Stochastic Modeling Framework of Catchment-Scale Reactive Transport (P07)

项目P7为流域尺度上的水流和反应性输运开发了一个随机建模框架。地表和土壤中的过程由随机化的土壤-作物模型模拟，该模型与根深以下的随机化三维流动模型和基于旅行/暴露时间的第四系含水层中硝酸盐和农药的多组分非线性反应运移模型以及喀斯特地区基于旅行/暴露时间的集总模型相耦合。参数和作用力被认为是统计分布，从而导致预测的可观测性(水头、流量、活性物质浓度)的分布。参数分布将取决于系综-卡尔曼滤波技术对观测数据的测量。

Project P7 develops a stochastic modeling framework for flow and reactive transport on catchment scale. Processes at the land surface and in soils are simulated by stochastified soil-crop models, which are coupled to a stochastified 3-D flow model of the subsurface below root depth with travel-/exposure-time based models of multi-component nonlinear reactive transport of nitrate and pesticides in domains of Quaternary aquifers and to travel-/exposure-time based lumped models in karst regions. Parameters and forcings are considered as statistical distributions, resulting in distributions of predicted observables (heads, discharge, concentrations of reactive species). The parameter distributions will be conditioned on measurements of the observables by Ensemble-Kalman Filter techniques.