Model Inputs, Outputs, and Scripts associated with: “Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin”

This data package is associated with the publication “Combined effects of stream hydrology and land use on basin‐scale hyporheic zone denitrification in the Columbia River Basin”, published in Water Resource Research (Son et al.2022) available at https://doi.org/10.1029/2021WR031131. This data package includes the key model inputs/outputs of the river corridor model for the Columbia River Basin (CRB) and the model source codes used in the manuscript. The model is a carbon-nitrogen-coupled river corridor model (RCM), and the model is used to quantify hyporheic zone (HZ) denitrification at the NHDPLUS stream reach scales. The RCM used in this study combines empirical substrate models derived from observations and three microbially driven reactions, including two-step denitrification and aerobic respiration, are considered within the HZ. The key input data of the model are exchange flux, residence time, and stream solute (dissolved organic carbon (DOC), dissolved oxygen (DO), and nitrate concentrations). These inputs are constant over time and represent long-term averaged values. This study uses the RCM to explore the spatial patterns of HZ denitrification across reaches with different sizes and land use in the CRB. Our main objective is to use the RCM as a virtual reality model, and the machine-learning models as surrogates that encapsulate the complexities of the physics-based model while identifying the importance of different variables that are not evident in the model conceptualization. We do not include a direct comparison of the modeled HZ denitrification and measurements; however, the RCM can capture the overall spatial patterns of the HZ denitrification because the model inputs and its reaction networks are based on well-established theory and a physical-based model. The combination of the model-based predictions and a machine-learning approach (e.g., random forest) is used to improve our understanding of what variables of the model are associated with spatial patterns of the modeled denitrification across reaches with different sizes and land uses, and to develop a proxy model using measurable variables to reproduce the simulated patterns.This dataset contains five folders: (1) model_inputs, (2) model_outputs, (3) Rscripts, (4) figures, and (5) model_codes. It also contains a readme, file level metadata (FLMD), and data dictionary (dd). Please see the FLMD for a list of all the files contained in this data package and descriptions for each. The model_inputs folder contains the model inputs used to drive the model simulations. The model_outputs folder contains key model output files from the river corridor model. The Rscripts folder contains the Rscripts for pre- and post- processing model results. The figures folder contains the raw figures associated with the manuscript. The model_codes folder includes key model source codes/input files. All files are .jpg, .jpeg, .out, .e, .od, .dat, .sub, .F90, .0, .R, .sbx, .cpg, .sbn, .shx, .shp, .dbf, .prj, .tfw, .tif, .xml, .pdf, or .csv.

本数据包关联于发表在《水资源研究》（Water Resource Research）的论文《哥伦比亚河流域河流水文与土地利用对流域尺度潜流带（hyporheic zone）反硝化的联合效应》（Son et al. 2022），论文链接为https://doi.org/10.1029/2021WR031131。该数据包包含哥伦比亚河流域（Columbia River Basin, CRB）河流廊道模型的关键输入/输出数据，以及手稿中使用的模型源代码。该模型为碳氮耦合河流廊道模型（RCM），用于量化NHDPLUS河段尺度（NHDPLUS stream reach scales）下潜流带（HZ）的反硝化作用。

本研究使用的RCM整合了基于观测的经验基质模型（empirical substrate models），并考虑了潜流带内三种微生物驱动反应（microbially driven reactions），包括两步反硝化（two-step denitrification）和有氧呼吸（aerobic respiration）。模型的关键输入数据包括交换通量（exchange flux）、滞留时间（residence time）以及河流溶质（stream solute）（溶解有机碳（DOC）、溶解氧（DO）和硝酸盐浓度）。这些输入数据在时间上保持恒定，代表长期平均值。

本研究利用RCM探究CRB内不同规模和土地利用类型河段的HZ反硝化空间格局（spatial patterns）。主要目标是将RCM作为虚拟现实模型（virtual reality model），机器学习模型作为替代模型（surrogates）——后者在识别模型概念化中未明确的变量重要性的同时，涵盖物理模型（physics-based model）的复杂性。本研究未直接对比模拟的HZ反硝化结果与实测数据；但由于模型输入及其反应网络基于成熟理论和物理模型，RCM能够捕捉HZ反硝化的整体空间格局。

结合基于模型的预测与机器学习方法（如随机森林），旨在加深对模型中哪些变量与不同规模和土地利用类型河段模拟反硝化空间格局相关的理解，并利用可测变量（measurable variables）构建代理模型（proxy model）以重现模拟格局。

本数据集包含五个文件夹：(1) model_inputs（模型输入）、(2) model_outputs（模型输出）、(3) Rscripts（R脚本）、(4) figures（图表）和(5) model_codes（模型代码）。此外还包含readme文件、文件级元数据（FLMD）和数据字典（dd）。有关本数据包所含所有文件的列表及其描述，请参见FLMD。

model_inputs文件夹包含驱动模型模拟的输入数据；model_outputs文件夹包含河流廊道模型的关键输出文件；Rscripts文件夹包含用于模型结果预处理和后处理的R脚本；figures文件夹包含与手稿相关的原始图表；model_codes文件夹包含关键模型源代码/输入文件。所有文件格式为.jpg、.jpeg、.out、.e、.od、.dat、.sub、.F90、.0、.R、.sbx、.cpg、.sbn、.shx、.shp、.dbf、.prj、.tfw、.tif、.xml、.pdf或.csv。