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Multiresponse modeling of variably saturated flow and isotope tracer transport for a hillslope experiment at the Landscape Evolution Observatory

机译:景观演化天文台山坡实验的饱和流和同位素示踪剂运移的多响应建模

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This paper explores the challenges of model parameterization and process representation when simulating multiple hydrologic responses from a highly controlled unsaturated flow and transport experiment with a physically based model. The experiment, conducted at the Landscape Evolution Observatory (LEO), involved alternate injections of water and deuterium-enriched water into an initially very dry hillslope. The multivariate observations included point measures of water content and tracer concentration in the soil, total storage within the hillslope, and integrated fluxes of water and tracer through the seepage face. The simulations were performed with a three-dimensional finite element model that solves the Richards and advection–dispersion equations. Integrated flow, integrated transport, distributed flow, and distributed transport responses were successively analyzed, with parameterization choices at each step supported by standard model performance metrics. In the first steps of our analysis, where seepage face flow, water storage, and average concentration at the seepage face were the target responses, an adequate match between measured and simulated variables was obtained using a simple parameterization consistent with that from a prior flow-only experiment at LEO. When passing to the distributed responses, it was necessary to introduce complexity to additional soil hydraulic parameters to obtain an adequate match for the point-scale flow response. This also improved the match against point measures of tracer concentration, although model performance here was considerably poorer. This suggests that still greater complexity is needed in the model parameterization, or that there may be gaps in process representation for simulating solute transport phenomena in very dry soils.
机译:本文在基于物理模型的高度受控的非饱和流和输运实验中模拟多种水文响应时,探索了模型参数化和过程表示的挑战。在景观演化天文台(LEO)进行的实验涉及将水和富含氘的水交替注入最初非常干燥的山坡中。多变量观测包括对土壤中水含量和示踪剂浓度,山坡内的总存储量以及通过渗漏面的水和示踪剂积分通量的点测量。使用三维有限元模型进行了模拟,该模型解决了Richards和对流扩散方程。依次分析了集成流,集成传输,分布式流和分布式传输响应,并在每个步骤的参数化选择得到标准模型性能指标的支持。在我们分析的第一步中,以渗流面流量,蓄水量和渗流面的平均浓度为目标响应,使用与先前流量相同的简单参数化,获得了测量变量和模拟变量之间的充分匹配,仅在LEO进行实验。当传递到分布式响应时,有必要将复杂性引入附加的土壤水力参数中,以获得与点尺度流量响应的足够匹配。这也改善了与示踪剂浓度点测量的匹配,尽管此处的模型性能相当差。这表明在模型参数化中还需要更大的复杂性,或者在非常干燥的土壤中模拟溶质运移现象的过程表示中可能会有空白。

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