The Sustainable Groundwater Management Act (SGMA), enacted in 2014, serves as California’s first foray into establishing a comprehensive groundwater management program. Under this legislation, basins are required to mitigate groundwater overdraft to reach sustainable conditions by 2040 or 2042. Reductions in groundwater pumping are anticipated to drive substantial shifts in the San Joaquin Valley’s agricultural sector, which has historically depended on groundwater to provide water for irrigation. This research examines a case study of SGMA implementation in the Kings and Tulare Lake groundwater basins, focusing on potential impacts for agricultural land cover and economics. Publicly available information on spatial cropping patterns, irrigation requirements, and crop production economics as well as overdraft information and historical water availability from Groundwater Sustainability Plans (GSPs) are used to calibrate a hydroeconomic agricultural production optimization model representing the agriculture in the study area. Scenarios integrating overdraft responsibilities with options for surface water trading and groundwater supply augmentation through recharge are modeled to explore potential outcomes for future agriculture under SGMA. Results suggest ranges and distributions for land fallowing and losses of agricultural revenue under a variety of possible scenarios. Findings also highlight the importance of water trading and groundwater recharge programs in meeting sustainability in the basins and barriers to implementing these programs are discussed.

California has diversified landscapes and complex water networks, contributing to its intertwined ecosystems’ relations so that biodiversity conservation and human socio-economic development share close to the same set of water and land resources. Biodiversity is threatened by climate change. Intermediate conservation actions are required and need to be supported by scientific information that minimizes the trade-offs between biodiversity conservation and human socio-economic development.In this doctoral research, I designed a synthesis future-oriented approach that integrates multi-disciplinary methods, namely economic optimization, remote sensing, ecological modeling of species distribution, and systematic conservation plan. With this approach, I aim to help us find the conservation solutions that are good today but also are going to be good in the future climate change. With economic optimization, I modeled the fluctuation in agricultural water and land use across different management and climate change scenarios but also across different water year types that are embroidered by the Mediterranean climate. I also find that the upper bound dual value of the economic optimization model water network can be a good indicator for the conservation of water use. Cost is a critical piece of information for the later systematic compensation planning. I used species distribution modeling to predict species abundance distribution with climate change to represent the change in conservation benefit as a result of species migratory and phenological adaptation to climate change. Land and water opportunity costs under climate were updated based on simulation optimization models. Resulted in species range and cost were used for spatial and temporally explicit, systematic conservation planning. I applied this approach to California’s Central Valley and predicted the weekly ranges of shorebird species of a range of morphological features and conservation status. Water and land opportunity costs were estimated in climate change and historical scenarios. The conservation actions considered in this research are to create dynamic flooded habitats on agricultural lands as a nature-based solution to carbon sequestration, groundwater overdraft, and shorebird conservation. I found that if we navigate the use of environmental flow in a relatively blind way, it will significantly conflict with agricultural production with minimal positive ecosystem benefits. To do it right, we must understand the new hydrological patterns and build more storage to make use of excess flows, particularly in the southern part of Central Valley. Climate change and water conservation management will increase the costs of water used for environmental use. Therefore, I considered an increased cost of water in creating dynamic flooded habitats in the final prioritization analysis by using the economic models’ outputs. Conservation prioritization was created based not only on species' seasonal dynamics but also on varying seasonal costs resulting from timed land use on a cultured landscape of California and a range of water availability across seasons and different water year types. I considered both spatial and temporal hydrological connectivity, which might be even more important for aquatic species of fish and amphibians, and improved conservation efficacy. The intellectual merit of this thesis is synthesizing different metrologies across disciplines and making broader implications for integrated agricultural land use and water management in California for climate change adaptation and ecosystem conservation.

This research analyzes the potential effects of climate change and land use dynamics on groundwater in highly productive agricultural regions dependent on water imports and groundwater regulation. Before focusing on the research topic, solving a series of conceptual, operational, and computational challenges, such as having reliable, integrable, and fast models, was necessary. So, in the first part of the research, we evaluate the performance of three emulators of the sophisticated hydrology model known as the Fine Grid California Central Valley Groundwater-Surface Water Simulation Model (C2VSimFG) to estimate how climate and agriculture affect groundwater levels. Once the best emulator was identified, we assessed the hypothesis that groundwater levels in the Greater Kern County Region would exhibit a more rapid decline with projected climate change scenarios compared to a historical climate resembling 1995 and 2015. Finally, we focus on determining economically and environmentally optimal operational policies for the Shafter-Wasco irrigation district by considering the conjunctive water use approach and identifying the best policies through Bayesian Optimization Programming. The findings suggest groundwater levels are likely to decline unless agricultural water demand is reduced and recharge is increased, with climate scenarios exacerbating this decline compared to historical conditions. Our findings underscore the balance between profit and aquifer recovery, indicating farmers' need to curtail profits to achieve groundwater sustainability. Ultimately, our method can potentially integrate water and agricultural systems facing various uncertainties, providing valuable insights into optimal operational policies and tradeoffs.

This paper employs an economic-engineering optimization model to explore water supply options for environmental restoration of the Colorado River Delta, Mexico. Potential water sources include reductions in local agricultural and urban Water use through water markets, wastewater reuse, and additional Colorado River flows from the United States. For these alternatives, the optimization model estimates operating and water scarcity costs, water scarcity volumes, and marginal economic costs of environmental flows and values of additional Colorado River flows from the United States over a range of required delta environmental flows. Economic values for agricultural and urban water uses were estimated by two ancillary models. The results provide insights into economically promising water supplies for restoration activities. Quantifying the trade-off between agricultural and urban economic valuation and environmental flows provides a framework for decision makers to quantify their valuation of environmental flows. The model also provides a framework for integrating additional knowledge of the system as information becomes available.

https://doi.org/10.15447/sfews.2016v14iss1art6

Reservoir operating rules for water resource systems are typically developed by combining intuition, professional discussion, and simulation modeling. This paper describes a joint optimization–simulation approach to develop preliminary economically-based operating rules for major reservoirs in California’s Sacramento Valley, based on optimized results from CALVIN, a hydro-economic optimization model. We infer strategic operating rules from the optimization model results, including storage allocation rules to balance storage among multiple reservoirs, and reservoir release rules to determine monthly release for individual reservoirs. Results show the potential utility of considering previous year type on water availability and various system and sub-system storage conditions, in addition to normal consideration of local reservoir storage, season, and current inflows. We create a simple simulation to further refine and test the derived operating rules. Optimization model results show particular insights for balancing the allocation of water storage among Shasta, Trinity, and Oroville reservoirs over drawdown and refill seasons, as well as some insights for release rules at major reservoirs in the Sacramento Valley. We also discuss the applicability and limitations of developing reservoir operation rules from optimization model results.

Agricultural practices have developed immensely to feed a globally growing population. As our agricultural systems have grown for more globalized food systems, many practices have been implemented without considering the sustainability of these actions. Annually, approximately one-third of food globally produced for human consumption is lost or wasted, contributing to 19%-29% of our global anthropogenic greenhouse gas emissions. Therefore, finding a balance between the environment, society, and economics is of utmost importance for our growing agricultural needs. Environmental, social, and economic advantages and disadvantages can be assessed through Life Cycle Assessment (LCA) to better understand and improve our current food systems. This dissertation proposal conducts a combination of four different environmental and social LCAs and advances LCA methodology. The environmental impacts of fresh tomatoes produced in California are assessed in the first chapter and the second chapter proposes a methodology to assess social implications of the strawberry system in California. Lastly, the third chapter includes a combination of addressing environmental and social implications of large-scale pineapple farming in the northern area of Costa Rica. The E-LCA methodology is advanced through the inclusion of quantified farm level food loss as Life Cycle Inventory (LCI). Similarly, S-LCA framework is improved upon through the refining of the 2020 United Nations Environment Program’s methodology and demonstrating concrete examples of abstract social performance. California and Costa Rica were chosen as case study areas because of the role agriculture plays in their economy and their increasing importance on environmental conservation. The goal of this dissertation proposal is to address environmental and social implications of agricultural products and improve LCA methodology and inform participating growers and consumers of the sustainability of our food systems.