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Science-based approaches to water resources management: Studies in remote sensing, groundwater and California's Central Valley
- Miro, Michelle
- Advisor(s): Margulis, Steven A
Abstract
This dissertation is motivated by the principle that data availability and scientific analysis are fundamental for effective natural resources management. The research in this thesis presents approaches that can enhance water management institutions’ ability to more comprehensively measure and manage groundwater resources. This research draws from a diverse scientific body of work in numerical modeling, remote sensing science, hydrology and public policy. A robust, artificial neural network model is presented that downscales GRACE gridded land datasets (~150,000km2) to higher-resolution (~16km2) groundwater storage change estimates, a 100-fold higher resolution. This modeling approach uses minimum input data - five key data sets and minimally processed GRACE data - and thus has applicability to data scarce regions. For California’s Central Valley, downscaled groundwater storage change maps can be used to inform groundwater management as they point to specific sub-regional patterns in groundwater storage change. This dissertation also presents a framework intended to strengthen the scientific underpinnings of groundwater management in California. A methodology is developed to calculate sustainable yield under California's new Sustainable Groundwater Management Act (SGMA) that is flexible to varying input data as well as to a given region’s local socio-economic and environmental dynamics. The long-term implications of three different determinations of sustainable yield are assessed through an empirical groundwater balance that is projected to 2040. The results of these three scenarios show that there are tradeoffs to be had between groundwater availability, future climate uncertainty and socio-economic preferences that must be carefully weighed. Finally, research is presented that addresses the future of remote sensing. A novel approach to quantify the value of geospatial data for decision makers is presented, along with an unbiased assessment of a rapidly developing branch of remote sensing – privately-owned and privately-funded small satellites. Overall, groundwater management in California is a critical example of the need for robust management strategies in the face of increasing resource scarcity and rising climate variability. California is not alone in this task. The lessons and takeaways presented in this dissertation can be applied to address similar natural resource management challenges across the globe.
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