Erosion extremes under changing climate: Integrating extreme rainfall erosivity in a tropical mining landscape
Abstract
ABSTRACT Climate change is intensifying extreme rainfall globally, yet its role in controlling erosion dynamics in highly disturbed tropical mining landscapes remains poorly understood, as most studies rely on total precipitation rather than rainfall extremes. This study developed an extreme-driven erosion framework by integrating bias-corrected climate projections (Quantile Mapping), the P95 rainfall index, and RUSLE–SDR modelling across seven tropical nickel mining catchments on Obi Island, North Maluku, Indonesia, under future climate scenarios up to 2100. The results revealed that upper-tail rainfall intensification systematically amplified rainfall erosivity, with R-factor values exceeding 2,900 MJ·mm·ha⁻¹·yr⁻¹, leading to non-linear increases in erosion rates (up to >12,000 tonnes/year) and spatial redistribution of sediment hotspots. Importantly, erosion responses were governed primarily by extreme rainfall behavior, rather than total annual precipitation, challenging conventional rainfall-based erosion assumptions. Furthermore, climate-driven shifts in seasonal rainfall structure induced temporal reorganization of peak erosion, advancing from mid-year to early wet-season periods, thereby altering hydrological connectivity and sediment transport efficiency. These findings demonstrate that extreme rainfall acts as the dominant control on erosion and sediment dynamics in tropical mining systems, providing new process-based insights into future land degradation under climate change. The proposed framework offers a robust scientific basis for climate-adaptive, water-sensitive mining management and is transferable to other erosion-prone landscapes experiencing intensifying hydroclimatic extremes.
Fields of Study & Subjects
Soil erosion and sediment transport
Mining and Resource Management
Karst Systems and Hydrogeology
Publication details
- Journal / source
- Environmental Challenges
- Publisher
- Elsevier BV
- Volume
- 24
- Pages
- 101574–101574
- Publication date
- 8 July 2026
- Language
- EN