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Soil erosion is particularly affected by climate change, especially increases in the amount and intensity of rainfall. The Revised Universal Soil Loss Equation (RUSLE2) developed by USDA-ARS has been developed to quantify soil erosion. However, it does not consider current climate and topographic conditions for estimating those factors, including the rainfall erosivity factor (R-factor) which is particularly significant given more frequent extreme storm events resulting from climate change. This chapter reviews developing a modified RUSLE model using ArcGIS ModelBuilder automation to develop processes for improving USLE factors so that soil erosion quantification can be estimated more precisely in both temporal and spatial dimensions.
- 1 Introduction
- 2 The development of the universal soil loss equation and revised universal soil loss equation models
- 3 Introducing the R-factor (rainfall factor) into universal soil loss equation/revised universal soil loss equation/revised universal soil loss equation 2
- 4 Introducing the K-factor (soil erodibility factor) into universal soil loss equation/revised universal soil loss equation/revised universal soil loss equation 2
- 5 Introducing the L-factor (slope length factor) and the S-factor (slope gradient factor) into universal soil loss equation/revised universal soil loss equation/revised universal soil loss equation 2
- 6 Introducing the C-factor (cropping/cover management factor) and the P-factor (area control practice factor) into universal soil loss equation/ revised universal soil loss equation/revised universal soil loss equation 2
- 7 Case study: using high spatial resolution precipitation data for R-factor estimation
- 8 Conclusion and future trends
- 9 Acknowledgement
- 10 References