Developing a data-driven understanding of water management connectivity across physical and social boundaries

Abstract:

Limited and variable accounting of surface water and groundwater complicates sustainable water management. For example, California's Sustainable Groundwater Management Act (SGMA) requires coordination across distinct physical basins and management boundaries, each with varied data endowments and management structures. In the groundwater-dependent San Joaquin Valley, scarce or inconsistent data hinder traditional model-driven approaches, and the spatial extent of coordination for effective groundwater management is unclear. In this setting, we explore the capacity for data-driven approaches to provide spatially-consistent and extensible tools for sustainable water management. We synthesize spatiotemporal land surface datasets relevant to joint surface water and groundwater use. Building on previous work, we construct data-derived subsurface water connectivity boundaries by clustering satellite land surface displacement data from interferometric synthetic aperture radar (InSAR). We compare these data-driven InSAR boundaries to water management agency-defined surface water basins and groundwater basins, as well as new groundwater sustainability agency boundaries. We find that data-driven connectivity boundaries diverge from existing management boundaries, and we explore the ramifications of that divergence with respect to land use, climate, hydrology, and infrastructure. We discuss implications for existing sustainability indicators, and explore the design of indicators that capture basic features of connectivity both within and beyond existing management boundaries. This research presents an example of exploiting emerging spatiotemporal data sources to develop straightforward tools to understand and better manage coupled human-water systems.