Data Repository for "Forecasting Mixed Tidal–Fluvial River Water Levels Using a Non-Stationary Tidal Model"

This archive contains data and code that support the findings in M. Dunphy, S.M. Taylor, and M.V. Krassovski. Forecasting Mixed Tidal–Fluvial River Water Levels Using a Non-Stationary Tidal Model. DOI: 10.1080/1755876X.2026.2682048 Submitted to Journal of Operational Oceanography on June 30, 2025. Article received July 14, 2025, and accepted May 26, 2026. The data are organized in the following directories. sshbdy: Python code to run case studies presented in the above publication. Installation instructions can be found in README.md, and the run scripts are in bin/run-[CASE].sh Before running the scripts, appropriate paths should be set in bin/run-paths.sh pointing to the two directories below, as well as to the user's output directory. Gauge_data: Observation data used by the above scripts. Models_and_constituents: Tidal constituents used to predict the water level in the case scripts.本归档文件包含支撑M. Dunphy、S.M. Taylor及M.V. Krassovski研究成果的数据与代码，对应研究论文为《采用非平稳潮汐模型预报潮滩-河流混合河段水位》（Forecasting Mixed Tidal–Fluvial River Water Levels Using a Non-Stationary Tidal Model），该论文于2025年6月30日提交至《作业海洋学杂志》(Journal of Operational Oceanography)。 数据按以下目录结构组织： sshbdy：用于复现上述论文中案例研究的Python代码。安装说明详见README.md文件，运行脚本存放于bin/run-[CASE].sh路径下。在运行脚本前，需在bin/run-paths.sh中配置合适路径，指向以下两个目录以及用户自定义的输出目录。 测站数据（Gauge_data）：上述脚本所使用的观测数据。 Models_and_constituents：案例脚本中用于水位预报的潮汐分潮（tidal constituents）参数。