Specific Objectives of the Project:
Using panel data at the individual and county levels, we propose to investigate the causal impact of extreme temperature events and drought on mental health in California with particular attention to agricultural communities. More specifically, we will:
● use spatially-explicit health data (~245,000 respondents over 18 years of age) from multiple waves of the California Health Interview Survey (CHIS) between 2005 and 2015 to assess the impact of extreme temperatures and drought on psychological distress in agricultural communities
● combine county-level time series on temperature, drought, and suicide rates over the period, 1999–2013 to determine if suicide rates respond to extreme temperatures and drought, and if this response varies between metropolitan and rural counties.

Summary of Results:
The main contribution of the project is in highlighting the relationship between heat waves and adult psychological distress. Previous research in this area, i.e., investigating the role ambient temperature plays in influencing mental health, has considered the impact of rising temperatures on hospitalizations for mental illnesses or suicides, yet there is a lack of attention to how warming affects mental health on a more basic level. In psychiatric research and practice, psychological distress is recognized as a precursor to exhaustion (Arvidsdotter et al. 2016). Furthermore, the majority of analyses in this area focus on non-consecutive instances of extreme heat and extreme cold, rather than heat waves, or cold waves. As sustained extreme weather events, heat waves draw down physiological and economic resources at a greater rate, leaving greater psychological distress in their wake. Consequently, the primary contribution of our study is in showing the type and aspect of heat waves that exerts the most adverse impact on psychological distress. To wit, we find that nighttime heat waves compound psychological distress while daytime heat waves do not. Furthermore, as the number of days in a heat wave increases, the greater the impacts on psychological distress.

A second contribution of the study is to show that non-wave extreme heat events do not compound psychological distress. This result is counter to the clear negative impact that extreme heat appears to have on other mental health outcomes such as emergency department visits or suicides (see for example, Mullins and White 2019 and Burke et al. 2018).

A third and methodological contribution of the study is its assessment of individual heat exposure at a finer geographical scales than seen in previous studies in the heat-health literature. By measuring temperature exposure at the respondent’s residential ZIP code area rather than their county, we ensure that intra-county differences in extreme temperature events are recognized.

From a policy perspective, one takeaway from our research is the possible welfare enhancing impact of a policy that reinforces messaging related to heat warnings and advisories with particular attention to local percentile thresholds. Such a policy is consistent with previous research, such as Guirguis et al.’s (2014) who found that in California, between 1999 and 2009, “there were 11 000 excess hospitalizations that were due to extreme heat over the period, yet the majority of impactful events were not accompanied by a heat advisory or warning from the National Weather Service. These results suggest that heat-warning criteria should consider local percentile thresholds to account for acclimation to local climatological conditions as well as the seasonal timing of a forecast heat wave.”

In terms of the mechanism at work here, we hypothesize the following. Heat exerts an adverse impact on mental health. Adult psychological distress is sensitive to sustained rather than scattered heat exposure, and to nighttime rather than daytime heat. A nighttime heat wave is particularly damaging to mental health. We believe that this may stem from the disruptive impact of nighttime heat waves on human sleep. Our hypothesis is consistent with Lohmus (2018) who, after reviewing experimental data on sleep and temperature, concludes that, “… a heatwave with greatly elevated night temperatures is probably more detrimental for sleep than high temperatures during daytime only.” Lohmus also observes that in people who are not acclimatized to warmer weather, “high nighttime temperatures are almost always deleterious to sleep quality.” Though more interdisciplinary research is often recommended, these preliminary pieces of evidence suggest that the mechanism by which (nighttime) heat affects adult mental health may travel through sleep patterns.

Negative / Incomplete Results. Unfortunately, due to the period over which the project was funded (and extended), challenges arose surrounding Covid-19 that limited the extent to which we could investigate all the objectives listed above. As illustrated in the results section above, while we were able to investigate the role of extreme temperature events on mental health (as measured by psychological distress), we were not able to (i) further disaggregate the analysis to fully investigate the relationship within agricultural communities nor (ii) perform a less granular and complete analysis of suicides and their relationship to extreme temperature events at the county level. Preliminary assessments were performed with lackluster results. That is, preliminary investigations of the relationship between psychological distress and extreme temperature events within agricultural communities did not show any strong relationship nor did preliminary analysis of suicide rates and drought when measured at the county level. The lack of statistically significant results does not suggest that such relationships do not exist, but rather indicate that with the data we had available and the specifications we were limited to, such relationships were not identified. We feel that both of these areas warrant further research.

Specific Objectives of the Project
Using a dynamic programming model of irrigated agricultural production linked to a lumped-parameter groundwater model, we:
• Investigated the impacts of increased perennial crop production regional net benefits and groundwater sustainability, and
• identified the role annual crops play in mitigating the impacts of drought and, consequently, the impacts of trends towards less annual crop cultivation on resilience to drought.

Project Report/Summary of Results
This study provides the first analysis within the agricultural economics literature that combines the economic dynamics of perennial crops and groundwater management, thus extending the literature on both topics. Characteristics of perennial crops include large fixed costs from planting, multi-year periods of establishment and senescence, age-dependent productivity and input requirements are all included in the model here. The resulting transitional dynamics imply a strong incentive to pump groundwater in the face of surface water reductions, with additional incentives when the price of perennials increase as the case in California’s most recent drought. A comparison of outcomes from modeling frameworks from the literature which represent perennial crops in a more simplified manner highlight how these simpler models are, by construction, limited in their ability to capture such effects and therefore may not be reliable aids for policy analysis in periods of water scarcity.

Understanding how the pressures to pump groundwater vary under different cropping systems, biophysical characteristics, and market factors is increasingly important in California as well as most regions worldwide given the pervasiveness of groundwater depletion and associated efforts to counter such overdraft. Market forces combined with interruptions to water supplies can create powerful incentives to continue pumping groundwater almost regardless of the height of the aquifer. Clearly, growers will rely on groundwater pumping as a means of protecting their investment in perennials. This highlights the need for monitoring and enforcement of groundwater pumping, such as the recently enacted Sustainable Groundwater Management Act in California (SGMA) is to be successful in limiting aquifer draw-down in California. A relevant cautionary note may be drawn from the Australian experience. While the Murray-Darling Basin Plan was intended to spread the pain of reduced surface water allocations across the basin, it has been undermined by an allegedly illegal increase in water use by irrigators in New South Wales (Keane 2019). It would be wishful thinking to imagine a similar fate is not possible, or even likely, should a major drought coincide with the deadline for implementation of SGMA in California.

Specific Objectives of the Project

Develop a theoretically consistent approach for estimating the welfare effects of switching to block-rate water pricing; apply the model to a data set from a southern California water district; investigate distributional effects particularly for disadvantaged groups.

Summary of Results

During the funding cycle, the PIs worked closely with a graduate student to develop the theoretical framework and convert it to computer code for empirical estimation. We have made substantial progress and expect to have preliminary results ready for disse mination at two conferences this summer. The theoretical framework is complete and has been written-up as a draft manuscript (see below). The framework essentially modifies the DCC statistical structure so that it is applicable to a direct utility function rather than a demand function. The resulting likelihood equation is similar to but more complicated than the standard DCC likelihood equation and requires simulation techniques for evaluation. We are currently writing the computer code to implement these techniques and will then apply the model to an existing dataset to estimate the welfare effects of changes in block rate water prices.

The objectives of this research were to evaluate the impact of a water conservation program being promoted by many of the water districts in southern California—the high efficiency sprinkler nozzle program—on water use. In particular, we intended to investigate the impact of these sprinkler heads on water use at the household level and the subsequent potential impact at the district level. Furthermore, we attempted to estimate an adoption model that identified factors which influence a household's decision to adopt the technology.

In this program, households can receive vouchers for up to 25 free high efficiency sprinkler nozzle heads. The data consists of monthly water use and household characteristics over ten years on approximately 120,000 residential meters. Our analysis consists of two approaches to evaluating these potential effects. First, we compared different subpopulations average use before and after adoption; second, we estimate a discrete continuous choice (DCC) model. Preliminary results suggest that residential customers who redeemed vouchers for 25 high efficiency sprinkler nozzles typically experienced a subsequent reduction in overall water use of around 1.2%. As a fraction of total outdoor water use, the reduction is around 2.7%. This is markedly lower than the technically achievable reduction of 30% that has been estimated by the manufacturer.

In terms of what factors seem to influence adoption, we find that adoption rates were positively related to house value, income levels, average water prices, ET, household size, and landscape area (although nonlinearly); adoption rates were negatively related to distance to the nearest nozzle head distributor (which suggests travel and time costs are important factors influencing whether households redeem their vouchers). Adoption rates for those in the top, middle, and bottom terciles of water use were approximately 2.3%, 2.0%, and 0.78%. Ongoing research is currently focusing on gathering more complete information on those households that redeemed the vouchers in terms of the number of nozzles they actually installed and the degree to which they were installed correctly.

The objective of this research is to estimate the damages to irrigated agriculture from salinity and limited drainage conditions in the San Joaquin Valley, California and in particular, to the farms along the Westside. A hedonic property value model of farmland valuation is developed to analyze the relationships between sales prices on 1,914 agricultural parcels sold between 2004-2010 (in and around the SJV) and groundwater depth and groundwater salinity while controlling for environmental, economic, and institutional factors. We collected sales price and parcel characteristic data on approximately 1900 farms in Tulare, Fresno, Kings, Kern, Merced, Napa, San Luis Obispo, Riverside, Monterey and Imperial countries. Salinity and drainage problems often arise in situations where a highly saline water table, which along the westside of the Central Valley has resulted from a lack of drainage opportunities, threatens soil quality and crop production. One way to possibly illustrate how the lack of drainage services and salinity impacts farmland values is to compare the elasticities of groundwater salinity across three agricultural regions—the Central Valley, the Central Coast, and the North Coast—where the Central Valley has a significant area of farmland confronting high water tables due to the lack of drainage services. Results show that the elasticity of groundwater salinity for the Central Valley is -0.13 and is highly significant, whereas the elastic ity of groundwater salinity for the North Coast and Central Coast is 0.13 and -0.09, respectively, although the North Coast estimate is not statistically significant. Alternatively, we also estimate the impact of changes in groundwater depth for different levels of salinity. Categorizing groundwater salinity as low (EC<.6 dS/m), moderately low (EC<.6 dS/m), moderately low (.6<EC<1dS/m), moderately high (1<EC<2 dS/m), and high (2<EC<11 dS/m), we find that the elasticity of groundwater is 0.08 (and statistically significant) when it is categorized as high salinity, 0.06 (and statistically significant) when it is categorized as moderately high salinity, -0.06 (and statistically significant) when it is categorized as moderately low salinity, and -0.48 (and statistically significant) when it is categorized as low salinity. These results suggest that the more saline the groundwater source, the less valuable the land. In fact, when groundwater salinity levels move from moderately low levels to moderately high levels, farmland values increase with depth to the water table; conversely, and what is typically found in the literature, as depth to the groundwater table increases, land values decrease (e.g., Schlenker et al. 2007). In conclusion, our results suggest that assessments as to the value of groundwater to irrigated agriculture must be conditioned by the quality of the groundwater.

The broad objective of this work is to improve upon zonal approaches to recreation demand modeling. A standard zonal model ignores important aspects of spatial heterogeneity that are inherent in recreation demand contexts. The standard approach aggregates across groups of heterogeneous agents, and models them as homogenous points of origin for demand estimation. The standard approach also ignores that these heterogeneous agents deliberately choose their points of origin, which introduces a source of bias into the estimation. This work has produced a peer-reviewed article that addresses these shortcomings. This article, “A Latent Class Approach to Modeling Endogenous Spatial Sorting in Zonal Recreation Demand Models” (Land Economics86(4):800-816), demonstrates how a latent class count data model can control for unobserved heterogeneity that may lead to spatial sorting of recreationists. Results show that welfare estimates from this model for a southern California wilderness site are substantially smaller than for the standard approach.