Millions of Californians access drinking water via domestic wells, which are vulnerable to drought and unsustainable groundwater management. Groundwater overdraft and the possibility of longer drought duration under climate change threatens domestic well reliability, yet we lack tools to assess the impact of such events. Here, we leverage 943 469 well completion reports and 20 years of groundwater elevation data to develop a spatially-explicit domestic well failure model covering California’s Central Valley. Our model successfully reproduces the spatial distribution of observed domestic well failures during the severe 2012–2016 drought (n = 2027). Next, the impact of longer drought duration (5–8 years) on domestic well failure is evaluated, indicating that if the 2012–2016 drought would have continued into a 6 to 8 year long drought, a total of 4037–5460 to 6538–8056 wells would fail. The same drought duration scenarios with an intervening wet winter in 2017 lead to an average of 498 and 738 fewer well failures. Additionally, we map vulnerable wells at high failure risk and find that they align with clusters of predicted well failures. Lastly, we evaluate how the timing and implementation of different projected groundwater management regimes impact groundwater levels and thus domestic well failure. When historic overdraft persists until 2040, domestic well failures range from 5966 to 10 466 (depending on the historic period considered). When sustainability is achieved progressively between 2020 and 2040, well failures range from 3677 to 6943, and from 1516 to 2513 when groundwater is not allowed to decline after 2020.

Although many recent studies have quantified the potential effects of climate change on water resource systems, the scientific community faces now the challenge of developing methods for assessing and selecting climate change adaptation options. This paper presents a method for assessing impacts and adaptation strategies to global change in a river basin system at different temporal horizons using a hydro-economic model. First, a multiobjective analysis selects climate change projections based on the fitting of the climate models to the historical conditions for the historical period. Inflows for climate change scenarios are generated using calibrated rainfall-runoff models, perturbing observed meteorological time series according to the projected anomalies in mean and standard deviation. Demands are projected for the different scenarios and characterized using economic demand curves. With the new water resource and demand scenarios, the impact of global change on system performance is assessed using a hydro-economic model with reliability and economic indices. A new economic loss index is defined to assess the economic equity of the system. Selected adaptation strategies are simulated to compare performance with the business-as-usual scenario. The approach is applied to the Jucar River water resource system, in eastern Spain, using climate projections from the European Union (EU) ENSEMBLES project. Results show that the system is vulnerable to global change, especially over the long term, and that adaptation actions can save $€3–65\mathrm{million}/\mathrm{year}$ .

California agriculture will undergo significant transformations over the next few decades in response to climate extremes, environmental regulation and policy encouraging environmental justice, and economic pressures that have long driven agricultural changes. With several local climates suited to a variety of crops, periodically abundant nearby precipitation, and public investments that facilitated abundant low-priced irrigation water, California hosts one of the most diverse and productive agroecosystems in the world. California farms supply nearly half of the high-nutrient fruit, tree nut, and vegetable production in the United States. Climate change impacts on productivity and profitability of California agriculture are increasing and forebode problems for standard agricultural practices, especially water use norms. We highlight many challenges California agriculture confronts under climate change through the direct and indirect impacts on the biophysical conditions and ecosystem services that drive adaptations in farm practices and water accessibility and availability. In the face of clear conflicts among competing interests, we consider ongoing and potential sustainable and equitable solutions, with particular attention to how technology and policy can facilitate progress.

Water use directly causes a significant amount of energy use in cities. In this paper we assessed energy and carbon dioxide emissions related to each part of the urban water cycle and the consequences of some water demand management policies in terms of water, energy, and CO₂ emissions in urban water users, water and energy utilities, and the environment. First, we developed an hourly model of urban water uses by customer category, including water‐related energy consumption. Next, using real data from the East Bay Municipal Utility District in California, we calibrated a model of the energy used in water supply, treatment, pumping, and wastewater treatment by the utility, obtaining also energy costs. Then, using data from the California Independent System Operator, we obtained hourly costs of energy generation and transport to the point of use for the energy utility. Finally, using average emission factors reported by energy utilities, we estimated greenhouse gas emissions for the entire urban water cycle. Results for East Bay Municipal Utility District show that water end uses account for almost 95% of all water‐related energy use; however, the remaining 5% of energy used by the utility still costs over USD12 million annually. The carbon footprint of the urban water cycle is 372 kg CO₂/person/year, representing approximately 4% of the total per capita emissions in California. Several simulations analyze the consequences of different water demand management policies, resulting in significant economic impacts for water and energy utilities and environmental benefits by reducing CO₂ emissions.

Although most freshwater resources are used in agriculture, residential water use is a much more energy intensive user. Based on this, we analyze the increased willingness to adopt water conservation strategies if energy cost is included in the customers' utility function. Using a Water‐Energy‐CO₂ emissions model for household water end uses and probability distribution functions for parameters affecting water and water‐related energy use in 10 different locations in California, this research introduces a probabilistic two‐stage optimization model considering technical and behavioral decision variables to obtain the most economical strategies to minimize household water and water‐related energy bills and costs given both water and energy price shocks. Results can provide an upper bound of household savings for customers with well‐behaved preferences, and show greater adoption rates to reduce energy intensive appliances when energy is accounted, resulting in an overall 24% reduction in indoor water use that represents a 30% reduction in water‐related energy use and a 53% reduction in household water‐related CO₂ emissions. Previous use patterns and water and energy rate structures can affect greatly the potential benefits for customers and so their behavior. Given that water and energy are somewhat complementary goods for customers, we use results of the optimization to obtain own‐price and cross‐price elasticities of residential water use by simulating increases in water and energy prices. While the results are highly influenced by assumptions due to lack of empirical data, the method presented has no precedent in the literature and hopefully will stimulate the collection of additional relevant data.