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Reliability-Based Water Quality Assessment with Load Resistance Factor Design: Application to TMDL

机译:基于负载阻力因子设计的基于可靠性的水质评估:在TMDL中的应用

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摘要

Effective load reduction strategies rely on an accurate Total Maximum Daily Load (TMDL) calculation, which quantifies contaminant loading from various sources. There is a wide range of methods to consider uncertainties in TMDLs: from simple, conservative assumptions regarding factors that contribute to the TMDL required margin of safety (MOS), to probability-based approaches such as Monte Carlo simulations, which explicitly quantifies TMDL uncertainty. In this paper the authors adapt the Load Resistance Factor Design (LRFD), a rigorous, reliability-based framework, to water quality assessment and the TMDL process. The LFRFD replaces the lumped MOS with design factors that reflect the magnitude and distribution of uncertainty among the various contaminant loads. In addition, it produces load reduction estimates to meet management objectives with a contaminant-specific frequency-based target. The LRFD is computationally efficient and flexible in that, to compute the design factors, the procedure can utilize: measurement data, analytical solutions or model simulation results, as well as full or marginal probability distributions.
机译:有效的减负荷策略依赖于准确的总最大日负荷(TMDL)计算,该计算可量化来自各种来源的污染物负荷。有多种方法可以考虑TMDL中的不确定性:从关于影响TMDL所需安全裕度(MOS)的因素的简单,保守的假设,到诸如Monte Carlo仿真之类的基于概率的方法,该方法可以明确地量化TMDL的不确定性。在本文中,作者将负载阻力因子设计(LRFD)(一种严格的,基于可靠性的框架)应用于水质评估和TMDL过程。 LFRFD用反映各种污染物负载之间不确定性的大小和分布的设计系数代替了集总MOS。此外,它还可以得出减少负荷的估算值,以达到基于污染物的特定频率目标的管理目标。 LRFD具有高效的计算能力和灵活性,可以计算设计因素,该程序可以利用:测量数据,分析解决方案或模型仿真结果以及全部或边际概率分布。

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