Hydrological records can be used to reconstruct the resilience of watersheds to climatic extremes
Fecha
2024Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión publicada / Argitaratu den bertsioa
Impacto
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10.1038/s43247-023-01181-x
Resumen
Hydrologic resilience modeling is used in public watershed management to assess watershed ability to supply life-supporting ecoservices under extreme climatic and environmental conditions. Literature surveys criticize resilience models for failing to capture watershed dynamics and undergo adequate testing. Both shortcomings compromise their ability to provide management options reliably protectin ...
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Hydrologic resilience modeling is used in public watershed management to assess watershed ability to supply life-supporting ecoservices under extreme climatic and environmental conditions. Literature surveys criticize resilience models for failing to capture watershed dynamics and undergo adequate testing. Both shortcomings compromise their ability to provide management options reliably protecting water security under real-world conditions. We formulate an empirical protocol to establish real-world correspondence. The protocol applies empirical nonlinear dynamics to reconstruct hydrologic dynamics from watershed records, and analyze the response of reconstructed dynamics to extreme regional climatic conditions. We devise an AI-based early-warning system to forecast (out-of-sample) reconstructed hydrologic resilience dynamics. Application to the La Tejería (Spain) experimental watershed finds it to be a low dimensional nonlinear deterministic dynamic system responding to internal stressors by irregularly oscillating along a watershed attractor. Reconstructed and forecasted hydrologic resilience behavior faithfully captures monthly wet-cold/dry-warm weather patterns characterizing the Mediterranean region. [--]
Materias
Watershed management,
Climatic extremes,
Hydrologic resilience modeling
Editor
Nature Research
Publicado en
Communications Earth and Environment (2024), 5(19)
Departamento
Universidad Pública de Navarra/Nafarroako Unibertsitate Publikoa. Institute on Innovation and Sustainable Development in Food Chain - ISFOOD
Versión del editor
Entidades Financiadoras
All authors acknowledge funding from the Ministerio de Economía y Competitividad (Government of Spain) via the Research Project CGL2015-64284-C2-1-R. R.H. acknowledges support from USDA-NIFA (FLA-ABE-005414). R.H. and R.M.-C. acknowledge support from the University of Florida Artificial Intelligence Research Catalyst Fund.