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.

Evaluating the environmental impacts of climate change on water resources and biological components of the landscape is an integral part of hydrologic and ecological investigations, and the resultant land and resource management in the twenty-first century. Impacts of both climate and simulated hydrologic parameters on ecological processes are relevant at scales that reflect the heterogeneity and complexity of landscapes. At present, simulations of climate change available from global climate models [GCMs] require downscaling for hydrologic or ecological applications. Using statistically downscaled future climate projections developed using constructed analogues, a methodology was developed to further downscale the projections spatially using a gradient-inverse-distance-squared approach for application to hydrologic modeling at 270-m spatial resolution. This paper illustrates a methodology to downscale and bias-correct national GCMs to subkilometer scales that are applicable to fine-scale environmental processes. Four scenarios were chosen to bracket the range of future emissions put forth by the Intergovernmental Panel on Climate Change. Fine-scale applications of downscaled datasets of ecological and hydrologic correlations to variation in climate are illustrated. The methodology, which includes a sequence of rigorous analyses and calculations, is intended to reduce the addition of uncertainty to the climate data as a result of the downscaling while providing the fine-scale climate information necessary for ecological analyses. It results in new but consistent data sets for the US at 4 km, the southwest US at 270 m, and California at 90 m and illustrates the utility of fine-scale downscaling to analyses of ecological processes influenced by topographic complexity.

This report documents the computer software package, Basin Characterization Model, version 8 (BCMv8)—a monthly, gridded, regional water-balance model—and provides detailed operational instructions and example applications. After several years of many applications and uses of a previous version, CA-BCM, published in 2014, the BCMv8 was refined to improve the accuracy of the water-balance components, particularly the recharge estimate, which is the most difficult to accurately assess. The improvement of the various water-balance components targeted the actual evapotranspiration component, which, in turn, reduced the uncertainty of the recharge estimate. The improvement of this component was enabled by the availability of a national, gridded actual-evapotranspiration product from the U.S. Geological Survey that was unique in its scope to combine remotely sensed spatial variability and ground-based long-term water-balance constraints. This dataset provided the ability to assess monthly actual evapotranspiration for 62 vegetation types and to perform regional calibration in watersheds throughout California with the objective of closing the water balance using improved estimates for each component. The refinements, including vegetation-specific evapotranspiration, enabled the development of applications that could explore various aspects of landscape disturbance, such as wildfire, forest management, or urbanization. The improvements to BCMv8 also provided the ability to assess long-term sustainability of water resources under a variety of management applications or future climate projections.

California’s recent drought (2012–2016) has implications throughout the state for natural resource management and adaptation planning and has generated many discussions about drought characterization and recovery. This study characterizes drought conditions with two indices describing deficits in natural water supply and increases in landscape stress developed on the basis of water balance modeling, at a fine spatial scale to assess the variation in conditions across the entire state, and provides an in-depth evaluation for the Russian River basin in northern California to address local resource management by developing extreme drought scenarios for consideration in planning and adaptation. We employed the USGS Basin Characterization Model to characterize drought on the basis of water supply (a measure of recharge plus runoff) and landscape stress (climatic water deficit). These were applied to the state and to the Russian River basin where antecedent soil moisture conditions were evaluated and extreme drought scenarios were developed and run through a water management and reservoir operations model to further explore impacts on water management. Drought indices indicated that as of the end of water year 2016 when reservoirs were full, additional water supply and landscape replenishment of up to three average years of precipitation in some locations was needed to return to normal conditions. Antecedent soil conditions in the Russian River were determined to contribute to very different water supply results for different years and were necessary to understand to anticipate proper watershed response to climate. Extreme drought scenarios manifested very different kinds of drought and recovery and characterization helps to guide the management response to drought. These scenarios and indices illustrate how droughts differ with regard to water supply and landscape stress and how long warm droughts recover much more slowly than short very dry droughts due to the depletion of water in the soil and unsaturated zone that require filling before runoff can occur. Recognition of ongoing conditions and likelihood of recovery provides tools and information for a range of resource managers to cope with drought conditions.

From a conservation perspective, quantifying potential refugial capacity has been predominantly focused on climate refugia, which is critical for maintaining the persistence of species and ecosystems. However, protection from other stressors, such as human‐induced changes in fire and hydrology, that cause habitat loss, degradation, and fragmentation is also necessary to ensure that conservation efforts focused on climate are not undermined by other threats. Thus, conceptual and methodological advances for quantifying potential refugia from multiple anthropogenic stressors are important to support conservation efforts. We devised a new conceptual approach, the domains of refugia, for assessing refugial capacity that identifies areas where exposure to multiple stressors is low. In our framework, patterns of environmental variability (e.g., increased frequency of warm summers), thresholds of resilience, and extent and intensity of stressors are used to identify areas of potential refugia from a suite of ongoing anthropogenic stressors (e.g., changes in fire regime). To demonstrate its utility, we applied the framework to a Southern California landscape. Sites with high refugial capacity (super‐refugia sites) had on average 30% fewer extremely warm summers, 20% fewer fire events, 10% less exposure to altered river channels and riparian areas, and 50% fewer recreational trails than the surrounding landscape. Our results suggest that super‐refugia sites (∼8200 km ² ) for some natural communities are underrepresented in the existing protected area network, a finding that can inform efforts to expand protected areas. Our case study highlights how considering exposure to multiple stressors can inform planning and practice to conserve biodiversity in a changing world.

A daily watershed model of the Sacramento River Basin of northern California was developed to simulate streamflow and suspended sediment transport to the San Francisco Bay-Delta. To compensate for sparse data, a unique combination of model inputs was developed, including meteorological variables, potential evapotranspiration, and parameters defining hydraulic geometry. A slight decreasing trend of sediment loads and concentrations was statistically significant in the lowest 50% of flows, supporting the observed historical sediment decline. Historical changes in climate, including seasonality and decline of snowpack, contribute to changes in streamflow, and are a significant component describing the mechanisms responsible for the decline in sediment. Several wet and dry hypothetical climate change scenarios with temperature changes of 1.5 °C and 4.5 °C were applied to the base historical conditions to assess the model sensitivity of streamflow and sediment to changes in climate. Of the scenarios evaluated, sediment discharge for the Sacramento River Basin increased the most with increased storm magnitude and frequency and decreased the most with increases in air temperature, regardless of changes in precipitation. The model will be used to develop projections of potential hydrologic and sediment trends to the Bay-Delta in response to potential future climate scenarios, which will help assess the hydrological and ecological health of the Bay-Delta into the next century.