Integrating ENSO Variability and CMIP6 Projections to Assess Future Rainfall Erosivity in a Tropical Data-Scarce Watershed in Indonesia

Rainfall erosivity is a critical driver of soil erosion, particularly in tropical watersheds experiencing intense precipitation and hydroclimatic variability. However, few studies have examined how long-term climate change and short-term climate oscillations jointly influence erosivity patterns, especially in data-scarce regions. This study integrates El Niño–Southern Oscillation (ENSO) variability and CMIP6-based climate projections to assess the spatio-temporal trends of annual rainfall erosivity in the Podi Watershed, Central Sulawesi, Indonesia. Bias correction was applied to CHIRPS and 15 CMIP6 models using Quantile Mapping and Mean Ratio methods. CNRM-CM6-1 was identified as the best-performing model for future projections under SSP2-4.5 and SSP5-8.5 scenarios. Results indicate that rainfall erosivity during ENSO phases displays asymmetric responses: strong El Niño reduces erosivity in downstream areas, while weak La Niña significantly increases erosivity upstream. Trend analysis shows a significant historical increase (Sen’s slope = 7.42 MJ·mm·ha⁻¹·h⁻¹·yr⁻¹), with future erosivity remaining stable under SSP2-4.5 but increasing under SSP5-8.5 (Sen’s slope = 4.55). Spatially, erosivity hotspots shift between downstream and midstream areas depending on emission scenarios and ENSO phases. These findings underscore the urgent need to incorporate both interannual climate variability and long-term projections in erosion risk assessments, particularly in ecologically fragile tropical watersheds. The study offers new insights for adaptive watershed management in regions with limited observational data.