Machine Learning Assisted Gap-Filled Discharge Data for the East River Community Watershed, Colorado, for Water Years 2014-2021

This dataset contains a collection of machine learning assisted gap-filled discharge data created for all discharge stations across the East River Watershed, Colorado. This data was generated by using raw discharge data collected by Rosemary Carroll, and conducting a random forest machine learning analysis to gap-fill discharge data across all years at the hourly time level. Discharge data with gaps creates problems for analysis of measured and modeled fluxes of carbon and nitrogen exported out of each sub-watershed. Gap-filled data is also required as an input to surface water models, which helps to address our main research question related to how snowmelt timing impacts the timing and magnitude of nitrogen exports. Data is provided in one csv file.

本数据集收录了为科罗拉多州东河流域所有径流监测站构建的、经机器学习辅助补全的径流量数据集合。本数据集以罗斯玛丽·卡罗尔采集的原始径流量数据为基础，通过随机森林机器学习分析方法，对所有年份的逐小时径流量数据完成缺失值补全处理。存在缺失值的径流量数据会干扰各子流域碳、氮输出通量的实测与模拟分析，而补全后的径流量数据同时也是地表水模型的必要输入项，可用于解答本研究的核心科学问题：融雪时机如何影响氮素输出的时机与强度。本数据集以单个CSV文件形式提供。