LAGOS-US NETWORKS v1.0: Data module of surface water networks characterizing connections among lakes, streams, and rivers in the conterminous U.S

Knowing the degree of surface water connectivity among aquatic ecosystems can help scientists better understand and predict the movement of materials and biota across ecosystems. Methods to quantify surface water networks that include lake and stream connections at broad spatial scales are rare because it is difficult to balance accurate estimates of surface water connectivity and computational challenges. The LAGOS-US NETWORKS (NETS) module contains surface connectivity metrics for lake networks across the conterminous United States. We applied a graph theory approach to identify lake networks (i.e. a set of lakes connected by streams either upstream, downstream, or both) created from the medium resolution NHD lakes, streams, and rivers and subsequently derive surface water connectivity metrics for lakes and networks. Using this approach, we created a total of 898 networks that include 86,511 lakes. The NETS module includes a table with metrics for connections between lakes (both upstream and downstream), dams, network position, and whole networks. NETS also includes a flow table and bidirectional and unidirectional distance tables that provide the distances between every pair of connected lakes.

明晰水生生态系统间的地表水连通性程度，可助力科研人员更深入地理解并预测物质与生物群在各生态系统间的迁移过程。目前，在大空间尺度上量化包含湖泊与溪流连通关系的地表水网络的方法较为匮乏，原因在于难以兼顾地表水连通性的精准估算与计算层面的挑战。LAGOS-US NETWORKS（NETS）模块包含覆盖美国本土的湖泊网络地表水连通性指标。我们采用图论（graph theory）方法，基于中等分辨率国家水文数据集（National Hydrography Dataset，NHD）的湖泊、溪流与河流数据，识别由溪流通过上游、下游或双向连通的湖泊集合（即湖泊网络），并据此推导湖泊与湖泊网络的地表水连通性指标。通过该方法，我们共构建了898个湖泊网络，涵盖86,511个湖泊。NETS模块包含一张数据表，涵盖湖泊（上游与下游双向）、大坝间的连通性指标，以及网络位置与整体网络的相关指标。此外，NETS模块还包括流量表，以及双向与单向距离表，可提供每一对连通湖泊间的距离数据。