The hydrologic model as a source of nutrient loading uncertainty in a future climate

Area of Science:

• Environmental science
• Climate modeling
• Hydrologic modeling

Background:

• Climate projections are increasingly used with hydrologic models to predict future water conditions.
• Uncertainty exists in predictions due to variations in climate and hydrologic model inputs, assumptions, and structures.
• Existing studies often use multiple climate models but fewer hydrologic models, and may assume nutrient loading mirrors discharge patterns.

Purpose of the Study:

• To characterize and quantify uncertainty from both climate and hydrologic models in predicting riverine discharge and nutrient loading.
• To assess future hydrology and nutrient loadings under mid-century climate projections in the Maumee River Watershed.
• To determine the dominant sources of uncertainty in predicting future hydrologic conditions and nutrient loads.

Main Methods:

• Utilized six climate models from the Coupled Model Intercomparison Project Phase 5 ensemble.
• Employed five independently developed and calibrated Soil and Water Assessment Tool (SWAT) models.
• Analyzed predictions for mid-century (2046-2065) in the Maumee River Watershed, focusing on discharge and nutrient loadings (total nitrogen and phosphorus).

Main Results:

• No clear consensus emerged on the direction of change for future nutrient loadings or discharge.
• Analysis of variance indicated climate model variation was the primary source of uncertainty for total discharge, tile discharge, evapotranspiration, and total nitrogen.
• Hydrologic models were identified as the main source of uncertainty for predicted surface runoff and phosphorus loadings.

Conclusions:

• This study quantifies the significant influence of hydrologic model selection on predicting riverine nutrient loadings under future climate scenarios.
• Understanding the interplay between climate and hydrologic model uncertainty is crucial for accurate future environmental predictions.
• The findings underscore the need to consider a suite of hydrologic models alongside climate models for robust assessments.