4.1 Article

The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware

期刊

WETLANDS ECOLOGY AND MANAGEMENT
卷 26, 期 1, 页码 63-86

出版社

SPRINGER
DOI: 10.1007/s11273-017-9554-y

关键词

Connectivity; Depressions; Forested wetlands; Headwater streams; Inundation; Lidar

资金

  1. U.S. EPA Office of Research and Development, National Center for Environmental Assessment [EPA-USGS IA-92410201-1]

向作者/读者索取更多资源

The dependence of downstream waters on upstream ecosystems necessitates an improved understanding of watershed-scale hydrological interactions including connections between wetlands and streams. An evaluation of such connections is challenging when, (1) accurate and complete datasets of wetland and stream locations are often not available and (2) natural variability in surface-water extent influences the frequency and duration of wetland/stream connectivity. The Upper Choptank River watershed on the Delmarva Peninsula in eastern Maryland and Delaware is dominated by a high density of small, forested wetlands. In this analysis, wetland/stream surface water connections were quantified using multiple wetland and stream datasets, including headwater streams and depressions mapped from a lidar-derived digital elevation model. Surface-water extent was mapped across the watershed for spring 2015 using Landsat-8, Radarsat-2 and Worldview-3 imagery. The frequency of wetland/stream connections increased as a more complete and accurate stream dataset was used and surface-water extent was included, in particular when the spatial resolution of the imagery was finer (i.e., < 10 m). Depending on the datasets used, 12-60% of wetlands by count (21-93% of wetlands by area) experienced surface-water interactions with streams during spring 2015. This translated into a range of 50-94% of the watershed contributing direct surface water runoff to streamflow. This finding suggests that our interpretation of the frequency and duration of wetland/stream connections will be influenced not only by the spatial and temporal characteristics of wetlands, streams and potential flowpaths, but also by the completeness, accuracy and resolution of input datasets.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.1
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据