被引:36
作者
Kogo, Benjamin Kipkemboi [1 ]
Kumar, Lalit [1 ]
Koech, Richard [2 ]
机构
[1] Univ New England, Sch Environm & Rural Sci, Armidale, NSW 2351, Australia
[2] Cent Queensland Univ, Dept Agr Sci & Environm, Bundaberg, Qld 4670, Australia
关键词
agricultural sustainability; land use; cover; land degradation; erosivity; erodibility; RUSLE; western Kenya; LOSS EQUATION RUSLE; WATER EROSION; CLIMATE-CHANGE; GIS FRAMEWORK; MANAGEMENT; CATCHMENT; RISK; INTENSITY; QUALITY; MAIZE;
D O I
10.3390/su12229740
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study examined the impact of land use/cover changes on soil erosion in western Kenya in the years 1995 and 2017. The study used the GIS-based Revised Universal Soil Loss Equation (RUSLE) modelling approach and remote sensing assessment. The results showed that the average soil loss through sheet, rill and inter-rill soil erosion processes was 0.3 t/ha/y and 0.5 t/ha/y, in the years 1995 and 2017, respectively. Of the total soil loss, farms contributed more than 50%, both in 1995 and 2017 followed by grass/shrub (7.9% in 1995 and 11.9% in 2017), forest (16% in 1995 and 11.4% in 2017), and the least in built-up areas. The highest soil erosion rates were observed in farms cleared from forests (0.84 tons/ha) followed by those converted from grass/shrub areas (0.52 tons/ha). The rate of soil erosion was observed to increase with slope due to high velocity and erosivity of the runoff. Areas with high erodibility in the region are found primarily in slopes of more than 30 degrees, especially in Mt. Elgon, Chereng'anyi hills and Elgeyo escarpments. This study forms the first multi-temporal assessment to explore the extent of soil erosion and seeks to provide a useful knowledge base to support decision-makers in developing strategies to mitigate soil erosion for sustainable crop production.
引用
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页码:1 / 17
页数:17
相关论文
共 65 条
[51]  
Ringius L., 1996, CICERO REP, V8, P84
[52]   Fertility capability soil classification: a tool to help assess soil quality in the tropics [J].
Sanchez, PA ;
Palm, CA ;
Buol, SW .
GEODERMA, 2003, 114 (3-4) :157-185
[53]   Comparison between ordinary kriging (OK) and inverse distance weighted (IDW) based on estimation error. Case study: Dardevey iron ore deposit, NE Iran [J].
Shahbeik, Shahab ;
Afzal, Peyman ;
Moarefvand, Parviz ;
Qumarsy, Mania .
ARABIAN JOURNAL OF GEOSCIENCES, 2014, 7 (09) :3693-3704
[54]   Soil conservation planning at the small watershed level using RUSLE with GIS: a case study in the Three Gorge Area of China [J].
Shi, ZH ;
Cai, CF ;
Ding, SW ;
Wang, TW ;
Chow, TL .
CATENA, 2004, 55 (01) :33-48
[55]  
Singh G, 1981, Bulletin
[56]   Heterogeneity of crop productivity and resource use efficiency within smallholder Kenyan farms: Soil fertility gradients or management intensity gradients? [J].
Tittonell, P. ;
Vanlauwe, B. ;
de Ridder, N. ;
Giller, K. E. .
AGRICULTURAL SYSTEMS, 2007, 94 (02) :376-390
[57]  
Van der Knijff J, 2000, Soil erosion risk assessment in Europe
[58]   Mapping multiple variables for predicting soil loss by geostatistical methods with TM images and a slope map [J].
Wang, GX ;
Gertner, G ;
Fang, SF ;
Anderson, AB .
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2003, 69 (08) :889-898
[59]  
Waswa B, 2012, THESIS
[60]  
Williams J. R., 1990, EPIC-Erosion/Productivity Impact Calculator Technical Bulletin, V1768