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• W3138913807 startingPage "E1099" @default.
• W3138913807 abstract "Abstract Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snowpack evolution now support a range of drought indicators that better reflect coupled water, energy, and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity, and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts." @default.
• W3138913807 created "2021-03-29" @default.
• W3138913807 creator A5019281835 @default.
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• W3138913807 creator A5052246186 @default.
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• W3138913807 creator A5077888776 @default.
• W3138913807 date "2021-05-01" @default.
• W3138913807 modified "2023-10-14" @default.
• W3138913807 title "Advances in Land Surface Models and Indicators for Drought Monitoring and Prediction" @default.
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