This project examined the complex coupled human and natural system dynamics between poverty, land use, and water supply dynamics in the Tulare Lake Basin of California - one of the most productive agricultural regions in the world. Here, surface and groundwater supplies are strained by agricultural water demand which have left rural communities and ecosystems vulnerable to hydro-climatic variability. Our project examined these system dynamics from three unique perspectives. 

First our project examined the dynamics of the natural hydrologic system under various climate and land use changes and their impact on agricultural production in the region to understand how these may impact interconnected surface and groundwater systems and communities. We assessed future changes in natural streamflow and surface water availability in four major tributaries to the Tulare Lake basin (Kings, Kaweah, Tule and Kern rivers) using the Soil Water Assessment Tool and CMIP5 climate projections (HadGEM_ES, CNRM-CM5, CanESM2 and MIROC5). Results indicate that in the coming decades under a warming climate, peak streamflow is expected to increase 0.5–4 times in magnitude and to arrive 2–4 months earlier in the year because of earlier snowmelt. Using groundwater modeling, we ran a groundwater model in a multi-objective optimization to identify the optimal for intentional groundwater recharge using biophysical (e.g. groundwater storage gain, regional water level rise) and economic constraints (e.g. capital cost, surface water conveyance or lift cost, water acquisition cost, maintenance cost). Results identified not only optimal recharge locations but also show that if the 10% largest flows were recharged, groundwater storage gain would double at a cost of $30 - $50 million per km3.

Second,  the project aimed to understand the interconnections between water supply dynamics and the social systems in which they are embedded in disadvantaged communities within the Tulare Lake Basin. Disadvantaged communities are those that are disproportionately impacted by land use and cropping decisions of large landowners, whose median income is less than 80% of the California statewide median and exhibit characteristics that include: an inability to achieve the economy of scale, lower levels of educational attainment, and limited capacity to influence regional and state dialogue concerning water policy. Through community meetings, in-depth interviews with various stakeholders and agricultural actors in disadvantaged communities in the Tulare Lake Basin we were able to identify and articulate the ways in which various groups of stakeholders perceived, experienced, and influenced land-use and water resource allocation decisions and policy in the study area.  One key challenge in this area was understanding the ways in which policy preferences and values influence policy debates and discussions.  We conducted interviews, focus groups, and in person ethnographic research with over 117 participants from three stakeholder groups in the region: policymakers, farmers, and community members. Our analysis identified the primary stakeholders and governance structure surrounding water management in the region as well as the challenges and opportunities experienced by various stakeholder groups.  The information helped to inform the results of modeling scenarios, brought diverse groups of stakeholders together in discussion of these issues, and identified adaptation strategies utilized by farmers and community members to address water scarcity and influence policy decisions. 

 Third, our project sought to understand how water management and land use decisions can impact the natural system. In doing so, our project considered feedbacks between water resources and agriculture in California's Central Valley, with the potential to extend to other systems. One key challenge in this area is the expansion of perennial crops, which has continued despite severe droughts and new regulations on groundwater pumping. As a result, agricultural areas may be especially vulnerable to changing climate, as these crops cannot be fallowed without substantial crop and economic losses. This land use dataset was derived from statewide pesticide reports over the period 1979-2019. We then applied machine learning approaches to predict land use change given water availability and other factors, with the goal of developing models that are both accurate and interpretable.

 Comprehensively our project illuminated how the natural system surrounding water supply is affected by the human system through land use and water management decisions, and simultaneously how the human system is impacted by the natural system through water availability and variability. In doing so we developed methods to understand the complex relationships between water supply regulation and socioeconomic outcomes for landowners and communities, particularly in cases where over extraction of groundwater leads to dry wells or contamination. These problems were modeled as networks of actors to generalize the problem of resource management. We aimed to identify the properties of the actors and regulators in the system that lead to sustainable outcomes. These efforts were coupled with early warning signals of long-term water supply vulnerabilities under climate change. Collectively, the project utilized statistical and theoretical modeling advances to better understand water-agriculture feedbacks in the Central Valley and similar water-stressed systems.

Last Modified: 01/02/2024
Modified by: Helen Dahlke