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

项目P7开发了流域尺度上的流动和反应性输运的随机建模框架。采用随机土壤-作物模型对地表和土壤中的过程进行模拟，该模型与第四纪含水层中硝酸盐和农药多分量非线性反应迁移的基于旅行/暴露时间的随机三维地下流动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。参数和强迫被认为是统计分布，从而得到预测的可观测值（水头、流量、反应物质浓度）的分布。参数分布将取决于通过集成卡尔曼滤波技术对观测值的测量。

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.