The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware
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 (SWE) influences the frequency and duration of wetland/stream connectivity. The Delmarva Peninsula in eastern Maryland and Delaware is dominated by a high density of small, forested wetlands, and therefore represents a particularly challenging environment to remotely detect wetland/stream connectivity. In this analysis wetland/stream surface water connections were quantified using two wetland datasets and three stream datasets. These included headwater streams and depressions mapped from a lidar-derived digital elevation model across the Upper Choptank River watershed within the Delmarva Peninsula. SWE was mapped across the watershed for spring 2015 using Landsat-8, Radarsat-2 and Worldview-3 imagery. We examined how input datasets influenced our interpretation of remotely-sensed wetland/stream surface-water connections. Depending on the datasets used, 12% to 60% of wetlands by count (21% to 93% of wetlands by area) experienced surface-water interactions with streams during spring 2015. This translated into a range of 50% to 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 quality and characteristics of the input datasets.