Jaeger Kristin L, Hafen Konrad C, Dunham Jason B, Fritz Ken M, Kampf Stephanie K, Barnhart Theodore B, Kaiser Kendra E, Sando Roy, Johnson Sherri L, McShane Ryan R, Dunn Sarah B
U.S. Geological Survey, Washington Water Science Center, Tacoma, WA 98402, USA.
U.S. Geological Survey, Idaho Water Science Center, Boise, ID 83702, USA.
Water (Basel). 2021 Jun 9;13(12):1-20. doi: 10.3390/w13121627.
Observations of the presence or absence of surface water in streams are useful for characterizing streamflow permanence, which includes the frequency, duration, and spatial extent of surface flow in streams and rivers. Such data are particularly valuable for headwater streams, which comprise the vast majority of channel length in stream networks, are often non-perennial, and are frequently the most data deficient. Datasets of surface water presence exist across multiple data collection groups in the United States but are not well aligned for easy integration. Given the value of these data, a unified approach for organizing information on surface water presence and absence collected by diverse surveys would facilitate more effective and broad application of these data and address the gap in streamflow data in headwaters. In this paper, we highlight the numerous existing datasets on surface water presence in headwater streams, including recently developed crowdsourcing approaches. We identify the challenges of integrating multiple surface water presence/absence datasets that include differences in the definitions and categories of streamflow status, data collection method, spatial and temporal resolution, and accuracy of geographic location. Finally, we provide a list of critical and useful components that could be used to integrate different streamflow permanence datasets.
观察溪流中地表水的有无对于表征径流的持续性很有用,径流持续性包括溪流和河流中地表水流的频率、持续时间和空间范围。此类数据对于源头溪流尤为重要,因为源头溪流占溪流网络中绝大部分河道长度,通常并非常年流水,且往往是数据最匮乏的。美国多个数据收集小组都有地表水存在情况的数据集,但这些数据集并未很好地对齐以便于整合。鉴于这些数据的价值,采用统一方法来整理不同调查收集的地表水有无信息,将有助于更有效地广泛应用这些数据,并填补源头径流数据的空白。在本文中,我们重点介绍了现有的众多关于源头溪流地表水存在情况的数据集,包括最近开发的众包方法。我们确定了整合多个地表水有无数据集所面临的挑战,这些挑战包括径流状态的定义和类别、数据收集方法、时空分辨率以及地理位置准确性方面的差异。最后,我们提供了一份关键且有用的组件清单,可用于整合不同的径流持续性数据集。