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- W4242827103 abstract "Abstract. Globally, many different kinds of water resources management issues call for policy and infrastructure based responses. Yet responsible decision making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal-to-century long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle – a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management." @default.
- W4242827103 created "2022-05-12" @default.
- W4242827103 creator A5002766884 @default.
- W4242827103 creator A5008324501 @default.
- W4242827103 creator A5015678021 @default.
- W4242827103 creator A5019794106 @default.
- W4242827103 creator A5019878009 @default.
- W4242827103 creator A5034553808 @default.
- W4242827103 creator A5072661874 @default.
- W4242827103 creator A5089753390 @default.
- W4242827103 date "2013-06-20" @default.
- W4242827103 modified "2023-10-14" @default.
- W4242827103 title "Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene" @default.
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