Abstract

Groundwater systems in snow-dominated drainage areas supply cool baseflows that support instream and downstream users late into the dry season. Yet, these catchments are becoming rarer with climate change and anthropogenic pressures that threaten groundwater systems. Restoration of low-gradient meadows and streams can recover a catchment’s natural storage potential, especially in Mediterranean biomes such as the Sierra Nevada of California where summer groundwater recharge is scarce. The degradation of meadows due to intense human modification has decreased groundwater elevations and shifted wet meadow plant communities toward more xeric forest and shrub communities. We applied machine learning tools to find potential “lost meadows” that may no longer support high groundwater elevations or meadow vegetation but do exhibit basic geomorphic and climatic characteristics similar to existing meadows. The model reveals potential meadow habitat in the Sierra Nevada of nearly three times its current extent. We offer two conceptual applications of the model for incorporating meadows in watershed restoration planning. The first application focuses on strategically expanding wet meadows already associated with fuel breaks for increasing wildfire resistance. The second shows how meadow restoration in post-wildfire landscapes could increase capture of sediment from burned hillslopes where increased sediment storage would benefit water storage. Meadows are important habitats that have become degraded due to long-term overuse. Re-envisioning their potential extent shows that, with restoration, meadows could also serve as components of California’s multi-tiered efforts to manage pressing threats to its forests and water supply.

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