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水文学模型作为未来气候下营养物负荷不确定性的一个来源。

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

机构信息

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.

Department of Food, Agricultural and Biological Engineering, The Ohio State University, Columbus, OH, USA.

出版信息

Sci Total Environ. 2020 Jul 1;724:138004. doi: 10.1016/j.scitotenv.2020.138004. Epub 2020 Mar 16.

Abstract

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.

摘要

水文模型越来越多地与气候预测结合使用,以深入了解未来的水文状况。然而,水文模型和气候模型都可以根据模型输入、假设和结构产生广泛的预测。为了描述一系列未来的预测,通常使用多个气候模型来驱动水文模型,但使用一系列水文模型的情况较少。水文模型通常报告河川径流量,并假设营养负荷将遵循类似的模式,但情况可能并非如此。在这项研究中,我们对气候模型和水文模型在预测河川径流量和营养负荷方面的不确定性进行了描述。从耦合模型比较计划第 5 阶段的集合中选取了六个气候模型,用于驱动五个独立开发和校准的土壤和水评估工具模型,以评估 2046-2065 年中期的莫米河流域的水文和营养负荷,这是流入大湖的最大流域。在这些条件下,未来营养负荷或径流量变化的方向没有明确的共识。方差分析表明,在预测未来总径流量、排水(即地下排水)、蒸散量和总氮负荷方面,气候模型之间的差异是不确定性的主要来源,而在预测地表径流量和磷负荷方面,水文模型是不确定性的主要来源。这项创新研究量化了在未来气候下水文模型在预测河川营养负荷中的重要性。

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