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Watershed modeling using large-scale distributed computing in Condor and the Soil and Water Assessment Tool model

机译:使用Condor中的大规模分布式计算的分水岭模型和水土评估工具模型

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Models are increasingly being used to quantify the effects of best management practices (BMPs) on water quality. While these models offer the ability to study multiple BMP scenarios, and to analyze impacts of various management decisions on watershed response, associated analyses can be very computationally intensive due to a large number of runs needed to fully capture the various uncertainties in the model outputs. There is, thus, the need to develop suitable and efficient techniques to handle such comprehensive model evaluations. We demonstrate a novel approach to accomplish a large number of model runs with Condor, a distributed high-throughput computing framework for model runs with the Soil and Water Assessment Tool (SWAT) model. This application required more than 43,000 runs of the SWAT model to evaluate the impacts of 172 different watershed management decisions combined with weather uncertainty on water quality. The SWAT model was run in the Condor environment implemented on the TeraGrid. This framework significantly reduced the model run time from 2.5 years to 18 days and enabled us to perform comprehensive BMP analyses that may not have been possible with traditional model runs on a few desktop computers. The Condor system can be used effectively to make Monte Carlo analyses of complex watershed models requiring a large number of computational cycles.
机译:越来越多地使用模型来量化最佳管理规范(BMP)对水质的影响。尽管这些模型提供了研究多个BMP场景并分析各种管理决策对分水岭响应的影响的能力,但是由于需要大量运行才能完全捕获模型输出中的各种不确定性,因此相关的分析可能需要大量的计算。因此,需要开发合适和有效的技术来处理这种全面的模型评估。我们演示了一种新的方法来使用Condor(使用土壤和水评估工具(SWAT)模型进行模型运行的分布式高通量计算框架)来完成大量模型运行。此应用程序需要运行超过43,000次SWAT模型,以评估172个不同的流域管理决策以及天气不确定性对水质的影响。 SWAT模型在TeraGrid上实现的Condor环境中运行。该框架将模型的运行时间从2.5年显着减少到了18天,使我们能够执行全面的BMP分析,而在少数台式计算机上运行传统模型可能无法做到这一点。 Condor系统可以有效地用于对需要大量计算周期的复杂流域模型进行蒙特卡洛分析。

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