Land Cover Change Modulates River Flow Responses to Climate Variability in Central Chile

There are growing concerns regarding the hydrological impacts of native forest loss and exotic plantation expansion; yet these effects remain poorly constrained in regions where climate variability associated with the El Niño–Southern Oscillation (ENSO) may mask underlying land cover change signals. In addition, legacy soil conditions inherited from previous land uses can further modulate hydrological responses. This study examines the combined influence of land cover change, and ENSO variability on river flow dynamics in coastal catchments of central Chile.

Using a 45-year hydroclimatic dataset (1979–2023), we analysed seasonal and annual streamflow trends across four catchments with contrasting land cover trajectories. Significant streamflow declines were detected in four catchments, particularly during summer, when water availability is most critical. Catchments experiencing 4–9% native forest loss exhibited reduced baseflows, whereas catchments with largely preserved native forest cover maintained or even increased summer flows. Interaction analyses indicate that native forest cover enhances precipitation–runoff conversion, while exotic plantations reduce runoff efficiency (precipitation × land cover interactions; R² = 0.46–0.77, negative slopes). ENSO phases alone explained little streamflow variability (R² < 0.04), but significant ENSO-precipitation interactions across all catchments (p < 0.001) highlight an indirect, yet consistent, climatic influence.

To extend these observational findings and explore underlying hydrological processes, a physically-based hydrological model (SWAT) was implemented for the study catchments. Model calibration and validation show satisfactory performance, providing a robust basis for scenario-based simulations. Ongoing modelling explores the relative and combined impacts of land cover change and climate variability on streamflow under current conditions. The integration of long-term observations with process-based modelling offers new insights into how vegetation change modulates hydrological resilience to climate variability, with important implications for water security and ecosystem management in this type of regions.