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A framework for validating watershed ecosystem service models in the United States using long-term water quality data: Applications with the InVEST Nutrient Delivery (NDR) model in Puerto Rico.
Valladares-Castellanos, Mariam; de Jesús Crespo, Rebeca; Xu, Y Jun; Douthat, Thomas H.
Afiliação
  • Valladares-Castellanos M; Department of Environmental Sciences, Louisiana State University, Baton Rouge, LA, USA.
  • de Jesús Crespo R; Department of Environmental Sciences, Louisiana State University, Baton Rouge, LA, USA.
  • Xu YJ; Department of Renewable Natural Resources, Louisiana State University, Baton Rouge, LA, USA; Coastal Studies Institute, Louisiana State University, Baton Rouge, LA, USA.
  • Douthat TH; Department of Environmental Sciences, Louisiana State University, Baton Rouge, LA, USA. Electronic address: tdouthat1@lsu.edu.
Sci Total Environ ; 949: 175111, 2024 Nov 01.
Article em En | MEDLINE | ID: mdl-39079631
ABSTRACT
Modeling of watershed Ecosystem Services (ES) processes has increased greatly in recent years, potentially improving environmental management and decision-making by describing the value of nature. ES models may be sensitive to different conditions and, therefore, should ideally be validated against observed data for their use as a decision-support instrument. However, outcomes from such ES modeling are barely validated, making it difficult to assess uncertainties associated with the modeling and justify their actual usefulness to develop generalizable management recommendations. This study proposes a framework for the systematic validation of one of such tools, the InVEST Nutrient Delivery Model (NDR) for nutrient retention estimates. The framework is divided into three stages 1) running the NDR model inputs, processes, and outputs; 2) building a long-term reference dataset from open access water quality observations; and 3) using the reference data for model calibration and validation. We applied this framework to twenty watersheds in the Commonwealth of Puerto Rico, where data availability resembles thar of watersheds across the United States. Long-term water quality data from monitoring stations facilitated model calibration and validation. Our framework provided a reproducible method to linking the vast monitoring network in the U.S. and its territories for evaluating the InVEST's NDR model performance. Beyond the framework development, this study found that the InVEST NDR model explained 62.7 % and 79.3 % of the variance in the total nitrogen and total phosphorus between 2000 and 2022, respectively, supporting the suitability of the model for watershed scale ecosystem services assessment. The findings can also serve as a reference to support the use of InVEST for other locations in the tropics without publically available monitoring data.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE País/Região como assunto: Puerto rico Idioma: En Revista: Sci Total Environ Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Holanda
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE País/Região como assunto: Puerto rico Idioma: En Revista: Sci Total Environ Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Holanda