Travel time distributions (TTDs) provide an effective way to describe the transport and mixing processes of water parcels in a subsurface hydrological system. A major challenge in characterizing catchment TTD is quantifying the travel times in deep groundwater and its contribution to the streamflow TTD. Here, we develop and test a novel modeling framework for an integrated assessment of catchment scale TTDs through explicit representation of 3D-groundwater dynamics. The proposed framework is based on the linkage between a flux tracking scheme with the surface hydrologic model (mHM) for the soil-water compartment and a particle tracking scheme with the 3D-groundwater model OpenGeoSys (OGS) for the groundwater compartment. This linkage provides us with the ability to simulate the spatial and temporal dynamics of TTDs in these different hydrological compartments from grid scale to regional scale. We apply this framework in the Nägelstedt catchment in central Germany. Simulation results reveal that both shape and scale of grid-scale groundwater TTDs are spatially heterogeneous, which are strongly dependent on the topography and aquifer structure. The component-wise analysis of catchment TTD shows a time-dependent sensitivity of transport processes in soil zone and groundwater to driving meteorological forcing. Catchment TTD exhibits a power-law shape and fractal behavior. The predictive uncertainty in catchment mean travel time is dominated by the uncertainty in the deep groundwater rather than that in the soil zone. Catchment mean travel time is severely biased by a marginal error in groundwater characterization. Accordingly, we recommend to use multiple summary statistics to minimize the predictive uncertainty introduced by the tailing behavior of catchment TTD.

行进时间分布（TTD）提供了一种有效的方法来描述地下水文系统中水包的运输和混合过程。表征流域TTD的主要挑战是量化深层地下水的传播时间及其对河流TTD的贡献。在这里，我们通过明确表示3D地下水动力学，开发和测试了一种新颖的建模框架，用于对流域规模TTD进行综合评估。拟议的框架基于土壤水室通量跟踪方案与地表水文模型（mHM）与地下水室3D地下水模型OpenGeoSys（OGS）之间的联系。这种联系使我们能够模拟从网格规模到区域规模的这些不同水文区室中TTD的时空动态。我们将此框架应用于德国中部的Nägelstedt流域。模拟结果表明，网格规模的地下水TTD的形状和规模在空间上都是异质的，这在很大程度上取决于地形和含水层结构。流域TTD的逐项分析显示，土壤带和地下水中运输过程对驱动气象强迫具有时间依赖性。集水区TTD表现出幂律形状和分形行为。集水区平均旅行时间的预测不确定性主要由深层地下水的不确定性而不是土壤区域的不确定性决定。集水区平均旅行时间受到地下水特征描述中的边际误差的严重影响。因此，我们建议使用多个汇总统计信息来最大程度地减少由流域TTD尾矿行为引起的预测不确定性。