Great Lakes monthly water balance components from the Large Lakes Statistical Water Balance Model (L2SWBM)

These data sets are the results of leveraging bi-national data and the Large Lakes Statistical Water Balance Model (L2SWBM) specifically tailored for the Laurentian Great Lakes to produce value-added time series of water supply components, including expressions of uncertainty, that ultimately close the water balance across the interconnected Great Lakes system. The model serves as a new cornerstone for bi-national coordination of hydrologic data throughout this international transboundary basin, providing an improved means of capturing data patterns, revealing seasonal variabilities, as well as short-term and long-term trends. A full description of the dataset will be found in a paper that has been submitted to Nature - Scientific Data. Details on the paper will be provided here once available.本数据集基于双边观测数据与专为劳伦琴五大湖（Laurentian Great Lakes）定制开发的大湖统计水量平衡模型（Large Lakes Statistical Water Balance Model, L2SWBM）生成，产出了包含不确定性表征的供水组分增值时间序列，最终实现互联互通的五大湖系统水量平衡闭合。该模型为本国际跨界流域内的水文数据双边协调工作提供了全新核心支撑，可更精准地捕捉水文数据模式、揭示季节变异性以及短期与长期变化趋势。本数据集的完整描述将发表于已投稿至《自然-科学数据》（Nature - Scientific Data）的论文中，该论文的详细信息待公开后将在此处补充发布。