Runoff and erosion maps in Saen Thong sub-district (Tha Wang Pha district, Nan province, Thailand)

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This dataset contains three runoff and erosion vector maps classified by value ranges: i) a map of runoff coefficient (Krc %) predicted from local surface conditions and runoff data from 535 1- m² plots in Southeast Asia; (ii) a map of mean soil loss (kgm-2) predicted from the same database; and (iii) a map of gully index, which is based on catchment area, runoff coefficient and LS, a topographic factor. These runoff and erosion maps were produced as part of the ANR FutureHealthSEA project: predictive scenarios of health in Southeast Asia, linking land use and climate change to infectious diseases.

In November 2019 and June 2022, we assessed soil surface conditions across 100 individual 1-square meter plots, using a robust methodology (Casenave and Valentin, 1992), tailored to Southeast Asia (Patin et al., 2018; Song et al., 2020). We ensured representation of each land use category with a minimum of four plots, at various topographic positions. Our objective was to determine runoff and soil loss based on these surface conditions, using a database of 535 1-square meter plots representing a variety of land uses in Southeast Asia (Boithias 2021; available at mtropics.obs-mip.fr/catalogue-m-tropics/).

We conducted multiple linear regressions for the ten land use categories identified in the field to establish statistically significant relationships between the observed surface conditions and annual runoff as well as soil loss (e.g., Lacombe et al., 2018). Subsequently, we used Copernicus satellite imagery to identify land use patterns (Mahuzier et al. 2022) within the 287 catchments of the Saen Thong region and generated maps of runoff production (Krc %) and inter-rill erosion (Mean soil loss kg m-2) as predicted by these models.

To address gully erosion on steep slopes (Valentin et al., 2005), we introduced a gully erosion index (Gi = A krc LS), where "A" represented the catchment area in hectares, "krc" accounted for the sum of runoff contributions attributed to different land use categories weighted by their respective surface areas within each catchment, and "LS" incorporated the topographic factor derived from mean slope steepness and length. We sourced values for "A" and "LS" from satellite imagery and digital elevation models (DEMs), generating the map of this gully erosion index (Gully index).