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Spatiotemporal dynamics of soil erosion risk for Anji County, China
- Source :
- Stochastic Environmental Research and Risk Assessment. 26:751-763
- Publication Year :
- 2012
- Publisher :
- Springer Science and Business Media LLC, 2012.
-
Abstract
- Soil erosion, as a serious environmental problem worldwide, poses a great threat to human sustainability. Spatiotemporal information on soil erosion is of vital importance to finding a solution for this problem. A case study was conducted to characterize the dynamics of soil erosion risk in 1985, 1994, 2003 and 2008 for Anji County, China, a region with seemingly high ecological quality. Remote sensing and geographic information systems were integrated to parameterize soil erosion-controlling factors. By using the Revised Universal Soil Loss Equation, we estimated annual soil loss, and generated categorical maps of soil erosion risk in the County for the 4 years. Results showed that, while appearing to improve in some areas, soil erosion risk increased and eroded area expanded from 1985 to 2008. Spatial analysis revealed that the most vulnerable hotspots were erosion-free forests, where newly eroded areas were most likely to occur. These results implied that, similar to findings in many parts of the world, soil erosion is an important issue in the study area, which could be closely associated with local eutrophication and algal blooms. Our research indicated that there should be more focus on this issue. From a methodological point of view, we believe that the approach used to estimate soil loss in the study area has the potential to be applied in other similar regions.
- Subjects :
- Soil map
Environmental Engineering
Geographic information system
business.industry
Universal Soil Loss Equation
Soil functions
Erosion
Environmental Chemistry
Environmental science
Spatial variability
Safety, Risk, Reliability and Quality
business
Water resource management
Risk assessment
Eutrophication
General Environmental Science
Water Science and Technology
Subjects
Details
- ISSN :
- 14363259 and 14363240
- Volume :
- 26
- Database :
- OpenAIRE
- Journal :
- Stochastic Environmental Research and Risk Assessment
- Accession number :
- edsair.doi...........b6870b88bc32dffc9929cc49612e19eb
- Full Text :
- https://doi.org/10.1007/s00477-012-0590-0