Application of a prior-based model discrimination framework using synthetic MODFLOW 6 groundwater models

A synthetic one-dimensional groundwater flow model was developed using MODFLOW 6 as a test application of the prior-based model discrimination method described in the associated publication (https://doi.org/10.1029/2025WR040323). The model represents a steady-state unconfined aquifer where water flows horizontally between two constant head boundaries (a lake at the lefthand side and river at the righthand side) and precipitation recharges the aquifer. Process module uncertainty is considered in the representations of groundwater recharge, geologic structure, and snowmelt that controls the river stage constant head boundary. Two process modules are considered to represent each of the three uncertain system processes. This yielded eight candidate configurations of the groundwater model. This USGS data release contains all of the input and output files and ancillary Python scripts for the simulations and results described in the associated publication (https://doi.org/10.1029/2025WR040323).

本研究采用MODFLOW 6构建了一套合成一维地下水流模型，作为关联论文（https://doi.org/10.1029/2025WR040323）中所述基于先验信息的模型判别方法的测试应用案例。该模型表征了稳态无压含水层，水流在两个定水头边界之间水平流动——左侧为湖泊，右侧为河流，同时有降水补给该含水层。研究考虑了地下水补给、地质构造以及控制河流定水头边界的融雪过程这三类不确定系统过程的模块不确定性，针对每一类不确定过程均设置了两类过程模块，最终得到8种地下水模型候选配置方案。本美国地质调查局（USGS）发布的数据集包含了关联论文所述模拟研究与结果所需的全部输入输出文件及配套Python脚本。