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水文流量测站构建的、经机器学习辅助完成缺测值插补的径流流量数据。该数据集基于Rosemary Carroll采集的原始径流流量数据生成，通过随机森林机器学习分析方法，对逐小时时间尺度下所有年份的径流流量数据进行了缺测值插补处理。存在缺测值的径流流量数据，会对各子流域出口处碳、氮通量的实测与模拟分析造成不利影响；经插补后的径流数据同时也是地表水模型的必要输入项，可助力解答本研究的核心科学问题：融雪时序如何影响氮素输出的时间特征与总量规模。本数据集以单个CSV文件格式提供。