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.

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.

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.

Tabular data output from a series of groundwater modeling simulations for five counties along the Central Coast of California, USA. We used a spatially explicit state-and-transition simulation model with stocks and flows that integrates climate, land-use change, human water use, and groundwater gain-loss to examine the impact of future climate and land use change on groundwater balance and water demand at 270-m resolution from 2010 to 2060. The model incorporated downscaled groundwater recharge projections based on a Warm/Wet and a Hot/Dry climate future using output from the Basin Characterization Model, a spatially explicit hydrological process-based model. Two urbanization projections from a parcel-based, regional urban growth model representing 1) recent historical and 2) state-mandated housing growth projections were used as alternative spatial targets for future urban growth. Agricultural projections were based on recent historical trends from remote sensing data. Annual projected changes in groundwater balance were calculated as the difference between land-use related water demand, based on historical estimates, and climate-driven recharge plus agriculture return flows to groundwater from excess irrigation. For each combination of the two climate and two land-use change scenarios, we ran 50 Monte Carlo realizations of the model. Results presented here have been aggregated from the individual cell level and summarized by county.

Tabular data output from a series of groundwater modeling simulations for five counties along the Central Coast of California, USA. We used a spatially explicit state-and-transition simulation model with stocks and flows that integrates climate, land-use change, human water use, and groundwater gain-loss to examine the impact of future climate and land use change on groundwater balance and water demand at 270-m resolution from 2010 to 2060. The model incorporated downscaled groundwater recharge projections based on a Warm/Wet and a Hot/Dry climate future using output from the Basin Characterization Model, a spatially explicit hydrological process-based model. Two urbanization projections from a parcel-based, regional urban growth model representing 1) recent historical and 2) state-mandated housing growth projections were used as alternative spatial targets for future urban growth. Agricultural projections were based on recent historical trends from remote sensing data. Annual projected changes in groundwater balance were calculated as the difference between land-use related water demand, based on historical estimates, and climate-driven recharge plus agriculture return flows to groundwater from excess irrigation. For each combination of the two climate and two land-use change scenarios, we ran 50 Monte Carlo realizations of the model. Results presented here have been aggregated from the individual cell level and summarized by county.

This data release provides 270-m resolution maps of hotspots of vulnerability to projected changes in land-use, water shortages, and climate from 2001-2061 for agricultural, domestic, and ecological communities in the Central Coast of California, USA, under five management scenarios. This data covers the counties of Santa Cruz, San Benito, Monterey, San Luis Obispo, and Santa Barbara counties, but only cover those areas overlying a groundwater basin (because these contain the overwhelming majority of regional anthropogenic land-uses). Data are provided as .zip compressed file packages containing geospatial raster surfaces (.tif format). Each map is the product of one of three types of exposure to change (land, water, or climate) and one of three types of sensitivity to that change (agricultural, domestic, ecological). The resulting vulnerability measures map hotspots of nine vulnerabilities, plus a tenth map that is the sum of all nine measures to identify hotspots of overall vulnerability. See Van Schmidt et al. (2023) in Ecology & Society (doi: TBD) for full methodological details. Briefly, exposure to future land-use change and water shortages were jointly forecast from 2001 to 2061 with the Land Use and Carbon + Water Simulator (LUCAS-W) based on historical empirical rates. Exposure to climate change was calculated from five model-averaged RCP 8.5 forecasts of the Basin Characterization Model (BCM), which estimated change in runoff as surface water, potential recharge to groundwater aquifers, and climatic water deficit (CWD), among other variables. Lastly, sensitivity for communities was obtained from diverse datasets including LUCAS-W cropland projections, crop water demand data, farmland importance rankings, 2017 census data, range maps for imperiled species and subspecies, and wildlife agency reports. Sensitivity and exposure layers were rescaled 0-1 to allow for comparison, and the final vulnerability measures therefore have a possible range from 0 (no vulnerability) up to a maximum of 1 (maximum exposure and maximum sensitivity). The nine measures are as follows: (1) Land-Agricultural: Loss of important farmland; (2) Land-Domestic: Lack of new development in areas with housing needs; (3) Land-Ecological: Loss of critical habitats for endangered species; (4) Water-Agricultural: Increased water demand that cannot be fallowed (orchards/vineyards); (5) Water-Domestic: Household vulnerability to increased water inaffordability; (6) Water-Ecological: Drying of groundwater-dependent habitats for endangered species; (7) Climate-Agricultural: Increased irrigation water needs of crops; (8) Climate-Domestic: Household vulnerability to heat-related health impacts; (9) Climate-Ecological: Loss of runoff & recharge that keeps streams, ponds, and vernal pools wet. Each .zip file is a compressed file package containing maps of each measure under five scenarios, which have different sets of management assumptions along two axes, Water management Low/Moderate/High intensity and Land use management Low/Moderate/High intensity: - MM (Moderate / Moderate management intensity): a scenario where water demand caps under the Sustainable Groundwater Management Act (SGMA) 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 intensity): a pre-SGMA "business-as-usual" scenario where water demand is uncoupled from land-use change and does not need to stabilize at sustainable levels. -- WH (Water management High intensity): a scenario that assumes that water demand caps, but with increased caps due

This data release provides 270-m resolution maps of hotspots of vulnerability to projected changes in land-use, water shortages, and climate from 2001-2061 for agricultural, domestic, and ecological communities in the Central Coast of California, USA, under five management scenarios. This data covers the counties of Santa Cruz, San Benito, Monterey, San Luis Obispo, and Santa Barbara counties, but only cover those areas overlying a groundwater basin (because these contain the overwhelming majority of regional anthropogenic land-uses). Data are provided as .zip compressed file packages containing geospatial raster surfaces (.tif format). Each map is the product of one of three types of exposure to change (land, water, or climate) and one of three types of sensitivity to that change (agricultural, domestic, ecological). The resulting vulnerability measures map hotspots of nine vulnerabilities, plus a tenth map that is the sum of all nine measures to identify hotspots of overall vulnerability. See Van Schmidt et al. (2023) in Ecology & Society (doi: TBD) for full methodological details. Briefly, exposure to future land-use change and water shortages were jointly forecast from 2001 to 2061 with the Land Use and Carbon + Water Simulator (LUCAS-W) based on historical empirical rates. Exposure to climate change was calculated from five model-averaged RCP 8.5 forecasts of the Basin Characterization Model (BCM), which estimated change in runoff as surface water, potential recharge to groundwater aquifers, and climatic water deficit (CWD), among other variables. Lastly, sensitivity for communities was obtained from diverse datasets including LUCAS-W cropland projections, crop water demand data, farmland importance rankings, 2017 census data, range maps for imperiled species and subspecies, and wildlife agency reports. Sensitivity and exposure layers were rescaled 0-1 to allow for comparison, and the final vulnerability measures therefore have a possible range from 0 (no vulnerability) up to a maximum of 1 (maximum exposure and maximum sensitivity). The nine measures are as follows: (1) Land-Agricultural: Loss of important farmland; (2) Land-Domestic: Lack of new development in areas with housing needs; (3) Land-Ecological: Loss of critical habitats for endangered species; (4) Water-Agricultural: Increased water demand that cannot be fallowed (orchards/vineyards); (5) Water-Domestic: Household vulnerability to increased water inaffordability; (6) Water-Ecological: Drying of groundwater-dependent habitats for endangered species; (7) Climate-Agricultural: Increased irrigation water needs of crops; (8) Climate-Domestic: Household vulnerability to heat-related health impacts; (9) Climate-Ecological: Loss of runoff & recharge that keeps streams, ponds, and vernal pools wet. Each .zip file is a compressed file package containing maps of each measure under five scenarios, which have different sets of management assumptions along two axes, Water management Low/Moderate/High intensity and Land use management Low/Moderate/High intensity: - MM (Moderate / Moderate management intensity): a scenario where water demand caps under the Sustainable Groundwater Management Act (SGMA) 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 intensity): a pre-SGMA "business-as-usual" scenario where water demand is uncoupled from land-use change and does not need to stabilize at sustainable levels. -- WH (Water management High intensity): a scenario that assumes that water demand caps, but with increased caps due

Seamless unconfined groundwater heads for coastal California groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (i.e. land surface less than approximately 10 m above mean sea level) areas. In areas where coastal elevations increase rapidly (e.g., bluff stretches), the model boundary was set approximately 1 kilometer inland of the present-day shoreline. Steady-state MODFLOW groundwater flow models were used to obtain detailed (10-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0 to 2 meters (m) in 0.25 m increments, 2.5 m, 3 m, and 5 m) using a range of horizontal hydraulic conductivity (Kh) scenarios (0.1, 1, and 10 m/day). For each SLR/Kh combination, results are provided for two marine boundary conditions, local mean sea level (LMSL) and mean higher-high water (MHHW), and two model versions. In the first model version, groundwater reaching the land surface is removed from the model, simulating loss via natural drainage. In the second model version, groundwater reaching the land surface is retained, simulating the worst-case "linear" response of groundwater head to sea-level rise. Modeled groundwater heads were then subtracted from high-resolution topographic digital elevation model (DEM) data to obtain the water table depths, which are represented as polygons for specific depth ranges in this dataset. Additional details about the groundwater model and data sources are outlined in Befus and others (2020) and in Groundwater_model_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5b8ef008e4b0702d0e7ec72b?name=Groundwater_model_methods.pdf). Methods specific to groundwater head and water table depth products are outlined in Groundwater_head_and_water_table_depth_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5bda1563e4b0b3fc5cec39b4?name=Groundwater_head _and_water_table_depth_methods.pdf). Methods specific to groundwater emergence and shoaling products are outlined in Groundwater_emergence_and_shoaling_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5bd9f318e4b0b3fc5cec20ed?name=Groundwater_emergence_and_shoaling_methods.pdf). Please read the model details, data sources and methods summaries and inspect model output carefully. Data are complete for the information presented. Users should note that while the metadata Spatial Reference Information/UTM Zone Number in this document is 10, some files in southern California are in UTM Zone 11, as noted in the Format Specification for individual downloadable files. As a result users may need to modify the metadata for automated import and display of Zone 11 datafiles.

Seamless unconfined groundwater heads for coastal California groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (i.e. land surface less than approximately 10 m above mean sea level) areas. In areas where coastal elevations increase rapidly (e.g., bluff stretches), the model boundary was set approximately 1 kilometer inland of the present-day shoreline. Steady-state MODFLOW groundwater flow models were used to obtain detailed (10-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0 to 2 meters (m) in 0.25 m increments, 2.5 m, 3 m, and 5 m) using a range of horizontal hydraulic conductivity (Kh) scenarios (0.1, 1, and 10 m/day). For each SLR/Kh combination, results are provided for two marine boundary conditions, local mean sea level (LMSL) and mean higher-high water (MHHW), and two model versions. In the first model version, groundwater reaching the land surface is removed from the model, simulating loss via natural drainage. In the second model version, groundwater reaching the land surface is retained, simulating the worst-case "linear" response of groundwater head to sea-level rise. Modeled groundwater heads were then subtracted from high-resolution topographic digital elevation model (DEM) data to obtain the water table depths, which are represented as polygons for specific depth ranges in this dataset. Additional details about the groundwater model and data sources are outlined in Befus and others (2020) and in Groundwater_model_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5b8ef008e4b0702d0e7ec72b?name=Groundwater_model_methods.pdf). Methods specific to groundwater head and water table depth products are outlined in Groundwater_head_and_water_table_depth_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5bda1563e4b0b3fc5cec39b4?name=Groundwater_head _and_water_table_depth_methods.pdf). Methods specific to groundwater emergence and shoaling products are outlined in Groundwater_emergence_and_shoaling_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5bd9f318e4b0b3fc5cec20ed?name=Groundwater_emergence_and_shoaling_methods.pdf). Please read the model details, data sources and methods summaries and inspect model output carefully. Data are complete for the information presented. Users should note that while the metadata Spatial Reference Information/UTM Zone Number in this document is 10, some files in southern California are in UTM Zone 11, as noted in the Format Specification for individual downloadable files. As a result users may need to modify the metadata for automated import and display of Zone 11 datafiles.

Seamless unconfined groundwater heads for coastal California groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (i.e. land surface less than approximately 10 m above mean sea level) areas. In areas where coastal elevations increase rapidly (e.g., bluff stretches), the model boundary was set approximately 1 kilometer inland of the present-day shoreline. Steady-state MODFLOW groundwater flow models were used to obtain detailed (10-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0 to 2 meters (m) in 0.25 m increments, 2.5 m, 3 m, and 5 m) using a range of horizontal hydraulic conductivity (Kh) scenarios (0.1, 1, and 10 m/day). For each SLR/Kh combination, results are provided for two marine boundary conditions, local mean sea level (LMSL) and mean higher-high water (MHHW), and two model versions. In the first model version, groundwater reaching the land surface is removed from the model, simulating loss via natural drainage. In the second model version, groundwater reaching the land surface is retained, simulating the worst-case "linear" response of groundwater head to sea-level rise. Additional details about the groundwater model and data sources are outlined in Befus and others (2020) and in Groundwater_model_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5b8ef008e4b0702d0e7ec72b?name=Groundwater_model_methods.pdf). Methods specific to groundwater head and water table depth products are outlined in Groundwater_head_and_water_table_depth_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5bda1563e4b0b3fc5cec39b4?name=Groundwater_head _and_water_table_depth_methods.pdf). Please read the model details, data sources and methods summaries and inspect model output carefully. Data are complete for the information presented. Users should note that while the metadata Spatial Reference Information/UTM Zone Number in this document is 10, some files in southern California are in UTM Zone 11, as noted in the Format Specification for individual downloadable files. As a result users may need to modify the metadata for automated import and display of Zone 11 datafiles.