You are in: All categories > Chapters > Crops > Regenerative techniques > Soil health

Advances in modeling soil erosion risk

Code: 9781835452257
Publication date: 21/08/2024
Extent: 24 pages

Contributions by: Sudhanshu S Panda, University of North Georgia, USA; Debasmita Misra, University of Alaska Fairbanks, USA; Devendra M Amatya and Johnny M Grace III, USDA Forest Service, USA; and Anita Thompson, University of Wisconsin-Madison, USA

Chapter synopsis:

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.



DOI: 10.19103/AS.2023.0131.09
£25.00
Buy ePub   
Table of contents
  • 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

Related products

Also in Soil health