UC Berkeley

Water availability in mountain forests affects vegetation response to drought, which in turn changes evapotranspiration (ET). We investigated water-balance indicators based on precipitation (P) minus ET to assess Mediterranean-climate forest vulnerability to multi-year droughts. We used the drought-vulnerable dense mixed-conifer forests of California's Sierra Nevada, which includes 78 groves of giant sequoia as study area. With long-term Landsat-based ET data during 1985–2018, water-stress patterns at 30-m resolution during two historical droughts (1987–92 and 2012–15) were analyzed. Canopy moisture loss and tree mortality were used as indices of drought vulnerability. Using cumulative multi-year P–ET as an indicator, groves that were water stressed in 1987–92 were more vulnerable in California's unprecedented 2012–15 drought. Historical-minimum annual P–ET is an indicator of water stress, explaining 32% and 29% of the variances of canopy moisture loss and tree mortality, respectively. As an extreme test to explore potential vegetation response, we trained a deep-learning Long Short-Term Memory (LSTM) model to project ET during hypothetical extended-drought scenarios. The LSTM model reasonably predicted ET with r2 of 0.72 for the testing period. Annual P–ET using LSTM-based ET agreed (r2 = 0.99) with that using ET values from Landsat. Historical water-stress-prone areas were projected to suffer larger ET decreases and to experience more-severe stress during a 12-yr drought scenario. Water stress is more severe in lower-elevation forests, versus mid-to-high areas that have higher precipitation and shorter growing season under current climate. Our study provides water-balance-based indicators to project drought vulnerability and assess effects of disturbance in forests in a warming climate.