Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Rainfall Erosivity in Peru: A New Gridded Dataset Based on GPM-IMERG and Comprehensive Assessment (2000–2020)

Leonardo Gutierrez
* ORCID logo ,
Adrian Huerta
* ORCID logo ,
Evelin Sabino
ORCID logo ,
Luc Bourrel
,
Frederic Frappart
ORCID logo ,
Waldo Lavado-Casimiro
* ORCID logo
Version 1 : Received: 4 August 2023 / Approved: 7 August 2023 / Online: 8 August 2023 (10:56:40 CEST)

A peer-reviewed article of this Preprint also exists.

Gutierrez, L.; Huerta, A.; Sabino, E.; Bourrel, L.; Frappart, F.; Lavado-Casimiro, W. Rainfall Erosivity in Peru: A New Gridded Dataset Based on GPM-IMERG and Comprehensive Assessment (2000–2020). Remote Sens. 2023, 15, 5432. Gutierrez, L.; Huerta, A.; Sabino, E.; Bourrel, L.; Frappart, F.; Lavado-Casimiro, W. Rainfall Erosivity in Peru: A New Gridded Dataset Based on GPM-IMERG and Comprehensive Assessment (2000–2020). Remote Sens. 2023, 15, 5432.

Abstract

In soil erosion estimation models, the variable with the greatest impact is rainfall erosivity (RE), which is the measurement of precipitation energy and its potential capacity to cause erosion, and erosivity density (ED), which relates RE to precipitation. The RE requires high temporal resolution records for its estimation. However, due to the limited observed information and the increasing availability of rainfall estimates based on remote sensing, recent research has shown the usefulness of using observed-corrected satellite data for RE estimation. This study evaluates the performance of a new gridded dataset of RE and ED in Peru (PISCO_reed) by merging data from the IMERG v06 product, through a new calibration approach with hourly records of automatic weather stations, during the period of 2000-2020. By using this method, a correlation of 0.7 was found between the PISCO\_reed and RE obtained by the observed data. An average annual RE for Peru of 4831 MJ·mm·ha-1·h-1 was estimated with a general increase towards the lowland Amazon regions and high values are found on the north-coast Pacific area of Peru. The spatial identification of the most risk areas of erosion, was carried out through a relationship between the ED and rainfall. Both erosivity data sets will allow us to expand our fundamental understanding and quantify soil erosion with greater precision.

Keywords

Rainfall erosivity; satellite precipitation product; IMERG; Hourly observed rainfall; Peru; Andes

Subject

Environmental and Earth Sciences, Remote Sensing

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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