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1 December 2016 Hydrologic Connectivity: Quantitative Assessments of Hydrologic-Enforced Drainage Structures in an Elevation Model
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Poppenga, S.K. and Worstell, B.B., 2016. Hydrologic connectivity: Quantitative assessments of hydrologic-enforced drainage structures in an elevation model. In: Brock, J.C.; Gesch, D.B.; Parrish, C.E.; Rogers, J.N., and Wright, C.W. (eds.), Advances in Topobathymetric Mapping, Models, and Applications. Journal of Coastal Research, Special Issue, No. 76, pp. 90–106. Coconut Creek (Florida), ISSN 0749-0208.

Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal regions.


As the risk for hazardous events resulting from climate change escalates, there is a need to accurately identify and map hydrologic connectivity between inland surface flow and coastal waters impacted by natural disasters. Because of the increased need to mitigate associated risks to communities and ecosystems, land use planners, managers, and scientists increasingly rely on high-resolution light detection and ranging (lidar) elevation surfaces to define overland surface flow on the landscape. Lidar elevation surfaces contain highly detailed topographic information. Therefore, raised features, such as road grade, can cause modeled surface flow to become impounded, resulting in a loss of hydrologic connectivity in the lidar elevation surface. Without hydrologic connectivity in a lidar elevation surface, uncertainties may arise in storm surge, inundation, or sea-level rise predictions that rely upon high-resolution elevation data. Therefore, lidar elevation surfaces, or lidar digital elevation models (DEMs), need to be hydrologically-corrected, or hydrologically (hydro)-enforced, prior to using the data in hydrodynamic models.

The objective of this paper is to contrast two types of quantitative assessments conducted in New Jersey coastal watersheds to demonstrate the feasibility of using hydro-enforcement to achieve hydrologic connectivity in lidar elevation surfaces. A description is provided of the complexities that arise when using culvert/bridge datasets, collected by numerous public agencies, as reference points to validate hydro-enforcement. A justification is also provided describing the need for a second quantitative assessment that consists of image interpretation of aerial photographs to identify reference drainage. Both types of assessments were conducted on hydro-enforced lidar elevation surfaces generated using previously published semi-automated hydro-enforcement methods developed by the U.S. Geological Survey (USGS) (Poppenga et al., 2010; 2012). The objective of this paper is an ambitious approach for several reasons: 1) quantitative assessments on semi-automated hydro-enforcement methods are rarely published in the scientific literature; 2) culvert/bridge reference points are not as readily available, as reliable, or as comprehensive as elevation control points, and 3) culvert/bridge reference points are not available to validate hydro-enforcement of depressions that are not located near roads.

The Need for Hydrologic Connectivity in Lidar Elevation Surfaces

This section explains the importance of achieving hydrologic connectivity in lidar DEMs. It also describes hydrologic connectivity issues that have been addressed in the scientific literature, and the lack of reference points to validate hydro-enforcement results in drainage structure locations.

As the need for coastal mapping, monitoring, and change detection increases in response to inundation hazards that impact vulnerable coastal zones (Brock and Purkis, 2009; Burkett and Davidson, 2012; Buxton et al., 2013; Gesch, 2009; Gesch, Gutierezz, and Gill, 2009; Stoker et al., 2009; Turnipseed et al., 2007), hydrologic connectivity in lidar DEMs has become essential for storm surge and sea-level rise hydrodynamic modeling (ARCADIS, 2011; Gesch, 2009; Gesch, 2013; Li et al., 2009; MacDonald, 2012; NOAA, 2010; Poulter, Goodall, and Halpin, 2008; Poulter and Halpin, 2008; Sheets, Brenner, and Gilmer, 2012; Westerink et al., 2008; Zhang et al., 2011). Although lidar has become a commonly used technology for the collection of highly accurate elevation information (Buxton et al., 2013; Poppenga et al., 2010; Schmid, Hadley, and Wijekoon, 2011; Stoker, Harding, and Parrish, 2008; Webster and Forbes, 2006) that is used for hydrologic applications (Brock and Sallenger, 2001; Medeiros, 2012; Medeiros et al., 2011; Poppenga et al., 2010; 2012; 2013), according to Barber and Shortridge (2005), a high-resolution, high-accuracy elevation dataset does not necessarily produce a highly reliable model of overland surface flow. Lidar DEMs capture elevated features, such as road fill overlaying culverts, that impact any standard surface hydrology model by impeding the representation of overland surface flow (Figure 1A) (Barber and Shortridge, 2005; Duke et al., 2003; Maune et al., 2007; Poppenga et al., 2013; Poppenga et al., 2014a,b). These elevated road features were not as problematic in the past with lower resolution (~30-m) DEMs derived from topographic maps because the level of topographic detail was much lower than lidar DEMs.