Resource managers need spatially explicit models of hydrologic response to changes in key climatic drivers across variable landscape conditions. We demonstrate the utility of a Basin Characterization Model for California (CA-BCM) to integrate high-resolution data on physical watershed characteristics with historical or projected climate data to predict watershed-specific hydrologic responses.

Process‐based models that link climate and hydrology permit improved assessments of climate change impacts among watersheds. We used the Basin Characterization Model (BCM), a regional water balance model to (1) ask what is the magnitude of historical and projected future change in the hydrology of California's watersheds; (2) test the spatial congruence of watersheds with the most historical and future hydrologic change; and (3) identify watersheds with high levels of hydrologic change under drier and wetter future climates. We assessed change for 5135 watersheds over a 60‐year historical period and compared it to 90‐year future projections. Watershed change was analyzed for climatic water deficit, April 1st snowpack, recharge, and runoff. Watersheds were ranked by change for the historical and two future scenarios. We developed a normalized index of hydrologic change that combined the four variables, and identified which watersheds show the most spatial congruence of large historical change and continued change under the two futures. Of the top 20% of all watersheds (1028), 591 in the Sierra Nevada Mountains and Northwestern ecoregions have high spatial congruence across all time periods. Among watersheds where change accelerates in the future, but not historically, a majority are congruent between both climate models, predominantly in the Sierra Nevada, Cascade Ranges and the Northwestern ecoregions. This congruence of impacts in watersheds under drier or wetter scenarios is driven by snowpack, but in areas with low snowpack, hydrologic change varied spatially depending on projected precipitation and temperature, with 151 watersheds in Northwestern California showing high levels of drying under the drier scenario, while 103 watersheds in Central western and Southwestern California show increasing hydrologic activity under the wetter scenario. In some regions, the loss of snowpack allows the cycle of runoff and recharge to function without delay represented by springtime snow melt, causing these watersheds to become more immediately hydrologically responsive to changing climate. The study also found watersheds with low rainfall that have already passed through their highest response to changing climate, and show less future change. The methods used here can also be used to identify watersheds resilient to changing climate.

The impacts of different emission levels and climate change conditions to landscape‐scale natural vegetation could have large repercussions for ecosystem services and environmental health. We forecast the risk‐reduction benefits to natural landscapes of lowering business‐as‐usual greenhouse gas emissions by comparing the extent and spatial patterns of climate exposure to dominant vegetation under current emissions trajectories (Representative Concentration Pathway, RCP8.5) and envisioned Paris Accord target emissions (RCP4.5). This comparison allows us to assess the ecosystem value of reaching targets to keep global temperature warming under 2°C. Using 350,719 km² of natural lands in California, USA, and the mapped extents of 30 vegetation types, we identify each type's current bioclimatic envelope by the frequency with which it occupies current climate conditions. We then map the trajectory of each pixel's climate under the four climate futures to quantify areas expected to fall within, become marginal to (outside a 95% probability contour), or move beyond their current climate conditions by the end of the 21st century. In California, these four future climates represent temperature increases of 1.9–4.5°C and a −24.8 to +22.9% change in annual precipitation by 2100. From 158,481 to 196,493 km² (45–56%) of California's natural vegetation is predicted to become highly climatically stressed under current emission levels (RCP8.5) under the drier and wetter global climate models, respectively. Vegetation in three California ecoregions critical to human welfare, southwestern CA, the Great Valley, and the Sierra Nevada Mountains, becomes >50% impacted, including 68% of the lands around Los Angeles and San Diego. However, reducing emissions to RCP4.5 levels reduces statewide climate exposure risk by 86,382–99,726 km². These projections are conservative baseline estimates because they do not account for amplified drought‐related mortality, fires, and beetle outbreaks that have been observed during the current five‐year drought. However, these results point to the landscape benefits of emission reductions.

From 2011 to 2016, California experienced a millennial‐intensity drought, generating high levels of tree mortality. Remote sensing has been used to monitor the long‐term impacts of drought; however, discriminating dead from live trees in arid and semiarid deciduous woodlands is challenging. The goals of this study were to assess and map the spatial patterns of drought‐induced tree mortality in a blue oak (Quercus douglasii) woodland, a highly drought‐tolerant species forming savannas along the lower foothills surrounding California's Central Valley. Airborne hyperspectral imagery was used to identify the most important wavelength regions predicting drought‐induced blue oak mortality. The best metric to predict canopy stress was a normalized ratio using the spectral bands 937.53 and 1100.08 nm with a correlation with tree mortality of R² = 0.83. The image prediction of mortality for nine field plots found that 16 of 98 trees died (17.9%) during the drought. We further evaluated tree mortality in 82 independent plots, and we found the greatest image predictive accuracy for tree mortality between 1% and 10%. When applied at the landscape level, the regression‐based index found mortality ranged from 1% to more than 51% in oak stands with an average mortality of 10% over the entire study region. In addition, tree mortality at landscape level showed higher tree mortality in blue oaks on south‐facing aspects probably because of higher insolation rates and in sites with low potential for accumulated drainage.