Emerging interdisciplinary science efforts are providing new understanding of the interdependence of food, energy, and water (FEW) systems. These science advances, in turn, provide critical information for coordinated management to improve the affordability, reliability, and environmental sustainability of FEW systems. Here we describe the current state of the FEW nexus and approaches to managing resource conflicts through reducing demand and increasing supplies, storage, and transport. Despite significant advances within the past decade, there are still many challenges for the scientific community. Key challenges are the need for interdisciplinary science related to the FEW nexus; ground‐based monitoring and modeling at local‐to‐regional scales; incorporating human and institutional behavior in models; partnerships among universities, industry, and government to develop policy relevant data; and systems modeling to evaluate trade‐offs associated with FEW decisions.

Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community‐managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally‐managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responses to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. Continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.

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[1] Using high-resolution lidar scans of a braided stream deposit, we investigate solute transport characteristics and streamline-based connectivity that are lost when simulating the outcrop heterogeneity using geostatistical methods based on two-point covariance functions. Attributes of the lidar scans were used to segment the outcrop into sand-and gravel-dominated lithofacies. Simulated fields were created using sequential indicator methods based on the two-point covariance of the binary segmented lidar field. Sand and gravel lithofacies are then assigned reasonable hydraulic conductivity values. Twodimensional advective-diffusive solute transport simulations in the segmented lidar field show strong solute focusing through gravel-dominated strata, resulting in a heavy-tailed (e.g., non-Fickian) breakthrough. The sequential indicator fields do not replicate the early and late time arrival characteristics. Streamline-based analysis shows that the sequential indicator fields do not reproduce connectivity of the segmented lidar field. Even when the sequential indicator fields are highly conditioned, streamlines migrate between sands and gravel beds nearly twice as often as streamlines in the segmented lidar field.