Alignment of tree phenology and climate seasonality influences the runoff response to forest cover loss

Abstract

Trees shape the critical zone and modulate terrestrial water storage yet observed streamflow responses to forest cover change vary. Differences in catchment area, soil water storage, management practices, tree species, and climate are among the many explanations proposed for heterogeneous hydrologic responses. We addressed evidence for the hypothesis that mean annual temperature (MAT) and the phase shift between precipitation and enhanced vegetation index (EVI) peaks, θ , explain a significant amount of the variation in hydrologic response to forest cover loss. We selected 50 catchments with daily streamflow records spanning eight nations and seven climate regions. Categorical clustering of catchments was performed with MAT, θ, minimum EVI, catchment area, and percentage forest loss. Similar storm event runoff ratio responses to deforestation were best clustered by MAT and θ . High MAT tropical monsoonal catchments (Brazil, Myanmar, and Liberia) exhibited minimal evidence of increasing runoff ratios (increases observed in 9% of catchments). Low MAT subarctic, cold semi-arid, and humid continental catchments (US, Canada, and Estonia) showed consistent runoff increases around the time of snowmelt (94%). The deforestation runoff responses of temperate and subtropical catchments with Mediterranean, humid, and oceanic climates depended strongly on θ . We observe increased runoff following forest loss in a majority of catchments (90%) where precipitation peaks followed peak growing season (max EVI) (US). In contrast, where precipitation peaks preceded the growing season (South Africa and Australia) there was less evidence of increased runoff (25% of catchments). This research supports the strategic implementation of native forest conservation or restoration for simultaneously mitigating the effects of global climate change and regional or local surface runoff.

Keywords

• deforestation
• runoff
• enhanced vegetation index (EVI)
• hierarchical clustering
• forests