For many years, the California Department of Water Resources (DWR) has collected land use data throughout the state and used this information to develop water use estimates for statewide and regional planning efforts, including water use projections, water use efficiency evaluation, groundwater model development, and water transfers. These data are essential for regional analysis and decision making, which has become increasingly important as DWR and other state agencies seek to address resource management issues, regulatory compliance issues, environmental impacts, ecosystem services, urban and economic development, and other issues. Increased availability of digital satellite imagery, aerial photography and new analytical tools make remote sensing based land use surveys possible at a field scale that is comparable to that of DWR’s historical on the ground field surveys. Current technologies allow accurate, large-scale crop and land use identification to be performed at desired time increments, and make possible more frequent and comprehensive statewide land use information. Responding to this need, DWR sought expertise and support for identifying crop types and other land uses and quantifying crop acreages statewide using remotely sensed imagery and associated analytical techniques. Currently, Statewide Crop Maps are available for the Water Years 2014, 2016, 2018, 2019, 2020, 2021 and PROVISIONALLY for 2022. Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer: https://gis.water.ca.gov/app/CADWRLandUseViewer. For Regional Land Use Surveys follow: https://data.cnra.ca.gov/dataset/region-land-use-surveys. For County Land Use Surveys follow: https://data.cnra.ca.gov/dataset/county-land-use-surveys.

The California Flood Management Districts geodatabase contains several spatial data layers indicating boundaries of various local flood management agencies throughout the state. There are also attribute tables indicating current contact information, updated as of Spring, 2006, as included in the Directory of Flood Officials, produced by the California Department of Water Resources Division of Flood Management. Of the various layers, the most numerous are referred to as reclamation districts. The reclamation districts layer is an indication of the approximate jurisdictional boundary of both currently active or once-active-but-now-inactive reclamation districts. Districts have in some cases merged, dissolved, divided, and been modified since their original formation. The reclamation districts indicated here were generated from a variety of sources, including (in order of boundary accuracy preference) complete legal descriptions submitted at the time of District formation, CAD boundary files provided by District engineers, boundaries digitized by Department of Water Resources Delta-Suisun Office over orthophotography, incomplete legal descriptions submitted at the time of District formation, DWR Land Use maps, a 1997 California Office of Emergency Services effort to map boundaries, and sundry other means. The work has essentially been an ongoing effort since the production of the original 1997 layer, in order to improve that first effort somewhat. Most of the improvements have focused on Districts within the Sacramento-San Joaquin Delta region, since DWR's office responsible for that area has undertaken most of the improvement work. As a result, there are probably many remaining data gaps and inaccuracies, particularly in areas outside of the Delta. This is particularly true of DWR maintenance areas and for levee districts, both of which will certainly require updating in the future.

DWR has a long history of studying and characterizing California’s groundwater aquifers as a part of California’s Groundwater (Bulletin 118). The Basin Characterization Program provides the latest data and information about California’s groundwater basins to help local communities better understand their aquifer systems and support local and statewide groundwater management.

Under the Basin Characterization Program, new and existing data (AEM, lithology logs, geophysical logs, etc.) will be integrated to create continuous maps and three-dimensional models. To support this effort, new data analysis tools will be developed to create texture models, hydrostratigraphic models, and aquifer flow parameters. Data collection efforts will be expanded to include advanced geologic, hydrogeologic, and geophysical data collection and data digitization and quality control efforts will continue. To continue to support data access and data equity, the Basin Characterization Program will develop new online, GIS-based, visualization tools to serve as a central hub for accessing and exploring groundwater related data in California.

Additional information can be found on the Basin Characterization Program webpage.

DWR's Evaluation of Groundwater Resources: Maps and Models

DWR will undertake local, regional, and statewide investigations to evaluate California's groundwater resources and develop state-stewarded maps and models. New and existing data will be combined and integrated using the analysis tools described below to develop maps and models to be developed will describe the grain size, the hydrostratigraphic properties, and hydrogeologic conceptual properties of California’s aquifers. These maps and models help groundwater managers understand how groundwater is stored and moves within the aquifer. The models will be state-stewarded, meaning that they will be regularly updated, as new data becomes available, to ensure that up-to-date information is used for groundwater management activities. The first iterations of the following maps and models will be published as they are developed:

• Texture Models
• Hydrostratigraphic Models
• Aquifer Recharge Potential Maps
• Extent of Important Aquifer Units
• Depth to Basement
• Depth to Freshwater

Data Collection

As a part of the Basin Characterization Program, advanced geologic, hydrogeologic, and geophysical data will be collected to improve our understanding of groundwater basins. Data collected under Basin Characterization are collected at a local, regional, or statewide scale depending on the scope of the study.

Local Investigations:

• Madera & North Kings
• Pajaro
• Western San Joaquin Valley

Regional Investigations:

• Sacramento Valley
• Four County Area of San Joaquin Valley (Madera, Fresno, Kings, and Tulare)
• San Joaquin Valley

Statewide Investigations:

• Statewide AEM Surveys

Data Compilation and Digitization

Digitized Existing Lithology and Geophysical Logs

Lithology and geophysical logging data have been digitized to support the Statewide AEM Survey Project and will continue to be digitized to support Basin Characterization efforts. All digitized lithology logs with Well Completion Report IDs will be imported back into the OSWCR database.

Digitized lithology and geophysical logging can be found under the following resource:

• Digitized Lithology and Geophysical Logs.

Analysis Tools and Process Documents

To develop the state-stewarded maps and models outlined above, new tools and process documents will be created to integrate and analyze a wide range of data, including geologic, geophysical, and hydrogeologic information. By combining and assessing various datasets, these tools will help create a more complete picture of California's groundwater basins. All tools, along with guidance documents, will be made publicly available for local groundwater managers to use to support development of maps and models at a local scale. All tools and guidance will be updated as revisions to tools and process documents are made.

Analysis tools and process documents can be found under the following resource:

• Data Analysis Tools and Process Documents.

Data Visualization

Data access equity is a priority for the Basin Characterization Program. To ensure data access equity, the Basin Characterization Program has developed applications and tools to allow data to be visualized without needing access to expensive data visualization software. This list below provides links and descriptions for the Basin Characterization's suite of data viewers.

SGMA Data Viewer: Basin Characterization tab: Provides maps, depth slices, and profiles of Basin Characterization maps, models, and datasets, including the following:

• Aquifer Recharge Potential Maps
• Subsurface Texture Model Depth Slices
• Statewide AEM Survey Texture Depth Slices
• Lithology Log Location Maps
• Geophysical Logs Location Maps
• Statewide AEM Survey Profile Images

3D AEM Data Viewer: Displays the Statewide AEM Survey electrical resistivity and coarse fraction data, along with lithology logs, in a three-dimensional space.

DWR's Subsurface Viewer: Provides a map view and profile view of the Statewide AEM Survey electrical resistivity and coarse fraction data, along with lithology logs. The map view dynamically shows the exact location of AEM data displayed.

Basin Characterization Exchange

The Basin Characterization Exchange (BCX) is a meeting series and network space for the Basin Characterization community to exchange ideas, share lessons learned, define needed guidance, and highlight research topics. The BCX is open to federal, state, and local agencies, consultants, NGOs, academia, and interested parties who participate in Basin Characterization efforts. The BCX also plays a pivotal role in advancing the Basin Characterization Program’s activities and goals. BCX meetings will include regular updates from the Basin Characterization Program and participants can provide feedback and recommendations. Participants will also be provided with early opportunities to test data analysis tools and submit comments on draft process and guidance documents. BCX meetings are (generally) held the 3rd Tuesday of the month from 12:30 - 1:30 pm (PST).

Join the BCX listserv to become a BCX member and receive meeting registration emails. Check the BCX Hub for the upcoming schedule and past meeting materials.

(Webpage Under Development) The Department of Water Resources (DWR) provides Technical Support Services (TSS) to assist Groundwater Sustainability Agencies (GSAs) with the implementation of their Groundwater Sustainability Plans (GSPs) and other local entities to better understand groundwater conditions. These services support data collection, groundwater monitoring, and improved understanding of groundwater conditions to help advance sustainable groundwater management efforts across California. Through the TSS program, DWR has partnered with GSAs and other entities on projects across the state to drill and construct groundwater monitoring wells, install groundwater level recording and telemetry equipment, perform downhole camera and geophysical surveys, and collect and analyze groundwater for general chemistry. The data and reports generated from these efforts are publicly available to support ongoing groundwater management and planning. Additional information can be found on the Assistance and Engagement webpage. Summary of Completed TSS Projects To date, DWR has completed TSS projects in 35 groundwater subbasins, constructing 234 monitoring wells at 92 sites statewide. Each of these wells have been assigned a State Well Number (SWN), have had a Well Completion Report (WCR) submitted to DWRs Online System for Well Completion Reports (OSWCR), and have been registered either through the California Statewide Groundwater Elevation Monitoring (CASGEM) Online System or the Sustainable Groundwater Management Act (SGMA) Portal’s Monitoring Network Module (MNM). Groundwater level data from these wells are collected by the GSA or DWR and submitted to CASGEM and/or the MNM. These data can be viewed on the Water Data Library (WDL). WCRs for these wells can be found using the Well Completion Report Map Application. A summary table of completed TSS wells including their associated well name(s), site code(s), SWN(s), and WCR number(s), can be viewed and/or downloaded here: DWR Completed TSS Wells An interactive GIS map containing a feature set of all completed TSS wells can be accessed here: GIS Map of Completed TSS Wells The individual TSS well locations, associated borehole lithologic information, and groundwater level data can be viewed on the SGMA Data Viewer by: Checking the “DWR TSS Wells” box under the “Groundwater Levels” tab on the left side of the screen. Clicking on any one of the well location symbols that appear on the interactive map. Clicking on one of the associated Site Code numbers that appear in the results table. Completed TSS Projects by Groundwater Subbasin Below is a list of subbasins in which TSS projects have been completed. These projects are organized by DWR Region (Northern Region, North Central Region, South Central Region, and Southern Region). Each subbasin listed below has one or more completed TSS project. As more TSS projects are completed, they will be added to this list. All completed TSS projects have several associated documents and datasets, including a Well Installation Summary Report, TSS Agreement between DWR and the GSA, CEQA Notice of Exemption (NOE), Land Use or License Agreement, Local Drilling Permit, Composite Lithologic Log, Survey Report, and a Water Quality Analytical Report. Some projects also include downhole geophysical logs. These data and reports can be accessed by clicking on the subbasin below in which the project is located. Northern Region Antelope Subbasin Big Valley Subbasin Butte Valley Subbasin Colusa Subbasin Corning Subbasin Enterprise Subbasin Red Bluff Subbasin Shasta Valley Subbasin Sierra Valley Subbasin Wyandotte Creek Subbasin North Central Region Cosumnes Subbasin Eastern San Joaquin Subbasin North Yuba Subbasin Petaluma Valley Subbasin Santa Rosa Plain Subbasin Solano Subbasin Sonoma Valley Subbasin South Yuba Subbasin Tracy Subbasin Ukiah Valley Subbasin Yolo Subbasin South Central Region Delta Mendota Subbasin Kaweah Subbasin Kern County Subbasin Kings Subbasin Paso Robles Area Subbasin Tule Subbasin Turlock Subbasin Southern Region Borrego Springs Subbasin Cuyama Valley Subbasin Indian Wells Subbasin Indio Subbasin Mound Subbasin Oxnard Plain Subbasin Pleasant Valley Subbasin

Land use data is critically important to the work of the Department of Water Resources (DWR) and other California agencies. Understanding the impacts of land use, crop location, acreage, and management practices on environmental attributes and resource management is an integral step in the ability of Groundwater Sustainability Agencies (GSAs) to produce Groundwater Sustainability Plans (GSPs) and implement projects to attain sustainability. Land IQ was contracted by DWR to develop a comprehensive and accurate spatial land use database for the 2021 water year (WY 2021), covering over 10.7 million acres of agriculture on a field scale and additional areas of urban extent.The primary objective of this effort was to produce a spatial land use database with an accuracy exceeding 95% using remote sensing, statistical, and temporal analysis methods. This project is an extension of the land use mapping which began in the 2014 crop year, which classified over 15 million acres of land into agricultural and urban areas. Unlike the 2014 and 2016 datasets, the annual WY datasets from and including 2018, 2019, 2020, and 2021 include multi-cropping.Land IQ integrated crop production knowledge with detailed ground truth information and multiple satellite and aerial image resources to conduct remote sensing land use analysis at the field scale. Individual fields (boundaries of homogeneous crop types representing true cropped area, rather than legal parcel boundaries) were classified using a crop category legend and a more specific crop type legend. A supervised classification process using a random forest approach was used to classify delineated fields and was carried out county by county where training samples were available. Random forest approaches are currently some of the highest performing methods for data classification and regression. To determine frequency and seasonality of multicropped fields, peak growth dates were determined for each field of annual crops. Fields were attributed with DWR crop categories, which included citrus/subtropical, deciduous fruits and nuts, field crops, grain and hay, idle, pasture, rice, truck crops, urban, vineyards, and young perennials. These categories represent aggregated groups of specific crop types in the Land IQ dataset.Accuracy was calculated for the crop mapping using both DWR and Land IQ crop legends. The overall accuracy result for the crop mapping statewide was 97% using the Land IQ legend (Land IQ Subclass) and 98% using the DWR legend (DWR Class). Accuracy and error results varied among crop types. Some less extensive crops that have very few validation samples may have a skewed accuracy result depending on the number and nature of validation sample points. DWR revised crops and conditions from the Land IQ classification were encoded using standard DWR land use codes added to feature attributes, and each modified classification is indicated by the value 'r' in the ‘DWR_REVISE' data field. Polygons drawn by DWR, not included in Land IQ dataset receive the 'n' code for new. Boundary change (i.e. DWR changed the boundary that LIQ delivered, could be split boundary) indicated by 'b'. Each polygon classification is consistent with DWR attribute standards, however some of DWR's traditional attribute definitions are modified and extended to accommodate unavoidable constraints within remote-sensing classifications, or to make data more specific for DWR's water balance computation needs. The original Land IQ classifications reported for each polygon are preserved for comparison, and are also expressed as DWR standard attributes. Comments, problems, improvements, updates, or suggestions about local conditions or revisions in the final data set should be forwarded to the appropriate Regional Office Senior Land Use Supervisor.Revisions were made if:- DWR corrected the original crop classification based on local knowledge and analysis,-PARTIALLY IRRIGATED CROPS Crops, irrigated for only part of their normal irrigation season were given the special condition of ‘X’,-In certain areas, DWR changed the irrigation status to non-irrigated. Among those areas the special condition may have been changed to 'Partially Irrigated' based on image analysis and local knowledge,- young versus mature stages of perennial orchards and vineyards were identified (DWR added ‘Young’ to Special Condition attributes),- DWR determined that a field originally classified ‘Idle’ or 'Unclassified' were actually cropped one or more times during the year,- the percent of cropped area was changed from the original acres reported by Land IQ (values indicated in DWR ‘Percent’ column),- DWR determined that the field boundary should have been changed to better reflect the cropped area of the polygon and is identified by a 'b' in the DWR_REVISED column,- DWR determined that the field boundary should have been split to better reflect separate crops within the same polygon and identified by a 'b' in the DWR_REVISED column,- The ‘Mixed’ was added to the MULTIUSE column refers to no boundary change, but percent of field is changed where more than one crop is found,- DWR identified a distinct early or late crop on the field before the main season crop (‘Double’ was added to the MULTIUSE column); if the 1st and 2nd sequential crops occupied different portions of the total field acreage, the area percentages were indicated for each crop).This dataset includes multicropped fields. If the field was determined to have more than one crop during the course of the WY (Water Year begins October 1 and ends September 30 of the following year), the order of the crops is sequential, beginning with Class 1. All single cropped fields will be placed in Class 2, so every polygon will have a crop in the Class 2 and CropType2 columns. In the case that a permanent crop was removed during the WY, the Class 2 crop will be the permanent crop followed by ‘X’ – Unclassified fallow in the Class 3 column. In the case of Intercropping, the main crop will be placed in the Class 2 column with the partial crop in the Class 3 column.A new column for the 2019, 2020, and 2021 datasets is called ‘MAIN_CROP’. This column indicates which field Land IQ identified as the main season crop for the WY representing the crop grown during the dominant growing season for each county. The column ‘MAIN_CROP_DATE’, another addition to the 2019, 2020, and 2021 datasets, indicates the Normalized Difference Vegetation Index (NDVI) peak date for this main season crop. The column 'EMRG_CROP' for 2019, 2020, and 2021 indicates an emerging crop at the end of the WY. Crops listed indicate that at the end of the WY, September 2021, crop activity was detected from a crop that reached peak NDVI in the following WY (2022 WY). This attribute is included to account for water use of crops that span multiple WYs and are not exclusive to a single WY. It is indicative of early crop growth and initial water use in the current WY, but a majority of crop development and water use in the following WY. Crops listed in the ‘EMRG_CROP’ attribute will also be captured as the first crop (not necessarily Crop 1) in the following WY (2022 WY). These crops are not included in the 2021 UCF_ATT code as their peak date occurred in the following WY.For the 2021 dataset new columns added are: 'YR_PLANTED' which represent the year orchard / grove was planted. 'SEN_CROP' indicates a senescing crop at the beginning of the WY. Crops listed indicate that at the beginning of the WY, October 2020, crop activity was detected from a crop that reached peak NDVI in the previous WY (2020 WY), thus was a senescing crop. This is included to account for water use of crop growth periods that span multiple WYs and are not exclusive to a WY. Crops listed in the ‘SEN_CROP’ attribute are also captured in the CROPTYP 1 through 4 sequence of the previous WY (2020 WY). These crops are not included in the 2021 UCF_ATT code as their peak NDVI occurred in the previous WY. CTYP#_NOTE: indicates a more specific land use subclassification from the DWR Standard Land Use Legend that is not included in the primary, DWR Remote Sensing Land Use Legend.DWR reviewed and revised the data in some cases. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.6, dated September 27, 2023. This data set was not produced by DWR. Data were originally developed and supplied by Land IQ, LLC, under contract to California Department of Water Resources. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Detailed compilation and reviews of Statewide Crop Mapping and metadata development were performed by DWR Land Use Unit staff, therefore you may forward your questions to Landuse@water.ca.gov.This dataset is current as of 2021.

2021 STATEWIDE CROP MAPPING - PROVISIONALLand use data is critically important to the work of the Department of Water Resources (DWR) and other California agencies. Understanding the impacts of land use, crop location, acreage, and management practices on environmental attributes and resource management is an integral step in the ability of Groundwater Sustainability Agencies (GSAs) to produce Groundwater Sustainability Plans (GSPs) and implement projects to attain sustainability. Land IQ was contracted by DWR to develop a comprehensive and accurate spatial land use database for the 2021 water year (WY 2021). The primary objective of this effort was to produce a spatial land use database with accuracies exceeding 95% using remote sensing, statistical, and temporal analysis methods. This project is an extension of the 2014, 2016, 2018, 2019, and 2020 land use mapping, which classified over 14 million acres of land into irrigated agriculture and urban area. Unlike the 2014 and 2016 datasets, the WY 2018, 2019, 2020, and 2021 datasets include multi-cropping and incorporates DWR ground-truth data from Siskiyou, Modoc, Lassen and Shasta counties. Land IQ integrated crop production knowledge with detailed ground truth information and multiple satellite and aerial image resources to conduct remote sensing land use analysis at the field scale. Individual fields (boundaries of homogeneous crop types representing cropped area, rather than legal parcel boundaries) were classified using a crop category legend and a more specific crop type legend. A supervised classification method using a random forest approach was used to classify delineated fields and was carried out county by county where training samples were available. Random forest approaches are currently some of the highest performing methods for data classification and regression. To determine frequency and seasonality of multiple-cropped fields, peak growth dates were determined for annual crops. Fields were attributed with DWR crop categories and included citrus/subtropical, deciduous fruits and nuts, field crops, grain and hay, idle, pasture, rice, truck crops, urban, vineyards, and young perennials. These categories represent aggregated groups of specific crop types in the Land IQ dataset. Accuracy was calculated for the crop mapping using both DWR and Land IQ crop legends. The overall accuracy result for the crop mapping statewide was XX.X% (UPDATE) using the Land IQ legend and XX% (UPDATE) using the DWR legend. Accuracy and error results varied among crop types. In particular, some less extensive crops that have very few validation samples may have a skewed accuracy result depending on the number and nature of validation sample points. DWR revised crops and conditions from the Land IQ classification were encoded using standard DWR land use codes added to feature attributes, and each modified classification is indicated by the value 'r' in the ‘DWR_REVISE' data field. Polygons drawn by DWR, not included in Land IQ dataset receive the 'n' code for new. Boundary change (i.e. DWR changed the boundary that LIQ delivered could be split boundary) indicated by 'b'. Each polygon classification is consistent with DWR attribute standards, however some of DWR's traditional attribute definitions are modified and extended to accommodate unavoidable constraints within remote-sensing classifications, or to make data more specific for DWR's water balance computation needs. The original Land IQ classifications reported for each polygon are preserved for comparison, and are also expressed as DWR standard attributes. Comments, problems, improvements, updates, or suggestions about local conditions or revisions in the final data set should be forwarded to the appropriate Regional Office Senior Land Use Supervisor. Revisions were made if: - DWR corrected the original crop classification based on local knowledge and analysis, -PARTIALLY IRRIGATED CROPS Crops irrigated for only part of their normal irrigation season were given the special condition of ‘X’, -In certain areas, DWR changed the irrigation status to irrigated or non-irrigated. Among those areas the special condition may have been changed to 'Partially Irrigated' based on image analysis and local knowledge, - young versus mature stages of perennial orchards and vineyards were identified (DWR added ‘Young’ to Special Condition attributes), - DWR determined that a field originally classified ‘Idle’ was actually cropped one or more times during the year, - the percent of cropped area was changed from the original acres reported by Land IQ (values indicated in DWR ‘Percent’ column), - DWR determined that the field boundary should have been split to better reflect separate crops within the same polygon and identified by a 'b' in the DWR_REVISED column, - The ‘Mixed’ was added to the MULTIUSE column refers to no boundary change, but percent of field is changed where more than one crop is found, - DWR identified a distinct early or late crop on the field before the main season crop (‘Double’ was added to the MULTIUSE column); if the 1st and 2nd sequential crops occupied different portions of the total field acreage, the area percentages were indicated for each crop). This dataset includes multicropped fields. If the field was determined to have more than one crop during the course of the water year, the order of the crops is sequential, beginning with Class 1. All single cropped fields will be placed in Class 2, so every polygon will have a crop in the Class 2 and CropType2 columns. In the case that a permanent crop was removed during the water year, the Class 2 crop will be the permanent crop followed by ‘X’ – Unclassified fallow in the Class 3 column. In the case of Intercropping, the main crop will be placed in the Class 2 column with the partial crop in the Class 3 column. The column 'MAIN_CROP' was added in 2019 and has been continued through the 2021 dataset. This column indicates which field Land IQ identified as the main season crop for the water year representing the crop grown during the dominant growing season for each county. The column ‘MAIN_CROP_DATE’, another addition to the 2019 dataset, indicates the NDVI peak date for this main season crop. Asterisks (* or **) in attribute table indicates no data have been collected for that specific attribute.

DWR has a long history of studying and characterizing California’s groundwater aquifers as a part of California’s Groundwater (Bulletin 118). The Basin Characterization Program provides the latest data and information about California’s groundwater basins to help local communities better understand their aquifer systems and support local and statewide groundwater management. Under the Basin Characterization Program, new and existing data (AEM, lithology logs, geophysical logs, etc.) will be integrated to create continuous maps and three-dimensional models. To support this effort, new data analysis tools will be developed to create texture models, hydrostratigraphic models, and aquifer flow parameters. Data collection efforts will be expanded to include advanced geologic, hydrogeologic, and geophysical data collection and data digitization and quality control efforts will continue. To continue to support data access and data equity, the Basin Characterization Program will develop new online, GIS-based, visualization tools to serve as a central hub for accessing and exploring groundwater related data in California. Additional information can be found on the Basin Characterization Program webpage. DWR's Evaluation of Groundwater Resources: Maps and Models DWR will undertake local, regional, and statewide investigations to evaluate California's groundwater resources and develop state-stewarded maps and models. New and existing data will be combined and integrated using the analysis tools described below to develop maps and models to be developed will describe the grain size, the hydrostratigraphic properties, and hydrogeologic conceptual properties of California’s aquifers. These maps and models help groundwater managers understand how groundwater is stored and moves within the aquifer. The models will be state-stewarded, meaning that they will be regularly updated, as new data becomes available, to ensure that up-to-date information is used for groundwater management activities. The first iterations of the following maps and models will be published as they are developed: Texture Models Hydrostratigraphic Models Aquifer Recharge Potential Maps Extent of Important Aquifer Units Depth to Basement Depth to Freshwater Data Collection As a part of the Basin Characterization Program, advanced geologic, hydrogeologic, and geophysical data will be collected to improve our understanding of groundwater basins. Data collected under Basin Characterization are collected at a local, regional, or statewide scale depending on the scope of the study. Local Investigations: Madera & North Kings Pajaro Western San Joaquin Valley Regional Investigations: Sacramento Valley Four County Area of San Joaquin Valley (Madera, Fresno, Kings, and Tulare) San Joaquin Valley Statewide Investigations: Statewide AEM Surveys Data Compilation and Digitization Digitized Existing Lithology and Geophysical Logs Lithology and geophysical logging data have been digitized to support the Statewide AEM Survey Project and will continue to be digitized to support Basin Characterization efforts. All digitized lithology logs with Well Completion Report IDs will be imported back into the OSWCR database. Digitized lithology and geophysical logging can be found under the following resource: Digitized Lithology and Geophysical Logs. Analysis Tools and Process Documents To develop the state-stewarded maps and models outlined above, new tools and process documents will be created to integrate and analyze a wide range of data, including geologic, geophysical, and hydrogeologic information. By combining and assessing various datasets, these tools will help create a more complete picture of California's groundwater basins. All tools, along with guidance documents, will be made publicly available for local groundwater managers to use to support development of maps and models at a local scale. All tools and guidance will be updated as revisions to tools and process documents are made. Analysis tools and process documents can be found under the following resource: Data Analysis Tools and Process Documents. Data Visualization Data access equity is a priority for the Basin Characterization Program. To ensure data access equity, the Basin Characterization Program has developed applications and tools to allow data to be visualized without needing access to expensive data visualization software. This list below provides links and descriptions for the Basin Characterization's suite of data viewers. SGMA Data Viewer: Basin Characterization tab: Provides maps, depth slices, and profiles of Basin Characterization maps, models, and datasets, including the following: Aquifer Recharge Potential Maps Subsurface Texture Model Depth Slices Statewide AEM Survey Texture Depth Slices Lithology Log Location Maps Geophysical Logs Location Maps Statewide AEM Survey Profile Images 3D AEM Data Viewer: Displays the Statewide AEM Survey electrical resistivity and coarse fraction data, along with lithology logs, in a three-dimensional space. DWR's Subsurface Viewer: Provides a map view and profile view of the Statewide AEM Survey electrical resistivity and coarse fraction data, along with lithology logs. The map view dynamically shows the exact location of AEM data displayed. Basin Characterization Exchange The Basin Characterization Exchange (BCX) is a meeting series and network space for the Basin Characterization community to exchange ideas, share lessons learned, define needed guidance, and highlight research topics. The BCX is open to federal, state, and local agencies, consultants, NGOs, academia, and interested parties who participate in Basin Characterization efforts. The BCX also plays a pivotal role in advancing the Basin Characterization Program’s activities and goals. BCX meetings will include regular updates from the Basin Characterization Program and participants can provide feedback and recommendations. Participants will also be provided with early opportunities to test data analysis tools and submit comments on draft process and guidance documents. BCX meetings are (generally) held the 3rd Tuesday of the month from 12:30 - 1:30 pm (PST). Join the BCX listserv to become a BCX member and receive meeting registration emails. Check the BCX Hub for the upcoming schedule and past meeting materials.

Utah Division of Wildlife Resources administrative region boundaries.

turkey distribution, season of habitat use, and habitat values are determined by local wildlife biologist relying on observations, surveys, transplant locations, and radio/satellite data. For use in large-scale planning and reporting.

Sierra Water Workgroup has created these data layers to support the Tahoe-Sierra IRWM Project Data Management Application. Data used to create these layers were largely sourced from the CA DWR, USGS, National Hydrography Database, The Nature Conservancy, USBR, USDA Forest Service, USDA, USFS, CalEPA, and the Sierra Nevada DDS. Data layers were created by Kate Gladstein of the Sierra Water Workgroup.

Jurisdictional Dams: Sierra Water Workgroup has modified this layer of Jurisdictional Dams within the Tahoe Sierra Integrated Regional Water Management Area. Data was provided by the CA Department of Water Resources. Additional Information.

Nonearthen Shores: Sierra Water Workgroup has modified this layer displaying "nonearthen shores" within the Tahoe Sierra Integrated Regional Water Management Area. Data was provided by the National Hydrography Database, a collaborative entity between DWR and the US Bureau of Reclamation. From NHD: "The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee." Original metadata.

Wetlands: The Sierra Water Workgroup modified this layer displaying wetland areas within the Tahoe Sierra Integrated Regional Water Management Boundaries. This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the conterminous United States. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979). Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery. By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps.

Streams: Sierra Water Workgroup has produced this layer displaying flowlines of both streams and canals, within the Tahoe Sierra Integrated Regional Water Management Area. Data was provided by the National Hydrography Database, a collaborative entity between DWR and the US Bureau of Reclamation. From NHD: "The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee." Original metadata.Critical Aquatic Refuges: Sierra Water Workgroup has created this layer of critical aquatic ecosystem refuges. USDA-originated data was provided to SWWG by the ecological forecasting team Sierra Nevada DSS. From USDA FS: "This polygon layer consists of Critical Aquatic Reguges (CARs) found in the Sierra Nevada. This data was developed by the USDA Forest Service for use in the Sierra Nevada Fores Plan Amendment. Critical aquatic refuges provide habitat for native fish, amphibian and aquatic invertebrate populations." Original metadata.

HUC-12 Watersheds Boundaries: Sierra Water Work Group has modified this layer showing HUC-12 watershed boundaries outside the Tahoe-Sierra IRWM. Watershed Boundary data for this was provided by the USGS National Watershed Boundary Dataset (WBD). From USGS: “WBD provides a uniquely identified and uniform method of subdividing large drainage areas. The data is intended to be used as a tool for water-resource management and planning activities, particularly for site-specific and localized studies requiring a level of detail provided by large-scale map information. The Watershed Boundary Dataset (WBD) defines the areal extent of surface water drainage to a point, accounting for all land and surface areas. Watershed Boundaries are determined solely upon science-based hydrologic principles, not favoring any administrative boundaries or special projects, nor particular program or agency. The intent of defining Hydrologic Units (HU) for the Watershed Boundary Dataset is to establish a baseline drainage boundary framework, accounting for all land and surface areas. At a minimum, the WBD is being delineated and georeferenced to the USGS 1:24,000 scale topographic base map meeting National Map Accuracy Standards (NMAS). Hydrologic units are given a Hydrologic Unit Code (HUC). For example, a hydrologic region has a 2-digit HUC. A HUC describes where the unit is in the country and the level of the unit. The document "Federal Standards and Procedures for the National Watershed Boundary Dataset (WBD)" can be found here. ‘A hydrologic unit is a drainage area delineated to nest in a multi-level, hierarchical drainage system. Its boundaries are defined by hydrographic and topographic criteria that delineate an area of land upstream from a specific point on a river, stream or similar surface waters. A hydrologic unit can accept surface water directly from upstream drainage areas, and indirectly from associated surface areas such as remnant, non-contributing, and diversions to form a drainage area with single or multiple outlet points. Hydrologic units are only synonymous with classic watersheds when their boundaries include all the source area contributing surface water to a single defined outlet point.’” Original metadata.Private Water Districts: Sierra Water Workgroup has modified this layer of private water district boundaries in the Tahoe-Sierra Watershed Region. The Private Water District boundaries database is cooperatively shared between the U.S. Bureau of Reclamation (USBR), Mid-Pacific regional office (MP), MPGIS Service Center and the California Department of Water Resources (DWR). The USBR maintains this database with the voluntary assistance of the Private Water Districts. Original metadata. Montane Meadow Vegetation: The Sierra Water Workgroup modified this layer displaying meadow vegetation within the Tahoe Sierra Integrated Regional Water Management Boundaries. From USDA: "Data for this layer was developed by the USDA Forest Service for use in the Sierra Nevada Forest Plan Amendment Environmental Impact Statement. This layer depicts montane meadow vegetation on National Forests in the Sierra Nevada range. Meadows are wet and dry grassland types and short emergent meadow types maintained by man-made dams. Vegetation consists of a mixture of grasses, perennial herbs, rushes, and sedges. Woody vegetation is typically associated with riparian meadows. Riparian vegetation can be shrub or tree form, such as willow, alder, cottonwood, and aspen types. Meadow types are coded as wet or dry, with or without woody vegetation, or short emergent wetland. Meadow polygons are mapped to a minimum of 5 acres. California Vegetation (CALVEG) types within a meadow polygon are mapped to a minimum of 2.5 acres." Original Metadata.

Wells, Springs, Waterfalls, Gage Stations: Sierra Water Workgroup has modified this layer of hydrographic points within the Tahoe Sierra Integrated Regional Water Management Area. Data was provided by the National Hydrography Database, a collaborative entity between DWR and the US Bureau of Reclamation. From NHD: "The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not

Every published digital survey is designated as either ‘Final’, or ‘Provisional’, depending upon its status in a peer review process.Final surveys are peer reviewed with extensive quality control methods to confirm that field attributes reflect the most detailed and specific land-use classification available, following the standard DWR Land Use Legendspecific to the survey year. Data sets are considered ‘final’ following the reconciliation of peer review comments and confirmation by the originating Regional Office. During final review, individual polygons are evaluated using a combination of aerial photointerpretation, satellite image multi-spectral data and time series analysis, comparison with other sources of land use data, and general knowledge of land use patterns at the local level.Provisional data sets have been reviewed for conformance with DWR’s published data record format, and for general agreement with other sources of land use trends. Comments based on peer review findings may not be reconciled, and no significant edits or changes are made to the original survey data.The 2005 Shasta County land use survey data set was developed by DWR through its Division of Planning and Local Assistance (DPLA). DPLA was later reorganized into the Division of Statewide Integrated Water Management and the Division of Integrated Regional Water Management. The data was gathered using aerial photography and extensive field visits, the land use boundaries and attributes were digitized, and the resultant data went through standard quality control procedures. Land use polygons in agricultural areas were mapped in greater detail than areas of urban or native vegetation. Quality control procedures were performed jointly by staff at DWR’s DSIWM headquarters and Northern Region, under the supervision of Tito Cervantes. The finalized countywide land use vector data is in a single, polygon, shapefile format. This data was developed to aid DWR’s ongoing efforts to monitor land use for the main purpose of determining current and projected water uses. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standards version 2.1, dated March 9, 2016. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov. This data represents a land use survey of Shasta County conducted by DWR, Northern District Office staff(ND), currently known as Northern Region Office, under the leadership of Tito Cervantes, Senior Land and Water Use Supervisor. The field work for this survey was conducted during the summer of 2005. ND staff physically visited each delineated field, noting the crops grown at each location. Field survey boundary date was developed using: 1. Linework developed for DWR’s 1995 survey of Shasta County was used as the starting point for the digital field boundaries developed for this survey. Where needed, Northern Region staff made corrections to the field boundaries using the 1993 Digital Orthophoto Quarter Quadrangle (DOQQ) images. After field visits had been completed, 2005 National Agricultural Imagery Program (NAIP), one-meter resolution imagery from the U.S. Department of Agriculture’s Farm Services Agency was used to locate boundary changes that had occurred since the 1993 imagery was taken. Field boundaries for this survey follow the actual borders of fields, not road center lines. Line work for the Redding area was downloaded from the City of Redding website and modified to be compatible with DWR land use categories and linework. 2. For field data collection, digital images and land use boundaries were copied onto laptop computers. The staff took these laptops into the field and virtually all agricultural fields were visited to positively identify agricultural land uses. Site visits occurred from July through September 2005. Using a standardized process, land use codes were digitized directly into the laptop computers using ArcMap. For most areas of urban land use, attributes were based upon aerial photo interpretation rather than fieldwork. 3. The digital land use map was reviewed using the 2005 NAIP four-band imagery and 2005 Landsat 5 images to identify fields that may have been misidentified. The survey data was also reviewed by summarizing land use categories and checking the results for unusual attributes or acreages. 4. After quality control procedures were completed, the data was finalized by staff in both ND and Sacramento's DPLA. Important Points about Using this Data Set: 1. The land use boundaries were drawn on-screen using orthorectified imagery. They were drawn to depict observable areas of the same land use. They were not drawn to represent legal parcel (ownership) boundaries or meant to be used as parcel boundaries. 2. This survey was a "snapshot" in time. The indicated land use attributes of each delineated area (polygon) were based upon what the surveyor saw in the field at that time, and whatever additional information the aerial photography might provide. The DWR land use attribute structure allows for up to three crops per delineated area (polygon). In the cases where there were crops grown before the survey took place, the surveyor may or may not have been able to detect them from the field or the photographs. For crops planted after the survey date, the surveyor could not account for these crops. Thus, although the data is very accurate for that point in time, it may not be an accurate determination of what was grown in the fields for the whole year. If the area being surveyed does have double or multicropping systems, it is likely that there are more crops grown than could be surveyed with a "snapshot". 3. Double cropping and mixed land use must be taken into account when calculating the acreage of each crop or other land use mapped in this survey. A delineated field of 40 acres might have been cropped first with grain, then with corn, and coded as such. For double cropped fields, a “D” will be entered in the “MULTIUSE” field of the DBF file of the shapefile. To calculate the crop acreage for that field, 40 acres should be allocated to the grain category and then 40 acres should also be allocated to corn. For polygons mapped as “mixed land use”, an “M” will be entered in the “MULTIUSE” field. To calculate the appropriate acreages for each land use within this polygon, multiply the percent (as a decimal fraction) associated with each land use by the acres represented by the polygon. 4. All Land Use Codes are respresentative of the current 2016 Legend unless otherwise noted. Not all land use codes will be represented in the survey. The primary focus of this land use survey is mapping agricultural fields. Urban residences and other urban areas were delineated using aerial photo interpretation. Some urban areas may have been missed, especially in forested areas. Before final processing, standard quality control procedures were performed jointly by staff at DWR's Northern District, and at DPLA headquarters under the leadership of Jean Woods, Senior Land and Water Use Supervisor. After quality control procedures were completed, the data was finalized. The positional accuracy of the digital line work, which is based upon the 9' x 9' color photos, is approximately 23 meters. The land use attribute accuracy for agricultural fields is high, because almost every delineated field was visited by a surveyor. The accuracy is 95 percent because some errors may have occurred. Possible sources of attribute errors are: a) Human error in the identification of crop types, b) Data entry errors.

Every published digital survey is designated as either ‘Final’, or ‘Provisional’, depending upon its status in a peer review process. Final surveys are peer reviewed with extensive quality control methods to confirm that field attributes reflect the most detailed and specific land-use classification available, following the standard DWR Land Use Legendspecific to the survey year. Data sets are considered ‘final’ following the reconciliation of peer review comments and confirmation by the originating Regional Office. During final review, individual polygons are evaluated using a combination of aerial photointerpretation, satellite image multi-spectral data and time series analysis, comparison with other sources of land use data, and general knowledge of land use patterns at the local level.Provisionaldata sets have been reviewed for conformance with DWR’s published data record format, and for general agreement with other sources of land use trends. Comments based on peer review findings may not be reconciled, and no significant edits or changes are made to the original survey data.The 2006 Trinity County land use survey data was developed by the State of California, Department of Water Resources (DWR) through its Division of Integrated Regional Water Management (DIRWM) and Division of Statewide Integrated Water Management (DSIWM). Land use boundaries were digitized and land use data was gathered by staff of DWR’s Northern Region using extensive field visits and aerial photography. The land uses that were mapped were detailed agricultural land uses, and lesser detailed urban and native vegetation land uses. The land use data went through standard quality control procedures before final processing. Quality control procedures were performed jointly by staff at DWR’s DSIWM headquarters and Northern Region, under the supervision of Tito Cervantes, Senior Land and Water Use Scientist. This data was developed to aid DWR’s ongoing efforts to monitor land use for the main purpose of determining current and projected water uses. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standards version 2.1, dated March 9, 2016. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov. This data represents a land use survey of Trinity County conducted by the California Department of Water Resources, Northern Region Office staff. Data development: Trinity County was surveyed using the 2005 one-meter resolution National Agriculture Imagery Program (NAIP) digital aerial photos from the U.S. Department of Agriculture's Farm Services Agency as a base for line work. Digital 7.5’ quadrangle sized images were created from the 2005 NAIP imagery. In the spring of 2006, DWR's Northern Region staff digitized land use boundaries using AutoCAD Map software. The digital images and land use boundaries were copied onto laptop computers that were used as the field data collection tools. Staff visited all accessible fields to positively identify agricultural land uses. These site visits occurred between June and August 2006. Land use codes were digitized directly into the laptop computers in the field using AutoCAD Map (using a standardized digitizing process). Some staff took printed aerial photos into the field and wrote land use codes directly onto these photo field sheets. The data from the photo field sheets were digitized using AutoCAD Map back in the office. For both data gathering techniques, any land use boundary changes were noted and then corrected in the office. The primary focus of this land use survey is mapping agricultural fields. Urban residences and other urban areas were delineated using primarily aerial photo interpretation, so some urban areas may have been missed. In some rural residential areas, urban land use was delineated by drawing polygons to surround houses or other buildings along with a minimal area of land surrounding these structures. These footprint areas represent the locations of structures but do not represent the entire footprint of urban land. Sources of irrigation water were not mapped in this survey. The linework and attributes from each AutoCAD drawing file were brought into ArcInfo and both quadrangle and survey-wide coverages were created, and underwent quality checks. The coverages were converted to shapefiles using ArcView. After quality control procedures were completed on each file, the data was finalized. Before final processing, standard quality control procedures were performed jointly by staff at DWR's Northern District, and at DPLA headquarters under the leadership of Jean Woods, Senior Land and Water Use Supervisor. After quality control procedures were completed, the data was finalized. The positional accuracy of the digital line work, which is based upon the 2005 orthorectified NAIP imagery, is approximately 6 meters, but in some areas linework may be 10 meters from the actual location. The land use attribute accuracy for agricultural fields is high, because almost every delineated field was visited by a surveyor. The accuracy is 95 percent because some errors may have occurred. Possible sources of attribute errors are: a) Human error in the identification of crop types, b) Data entry errors.

December 6, 2023 (Final DWR Data) The 2018 Legislation required DWR to provide or otherwise identify data regarding the unique local conditions to support the calculation of an urban water use objective (CWC 10609. (b)(2) (C)). The urban water use objective (UWUO) is an estimate of aggregate efficient water use for the previous year based on adopted water use efficiency standards and local service area characteristics for that year. UWUO is calculated as the sum of efficient indoor residential water use, efficient outdoor residential water use, efficient outdoor irrigation of landscape areas with dedicated irrigation meter for Commercial, Industrial, and Institutional (CII) water use, efficient water losses, and an estimated water use in accordance with variances, as appropriate. Details of urban water use objective calculations can be obtained from DWR’s Recommendations for Guidelines and Methodologies document (Recommendations for Guidelines and Methodologies for Calculating Urban Water Use Objective - https://water.ca.gov/-/media/DWR-Website/Web-Pages/Programs/Water-Use-And-Efficiency/2018-Water-Conservation-Legislation/Performance-Measures/UWUO_GM_WUES-DWR-2021-01B_COMPLETE.pdf). The datasets provided in the links below enable urban retail water suppliers calculate efficient outdoor water uses (both residential and CII), agricultural variances, variances for significant uses of water for dust control for horse corals, and temporary provisions for water use for existing pools (as stated in Water Boards’ draft regulation). DWR will provide technical assistance for estimating the remaining UWUO components, as needed. Data for calculating outdoor water uses include: • Reference evapotranspiration (ETo) – ETo is evaporation plant and soil surface plus transpiration through the leaves of standardized grass surfaces over which weather stations stand. Standardization of the surfaces is required because evapotranspiration (ET) depends on combinations of several factors, making it impractical to take measurements under all sets of conditions. Plant factors, known as crop coefficients (Kc) or landscape coefficients (KL), are used to convert ETo to actual water use by specific crop/plant. The ETo data that DWR provides to urban retail water suppliers for urban water use objective calculation purposes is derived from the California Irrigation Management Information System (CIMIS) program (https://cimis.water.ca.gov/). CIMIS is a network of over 150 automated weather stations throughout the state that measure weather data that are used to estimate ETo. CIMIS also provides daily maps of ETo at 2-km grid using the Spatial CIMIS modeling approach that couples satellite data with point measurements. The ETo data provided below for each urban retail water supplier is an area weighted average value from the Spatial CIMIS ETo. • Effective precipitation (Peff) - Peff is the portion of total precipitation which becomes available for plant growth. Peff is affected by soil type, slope, land cover type, and intensity and duration of rainfall. DWR is using a soil water balance model, known as Cal-SIMETAW, to estimate daily Peff at 4-km grid and an area weighted average value is calculated at the service area level. Cal-SIMETAW is a model that was developed by UC Davis and DWR and it is widely used to quantify agricultural, and to some extent urban, water uses for the publication of DWR’s Water Plan Update. Peff from Cal-SIMETAW is capped at 25% of total precipitation to account for potential uncertainties in its estimation. Daily Peff at each grid point is aggregated to produce weighted average annual or seasonal Peff at the service area level. The total precipitation that Cal-SIMETAW uses to estimate Peff comes from the Parameter-elevation Relationships on Independent Slopes Model (PRISM), which is a climate mapping model developed by the PRISM Climate Group at Oregon State University. • Residential Landscape Area Measurement (LAM) – The 2018 Legislation required DWR to provide each urban retail water supplier with data regarding the area of residential irrigable lands in a manner that can reasonably be applied to the standards (CWC 10609.6.(b)). DWR delivered the LAM data to all retail water suppliers, and a tabular summary of selected data types will be provided here. The data summary that is provided in this file contains irrigable-irrigated (II), irrigable-not-irrigated (INI), and not irrigable (NI) irrigation status classes, as well as horse corral areas (HCL_area), agricultural areas (Ag_area), and pool areas (Pool_area) for all retail suppliers.

Division of Water Resources Non-Discharge Permits include the following permits: Wastewater Irrigation, Single-Family Residence Wastewater Irrigation, High-Rate Infiltration, Other Wastewater, Closed-Loop Recycle, Reclaimed Water, and Residual Management. Non-Discharge is the treatment of wastewater and disposal/reuse. Non-Discharge is NOT the discharge to surface waters of the state or utilize a sub-surface disposal system (i.e., septic system with leach field). This map includes permit locations, disposal field locations, and monitoring well locations.

Data Update Cycle: This data is pulled out of the Div. of Water Resources permit database and updated every Sunday at 2:00 am.

Contacts: Data Contact: Nathaniel Thornburg GIS Contact: Melanie Williams

NOTICE TO PROVISIONAL 2023 LAND USE DATA USERS: Please note that on December 6, 2024 the Department of Water Resources (DWR) published the Provisional 2023 Statewide Crop Mapping dataset. The link for the shapefile format of the data mistakenly linked to the wrong dataset. The link was updated with the appropriate data on January 27, 2025 and a notice was posted on the shapefile download site. If you downloaded the Provisional 2023 Statewide Crop Mapping dataset in shapefile format between December 6, 2024 and January 27, we encourage you to redownload the data. The Map Service and Geodatabase formats were correct as posted on December 06, 2024. Thank you for your interest in DWR land use datasets. The California Department of Water Resources (DWR) has been collecting land use data throughout the state and using it to develop agricultural water use estimates for statewide and regional planning purposes, including water use projections, water use efficiency evaluations, groundwater model developments, climate change mitigation and adaptations, and water transfers. These data are essential for regional analysis and decision making, which has become increasingly important as DWR and other state agencies seek to address resource management issues, regulatory compliances, environmental impacts, ecosystem services, urban and economic development, and other issues. Increased availability of digital satellite imagery, aerial photography, and new analytical tools make remote sensing-based land use surveys possible at a field scale that is comparable to that of DWR’s historical on the ground field surveys. Current technologies allow accurate large-scale crop and land use identifications to be performed at desired time increments and make possible more frequent and comprehensive statewide land use information. Responding to this need, DWR sought expertise and support for identifying crop types and other land uses and quantifying crop acreages statewide using remotely sensed imagery and associated analytical techniques. Currently, Statewide Crop Maps are available for the Water Years 2014, 2016, 2018- 2022 and PROVISIONALLY for 2023. Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer: https://gis.water.ca.gov/app/CADWRLandUseViewer. For Regional Land Use Surveys follow: https://data.cnra.ca.gov/dataset/region-land-use-surveys. For County Land Use Surveys follow: https://data.cnra.ca.gov/dataset/county-land-use-surveys. For a collection of ArcGIS Web Applications that provide information on the DWR Land Use Program and our data products in various formats, visit the DWR Land Use Gallery: https://storymaps.arcgis.com/collections/dd14ceff7d754e85ab9c7ec84fb8790a.