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Use of Water Quality Model Uncertainty Analysis to Develop Sampling Design Criteria for In-stream Carbon

机译:利用水质模型不确定性分析制定流式碳的采样设计标准

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The present research is motivated by the need to include recognized uncertainty within water quality sampling methods performed in agricultural and urban watersheds. We use uncertainty analysis of water quality model results to help define a sampling method for particulate organic carbon in disturbed watershed systems. Low-gradient watersheds with agriculture and urban land use disturbances receive a significant portion of organic matter from in-stream benthic carbon production in which coupled physical and biological processes govern the degree of organic carbon accrual. A lack of uniformity in methodological approaches and temporal domains has driven the need to develop an appropriate and repeatable sampling strategy to capture the range and distribution of transported organic carbon. Therefore for this study a conceptual model for sediment carbon fate and transport was applied to a lowland watershed system with pronounced fluvial storage and agriculturally and urban disturbed lands. A suite of sampling routines was implemented to test the sensitivity of the transported carbon (C_T) distribution, aiming to isolate the importance of physical and biological processes. Results of the study highlight C_T followed a Gamma distribution, with a root mean square error approximation of 0.066. Low flow sampling routines performed as well as routines including high and low flows, contradicting previous studies that emphasize capturing high flow events for C_T variability. Likewise, monthly and bimonthly sampling routines were as adequate as a weekly or bimonthly routine. Although the two year routine did well at capturing variability, the equality of the central measure of tendency was not statistically significant, imploring us to recommend a three plus year study if feasible, especially if consecutive years have similar hydrologic patterns.
机译:本研究的动机是需要在农业和城市流域执行的水质采样方法中纳入公认的不确定性。我们使用水质模型结果的不确定性分析来帮助定义受干扰流域系统中颗粒有机碳的采样方法。农业和城市土地利用受到干扰的低坡度流域从河流底栖碳生产中获得了很大一部分有机物,其中物理和生物过程共同控制着有机碳的累积程度。方法学方法和时域上缺乏统一性,因此有必要制定一种适当且可重复的采样策略,以捕获所运输的有机碳的范围和分布。因此,在本研究中,将沉积物碳的归宿和运输的概念模型应用于具有明显河流储量以及农业和城市受干扰土地的低地流域系统。实施了一套采样程序,以测试运输的碳(C_T)分布的敏感性,目的是隔离物理和生物过程的重要性。研究结果突出显示C_T遵循Gamma分布,均方根误差近似为0.066。执行的低流量采样例程以及包括高流量和低流量的例程,与以前的研究相矛盾,后者强调捕获高流量事件以获取C_T变异性。同样,每月和每两个月的例行采样与每周或每两个月的例行采样就足够了。尽管两年例行程序在捕获变异性方面做得很好,但趋势的中心度量的均等性在统计上并不显着,因此建议我们在可行的情况下建议进行为期三年以上的研究,尤其是连续两年的水文模式相似时。

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