Report: Impact of the Drought in the San Joaquin Valley of California

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Impact of the Drought in the San Joaquin Valley of California

A Study Funded by Wells Fargo Foundation California State University, Fresno July 2015

Overgrown Boat Ramp Lake Success: Sierra Reservoir, Eastern San Joaquin Valley Wildflowers grow where water should be. A recent rain has greened the hillsides and the lakebed but has done little to reverse the dwindling water level. The boat ramp is a full 100 yards shy of the current water level. Geographic Area: Town of Porterville which has run out of water. Photograph: Neil Chowdhury Principal Investigator

Dr. Lynnette Zelezny, Provost

Co-Principal Investigator, Project Director

Dr. Xuanning Fu, Associate Dean of College of Social Sciences

Editor

Dr. Gillisann Harootunian, Director, University Initiatives

Co-Project Director

David Drexler, Henry Madden Library

Faculty/Staff Researchers

Dr. Antonio Avalos, Department of Economics

Neil Chowdhury, MFA, Department of Art and Design

Dr. Fayzul Pasha, Department of Civil and Geomatics Engineering

Dr. Samendra Sherchan, Department of Public Health

Jes Therkelsen, MFA, Department of Mass Communication and Journalism

Dr. Chih-Hao Wang, Department of Geography and City and Regional Planning

Dr. David Zoldoske, California Water Institute

Sargeant Green, California Water Institute

Photographer

Cary Edmondson, University Communications Department

Table of Contents

Introduction …………………………………………………………………………..... i

1. Severity of the Drought and its Impact on Agriculture and Use of Energy ……... 1 Editorial Snapshot: Is There a “Central” Valley? ……………………………... 53 Photo Spread: The Vineyard ………………………………………………….... 54

Video Vignette: Switching to Almonds: Drought Impact on Farming and People ……………………………………………………………………... 57

2. The Economic Impact of the Drought in the California San Joaquin Valley …...58 Editorial Snapshots: Who Are They?: Moving from Economic Impact to Human Impact ….. 72 The Shadow Economy: How to Document the Un-Documented? ….…. 73 Food Insecurity in the San Joaquin Valley, with a video vignette …...… 74 Sharing the Bounty: Fresno State Food Insecurity Project

3. Water Usage and Residential Water Consumption in the California San Joaquin Valley …………………………………………………..………...….. 75 Intra-Chapter Snapshot: A Census-Designated Place: A Glimpse into One Disadvantaged Community ………………………………………….… 89

4. Public Health Implications of Drought ...... ……. 90 Editorial Snapshots: The Health Drought ……………………………………………..……. 112 From Economic Distress to Psychological Distress …………..……… 113 Map: San Joaquin Valley: Environmental Justice Areas ……………..………. 114

Video Vignette: East Porterville: Drought Impact on one Disadvantaged Community ………………………………………………………………..…. 115

Conclusion and Recommendations ………………………………………………… 116

References ……………………………………………………………………….….. 121

Appendices Appendix 1 Maps …………………………………………………………….…….… 129 Appendix 2 Annotated bibliography …………………………………………….…… 134 Appendix 3 Stakeholder organizations, with contact information ……………….….. 145 Appendix 4 Data Sources (URL links) ……………………………………………..… 151

INTRODUCTION

For the past three years (2012–2014), California has experienced the most severe drought conditions in its recorded history. When examined by using two paleoclimate reconstructions of drought and precipitation for Central and Southern California to place this current event in the context of the last millennium, the current drought was determined to be the most severe in the last 1,200 years, with 2014 moisture deficits worse than any previous continuous span of dry years (Griffin & Anchukaitis, 2014).

The rainy season of 2014–15 has resulted in disappointment for the fourth straight year: the drought has deepened. The Sierra Nevada snowpack is only 5% of average, one-fifth the size of the smallest ever recorded, prompting Governor Jerry Brown to announce the state’s first mandatory water reductions, aiming at cutting water use by 25%. Brown promised more enforcement in cities and actions against water agencies in groundwater-depleted areas that have not shared data with the state (Grossi, 2015).

Historically, the state of California has faced many droughts, and several studies have been completed to assess the impacts on different sectors. These studies have considered the entire state, and not focused on the San Joaquin Valley, the center of agriculture in the state. The impact of late 1980s drought in California on the societal and environmental costs was assessed by Gleick and Nash (1991). The Institute for Water Resources (IWR) of the U.S. Army Corps of Engineers also published a report on the 1987–1992 drought, focusing on all of California. The lessons that were learned from this study were published in Dziegielewski, Garbharran & Langowski, 1993. The Pacific Institute published a report on the drought from 2007 to 2009. The report analyzed the impacts on California’s economy and environment (Christian-Smith, Levy, & Gleick, 2011). Recently the Center for Watershed Science, University of California Davis (UC Davis) published “Economic Analysis of the 2014 Drought on for California Agriculture,” a report focusing on the current drought’s impact on the state’s agriculture (Howitt, Medellín- Azuara, MacEwan, Lund, & Sumner, 2014). This was followed on May 31, 2015 by “Preliminary Analysis: 2015 Drought Economic Impact Study.” Also issued was the “Preliminary 2014 Drought Economic Impact Estimates in Central Valley Agriculture” (Howitt, Medellín-Azuara, MacEwan, & Lund, 2014) which studied all 25 counties of the Central Valley. None of the reports focused on the San Joaquin Valley’s agriculture, an industry of significance.

The story of the San Joaquin Valley has largely gone untold, being included as one chapter within the history of the State of California. The drought has changed that, with the story of the San Joaquin Valley, complete with interactive maps and high tech reader resources, published almost weekly in the New York Times and other major media. The San Joaquin Valley has become the focus of a national conversation. To better understand the impact of drought on the San Joaquin Valley, and so to inform the national conversation, Fresno State conducted a drought impact study in spring 2015, funded by the Wells Fargo Foundation.

The study was conducted by a selected team of faculty and staff at Fresno State, focused on the goal of delivering usable information for public officials, private officials, and the general public, on the range of impacts (economic, public health, municipal) resulting from the drought.

i Chapter 1 Severity of the Drought and its Impact on Agriculture and Use of Energy

Dr. Fayzul Pasha, Department of Civil and Geomatics Engineering

Abstract

The San Joaquin Valley of California is historically known for its agricultural production and ranks as one of the highest agricultural producers in the world. It produces a wide variety of crops, livestock, and poultry. Agriculture contributes significantly towards the economy of the San Joaquin Valley (SJV). Adverse events in agriculture will result in multiple adverse effects in the region’s economy, which can impact employment, population migration, and wage levels and food prices which the most vulnerable residents can experience in the most direct and harshest manner. For this reason, this study of the drought’s impact on agriculture and use of energy sets the stage for this report.

Although there are numerous studies conducted on the economic impacts of the historical droughts in California, there are a limited number of studies to assess the economic impact focusing on the SJV. This study focuses on a key economic impact of the recent drought on the SJV, specifically the impact on energy usage and agricultural revenue, in its eight counties (Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare).

Agriculture consumes a huge amount of water and energy. The availability of surface water, which is directly affected by the amount of precipitation, is decreasing as a result of the lower precipitation in recent years. A year that has the mean annual precipitation much lower than the historical mean precipitation can be defined as a drought year. With this definition, a tremendous drought has been affecting the SJV in recent years starting in 2012. This drought is not only lowering the surface water availability but also affecting the groundwater depth, as there is not enough surface water to recharge the groundwater basins. SJV agriculture is heavily dependent on groundwater which needs to be pumped from a significant depth, causing high energy consumption. It is therefore expected that the drought has a significant impact on energy consumption.

By examining the historical trends related to precipitation, streamflow, reservoir water storage, irrigation water use, and groundwater depth, the impact of the drought was assessed. Agriculture, water, and energy usage are highly correlated. As noted, energy consumption increases from heavier pumping as a result of lower groundwater levels, lower streamflow, and lower water levels in lakes and reservoirs due to the drought. Therefore, this study is structured as follows:

1. Examining the impacts of drought on surface water availability including streamflow and water storage in lakes and reservoirs and groundwater storage. 2. Examining the impacts of the above decreased surface water availability and groundwater storage on agriculture and energy consumption.

1 3. Assessing the final impact of increased energy consumption on agricultural revenue.

Different statistical analysis including the correlation and regression analysis and geospatial processing have been used to conduct this study.

Analysis shows that the last few years’ mean annual precipitations in all eight counties are about 30–60% lower than the historical means. This lower precipitation has a tremendous impact on surface water availability in terms of streamflow and reservoir storage. Data from a total of twenty (20) stream gauge locations has been analyzed, and it is found that streamflow at all of these locations throughout the study area is significantly lower than the historical average. Similarly to precipitation, the streamflow is about 30–60% lower than the historical average. The historical reservoir storage data for the 10 largest reservoirs in the study area was analyzed. It is found that in recent years, the reservoir levels are significantly lower than the historical average storage. If future years’ precipitations are as low as 2014, the impact on reservoir storage will be severe, ranging from 0.003 million acre-feet in Courtright Reservoir to 1.02 million acre-feet in San Luis Reservoir in the month of February.

The impact of groundwater depth has been predicted considering precipitation amounts ranging from 2 inches to 5 inches. If the drought continues, the groundwater depletion rate will be higher. The higher depletion rate will cause additional change in the groundwater depth. If annual precipitation is as low as 4 inches, the groundwater depths in each county will be lowered by about 9.1 (Fresno), 21.5 (Kern), 13.9 (Kings), 15.1 (Madera), 5.5 (Merced), 8.3 (San Joaquin), 6.8 (Stanislaus), and 14.7 (Tulare) more feet per year than the historical rate of groundwater change in each county. The additional groundwater depth will consume additional energy.2 Considering the Tulare basin low energy consumption estimate, this study found that if rainfall in a given year is 4 inches, the additional energy requirement will be approximately 147,765 (Fresno), 51,013 (Kern), 60,722 (Kings), 27,616 (Madera), 71,661 (Merced), 60,735 (San Joaquin), 70,072 (Stanislaus), and 133,877 (Tulare) megawatt-hours.

The impact on irrigation water usage has also been assessed, also using rainfall in a given year at 4 inches. Considering both surface and groundwater usage for irrigation, the total shortages in millions gallons per day (mgd) may be approximately 1,337 (Fresno), 130 (Kern), 123 (Kings), 526 (Madera), 206 (Merced), 768 (San Joaquin), 370 (Stanislaus), and 377 (Tulare).

Accordingly, the yearly revenues from agricultural productions in these counties will suffer. For the annual precipitation of 4 inches in a given year, the reduction in agricultural revenue in billion dollars will be 0.676 (Fresno), 0.358 (Kern), 0.197 (Kings), 0.395 (Madera), 0.271 (Merced), 0.254 (San Joaquin), 0.220 (Stanislaus), 0.456 (Tulare). The total loss in agricultural revenue will be $2,827,000,000 (Table 1).

It is important to note that population and other parameters that affect agricultural production, water usage, energy consumption, and revenue were assumed to be constant in this study.

2 Editor’s note: “Groundwater depth” is used to indicate the depth from the land surface to the groundwater surface. This use differs from the popular use of “groundwater depth” which is taken as a reference to the volume of the groundwater: in that popular parlance, an increasing “depth” would indicate an increased groundwater supply.

Increased Additional Energy Lower SJV County Groundwater Requirement Agricultural Depths (feet) (megawatt hours) Revenue (billions of dollars) Fresno 9.1 147,765 0.676 Kern 21.5 51,013 0.358 Kings 13.9 60,722 0.197 Madera 15.1 27,616 0.395 Merced 5.5 71,661 0.271 San Joaquin 8.3 60,735 0.254 Stanislaus 6.8 70,072 0.220 Tulare 14.7 133,877 0.456 TOTAL 94.9 623,461 2.827

Table 1 Estimated impact per year at 4 inches precipitation depth

3 1. Introduction

1.1 Background

The SJV is historically known for its agriculture and ranks as one of the highest agricultural producers in the world. It produces a wide variety of crops, livestock, and poultry. While agriculture contributes significantly towards the SJV economy, it also consumes a huge amount of water and energy. Both surface and groundwater are heavily used in agricultural production and as a consequence wield an effect on agricultural revenue.

The availability of surface water, which is directly affected by the amount of precipitation, is decreasing as a result of the lower precipitation in recent years. A year that has the mean annual precipitation much lower than the historical mean precipitation can be defined as a drought year. With this definition, a tremendous drought has been affecting the SJV in recent years starting in 2012. This drought is not only lowering the surface water availability but also affecting the groundwater depth, as there is not enough surface water to recharge the groundwater basins. This scarcity of water will adversely impact the agricultural sector which is heavily dependent on water, with the damage to agricultural revenue impacting the entire region.

1.2 Objectives

This study focused on the impact of the current drought on the SJV’s agriculture, specifically the impact on agricultural water and energy usage and so on agricultural revenue, in the eight counties of Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare. By examining the historical trends related to precipitation, streamflow, reservoir water storage, irrigation water use, and groundwater depth, the impact of the drought was assessed.

4 2. Study Area and Data

2.1 Study Area

For the purposes of this study, the SJV study area consists of the eight counties: Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare.

2.2 Data

Historical data for different time ranges and resolutions were collected to evaluate the drought impacts. Data sets include precipitation, streamflow, reservoir storage, groundwater depth, irrigation water use, and, finally, agricultural revenue. The longest data set is that for precipitation, which ranges from 1901 to March 2015. Each of these data sets is described below.

2.2.1 Precipitation Data Monthly precipitation recorded by National Weather Service (2015) was collected from 28 stations throughout the SJV. The data was downloaded from the Weather Warehouse (2015). Stations were chosen based on two criteria: proximity within the counties of interest and length of record. It was expected that the stations would be spread throughout each county rather than clumped in small clusters. It was required that each station should have at least 50 years of historical data. Many of the chosen stations met and exceeded this requirement, with some having records from as far back as 1900. The data of interest was the total precipitation for each month. The total precipitation was a sum of all the precipitation events in a month in inches. Figure 1 shows the locations of precipitation stations.

The data was processed to find the total annual precipitation (for the water year spanning October to September) for each station first. Then it was further processed to find the average annual precipitation of all the stations in each county, and then finally to calculate the mean annual average precipitation for each county. Figure 1 below presents the Data Collection Locations. Figure 2 to Figure 9 show yearly average precipitation and mean annual average precipitation for each of the eight counties. The mean annual precipitation ± one standard deviation is also shown on the figures to estimate the width of the statistical confidence bounds and provide an assessment of drought. While Madera County has the highest mean annual precipitation, Kern County has the lowest.

Figure 1 Data collection locations

Figure 2 Historical precipitation in Fresno County

Figure 3 Historical precipitation in Kern County

Figure 4 Historical precipitation in Kings County

Figure 5 Historical precipitation in Madera County

Figure 6 Historical precipitation in Merced County

Figure 7 Historical precipitation in San Joaquin County

Figure 8 Historical precipitation in Stanislaus County

Figure 9 Historical precipitation in Tulare County

10 2.2.2 Surface Water Data Monthly mean streamflow data was collected from major rivers and streams within or near to the study area. The majority of the streams studied were located in Stanislaus and Fresno counties, primarily due to the availability of historical data. Total twenty (20) stream gauges maintained and operated by the United States Geological Survey [USGS] (2015a) that have long historical data lengths were considered for this study. Some of the stream gauges have data ranging from 1899 to 2014. Monthly mean streamflow data has been processed to calculate the historical monthly mean for all the stream gauges and is shown in Table 2. (Figure 1 has shown the locations of the stream gauges.)

USGS Historical mean streamflow (cfs) Stream County Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec gauge ID 11261100 Kern 68 93 162 344 424 168 48 23 18 24 38 55 11200800 Tulare 49 66 73 64 41 22 8 4 3 5 13 22 11251000 Fresno 672 962 1094 1663 1842 1639 955 542 433 333 249 363 11224500 Fresno 13 22 19 9 3 1 0 0 0 0 1 3 11253310 Fresno 7 10 12 4 2 1 0 0 0 0 0 2 11254000 Fresno 822 1222 1095 1350 1912 1895 707 351 240 208 255 466 11242400 Fresno 29 29 39 50 78 49 16 6 4 5 9 14 11267350 Fresno 9 11 18 23 29 17 4 1 1 1 3 6 11274000 Stanislaus 2257 2993 2929 2954 2808 2146 954 519 603 710 685 1153 11274500 Stanislaus 45 82 45 21 3 1 0 0 0 0 1 11 11274630 Stanislaus 18 31 22 9 4 2 0 0 0 0 1 4 11290000 Stanislaus 1828 2054 2049 1960 1949 1538 642 382 540 809 901 1400 11303000 Stanislaus 1183 1219 1361 1483 1948 1356 523 383 364 425 461 839 11289000 Stanislaus 55 87 298 642 808 876 796 655 441 252 105 73 11289650 Stanislaus 1434 1757 1800 1694 1570 814 450 249 448 600 347 795 11289500 Stanislaus 82 137 504 1022 1246 1363 1334 1117 700 309 133 126 San 11303500 5051 6912 7269 7137 7590 6309 2577 1452 1760 2278 2262 3433 Joaquin 11261100 Merced 175 273 342 230 191 189 204 204 135 139 166 138 11261500 Merced 498 759 1400 1980 1175 930 297 232 188 180 197 199 11262900 Merced 163 200 183 83 57 54 50 44 35 91 105 119

Table 2 Statistics of historical monthly streamflow (cfs) in main rivers and streams

The ten largest surface water reservoirs within the study area were considered for this study. The larger reservoirs tend to have more historical data available than the smaller reservoirs. The reservoirs vary in size from approximately 13,000 acres to 1,100 acres. Most of the reservoirs are located in Fresno County with others scattered in Tulare, Madera, Kern, and San Joaquin Counties. Monthly storage data from 1940s to 2015 was collected from the California Department of Water Resource’s data exchange center (CDEC) (DWR, 2015). Some of the data sets begin in the late 1950s or early 1960s. The monthly storage data was processed to calculate the historical mean monthly storage in each reservoir. Table 3 shows the calculated historical mean monthly reservoir storage for each reservoir considered in this study. Figure 10 through 15

11 show the fluctuations of historical mean monthly storage for six of the reservoirs. The San Luis reservoir is the largest reservoir studied, and the Success reservoir is the smallest. (Figure 1 on has shown the locations of these reservoirs.)

Area Reservoir Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec (ac) San Luis 13,000 1.57 1.70 1.81 1.79 1.59 1.28 1.00 0.87 0.96 1.04 1.19 1.36

Isabella 11,400 0.16 0.17 0.18 0.21 0.27 0.29 0.25 0.19 0.17 0.15 0.14 0.14

Camanche 7,700 0.25 0.25 0.26 0.27 0.28 0.31 0.29 0.27 0.25 0.24 0.23 0.24

Pine Flat 5,970 0.44 0.49 0.52 0.57 0.68 0.66 0.48 0.36 0.33 0.33 0.36 0.40

Friant 4,900 0.31 0.31 0.33 0.34 0.39 0.41 0.32 0.23 0.20 0.18 0.20 0.26

Success 2,450 0.02 0.02 0.03 0.04 0.05 0.05 0.03 0.02 0.01 0.01 0.01 0.01

Terminus 1,945 0.02 0.02 0.04 0.08 0.12 0.10 0.05 0.02 0.01 0.01 0.01 0.02

Hidden 1,500 0.02 0.03 0.04 0.05 0.05 0.04 0.03 0.02 0.02 0.02 0.02 0.02

Courtright 1,480 0.04 0.04 0.04 0.05 0.08 0.09 0.09 0.07 0.06 0.05 0.05 0.05

Wishon 970 0.04 0.04 0.04 0.05 0.09 0.10 0.09 0.08 0.07 0.06 0.05 0.04

Table 3 Historical water storage in million acre-ft (M ac-ft) in major reservoirs

Figure 10 Water storage in Millerton Lake

Figure 11 Water storage in San Luis Reservoir

Figure 12 Water storage in Isabella Lake

Figure 13 Water storage in Camanche Reservoir

Figure 14 Water storage in Pine Flat Lake

Figure 15 Water storage in Lake Success

2.2.3 Groundwater Data The groundwater depth data was collected from monitoring wells located throughout the study area. For the county of Fresno, a total of 40 monitoring wells were chosen. For the seven other counties, 30 monitoring wells were chosen from each county. Therefore, a total of 250 monitoring stations were chosen. While selecting the wells, emphasis was given to two criteria: (1) the locations of the monitoring wells should be distributed as uniformly as possible and (2) the length of the historical data should be around 50 years or longer. Data was downloaded from the California State Water Resources Control Board (CSWRCB, 2015) website, including data from 1921 to 2014. Some of the data set begins from late 1940s.

In any given year, the groundwater depth from a particular monitoring station was collected at irregular intervals. This data was used to find the average groundwater depth in each year for each monitoring well. This process was completed for all of the wells in each county. The county yearly average groundwater depth for each year was then computed from the average depths at all the monitoring stations in each county. In order to observe the historical change in groundwater depth, a moving average over 10 year periods was then calculated. The difference between the yearly average and moving average for a given year is a good indicator of groundwater depletion or recharge. Yearly average depth to groundwater (“groundwater depth”) higher than the moving average is an indicator of depletion. Similarly, yearly average groundwater depth lower than the moving average is an indicator of groundwater recharge.

Table 4 lists the statistics on groundwater depth.

Figure 16 through 23 show the per-county yearly average and 10-year moving average groundwater depths.

Number of Historical Average Depth (ft) Statistics monitoring Start year End year wells used Min Max Fresno 40 1921 2014 10.4 65.3 Kern 30 1936 2014 3.4 304.4 Kings 30 1936 2014 9.7 138.5 Madera 30 1920 2014 23.6 171.6 Merced 30 1958 2014 18.0 45.0 San Joaquin 30 1947 2015 54.0 105.8 Stanislaus 30 1940 2014 29.4 63.6 Tulare 30 1921 2014 5.7 102.1

Table 4 Statistics of groundwater data

16 The line graphs for Figures 16-23 provide for each county a long-term trend line (dashed) measuring the distance from the surface to the aquifer, with the surface represented by “0” depth and the descent measured by negative numbers/feet:

Figure 16 Average depth to groundwater in Fresno County

Figure 17 Average depth to groundwater in Kern County

Figure 18 Average depth to groundwater in Kings County

Figure 19 Average depth to groundwater in Madera County

Figure 20 Average depth to groundwater in Merced County

Figure 21 Average depth to groundwater in San Joaquin County

Figure 22 Average depth to groundwater in Stanislaus County

Figure 23 Average depth to groundwater in Tulare County

20 2.2.4 Agricultural Data Three types of agricultural data were collected: 1) groundwater water usage for irrigation, 2) surface water usage for irrigation, and 3) crop revenue.

Irrigation water usage data for 1985 to 2010 was collected from the USGS website (USGS, 2015b). For quality control, the data downloaded from the USGS website was compared with the data presented in the California Water Plan (DWR, 2013a, 2013b, & 2013c). Table 5 lists mean groundwater and surface water usage in million gallons per day (mgd), listed alongside each county’s amount of irrigated land. Fresno, Kern, and Tulare counties use more water total (surface and groundwater combined) for irrigation than the rest of the counties in the study area.

Irrigated Groundwater Usage Surface Water Usage County land Start year End year Mean Max Min Mean Max Min (acres*103) (mgd) (mgd) (mgd) (mgd) (mgd) (mgd) Fresno 1093.78 1985 2010 1,149 1,640 707 1,951 2,574 1,765

Kern 737.79 1985 2010 1,183 1,501 780 1,222 1,549 1,030

Kings 558.95 1985 2010 609 791 469 754 882 641

Madera 297.84 1985 2010 409 693 286 484 666 162

Merced 613.34 1985 2010 517 751 393 1,064 1,184 981

San Joaquin 740.77 1985 2010 498 727 83 1,064 1,576 903

Stanislaus 659.31 1985 2010 371 496 189 902 1,160 701

Tulare 974.67 1985 2010 1,153 1,432 986 1,005 1,269 443

Table 5 Irrigation water usage statistics

Crop revenue data was collected from annual agricultural crop reports. As required by the State of California, counties must produce and make available these reports.3 The county reports are available online from the websites for all of the eight counties in the study area. The data covers

3 The State of California Food and Agricultural Code requires county Ag Commissions the work to compile, record, report, and make available information on the gross production and value of crop and livestock. The State of California does not duplicate this effort but instead works closely with the counties to complete this effort. State reporting is aligned with federal reporting (see USDA National Agricultural Statistics Service: http://www.nass.usda.gov/Data_and_Statistics/index.asp). Table 5: Fresno County Agricultural Commissioner, 2015; Kern County Department of Agriculture and Measurement Standards, 2015; Kings County Department of Agriculture/Measurement Standards, 2015; Madera County Department of Agriculture, 2015; Merced County Department of Agriculture, 2015; San Joaquin County Office of the Agricultural Commissioner, 2015; Stanislaus County Agricultural Commissioner & Weights and Measures, 2015; Tulare County Agricultural Commissioner/Sealer, 2015

21 from 1950 to 2013. The total revenue value for each county was calculated from the rounded sum of the revenue from all agricultural products including fruit and nuts, field crops, vegetables, nursery crops, industrial and wood crops, seeds, livestock, and poultry. In total agricultural revenue, Fresno, Tulare, and Kern counties consistently rank significantly higher than the other counties included in this study. The top individual sources of revenue for each county are Fresno: almonds; Tulare: milk; and Kern: grapes.

Table 6 lists statistics on crop revenue for all counties in billions of dollars ($B). For fair comparison, all the yearly revenues are converted into their present values in 2015 considering a historical inflation rate of 3.32%. Generally the agricultural revenue increases over time, with some exceptions. However the rate of increase in the revenue may not be consistent each year. To observe this rate of increment in different years, a 5-year moving average has been calculated and compared with the yearly revenue. The yearly revenue and the moving average for each county are depicted in Figure 24 and Figure 25.

Historical Max Yearly revenue in recent years ($B) Statistics Start year End year Min mean ($B) ($B) 2010 2011 2012 2013 Fresno 1950 2013 4.52 7.76 2.06 7.00 7.76 7.27 6.87 Kern 1950 2013 3.10 7.23 1.37 5.60 6.11 7.01 7.23 Kings 1950 2013 1.28 2.53 0.48 2.02 2.53 2.44 2.42 Madera 1999 2013 1.46 2.02 1.03 1.59 1.79 1.92 2.02 Merced 1974 2013 2.59 4.06 1.33 3.22 3.71 3.62 4.06 San Joaquin 1950 2013 1.81 3.25 0.99 2.31 2.55 3.25 3.12 Stanislaus 1950 2013 1.83 3.91 0.78 3.03 3.50 3.60 3.91 Tulare 1950 2013 3.64 8.34 1.61 5.73 6.42 6.85 8.34 Table 6 Statistics of agricultural revenue (all numbers are calculated in 2015 dollars)

Figure 24 Yearly revenue in Fresno, Kings, Madera, and Tulare counties (all values in 2015 dollars)

Figure 25 Yearly revenue in Kern, Merced, San Joaquin and Stanislaus counties (all values in 2015 dollars)

3. Impact Analysis

3.1 Impact on Surface Water Availability

The impact of drought on surface water availability was evaluated by looking at three different data sets: precipitation, streamflow, and reservoir storage. Table 7 compares the mean annual precipitation with the total yearly precipitation in recent years (2010–2014) for each county, (noting also the standard deviation/Stdev and the coefficient in variation/CV). While 2010 and 2011 are shown to be wet years, 2012 to 2014 were dry years. The yearly precipitation in these dry years was found to be even lower than the lower bound of the confidence interval (less than one-third of the normal level) for most of the counties, indicating drought conditions. 4 As precipitation is the main source of water, decreased precipitation can be expected to have adverse impacts on streamflow and reservoir storage.

4 In plain English, the “confidence interval” is the range (more or less) that the findings might fluctuate.

Total Start End Mean Stdev. Yearly Precipitation (in) Statistics Rainfall CV year year (in) (in) Station 2010 2011 2012 2013 2014 Fresno 4 1912 2015 12.0 4.9 0.4 14.2 20.5 9.4 6.6 3.5 Kern 3 1901 2015 5.7 5.6 1.0 6.6 7.9 3.8 2.6 2.0 Kings 4 1900 2015 6.0 3.1 0.5 9.2 12.1 5.0 4.2 2.2 Madera 2 1904 2015 23.7 10.0 0.4 28.2 26.4 5.8 9.0 8.4 Merced 3 1900 2015 9.1 3.6 0.4 11.5 12.0 5.8 4.7 3.3 San Joaquin 4 1900 2015 13.4 6.2 0.5 14.9 17.1 7.5 8.0 5.7 Stanislaus 2 1906 2015 10.7 4.6 0.4 14.5 14.5 7.6 4.5 5.4 Tulare 6 1900 2015 14.1 6.6 0.5 18.2 24.0 11.4 8.4 5.7

Table 7 Historical rainfall

To observe the impact of drought on streamflow, historical mean monthly streamflow has been plotted with recent years’ streamflow on the same figure (2010–2013 or 2010-2014, depending on available data). Sample plots are shown in Figure 26 to Figure 31. As expected, the drought has a tremendous adverse impact on streamflow, as shown by mean monthly flow lower than the historical mean for the years shown at each stream gauge location. The streamflow was found to be directly related to the precipitation as shown by lower streamflow from 2012 to 2014, the worst three years of the drought, versus the higher streamflow in 2011, which had the highest precipitation levels in 2010-2015.

Figure 26 Monthly mean streamflow at USGS 11251000 San Joaquin in Fresno County

Figure 27 Monthly mean streamflow at USGS 11254000 San Joaquin in Fresno County

Figure 28 Monthly mean streamflow at USGS 11261100 Salt Slough in Kern County

Figure 29 Monthly mean streamflow at USGS 11261100 Salt Slough in Merced County

Figure 30 Monthly mean streamflow at USGS 11303500 San Joaquin in San Joaquin County

Figure 31 Monthly mean streamflow at USGS 11274000 San Joaquin in Stanislaus County

27 Similarly to streamflow, the historical mean monthly reservoir storage was plotted with recent years’ monthly storage on the same figure (Figure 26 to Figure 31) in order to observe the impact on storage. Storage in recent years was found to be significantly lower than the historical mean. An attempt was made to calculate the likely water shortage in coming years. This calculation is based on the assumption that the amount of precipitation in 2015 will be same as the amount of precipitation in 2014. These likely reservoir water shortages for all of the studied reservoirs are listed in Table 8.

Note: Positive numbers in the table represent water shortage, and negative numbers represent atypical higher storage than the historical mean.

Reservoir Area (ac) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec San Luis 13,000 0.959 1.022 0.958 0.834 0.741 0.623 0.543 0.492 0.498 0.649 0.698 0.540 Isabella 11,400 0.099 0.106 0.122 0.146 0.193 0.216 0.188 0.140 0.118 0.102 0.095 0.100 Camanche 7,700 0.033 0.049 0.072 0.095 0.133 0.163 0.149 0.135 0.118 0.105 0.109 0.101 Pine Flat 5,970 0.265 0.297 0.302 0.266 0.254 0.304 0.340 0.241 0.211 0.221 0.239 0.272 Friant 4,900 0.110 0.147 0.165 0.111 0.069 0.080 0.043 -0.002 0.012 0.004 0.029 0.077 Success 2,450 0.010 0.016 0.022 0.029 0.038 0.036 0.022 0.013 0.008 0.005 0.005 0.008 Terminus 1,945 0.009 0.006 0.012 0.021 0.035 0.058 0.024 -0.001 -0.005 -0.003 -0.003 -0.006 Hidden 1,500 0.019 0.024 0.034 0.039 0.040 0.036 0.026 0.018 0.015 0.012 0.011 0.012 Courtright 1,480 0.004 0.003 0.007 0.005 -0.012 0.000 0.051 0.015 0.024 0.017 0.018 0.015 Wishon 970 -0.003 -0.007 -0.016 -0.019 0.035 0.058 0.009 0.039 0.022 0.020 0.013 0.007

Table 8 Likely water storage shortage in million acre-feet (M ac-feet) in major reservoirs

3.2 Impact on Groundwater Depth

The historical change in groundwater depth was calculated by subtracting the county yearly average groundwater depth from 10-year moving average depth. This change in groundwater depth data was correlated with the total precipitation to observe the relationship between precipitation and groundwater recharge or depletion. The precipitation data was lagged from 0 to 4 years. While zero year lag refers the relationship in the same year, the 4 year lag refers to the relationship between the precipitation that occurred 4 years ago and the current year’s groundwater depth change. A linear relationship was assumed. It was also assumed that the water usage for all purposes will remain the same.

Table 9 lists the linear model coefficients for the best model for each county, which is defined as the model that has the highest correlation coefficient (CC).5 Note: A positive number indicates depletion and a negative number indicates recharge.

Figure 32 to Figure 39 show the relationship between the groundwater change and the total precipitation for each county with a best fit linear model.

Lag County CC Intercept Slope year Fresno 0.65 1 11.88 -0.70 Kern 0.45 1 38.04 -4.13 Kings 0.58 1 22.79 -2.23 Madera 0.50 1 16.93 -0.45 Merced 0.45 1 7.40 -0.47 San Joaquin 0.50 1 10.29 -0.49 Stanislaus 0.62 1 8.98 -0.55 Tulare 0.45 0 16.97 -0.66

Table 9 Coefficients in the groundwater depth prediction models

5 A high “correlation coefficient” indicates that the strength and direction of the linear relationship is very good.

Figure 32 Relationship between average groundwater depth and total annual precipitation in Fresno County

Figure 33 Relationship between average groundwater depth and total annual precipitation in Kern County

Figure 34 Relationship between average groundwater depth and total annual precipitation in Kings County

Figure 35 Relationship between average groundwater depth and total annual precipitation in Madera County

Figure 36 Relationship between average groundwater depth and total annual precipitation in Merced County

Figure 37 Relationship between average groundwater depth and total annual precipitation in San Joaquin County

Figure 38 Relationship between average groundwater depth and total annual precipitation in Stanislaus County

Figure 39 Relationship between average groundwater depth and total annual precipitation in Tulare County

The linear model coefficients (Table 9) were used to calculate the predicted change in the average groundwater depth for a given total precipitation in a year. Considering recent precipitation trends, the annual total precipitation was assumed to be from two to five inches.

Table 10 shows the impacts of these amounts of precipitation on groundwater depth in each county. As expected the change is greater with lower precipitation. The highest change in groundwater depth is predicted in Kern County, and the lowest change in groundwater depth is predicted in Merced County for all precipitation amounts.

Figure 40 depicts the impacts of total precipitation on the change in average groundwater depth by county.

Change in depth to groundwater level (ft) at given precipitation (in) Irrigated land County 2 in. 3 in. 4 in. 5 in. (acres*103) Fresno 1093.78 10.5 9.8 9.1 8.4 Kern 737.79 29.8 25.6 21.5 17.4 Kings 558.95 18.3 16.1 13.9 11.6 Madera 297.84 16.0 15.6 15.1 14.7 Merced 613.34 6.5 6.0 5.5 5.0 San Joaquin 740.77 9.3 8.8 8.3 7.8 Stanislaus 659.31 7.9 7.3 6.8 6.2 Tulare 974.67 15.7 15.0 14.3 13.7

Table 10 Predicted change in groundwater depth

Figure 40 Impact of total precipitation on the change in average groundwater depth.

3.3 Impact on Agriculture

The drought impact on three important sectors of agriculture was assessed: 1) energy usage, 2) total irrigation water usage, and 3) agricultural revenue. Each of them is described below.

3.3.1 Impact on Energy Usage It is expected that the drought will increase the groundwater depth assuming that groundwater usage and other parameters will remain the same. As groundwater depth increases, the energy consumption required for pumping also increases. Considering the impact of the drought on groundwater depth (Table 10), the additional energy required for pumping can be calculated.

Yeasmin and Zoldoske (2014) used low and high estimates of average energy consumption to determine the energy consumption for pumping in California. The low and high estimates are based on an analysis made by the California Public Utility Commission (CPUC). The average low and high estimates of energy consumption are 283 and 431 kWh to lift one acre-foot of groundwater in the Tulare region. The same assumption has been used in this study. Again following Yeasmin and Zoldoske, annual use of 3.1 acre feet of groundwater was assumed. Table 11 and Table 12 list the predicted additional energy requirements in megawatt-hours (mWh) due to the drought. The impact is also depicted on a map in Figure 41 and Figure 42.

Additional energy requirement (mWh) at given precipitation (in) County 2 in. 3 in. 4 in. 5 in. Fresno 170,532 159,149 147,765 136,381 Kern 70,618 60,815 51,013 41,210 Kings 80,290 70,506 60,722 50,938 Madera 29,251 28,433 27,616 26,798 Merced 83,928 77,794 71,661 65,527 San Joaquin 67,862 64,298 60,735 57,171 Stanislaus 81,420 75,746 70,072 64,398 Tulare 146,176 140,027 133,877 127,728

Table 11 Predicted additional energy requirement (mWh) for pumping groundwater based on Tulare Basin Low Estimate (283 kWh to life one ac-ft of groundwater)

Additional energy requirement (mWh) at given precipitation (in) County 2 in. 3 in. 4 in. 5 in. Fresno 259,715 242,378 225,041 207,704 Kern 107,549 92,620 77,690 62,761 Kings 122,280 107,378 92,477 77,576 Madera 44,549 43,303 42,058 40,813 Merced 127,820 118,478 109,137 99,795 San Joaquin 103,352 97,925 92,497 87,069 Stanislaus 124,000 115,359 106,717 98,076 Tulare 222,622 213,256 203,891 194,525

Table 12 Predicted additional energy requirement (mWh) for pumping groundwater based on Tulare Basin High Estimate (431 kWh to life one ac-ft of groundwater)

Figure 41 Impact of precipitation on additional energy requirement for pumping groundwater Tulare Basin Low Estimate

Figure 42 Impact of precipitation on additional energy requirement for pumping groundwater Tulare Basin High Estimate

3.3.2 Impact on Irrigation Water Usage To observe the historical relationships between irrigation water usage and total precipitation, scatter plots have been plotted. As with the groundwater impact analysis, a zero to four year lag in precipitation data was used to observe the best relationship. It was found that a linear model can describe the relationship between irrigation water usage and mean annual precipitation. The relationship between surface water usage and precipitation and between groundwater usage and precipitation were both found to be linear. Table 13 and Table 14 list the linear prediction model parameters used for calculating both for groundwater and surface water future usage (see Table 15 and 16 on next page).

County Lag year CC Intercept Slope Fresno 2 0.928 229.16 52.85 Kern 2 0.572 855.45 55.49 Kings 2 0.810 254.15 61.71 Madera 4 0.464 143.80 12.04 Merced 3 0.831 241.44 41.70 San Joaquin 2 0.773 77.91 22.00 Stanislaus 2 0.845 152.75 14.02 Tulare 4 0.330 1077.22 3.97

Table 13 Coefficients in groundwater use (for irrigation) prediction models

County Lag year CC Intercept Slope

Fresno 4 0.614 1049.55 68.04 Kern 3 0.444 917.16 70.17 Kings 3 0.444 917.16 70.17 Madera 3 0.771 101.68 18.29 Merced 2 0.935 905.80 15.16 San Joaquin 4 0.674 480.63 37.07 Stanislaus 4 0.501 596.09 24.69 Tulare 3 0.561 562.79 31.35

Table 14 Coefficients in the surface water use (for irrigation) prediction model

The linear models were used to predict surface and groundwater usages for total precipitation ranging from 2 to 5 inches. Average historical irrigation water usages were then used to calculate the water shortage at each precipitation amount. The model parameters listed above and the procedure mentioned here can be used predict the water shortage for any precipitation depth.

Table 15 and 16 list the predicted water shortages at different precipitation amounts. These impacts are mapped in Figure 43 and Figure 44.

Table 17 lists the total water shortage from adding groundwater shortage and surface water shortage. Figure 45 depicts in a plot and Figure 46 depicts in a map the total irrigation water shortage. As expected, the water shortage is higher when precipitation is lower.

Predicted water shortage (gpd/acre)1 Predicted water shortage (mgd)1 Irrigated land County at given precipitation (in) at given precipitation (in) (acres*103) 2 in. 3 in. 4 in. 5 in. 2 in. 3 in. 4 in. 5 in. Fresno 1093.78 744 696 647 599 814 761 708 655 Kern 737.79 293 218 143 67 216 161 105 50 Kings 558.95 415 304 194 83 232 170 108 47 Madera 297.84 809 769 728 688 241 229 217 205 Merced 613.34 313 245 177 109 192 150 109 67 San Joaquin 740.77 508 479 449 419 377 355 333 311 Stanislaus 659.31 289 268 247 225 191 177 163 149 Tulare 974.67 70 66 62 58 68 64 60 56 1 “gpd” = gallons per day and “mgd” = million gallons per day.

Table 15 Predicted groundwater shortage for irrigation

Predicted water shortage (gpd/acre)1 Predicted water shortage (mgd)1 Irrigated land County at given precipitation (in) at given precipitation (in) (acres*103) 2 in. 3 in. 4 in. 5 in. 2 in. 3 in. 4 in. 5 in. Fresno 1093.78 699 637 575 513 765 697 629 561 Kern 737.79 224 128 33 62 165 95 25 46 Kings 558.95 182 105 27 50 102 58 15 28 Madera 297.84 1160 1098 1037 975 345 327 309 291 Merced 613.34 208 184 159 134 128 113 97 82 San Joaquin 740.77 687 637 587 537 509 472 435 398 Stanislaus 659.31 389 351 314 276 256 232 207 182 Tulare 974.67 390 358 325 293 380 348 317 286 1 “gpd” = gallons per day and “mgd” = million gallons per day.

Table 16 Predicted surface water shortage for irrigation

Figure 43 Impact of precipitation on groundwater shortage for irrigation

Figure 44 Impact of precipitation on surface water shortage for irrigation

Predicted water shortage (gpd/acre)1 Predicted water shortage (mgd)1 Irrigated land County at given precipitation (in) at given precipitation (in) (acres*103) 2 in. 3 in. 4 in. 5 in. 2 in. 3 in. 4 in. 5 in. Fresno 1093.78 1443 1333 1222 1112 1579 1458 1337 1216 Kern 737.79 516 346 176 129 381 255 130 95 Kings 558.95 597 409 221 134 333 228 123 75 Madera 297.84 1969 1867 1765 1663 586 556 526 495 Merced 613.34 522 429 336 243 320 263 206 149 San Joaquin 740.77 1196 1116 1036 957 886 827 768 709 Stanislaus 659.31 678 619 560 502 447 408 370 331 Tulare 974.67 460 423 387 351 448 413 377 342 1“gpd” = gallons per day and “mgd” = million gallons per day.

Table 17 Predicted total irrigation water shortage

Figure 45 Predicted total irrigation water shortage for different total annual precipitation

Figure 46 Impact of precipitation on total irrigation water shortage

3.3.3 Impact on Agricultural Revenue ($B) The historical yearly revenue, calculated at today’s (2015) prices at an inflation rate of 3.32%, shows a general trend of increase as time progresses (Figure 24 and Figure 25). However, the rate of increase in revenue is not consistent throughout the period from approximately 1950 to 2013. To observe this rate in different years a five-year moving average was calculated and compared with the yearly revenue. The difference between yearly revenue and the five-year moving average indicates the relative change in revenue for a particular year. A positive number indicates relative reduction in revenue and negative indicates relative increase in the revenue. Again, revenues are given in billions of dollars.

There are many parameters that can contribute towards the change of rate of revenue increase. However water was considered to be the most important one as water directly affects the agricultural production. As such, the relationship between the relative change in yearly revenue and total mean annual precipitation was observed for all the counties. Figure 47 to Figure 54 show these relationships for different counties.

Figure 47 Relationship between relative change in yearly revenue and total mean annual precipitation in Fresno County

Figure 48 Relationship between relative change in yearly revenue and total mean annual precipitation in Kern County

Figure 49 Relationship between relative change in yearly revenue and total mean annual precipitation in Kings County

Figure 50 Relationship between relative change in yearly revenue and total mean annual precipitation in Madera County

Figure 51 Relationship between relative change in yearly revenue and total mean annual precipitation in Merced County

Figure 52 Relationship between relative change in yearly revenue and total mean annual precipitation in San Joaquin County

Figure 53 Relationship between relative change in yearly revenue and total mean annual precipitation in Stanislaus County

Figure 54 Relationship between relative change in yearly revenue and total mean annual precipitation in Tulare County

A linear model with relative change in revenue as dependent variable and mean annual precipitation as independent variable was found to be the best fit to describe these relationships.

Table 18 lists the prediction model parameters used to calculate future reductions agricultural revenues.

Table 19 lists the predicted reductions in agricultural revenue due to lower precipitation. Figure 55 maps the predicted reductions in revenues due to lower precipitation. The reduction in revenue due to lower precipitation was found to be highest for the County of Fresno.

County CC Lag year Intercept Slope Fresno 0.50 3 0.868 -0.048 Kern 0.39 0 0.622 -0.066 Kings 0.62 4 0.406 -0.052 Madera 0.63 4 0.449 -0.013 Merced 0.42 0 0.373 -0.026 San Joaquin 0.43 3 0.315 -0.015 Stanislaus 0.45 3 0.284 -0.016 Tulare 0.57 3 0.553 -0.024

Table 18 Coefficients in agricultural revenue prediction models

County 2 in. 3 in. 4 in. 5 in. Fresno 0.772 0.724 0.676 0.628 Kern 0.490 0.424 0.358 0.291 Kings 0.302 0.249 0.197 0.144 Madera 0.422 0.409 0.395 0.382 Merced 0.322 0.297 0.271 0.245 San Joaquin 0.285 0.269 0.254 0.239 Stanislaus 0.252 0.236 0.220 0.203 Tulare 0.505 0.481 0.456 0.432 TOTAL 3.35 3.089 2.827 2.564

Table 19 Predicted reduction in yearly agricultural revenues ($B at today’s price) at given precipitation amount (in)

Figure 55 Impact of precipitation on yearly revenue reduction at today’s price ($B)

SNAPSHOT: IS THERE A “CENTRAL” VALLEY? By G. Harootunian, PhD The preceding chapter measures the billions of dollars in costs to farm revenue from the drought in the SJV. But is there a “Central Valley” farm? A “San Joaquin Valley” farm? What qualitative differences are there among categories of farms, for example a giant agribusiness; a modest family-owned farm; a limited resource minority/immigrant farmer; and a farmer with senior and land-inherited water rights? The intent of the U.S. Bureau of Reclamation limiting federal water supply availability to farms of 160 acres or less was a democratizing one. What is the value to be assigned to preserving the model of democratized agriculture or encouraging new entrepreneurs versus other models, including those involving the national food supply or global competitiveness? To what extent should the dialogue about the future of water in the SJV include the qualitative differences among farms within the SJV? “West Side” farmers versus “East Side” farmers exemplify this issue. The “East Side” was farmed early and eagerly for good reason: the rivers of the Sierra Nevada Mountains cascaded down every spring, at times roaring and deep, and watered the lands. The “West Side” however was harshly dry. In the “Largest Alteration of the Earth’s Surface,” USGS researchers describe water sources for the West Side as “intermittent and ephemeral, flowing only episodically.” West Side East Side Westlands Water District - Largest Friant Water Authority – Large coalition of agricultural water authority in the U.S. smaller, family farms. Farms served: About 700 Farms served: About 15,000 Average size of farms: 875 acres Average size of farms: 20-200 acres Typical Labor: The 875-acre farm would Typical Labor: The 100-acre farm would have permanent labor (e.g., farm have family members working it, with farm managers), with farm workers (including workers (including crop workers) secured crop workers) secured from contractors at from contractors at peak demand times, such peak demand times, such as harvest. as harvest. Portrait of a West Side Emperor The King of California is a 531-page book detailing the rise of a secret American empire: the J.G. Boswell Company. J.G. Boswell II was the biggest private farmer in U.S. His family travelled due west from their old plantation in Georgia to the SJV and built what was to be California’s first giant agribusiness model (estimates range from 150,000- 200,000 acres). Boswell and another giant, Clarence “Cockeye” Salyer, dominated the Westlands Water District for years. Boswell’s agribusiness was so huge he is also credited with dominating the Tulare Water District. Portrait of Well-Being When Measure of America published its groundbreaking report on the well-being of Americans in 2008, the 20th congressional district, which included the Westlands Water District, ranked at the absolute bottom of the list. California saw re-districting for the 2012 elections, and the 21st congressional district now includes the Westlands Water District. For 2013-2014, the state of California had both the lowest and the highest scores for the nation: 3.04 (congressional district 21) and 8.18 (congressional district 18, the San Francisco Bay Area).

THE VINEYARD: Launched by Richard Erganian, the son of Armenian immigrants, farmers, and entrepreneurs, The Vineyard farmers’ market offers local produce. Its farmers typify the smaller “East Side” farmer. Photographer Cary Edmondson offers a ‘window’ into their world on the next few pages.

Sun Smiling Valley Farm – Farmers Juro Watanuki and Nine Abe from Sanger selling another pound of their variety of mushrooms.

Top of the Hill – This farmer, jam-maker, and pickler from Thao Produce – This family is one of many Hmong Reedley puts up handmade signs for that week’s harvest. immigrant families who started small farms in Fresno. 54

Vine Ripe Farms – Rocio and Agustin Agraz run this family farm in Hanford, CA

Triple Delight Blueberries – Three daughters of the Sorenson Berry Lady Farms - Farmer Gayle Willems with her son Matt family (raisin growers) operate this 20-acre farm in and daughter-in-law Cassie, pastry chef, operate this family Caruthers, CA farm growing blueberries, blackberries, and boysenberries in Kingsburg, CA.

Mediterranean To Go – Maha Muhawi and husband Ellias sell Ms. Felix Muzquiz, Executive Director of The Vineyard, sports Mediterranean specialty dishes (many of which are now Fresnan, her signature farmer’s hat and smile. too).

MOA – The 10-acre Oasis Garden in Clovis embodies the

philosophy and methods of Nature Farming created by Mokichi K.M.K. Organic Farms – This 70 acre organic farm in Okada. The Mokichi Okada Association (MOA) carries on the Kingsburg, CA sells a range of produce. founder’s system of shizen nōhō (“no fertilizer farming”). Above is Bruno Luconi who operates the Oasis Garden as a form of art. 56

Switching to Almonds: A Video Narrative of Drought Impact on Farming and People

By Jes Therkelsen, MFA, Department of Mass Communication and Journalism

Russ Wilson, a fourth generation farmer in Fowler, California, decides to plant almonds on 35 acres of his 120-acre farm. Russ is an “East Sider” though his switch to almonds is common throughout the SJV. The reason is simple: farmers have long switched to higher-value crops during droughts. Crop substitutions and crop introductions are a typical and a critical response to water markets.

Some recent media coverage has pointed out almonds need twice the amount of water as do grapes, the traditional crop of the SJV. Almonds do not produce any fruit for three years, during which time they need to be watered. They are also a permanent crop, meaning once farmers plant almonds, they stay in the ground for 20–30 years, needing water constantly. Annual plants (ex. lettuce) are not permanent, and lettuce fields can be let fallow, for short or long periods of time. These reasons make it easy to criticize almonds and the farmers who decide to plant them.

In this video vignette, you can follow Russ as he watches all of his neighbors tear up their fields and plant almonds. Faced with the financial responsibility to maintain his business as a viable entity, Russ knows he must diversify, and almonds are the direction he decides to go in. https://vimeo.com/124495171. Password: almonds

“The law of the land and the custom has been you can use the water you need on your own land as much as you need. That’s our history.” Russ Wilson, 4th generation farmer (from Scotland to the San Joaquin Valley).

Chapter 2 The Economic Impact of the Drought in the California San Joaquin Valley: An Expanded Look

Dr. Antonio Avalos, Department of Economics

Abstract This segment of the report aims at expanding the scope of the UC Davis Study (Howitt, Medellín-Azuara, MacEwan, Lund, & Sumner, 2014)6 in four areas critical to understanding the economic impact of the drought in the San Joaquin Valley (SJV) by: 1. Focusing on the San Joaquin Valley eight counties (Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus and Tulare). 2. Examining the possibility that in addition to a decline in farm employment as consequence of the drought, the observed reduction in household income is due to farm workers working fewer hours per day, fewer days per week, and receiving a lower wage rate. 3. Exploring the economic impact of the drought in selected cities within each of the SJV counties, paying particular attention to a selected list of Disadvantaged Communities (DACs). 4. Assessing the impact of the drought on food prices and its impact on low-income households. Unemployment and Median Household Income (MHI) data at the county level conceal valuable and useful information that only becomes apparent when examining more refined geographical units. Thus this segment also examines available data at the city level, with particular emphasis on Disadvantaged Communities (DACs). The findings indicate that the observed fall in the MHI in some counties and in most disadvantaged communities during the drought years is due to a combination of job loss, lower hourly wage, and lower annual wages paid to farm workers, as well as working fewer days per year. The evidence also suggests that as a consequence of the drought some workers migrated to locations outside the SJV, possibly in pursuit of better working and living conditions. These patterns could at least partially explain why the MHI is falling at the same time that the unemployment rate is decreasing. In addition, although it is not totally clear at what extent overall food prices will go up as consequence of the drought, the data indicates that the price of some food items has increased during the dry years. This is relevant from the consumer perspective, particularly for low-income households that spend a larger share of their income on food, because a surge in food prices can significantly impact their disposable income.

6 Economic analysis of the 2014 drought for California agriculture. This Study is the first of three reports released by UC, Davis on the economic analysis of the drought’s impact on California agriculture. The subsequent two are a preliminary report of the economic impact on agriculture in all 25 counties of the Central Valley (2014, May 19) and a preliminary economic analysis of the 2015 drought’s impact on California agriculture (2015, May 31). .

Unemployment and Household Median Income (MHI) in the SJV

During the past three years, unemployment rates at the county level in the SJV have shown a declining trend. Although no county has returned to the unemployment rate levels before the 2007–2009 Great Recession (when this rate averaged 8%), it is not evident that the ongoing drought has caused unemployment rates to increase. Figure 1 below illustrates this falling unemployment trend during the drought years of 2012, 2013, and 2014 (shadowed rectangle).7 It is important to notice that although unemployment rates have declined in recent years in SJV counties, at the State level the unemployment rate is still much lower, currently at 7%. This indicates that SJV counties are still lagging behind the state unemployment rates and, apparently, the drought does not help to close the gap.

20.0% 18.0% 16.0% 14.0% 12.0% 10.0% 8.0% 6.0% 4.0% 2.0% 0.0% 2006 2007 2008 2009 2010 2011 2012 2013 2014 Fresno Kern Kings Madera Merced San Joaquin Stanislaus Tulare Figure 1 Unemployment Rates in SJV Counties (2006-2014)8 (California Employment Development Department [CA EDD], 2015a)

7 The UC Davis Study (2014) mentioned 17,100 jobs lost, which represents a small percentage of total employment in the region (p. 9). Even if all those jobs were lost in the SJV, which is a radical assumption since the UC Davis Study defines the Central Valley as comprising 25 counties, they would only represent around 1% of total employment in the SJV counties at the end of 2014. In other words, annual unemployment rates at the county level do not capture unemployment variations of such magnitude, particularly when other economic recovery factors are driving the unemployment rate down.

8 Shadow indicates drought years (2012, 2013, and 2014).

In terms of the median household income (MHI) at the county level, the data portray a mixed record. First, however, it must be noted that Table 1 shows overall that with the exception of San Joaquin County, the average MHI in all eight counties is below the $48,706 threshold required to be classified as a Disadvantaged Community (DAC)9, even including those counties where the MHI increased during dry years. This categorization suggests that in terms of MHI, the San Joaquin Valley as a whole is a region in economic distress. That is the context within which recent and increasing declines in MHI are taking place.

Table 1 shows for four counties, following a seemingly counterintuitive trend, the MHI increased during the drought years of 2012 and 201310 (Fresno, Kern, San Joaquin and Stanislaus) while it fell for four counties (Kings, Madera, Merced and Tulare). Although numerous economic and non-economic factors can explain the behavior of the MHI, this difference partially reflects that counties with a more diversified industrial base (which are thus less dependent on agriculture) also have economies that are more resilient during dry conditions. In the case of Tulare County for example, where agriculture represents a core industry sector, in 2013 the MHI fell to $39,422 from its peak of $43,397 (in 2011). This represents a significant fall in income of more than 9% in only 3 years. Similarly in Madera, the MHI fell to $39,758, which is below the $44,975 level it had at the onset of the 2007–2009 Great Recession, representing an income reduction of more than 11% in 6 years.

County 2006 2007 2008 2009 2010 2011 2012 2013 Fresno $42,732 $47,298 $43,737 $45,661 $45,221 $42,807 $41,627 $43,925 Kern $43,106 $47,105 $44,733 $47,368 $45,524 $45,224 $45,910 $46,879 Kings $43,178 $46,756 $50,962 $44,506 $44,609 $50,345 $45,935 $45,774 Madera $39,068 $44,975 $47,394 $44,135 $48,268 $46,570 $42,039 $39,758 Merced $40,447 $44,410 $42,303 $39,535 $42,449 $40,055 $43,597 $40,687 San Joaquin $51,951 $52,470 $54,882 $52,789 $50,011 $50,853 $50,722 $51,432 Stanislaus $48,566 $50,616 $50,359 $48,716 $48,044 $44,076 $46,405 $47,962 Tulare $41,933 $40,595 $45,117 $39,997 $43,397 $41,167 $40,302 $39,422

Table 1 Median Household Income (MHI) in SJV Counties (2006-2013) (Inflation-adjusted dollars)11 (U.S. Census Bureau, 2015)

9 As defined by the California Department of Water Resources (DWR)’s Propositions 84 and 1E Integrated Regional Water Management (IRWM) Guidelines (dated August 2010).

10 MHI county level data for 2014 is not yet available.

11 Shadow indicates drought years 2012 and 2013 only since 2014 data are not available yet.

Although illustrative of the challenging economic conditions that the SJV has endured in recent years, particularly during the ongoing dry years, unemployment and MHI data at the county level conceal valuable and useful information that only becomes apparent when examining more refined geographical units. At the city level for example, for which some data is available, evidence reveals a more dramatic picture than at the county level. Table 2 shows the MHI for 15 SJV selected cities classified as DACs. At this geographical level, data earlier than 2009 is not available and thus it is not possible to compare current MHI levels with levels before the 2007– 2009 Great Recession. However, the data illustrate at least two salient facts.

First, in all these communities the 2013 MHI fell from either the preceding year or from 2 years ago, in some cases to dramatic levels. According to the U.S. Census Bureau (2013), the federal poverty threshold for a household composed of 5 people (2 adults and 3 related children under 18) is $27,801. This means that in communities, such as Mendota and Tranquility for instance, in 2013 more than 50% of the households in these cities were officially classified as poor. Second, with the exception of Coalinga and Porterville, which historically exhibit a relatively larger income than other disadvantaged communities, the 2013 MHI for all other communities is below the lowest average MHI at county level, which corresponds to Tulare County at $39,422. This suggests that while the economic distress is generalized across the SJV, it is more acute in some agricultural communities, particularly in those most affected by reductions in surface water.

DAC12 County 2009 2010 2011 2012 2013 Avenal Kings $34,273 $33,350 $29,183 $27,927 $28,794 Chowchilla Madera $39,561 $39,902 $41,858 $41,373 $37,466 Coalinga Fresno $43,114 $46,229 $47,101 $46,712 $46,500 Corcoran Kings $31,728 $35,051 $31,641 $34,594 $32,914 Delano Kern $37,394 $35,673 $37,810 $35,507 $35,122 Dinuba Tulare $39,845 $39,165 $40,463 $39,228 $39,328 Dos Palos Merced $41,120 $40,121 $39,959 $34,522 $33,898 Exeter Tulare $45,363 $43,690 $42,446 $39,987 $39,063 Kettleman City Kings $25,488 $25,988 $34,323 $36,111 $35,625 Keyes Stanislaus $40,905 $35,130 $34,423 $34,819 $34,967 Mendota Fresno $25,422 $25,216 $25,807 $26,061 $24,264 Parlier Fresno $33,523 $34,405 $36,388 $36,161 $35,327 Porterville Tulare $38,079 $39,838 $39,933 $42,628 $41,905 Tranquility Fresno $31,763 $32,532 $24,293 $26,250 $24,609 Wasco Kern $38,096 $40,054 $40,295 $42,221 $39,061 Table 2 Median Household Income (MHI) in Selected SJV Cities (2009-2013) (Inflation-adjusted dollars)13 (U.S. Census Bureau, 2015)

12 DAC = Disadvantaged Community.

13 Shadow indicates drought years 2012 and 2013 only, since 2014 data are not available yet.

When looking at unemployment in DACs (Figure 2), the unemployment rates show a declining trend during the drought years, which mirrors what is happening at the county level as shown in Figure 1. However, it is important to notice that the 2014 average unemployment rate for DACs is significantly higher (18.4%) than the average for the SJV (11.5%). In a few cases the difference is not large, such as in Coalinga, Chowchilla, or Porterville, but in other cases the difference is substantial, such as in Avenal, Delano, or Mendota.14 This suggests that the industrial composition as well as other factors unique to each DAC determine its economic performance as well as its resilience when facing water challenges. Further, similarly to the path shown at the county level, none of these DACs has been able to return to the unemployment rate before the 2007–2009 Great Recession.

14 See Editorial Snapshot: “Who Are They: Moving from Economic Impact to Human Impact” following this chapter for more information on Avenal, Delano, and Mendota.

45.0% Avenal

40.0% Chowchilla Coalinga 35.0% Corcoran

30.0% Delano Dinuba

25.0% Dos Palos

Ke leman City 20.0% Keyes

15.0% Mendota Parlier 10.0% Porterville

Tranquillity 5.0% Wasco

0.0% SJV 2006 2007 2008 2009 2010 2011 2012 2013 2014

Figure 2 Unemployment Rates in Selected SJV Cities/Disadvantaged Communities 2006-2014)15 (CA EDD, 2015a)

15 Shadow indicates drought years (2012, 2013, and 2014).

Based on the data examined so far, an intriguing observation emerges which needs to be addressed: How can the MHI be falling at the same time that the unemployment rates are declining, which seems to be case in all DACs and also in some counties? In other words, if fewer workers are unemployed, the logical expectation is higher MHI (not lower MHI), at both the city and county levels. This expectation however implies some assumptions that do not always hold. This matter is examined in the next section.

Changing Employment Conditions and Migration Patterns

Expecting that lower unemployment rates will increase the MHI assumes that the number of hours per day worked, the number of days per week worked, as well as the wage rate paid to workers do not change. If either one or more of these variables fall, higher employment does not necessarily imply an increase in the MHI: a larger number of workers would be employed but they would be earning less labor income. In addition, although the unemployment rate falls as more workers are employed, it can also fall when fewer people look for jobs, either because they drop out of the labor force when discouraged or because they migrate to other locations. The necessary data to explore these issues is only available at the state and county levels, and not at the city level. However, the existing evidence sheds significant light to explain the seemingly contradictory observation of declining MHI while unemployment rates are falling.

At the state level, the data shown in Table 3 indicates that although the number of farm workers is slightly lower during the dry years (compared to farm labor before the 2007–2009 Great Recession and also during the first recovery years of 2009 and 2010), the number of hours worked per week does not change much. The data also show, however, that the number of farm laborers expected to work more than 150 days per year is slightly lower during the dry years. So, statewide the evidence suggests lower farm employment working fewer days per year but working the same number of hours per week.

Number of Employed Expected to be Employed Number of Hours Workers 150+ days <149 days Worked 2006 183,000 149,000 34,000 44.6 2007 177,000 139,000 38,000 45.7 2008 173,000 139,000 34,000 45.8 2009 157,000 124,000 33,000 42.1 2010 192,000 156,000 36,000 44.3 2011 185,000 150,000 35,000 43.6 2012 162,000 129,000 33,000 46.5 2013 181,000 144,000 37,000 43.8 2014 169,000 133,000 36,000 45.1 Table 3 California Farm Labor (2006-2014)16 (USDA, 2015)

At the county level, the data is mixed but also more enlightening in some cases as shown in Table 4. Data on farm labor reveal at least three salient facts:

1. With the exception of Tulare, in all other counties the farm employment estimates show an increasing trend during the drought. This observation mirrors the behavior of the overall unemployment rate. 2. In five of eight SJV counties (Kern, Madera, Merced, San Joaquin and Tulare) the mean hourly wage of farm workers fell during the dry years below its peak in either 2010 or 2011. 3. In the same counties where the mean hourly wage of farm workers fell, the mean annual wage also fell during the dry years below its peak in either 2010 or 2011.

The importance of these observations cannot be overstated. Both falling hourly wage and annual wage, as well as working fewer days per year, could partially explain the fall in MHI despite declining unemployment rate, particularly in those disadvantaged communities that heavily depend on agriculture and that have faced significant reductions in surface water for the last three years.

In Table 4, the dry years (2012, 2013, 2014) are shaded in grey, with the peak year (2010, 2011) immediately above for comparison.

16 Shadow indicates drought years (2012, 2013, and 2014).

FRESNO MERCED Employment Mean Hourly Mean Annual Employment Mean Hourly Mean Annual Estimates Wage Wage Estimates Wage Wage 2006 17,350 $8.00 $16,632 2006 2,430 $7.96 $16,537 2007 16,960 $8.01 $16,664 2007 2,050 $7.82 $16,265 2008 21,360 $8.49 $17,680 2008 3,000 $8.56 $17,794 2009 22,990 $8.83 $18,375 2009 2,770 $8.90 $18,521 2010 25,220 $8.98 $18,670 2010 2,770 $9.22 $19,167 2011 23,440 $9.03 $18,785 2011 1,740 $9.08 $18,869 2012 22,670 $9.05 $18,821 2012 2,200 $8.88 $18,467 2013 25,440 $9.00 $18,724 2013 2,560 $8.77 $18,240 2014 24,870 $9.18 $19,085 2014 3,570 $8.81 $18,336 KERN SAN JOAQUIN Employment Mean Hourly Mean Annual Employment Mean Hourly Mean Annual Estimates Wage Wage Estimates Wage Wage 2006 19,340 $8.00 $16,634 2006 6,570 $7.95 $16,535 2007 26,100 $7.94 $16,521 2007 4,910 $8.12 $16,879 2008 25,820 $8.34 $17,350 2008 6,090 $8.69 $18,073 2009 25,990 $8.67 $18,033 2009 5,790 $9.13 $18,992 2010 25,890 $9.05 $18,825 2010 5,120 $9.31 $19,373 2011 20,560 $9.21 $19,148 2011 4,880 $9.05 $18,842 2012 25,390 $9.12 $18,968 2012 4,970 $8.89 $18,493 2013 29,840 $8.95 $18,630 2013 4,650 $8.80 $18,310 2014 36,590 $8.98 $18,680 2014 6,170 $8.82 $18,356 KINGS STANISLAUS Employment Mean Hourly Mean Annual Employment Mean Hourly Mean Annual Estimates Wage Wage Estimates Wage Wage 2006 2,490 $8.51 $17,706 2006 5,730 $8.21 $17,085 2007 3,700 $8.55 $17,780 2007 4,630 $8.27 $17,206 2008 5,220 $9.43 $19,621 2008 3,470 $8.48 $17,639 2009 3,240 $9.66 $20,107 2009 3,890 $8.83 $18,371 2010 2,860 $9.81 $20,417 2010 4,330 $9.29 $19,325 2011 2,970 $9.60 $19,963 2011 4,610 $9.43 $19,612 2012 1,980 $9.52 $19,786 2012 5,060 $9.12 $18,986 2013 2,710 $9.75 $20,284 2013 4,820 $9.33 $19,403 2014 2,190 $10.18 $21,170 2014 5,860 $9.52 $19,814 MADERA TULARE Employment Mean Hourly Mean Annual Employment Mean Hourly Mean Annual Estimates Wage Wage Estimates Wage Wage 2006 4,120 $8.34 $17,351 2006 12,540 $8.37 $17,418 2007 5,380 $8.30 $17,268 2007 17,530 $8.35 $17,380 2008 5,470 $8.41 $17,495 2008 16,620 $8.84 $18,362 2009 5,300 $8.76 $18,219 2009 19,040 $9.16 $19,044 2010 5,090 $8.98 $18,658 2010 17,180 $9.45 $19,648 2011 4,810 $9.04 $18,807 2011 20,170 $9.70 $20,187 2012 3,680 $8.96 $18,639 2012 21,730 $9.55 $19,859 2013 5,590 $8.92 $18,559 2013 19,780 $9.33 $19,399 2014 6,180 $8.92 $18,549 2014 18,280 $9.56 $19,895

Table 4 Farm Labor in SJV Counties (2006-2014) (CA EED, 2015b)

As discussed earlier, it is possible that a number of workers in the SJV, discouraged by the challenging economic and labor conditions generated by the drought, decide to migrate to other places. Some migrate to other cities within the SJV while others migrate to other states and even other countries, as is the case of many foreign workers either temporarily or permanently returning to their home countries.

As shown in Table 5, the data show a mixed record:

1. In all SJV counties the population increased at an average growth rate of 0.7% during the three years of the drought. This figure is not much different from the population growth rates registered before the drought. However, the average population growth rate for the SJV disguises what happened in individual counties. For example in Kings County, the population actually decreased during the last three years. 2. With the exception of Madera and San Joaquin counties, all other counties show a significant large net number of people leaving during the three drought years (net domestic migration). This suggests that some residents decided to move somewhere else within the country, possibly in pursuit of better working and living conditions. 3. All SJV counties exhibit a large net number of foreign immigrants during the three drought years. The motivation to migrate into the counties from abroad during the drought years is not clear. For some migrant workers, the working and living conditions in their home countries are worse than in the SJV despite the drought. For others, perhaps the drought coincided with other non-economic factors such as those undergoing family reunification processes. 4. During the drought years, in most of the counties the balance between net domestic migration and net foreign migration is negative, which means a decrease in the county population. The population decrease due to immigration is relative small in some counties (like in Fresno, San Joaquin, and Stanislaus counties) and relatively large in others (such as Kings and Tulare counties).

In sum, the evidence indicates that in those counties where agriculture plays a relatively major role in the economy, the decrease in MHI can be partially explained by a decrease in the mean hourly wage paid to farm workers as well as a fall in the number of farmers expected to work more than 150 days per year. Also, the evidence suggests that, as consequence of the drought and in pursuit of better working and living conditions, some workers decided to migrate to locations outside the SJV.

Net Net Population Percent Numeric Natural Net Foreign Domestic County (July 1) Change Change Births Deaths Increase Migration Immigration Migration 2010 932,343 0.2% 1,893 3,893 1,539 2,354 ‐461 121 ‐582 2011 939,329 0.8% 6,986 16,312 5,975 10,337 ‐3,351 847 ‐4,198 FRESNO 2012 948,453 1.0% 9,124 15,946 6,251 9,695 ‐571 1,570 ‐2,141 2013 956,967 0.9% 8,514 15,721 6,514 9,207 ‐693 2,172 ‐2,865 2014 967,491 1.1% 10,524 16,016 6,703 9,313 1,211 2,104 ‐893 2010 841,158 0.2% 1,527 3,485 1,316 2,169 ‐642 114 ‐756 2011 848,880 0.9% 7,722 14,400 5,391 9,009 ‐1,287 741 ‐2,028 KERN 2012 855,974 0.8% 7,094 14,204 5,228 8,976 ‐1,882 1,447 ‐3,329 2013 865,511 1.1% 9,537 14,416 5,642 8,774 763 1,926 ‐1,163 2014 872,322 0.8% 6,811 13,926 5,814 8,112 ‐1,301 1,865 ‐3,166 2010 152,693 ‐0.2% ‐289 568 192 376 ‐665 14 ‐679 2011 151,685 ‐0.7% ‐1,008 2,576 752 1,824 ‐2,832 99 ‐2,931 KINGS 2012 150,643 ‐0.7% ‐1,042 2,394 813 1,581 ‐2,623 197 ‐2,820 2013 150,507 ‐0.1% ‐136 2,464 801 1,663 ‐1,799 235 ‐2,034 2014 149,788 ‐0.5% ‐719 2,356 849 1,507 ‐2,226 229 ‐2,455 2010 151,318 0.3% 453 574 276 298 155 13 142 2011 152,019 0.5% 701 2,438 1,007 1,431 ‐730 93 ‐823 MADERA 2012 151,242 ‐0.5% ‐777 2,376 1,045 1,331 ‐2,108 172 ‐2,280 2013 152,857 1.1% 1,615 2,288 1,048 1,240 375 235 140 2014 154,278 0.9% 1,421 2,284 1,116 1,168 253 227 26 2010 255,886 0.0% 93 1,067 373 694 ‐601 31 ‐632 2011 259,186 1.3% 3,300 4,299 1,452 2,847 453 215 238 MERCED 2012 261,002 0.7% 1,816 4,303 1,580 2,723 ‐907 414 ‐1,321 2013 262,336 0.5% 1,334 4,188 1,612 2,576 ‐1,242 566 ‐1,808 2014 265,069 1.0% 2,733 4,240 1,686 2,554 179 548 ‐369 2010 686,576 0.2% 1,270 2,546 1,155 1,391 ‐121 123 ‐244 2011 692,713 0.9% 6,137 10,545 4,719 5,826 311 858 ‐547 SAN JOAQUIN 2012 697,758 0.7% 5,045 10,081 4,957 5,124 ‐79 1,605 ‐1,684 2013 702,669 0.7% 4,911 10,047 4,957 5,090 ‐179 2,018 ‐2,197 2014 711,797 1.3% 9,128 9,940 5,057 4,883 4,245 1,954 2,291 2010 515,183 0.1% 730 1,922 927 995 ‐265 78 ‐343 2011 518,178 0.6% 2,995 7,781 3,650 4,131 ‐1,136 520 ‐1,656 STANISLAUS 2012 523,126 1.0% 4,948 7,694 3,787 3,907 1,041 995 46 2013 526,549 0.7% 3,423 7,503 3,844 3,659 ‐236 1,224 ‐1,460 2014 530,327 0.7% 3,778 7,462 4,052 3,410 368 1,187 ‐819 2010 443,086 0.2% 907 1,852 688 1,164 ‐257 49 ‐306 2011 447,591 1.0% 4,505 8,149 2,847 5,302 ‐797 358 ‐1,155 TULARE 2012 452,301 1.1% 4,710 8,019 2,820 5,199 ‐489 700 ‐1,189 2013 455,376 0.7% 3,075 7,764 2,850 4,914 ‐1,839 970 ‐2,809 2014 459,176 0.8% 3,800 7,531 2,956 4,575 ‐775 939 ‐1,714

Table 5 Population Estimates and Components of Change by County (2010-2014)17 (California Department of Finance, Demographic Research Unit, 2015)

17 Shadow indicates drought years (2012, 2013 and 2014). Natural increase = Births - Deaths Net Migration = Net Foreign Migration - Net Domestic Migration Numeric Change = Natural Increase + Net Migration

Impact of the Drought on Food Prices

According to the USDA Economic Research Service [USDA ERS], it is not totally clear yet the extent at which the ongoing drought will drive up current and future food prices. While it is clear that “…the impact of the drought on food prices depends on its severity, the impact it has on production, and the acreage and planting decisions of California farmers” is less clear, and less able to be clarified (USDA ERS, 2014). It is reasonable to expect that higher production costs— due to the cost and availability of water—will drive food prices up. Droughts in California are typically linked to higher retail food prices. However, the price effects of higher production costs do not occur immediately. As the USDA ERS further explains, “…price increases associated with a drought are lagged due to the time it takes for weather conditions and planting decisions to alter crop production.” The complexity in isolating the effect of the California drought on food prices is compounded by an assorted list of domestic and international factors. These include for example the pressure observed in the cattle and beef markets after the cold weather of 2013, the ongoing drought conditions in Texas and Oklahoma, and the domestic and foreign appetite for non-traditional crops driving demand and prices up and thus influencing farming decisions.

Although neither the extent nor the timing at which the ongoing drought will drive food prices up is fully understood yet, examining the behavior of food prices and its impact on residents in the SJV is relevant for at least two reasons. First, the magnitude, duration, and point in time in which food prices go up vary across the several droughts that California has sustained over the years. Yet, California droughts have historically been associated with higher food prices, that is, food prices eventually increase. Second, the evidence regarding the negative impact of higher food prices on low-income people is undeniable. Low-income people spend a larger share of their income on food and thus, when facing a food price spike, the income available to buy other items is reduced. Conversely, people with higher income levels spend a smaller share of their income on food and thus a food price surge does not impact them as much as low-income people.18 This means that the economic impact of the drought is felt in two ways, as producers of food (the impact is felt through job loss, working less, receiving a lower wage), and as consumers of food (the impact is felt through having to purchase food at higher prices).

Food inflation for the period 2006–2014 is shown in Table 6 for a variety of items classified by the U.S. Bureau of Labor Statistics (BLS). The forecast figures are produced by the USDA ERS. The forecast for 2015 looking at “All food” items indicates normal food price inflation, with retail prices expected to rise 2.5% to 3.0% over 2014 levels, which is ordinary according to its 20-year historical average. In fact, the forecast is for most individual food price categories to increase around their historical average.

18 Economists call this observation Engel’s Law, according to which as income rises, the proportion of income spent on food falls, even if actual expenditure on food rises.

20-Year Forecast Item Historical 2006 2007 2008 2009 2010 2011 2012 2013 2014Average 2015

All food 2.4 4.0 5.5 1.8 0.8 3.7 2.6 1.4 2.4 2.6 2.0 to 3.0

Food away from home 3.13.64.43.51.32.32.82.12.42.7 2.0 to 3.0

Food at home 1.74.26.40.50.34.82.50.92.42.6 2.0 to 3.0 Meats, poultry, and fish 0.83.84.20.51.97.43.62.17.23.1 3.0 to 4.0 Meats 0.73.33.5-0.62.88.83.41.29.23.3 3.5 to 4.5 Beef and veal 0.8 4.4 4.5 -1.0 2.9 10.2 6.4 2.0 12.1 4.1 5.0 to 6.0 Pork -0.2 2.0 2.3 -2.0 4.7 8.5 0.3 0.9 9.1 2.8 2.0 to 3.0 Other meats 1.8 2.3 3.1 2.3 -0.1 6.4 1.7 -0.1 3.9 2.4 2.5 to 3.5 Poultry -1.8 5.1 5.0 1.7 -0.1 2.9 5.5 4.7 2.0 2.6 2.5 to 3.5 Fish and seafood 4.74.65.93.61.17.12.42.55.82.9 2.5 to 3.5 Eggs 4.9 29.2 14.0 -14.7 1.5 9.2 3.2 3.3 8.4 4.3 2.5 to 3.5 Dairy products -0.5 7.4 8.0 -6.4 1.1 6.8 2.1 0.1 3.6 2.8 2.5 to 3.5

Fats and oils 0.2 2.9 13.8 2.3 -0.3 9.3 6.1 -1.4 0.1 2.8 0.0 to 1.0 Fruits and vegetables 4.8 3.8 6.2 -2.1 0.2 4.1 -0.6 2.5 1.5 3.0 2.5 to 3.5 Fresh fruits & vegetables 5.3 3.9 5.2 -4.8 0.7 4.5 -2.0 3.3 1.9 3.1 2.5 to 3.5 Fresh fruits 6.0 4.5 4.8 -6.1 -0.6 3.3 1.0 2.0 4.8 3.0 2.5 to 3.5 Fresh vegetables 4.63.25.6-3.42.05.6-5.14.7-1.33.2 2.0 to 3.0 Processed fruits & vegetables 2.9 3.6 9.5 6.6 -1.3 2.9 3.8 0.3 0.1 2.8 2.5 to 3.5 Sugar and sweets 3.8 3.1 5.5 5.6 2.2 3.3 3.3 -1.7 -0.8 2.2 1.5 to 2.5 Cereals and bakery products 1.8 4.4 10.2 3.2 -0.8 3.9 2.8 1.0 0.2 2.6 0.5 to 1.5 Nonalcoholic beverages 2.1 4.1 4.3 1.9 -0.9 3.2 1.1 -1.0 -0.5 1.5 2.0 to 3.0 Other foods 1.4 1.8 5.2 3.7 -0.5 2.3 3.5 0.5 1.0 2.0 1.5 to 2.5

Table 6 Changes in Food Price Indexes (2006-2015)19 (U.S. Department of Labor, Bureau of Labor Statistics 2015, USDA ERS, 2015)

However, the data also illustrate at least three more salient facts. First, prices in the “All food” category increased 2.4% in 2014, which is closer to the 20-year historical average of 2.6% than in 2013. Although still premature to call it a trend, the actual price increase in 2015 is likely to reveal more information about the impact of the drought on all food prices, particularly if it surpasses the historical average. Second, similarly to the all food category, prices in the fresh fruits category increased 4.8% in 2014, which is not only above the 20-year historical average of 3.0%, but also shows an upward trend during the drought years. Third, the forecast by USDA ERS indicates that the price of meats in general is expected to increase beyond the 20-year historical average. The price forecast for beef and veal in particular is predominantly high, and the price forecast for pork almost as high.

In summary, although for some food categories the data suggest that prices are increasing during drought years, the USDA ERS’s overall assessment regarding the unknown nature of the extent of the impact of the drought on overall food prices seems appropriate. The evidence is still

19 Shadow indicates drought years (2012, 2013, and 2014).

inconclusive and the complexity to separate the impact of the drought on prices from other important factors represents a major challenge.

The current inability to accurately evaluate the impact of the drought on food prices, however, is independent from the impact of increasing food prices on households (regardless of whether food price increases are drought-driven or not), particularly among low-income residents of the SJV. Assessing this impact has its own complexities and thus represents an entirely different challenge. For example, since poor households can be both producers and consumers of food, they are impacted in different ways by food price increases depending on their net consumption status and on the food items they consume and produce. In general, it can be expected that food price increases hurt poor households that are net food buyers while benefiting those that are net food sellers. Thus, it can be argued that the net impact on welfare in any given community (either a county or a city in the eight counties) depends of the magnitude of these two forces. Further, it can also be argued that the impact on welfare substantially depends on the products involved and the policy response of different communities. An analysis of this nature falls outside the scope of this report, but it is mentioned as a potential future line of research.

Summary

This segment of the report examined the behavior of unemployment rates, MHI levels, migration patterns, and food prices in the eight counties that comprise the SJV. A more comprehensive economic impact analysis should look beyond agriculture to include other sectors such as manufacturing, recreation and tourism, and energy production, among others. That more inclusive examination should also look at the impact of the drought on urban areas and on the environment. During the drought of 1987–1992 for example, the Institute for Water Resources, Water Resources Support Center, and the U.S. Army Corps of Engineers commissioned a study aimed at articulating the lessons learned from the drought (Dziegielewski, Garbharran, & Langowski, 1993). The structure and content of this report could be the starting point of a similar analysis of the current drought.

Despite the more limited scope of this segment of the report however, the analysis provides valuable information. The findings indicate that the observed fall in MHI in some counties and in most disadvantaged communities during the drought years is due to a combination of job loss, lower hourly wage, and lower annual wages paid to farm workers, as well as working fewer days per year. The evidence also suggests that as a consequence of the drought some workers decided to migrate to locations outside the SJV, possibly in pursuit of better working and living conditions. These patterns could explain why the MHI is falling at the same time that the unemployment rate is decreasing. In addition, although it is not totally clear at what extent overall food prices will go up as consequence of the drought, the data indicates that the price of some food items has increased during the dry years. This is relevant from the consumer perspective, particularly for low-income households that spend a larger share of their income on food, because a food price surge can significantly impact their disposable income.

SNAPSHOT: WHO ARE THEY? Moving from Economic Impact to Human Impact by Gillisann Harootunian, PhD In the preceding chapter, the author clarifies how the 2014 average unemployment rates for Disadvantaged Communities such as Avenal, Delano, and Mendota are significantly higher than those for the San Joaquin Valley. The unemployment (and under-employment) rates discussed in that chapter constitute one of the economic impacts of the drought. What of the human impact from those economic ones? Who lives in Avenal, Delano, and Mendota? Who are they? How will the reduced—or eliminated—wages affect them? Their families? Their ability to pay for medical care? Or for a post-high school work certificate so they can re-enter the workforce? One way to begin to think about the answers to such questions is to take a demographic “snapshot” of the populations of Avenal, Delano, and Mendota. When a water drought occurs, how thick or thin is the margin of safety for those residents who are already living in a financial drought? Avenal Delano Mendota CA State Population: General Profile Total 15,505 53,041 11,014 37,253,956 Male 72.4% 59.9% 55.3% 49.7% Female 27.6% 40.1% 44.7% 50.3% Ethnicity/Race (alone or combination) Hispanic or Latino 71.8% 71.5% 96.6% 37.6% White 40.8% 39.1% 55.6% 57.6% African American 10.8% 8.2% 1.4% 7.2% Institutionalized [male prison] 41.4% 20% N/A 0.8% Institutionalized [female prison] N/A 0.2% N/A 0.3% Foreign born (5 years and older) 44.8% 41.3% 60.7% 28.8% Not a U.S. citizen 38.6% 29.7% 53.2% 15.2% Naturalized U.S. citizen 6.1% 11.6% 7.5% 13.6% Economic Profile Unemployed 20.4% 16.2% 27.1% 11.5% No Health Insurance (civilian non- 30.4% 27.4% 39.4% 17.8% institutionalized population) No Health Insurance – Employed 43.9% 38.8% 64.2% 21.2% Median Household Income $28,794 $35,122 $24,264 $61,094 Median Family Income $29,811 $35,643 $24,621 $69,661 Income Below Poverty Level in Past 12 40% 27.6% 44.3% 12% Months – All Families Educational Profile: Population 25 years and older Less than 9th grade 29.3% 26.9% 57.2% 10.2% High school graduate (includes equivalency) 23.5% 27.6% 15.5% 20.7% Associate’s Degree 3% 3.3% 2.4% 7.8% Bachelor’s Degree or Higher 4% 6.8% 1.6% 30.7% Sources: U.S. Census 2010; 2009-2013 American Community Survey 5-Year Estimates

72 SNAPSHOT: THE SHADOW ECONOMY How To Document the Undocumented? By G. Harootunian, PhD Many farm workers are undocumented in the San Joaquin Valley. How to grasp the impact of the under-employment described in the preceding chapter on people who live in the shadow economy? One way would be to look at the raw data available from the U.S. Department of Labor. Below, selected data is given for both U.S. Farm Workers and for Farm Labor Contractors (the intermediaries who supply farm labor to the farmers). Also, the categories used by California Farm Labor Contractor Association provide a lens to view the economic tier structure: In good years, large farmers and farm labor contractors make billions. Medium farmers and farm labor contractors make millions. Small farmers and farm labor contractors can make tens or even hundreds of thousands. The undocumented farm worker: $10,000 per year, or less, with minimal use of benefits. U.S. DOL: Registered Farm Labor Contractor Listing # U.S. % U.S. % CA Farm Labor Contractors Headquartered in U.S. 9,336 100% N/A Farm Labor Contractors Headquartered in CA 4,060 43% 100% Farm Labor Contractors Headquartered in Avenal, CA 79 0.85% 1.94% Farm Labor Contractors Headquartered in Delano, CA 116 1.24% 2.86% Farm Labor Contractors Headquartered in Mendota, CA 127 1.36% 3.13% California Farm Labor Contractor Association – Categories [May 2015] Small Farm Labor Contractor1 Under $2M annual total payroll Medium Farm Labor Contractor $2M - $5M annual total payroll Large Farm Labor Contractor Over $5M annual total payroll U.S. Department of Labor: “National Agricultural Workers Survey” Annual Median Income: Farm Workers Permanent Resident/Green Card Holder $7,500-$10,000 Work Authorization (e.g., Amnesty, Family Unity) $5,000-$7,500 Unauthorized2 $2,500-$5,000 Living Below Poverty Line: Farm Workers U.S. Citizen 46% Legal Permanent Resident 54% Work Authorization (e.g., Amnesty, Family Unity) 68% Unauthorized 80% Unemployment Insurance [used]: Farm Workers U.S. Citizen (able to secure non-farm work) 17% Legal Permanent Resident 46% Other Work Authorized 32% Unauthorized 5%

1 The “Small Farm Labor Contractor” category hides the smallest of these, ex-farm workers who create their own small business as farm labor contractors. See Philip L. Martin’s “Migration and U.S. Agricultural Competitiveness” for an analysis of the precarious situation of these small farm labor contractors. 2 Editor’s Note: While such families can survive and send money back home by doubling up in good times, in bad times, families might have to squeeze in 3 or 4 together in a small house.

SNAPSHOT: Food Insecurity in the San Joaquin Valley By Gil Harootunian The preceding chapter also analyzed a potential surge in food prices, which impacts most low income households who spend a larger proportion of their income on food. What is the state of food insecurity in the San Joaquin Valley? These percentages are given by the UCLA Center for Health Policy Research’s “Health Profiles” in 2012-201322 (the beginning of the drought). State/County Food Insecurity* California 15.7% Fresno 25.2% Kern 26% Kings 18.6% Madera 29.3% Merced 19.2% San Joaquin 20% Stanislaus 21.8% Tulare 23.6% *Defined as adults who had difficulty reliably putting food on the table in the past year. The question assumes that adults who are above 200% of the federal poverty level are food secure. A Video Vignette Sharing the Bounty: The Fresno State Student Cupboard [Food Pantry] In November 2014, Fresno State opened “The Student Cupboard” as one of many initiatives in its new Food Security Project. The project aims to be a national model for universities and colleges to keep students fed and focused. The video vignette below captures its opening day: http://www.fresnostate.edu/magazine/sharing-the-bounty/.

22 Most recently available data

Chapter 3 Water Usage and Residential Water Consumption in the California San Joaquin Valley (SJV)

Dr. Chih-Hao Wang, Department of Geography and City and Regional Planning

Abstract

In the San Joaquin Valley, water use for agriculture is much larger than that for other land uses (e.g. residential, industrial, and commercial). For this reason, this study begins with a preliminary analysis to assess and compare agricultural, industrial, and residential water use in all 58 counties of California, in the eight San Joaquin Valley counties, and in the remaining 50 counties outside of the San Joaquin Valley, throughout the previous decade.

This preliminary assessment reveals that residential water use in the San Joaquin Valley is not very significant when compared to agricultural water use. Documenting the level of residential water use in the SJV area, however, is important to inform public dialogue and policy making when the aim is to target precious time and resources to manage a potential long-term drought and long-term water use in general. Furthermore, the level of significance of residential water use does not preclude efforts to encourage residential awareness and use of water as a finite resource, nor does it preclude application of the analysis at different levels (especially county level vs. municipal level).23 Nor does the level of significance of residential water use mitigate the fact that every person is a stakeholder in a situation of water scarcity.

Finally, residential water use is important because it is a factor in water scarcity. From 2000 to 2010, California’s population increased by 10%, and the San Joaquin Valley’s population doubled that rate at 20%. The San Joaquin Valley population is predicted to increase further, and such growth exacerbates water scarcity in a drought. Less and less water can be used to support all uses of water (agriculture, industrial, and residential) for the increased population. Therefore, improving residential water use efficiency plays an important part in comprehensive planning and preparation for a potential long-term drought.

Coping with municipal water scarcity has become a new research focus in city and regional planning. To mitigate the impacts of water scarcity, it is extremely important to improve our understanding of the relationships between development-induced water consumption and demographic characteristics and features of the built environment (building attributes, the presence or absence of pools, and yard sizes). A spatial statistical analysis on residential water

23 Editor’s Note: Residential water use can be significant at the municipal level when keen and immediate economic and human impacts can be felt from water scarcity. For example, the City of Fresno, the 5th largest city in California, struggled during the recent and prolonged recession, and as the aquifer levels have dropped, the costs of pumping water from increasing depth became increasingly punitive for the City. As the case of East Porterville shows, water scarcity—to the point of running out of water for domestic consumption-—can have dramatic immediate human impact (see video vignette, page 126).

consumption in Fresno neighborhoods will illustrate these relationships to help inform policy makers about water conservation strategies.

A small water consumption survey was conducted as a Fresno State class project (Geography 184) in spring 2015. The “Residential Consumption Water Survey” was administered to 60 households in Fresno and Clovis during the months of February and March.24 Survey questions related to water consumption include indoor and outdoor physical conditions of the house and socioeconomic factors of the household. Below are the multiple interesting findings, with recommendations to encourage residential water savings through incentives based on the understanding of water-use behavior and through innovations being integrated into the policy- making process.

Findings related to outdoor physical conditions, with summary recommendations: 1. Houses facing south consumed more water in the summer. This could be improved by better site planning to consider the effects of summer sunshine on water demand, including the setting of buildings and yards. 2. Houses with sprinkler irrigation systems consumed more water, particularly in the summer. Improved sprinkler design for all landscape plants (including water wise plants) could help to reduce water consumption. 3. Houses with a pool consume slightly more water than those without a pool in both summer and winter. This also could be improved through incentives to encourage water conservation (e.g., use of pool covers to reduce evaporation).

Findings related to indoor physical conditions: 1. More water consumption was measured by the number of bathrooms, with a strong positive relationship found in both the winter and summer. Water saving innovations for toilets and all faucets would be helpful for reducing this aspect of water consumption. 2. Household size does not seem to have clear impacts on water consumption, though this lack of finding may result from the small size of the survey. 3. Household income also does not seem to have clear impacts on water consumption except for the highest category ($60,000-plus), most likely from the presence of a pool and the size and condition of the yard (outdoor physical conditions). This lack of finding may also results from the small size of the survey.

Findings related to non-physical conditions: 1. Self-perception. Respondents who ranked themselves as moderate water users actually consume as much or more water than those who ranked themselves as heavy water users. Therefore, water use education to correct self-perception would be helpful to promote awareness of water scarcity. 2. Neighborhood social effects. Water consumption of a given household is likely affected by its neighbors for winter water consumption. The timing of the survey precluded findings for summer water consumption. Moreover, the size of the survey used is small for the spatial regression modeling. The spatial lag model, however, clearly shows that residential winter water use is positively affected by the way your neighbors use water (as

24 This is the end of the cooler rainy season.

well as by the number of bathrooms). Integrating neighborhood social effects with water saving innovations may be helpful in the policy-making process.

Finally, findings in this survey indicate a need to conduct a large-scale residential summer water consumption survey to gather sufficient data for further analyses and to provide sufficient planning information for the potential long-term drought. The resulting information could help with reducing water consumption not only in the San Joaquin Valley, but in all of California.

San Joaquin Valley (SJV) vs. Non-SJV Water Use Changes from 2000 to 2010

A preliminary analysis was conducted to assess and compare agricultural, industrial, and residential water use within the SJV throughout the previous decade, and then to compare those findings with levels of water use in the rest of the state. This makes clear longer term patterns of water use and provides a good lens through which to view the results of the Fresno State survey. Simply put, the analysis will reveal the SJV consumes more water for a smaller population, and the rate of population increase in the SJV is more significant than in non-SJV. The potential long-term drought will eventually have huge impacts in this region not only on agriculture but also on the increased population.

The analysis also suggests both the extent of water scarcity in the SJV and its heavy dependence on water. The analysis also reiterates that in the SJV residential water use is insignificant compared to agricultural water use but as a discrete category residential water use is significant and presents an opportunity for savings. The scale is also important to ascertain to inform public discussion and prioritize effort in policy making. We examine changes in water use from 2000- 2010. Unfortunately, we do not have data to examine changes in water use from 2010 to 2015.

The county level was selected as the geographical unit for regional water-use analysis, with a total of 58 observations in California (58 counties). The US Geological Survey (USGS) Water Data from 2000 to 2010 was used for the spatial analysis. Table 1 presents descriptive statistics for all the water uses for the SJV and non-SJV regions over different time periods. California’s population increased by 3.4 million in 2000-2010, with about a 3% (1.1 million) increase from 2005 to 2010 and approximately 6% (2.3 million) from 2000 to 2005. The population growth rate in the SJV (20%) is much larger than that (9%) in the non-SJV region during this 10-year time period. With California’s total population increase of 3.4 million, an increase in water use would be expected. Surprisingly, total water use decreased by 11% from 2000 to 2005, and decreased even more (-17%) from 2005 to 2010. The reasons for this water use reduction might include changes in water use behavior, new technologies, and economic changes. However, it might be simply caused by water scarcity in recent years. In other words, the water demand for the increased population is mostly likely not satisfied. From 2005 to 2010, it is interesting that the reduction of total water use in the SJV (-3%) is much smaller than that in the non-SJV region (-24%). This implies that the SJV strongly depends on water (mostly likely due to its intensive agricultural activities).

Year 2010 2005 2000 # % # % # CA - total population (millions) 37254 3% 36132 6% 33872 San Joaquin Valley population (8 counties) 3972 6% 3743 13% 3303 Other County (OT) population (50 counties) 33282 3% 32389 6% 30569 CA - total water use (Mgal/day) 37962 (-17%) 45720 (-11%) 51173 SJV water use (8 counties) 14512 (-3%) 14980 (-11%) 16810 OT water use (50 counties) 23450 (-24%) 30739 (-11%) 34363 Table 1 Total Water-Use Growth in California (SJV vs. Non-SJV) from 2000 to 2010

The above analysis on all water use can be analyzed further by examining water use separately in the two major sources: groundwater and surface water. Table 2 shows that statewide groundwater use decreased by 29% from 2000 to 2005, but increased by 16% from 2005 to 2010, most likely due to the drought. However, groundwater use in 2010 is still lower than that in 2000. On the other hand, statewide surface-water use decreased by approximately 30% in total from 2000 to 2010, more evidence for recent water scarcity. In the SJV, surface water use decreased at a lower rate (-9%) than in the non-SJV region (-34%) from 2005-2010. Moreover, in 2010, the SJV relied more on surface water (8825 Mgal/day) than on groundwater (5687 Mgal/day) to maintain its economic activities. Farmers might use surface water as much as possible to lower their costs (e.g., more energy is consumed to pump groundwater from increasing depths). However, interview results indicated that small farmers have been able to access only groundwater in recent years.

From the regional policy-making viewpoint, it is an extremely important to improve the efficiency of the surface water delivery system particularly in the SJV where reliance on it can be pronounced. This does not mitigate the need to regulate groundwater use also since it has become the major water source for agriculture. Moreover, both recommendations though given urgency by the extent of agriculture in the SJV would also improve results in water use efficiency and conservation for all uses, including residential and industrial.

Finally, examining irrigation water use in the State, in the eight SJV counties, and in the 50 non- SJV counties indicates the importance of the role that water for irrigation plays in the SJV. From 2000 to 2010, California’s total irrigation water use decreased by 24%. In the SJV, irrigation water use decreased by 17% from 2000 to 2005, but increased by 2% from 2005 to 2010. In the non-SJV region, irrigation water use decreased by a total of 34% from 2000-2010. In 2010, for instance, irrigation water used in the eight SJV counties (13,184 mgal/day) is about 1.3 times the amount used in the other 50 counties total in 2010 (9,872 mgal/day), reinforcing the heavy economic dependence in the SJV on it.

Year 2010 2005 2000 # % # % # CA - groundwater use (Mgal/day) 12652 16% 10951 (-29%) 15395 SJV groundwater use (8 counties) 5687 (-9%) 5236 (-34%) 7977 OT groundwater use (50 counties) 6965 (-22%) 5721 (-23%) 7419 CA - surface-water use (Mgal/day) 25311 (-27%) 34763 (-3%) 35777 SJV surface-water use (8 counties) 8825 (-9%) 9745 10% 8833 OT surface-water use (50 counties) 16486 (-34%) 25018 (-7%) 26944 CA - Irrigation water use 23056 (-5%) 24364 (-20%) 30497 SJV irrigation water use (8 counties) 13184 2% 12940 (-17%) 15503 OT irrigation water use (50 counties) 9872 (-14%) 11424 (-24%) 14994

Table 2 Ground, Surface, and Irrigation Water-Use Growth in California (SJV vs. Non-SJV) from 2000 to 2010

Before moving into the discussion of the regional patterns revealed by this preliminary analysis of water use intra-SJV and extra-SJV, it should be noted that as compared to agriculture, changes in domestic and industrial water use are not very significant in all regions (Table 3). The USGS does not even provide complete data on public-supplied water use. In the SJV, public-supplied and self-supplied domestic water use is a smaller percentage of total water use than in the non- SJV. Both public-supplied and self-supplied domestic water use show a decrease from 2005- 2010 while self-supplied industrial water use shows a sharp increase.

Year 2010 2005 2000 CA - total water use (Mgal/day) 37962 45720 51173 SJV water use (8 counties) 14512 14980 16810 OT water use (50 counties) 23450 30739 34363 CA - domestic public-supplied water use 3866 3984 − SJV domestic public-supplied water use (8 counties) 530 590 − OT domestic public-supplied water use (50 counties) 3335 3393 − CA - domestic self-supplied water use 172 486 286 SJV domestic self-supplied water use (8 counties) 31 181 40 OT domestic self-supplied water use (50 counties) 141 304 246 CA - industrial self-supplied water use 400 96 202 SJV industrial self-supplied water use (8 counties) 81 2 52 OT industrial self-supplied water use (50 counties) 319 94 150 Table 3 Public- and Self- Supplied Water-Use Growth in California (SJV vs. Non-SJV) from 2000 to 2010

Water-Use Patterns: San Joaquin Valley (SJV) vs. Non-SJV in 2010

The average population of a county in the SJV (496,000) is slightly smaller than that in the non- SJV region (666,000), even though the population growth of the entire SJV from 2000 to 2010 (20%) is the double of the rate in the non-SJV region (9%) for the same period. However, the eight SJV counties use much more water (1,814 Mgal/day), on average, than the other 50 counties (469 Mgal/day). Simply put, the SJV consumes more water for a smaller population. The potential long-term drought will eventually have huge impacts in this region not only on agriculture but also on the increased population. Surface water use in the SJV makes up on average about 61% of total water use while groundwater use accounts for the other 39%. Similarly, surface water makes up about 64% of total water use in the non-SJV region while groundwater use represents the remanding 36%. Table 4 shows average population and water use for 2010.

The 2010 average irrigation water use of SJV counties (1,648 Mgal/day) is about eight times the average of non-SJV counties (197 Mgal/day). It is interesting to look at the share of water used for irrigation. Irrigation water use (1,648 Mgal/day) represents about 91% of the total water use (1,814 Mgal/day) for a county in the SJV while irrigation water use (197 Mgal/day) makes up only about 42% of the total (469 Mgal/day) for the other counties. Of irrigation water use (1,648 Mgal/day) in the SJV, about 64% (1,056 Mgal/day) is from surface water while the other 36% (592 Mgal/day) is from groundwater. For counties in the non-SJV region, about 60% of irrigation water (197 Mgal/day) is from surface water (118 Mgal/day), and 40% comes from groundwater (79 Mgal/day).

Average domestic water use is only 4% of total use in the SJV, but it is about 15% of total use for non-SJV counties. It should be noted that the average amount of domestic water use (70 Mgal/day) in the SJV is the same as that in the rest of California. Industrial water use is not a large share of total water use in either SJV or non-SJV counties. The difference in domestic and industrial water use between the SJV and the non-SJV region is mostly caused by irrigation use.

To conclude this preliminary analysis, in the SJV the importance of reducing residential water consumption through water-saving incentives is to help manage water through the potential long- term drought. This indicates the need for more research on residential water-use behavior and industrial water-use processes so that policy makers can design effective incentives to reduce water consumption.

Average water use in 2010 SJV Counties (8) Other Counties (50) Population (000s) 496 666 Total water use 1814 469 Total groundwater use 711 139 Total surface water use 1103 330 Irrigation water use 1648 197 Irrigation groundwater use 592 79 Irrigation surface water use 1056 118 Domestic water use 70 70 Industrial water use 10 6 Table 4 The Average Water Use in California (SJV vs. Non-SJV) in 2010

Residential Water Consumption in Fresno Neighborhoods

To mitigate drought impacts, residential water consumption needs to be reduced in the most efficient ways. Therefore, the ability to analyze water consumption behavior at the household level would help planners to target initiatives aimed at reducing water consumption (Troy and Holloway, 2004). Residential water consumption is affected by physical and socioeconomic factors. The physical factors can be separated into outdoor and indoor factors, such as lot size, the presence of pool, landscaping practices, number of bathrooms, and aspect, which is the direction a house faces (Domene and Sauri, 2006; Wentz and Gober, 2007; Janmaat, 2013). The socioeconomic characteristics related to household water consumption include household size, income, and family members’ perceptions of water use (Domene and Sauri, 2006; Wentz and Gober, 2007; Shandas and Parandvash, 2010; Janmaat, 2013).

A small survey on residential water consumption was conducted for neighborhoods around the Fresno State campus. Participants were asked to report their winter and summer water consumption in Hundred Cubic Fee/HCF (1 HCF = 100 cubic feet = 748.5 gallons) along with the aforementioned physical and socioeconomic factors. Summer water consumption might be affected more significantly than winter consumption by the aspect of the house and by use for pools and yard irrigation. Other factors included the size of the house, bathroom count, household size, and family income. The questionnaire is shown in the Appendix. Tables 5 and 6 present the descriptive statistics for the continuous and discrete water use factors, respectively. The average water consumption in the winter is 13 HCF while average summer use is 23 HCF, most likely due to increased water use for pools and yards. The house sizes range from 850 to 3300 square feet. The average house has two bathrooms and three household members.

Continuous variable Observation Mean Minimum Maximum Winter water consumption (wwc) 49 13 4 34 Summer water consumption (swc) 37 23 9 68 House size 49 1790 850 3300 Bathroom number 49 2 1 4 Household size 49 3 1 6

Table 5 Descriptive Statistics of Continuous Water Consumption Factors

Discrete variable Share (%) Pool 41% Water yard by sprinkler 84% Water yard by drip 10% Facing the north 31% Facing the west 28% Facing the east 22% Facing the south 19% Income larger than $60,000 44% Income between $40,000 and $60,000 25% Income between $25,000 and $40,000 19% Income between $15,000 and $25,000 12% Light water user 28% Moderate water user 59% Heavy water user 13% Table 6 Descriptive Statistics of Discrete Water Consumption Factors

Winter (wwc) and summer (swc) water consumption were compared against various factors (e.g., number of bathrooms, presence of pool), with the results shown in Figures 1 to 7.

Physical indoor conditions. Among indoor physical conditions, there is a clear linear trend between water consumption and number of bathrooms in both the winter and summer (Figure 1). The number of bathrooms can therefore be used to measure the indoor physical conditions. The bathroom count might be more suitable for representing the household-scale effects also because no clear patterns were found for other household size (number of persons) and household income (Figures 5 and 6). For example, three bathrooms in a house might drive water use more than there being four or five persons (household size) or an income of $40,000. Only household incomes exceeding $60,000 appeared to have a significant effect on water usage, most likely from the presence of a pool and/or the size and condition of the yard.

Outdoor physical conditions. The presence of a pool and the method of yard watering can be used to measure the outdoor physical conditions. Figure 2 shows households with a pool consume slightly more water than those without a pool in both summer and winter. Figure 3 clearly reflects the need to water landscape plants and yards in summer. The results show that using sprinklers is likely to consume more water than other yard-watering means such as hand watering and drip irrigation. House aspect is another physical factor related to water consumption. Figure 4 shows that south-facing houses consume more water, particularly in the summer.

Self-perception. Figure 7 indicates that participants’ perceptions of their water use are mostly consistent with their actual water consumption. However, the actual water consumption of self- described moderate users is no different from those who perceive themselves as heavy water users. Education on water conservation could improve the perceptions of self-described moderate water users, who are the majority (59%) compared to self-perceived light water users (28%) and self-perceived heavy water users (13%).

50 40 30 20 10 0 1234 mean of wwc mean of swc

Figure 1. Winter water consumption (wwc) and summer water consumption (swc) by number of bathrooms

25 20 15 10 5 0 01 mean of wwc mean of swc

Figure 2. Winter water consumption (wwc) and summer water consumption (swc) by the presence of pool (1: pool present; 0: no pool present) 25 20 15 10 5 0 01 mean of wwc mean of swc

Figure 3. Winter water consumption (wwc) and summer water consumption (swc) by the use of sprinklers (1: sprinklers used; 0: sprinklers not used)

40 30 20 10 0 1234 mean of wwc mean of swc

Figure 4. Winter water consumption (wwc) and summer water consumption (swc) by house aspect (1: East; 2: South; 3: West; 4: North)

40 30 20 10 0 $15000 to $25000 $25000 to $40000 $40000 to $60000 > $60000 mean of wwc mean of swc

Figure 5. Winter water consumption (wwc) and summer water consumption (swc) by household income

25 20 15 10 5 0 123456 mean of wwc mean of swc

Figure 6. Winter water consumption (wwc) and summer water consumption (swc) by household size 25 20 15 10 5 0 123 mean of wwc mean of swc

Figure 7. Winter and summer water consumption by water-use perception (1: light water user; 2: moderate water user; 3: heavy water user)

The most interesting part of this small survey was to apply spatial statistics to examine neighborhood social effects on residential water consumption. The basic assumption is that the water consumption of a given household will be affected by its neighbors’ water consumption. A spatial statistical model can capture such spatial autocorrelation between individuals or neighborhoods on a variety of factors (Wang, Akar, & Guldmann, 2015). Relevant water use research has found neighborhood social effects on summer water use for yard maintenance (Janmaat, 2013) and on policy-making for water saving innovations (Wentz and Gober, 2007). The presence of spatial autocorrelation could imply a spatial multiplier in connection with water saving innovations. Water policy makers might therefore want to consider neighborhood effects in conjunction with efforts to reduce water use.

Based on the small survey, a spatial lag model for winter water consumption has been constructed as shown in Equation 1.

Equation 1 WWC = 0.057·W·WWC+3.06·Bathroom Count where WWC represents the household winter water consumption, and W represents a spatial weight matrix based on a defined neighborhood structure to capture the neighborhood social effects. The spatial lag term W·WWC represents the neighbors’ water consumption within a 1.5- mile buffer around a given household.

Only the spatial lag term W·WWC and the variable Bathroom Count are statistically significant in this case, even though we have observed clear relationships between seasonal water consumption and several other physical and socioeconomic factors. This may be due to the small size of the survey we used for the spatial regression modeling. The spatial lag model, however, clearly shows that residential winter water use is positively affected by the number of bathrooms and the way your neighbors use water.

The methods of this model could be applied to neighborhood social effects on summer water use as well. Unfortunately, the responses to our survey were not sufficient to support. An important factor is the timing of conducting a water consumption survey is important. We found that many household participants could not provide their summer water consumption because they did not keep their summer water bills. Studying summer water use would likely prove valuable since people tend to use more water in the summer in the SJV. A further large-scale residential water consumption survey is needed to provide necessary water planning information.

Summary

California has been suffering from a severe drought problem, particularly the SJV where less and less water can be used to support existing activities. Obviously, agriculture takes the lion’s share of water use in the SJV and is definitely the first area of concern in a drought, representing about 91% of total water use. The findings outlined above demonstrating that residential water use is not very significant, however, can in itself inform public dialogue and education and inform policy making, especially when debating how to target precious time and resources when addressing a potential long-term drought.

In addition, while on the county level in the SJV municipal water use might be of little overall significance that does not preclude efforts to help improve residential awareness and use of water as a finite resource. Residential water saving could be encouraged by incentives based on the understanding of water use behavior. Residential water saving innovations could be integrated into a comprehensive policy-making process. Finally, residential water use is a factor in water scarcity.

A small water consumption survey from a class project was conducted to serve the above- mentioned purpose. The factors related to water consumption included indoor and outdoor physical conditions of the house and socioeconomic characteristics of the household. The results revealed several interesting findings. Among the outdoor physical conditions, the presence of pools and sprinkler systems resulted in higher water consumption, particularly in the summer. Also, the houses facing south used more water in the summer. These results all indicate that summer water use is highly related to outdoor physical conditions, implying the need for innovation related to summer water use. The indoor physical conditions related to water consumption are best measured by the number of bathrooms. A strong positive relationship has been found between the number of bathrooms and both the winter and summer water use. Again, water saving innovations for toilets and faucets would be most helpful for reducing water consumption. Household size and income do not seem to have clear impacts on water consumption. This result might be due to the small survey size, a problem which could be resolved by conducting a large-scale residential water consumption survey.

Two other important factors were included. First, examining people’s perception of their water use showed interesting results in that people who rank themselves as moderate water users actually consume as much or more water than those who think of themselves as heavy water users. Water conservation education could help to promote awareness of water scarcity.

Second, and most importantly, neighborhood social effects have become a new research focus for residential water use. The water consumption of a given household is likely affected by its neighbors, resulting in similar water use patterns across neighborhoods. This result was found in our spatial statistical model for winter water consumption. Modeling summer residential water consumption might have more interesting results, especially in a region such as the SJV, and was only precluded due to timing of this study. It would be helpful to have knowledge of neighborhood social effects on summer residential water consumption for policy making.

In sum, a large-scale residential water consumption survey is needed to provide sufficient planning information for the potential long-term drought. The resulting information could help with reducing water consumption not only in the San Joaquin Valley but in all of California.

Intra-Chapter Snapshot By G. Harootunian and N. Chowdhury

Mohammed Alrihimi, who travelled from Yemen, predicted to be the first nation in the world to run out of water, to search for a better future in the San Joaquin Valley.

A Census-Designated Place: A Glimpse into One Disadvantaged Community Strathmore is typical of the rural nature of many parts of the Valley, where small towns formally exist only as “census-designated places” for the purpose of counting U.S. citizens every 10 years. Strathmore’s population (2,819) reflects the SJV’s population: majority-minority, predominately Latino with a sizable chunk of Caucasians and a sprinkling of other populations such as American Indian or African American. The U.S. Census shows that Median Family Income is $25,236. Photographer Neil Chowdhury ended up in Strathmore on March 8th 2015 while driving to take a look at the former site of Tulare Lake, drained in the early 20th century to be used for cotton fields, though the area seemed devoid of any crops that day. Neil met Mohammed Alrihimi, and his two young sons tending his general store on the Strathmore’s tiny main street, which boasted few other occupied buildings. Neil is not sure where the other 2,816 people of Strathmore were hiding on that particular Sunday afternoon, as other than Mohammed and his family, the place seemed deserted. When Neil asked Mohammed if he thought the drought had changed things in Strathmore, the reply was simple: Sundays used to be very busy for the general store, but now hardly anyone comes in to shop. Editor’s Note: See Boucek, Christopher. “Yemen: Avoiding a Downward Spiral.” Carnegie Endowment for International Peace. http://carnegieendowment.org/2009/09/10/yemen-avoiding-downward-spiral [accessed 2015, 21 May]. See U.S. Census American Fact Finder (2009-2013) for Strathmore demographics.

Chapter 4 Public Health Implications of Drought

Dr. Samendra Sherchan, Department of Public Health

Abstract

Drought leads to many environmental issues that affect human health and the ecosystem. Health- related issues that can arise from drought include infectious diseases, chronic diseases, and vector-borne diseases, themselves exacerbated by the sanitation and hygiene, food and nutrition, and water limitation issues also caused by the drought. Changes in air quality have a tendency to cause respiratory health issues and can increase the risk of diseases such as Chronic Obstructive Pulmonary Disease and asthma. Other drought-related factors can affect air quality, including the presence of toxins originating from freshwater blooms of cyanobacteria, which can become airborne and can lead to adverse public health. Outbreaks of West Nile Virus are common during drought and can pose many health issues. West Nile Virus is a virus where birds are the reservoirs and humans and horses become the hosts. A person can become infected when bitten by a mosquito that has fed off an infected bird. Mosquitos tend to reproduce in areas where there is stagnant water, and this has become a huge problem in California where the drought results in shrunken standing pools and reservoirs of water. Drought can also impact human health through its impact on agricultural production. Low crop yields can result in rising food prices and shortages, potentially leading to malnutrition. In addition, severe drought poses an immediate and severe threat to freshwater sources. Over time, reduced precipitation and increased evaporation of surface water mean that groundwater supplies are not replenished at a typical rate. As a result, water utilities around the State are planning to augment their current drinking water supplies with treated wastewater, but in order to implement direct potable reuse they have to overcome public health risks and public perception regarding “toilet to tap” water. 25

Key Findings

25 Drought impacts can also include mental and behavioral health issues for those most at-risk. For example, the National Farm Medicine Center conducted a study during nine years of an epic drought in Upper Midwest. Findings included that more than 900 male farmers and ranchers in Wisconsin, Minnesota, North Dakota, South Dakota, and Montana committed suicide in the 1980s. In some years, the suicide rate was nearly double the national average for white men (cited in “Public Health and Drought: Challenges for the 21st Century, Centers for Disease Control and Prevention, http://www.cdc.gov/features/drought/index.html).

West Nile Virus (WNV) 3. WNV was also detected at an all-time high in 44 counties in California, with 379 human cases reported (2013). 4. In 2013, the baseline incidence statewide for WNV Disease was 1.00 (1 case per 100,000 persons) though the incidence for WNV infection is 1.14.26 The incidence for San Joaquin Valley counties were Stanislaus (3.25); Kern (2.90); Madera (1.97); San Joaquin (1.14); Tulare (1.10); Fresno (0.84); Kings (0.66); and Merced (0.00). 5. In 2013, WNV was detected in 2,528 mosquito pools from 27 counties (CDPH, 2013b). The baseline incidence Minimum Infection Rate statewide was 3.2. In the San Joaquin Valley, the rate were Madera (8.7), Kings (6.2), Kern (5.4), Tulare (4.8), San Joaquin (4.6), Stanislaus (3.2), Merced (3.0), and Fresno (2.2) counties. 6. Fresno County observed rate increases in WNV and Campylobacteriosis (Diarrheal Illness) infections. Campylobacteriosis (Diarrheal Illness) 7. In 2012, Fresno Country observed a significant increase in Campylobacteriosis cases with an incidence of 40.3 per 100,000 populations. 8. The Campylobacteriosis statewide incidence rate was 20.1 (per 100,000) in 2013. Seven out of the eight San Joaquin Valley counties’ incidences were higher than the statewide incidence. The incidence rates in Fresno County (43.6) and Tulare County (42.3) were over twice the statewide rate (20.1). The incidence rate in Kern (39.7) was almost twice as high as the statewide rate. The incidence rates in the four other counties were above the statewide rate to varying degrees: Madera (33.3), San Joaquin (26.6), Merced (23.2), and Stanislaus (22.0). The eighth county, Kings, had a potentially unreliable rate.

The San Joaquin Valley (SJV)

1. Air quality

The dry, dusty conditions associated with drought can lead to infectious disease, such as Coc- cidioidomycosis (Valley Fever). This fungal infection is associated with inhaling spores of the fungus, Coccidioides spp., that become airborne when soil is disrupted. Coccidioidomycosis causes a range of symptoms, including fever, chest pain, coughing, rash, and muscle aches. The SJV is the major region of Coccidioidomycosis endemicity in California.

Air quality issues created by the drought can also cause illnesses such as Chronic Obstructive Pulmonary Disease and asthma, which are very common with people residing in the California’s SJV. People who are at higher risk for developing respiratory issues include those who are

26 WNV infection identifies infections that are detected through blood bank screen, but no associated illness is reported.

immunocompromised, older, in their third trimester of pregnancy, or of African-American, Asian, Hispanic, or Filipino descent.27

Fresno County observed significant increase in cases of reported Coccidioidomycosis in 2010 and 2011 with total community and institutional cases of 726 and 720 respectively. After implementation of active control measures such as spraying soil sealants, the number of cases decreased significantly to 502 in 2012 (Figure 1). From 2007–2012, the 25–64 year age group was at higher risk and represented the highest number of Coccidioidomycosis cases (Table 1). The annual incidence rates of Coccidioidomycosis reported among African Americans, Whites, and Hispanics decreased significantly by 31.65%, 42.2%, and 22.6% respectively. However, during 2007–2012, the rate of Coccidioidomycosis reported among Native Americans/Alaskan natives and Asian/Pacific Islanders increased significantly by 380% and 97.67% respectively (Figure 2).

In all of California, the annual rate of Coccidioidomycosis increased by 67.7 percent from 2009 (2,399 case-patients; 6.5 per 100,000 population) to 2012 (4,094 case-patients; 10.9 per 100,000). The annual incidence rate was highest in 2011 with 13.9 per 100,000 population and from 2009–2012, 213 case-patients were reported to have died with Coccidioidomycosis (California Department of Public Health, 2012).

Approximately 73.6% of case-patients with Coccidioidomycosis were reported from only six counties in California, however, which are established Coccidioides-endemic areas in the state of California. Five of those six counties with the highest average annual incidence rates from 2009– 2012 are in the SJV: Kern (205.1 per 100,000), Kings (191.7 per 100,000), Fresno (64.5 per 100,000), San Luis Obispo (47.2 per 100,000), Tulare (39.2 per 100,000), and Madera (20.7 per 100,000) counties (Figure 3). The one county—San Luis Obispo—not within the SJV region of this study abuts it (Kern County).

27 Editor’s Note: The SJV has a majority population of Hispanic descent, as well as sizable populations of Filipino and Asian descent, followed by large numbers of persons with African descent. The predominant SJV population, therefore, is at higher risk for respiratory issues such as COPD and asthma. Moreover, the SJV is already experiencing serious challenges with these health issues. Vast tracts of the San Joaquin Valley have been designated as Environmental Justice areas by the San Joaquin Valley Air Pollution Control District. See Editor’s Insert: San Joaquin Valley Air Pollution Control District: Environmental Justice Map (8 June 2015) and Editor’s Snapshot: “The Health Drought” following this chapter.

Figure 1 Annual trend of reported cases of Coccidioidomycosis in Fresno County from 2007-2012 (Rutledge, 2013)

Table 1 Annual trend of reported cases of Coccidioidomycosis in Fresno County from 2007-2012, stratified by age group (Rutledge, 2013)28

**Total includes both institutional and community cases.

28 The totals in Table 1 may not add up to annual totals due to incomplete data.

Figure 2 Annual trend of reported cases of Coccidioidomycosis in Fresno County from 2007-2012, stratified by race/ethnicity (Rutledge, 2013)

Figure 3 California county-specific coccidioidomycosis incidence rates (California Department of Public Health [CDPH], 2012)

2. Water quality and mosquito-borne diseases

The conditions caused by a drought can lead to breeding grounds for mosquitoes and a potential increase in mosquito-borne diseases, such as Western Equine encephalomyelitis virus, St. Louis encephalitis virus, and West Nile Virus (WNV).

For example, the SJV like many parts of California depends on groundwater as a primary source of drinking water. Reduced precipitation and increased evaporation of surface water can impact the recharge of groundwater supplies over time. Several areas throughout the SJV have reported decreased levels of water in wells in the face of drought. A USGS monitoring well in Mendota is an illustration, where water depth has been significantly reduced due to drought (Figure 4).

Decreased reliance on groundwater levels during a drought results in increased reliance on surface water (already experiencing reduction from the drought). The Merced River flow is an example of surface water affected by the drought (Figure 5). The discharge and quality of water from rivers such as the Merced River have broad effects on several factors such as water availability and ecosystem health. Mosquito-borne diseases, such as Western Equine encephalomyelitis virus, St. Louis encephalitis virus, and WNV, are a prime concern.

Figure 4 Monitoring well in Mendota (United States Geological Survey [USGS], 2014)

Figure 5 Surface water monitoring in Merced River (USGS, 2014)

West Nile Virus (WNV)

WNV is one of the major environmental health issues associated with a drought in California. WNV activity was detected in 44 counties in 2013 with 379 human cases reported, the highest since surveillance began for WNV in California in 2000. Over the ten-year period from 2004– 2013, over 4,000 human WNV cases, including 145 fatalities, have been detected in the state of California.

Table 2 provides the 2013 baseline incidence statewide for WNV Disease (1.00, or 1 case per 100,000 persons) though the incidence for WNV infection is 1.14.29 The incidence for SJV counties was Stanislaus (3.25); Kern (2.90); Madera (1.97); San Joaquin (1.14); Tulare (1.10); Fresno (0.84); Kings (0.66); and Merced (0.00). Five of the eight SJV counties—Stanislaus, Kern, Madera, Tulare, and San Joaquin—have incidence rates equal to or above the statewide rate. 30

In June 2013, Aedes aegypti (Yellow Fever mosquito), an exotic mosquito species, was also detected, first in Madera County and subsequently in Fresno and San Mateo counties (CDPH, 2013b).

Mosquito surveillance

In 2013, WNV was detected in 2,528 mosquito pools from 27 counties (CDPH, 2013b). Table 3 provides the 2013 baseline incidence Minimum Infection Rate statewide as 3.2.31 In the SJV, the rates were Madera (8.7), Kings (6.2), Kern (5.4), Tulare (4.8), San Joaquin (4.6), Stanislaus (3.2), Merced (3.0), and Fresno (2.2) counties.32 Six of these counties—Madera, Kings, Kern, Tulare, San Joaquin, and Stanislaus—have minimum infection rates equal to or above the statewide rate.33 Of the counties with the highest minimum infection rates in the entire state, one was in a northern cluster, Glen (7.6), but the other three were in the SJV: Madera (8.7), Kings (6.2), and Kern (5.4).

29 WNV infection identifies infections that are detected through blood bank screen, but no associated illness is reported.

30 Editor’s Note: A northern cluster of California counties have sharply high incidence rates: Glenn County (31.7); Yuba (17.7) Butte (10.8); Sutter (10.4); Colusa (9.24); and Tehama (7.87).

31 The “Minimum Infection Rate” = (No. of positive pools x No. mosquitos in pool) x 1,000.

32 Again, a northern cluster of counties have high rates, such as Glen (7.6), Butte (4.7), Yolo (4.7), and Yuba (4.6).

33 Editor’s Note: Five of these counties also have the highest average annual incidence rates of Valley Fever in California from 2009–2012: Kern (205.1 per 100,000), Kings (191.7 per 100,000), Fresno (64.5 per 100,000), San Luis Obispo (47.2 per 100,000), Tulare (39.2 per 100,000), and Madera (20.7 per 100,000) counties (see pg. 103; Figure 3, pg. 106). As noted, the one county—San Luis Obispo—not within the SJV region of this study abuts it (specifically, Kern County).

Table 2 Reported WNV human cases by county of residence, California, 2004-2013 (CDPH, 2013b)

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Table 3 Results of testing mosquitoes for West Nile virus, California 2013 (CDPH, 2013b)

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Animal surveillance

In 2013, out of 16,849 chicken blood samples that were tested, 485 seroconversions to WNV were detected among 112 flocks in 26 counties. WNV was detected 1,416 (43%) dead bird carcasses out of 3,306 from 40 counties, and of these, 1,251 (37.8%) were acute infections, meaning the infection occurred within the 2013 surveillance season, from 37 counties. Of 97 dead squirrels carcasses tested, WNV was detected in eight (8.2%) carcasses from 7 counties (Table 4). The California Animal Health and Food Safety Laboratory tested horses displaying neurological signs and detected WNV in 13 horses from seven counties (Table 4). The statewide WNV infection rate in mosquitoes was higher in 2013 than in any other year (CDPH, 2013b).

Table 4 also shows WNV human infections in California in 2013. Out of the state’s total fifty eight counties, twenty five counties (43%) had no reported WNV human infection, and 10 counties (17%) had 1 reported WNV infection. The highest numbers of WNV infections were in Los Angeles (172), Kern (30), Stanislaus (19), San Joaquin (10), Tulare (9), Fresno (8), and Madera (4) counties. Kings had only 1 infection, and, again, Merced had no reported WNV human infection. In the entire state, of the five counties with the highest human WNV infection rate, two are in the SJV: Kerns (30) and Stanislaus (19). The three other counties are Los Angeles (172) and nearby Riverside (40), and Butte (24) in the northern cluster.

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Table 4 Infection with West Nile virus in California, 2013 (CDPH, 2013b)

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Fresno County

Table 5 shows an across the board increase in WNV confirmed cases from 2011 to 2012. Of note are the following: 1) 24 total confirmed WNV cases of in 2012 compared to 9 total confirmed WNV cases in 2011. 2) 19 confirmed WNV hospitalized cases in 2012 compared to 5 confirmed WNV hospitalized cases in 2011. 3) 16 confirmed WNV neuroinvasive cases in 2012 compared to 6 confirmed WNV neuroinvasive cases in 2011 (Rutledge, 2013).

Figure 6 shows the historical trends of WNV cases from 2005–2012. All non-neuroinvasive, neuroinvasive and presumptive (PVDs) cases have increased since 2006. Ethnic/race differences presented in Figure 7 illustrates that white and Hispanic/Latino populations were at higher risk and reported the greatest burden of WNV. Age also enters into a person’s risk. 54% of the total reported cases in 2012 were in people over 60 years old, 37.5% were people from 40-59 years of age, and 8.5% were in people from 20-39 years of age. There were no reported cases in people from 0–19 years of age. A unique characteristic of this disease is it occurs during specific times of the year, mostly in fall (Figure 8).

Table 5 WNV 2011 and 2012 comparison, Fresno County (Rutledge, 2013)

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Figure 6 WNV annual trend 2005–2013 by disease severity, Fresno County (Rutledge, 2013).

Figure 7 WNV ethnic/race difference by age group, Fresno County (Rutledge, 2013).

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Figure 8 WNV seasonal trend 2012 in cases, Fresno County (Rutledge, 2013).

3. Food-borne illnesses

The quality and quantity of the nation’s food supply can be affected by drought conditions, which can potentially lead to several types of adverse health effects. The SJV is primarily known for being the bread basket of the United States but due to inadequate rainfall and precipitation, crop yields have decreased. Also, substantial amounts of water are needed to produce and prepare food at the industrial level; water shortages can then affect food safety and potentially cause an increase in food-borne diseases. In California, Campylobacteriosis (a diarrheal illness) has increased significantly.

Fresno County

In 2012, Fresno Country observed a significant increase in Campylobacteriosis cases with an incidence of 40.3 per 100,000 populations, which stands in contrast to the clear but slower increase in Salmonellosis (Figure 9). The annual incidence rate of Campylobacteriosis observed in 2012 is significant with a p-value of 0.0000 and a rate ratio of 1.63 whereas the rate ratio of Salmonellosis is 0.9731 with an insignificant p-value of 0.7609 (Rutledge, 2013). These p-values represent the probability of getting the observed or more extreme results, given that the null hypothesis is true, so the low p-value for Campylobacteriosis indicates that the observed 2012 results are not probable whereas the high p-value for Salmonellosis means that the observed 2012 results were probable. Figure 10 depicts the monthly trend of reported cases of Salmonellosis and Campylobacteriosis in Fresno County in 2012 and summer months (May, June, and July), which have the greatest cases of both foodborne illnesses. Children are more

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susceptible to these foodborne illnesses as shown in Figure 11. Ethnic/race differences presented in Table 6 illustrate that Hispanic/Latino populations appear to have a higher rate of Campylobacteriosis (42.44 per 100,000 population); followed by white (38.61 per 100,000 population); and Black/African American (34.51 per 100,000 population).

For the state of California, Campylobacteriosis was detected in 55 counties in 2013 with 7,698 cases reported, with an incidence rate of 20.1 per 100,000, whereas Salmonellosis was detected in 52 counties in 2013 with 5,046 cases reported, with an incidence rate of 13.2 per 100,000 (CDPH, 2013a). Over the three-year period from 2011–2013, Campylobacteriosis cases increased from 6,758 to 7,698, whereas Salmonellosis cases increased from 4,034 to 5,046 (CDPH, 2013 a).

Figure 12 shows the Campylobacteriosis incidence rate for the SJV counties compared to the statewide rate of 20.1 (per 100,000) in 2013. The highest incidence was in San Francisco County (47.4). Seven out of the eight San Joaquin Valley counties’ incidences were higher than the statewide incidence. The incidence rates in Fresno County (43.6) and Tulare County (42.3) were over twice the statewide rate (20.1). The incidence rate in Kern (39.7) was almost twice as high as the statewide rate. The incidence rates in the four remaining SJV counties were above the statewide rate to varying degrees: Madera (33.3), San Joaquin (26.6), Merced (23.2), and Stanislaus (22.0). The eighth county, Kings, had a potentially unreliable rate.

Figure 13 shows the Salmonellosis incidence rate for the SJV counties compared to the statewide rate of 13.2 (per 100,000 persons). The highest incidence was in Yuba County (34.1). Four SJV counties’ incidences were above the statewide rate: Fresno (20.5 per 100,000), San Joaquin (15.2) Madera (15.0), and Stanislaus (13.7). The incidence rates in the remaining two other SJV counties were below the statewide rate: Merced (12.9) and Tulare (12.3). One SJV county has the lowest reliable incidence rate: Kern (7.8).

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Figure 9 Annual trend of reported cases of Salmonellosis and Campylobacteriosis in Fresno County from 2004–2012 (Rutledge, 2013). 34

Figure 10 Monthly trend of reported cases of Salmonellosis and Campylobacteriosis in Fresno County in 2012 (Rutledge, 2013)

34 Editor’s Note: Rutledge notes that public health campaigns may have contributed to the reported increase for a variety of factors (more people are aware of the infection and seek treatment, more physicians test for it, and so on).

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Figure 11 Age Group trend of reported cases of Salmonellosis and Campylobacteriosis in Fresno County from 2012 (Rutledge, 2013).

Table 6 Cases and Rates of Salmonellosis and Campylobacteriosis stratified by Ethnicity and Race in 2012. Rates are per 100,000 population (Rutledge, 2013).

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Year of Estimated Illness Onset

Fresno Kern Madera Merced San Joaquin Stanislaus Tulare CALIFORNIA TOTAL

0 5 10 15 20 25 30 35 40 45 50

2013 2012 2011

Figure 12 Campylobacteriosis, Cases and Rates by Health Jurisdiction, California, 2011–2013 (CDPH, 2013a)35

Year of Estimated Illness Onset

Fresno

Kern

Madera

Merced

San Joaquin

Stanislaus

Tulare

CALIFORNIA TOTAL

0 5 10 15 20 25

2013 2012 2011

Figure 13 Salmonellosis, Cases and Rates by Health Jurisdiction, California, 2011–2013 (CDPH, 2013a)

35 Editor’s Note: Kings County had a “potentially unreliable rate, relative standard error 23 percent of more” (pg. 22).

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Key Findings

Coccidioidomycosis (Valley Fever) 1. The annual rates of Coccidioidomycosis (Valley Fever) in California increased by 67.7 percent from 2009 (6.5 per 100,000 population) to 2012 (10.9 per 100,000). The San Joaquin Valley is the major region of Coccidioidomycosis endemicity in California. 2. For the SJV counties, the annual incidence rates from 2009–2012 were Kern (205.1 per 100,000), Kings (191.7 per 100,000), Fresno (64.5 per 100,000), Tulare (39.2 per 100,000), and Madera (20.7 per 100,000). West Nile Virus (WNV) 3. WNV was also detected at an all-time high in 44 counties in California, with 379 human cases reported (2013). 4. In 2013, the baseline incidence statewide for WNV Disease was 1.00 (1 case per 100,000 persons) though the incidence for WNV infection is 1.14.36 The incidence for SJV counties were Stanislaus (3.25); Kern (2.90); Madera (1.97); San Joaquin (1.14); Tulare (1.10); Fresno (0.84); Kings (0.66); and Merced (0.00). 5. In 2013, WNV was detected in 2,528 mosquito pools from 27 counties (CDPH, 2013b). The baseline incidence Minimum Infection Rate statewide was 3.2. In the SJV, the rate were Madera (8.7), Kings (6.2), Kern (5.4), Tulare (4.8), San Joaquin (4.6), Stanislaus (3.2), Merced (3.0), and Fresno (2.2) counties. 6. Fresno County observed rate increases in West Nile Virus and Campylobacteriosis (Diarrheal Illness) infections. Campylobacteriosis (Diarrheal Illness) 7. In 2012, Fresno Country observed a significant increase in Campylobacteriosis cases with an incidence of 40.3 per 100,000 populations. 8. The Campylobacteriosis statewide incidence rate was 20.1 (per 100,000) in 2013. Seven out of the eight SJV counties’ incidences were higher than the statewide incidence. The incidence rates in Fresno County (43.6) and Tulare County (42.3) were over twice the statewide rate (20.1). The incidence rate in Kern (39.7) was almost twice as high as the statewide rate. The incidence rates in the four other SJV counties were above the statewide rate to varying degrees: Madera (33.3), San Joaquin (26.6), Merced (23.2), and Stanislaus (22.0). The eighth county, Kings, had a potentially unreliable rate.

36 WNV infection identifies infections that are detected through blood bank screen, but no associated illness is reported.

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SNAPSHOT: The Health Drought By Gil Harootunian, PhD While the preceding chapter explores the public health impact of the drought, one need only click on the “Environmental Justice” map of the San Joaquin Valley Air Pollution Control District to see that map blankets the entire region (as it has for a long, long time): http://valleyair.org/Programs/EnvironmentalJustice/Environmental_Justice_idx.htm. Some questions that might arise are these: How does a region already in a health drought absorb more impacts? How does a region already in a financial drought absorb more costs of health care? “California Health Profiles” UCLA Center for Health Policy Fresno County California Adults (18 years-+) (2012-2013) Uninsured 35% 26.1% No usual source of care 24.9% 16.8% Medi-Cal or Health Families 27.7% 11.7% Fair or Poor Health 29.2% 19.6% Current Asthma 12.4% 7.9% Children (0-17 years) (2011-2012) Uninsured (all or part of year) 11% 7.7% No usual source of care 4.7% 8.8% Medi-Cal or Health Families 49.9% 40.5% Current Asthma 15.7% 10.1% The American Lung Association rates the cleanest and the most polluted cities in U.S. For all three measures―ozone pollution, short-term particle pollution, and year-round particle pollution―four of the five worst cities are in the Central Valley.37 As far back as 2008, the William and Flora Hewett Foundation funded a study, The Benefits of Meeting Federal Clean Air Standards in the South Coast and San Joaquin Valley Air Basins (see Hall). Findings include the following:  Air pollution is a particularly detrimental situation in an enclosed air basin like the SJV. Ozone levels typically exceed during warmer months, and PM2.5 typically exceeds during the cooler fall and winter months, so there is no “clean” season.  In the SJV overall, the cost of air pollution is more than $1,600 per person per year, which translates into a total of nearly $6 billion in savings if federal ozone and PM2.5 standards were met (5).  The documented health effects include both infant and premature adult mortality, plus events such as nonfatal heart attacks and conditions such as chronic bronchitis and asthma. Related consequences include school absenteeism and work loss days. There is no measure for the “value of avoiding the pain and anxiety caused by the underlying condition” (58-75).  In the SJV, “…the overall benefits of attaining the NAAQS are dominated by premature mortality…. [O]ver 800 people are estimated to avoid premature death annually, accounting only for the effect of PM2.5 and only for the population aged 30 and older. With a value for each life of $6.63 million, this effect alone offers a benefit of attainment of over $5 billion each year” (77).

37 http://www.stateoftheair.org/2015/city-rankings/most-polluted-cities.html

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SNAPSHOT: From Economic Distress to Psychological Distress By Gil Harootunian The National Farm Medicine Center conducted a study during nine years of an epic drought in Upper Midwest in the 1980s. Findings included that more than 900 male farmers and ranchers in Wisconsin, Minnesota, North Dakota, South Dakota, and Montana committed suicide. In some years, the suicide rate was nearly double the national average for white men.38 The CDC’s “Drought Toolkit” for vulnerable populations includes those experiencing mental illness (particularly stress, anxiety, and depression).39 The question is posed for this final time: when water distress hits, how thick or thin is the margin for those areas already experiencing higher than average psychological distress? The UCLA Center for Health Policy Research provides information on Serious Psychological Distress (SPD)* in county populations for 2012-2013 (the beginning of the drought). Measure of America’s well-being profiles provide the number of practicing physicians per county (2013-2014 data sets), one indicator of the community’s capacity to meet medical demands. Below, three counties—Kern, Kings, Madera—have the highest percentage of persons experiencing Serious Psychology Distress and the lowest number of practicing physicians. This in itself raises another set of questions, e.g., among such limited medical personnel, are there enough Spanish and Hmong speakers to handle crisis situations? State/County Serious Psychological Practicing Physicians Distress Per County (per 10,000 population) California 8.1% Fresno 8.8% 6 Kern 13.9% 4 Kings 14.4% 3 Madera 12.4% 4 Merced 4.7% 4 San Joaquin 11.8% 5 Stanislaus 7.0% 6 Tulare 8.8% 4 San Francisco (high) 14 Los Angeles 7 San Diego 7 *Serious Psychological Distress (SPD) is often used as a proxy measure for severe mental illness in a population. Adult respondents were asked 6 questions, known as the “Kessler 6,” to assess symptoms of distress during a 30-day period in the past year.

38 Cited in “Public Health and Drought: Challenges for the 21st Century,” Centers for Disease Control and Prevention: http://www.cdc.gov/features/drought/index.html.

39 See http://www.cdc.gov/nceh/drought/toolkit/vulnerable_populations.htm.

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San Joaquin Valley Air Pollution Control District: Environmental Justice Areas (green areas do not meet standards).

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East Porterville: A Video Vignette of Drought Impact on one Disadvantaged Community By Jes Therkelsen, MFA, Department of Mass Communication and Journalism

“[T]his is global.” Donna Johnson, Porterville resident.

The preceding chapter addressed the public health impacts from the drought. What happens when drinking water actually runs out?

East Porterville, California, is a small, economically Disadvantaged Community whose residents rely on wells for their potable water. In 2014, wells in East Porterville began to dry up. County officials found themselves responding to an emergency they have never faced before: a community without water.

International media attention soon came. Resident Donna Johnson explains, “I pushed for [the media attention] because everyone wanted to brush it under the carpet.” Porterville became the poster child for the California drought, having been reported by every major news organization in the U.S. and abroad.

This video vignette follows the work of Donna Johnson, a Porterville resident who began buying bottled water for her neighbors who could not afford it. Andrew Lockman, a county official, works with Donna Johnson and the residents to establish temporary solutions until a more permanent resolution is determined. Lockman notes that residents with only 10’ of water left in their wells began giving this “last little bit of water” to help neighbors who wells have gone dry. The community’s response has inspired others who might face similar situations as the drought worsens in other parts of the state. https://vimeo.com/124558471. Password: Porterville.

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Conclusion and Recommendations

Overview: Severity and Impact of the California Drought

Researchers from NASA and Cornell and Columbia Universities recently warned of major water shortages that will dry out vegetation, leading to monster wildfires in Arizona and California (Fears, February 12, 2015). These studies were forecasting mega-droughts over the next 35 years in the western United States.

A study led by Noah Diffenbaugh at Stanford University concluded that California should get used to extended drought conditions (Diffenbaugh, Swain, & Touma, 2015). Diffenbaugh and his team explored the role temperature has played in California’s drought for the last 120 years. Between 1896 and 1994, climate patterns in the state created a 50 percent chance that a year of extremely warm temperatures would merge with a year of moderately dry conditions. But between 1995 and 2014, extreme temperature years were so common that the chance of combining with a dry year increased to 80 percent.

The lowest precipitation year on record in the state was between 2013 and 2014, and 2014 was the single hottest year in California’s recorded history. These conditions are expected to persist in the years to come. In other words, before we experience mega-droughts in a few decades, it is very likely we will be living with regularly hot and dry years.

The economic impact of the drought in the San Joaquin Valley will have wider impacts. California supplies nearly half of all U.S. fruits, vegetables, and nuts. The San Joaquin Valley is the source of roughly 25 percent of the nation’s table food. This means California’s agriculture is concentrated where the drought has hit the hardest. If drought continues, agriculture may soon play a less important role in California’s economy, as the more water-intensive segment of agriculture move to the South and the Midwest, where water for irrigation is more available. Production levels for thirsty crops like alfalfa and cotton have already diminished significantly in the last few years. Between 2006 and 2010 alone, the amount of land irrigated for cotton fell by 46 percent. Continued drought may eventually force the U.S. to import products that have been produced in California, such as select vegetables, fruits, and hard nuts.

A serious consequence of reduced precipitation and resulting decreased surface water availability is the overdraft of groundwater. Three years ago, groundwater made up one-third of California’s total supply. Today, groundwater makes up a full 75 percent of California’s total supply. It is estimated that 15 to 20 percent of the nation’s groundwater use is coming from the Central Valley alone. The total economic impact of this factor is beyond the scope of this report, but it is noted that in some groundwater aquifers, excessive extraction causes subsidence (ground sinking), potentially damaging infrastructure such as canals, roads, and buildings (Shalby, 2015).

Our Findings from this Study: The San Joaquin Valley

An examination of the historical trends of precipitation, streamflow, reservoir storage, irrigation water use, and changes in groundwater depth clearly indicates the unprecedented impact of drought in California, with a disproportionate heavy blow to the San Joaquin Valley (SJV)

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region that has a high concentration of irrigated agriculture. In the past three years, precipitation has dropped to less than one-third (over one standard deviation) of its normal level during the past one hundred years. If subsequent years have precipitation ranges approaching those of 2014, the state’s reservoir storage shortage will continue to worsen. As a result, SJV water use will likely come under additional scrutiny. The SJV has higher-than-average water consumption compared to the rest of the state, largely due to its hotter climate and agricultural activities. On average, the SJV counties use more water (1,814 Mgal/day) per county than non-SJV counties (469 Mgal/day), due to agricultural activities.40 Recent news reports have already reflected concerns by some citizens and pundits about water use and agricultural investments in the SJV. The issue is that it takes more water in the SJV to sustain the equivalent living conditions found in other parts of the state. Decreased water availability in the SJV could cause collapse of both the economy and government, forcing the balance of the state to support the remaining population that cannot leave. Growers are now relying more on groundwater than in the past, and this consumption pattern is not sustainable long-term.

Agriculture, water, and energy usages are highly correlated. While water shortage due to drought has a direct adverse impact on water availability and thus crop production, it also increases energy consumption as a result of extended lift that is required for groundwater extraction. On top of this, California loses significant hydropower energy production due to reductions in surface water supplies that drive the turbines.

In the SJV, the economic impact on agricultural revenue alone will be billions of dollars. Dr. Fayzul Pasha’s findings (chapter 1) on the impact of the drought on agricultural revenue solely from escalating pumping costs were as follows: 5 inches of precipitation (annual): $2.564 billion loss in agricultural revenue 4 inches of precipitation (annual): $2.827 billion loss in agricultural revenue 3 inches of precipitation (annual): $3.098 billion loss in agricultural revenue 2 inches of precipitation (annual): $3.35 billion loss in agricultural revenue

The continued drought also affects local economies (chapter 2). This can result in reduced/lost household income and negatively impacted tax bases for local governments. The combination of these effects is especially felt in families living in Disadvantaged Communities. Dr. Antonio Avalos’s analysis indicates that although the unemployment rate hasn’t risen during the drought, people suffered real wage loss and related household economic hardships. Decline in household income in Disadvantaged Communities during this time is largely due to a combination of job loss, lower hourly wage, and lower annual wages paid to farm workers, as well as working less days per year. As a consequence of the drought some workers migrated away from the SJV in pursuit of better working and living conditions. These patterns explain why household income is falling without a rise of the unemployment rate: there are fewer people looking for work and those who have jobs work on a reduced basis. Low income households can also be particularly impacted indirectly through rising food prices during a drought because these households spend a larger share of their income on food, so a food price surge can significantly impact their disposable income. Disadvantaged Communities, whose residents include both domestic and

40 US Geological Survey (USGS) Water Data from 2000 to 2010 (see chapter III by Dr. Chih-hao Wang).

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migrant workers, have long experienced a “financial” drought, and the economic impact from the current water drought will be added to their financial distress.

Dr. Chih-Hao Wang addressed a key municipal use of water: residential (chapter 3). From 2000 to 2010, the state population in California increased by 10% with the SJV doubling this rate at 20%. Water use dropped by 26% in the same period (-14% in the SJV and -32% in the rest of the state) due to better irrigation technology and conscientious conservation. However, in face of the severe drought in the past three years, less water will be available to support municipal water demand from the increased population. In the SJV, there is so little water this year that some municipalities are in danger of running out it. Dr. Wang and his team conducted a survey of urban residents that revealed many physical and social factors affect water consumption. Physical factors include directions of a house (those facing south consume more water), size of the house, and number of bathrooms per house. In addition to these physical factors, neighborhood social patterns also affect water consumption. How much water a given household uses can correlate with how its neighbors use water after home sizes are controlled, resulting in similar water consumption patterns in neighborhoods. These findings led to the recommendation for a large scale survey of residential water use, a valuable tool to produce actionable data that can inform comprehensive municipal water policy and planning.

Dr. Samendra Sherchan examined how the continued drought introduces health-related problems due to environmental deterioration (chapter 4). Drought can induce poor air quality and higher risk of spreading infectious diseases, besides worsening conditions of sanitation and hygiene. Poorer air quality causes respiratory health problems, increasing incidences of Chronic Obstructive Pulmonary Disease and asthma. Other drought-related public health impacts include higher levels of airborne toxins originating from freshwater blooms of cyanobacteria, and outbreaks of West Nile Virus. These impacts are occurring in a region that has already been declared an “Environmental Justice” area, with well documented health impacts, by the state Air Resources Board.

Finally, we need to keep in mind that although the drought has continued for three years, its worst impact may as yet to come. There is usually a time lag between the occurrence of the drought (reduced precipitation) and its impact on human life. We are still living on the “inheritance” of normal precipitation years although this is being quickly depleted. The impact and effects we are describing in this study are anticipated to deepen and worsen, even if precipitation levels were to improve soon.

The Future: Water Budgets

Evidence is currently incomplete, but the drought we are facing maybe primarily thought of as a human and social problem.

There is much discussion on how the previous rules allocating water to growers, cities, and the environment should be extended going forward. Critics say the governor is only asking urban areas to reduce consumption while outlining no tangible restriction on agriculture. Supporters argue that farmers are slated to receive zero Federal project water and only 20% of State Project water in 2015; far less the than the presumptive 75% supply available to urban water users.

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Again, critics will argue that agricultural activities use 80% of the state’s developed water supply, but fail to mention that this excludes environmental water releases and uses. When this is added back into the equation, agricultural use is closer to 40%. In addition, a seldom mentioned aspect of water consumption related to population growth is production of meat, dairy products, and beverages. Only focusing on agricultural production for food, vegetables, and fruits does not give us a complete review of water consumption. In the end, both urban and agricultural communities should be recognized for reducing per capita water use and reducing the water footprint (more crop per drop) of food and fiber produced, respectively.

In fact, given the reduction in water availability, it is imperative that the state determine the level of long-term sustainable water supply availability. This decision will impact all water users, and the environmental, urban, and agricultural sectors, significantly. The water world going forward will most likely be one of water budgets for all concerned.

Recommendations

The findings of this study of the San Joaquin Valley lead us to return to all Californians these recommendations. We need to change our established paradigm when thinking about water and water use. Based on the findings of this study, we ask that all Californians consider these recommendations.

 Spark deep political discussions about the future availability of water in California and how it is impacted by the current laws and policies on water. Emphasize four components: o Developing water budgets as both a smart growth strategy for population increases and a sustainable management strategy. o Creating a broad-based consensus on California’s water future, with the appropriate leadership. Citizens should understand that competing ideas for water use will continue to exist and a broad-based consensus with good leadership is an immense benefit. o Understanding every single citizen should have and know his or her water budget and use it appropriately. o Understanding that groundwater, our largest water storage system and water savings account, is a finite resource. Continued overuse of groundwater will cause long-term damage in the form of subsidence. Deeper pumping levels of extraction will become unaffordable except for the highest income-producing uses or affluent users.  Increase funding in water education and technology at all levels to raise awareness of the role of water in our society, and inspire the next generation of water leaders.  Avoid single uses of water. Water should be reclaimed and used again and again wherever possible. The culture of water in our society must be changed to reflect the new reality of less water for all. Dual plumbing for houses, gray water use, rainwater harvesting, and water recycling must be adopted by all communities.  Explore non-conventional sources of water, including saline or brackish aquifers and produced water from oil fields that may be reclaimed for agricultural or other uses.  Recognize the true value of water and price it accordingly.

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Our water sources, watersheds, are a system. Understanding our systems, their components and complex needs and how they work, will be imperative in order to come to agreement on how to manage water properly in the future, especially to establish a comprehensive California water budget.

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nothing-compared-to-what-may-be-coming/2015/02/12/0041646a-b2d9-11e4-854b- a38d13486ba1_story.html

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Appendix 1 Maps

Appendices compiled by David Drexler, Digital Initiatives Librarian The Henry Madden Library California State University, Fresno

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California State Water Project (SWP) if t t

Map 1 Water storage and distribution in California Data from U.S. Geological Survey, retrieved from http://nhd.usgs.gov/, http://water.usgs.gov/GIS/metadata/usgswrd/XML/pp1766_cvhm_sfr_network.xml, and http://water.usgs.gov/lookup/getspatial?reservoir, and California Department of Transportation retrieved from http://earth.dot.ca.gov/

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Map 2 Depth to groundwater, Spring 2014

Data from California Department of Water Resources Groundwater Information Center, retrieved from https://gis.water.ca.gov/app/groundwater/, and California Department of Transportation, retrieved from http://earth.dot.ca.gov/.

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Map 3 Overview of public water agencies in the San Joaquin Valley, from the California Department of Water Resources

Retrieved from http://www.water.ca.gov/pubs/drainage/2008_bo undaries_of_public_water_agencies__san_joaqui n_valley/pwa08_sjv.pdf

Note: This is an oversized file and is properly viewed by accessing the site above.

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Online Interactive Maps

Geospatial Information Services, Henry Madden Library. GIS Projects Showcase. http://libguides.csufresno.edu/content.php?pid=624414&sid=5164578

This collection of demonstration geospatial projects at Fresno State’s Henry Madden Library includes interactive maps dealing with groundwater depth, recharge, current reservoir storage, and drought intensity.

New California Water Atlas. http://ca.statewater.org/

This work-in-progress to produce a series of interactive maps that will explain water issues in California. The first completed map shows water rights by locations, amount, and purpose.

USGS Center for Integrated Data Analytics. California drought, visualized with open data. http://cida.usgs.gov/ca_drought/

This interactive map visualizes the effects of the drought over time on reservoir storage and area.

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Appendix 2 Bibliography

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Scholarly studies and policy reports

Aghakouchak, A., Feldman, D., Stewardson, M. J., Saphores, J.-D., Grant, S., & Sanders, B. (2014). Australia’s drought: lessons for California. Science, 343(6178), 1430–1431. http://doi.org/10.1126/science.343.6178.1430

A letter describes water reforms that helped mitigate drought impacts in Australia, including well-developed water markets, modernization of irrigation infrastructure, and water allotments for environmental purposes.

Alyssa J. Galik. (2015, April 3). Water poverty in California’s rural Disadvantaged Communities. Pepperdine University, Malibu, CA. Retrieved from http://digitalcommons.pepperdine.edu/sturesearch/91/

This study used an international measure known as the Water Poverty Index to determine how water availability in rural Disadvantaged Communities in the San Joaquin Valley relates to community relations with government and non-profit organizations.

Amos, C. B., Audet, P., Hammond, W. C., Bürgmann, R., Johanson, I. A., & Blewitt, G. (2014). Uplift and seismicity driven by groundwater depletion in central California. Nature, 509(7501), 483–486. http://doi.org/10.1038/nature13275

Groundwater depletion, which is associated with land subsidence in the Central Valley, also reduces the weight on the earth’s crust in the area of the depleted aquifer. This study suggests that depletion of groundwater is associated with an uplift of 1-3 mm per year around the southern Central Valley, possibly increasing the risk of earthquake.

Association of California Water Agencies. (2005). No time to waste: A blueprint for California water. Sacramento, CA: Association of California Water Agencies. Retrieved from http://www.acwa.com/spotlight/no-time-waste

A water policy document produced by public water agencies with a suite of recommendations for California’s water system.

Balazs, C. L., & Ray, I. (2014). The drinking water disparities framework: On the origins and persistence of inequities in exposure. American Journal of Public Health, 104(4), 603– 611. http://doi.org/10.2105/AJPH.2013.301664

The authors used data from the San Joaquin Valley to develop the Drinking Water Disparities Framework, which attempts to model social disparities in exposure to drinking water contaminants.

California Council on Science and Technology. (2014). Achieving a sustainable California water future through innovations in science and technology. Sacramento, CA: California Council on Science and Technology. Retrieved from http://www.calstate.edu/water/documents/Achieving-Sustainable.pdf

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This report recommends viewing and managing the California water system as a whole, and identifies policy recommendations and technology opportunities as well as barriers to implementation.

California Department of Water Resources. (2013a). 2013 Draft Bay Delta conservation plan. Sacramento, CA: California Department of Water Resources. Retrieved from http://baydeltaconservationplan.com/2013- 2014PublicReview/2013PublicReviewDraftBDCP.aspx

Draft version of a comprehensive conservation plan for the Sacramento-San Joaquin Delta, a critical region for California’s water infrastructure. The plan seeks to balance two goals: water supply reliability and ecosystem restoration.

California Department of Water Resources. (2013b). Final California water plan update 2013. Sacramento, CA. Retrieved from http://www.waterplan.water.ca.gov/cwpu2013/final/

Substantial strategic plan produced by the California Department of Water Resources provides a framework for water resource management and planning along with 300 action recommendations.

Christian-Smith, J., Levy, M., & Gleick, P. (2011). Impacts of the California drought from 2007 to 2009: Surprising outcomes for California’s agriculture, energy, and environment. Oakland, CA: Pacific Institute. Retrieved from http://pacinst.org/publication/impacts-of- the-drought-2007-2009/

An assessment of agricultural, economic, and environmental impacts of the 2007-2009 California drought.

Cook, B. I., Ault, T. R., & Smerdon, J. E. (2015). Unprecedented 21st century drought risk in the American Southwest and Central Plains. Science Advances, 1(1), e1400082. http://doi.org/10.1126/sciadv.1400082

Several climate models predict conditions in California and the southwest in the late 21st century will be much drier than anything seen in the historical record or in paleoclimate reconstructions.

Analysis of historical climate observations from California and computer models both indicate that anthropogenic global warming is increasing the probability of drought occurrences in California.

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Dziegielewski, B., Garbharran, H. P., & Langowski, J. F. (1993). Lessons learned from the California drought (1987-1992). Fort Belvoir, VA: Institute for Water Resources, U.S. Army Corps of Engineers. Retrieved from http://www.iwr.usace.army.mil/Portals/70/docs/iwrreports/93-NDS-5.pdf

Substantial report makes strategic recommendations for water management and policy in California based on experiences during the 1987-1992 drought.

Famiglietti, J. S., Lo, M., Ho, S. L., Bethune, J., Anderson, K. J., Syed, T. H., … Rodell, M. (2011). Satellites measure recent rates of groundwater depletion in California’s Central Valley. Geophysical Research Letters, 38(3). http://doi.org/10.1029/2010GL046442

A study conducted just before the current California drought used satellite data to estimate groundwater depletion.

Gleick, P. (2015). Impacts of California’s ongoing drought: Hydroelectricity generation (p. 13). Oakland, CA: Pacific Institute. Retrieved from http://pacinst.org/publication/impacts-of- californias-ongoing-drought-hydroelectricity-generation/

Reduced river flows reduce hydroelectric power generation and increase reliance on natural gas, leading to higher costs and environmental consequences.

Griffin, D., & Anchukaitis, K. J. (2014). How unusual is the 2012–2014 California drought? Geophysical Research Letters, 41(24), 2014GL062433. http://doi.org/10.1002/2014GL062433

The current California drought is the most severe in the last 1200 years. Precipitation from 2012-2014 has been extremely low but not within the range of natural variability.

Hanak, E., Lund, J., Dinar, A., Gray, B., Howitt, R., Mount, J., … Thompson, B. “Buzz.” (2001). Managing California’s water: From Conflict to reconciliation. San Francisco, CA: Public Policy Institute of California. Retrieved from http://www.ppic.org/main/publication.asp?i=944

This lengthy report provides a brief history of water use in California, a description of current challenges, and a series of policy recommendations.

Hanak, E., Mount, J., Lund, J., Cayan, D., Davis, F., DeShazo, J. R., … Wilkinson, R. (2015). California’s water. San Francisco, CA: Public Policy Institute of California. Retrieved from http://www.ppic.org/main/publication.asp?i=1130

Briefing kit from PPIC discusses policy challenges around water in California, from climate change to agricultural use.

Herring, S. C., Hoerling, M. P., Peterson, T. C., & Stott, P. A. (2014). Explaining extreme events of 2013 from a climate perspective. Bulletin of the American Meteorological Society, 95(9), S1–S104. http://doi.org/10.1175/1520-0477-95.9.S1.1

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A supplement to the Bulletin of the American Meteorological Society with reports from several groups attempting to assess the role of climate change in extreme weather events. Three groups looked at the California drought and, though all agree that climate change has the potential to make droughts more frequent, none find a causal role for climate change in the current drought.

Howitt, R., Medellin-Azuara, J., Lund, J. R., & MacEwan, D. (2014). Preliminary 2014 drought economic impact estimates in Central Valley agriculture. Davis, CA: Center for Watershed Sciences, University of California Davis. Retrieved from https://watershed.ucdavis.edu/files/biblio/DroughtReport_23July2014_0.pdf

Preliminary release of the UC Davis report on the drought’s economic impact on agriculture, this version focuses on the Central Valley.

Howitt, R., Medellín-Azuara, J., MacEwan, D., Lund, J., & Sumner, D. (2014). Economic analysis of the 2014 drought for California agriculture. Davis, CA: Center for Watershed Sciences, University of California Davis. Retrieved from http://meteora.ucsd.edu/cap/pdffiles/Howitt2014_Economics_CA_2014drought.pdf

UC Davis report uses a variety of economic models to assess the impact of the drought on California’s agriculture.

Lo, M.-H., & Famiglietti, J. S. (2013). Irrigation in California’s Central Valley strengthens the southwestern U.S. water cycle. Geophysical Research Letters, 40(2), 301–306. http://doi.org/10.1002/grl.50108

Computer simulations suggest that evaporated water from irrigation in the Central Valley causes increased precipitation in the Colorado River basin resulting in an increase of around 30% in Colorado River streamflow.

Seaton, P. S., Brodfuehrer, K., & Beaman, M. (2011). Furthering the fight to make clean water a right in California. Clearinghouse Review: Journal of Poverty Law and Policy, 45, 187– 501. Retrieved from http://www.crla.org/sites/all/files/content/uploads/Resources/CleanWater_JrnlPvrtLaw_2 011.pdf

Reviews many issues with water quality in rural California and San Joaquin Valley communities in support of (now enacted) legislation to declare a right to safe drinking water.

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Shahbazbegian, M., & Bagheri, A. (2010). Rethinking assessment of drought impacts: a systemic approach towards sustainability. Sustainability Science, 5(2), 223–236. http://doi.org/10.1007/s11625-010-0110-4

The authors note that assessments of drought impacts typically focus on direct effects on agriculture and the economy, and they propose a systemic approach to deal with secondary social and environmental effects in areas such as migration, education, conflicts, and ecosystem degradation.

Wang, S.-Y., Hipps, L., Gillies, R. R., & Yoon, J.-H. (2014). Probable causes of the abnormal ridge accompanying the 2013–2014 California drought: ENSO precursor and anthropogenic warming footprint. Geophysical Research Letters, 41(9), 2014GL059748. http://doi.org/10.1002/2014GL059748

Computer models suggest a link between increased greenhouse gases and weather patterns that led to the 2013-2014 California drought.

Zilberman, D., Dinar, A., MacDougall, N., Khanna, M., Brown, C., & Castillo, F. (2011). Individual and institutional responses to the drought: the case of California agriculture. Journal of Contemporary Water Research and Education, 121(1), 17. Retrieved from http://opensiuc.lib.siu.edu/cgi/viewcontent.cgi?article=1142&context=jcwre

An examination of responses to the 1987-1991 California drought from an economic perspective shows that agriculture managed with stored water for three years, then turned to increased groundwater pumping, conservation, and leaving land fallow. The introduction of water trading was an important institutional change.

Background reading

These books provide background on water issues and history of water use in the western U.S., California, and the San Joaquin Valley.

Carle, D. (2009). Introduction to water in California. Berkeley, CA: University of California Press.

A guide written for general audiences to the state’s water resources and how they’ve been developed.

Fishman, C. (2011). The big thirst: The secret life and turbulent future of water. New York: Free Press.

General introduction to many aspects of water from a global perspective, from its physical properties to industrial and agricultural use to attitudes towards the economics of water. Fishman is optimistic that water problems are solvable.

Hundley, N. (2001). The great thirst: Californians and water, a history. Berkeley, CA: University of California Press.

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Comprehensive history of water in California from before European settlers through the late 20th century.

Ingram, B. L., & Malamud-Roam, F. (2013). The West without water: What past floods, droughts, and other climatic clues tell us about tomorrow. Berkeley, CA: University of California Press.

Examines historical floods and droughts and paleoclimate research to try to define “normal” climate in California and the western U.S., with implications for future reliability of water supply.

Lassiter, A. (Ed.). (2015). Sustainable water: Challenges and solutions from California (First edition). Berkeley, CA: University of California Press.

Collection of writings by experts from many academic disciplines, government, and non- profits covering many different issues and challenges around creating more resilient water supplies. Forthcoming July 2015.

Pearce, F. (2006). When the rivers run dry: Water, the defining crisis of the twenty-first century. Boston, MA: Beacon Press.

A journalist explores water systems in crisis in more than thirty countries.

Reisner, M. (1993). Cadillac desert: The American West and its disappearing. New York: Penguin Books.

The definitive economic, political, and environmental history of the development of water resources in the American west.

Smith, W., & Secrest, W. B. (2004). Garden of the sun: A history of the San Joaquin Valley, 1772-1939 (2nd ed). Fresno, CA: Linden Publishing Co.

The most thorough history available of the San Joaquin Valley, first published in 1939 and updated in 2004. Begins with Native Americans in the area and includes the growth of agriculture in the valley.

News articles and sources

Selected articles

Newspaper, magazine, and blog articles that offer in-depth coverage of the drought or document specific drought impacts.

Famiglietti, J. (2015, March 13). California has about one year of water stored. Will you ration now? Los Angeles Times. Los Angeles, CA. Retrieved from http://www.latimes.com/opinion/op-ed/la-oe-famiglietti-drought-california-20150313- story.html

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Op-ed by UC Irvine professor calls for water rationing, speeding timetables in the Sustainable Groundwater Management Act, and developing long-term water management strategies.

Madrigal, A. C. (2014, February 24). American Aqueduct: The Great California Water Saga. The Atlantic. Retrieved from http://www.theatlantic.com/features/archive/2014/02/american- aqueduct-the-great-california-water-saga/284009/

Long article about the Bay Delta Conservation Plan with lots of background on California water history and issues.

Marcum, D. (2015). Scenes from California’s Dust Bowl. Los Angeles Times. Los Angeles, CA. Retrieved from http://www.latimes.com/local/great-reads/la-me-c1-drought-timeline- 20141210-html-htmlstory.html

Pulitzer Prize winning series of articles on the effects of drought in the Central Valley.

Mark Grossi. (2015, April 29). Drought is making San Joaquin Valley’s bad air worse, report says. Fresno Bee. Fresno, CA. Retrieved from http://www.fresnobee.com/news/local/news-columns-blogs/earth- log/article20925525.html

The American Lung Association’s “State of the Air” report indicates that PM 2.5 pollution has gotten worse with the drought.

Medina, J. (2014, October 2). With Dry Taps and Toilets, California Drought Turns Desperate. New York Times. New York. Retrieved from http://www.nytimes.com/2014/10/03/us/california-drought-tulare-county.html

New York Times description of impacts of wells drying up in East Porterville.

Nidever, S. (2015, January 30). Almonds: Good or bad? Hanford Sentinel. Hanford, CA. Retrieved from http://hanfordsentinel.com/news/local/almonds-good-or- bad/article_fbf8c37a-4ae5-526a-ab7d-597140ef8155.html

Series of articles examining the public relations issues with water required for almonds.

Nijhuis, M. (2014, September 18). Amid drought, new California law will limit groundwater pumping for first time. National Geographic News. Retrieved from http://news.nationalgeographic.com/news/2014/09/140917-california-groundwater-law- drought-central-valley-environment-science

Brief account of issues surrounding the Sustainable Groundwater Management Act.

Parker, D., & Kearns, F. California’s water paradox: Why enough will never be enough. Retrieved from https://theconversation.com/californias-water-paradox-why-enough-will- never-be-enough-40889

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University of California authors suggest that increased water supply will always lead to increased demand, meaning there will never be “enough” water.

Ritchel, Matt. (2015, June 5) California farmers dig deeper for water, sipping their neighbors dry - NYTimes.com. New York Times. New York. Retrieved from http://www.nytimes.com/2015/06/07/business/energy-environment/california-farmers- dig-deeper-for-water-sipping-their-neighbors-dry.html?smprod=nytcore- iphone&smid=nytcore-iphone-share&_r=0

Discussion of the “well drilling boom” in California as more and more wells dry up and new ones have to be drilled or old ones have to be drilled deeper. Includes analysis of subsidence in Central Valley as aquifer is depleted.

Schwartz, N. D. (2015, May 6). Water pricing in two thirsty cities: In one, guzzlers pay more, and use less - NYTimes.com. New York Times. New York. Retrieved from http://www.nytimes.com/2015/05/07/business/energy-environment/water-pricing-in-two- thirsty-cities.html?_r=0

Discussion of tiered rates for municipal water that compares use in Fresno, CA with Santa Fe, NM.

Sommer, L. (2015, June 1). Car washes and pools: Winners and losers of California’s drought. Retrieved from http://ww2.kqed.org/science/2015/06/01/car-washes-and-pools-winners- and-losers-of-californias-drought/

Anecdotes documenting how municipal water customers are reacting to new statewide water use restrictions.

Xia, R. (2015, May 15). Drought cuts power production of California dams. Los Angeles Times. Los Angeles, CA. Retrieved from http://www.latimes.com/local/california/la-me- drought-hydro-20150517-story.html

Low water levels and streamflow mean reduced generation of hydroelectric power.

News sources

A selection of newspaper portals and news aggregators where current coverage of water and drought issues can be found.

Association of California Water Agencies. Water News. Retrieved from http://www.acwa.com/mediazone/water_news

Regular updates on statewide water issues from the water agency perspective.

California Institute for Water Resources. Confluence. Retrieved from http://ucanr.edu/blogs/confluence/

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Blog published by the California Institute for Water Resources gathers water- and drought-related posts from many sources.

Fresno Bee. Water & Drought news. Retrieved from http://www.fresnobee.com/news/state/california/water-and-drought/

Drought coverage from the Fresno Bee, including wire service stories.

Los Angeles Times. California Drought. Retrieved from http://www.latimes.com/local/drought/

Portal gathering Los Angeles Times coverage of the California drought. Much of the content is focused on the Los Angeles area, but occasional articles cover the Central Valley and many issues covered are of statewide interest.

New York Times. The Parched West. Retrieved from http://www.nytimes.com/interactive/2015/04/05/us/DroughtSeriesBox.html

Articles in “ The Parched West” series explore the impact of the drought that has hit states from the Pacific Coast to the Great Plains, with a majority on the drought, its history, and its impacts in California.

Pacific Institute. Pacific Institute Media Center. Retrieved from http://pacinst.org/media-center/

Includes press releases from and media appearances by the Pacific Institute along with new updates that collect articles from many sources about water issues.

Sacramento Bee. Water & Drought news. Retrieved from http://www.sacbee.com/news/state/california/water-and-drought/

Drought coverage from the Sacramento Bee.

San Francisco Chronicle. California Drought - SFGate. Retrieved from http://www.sfgate.com/drought/

Collected coverage of California drought from the San Francisco Chronicle.

UC Davis Center for Watershed Sciences. California Water Blog. Retrieved from http://californiawaterblog.com/

A blog on water policy issues written by researchers and students from the UC Davis Center for Watershed Sciences in collaboration with “experts from other universities, research institutes, government agencies and NGOs.”

Valley Public Radio. Drought. Retrieved from http://kvpr.org/term/drought

Stories on the “trending topic” of drought from Valley Public Radio.

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Water Education Foundation. Aquafornia. Retrieved from http://www.watereducation.org/aquafornia

The Water Education Foundation’s blog aggregates news reports on California water issues.

Media and artwork related to drought and its impacts

Black, M. Matt Black Photography. Retrieved from http://www.mattblack.com

Central Valley photographer explores impacts of drought in several projects. “The Dry Land” depicts agriculture during the drought, and “The Dispossesion” deals with poverty resulting from recession and drought.

Corcoran, T. Western Water Luv. Retrieved from https://www.youtube.com/channel/UCE63IFloqt2kd3Kb-DB07CA

YouTube channel of a Los Angeles man who takes video when he encounters water being wasted, sometimes using the hashtag #droughtshaming.

Dawson, R. Robert Dawson Photography. Retrieved from http://www.robertdawson.com/portfolio.html?folio=Projects

Photographer with a number of water-themed projects, including “Water in the West” and the “Great Central Valley Project.”

Little, J. Jennifer Little Photography. Retrieved from http://www.jenniferlittle.net/

Photographer and faculty member at University of the Pacific in Stockton does water- related art photography, including projects “Conduits” and “Owens Lake and the Los Angeles Aqueduct.”

Osequera, J. C. (2014). The fight for water: A farm worker struggle. Retrieved from http://www.thefightforwaterfilm.com

Documentary showing effects on the agricultural community of water restrictions during the 2009 drought. See a review at http://hanfordsentinel.com/ontap/documentary-sheds- light-on-drought/article_114aef9c-dd2d-11e3-a7dc-001a4bcf887a.html

Valley Public Radio. Voices of the Drought. Retrieved from http://kvpr.org/programs/voices- drought

This series of programs by Valley Public Radio covers drought impacts in California’s Central Valley and invites public participation through the use of the hashtag #droughtvoices on Instagram, Twitter, and Facebook. A tumblr page at http://voicesofthedrought.tumblr.com/ highlights some of these contributions along with Valley Public radio stories.

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Appendix 3 Stakeholder organizations

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Association of California Water Agencies. The Association of California Water Agencies (ACWA) is a coalition of 430 public water agencies working to promote water management with good quality, low cost, and environmental balance. 910 K Street, Suite 100 Sacramento, CA 95814 tel. (916) 441-4545 fax (916) 325-4849 http://www.acwa.com/

ACWA and the Department of Water Resources have partnered on the Save Our Water program, which includes a tool for finding local water agencies. http://saveourwater.com/find-your-water-agency/

California Department of Water Resources. The DWR is the state agency responsible for managing and protecting California’s water. P.O. Box 942836 Sacramento, CA 94236 Public Affairs Office tel. (916) 653-6192 fax (916) 653-4684 http://www.water.ca.gov/

California Farm Water Coalition. CFCW is a non-profit educational organization representing the interests of agricultural water users. 6133 Freeport Boulevard, 2nd Floor Sacramento, CA 95822 tel. 916-391-5030 http://farmwater.org/

California Governor’s Office of Emergency Services (CalOES). CalOES has prepared a brochure with information on assistance for those affected by the drought, including assistance with food, utilities, health care, and employment; grants and loans for drinking water emergencies and home repairs; and programs for farmers, ranchers, and small businesses. http://ca.gov/drought/pdf/Drought-Assistance-Brochure-2015.pdf

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California State University. Water Resources and Policy Initiatives. The California State University’s Water Resources and Policy Initiatives (WRPI) coordinates system-wide efforts to create effective water managers. Boykin Witherspoon III Executive Director 5500 University Parkway San Bernardino, CA 92407 tel. (909) 537-7681 fax (909) 537-7682 http://www.calstate.edu/water/

California State University, Fresno. Fresno State is at the heart of the most important agricultural region in the nation, and is committed to positively addressing water and agricultural issues. Water research related resources at Fresno State are listed at http://www.fresnostate.edu/water-research and includes the following resources:

California Water Institute, an academic center of excellence for research, education, and policy analysis of issues involving water resources. 6014 N. Cedar Ave, M/S OF 18 Fresno, CA 93710 tel. (559) 278-8650 fax (559) 278-8655 http://www.californiawater.org/cwi/index1.htm

The Center for Irrigation Technology, a leading independent testing laboratory and applied research facility for the irrigation industry. 5370 N. Chestnut Avenue M/S OF 18 Fresno, CA 93740 tel. (559) 278-2066 fax (559) 278-4496 http://www.fresnostate.edu/jcast/cit/

The Faculty Water Cohort, which has as its mission to engage the campus and community in discussions and activities to build awareness and develop understanding of water issues and challenges. http://www.fresnostate.edu/academics/water-cohort/

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The International Center for Water Technology, established to provide education and research to assist in developing and adopting innovative solutions and technologies that improve water use efficiency. California State University, Fresno 5370 N. Chestnut Avenue, M/S OF 18 Fresno, CA 93740-8021 tel. (559) 278-2066 fax (559) 278-6033 http://www.icwt.net/

The Water, Energy, and Technology (WET) Center, which supports innovators and entities working towards building sustainable technologies in the water, energy, and agricultural sectors. 2911 E. Barstow Avenue, M/S OF 144 Fresno, CA 93710 tel. (559) 278-4540 fax (559) 278-8401 http://wetcenter.org/

California Urban Water Conservation Council. CUWCC is a partnership between urban water agencies, non-profit groups, private organizations, and government that seeks to promote best practices in urban water conservation. 716 10th Street, Suite 200 Sacramento, CA 95814 tel. (916) 552-5885 fax (916) 552-5877 http://www.cuwcc.org/

Great Valley Center. A nonprofit that seeks to support economic, social, and environmental well-being in California's Central Valley. 1120 13th Street, Suite C Modesto, CA 95354 tel. (209) 522-5103 http://www.greatvalley.org/

The Nature Conservancy California Program. The worldwide conservation organization has several programs in California related to sustainable management of fresh water, described here: http://www.conserveca.org/our-stories/water/term/summary 201 Mission Street, 4th Floor San Francisco, CA 94105-1832 tel. (415) 777-0487 fax (415) 777-0244 http://www.conserveca.org/

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Pacific Institute: Water Program. The Pacific Institute is a non-profit organization which “works to create a healthier planet and sustainable communities.” Their water program engages with many issues around water efficiency, access, and environmental protection. 654 13th St. Preservation Park Oakland, CA 94612 (510) 251-1600 http://pacinst.org/about-us/programs/water-program/

PPIC Water Policy Center. The Public Policy Institute of California (PPIC) is a nonprofit, nonpartisan organization. The PPIC Water Policy Center produces publications focused on reliable water supplies, healthy ecosystems, and preparing for droughts and floods. 500 Washington Street, Suite 600 San Francisco, CA 94111 tel. (415) 291-4400 fax (415) 291-4401 http://www.ppic.org/water/

Revive the San Joaquin. Non-profit organization which has as its mission “To promote a collective stewardship that sustains the economic, environmental, and recreational benefits of a healthy San Joaquin River, including adequate flows, habitat, and native fisheries. ” 5132 N. Palm, PMB 121 Fresno, CA 93704 tel. (559) 226-0733 fax (559) 228-0547 http://www.revivethesanjoaquin.org/

Self-Help Enterprises Community development organization that seeks “to build and sustain healthy homes and communities.” They have many programs dealing with affordable housing along with programs aimed at access to water, including drought response efforts described here: http://www.selfhelpenterprises.org/programs/community-development/drought-response/ P.O. Box 6520 Visalia, CA 93290 tel. (559) 651-1000 fax (559) 651-3634 http://www.selfhelpenterprises.org/

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Water Education Foundation. A non-partisan, nonprofit organization dedicated to improving public understanding of water resources and water resource issues. 1401 21st Street, Suite 200 Sacramento, CA 95811 tel. (916) 444-6240 fax (916) 448-7699 http://www.watereducation.org/foundation

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Appendix 4 Data sources

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California Department of Finance. Research. http://www.dof.ca.gov/research/

Demographic, Economic, and Financial research units provide data on topics such as population, births, migration, housing, public school enrollment, income, and state revenues.

California Department of Public Health. Data & Statistics. http://www.cdph.ca.gov/DATA/Pages/default.aspx

Gateway to California public health data in many forms, including downloadable files, online queries, and spatial data and maps.

California Department of Water Resources. California Data Exchange Center. http://cdec.water.ca.gov/index.html

Hydrologic data from the California Department of Water Resources, including precipitation, snowpack, streamflow, and reservoir storage.

California Department of Water Resources. Groundwater Information Center. www.water.ca.gov/groundwater/gwinfo/

Data collected from 35,000 wells and from partner organizations provides information on groundwater levels and quality and land subsidence.

National Climatic Data Center (NCDC). Data Access. https://www.ncdc.noaa.gov/data-access

Climate data including observations from land-based stations, marine stations, satellites, radar, and weather balloons, along with climate models and paleoclimate data.

National Oceanic and Atmospheric Administration. U.S. Drought Portal - National Integrated Drought Information System. http://www.drought.gov/drought/

NOAA-led program involving drought information from many federal agencies, universities, and private organizations.

State of California Employment Development Department. Labor Market Information. http://www.labormarketinfo.edd.ca.gov/

California labor market indicators such as the unemployment rate and labor force size, with detail by industry, occupation, counties, and metropolitan areas.

State Water Resources Control Board. Sources of Groundwater Information. http://www.waterboards.ca.gov/water_issues/programs/gama/grid.shtml

State Water Resources Control Board’s compilation of their data related to groundwater along with pointers to groundwater data from many other sources.

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U.S. Census Bureau. American FactFinder. http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml

Portal to finding and downloading data from the U.S. Census and the American Community Survey.

USDA National Agricultural Statistics Service. Data and Statistics. http://www.nass.usda.gov/Data_and_Statistics/index.asp

Agricultural commodity data aggregated nationally from county-level reports.

U.S. Department of Labor Bureau of Labor Statistics. Consumer Price Index (CPI). http://www.bls.gov/cpi/

Data on changes to prices of consumer goods as a measure of economic inflation.

U.S. Geological Survey. National Hydrography Dataset. http://nhd.usgs.gov/

Geographic information systems datasets representing surface water features and watershed boundaries for the U.S.

U.S. Geological Survey. USGS Water Data for the Nation. http://waterdata.usgs.gov/nwis

Water resources data on surface water, ground water, water quality, and water use gathered at around 1.5 million locations across the United States and its territories.

USGS California Water Science Center. California Drought Information. http://ca.water.usgs.gov/data/drought/index.html

Portal for drought information includes description of drought impacts from a hydrologic point of view and data on streamflow, groundwater, surface water, and water quality.

County crop reports

The California Food and Agriculture Code requires county agriculture commissioners to compile annual crop and livestock reports on the amount and value of the county’s commodities. References to historical reports are provided for each of the eight counties in the study area.

County of Fresno - Agricultural Commissioner. Crop Report History. http://www.co.fresno.ca.us/DepartmentPage.aspx?id=54231

County of Madera Department of Agriculture. Crop Reports. http://www.madera- county.com/index.php/publications/crop-reports

Kern County Department of Agriculture and Measurement Standards. Annual Crop Reports. http://www.kernag.com/caap/crop-reports/crop-reports.asp

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Kings County Agriculture Department. Crop Reports 1941-2013. http://www.countyofkings.com/departments/agricultural-commissioner/crop-reports- 1941-2011

Merced County Department of Agriculture. Ag Commissioner - Annual Reports. http://www.co.merced.ca.us/Archive.aspx?AMID=36

San Joaquin County - Office of the Agricultural Commissioner. Annual Crop Reports. http://www.sjgov.org/agcomm/annualrpts.aspx

Stanislaus County Agricultural Commissioner. Crop Reports. http://www.stanag.org/crop- reports.shtm

Tulare County Agricultural Commissioner/Sealer. Crop Reports. http://agcomm.co.tulare.ca.us/default/index.cfm/standards-and-quarantine/crop-reports1/

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