Your browser doesn't support javascript.
loading
The hydrologic model as a source of nutrient loading uncertainty in a future climate.
Kujawa, Haley; Kalcic, Margaret; Martin, Jay; Aloysius, Noel; Apostel, Anna; Kast, Jeffrey; Murumkar, Asmita; Evenson, Grey; Becker, Richard; Boles, Chelsie; Confesor, Remegio; Dagnew, Awoke; Guo, Tian; Logsdon Muenich, Rebecca; Redder, Todd; Scavia, Donald; Wang, Yu-Chen.
Afiliación
  • Kujawa H; Environmental Science Graduate Program, The Ohio State University, Columbus, OH, USA; Department of Food, Agricultural and Biological Engineering, The Ohio State University, Columbus, OH, USA. Electronic address: kujawa.21@osu.edu.
  • Kalcic M; Department of Food, Agricultural and Biological Engineering, The Ohio State University, Columbus, OH, USA.
  • Martin J; Department of Food, Agricultural and Biological Engineering, The Ohio State University, Columbus, OH, USA; The Sustainability Institute at Ohio State, Columbus, OH, USA.
  • Aloysius N; Department of Biomedical, Biological and Chemical Engineering, University of Missouri, Columbia, MO, USA.
  • Apostel A; Department of Food, Agricultural and Biological Engineering, The Ohio State University, Columbus, OH, USA.
  • Kast J; Environmental Science Graduate Program, The Ohio State University, Columbus, OH, USA; Department of Food, Agricultural and Biological Engineering, The Ohio State University, Columbus, OH, USA.
  • Murumkar A; Department of Food, Agricultural and Biological Engineering, The Ohio State University, Columbus, OH, USA.
  • Evenson G; Department of Food, Agricultural and Biological Engineering, The Ohio State University, Columbus, OH, USA.
  • Becker R; Department of Environmental Sciences, University of Toledo, Toledo, OH, USA.
  • Boles C; LimnoTech, Ann Arbor, MI, USA.
  • Confesor R; Heidelberg University, Tiffin, OH, USA.
  • Dagnew A; Environmental Consulting and Technology, Inc., Ann Arbor, MI, USA; School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA.
  • Guo T; Heidelberg University, Tiffin, OH, USA.
  • Logsdon Muenich R; School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, USA.
  • Redder T; LimnoTech, Ann Arbor, MI, USA.
  • Scavia D; School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA.
  • Wang YC; School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA.
Sci Total Environ ; 724: 138004, 2020 Jul 01.
Article en En | MEDLINE | ID: mdl-32408425
Hydrologic models are applied increasingly with climate projections to provide insights into future hydrologic conditions. However, both hydrologic models and climate models can produce a wide range of predictions based on model inputs, assumptions, and structure. To characterize a range of future predictions, it is common to use multiple climate models to drive hydrologic models, yet it is less common to also use a suite of hydrologic models. It is also common for hydrologic models to report riverine discharge and assume that nutrient loading will follow similar patterns, but this may not be the case. In this study, we characterized uncertainty from both climate models and hydrologic models in predicting riverine discharge and nutrient loading. Six climate models drawn from the Coupled Model Intercomparison Project Phase 5 ensemble were used to drive five independently developed and calibrated Soil and Water Assessment Tool models to assess hydrology and nutrient loadings for mid-century (2046-2065) in the Maumee River Watershed,the largest watershedsdraining to the Laurentian Great Lakes. Under those conditions, there was no clear agreement on the direction of change in future nutrient loadings or discharge. Analysis of variance demonstrated that variation among climate models was the dominant source of uncertainty in predicting future total discharge, tile discharge (i.e. subsurface drainage), evapotranspiration, and total nitrogen loading, while hydrologic models were the main source of uncertainty in predicted surface runoff and phosphorus loadings. This innovative study quantifies the importance of hydrologic model in the prediction of riverine nutrient loadings under a future climate.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sci Total Environ Año: 2020 Tipo del documento: Article Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sci Total Environ Año: 2020 Tipo del documento: Article Pais de publicación: Países Bajos