Understanding the effects of climate change is a substantial challenge in estuarine systems because the mixing of freshwater and ocean water adds complexity to climate change projections. Such climate change projections have been conducted in the San Francisco Estuary as part of the U.S. Geological Survey’s CASCaDE Project. In this project, we assessed downscaled air temperature data from 10 Global Climate Change models under 2 Representative Concentration Pathway (RCP) trajectories for greenhouse gas concentrations for three regions of the upper San Francisco Estuary: Suisun and Grizzly Bays, Suisun Marsh, and the legal Delta. We also utilized previously derived regression models to estimate future water temperatures at 16 locations within the upper estuary based on the projected air temperature data.

This data release includes data containing projections of unimpaired hydrology, reservoir storage, and downstream managed flows in the Sacramento River/San Joaquin River watershed, California for scenarios of future climate change generated for the CASCaDE2 project (Computational Assessments of Scenarios of Change for the Delta Ecosystem, phase 2). Code used to produce the data is also included. The dataset is produced using a multiple-model approach. First, downscaled global climate model outputs are used to drive an existing Variable Infiltration Capacity/Variable Infiltration Capacity Routing (VIC/RVIC) model of Sacramento/San Joaquin hydrology, resulting in projections of daily, unimpaired flows throughout the watershed. A management model, CASCaDE2-modified CalSim (C2-CalSim), uses these projections as inputs and produces monthly estimates of reservoir and other infrastructure operations and resulting downstream managed flows. The CASCaDE2 resampling algorithm (CRESPI), also uses the projected daily unimpaired flows, along with historical managed flows, to estimate the daily variability in managed flows throughout the watershed. The monthly and daily managed-flow estimates are combined in a way that preserves the multi-decadal variability and century-scale trends produced by the C2-CalSim model and the day-to-day variability produced by the CRESPI algorithm. The resulting data are analyzed and processed to produce tables, figures, and text for the associated publications. To reduce the data release's size, data from a given step in the analysis that are not used in a subsequent step have not been included in this data release. All code generated by the USGS to produce the data in this data release is also included. This includes all code to download and preprocess external data; to set up and control the RVIC model runs; to modify, set up, and control runs of the CalSim 2 model; to implement and run the CRESPI algorithm; to postprocess and analyze model outputs; and to produce published figures, tables and text that includes calculated values. A detailed README file is included with instructions for running the code, including how to obtain the external RVIC and CalSim 2 models.

This data release contains monthly 270-meter gridded Basin Characterization Model (BCMv8) climate inputs and hydrologic outputs for San Francisco Coastal South (SFCS). Gridded climate inputs include: precipitation (ppt), minimum temperature (tmn), maximum temperature (tmx), and potential evapotranspiration (pet). Gridded hydrologic variables include: actual evapotranspiration (aet), climatic water deficit (cwd), snowpack (pck), recharge (rch), runoff (run), and soil storage (str). The units for temperature variables are degrees Celsius, and all other variables are in millimeters. Monthly historical variables from water years 1896 to 2019 are summarized into water year files and long-term average summaries for water years 1981-2010. Four future climate scenarios were spatially downscaled from 6 kilometers to 270 meters, and run through the BCMv8 using the same model parameters. The future climate scenarios are all Representative Concentration Pathway (RCP) 8.5 and include: CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 from California's Forth Climate Change Assessment. Future climate scenarios span from water year 2007 to 2099, and monthly variables were summarized by water year and the average 2070 to 2099 period. Streamflow for each calibration basin was calculated using a post processing Excel spreadsheet and BCMv8 recharge and runoff, and are provided in tabular comma separated *.csv files. Raster grids are in the NAD83 California Teale Albers, (meters) projection in an open format ascii text file (*.asc).

This data release contains monthly 270-meter gridded Basin Characterization Model (BCMv8) climate inputs and hydrologic outputs for San Diego (SD). Gridded climate inputs include: precipitation (ppt), minimum temperature (tmn), maximum temperature (tmx), and potential evapotranspiration (pet). Gridded hydrologic variables include: actual evapotranspiration (aet), climatic water deficit (cwd), snowpack (pck), recharge (rch), runoff (run), and soil storage (str). The units for temperature variables are degrees Celsius, and all other variables are in millimeters. Monthly historical variables from water years 1896 to 2019 are summarized into water year files and long-term average summaries for water years 1981-2010. Four future climate scenarios were spatially downscaled from 6 kilometers to 270 meters, and run through the BCMv8 using the same model parameters. The future climate scenarios are all Representative Concentration Pathway (RCP) 8.5 and include: CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 from California's Forth Climate Change Assessment. Future climate scenarios span from water year 2007 to 2099, and monthly variables were summarized by water year and the average 2070 to 2099 period. Streamflow for each calibration basin was calculated using a post processing Excel spreadsheet and BCMv8 recharge and runoff, and are provided in tabular comma separated *.csv files. Raster grids are in the NAD83 California Teale Albers, (meters) projection in an open format ascii text file (*.asc).

Climate change and climate variability impacts such as rising sea levels have the potential to exacerbate seawater intrusion and the strain on coastal freshwater resources in already stressed groundwater basins such as those in the Pajaro Valley groundwater basin, California. The U.S. Geological Survey (USGS) developed the Pajaro Valley Hydrologic model (PVHM) to quantitatively assess aquifer-system responses to climatic variation, surface-water deliveries, and seawater intrusion.The PVHM historical model (1963-2018) was updated, extended, and re-calibrated using a combination of manual adjustments to parameters and an assisted parameter estimation PEST++ software (White et al., 2020) to minimize differences between simulated values and historical observations of streamflow, groundwater levels, and agricultural pumping. Three future climate scenarios (2013-2100) were developed for the PVHM, using three climate projections from global general circulation models (GCMs) representing hot and dry conditions, average conditions, and cool and wet conditions. The climate ensemble was used to conduct a first-order second moment uncertainty analysis of groundwater level and seawater intrusion forecasts using PEST++ software (White et al., 2020). Understanding the reliability and uncertainty of forecasts is important for developing climate adaptation strategies such as developing protective thresholds, particularly at the basin scale where the impacts are felt, and adaptation is implemented. This USGS data release contains all of the input and output files for the historical updated PVHM and the three future climate scenarios described in the associated journal article.

LUCAS-W is a scenario-based simulation model of coupled land use change and associated water demand for California's Central Coast region from 2001-2061. The model is a verison of the LUCAS model, which uses the SyncroSim software framework (Software documentation available at http://doc.syncrosim.com/index.php?title=Reference_Guide), that contains a new coupling with statistical software R (https://www.r-project.org/) to enable dynamic feedbacks between land-use change, resulting water demand, and water availability. The model was parameterized with land-use change and water use empirically estimated from county-scale historic data, as well as results from dozens of local agencies’ groundwater modeling efforts. It was used to assess a set of five stakeholder-driven scenarios that explored alternative development pathways assuming the continuation of historic land use change rates but with different intensities of water supply and land-use management. Water management strategies were (1) water demand limits, and (2) water supply enhancement, while land use management strategies were (3) urban sprawl limits on recharge areas and prime farmland, and (4) preservation of priority habitat areas. By scaling up studies of local-scale diverse, heterogeneous aquifers and management approaches to a regional level, the model can enable a projection of spatial changes due to shifts in LULC and water management including leakage from land and water use regulated areas into unregulated areas, information that is key to future agency planning for sustainability. The resulting land-use projections provide a range of development projections under different sets of management assumptions: patterns of development that do not stabilize “business-as-usual” (WL), assume that water demand stabilizes at a range of possible sustainable water supply levels (MM, WH), and that assume a relatively unregulated (LL) or tightly compact (LH) pattern of future development. See Van Schmidt et al. (2022) Journal of Hydrology: Regional Studies (https://doi.org/10.1016/j.ejrh.2022.101056) for more details.

This data release contains monthly 270-meter gridded Basin Characterization Model (BCMv8) climate inputs and hydrologic outputs for South Bay (SBay). Gridded climate inputs include: precipitation (ppt), minimum temperature (tmn), maximum temperature (tmx), and potential evapotranspiration (pet). Gridded hydrologic variables include: actual evapotranspiration (aet), climatic water deficit (cwd), snowpack (pck), recharge (rch), runoff (run), and soil storage (str). The units for temperature variables are degrees Celsius, and all other variables are in millimeters. Monthly historical variables from water years 1896 to 2019 are summarized into water year files and long-term average summaries for water years 1981-2010. Four future climate scenarios were spatially downscaled from 6 kilometers to 270 meters, and run through the BCMv8 using the same model parameters. The future climate scenarios are all Representative Concentration Pathway (RCP) 8.5 and include: CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 from California's Forth Climate Change Assessment. Future climate scenarios span from water year 2007 to 2099, and monthly variables were summarized by water year and the average 2070 to 2099 period. Streamflow for each calibration basin was calculated using a post processing Excel spreadsheet and BCMv8 recharge and runoff, and are provided in tabular comma separated *.csv files. Raster grids are in the NAD83 California Teale Albers, (meters) projection in an open format ascii text file (*.asc).

This data release provides the resulting land-use projections for California's Central Coast from 2001-2061 at a resolution of 270-m. Data are provided as (1) annual rasters and (2) summarized as the mean annual transition probability across 10 Monte Carlo iterations. Each package contains folders for five scenarios, which have different sets of management assumptions along two axes: Water management Low/Moderate/High and Land use management Low/Moderate/High. - MM (Moderate/Moderate): a scenario where water demand caps reduce development in overdrafted groundwater basins based on current total water supplies, and where prime farmland and groundwater recharge areas will be protected from urban sprawl (i.e., land use projections assuming development stabilizes at a level sustainable with current water supplies, and urban sprawl limits). The other four scenarios differ from the MM scenario by altering one of these management strategies, while keeping the second strategy at the "Moderate" level. - WL (Water management Low): a scenario with no feedbacks between water supplies and development (i.e., land use projections assuming development is not constrained by water availability, closest to a "business-as-usual" continuation of the region's historic trajectory). - WH (Water management High): a scenario that assumes that water demand caps, but with increased caps due to enhanced water supplies proposed under local groundwater agencies' Groundwater Sustainability Plans (i.e., land use projections assuming development stabilizes at a higher water demand). - LL (Land use management Low): a scenario where prime farmland and groundwater recharge areas are not protected from urban sprawl (i.e., land use projections assuming relatively unregulated land use planning, with water sustainability based on current supplies). - LH (Land use management High): a scenario where almost all the state's priority habitats are preserved from urbanization or agricultural expansion (i.e., land use projections assuming a very compact pattern of development, with water sustainability based on current supplies). These projections were created with LUCAS-W, a scenario-based simulation model of coupled land use change and associated water demand. This model is a version of the LUCAS model, which uses the SyncroSim software framework (Software documentation available at http://doc.syncrosim.com/index.php?title=Reference_Guide), that contains a new coupling with statistical software R (https://www.r-project.org/) to enable dynamic feedbacks between land-use change, resulting water demand, and water availability. The model was parameterized with land-use change and water use empirically estimated from county-scale historic data, as well as results from dozens of local agencies’ groundwater modeling efforts. By scaling up studies of local-scale diverse, heterogeneous aquifers and management approaches to a regional level, the model can enable a projection of spatial changes due to shifts in LULC and water management including leakage from land and water use regulated areas into unregulated areas, information that is key to future agency planning for sustainability. See Van Schmidt et al. (2021) Water Resources Research (doi: XXXXXXXXXXXXX) for more details.

This dataset contains rasters of vegetation refugia and habitat exposure variables for the state of California. Two potential future climate scenarios were used: warmer and wetter (CNRM-CM5), and hotter and drier (MIROC-ESM) & 2 emission scenarios: a higher level one that represents our current trajectory (RCP 8.5) and a lower level one that represents a more optimistic scenario (RCP 4.5). The vegetation exposure models used aims to help in assessing potential climatic stress to vegetation communities and this dataset contains the statewide data for use in assessing the potential risk to each of the California Allotments. Current and future vegetation stress was determined by integrating the hydroclimate data with a detailed 2015 map of the spatial patterns of California’s vegetation community types, and examining how climate conditions will change at those locations using 9 hydroclimatic variables (30-year averages) from the Basin Characterization Model. The main habitat exposure outputs contain rasters all of the climate exposure results: 1 historic run: 1981-2010 and 12 future runs: 3 time periods (2010-2039, 2040-2069, 2070-2099) under 2 emission scenarios and 2 climate scenarios as well as reclassified rasters where the outputs were binned into 5 groups. To distinguish refugia areas from high-stress areas in the climate exposure results above, the team classified the climate frequency distribution for each vegetation type, which are labeled as CA refugia combined 45 and 85 for the respective RCP. Finally, the team looked at the spatial patterns of just refugia for the 2 climate models to identify areas where they align, defined as CA refugia concensus.

This data release contains monthly 270-meter resolution Basin Characterization Model (BCMv8) climate and hydrologic variables for Localized Constructed Analog (LOCA; Pierce et al., 2014)-downscaled HadGEM2-CC Global Climate Model (GCM) for Representative Concentration Pathway (RCP) 4.5 (medium-low emissions) and 8.5 (high emissions) for hydrologic California. The LOCA climate scenarios span water years 1950 to 2099 with greenhouse-gas forcings beginning in 2006. The LOCA downscaling method has been shown to produce better estimates of extreme events and reduces the common downscaling problem of too many low-precipitation days (Pierce et al., 2014). Ten GCMs were selected from the full ensemble of models from the fifth Coupled Model Intercomparison Project from the World Climate Research Programme (CMIP5) based on GCM historical performance to address specific needs for California water-resource planning (California Department of Water Resources Climate Change Technical Advisory Group, 2015). The 10 GCMs with RCP 4.5 and 8.5 each were statistically downscaled using the LOCA method (Pierce et al., 2014) from 2-degree (approximately 222-kilometer; km) quadrangles to 6-km resolution. Next, the scenarios were spatially downscaled from 6 km to 270 meters (Flint and Flint, 2012) and run through the BCMv8 using the same model parameters and input files as the historical BCM model (BCMv8; Flint et al., 2021). Downscaled gridded climate variables include precipitation (ppt), minimum temperature (tmn), maximum temperature (tmx), and potential evapotranspiration (pet). Gridded hydrologic variables include: actual evapotranspiration (aet), climatic water deficit (cwd), snowpack (pck), recharge (rch), runoff (run), and soil storage (str). The units for temperature variables are degrees Celsius, and all other variables are in millimeters per month. Monthly variables from water years 1951 to 2099 are summarized into water year files (for example, water year 1951 includes October 1950 - September 1951) and 30-year average summaries from 1951 to 2099. Raster grids are in the NAD83 California Teale Albers, (meters) projection in an open format ascii text file (*.asc). This data release includes a child item for each RCP (4.5 & 8.5) for the HadGEM2-CC GCM. Each RCP child item contains 4 child items: 1. 30-year summaries (Water year files averaged for selected 30-year periods, zipped by variable) 2. Monthly BCM hydrology variables (monthly BCM hydrology variables zipped by decade) 3. Monthly climate variables (monthly climate variables zipped by decade) 4. Water year summaries (monthly files summed (aet, cwd, pck, rch, run, str, pet, and ppt) or averaged (tmn and tmx) by water year, zipped by variable) References cited: California Department of Water Resources Climate Change Technical Advisory Group, 2015, Perspectives and guidance for climate change analysis: Sacramento, Calif., California Department of Water Resources Technical Information Record, 142 p. Flint, L.E., Flint, A.L., and Stern, M.A., 2021, The Basin Characterization Model - A monthly regional water balance software package (BCMv8) data release and model archive for hydrologic California (ver. 3.0, June 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P9PT36UI. Flint, L.E., and Flint, A.L., 2012, Downscaling future climate scenarios to fine scales for hydrologic and ecological modeling and analysis: Ecological Processes, v. 1, no. 2, 15 p., https://doi.org/10.1186/2192-1709-1-2. Pierce, D.W., Cayan, D.R. and Thrasher, B.L., 2014. Statistical downscaling using localized constructed analogs (LOCA). Journal of hydrometeorology, 15(6), pp.2558-2585.