Surface water supply allocation, crop, and disadvantaged community data for the San Joaquin Valley, CA, 2016

Societies globally are struggling to meet freshwater demands while agencies attempt to address water access inequities under a rapidly changing climate and growing population. An understanding of dynamic interactions between people and water, known as sociohydrology, regionally could provide approaches to addressing local water mismanagement and water access inequity. In semi-arid California, local water agencies, primarily agricultural irrigation districts, are at the intersection of rethinking approaches to balance freshwater demands. More than 150 years of complex water governance and management have defined San Joaquin Valley irrigation districts and the region's water access inequities and sociohydrologic instability.

Data in this dataset supported analysis of water governance, specifically including surface water and groundwater dependence within and outside of irrigation districts. Additional data includes disadvantaged community designation, allowing for assessment of inequities between water users and the relationship to broader societal inequities.

Methods
Data Availability & Software

This study brings together detailed data from different local and state sources about irrigation districts. It uses this data to figure out the factors (e.g., the district's history, politics, environment, and cultural characteristics) that influence the shortage of surface water and the dependence on groundwater in this agricultural area. Table 1 lists datasets and sources. The data sources table in the README describes variables calculated from the datasets highlighted in Table 1. The major variables used in this analysis show an irrigation district’s history (i.e., age, dedicated water amount), surface water allocation and delivery, and crop composition within the district’s boundaries (e.g., total crop fraction, perennial crop fraction, annual crop fraction, and revenue). This dataset has the following tables as separate CSV files:

Table 7 includes the variable values per irrigation district (freshwater variable normalized values reported)
Table 8 includes the surface water allocation amounts for irrigation districts in this study and the source of information
Table 9 specifies the Land IQ crop types that make up the annual, perennial, and irrigated forage categories
Table 10 lists the crop revenue values and the associated crop type used in the analysis for irrigation districts within the eight San Joaquin Valley counties.

The 2016 county crop report for each county is used to derive crop revenue values. The primary software used to facilitate this analysis is Esri ArcGIS Pro 2.7.1 and R software (R Core Team, 2021).

Irrigation District Boundaries 

The most up-to-date irrigation district boundaries were obtained directly from the Local Agency Formation Commission (LAFCO) for seven counties in the San Joaquin Valley—San Joaquin, Stanislaus, Merced, Fresno, Madera, Tulare, and Kern. Kings County LAFCO could not provide updated boundaries, and the Department of Water Resources 2015 water agency boundaries were used for irrigation districts in this county. This study focuses solely on water agencies in the San Joaquin Valley floor that distribute water for irrigation and exclude water conservation, domestic, and municipal water agencies. The irrigation district boundaries from these various sources were combined to create a single geospatial data file of irrigation districts in the San Joaquin Valley using ArcGIS software.

Era Analysis
Statistical analysis of the variables is done for irrigation districts within four major historical eras to shed light on how key water management events may have shaped irrigation districts over their formation. Irrigation district formation dates were categorized into major water management historical eras for infrastructure investments and economic development as outlined by Hanak et al. (2011). The four major eras considered are the Era of Local Organization (1887-1913), Hydraulic Era (1914-1968), Era of Conflict (1969-2000), and Era of Reconciliation (2001-2020), mainly following Hanak et al. (2011).

Groundwater Reliance Calculation

Groundwater use in the San Joaquin Valley has been measured by irrigation districts and estimates have relied mostly on crop use estimated modeling studies for decades (Famiglietti, 2014). Hence, resolving disaggregated data and understanding of groundwater use across the region will be improved through the implementation of SGMA. Key datasets used to quantify the estimates of groundwater reliance per irrigation district in this study were:

The 2016 crop land use data for California (often called Land IQ 2016)

electronic Water Rights Information Management System (eWRIMS) (State Water Resources Control Board, 2020) - archive link

U.S. Bureau of Reclamation agricultural contractors list
A gridded-based water balance model called Water Footprint Analysis in R (WAFR)  (Booth, 2018) that uses crop coefficients to estimate crop water requirements.

The Land IQ 2016 dataset includes primary agricultural land use, wetlands, and urban boundaries for 58 counties in California derived for 2016. This study uses only agricultural land use classifications from the Land IQ 2016 dataset to calculate crop composition within irrigation district boundaries. Crop composition within irrigation districts also served as an input to the WAFR model to calculate crop water requirements for each district. Surface water allocation amounts were obtained from various sources— including eWRIMS, USBR agricultural contract amount lists and reports, Groundwater Sustainability Plans (GSP), Agricultural Water Management Plans (AWMP), and irrigation district web pages. Surface water delivery averages from 2001-2015 were obtained from (Jezdimirovic, Hanak, & Escriva-bou, 2020 - archive link) except for Banta Carbona Irrigation Districts, Byron-Bethany Irrigation District, and South San Joaquin Irrigation District. Average 2008-2019 surface water deliveries 2008-2019 for Banta-Carbona and Byron-Bethany irrigation districts were obtained from Tracy Subbasin GSP and South San Joaquin Irrigation District 2005-2019 average surface water deliveries were obtained from their 2020 AWMP.

The water budget equation (Eqn. 1) is used to derive estimates of groundwater reliance per irrigation district, meaning the amount of groundwater needed to make up for irrigation demand unmet by surface water, defined as:

∆S+ P+QGW+ QSW-ET=0 (Eqn.1)

Where ΔS is the change in water storage, P is precipitation, QGW is groundwater outflow, QSW is surface water runoff, and ET is evapotranspiration. For this project, a series of assumptions were made to quantify the reliance on groundwater for    each irrigation district in the San Joaquin Valley using the water budget equation, these are:

Precipitation, P, varies by irrigation district. Precipitation observations from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) were used in the WAFR model to obtain the proportion of crop water requirements for irrigation districts. For more information on the data processing and WAFR model, refer to Booth (2018).
QSW varies across irrigation districts, and values are based on surface water allocations determined by each irrigation district’s surface water right amount. This study assumes that irrigation districts have 100% allocation of their claimed water rights to meet irrigation demands (i.e., crop water requirements) to simulate a districts groundwater dependence and crop water demand during drought with full surface water capacity. Refer to SI Table 1 for more details on surface water allocation sources.
Given that most groundwater basins in the San Joaquin Valley have been designated as critically overdrafted by the Department of Water Resources, the likelihood is that the volume of groundwater outflow, QGW is sufficiently substantial and included in the water budget is speculative. Although shallow groundwater drainage and water quality is a management concern, there has been a decline over time and limited discharge and water quality in delta. Therefore, the total volume of water from lateral exchange is not substantial in volume, but it is recognized that it could affect water quality (Schoups et al., 2005).
Crop water requirements (CWR) were calculated by accumulating daily crop evapotranspiration demand during the growing season within a given location and using a crop coefficient of evapotranspiration, ETc. For more information on the data processing and WAFR model, refer to Booth (2018).

This analysis quantifies irrigation district groundwater runoff, QGW, based on surface water allocation amounts (Eqn. 2) and average surface water delivery for irrigation districts (Eqn. 3).

SWallocation - CWR = ± SW (Eqn. 2) and

SWdelivery - CWR = ± SW (Eqn. 3),

SWallocation is an irrigation district’s surface water allocation, SWdelivery is an irrigation district’s surface water delivery, and CWR is an irrigation district’s crop water requirement. If Equation 2 or 3 results in surface water surplus, SWS, then it is assumed that an irrigation district is not reliant on groundwater to meet irrigation demands or CWR. Whereas, if Equation 2 or 3 results in surface water deficit, SWD, it is assumed that an irrigation district does not have enough surface water allocations or average surface water deliveries to meet irrigation demands and relies on groundwater to meet CWR amounts. Irrigation districts with surface water delivery of “no record” are assumed to receive no surface water delivery to facilitate calculating the surface water delivery surplus/deficit. 

Irrigation District and GDC Disadvantaged Community Comparison

The CalEnviroScreen 4.0 dataset (archive link) is obtained for the most recent environmental health hazard assessment (2018) from the California Office of Environmental Health Hazard Assessment (OEHHA) (California Office of Environmental Health Hazard Assessment, 2018), and the most up to date (2018) DAC census places boundaries were obtained from the Department of Water Resources (DWR) DAC Mapping Tool California Department of Water Resources, 2018). The CalEnviroScreen 4.0 dataset provides several indicators that reflect environmental conditions or poverty vulnerability for populations at the census tract level. The DAC census place boundaries provide the area, name, and location of DACs in California, reduced to the San Joaquin Valley floor (See shaded grey area in map, below) for this analysis. To assess environmental and poverty conditions in San Joaquin Valley's DACs, we combined the CalEnviroScreen 4.0 dataset with DAC census place centroids using Esri ArcGIS Pro software. We also used irrigation district boundaries to identify Groundwater Dependent Communities (GDCs) on the valley floor, which are areas not served by irrigation districts and are highly dependent on groundwater to meet domestic water needs. Descriptive statistics (e.g., mean, median) were used to compare the traits between DACS with GDCs and irrigation districts, and an unpaired two-sample Wilcoxon test comparing the mean of the variables between the two groups is used to derive the p-value (α=0.05).