Assessing soil erosion risk at national scale in developing countries: The technical challenges, a proposed methodology, and a case history

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Cayllahua-Cahuina E.
Chávez J.
Mora R.
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Elsevier B.V.
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Through an extensive bibliographic review, this contribution underlines the urgency and challenges to quantify soil erosion rates (ERs) in developing countries. It subsequently elaborates on the combined application of GIS-based RUSLE, generalized likelihood uncertainty estimation (GLUE) principles and sediment delivery ratio functions (SDR) to quantify ERs at country scale for these countries, as they commonly have limited measurements to that purpose. The methodology, termed RUSLE-GGS (RUSLE-GIS-GLUE-SDR) herein, comprises the following sequence: (1) construction of ER samples using RUSLE-GIS based on freely available local/global geoenvironmental observations and field relations, (2) construction of area-specific sediment yield samples utilizing SDR transfer functions, and (3) assessment of the most behavioral samples by means of bias analysis and cross validation. Its application to Peru allows obtaining 5-km resolution ER and potential erosion maps for the years 1990, 2000, and 2010. RUSLE-GGS is highly replicable and could potentially be used as an initial standard and systematic method to estimate ERs in developing countries through the active participation of local scientists. Thus, it potentially can contribute to improve the capacity building in such countries and set an initial frame to compare the evolution of soil erosion in their territories towards attaining Goal 15 of the UN 2030 Agenda for Sustainable Development.
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Uncertainty, Developing countries, Land use change, RUSLE, Soil erosion