Karst aquifers are characterized by high-conductivity conduits embedded in a low-conductivity fractured matrix, resulting in extreme heterogeneity and variable groundwater flow behavior. The conduit network controls groundwater flow, but is often unmapped, making it difficult to apply numerical models to predict system behavior. This paper presents a multi-model ensemble method to represent structural and conceptual uncertainty inherent in simulation of systems with limited spatial information, and to guide data collection. The study tests the new method by applying it to a well-mapped, geologically complex long-term study site: the Gottesacker alpine karst system (Austria/Germany). The ensemble generation process, linking existing tools, consists of three steps: creating 3D geologic models using GemPy (a Python package), generating multiple conduit networks constrained by the geology using the Stochastic Karst Simulator (a MATLAB script), and, finally, running multiple flow simulations through each network using the Storm Water Management Model (C-based software) to reject nonbehavioral models based on the fit of the simulated spring discharge to the observed discharge. This approach captures a diversity of plausible system configurations and behaviors using minimal initial data. The ensemble can then be used to explore the importance of hydraulic flow parameters, and to guide additional data collection. For the ensemble generated in this study, the network structure was more determinant of flow behavior than the hydraulic parameters, but multiple different structures yielded similar fits to the observed flow behavior. This suggests that while modeling multiple network structures is important, additional types of data are needed to discriminate between networks.

岩溶含水层的特征是埋在低电导率裂缝基质中的高电导率管道，导致极端的非均质性和可变的地下水流动行为。管道网络控制着地下水的流量，但通常没有映射，因此难以应用数值模型来预测系统行为。本文提出了一种多模型集成方法来表示有限空间信息的系统仿真中固有的结构和概念不确定性，并指导数据收集。这项研究通过将这种新方法应用到一个映射充分，地质复杂的长期研究站点：哥特萨克山地喀斯特系统（奥地利/德国）来进行测试。集成生成过程（链接现有工具）包括三个步骤：使用GemPy（Python程序包）创建3D地质模型，使用随机岩溶模拟器（MATLAB脚本）生成受地质约束的多个导管网络，最后，使用雨水管理模型（基于C的软件）通过每个网络运行多个流量模拟，以基于拟合拒绝非行为模型模拟的弹簧排放量与观察到的排放量之间的关系。这种方法使用最少的初始数据即可捕获各种可能的系统配置和行为。然后可以使用该集合来探索液压流量参数的重要性，并指导其他数据收集。对于本研究中产生的整体而言，网络结构比水力参数更能决定流动行为，但是多种不同的结构对观测到的流动行为具有相似的拟合度。