Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation

  • 1 State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2 Graduate University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2012-01-20

  Revised date: 2012-02-20

  Online published: 2012-06-30

Supported by

the Knowledge Innovation Program, Chinese Academy of Sciences (KZCX2-YW-442), National Basic Research Program of China (2007CB407207) and National Natural Science Foundation (40971236).


Critical source areas (CSAs), characterized by severe soil erosion and high sediment yield, are considered to have a high priority for conservation. How to identify CSAs and assess the effectiveness of conservation practices is a key issue in site-specific watershed management. The Soil and Water Assessment Tool (SWAT) model is a useful tool for site-specific conservation practices design and several studies have attempted to identify CSAs based on watershed models. However, limited research has reported about the effectiveness of conservation practices targeting CSAs. The aim of this study was to assess the effectiveness of conservation pracrices targeted on CSAs using the SWAT model. CSA was firstly identified based on the 4-year average yearly erosion of each HRU. Appropriate soil conservation practices were then designed for the CSAs. A scenario with conservation practices for the whole watershed was also established as the contrasting counter parts scheme and then compared to the outcome of CSA-targeted conservation pracrices. The result shows that SWAT can accurately simulate sediment yield in the study area. CSAs were mainly located in slope farmland areas and steep gullies, coinciding with the distribution of land use and slope. The identified CSA covered 20% of the HRUs and contributed on average 44% of sediment yield. Conservation practices targeting CSAs had higher sediment reduction effectiveness (24 115 t km-2 y-1) than conservation practice covering the whole watershed (20 290 t km-2 y-1). Thus conservation practices targeting CSAs are more effective than broad conservation practices. We conclude that soil conservation practices focusing on CSAs do increase sediment reduction effectiveness. Targeting the placement of soil conservation practices based on the CSAs concept will assist water quality control in watersheds.

Cite this article

CHEN Lajiao, ZHU Axing, QIN Chengzhi, LIU Junzhi . Effectiveness Assessment of Soil Erosion Critical Source Areas for Soil and Water Conservation[J]. Journal of Resources and Ecology, 2012 , 3(2) : 138 -143 . DOI: 10.5814/j.issn.1674-764x.2012.02.005


Arnold J G, R Srinivasan, R S Muttiah. 1998. Large area hydrologicmodeling and assessment. Part I: Model development. Journal of the American Water Resources Association, 34: 73-89.
Arabi M, Frankenberger J R, Engel B A, et al. 2008. Representation ofagricultural conservation practices with SWAT. Hydrological Processes,22(16): 3042-3055.
Bhuyan S, P K Kalita, K A Janssen. 2002. Soil loss predictions with threeerosion simulation models. Environmental Modelling & Software, 17:135-144.
Bouraoui F, T A Dillaha. 2000. ANSWERS-2000: non-point-source nutrientplanning model. Journal of Environment Engineering, 126(11): 1045-1055.
Busteed P R, D E Storm, M J White, et al. 2009. Using SWAT to Target Critical Source Sediment and Phosphorus Areas in the Wister Lake Basin, USA. American Journal of Environmental Sciences, 5 (2): 156-163.
Drungil C C, M S Srinivasan, et al. 2002. Variable-Source-Area Controls on Phosphorus Transport: Bridging the Gap between Research and Design. Journal of Soil and Water Conservation, 57(6): 534-543.
Gassman P W, M R Reyes, C H Green, et al. 2007. The Soil and Water Assessment Tool: Historical development, applications and futureresearch directions. Transaction of ASABE, 50: 1211-1250.
Gitau M W, T L Veith, W J Gburek. 2004. Farm-level optimization of BMPplacement for cost-effective pollution reduction. Transaction of ASABE,47: 1923-1931.
Hassen M, Y Fekadu, Z Gete. 2004. Validation of agricultural non-pointsource (AGNPS) pollution model in Kori watershed, South Wollo, Ethiopia. International Journal of Applied Earth Observation and Geoinformation, 6: 97-109.
Nash J E, J V Sutcliffe. 1970. Riverflow forecasting through conceptualmodels. Journal of Hydrology, 10(3): 282-290.
Ouyang W, H F Hao, X L Wang. 2008. Regional Nonpoint Source Organic Pollution Modeling and Critical Area Identification for Watershed Best Environmental Management. Water Air Soil Pollution, 187: 251-261.
Pionke H B, W J Gburek, A N Sharpley. 2000. Critical source area controlson water quality in an agricultural watershed located in the Chesapeakebasin. Ecological Engineering, 14: 325-335.
Sivertun A, L E Reinelt, R Castensson. 1998. A GIS method to aid in nonpointsource critical area analysis. International Journal of Geographical Information Science. 2: 365-378.
Srinivasan M S, P Gerard-Marchant, T L Veith, et al. 2005. Watershed scalemodeling of critical source areas of runoff generation and phosphorustransport. Journal of American Water Resources Association, 41: 361-377.
Strauss P, A Leone, M N Ripa, et al. 2007. Using critical source areas fortargeting cost-effective best management practices to mitigate phosphorusand sediment transfer at the watershed scale. Soil Use and Management,23 (Suppl. 1): 144-153.
Tripathi M P, R K Panda, N S Raghuwanshi. 2003. Identification andprioritization of critical sub-watersheds for soil conservation managementusing the SWAT model. Biosystems Engineering, 85: 365-379.
White M J, D E Storm, P R Busteed, et al. 2009. Evaluating Nonpoint Source Critical Source Area Contributions at the Watershed Scale. Journal of Environment Quality, 38(4): 1654-1663.
Williams J R. 1975. Sediment routing for agricultural watersheds. Water Resources Bulletin, 11(5): 965-974.