Dynamic rainfall erosivity estimates derived from IMERG data

Emberson, Robert A.

doi:https://doi.org/10.5194/hess-27-3547-2023

Articles | Volume 27, issue 19

https://doi.org/10.5194/hess-27-3547-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-27-3547-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 27, issue 19

Research article

|

09 Oct 2023

Research article |

| 09 Oct 2023

Dynamic rainfall erosivity estimates derived from IMERG data

Robert A. Emberson

Supplement

https://doi.org/10.5194/hess-27-3547-2023-supplement

Data sets

Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000 (http://www.earthstat.org/cropland-pasture-area-2000/) N. Ramankutty, A. T. Evan, C. Monfreda, and J. A. Foley https://doi.org/10.1029/2007GB002952

Short summary

Soil can be eroded by rainfall, and this is a major threat to agricultural sustainability. Estimating the erosivity of rainfall is essential as a first step to determine how much soil might be lost. Until recently, satellite data have not been used to estimate rainfall erosivity, but the data quality is now sufficient to do so. In this study, I test several methods to calculate rainfall erosivity using satellite rainfall data and contrast this with ground-based estimates.