Flood Management

Harvest Sources

DEPRECATED: use https://doi.org/10.6073/pasta/8a9b1837df88a4bea716f5a35c76da0f (edi.2467.1) package instead. This package is deprecated because these data have been consolidated into edi.2467.1. Central Valley Chinook Salmon populations differ in their Endangered Species Act listing status. It is often difficult to distinguish individuals from the different Evolutionarily Significant Units. As such, many of the salmon monitoring and evaluation efforts in the Central Valley and San Francisco Bay-Delta are hampered by uncertainty about population (stock) identification and proportional effects of management actions (Dekar et al. 2013; IEP 2019). Studies have identified that the current identification method (length-at-date models) of juvenile Chinook salmon (Fisher 1992) captured in the watershed vary in their accuracy, particularly for spring-run (NMFS 2013; Harvey et al. 2014; Merz et al. 2014). The inaccuracy of the size-based methods is likely due to differences in fish distribution during early rearing, habitat-specific growth rates, and inter-annual variability in temperatures and food availability that lead to overlap in size ranges among stocks. The primary objective of this project was the genetic classification (to race; Evolutionary Significant Unit) of Chinook Salmon captured from State Water Project and Central Valley Project fish protection facilities and Interagency Ecological Program monitoring programs. The population-of-origin was determined for sampled fish by comparing their genotypes to reference genetic baselines. Genetic methods, having less statistical uncertainty that size-based models for population identification, were intended to directly target (and reduce) one source of uncertainty in the estimation of loss (take) from water diversions (operations) and develop the information necessary for understanding stock-specific distribution, habitat utilization, abundance, and life history variation. This project supports recommendations from the Interagency Ecological Program’s Salmon and Sturgeon Assessment of Indicators by Life Stage and Interagency Ecological Program Science Agenda efforts to improve Central Valley salmonid monitoring (Johnson et al. 2017; IEP 2019). None Literature Cited None Dekar, M., P. Brandes, J. Kirsch, L. Smith, J. Speegle, P. Cadrett and M. Marshall. 2013. USFWS Delta Juvenile Fish Monitoring Program Review. Background Document. Prepared for IEP Science Advisory Group, June 2013. US Fish and Wildlife Service, Stockton Fish and Wildlife Office, Lodi, CA. 224 p. Fisher, F.W. 1992. Chinook Salmon, Oncorhynchus tshawytscha, growth and occurrence in the Sacramento-San Joaquin River system. California Department of Fish and Game, Inland Fisheries Divisions, draft office report, Redding. Harvey, B.N., D.P. Jacobson, M.A. Banks. 2014. Quantifying the uncertainty of a juvenile Chinook Salmon Race Identification Methyod for a Mixed-Race Stock. North American Journal of Fisheries Management. IEP, Interagency Ecological Program. 2019. Interagency Ecological Program Science Strategy 2020-2024: Invenstment Priorities for Interagency Collaborative Science. Johnson, R.C., S. Windell, P. L. Brandes, J. L. Conrad, J. Ferguson, P. A. L. Goertler, B. N. Harvey, J.Heublein, J. A. Israel, D. W. Kratville, J. E. Kirsch, R. W. Perry, J. Pisciotto, W. R. Poytress, K. Reece, and B. G. Swart. 2017. Increasing the management value of life stage monitoring networks for three imperiled fishes in California's regulated rivers: case study Sacramento Winter-run Chinook salmon. San Francisco Estuary and Watershed Science 15: 1-41. National Marine Fisheries Service (NMFS). 2013. Endangered and Threatened Species: Designation of a Nonessential Experimental Population of Central Valley Spring-Run Chinook Salmon Below Friant Dam in the San Joaquin River, CA. Federal Register 70: 79622, December 31, 2013. ## About This Federated Record This CNRA Open Data Platform record is based on metadata federated from the Environmental Data Initiative (EDI) Data Portal. Its purpose is to improve the discoverability of the data package through the CNRA Open Data Platform. The EDI Data Portal is the repository of record for this data package. Metadata, resource links, and supporting information displayed here may not reflect the latest updates available in EDI. Resources shown here—including Full Metadata, Provenance, and Data Quality Report—are provided to help users understand and evaluate the data package and the supporting information available from EDI. For the current data package, citation, DOI, data files, metadata, provenance, data quality documentation, revision history, and other supporting information, refer to the EDI data package landing page: https://portal.edirepository.org/nis/metadataviewer?packageid=edi.1056.2&key=vqSpNwnbe91Bi8trB5RY25CoPD4 Access requirements, permissions, and authorization policies for resources hosted by EDI are established and managed independently of the CNRA Open Data Platform.

Updated Oct 7, 2026

Harvest Sources

DEPRECATED: use https://doi.org/10.6073/pasta/8a9b1837df88a4bea716f5a35c76da0f (edi.2467.1) package instead. This package is deprecated because these data have been consolidated into edi.2467.1. Central Valley Chinook Salmon populations differ in their Endangered Species Act listing status. It is often difficult to distinguish individuals from the different Evolutionarily Significant Units. As such, many of the salmon monitoring and evaluation efforts in the Central Valley and San Francisco Bay-Delta are hampered by uncertainty about population (stock) identification and proportional effects of management actions (Dekar et al. 2013; IEP 2019). Studies have identified that the current identification method (length-at-date models) of juvenile Chinook salmon (Fisher 1992) captured in the watershed vary in their accuracy, particularly for spring-run (NMFS 2013; Harvey et al. 2014; Merz et al. 2014). The inaccuracy of the size-based methods is likely due to differences in fish distribution during early rearing, habitat-specific growth rates, and inter-annual variability in temperatures and food availability that lead to overlap in size ranges among stocks. The primary objective of this project was the genetic classification (to race; Evolutionary Significant Unit) of Chinook Salmon captured from State Water Project and Central Valley Project fish protection facilities and Interagency Ecological Program monitoring programs. The population-of-origin was determined for sampled fish by comparing their genotypes to reference genetic baselines. Genetic methods, having less statistical uncertainty that size-based models for population identification, were intended to directly target (and reduce) one source of uncertainty in the estimation of loss (take) from water diversions (operations) and develop the information necessary for understanding stock-specific distribution, habitat utilization, abundance, and life history variation. This project supports recommendations from the Interagency Ecological Program’s Salmon and Sturgeon Assessment of Indicators by Life Stage and Interagency Ecological Program Science Agenda efforts to improve Central Valley salmonid monitoring (Johnson et al. 2017; IEP 2019). None Literature Cited None Dekar, M., P. Brandes, J. Kirsch, L. Smith, J. Speegle, P. Cadrett and M. Marshall. 2013. USFWS Delta Juvenile Fish Monitoring Program Review. Background Document. Prepared for IEP Science Advisory Group, June 2013. US Fish and Wildlife Service, Stockton Fish and Wildlife Office, Lodi, CA. 224 p. Fisher, F.W. 1992. Chinook Salmon, Oncorhynchus tshawytscha, growth and occurrence in the Sacramento-San Joaquin River system. California Department of Fish and Game, Inland Fisheries Divisions, draft office report, Redding. Harvey, B.N., D.P. Jacobson, M.A. Banks. 2014. Quantifying the uncertainty of a juvenile Chinook Salmon Race Identification Methyod for a Mixed-Race Stock. North American Journal of Fisheries Management. IEP, Interagency Ecological Program. 2019. Interagency Ecological Program Science Strategy 2020-2024: Invenstment Priorities for Interagency Collaborative Science. Johnson, R.C., S. Windell, P. L. Brandes, J. L. Conrad, J. Ferguson, P. A. L. Goertler, B. N. Harvey, J.Heublein, J. A. Israel, D. W. Kratville, J. E. Kirsch, R. W. Perry, J. Pisciotto, W. R. Poytress, K. Reece, and B. G. Swart. 2017. Increasing the management value of life stage monitoring networks for three imperiled fishes in California's regulated rivers: case study Sacramento Winter-run Chinook salmon. San Francisco Estuary and Watershed Science 15: 1-41. National Marine Fisheries Service (NMFS). 2013. Endangered and Threatened Species: Designation of a Nonessential Experimental Population of Central Valley Spring-Run Chinook Salmon Below Friant Dam in the San Joaquin River, CA. Federal Register 70: 79622, December 31, 2013. ## About This Federated Record This CNRA Open Data Platform record is based on metadata federated from the Environmental Data Initiative (EDI) Data Portal. Its purpose is to improve the discoverability of the data package through the CNRA Open Data Platform. The EDI Data Portal is the repository of record for this data package. Metadata, resource links, and supporting information displayed here may not reflect the latest updates available in EDI. Resources shown here—including Full Metadata, Provenance, and Data Quality Report—are provided to help users understand and evaluate the data package and the supporting information available from EDI. For the current data package, citation, DOI, data files, metadata, provenance, data quality documentation, revision history, and other supporting information, refer to the EDI data package landing page: https://portal.edirepository.org/nis/metadataviewer?packageid=edi.1839.2&key=vqSpNwnbe91Bi8trB5RY25CoPD4 Access requirements, permissions, and authorization policies for resources hosted by EDI are established and managed independently of the CNRA Open Data Platform.

Updated Oct 7, 2026

California State Water Resources Control Board

This list includes detail information about every Point of Diversion water rights record in the State Water Resources Control Board's "Electronic Water Rights Information Management System" (EWRIMS) database. A Point of Diversion is the geographic area from which water is diverted using infrastructure (works) and put to beneficial use. Examples of works include water storage dams, diversion dams, dugouts, and pump sites along a surface water source. Each row correspond with a unique Point of Diversion ID and its associated data. The list include basic summary information about the Water Right record, such as the type and status, the location of the Points of Diversion, the amount of water allowed (Face Value), and summary data associated with the electronic Water Right record. This file is in flat file format and may not include all information associated to a water right such all uses and seasons or the amounts reported used for every month. That information may be available in the associated flat files for each category.

Updated Sep 29, 2026

Harvest Sources

Descriptions Excel Application Tool for Statewide Agricultural Water Use Data 2016 - 2020 Department of water resources, Water Use Efficiency Branch, Water Use Unit program, has developed an Excel application tool, which calculates annual estimates of irrigated crop area (ICA), crop evapotranspiration (ETc), effective precipitation (Ep), evapotranspiration of applied water (ETaw), consumed fraction (CF), and applied water (AW) for 20 crop categories by combinations of detailed analysis unit and county (DAUCo) over California. The 2016 – 2020 statewide agricultural water use data were developed by all 4 DWR’s Regional Offices (Northern Region Office, North Central Region Office, South Central Region Office, and Southern Region Office) using Cal_simetaw model for updating the information in the California Water Plan Updates-2023. Therefore, this current Excel application tool just covers agricultural water use data from the period of 2016 - 2020 water years. It should also be mentioned that there are 3 other similar Excel applications that cover 1998 - 2005 and 2006 – 2010, & 2011 - 2015 agricultural water use data for the California Water plan Updates 2005/2009, 2013, and 2018 respectively. Outputs data provided from this Excel application include ICA in acres, EP, both in unit values (Acre feet per acre) & volume (acre feet), ETc both in unit values (acre feet per acre), & volume (acre feet), ETaw, both in unit value (acre feet per acre), & volume (acre feet), AW, both in unit value (acre feet per acre) & volume (acre feet), CF (in percentage %) for WYs 2016 – 2020 at Detailed Analysis Unit by County (DAUCO), Detailed Analysis Unit (DAU), County, Planning Area (PA), Hydrological Region (HR), and Statewide spatial scales using the dropdown menu. Furthermore, throughout the whole process numerous computations and aggregation equations in various worksheets are included in this Excel application. And for obvious reasons all worksheets in this Excel application are hidden and password protected. So, accidentally they won’t be tampered with or changed/revised. Following are definitions of terminology and listing of 20 crop categories used in this Excel application. 1. Study Area Maps The California Department of Water Resources (DWR) subdivided California into study areas for planning purposes. The largest study areas are the ten hydrologic regions (HR), The next level of delineation is the planning area (PAS), which are composed of multiple detailed analysis units (DAU). The DAUs are often split by county boundaries, so the smallest study areas used by DWR is DAU/County. Many planning studies begin at the Dau or PA level, and the results are aggregated into hydrologic regions for presentation. 2. Irrigated Crop Area (ICA) in acres The total amount of land irrigated for the purpose of growing a crop (includes multi-cropping acres) 3- Multi-cropping (MC) in acres A section of land that has more than one crop grown on it in a year, this included one crop being planted more than once in a season in the same field. Please note that there are no double cropping acreages for 2017. Because on a normal year when Regional Offices (RO) receive data from Land IQ, they were able to provide double cropping acreages. Since the 2017 land use data was derived from average crop acres between water years 2016 and 2018,2019, & 2020, they lost spatial and temporal data necessary to calculate double cropping. 4. Evapotranspiration (ET) Combination of soil evaporation and transpiration is referred to as evapotranspiration or ET. The rate of evapotranspiration from the plant-soil environment is primarily dependent on the energy available from solar radiation but is also dependent on relative humidity, temperature, cloud cover, and wind speed. It is an indication for how much your crops, lawn, garden, and trees need for healthy growth and productivity. 5. Reference Evapotranspiration (ETo) Reference evapotranspiration (ETo) is an estimate of the evapotranspiration of a 10-15 cm tall cool season grass and not lacking for water. The daily Standardized Reference Evapotranspiration for short canopies is calculated using the Penman-Monteith (PM) equation (Monteith, 1965) as presented in the United Nations FAO Irrigation and Drainage Paper (FAO 56) by Allen et al. (1988). 6. Penman-Monteith Equation (PM) Equation is used to estimate ETo when daily solar radiation, maximum and minimum air temperature, dew point temperature, and wind speed data are available. It is recommended by both the America Society of Civil Engineers and United Nations FAO for estimating ETo. 7. Crop Evapotranspiration (ETc), both in unit value (acre feet per acre), & volume (acre feet) Commonly known as potential evapotranspiration, which is the amount of water used by plants in transpiration and evaporation of water from adjacent plants and soil surfaces during a specific time period. ETc is computed as the product of reference evapotranspiration (ETo) and a crop coefficient (Kc) value, i.e., ETc = ETo x Kc. One Acre foot equals about 325851 gallons, or enough water to cover an acre of land about the size of a football field, one foot deep. 8. Crop Coefficient (Kc) Relates ET of a given crop at a specific time in its growth stage to a reference ET. Incorporates effects of crop growth state, crop density, and other cultural factors affecting ET. The reference condition has been termed "potential" and relates to grass. The main sources of Kc information are the FAO 24 (Doorenbos and Pruitt 1977) and FAO 56 (Allen et al. 1988) papers on evapotranspiration. 9. Effective Precipitation (Ep), both in unit value (acre feet per acre), & volume (acre feet) Fraction of rainfall effectively used by a crop, rather than mobilized as runoff or deep percolation 10. Evapotranspiration of Applied Water (ETaw), both in unit value (acre feet per acre), & volume (acre feet) Net amount of irrigation water needed to produce a crop (not including irrigation application efficiency). Soil characteristic data and crop information with precipitation and ETc data are used to generate hypothetical water balance irrigation schedules to determine ETaw. 11. Applied Water (AW), both in unit value (acre feet per acre), & volume (acre feet) Estimated as the ETaw divided by the mean seasonal irrigation system application efficiency. 12. Consumed Fraction (CF) in percentage (%) An estimate of how irrigation water is efficiently applied on fields to meet crop water, frost protection, and leaching requirements for a whole season or full year. 13. Crop category numbers and descriptions Crop Category Crop category description. 1 Grain (wheat, wheat_winter, wheat_spring, barley, oats, misc._grain & hay) 2 Rice (rice, rice_wild, rice_flooded, rice-upland) 3 Cotton 4 Sugar beet (sugar-beet, sugar_beet_late, sugar_beet_early) 5 Corn 6 Dry beans 7 Safflower 8 Other field crops (flax, hops, grain_sorghum, sudan,castor-beans, misc._field, sunflower, sorghum/sudan_hybrid, millet, sugarcane 9 Alfalfa (alfalfa, alfalfa_mixtures, alfalfa_cut, alfalfa_annual) 10 Pasture (pasture, clover, pasture_mixed, pasture_native, misc._grasses, turf_farm, pasture_bermuda, pasture_rye, klein_grass, pasture_fescue) 11 Tomato processing (tomato_processing, tomato_processing_drip, tomato_processing_sfc) 12 Tomato fresh (tomato_fresh, tomato_fresh_drip, tomato_fresh_sfc) 13 Cucurbits (cucurbits, melons, squash, cucumbers, cucumbers_fresh_market, cucumbers_machine-harvest, watermelon) 14 Onion & garlic (onion & garlic, onions, onions_dry, onions_green, garlic) 15 Potatoes (potatoes, potatoes_sweet) 16 Truck_Crops_misc (artichokes, truck_crops, asparagus, beans_green, carrots, celery, lettuce, peas, spinach, bus h_berries, strawberries, peppers, broccoli, cabbage, cauliflower) 17 Almond & pistachios 18 Other Deciduous (apples, apricots, walnuts, cherries, peaches, nectarines, pears, plums, prunes, figs, kiwis) 19 Citrus & subtropical (grapefruit, lemons, oranges, dates, avocados, olives, jojoba) 20 Vineyards (grape_table, grape_raisin, grape_wine)

Updated Oct 7, 2026

Harvest Sources

The USGS National Hydrography Dataset (NHD) downloadable data collection from The National Map (TNM) is a comprehensive set of digital spatial data that encodes information about naturally occurring and constructed bodies of surface water (lakes, ponds, and reservoirs), paths through which water flows (canals, ditches, streams, and rivers), and related entities such as point features (springs, wells, stream gages, and dams). The information encoded about these features includes classification and other characteristics, delineation, geographic name, position and related measures, a "reach code" through which other information can be related to the NHD, and the direction of water flow. The network of reach codes delineating water and transported material flow allows users to trace movement in upstream and downstream directions. In addition to this geographic information, the dataset contains metadata that supports the exchange of future updates and improvements to the data. The NHD supports many applications, such as making maps, geocoding observations, flow modeling, data maintenance, and stewardship. For additional information on NHD, go to https://www.usgs.gov/core-science-systems/ngp/national-hydrography. DWR was the steward for NHD and Watershed Boundary Dataset (WBD) in California. We worked with other organizations to edit and improve NHD and WBD, using the business rules for California. California's NHD improvements were sent to USGS for incorporation into the national database. The most up-to-date products are accessible from the USGS website. Please note that the California portion of the National Hydrography Dataset is appropriate for use at the 1:24,000 scale. For additional derivative products and resources, including the major features in geopackage format, please go to this page: https://data.cnra.ca.gov/dataset/nhd-major-features Archives of previous statewide extracts of the NHD going back to 2018 may be found at https://data.cnra.ca.gov/dataset/nhd-archive. In September 2022, USGS officially notified DWR that the NHD would become static as USGS resources will be devoted to the transition to the new 3D Hydrography Program (3DHP). 3DHP will consist of LiDAR-derived hydrography at a higher resolution than NHD. Upon completion, 3DHP data will be easier to maintain, based on a modern data model and architecture, and better meet the requirements of users that were documented in the Hydrography Requirements and Benefits Study (2016). The initial releases of 3DHP include NHD vector data incorporated into the 3DHP data model. As new elevation-derived hydrography is created for California, that geometry will replace the legacy NHD vectors in the 3DHP dataset. It will take several years for the 3DHP to be built out for California. Please refer to the resources on this page for more information. The FINAL, STATIC version of the National Hydrography Dataset for California was published for download by USGS on December 27, 2023. This dataset can no longer be edited by the state stewards. The current generation of national hydrography data is the USGS 3D Hydrography Program (3DHP). USGS maintains a 3DHP feature service which is updated quarterly, and provides a downloadable dataset that will updated once per year. Questions about the California stewardship of these datasets may be directed to nhd_stewardship@water.ca.gov.

Updated Oct 7, 2026