Core Science Systems

A Comparison of Synthetic Flowpaths Derived from Light 

Detection and Ranging Topobathymetric Data and National 

Hydrography Dataset High Resolution Flowlines

Open-File Report 2018–1058

U.S. Department of the Interior

U.S. Geological Survey

A Comparison of Synthetic Flowpaths 

Derived from Light Detection and Ranging 

Topobathymetric Data and National 

Hydrography Dataset High Resolution 

Flowlines

By Cynthia Miller-Corbett

Open-File Report 2018–1058

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

RYAN K. ZINKE, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2018

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Suggested citation:

Miller-Corbett, C., 2018, A comparison of synthetic flowpaths derived from light detection and ranging topobathymetric data and National Hydrography Dataset high resolution flowlines: U.S. Geological Survey Open-File Report 

2018–1058, 29 p., https://doi.org/10.3133/ofr20181058.

ISSN 2331-1258 (online)
iii

Acknowledgments

I would like to thank John Young with the U.S. Geological Survey (USGS) Leetown Water Science Center; Gayla Evans, formerly with the USGS Earth Resources Observation and Science 

Center; and Jeffrey Danielson with the USGS Coastal National Elevation Database Applications 

Project for providing the Delaware River light detection and ranging survey digital elevation 

models to the National Geospatial Program to evaluate extraction of synthetic flowpaths to 

characterize river system flowpaths.

I especially would like to thank to the National Geospatial Program’s 3D Elevation Program and 

National Geospatial Technical Operations Center for their continued support.

v

Contents

Acknowledgments........................................................................................................................................iii

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................2

Experimental Advanced Airborne Research Lidar Sensor.....................................................................2

Sensor System and Processing .........................................................................................................4

Accuracy................................................................................................................................................4

Delaware River Survey Site Conditions .....................................................................................................4

Lidar Bathymetric and Topobathymetric Data ..........................................................................................6

Method for Developing Synthetic Flowpaths............................................................................................7

Comparison of Synthetic Flowpaths and National Hydrography Dataset High Resolution

Flowlines............................................................................................................................................9

Bathymetric Lidar Synthetic Flowpaths for the Delaware River ..................................................9

Synthetic Flowpaths Extracted Using Different Flow Accumulation Thresholds ....................11

Bathymetric Lidar Synthetic Flowpaths at Different Resolutions ..............................................14

Lidar Synthetic Flowpaths and National Hydrography Dataset High Resolution

Flowline Network Correspondence ...................................................................................18

Compatibility of Lidar Topobathymetry and 3D Elevation Program Digital Elevation

Models.....................................................................................................................................18

Discussion.....................................................................................................................................................23

Summary........................................................................................................................................................26

References....................................................................................................................................................27

Figures

1. Map showing Delaware River corridor Hancock Narrows, Middle River, and 

Trenton light detection and ranging survey groups................................................................3

2. Maps showing intersection of Watershed Boundary Dataset Hydrologic Unit Code

12 boundaries and the Hancock Narrows, Middle River, and Trenton Group reaches

of the Delaware River ..................................................................................................................5

3. Map showing synthetic flowpath extractions from light detection and ranging

digital elevation models...............................................................................................................8

4. Maps showing distribution of Trenton Group synthetic flowpaths for different flow

accumulation threshold values at 10-meter grid-spacing...................................................12

5. Map showing trellis patterned synthetic flowpaths for 10-meter resolution Trenton

Group at 0.05 percent of the maximum flow accumulation value ......................................13

6. Flow direction grids for 1-meter and 10-meter resolution bathymetric light

detection and ranging digital elevation models ....................................................................15

7. Maps showing synthetic flowpaths in flat terrain for Trenton Group at 1-meter and

10-meter resolution bathymetric digital elevation models ..................................................16

8. Maps showing synthetic flowpaths for Hancock Narrows Group at 0.05 percent of

the maximum flow accumulation for 1-meter, 5-meter, and 10-meter bathymetric

light detection and ranging resolutions ..................................................................................17

9. Maps showing Hancock Narrows Group D8 flow direction grid for 1-meter and

10-meter bathymetric light detection and ranging digital elevation model

resolution .....................................................................................................................................19
vi

10. Map showing correspondence between bathymetric light detection and ranging

synthetic flowpaths and the High Resolution National Hydrography Dataset

Flowline network.........................................................................................................................20

11. Bank slope to river channel bottom without gaps derived from light detection and

ranging bathymetric/topobathymetric digital elevation model...........................................21

12. Maps showing elevation difference by subtracting 3D Elevation Program digital

elevation models from bathymetric light detection and ranging digital

elevation models.........................................................................................................................22

13. Differences in topobathymetric light detection and ranging and 3D Elevation

Program digital elevation model surfaces..............................................................................24

Tables

1. Survey lengths for three resolutions and flow accumulation threshold values ..............10

2. Relation of change in area of flow accumulation threshold to create synthetic

flowpath segments and grid-cell size .....................................................................................10

3. Density and distribution of Hancock Narrows Group synthetic flowpaths at variable

resolutions and flow accumulation thresholds .....................................................................11

Conversion Factors

International System of Units to U.S. customary units

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

kilometer (km) 0.5400 mile, nautical (nmi) 

meter (m) 1.094 yard (yd) 

Area

square meter (m2

) 0.0002471 acre

square kilometer (km2

) 247.1 acre

square kilometer (km2

) 0.3861 square mile (mi2)

Datum

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 

83).
vii

Abbreviations

3DEP 3D Elevation Program

ALPS Airborne Lidar Processing System

ANPS aggregate nominal pulse spacing

BDEM bathymetric digital elevation model

CI confidence interval 

DEM digital elevation model

EAARL Experimental Advanced Airborne Ranging lidar

ESF extracted synthetic flowpath

FAC flow accumulation threshold

FDR flow direction gridgeodata geospatial data

GIS geographic information system

GPS global positioning satellite

HR NHD High Resolution National Hydrography Dataset

HUC hydrologic unit code

IHO International Hydrographic Organization

las laser data

lidar light detection and ranging

MaxFAC maximum flow accumulation

NAIP National Agricultural Imagery Program

NGP National Geospatial Program 

NTU nephelometric turbidity unit

QL quality level

RMSE root mean square error

sonar sound navigation and ranging

TauDEM Terrain Analysis Using Digital Elevation Models

tiff tagged image file format

USGS U.S. Geological Survey

WBD Watershed Boundary Dataset

A Comparison of Synthetic Flowpaths Derived from Light 

Detection and Ranging Topobathymetric Data and National 

Hydrography Dataset High Resolution Flowlines

By Cynthia Miller-Corbett

Abstract

Bathymetric and topobathymetric light detection and 

ranging (lidar) digital elevation models created for the Delaware River were provided to the National Geospatial Program and used to evaluate synthetic flowpath extraction from 

bathymetric/topobathymetric lidar survey data as a data source 

for improving the density, distribution, and connectivity of the 

National Hydrography Dataset High Resolution Flowline Network. As the surface-water component of The National Map, 

the National Hydrography Dataset maintains the Nation’s 

drainage network flow information and geometries for surfacewater features used in hydrologic, hydraulic, and other science 

and engineering disciplines. The regional lidar survey for the 

Delaware River between Hancock, New York, and Trenton, 

New Jersey, was collected for the U.S. Geological Survey 

using the Experimental Advanced Airborne Research Lidar 

sensor system and processed by the Coastal National Elevation 

Database Applications Program. 

Using 1 percent of the maximum flow accumulation 

value for the surveyed Delaware River corridor as the flow 

accumulation threshold for grid cells at 1-, 5-, and 10-meter 

resolution created 223 to 283 kilometers of synthetic flowpaths 

potentially representing the river channel thalweg, which is the 

deepest point in a riverbed cross-section. There was potential 

for improving the High Resolution National Hydrography 

Dataset (HR NHD) Flowline network in places where the 

Delaware River channel, depicted as an Artificial Path in the 

HR NHD, is offset from the extracted synthetic river flowpath 

which sometimes appeared better positioned than the Artificial 

Path to represent the river thalweg. For the same area, using 

0.05 percent of the maximum flow accumulation at the 1-, 5-, 

and 10-meter resolutions extracted 744 to 1,317 kilometers of 

synthetic flowpaths, with extracted synthetic flowpaths representing the main river channel and additional synthetic flowpaths representing tributaries or streams adjacent to the main 

channel. Overlaying these results with the HR NHDFlowline 

Network indicates that some of the additional synthetic flowpaths are connected to or extend HR NHD stream/river feature 

types. Some disconnected or isolated synthetic flowpaths 

not included in stream/river feature types were validated in 

orthoimagery and U.S. Topo Maps and provide examples of 

how extracted synthetic flowpaths could be used to delineate 

new stream/river features. Other additional extracted synthetic 

flowpaths depict linear features such as canals, tree lines, 

roads, or linear topographic depressions. 

For some river reaches where obstructions to flow or 

where low-relief topographic or bathymetric surfaces alter 

the flow direction, the software tool used to develop the flow 

direction grid did not calculate a primary flowpath for the river 

channel. Based on the results of this analysis, site conditions 

for the Delaware River corridor did not affect the quality of 

lidar bathymetric survey data. However, depending on the 

resolution of the lidar bathymetric digital elevation models 

(BDEMs), site conditions do have different effects on results 

for extracted synthetic flowpaths. We found that synthetic 

flowpaths extracted from 1-meter resolution lidar DEMs had 

more varied flow directions around in-channel landforms that 

obstructed flow than synthetic flowpaths extracted from 5- or 

10-meter resolution lidar DEMs. As a result the 1-meter resolution DEM created some isolated or discontinuous synthetic 

flowpath segments where the 5- and 10-meter DEMs developed more continuous flowpaths. In this case the river bed 

upstream from the in-channel obstruction is shallower than 

the river bed downstream. Under these conditions the 1-meter 

resolution DEM provided synthetic flowpaths delineating a 

potential river thalweg. In this same area, the software solution 

modified (virtually raised) the river bed in the 5- and 10-meter 

resolution DEMs and flattened the bathymetric surface to 

create a continuous downstream flow direction, which caused 

trellis-patterned synthetic flowpaths to form. Under different site conditions and converse to the above development of 

synthetic flowpaths at different resolutions, at an abandoned 

river flood plain (terrace) with low relief that is adjacent to the 

river channel, the flow direction grid for the 1-meter resolution 

DEM developed continuous synthetic flowpath corresponding to a HR NHD Flowline network stream/river feature that 

connected to the main river channel but the larger resolution 

DEMs created isolated or disconnected synthetic flowpaths. 

A project to continue an evaluation of benefits of or 

issues caused by extracting synthetic flowpaths to enhance 
2 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 

the HR NHD could include a study to assess the potential 

for merging surface-water flowpaths extracted from lidar 

topobathymetry and 3D Elevation Program digital elevation 

models. The merged DEM approach to synthetic flowpath 

extraction could extend the HR NHDFlowline network and 

enhance flow accumulations that might develop better flow 

direction grids in low-relief areas. Because of the confined 

lateral extent of the Delaware River, the lidar DEMs were not 

used to create catchments or watersheds; however, the merged 

DEM approach could also be tested as a resource for enhancing HR NHD catchments and watersheds. 

This lidar DEM synthetic flowpath extraction project 

supports the National Geospatial Program efforts to collect 

and produce high-quality lidar data to provide 3-dimensional 

representations of natural feature and aligns with the National 

Spatial Data Infrastructure to improve utilization of geospatial data. The results also can be useful for understanding 

strategies that can help maintain quality data in the HR NHD 

programs. 

KEYWORDS: bathymetric, digital elevation model, 

extracted synthetic flowpath, lidar, High Resolution National 

Hydrography Dataset, topobathymetric

Introduction

The purpose of the synthetic flowpath extraction project 

described here is to evaluate the validity of synthetic flowpaths 

extracted from light detection and ranging (lidar) bathymetric 

digital elevation models (BDEMs) and the usefulness of these 

flowpaths as a digital data source for enhancing the density, 

distribution, and connectivity of the HR NHDFlowline network. The evaluation is based on a lidar bathymetric survey for 

three survey areas along the Delaware River Corridor including the Hancock Narrows, Middle River, and Trenton Group 

(fig. 1). As the surface-water component of The National Map, 

the National Hydrography Dataset provides a comprehensive 

geospatial data (geodata) source for surface-water flowline 

networks with the goal of maintaining accurate data for use in 

mapping and analysis or modeling of surface-water systems in 

the United States and its territories. In the conterminous United 

States, the HR NHDFlowline network was originally developed from digitization of 1:24,000-scale topographic maps and 

national coverage, and compilation of the HR NHDFlowline 

network was completed in 2007 (U.S. Geological Survey, 

2014a). Since then, the HR NHDFlowline network has been 

enhanced and updated by the USGS and National Hydrography 

Dataset Stewards and Partners using areal imagery and other 

ancillary data sources to include more detailed local resolution 

content of scales up to 1:2,400.

Accurate hydrographic data for flowline networks and 

water bodies provide surface-water feature geometries fundamental to hydrologic and hydraulic analyses and modeling 

used in water resource management and science and engineering disciplines (Watkins, 2017; Carlisle and Woodside, 2013). 

A useful example of the potential improvement in flowline 

network accuracy through developing bathymetric lidar is 

described in the Colson and others (2006), in which lidar 

hydrography is compared with four other published hydrographic data sources: the HR NHDFlowline network, streams 

on Natural Resource Conservation Service survey maps, North 

Carolina Flood Plain Mapping Program stream breaklines, 

and county geographic information system (GIS) stream layers with streamlines developed from bare earth lidar DEMs. 

Based on comparisons of each data source to surveyed global 

positioning satellite (GPS) points, the overall horizontal positional accuracy of streamlines extracted from lidar data was 

estimated to be between 4 and almost 60 percent better than 

the other data source accuracies. 

Potential benefits for using lidar bathymetry compared to 

wading or sound navigation and ranging (sonar) surveys can 

include completing surveys for the same coverage in a shorter 

time, providing bathymetry for deeper rivers than possible for 

wading surveys, and collecting more accurate bathymetric data 

for inland river and lake areas than sonar surveys that may be 

limited by shallow water or other site conditions that require 

combined survey systems or multiple passes (U.S. Bureau 

of Reclamation, 2006; National Park Service, 2011). These 

potential benefits do not exclude use of wading or sonar 

survey systems and for some site conditions lidar bathymetry 

surveys might be used in combination with wading or sonar 

surveys. 

This report presents an overview of the lidar sensor system followed by a description of synthetic flowpath extraction 

software applications and of site conditions that can affect 

lidar survey collections or the successful use of synthetic flowpath extraction applications. Results for synthetic flowpath 

extraction and an analysis of these results are then described. 

Lastly, a discussion of benefits of and issues caused by using 

synthetic flowpaths derived from lidar bathymetric data is provided. The airborne bathymetric lidar survey system includes 

capabilities to collect bathymetric and topobathymetric data; 

however, the focus of this study is the benefits or potential 

issues associated with extraction of synthetic flowpaths.

Experimental Advanced Airborne 

Research Lidar Sensor

Lidar bathymetric and topobathymetric survey data for 

the Delaware River were collected using the U.S. Geological 

Survey (USGS) using the Experimental Advanced Airborne 

Ranging Lidar (EAARL)-B sensor system. Airborne lidar 

bathymetry referred to here as “lidar bathymetry” was originally developed in the 1960s for mapping coastal bathymetry 

(Guenther and others, 2000), and inland river bathymetry 

applications followed. There are several lidar bathymetric and 

topobathymetric survey systems designed for shallow and 

(or) deep water including the EAARL (Wright and others, 

2016); Chiroptera II (Leica Geosystems, 2017); Hawkeye III 
Experimental Advanced Airborne Research Lidar Sensor 3

Lordville, New York

Hancock, New York

Riegelsville, New Jersey

Narrowsburg, New York

Stockton Port, New Jersey

Whippoorwill Island, Pennsylvania

Trenton, New Jersey

Belvedere, New Jersey

Buck Bar Island, New Jersey

Port Jervis, New York

Delaware Water Gap, New Jersey

75°

41°25'

40°15'50"

.

0 10 20 KILOMETERS

20 MILES

5 15

0 5 10 15

EXPLANATION

Hancock Narrows

Middle River

Trenton

Survey group

Map image is the intellectual property of Esri and is used herein under license. 

Copyright © 2017 Esri and its licensors. All rights reserved.

Figure 1. Delaware River corridor Hancock Narrows, Middle River, and Trenton light detection and ranging (lidar) survey groups.
4 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 

(Leica Geosystems AG, part of Hexagon); 2017 Riegl VQ880 

(RIEGL Laser Measurement Systems GmbH, 2017); Scanning Hydrographic Operational Airborne Lidar Survey-3000 

(Optech Incorporated, 2006); and Coastal Zone Mapping 

and Imaging Lidar (Teledyne Optech Incorporated, 2017). 

A compilation of sources for inland bathymetric survey data 

available as of 2014 indicated that most of the inland bathymetric surveys were completed using acoustic sonar systems, 

but that surveys using only lidar bathymetric survey systems 

accounted for 18 percent and surveys using lidar bathymetry 

in combination with other methods accounted for 20 percent 

of the referenced surveys (Miller-Corbett, 2016). 

The USGS Coastal National Elevation Database Application Projects processed the collected data and ran point correspondence procedures using the Airborne Lidar Processing 

System (ALPS). The ALPS implements techniques to calculate and interpolate water surface and water feature bottom 

depths (Bonisteel and others, 2009; U.S. Geological Survey, 

2014b). 

Sensor System and Processing

The EAARL-B sensor system includes a raster-scanning, 

waveform-resolving, green-wavelength (532 nanometers) lidar 

sensor designed to map nearshore bathymetry, topography, and 

vegetation structure simultaneously (Wright and others, 2014). 

The sensor system includes the raster-scanning, water-penetrating, full-waveform adaptive lidar sensor system; downlooking red-green-blue and infrared (1,040 to 1,060 nanometers wavelength) digital cameras; two precision dual-frequency 

kinematic carrier-phase GPS receivers; and an integrated 

miniature digital inertial measurement unit, which provide for 

submeter georeferencing of each laser sample (Wright and 

others, 2014). Green waveform pulses penetrate the water 

surface, travel to and reflect off the water feature bottom, and 

return to the lidar system receiver with less dispersion than 

lower frequency waveforms used for creating land surface 

DEMs. 

Accuracy

Vertical and horizontal accuracies for lidar survey data 

points are calculated using a root mean square error (RMSE) 

to estimate the standard deviation between the collected data 

value and an observed, reference value at a 95-percent confidence interval (CI). In an evaluation of EAARL-B performance, Wright and others (2016) calculated vertical accuracies 

for EAARL-B with a nominal operating altitude of 300 meters 

(m) and laser targets with a 30-centimeter (cm) diameter 

(footprint) to range between 10.4 cm and 58 cm. These 

accuracies meet the International Hydrographic Organization 

(IHO) Special Order and are within or near Order 1 standard 

requirement for the 95-percent CI depth accuracy (0.56 m) for 

vertical accuracy down to a 20-m depth. The values also meet 

or exceed the IHO Order 1 vertical accuracy requirements for 

depths ranging from 0 to 34 m (Wright and others, 2016). 

Horizontal accuracy for lidar datasets is more difficult to 

assess than vertical accuracy because land surfaces often lack 

the well-defined topographic features required for such tests, 

or because resolution is too coarse to precisely locate distinct 

surface features (American Society for Photogrammetry and 

Remote Sensing, 2014). Based on a compilation of EAARL-B 

surveys reported in Hohenthal and others (2011), horizontal 

accuracy RMSEs for EAARL-B data that were calculated for 

15- and 200-cm laser beam footprints at a 95-percent CI range 

between 100 and 250 cm; referenced observations used for 

the calculations were based on observed Real Time Kinematic–GPS data. The horizontal accuracies reported for the 

EAARL-B system meet American Society for Photogrammetry and Remote Sensing 95-percent CI accuracy requirements 

for Class 1 digital planimetric data for 1:1,200 to 1:8,000 map 

scales (American Society for Photogrammetry and Remote 

Sensing, 2014). When converting the Circular Mapping 

Accuracy standard of 12.2 m for a 90-percent CI (Federal 

Geographic Data Committee, 1998) to the National Standard 

for Spatial Data Accuracy, the horizontal positional accuracy 

standard for HR NHD geodata is 13.6 m. 

Delaware River Survey Site Conditions

The Delaware River is characterized as a dendritic flow 

network for which the overall channel geometry is similar to 

a branching tree and streams flow downslope to merge at a 

confluence (Djokic, 2008). Between Hancock, New York, and 

Trenton, New Jersey, the river channel is about 320 kilometers 

(km) long and is referenced as the Upper, Middle, and Lower 

Delaware River (Delaware River Basin Commission, 2014; 

National Park Service, 2012). These river sections correspond 

with the lidar bathymetric survey areas, the Hancock Narrows, 

Middle River, and Trenton Group, respectively (fig. 1). Based 

on measurements of the lidar bathymetric survey DEMs in a 

GIS, the average bank-to-bank river width measured about 

100 m. In the Hancock Narrows Group area of the Delaware River, several HR NHD Watershed Boundary Datasets 

(WBDs) with hydrologic unit code (HUC) 12 merge at the 

river. In the Middle River Group area, elongated WBD HUC 

12s merge at the northern and midsection of the river. In the 

Trenton Group, the Delaware River crosses most of the WBD 

HUC 12 boundaries, with only one group of HUC 12s merging at the river (fig. 2). The range of surveyed area elevations 

is 198 to 433 m for the Hancock Narrows Group, 93 to 293 m 

for the Middle River Group and -18 to 202 m for the Trenton 

Group. The changes in elevation reflect the trend of lower 

regions moving from the northern limit of the survey at the 

confluence of the east and west branch of the Delaware River 

to the southern limit at Trenton, N.J. 

In addition to using the appropriate sensor system and 

supporting equipment for collecting and processing accurate 
Delaware River Survey Site Conditions 

5

75°

41°45'

EXPLANATION EXPLANATION EXPLANATION

Hancock Narrows Group survey elevation, 

in meters

Middle River Group survey elevation, 

in meters

Trenton Group survey elevation, 

in meters

High : 420.205Low : 199.31

Watershed boundary dataset

hydrologic unit code 02040101

U.S. Geological Survey, The National Map U.S. Geological Survey, The National Map U.S. Geological Survey, The National Map

0 5 MILES0 5 KILOMETERS

0 6 MILES0 6 KILOMETERS

0 10 MILES0 10 KILOMETERS

74°45'

41°15'

291.62494.2886

Watershed boundary dataset

hydrologic unit code 02040105

75°

40°30'

High : 176.806Low : -3.8582

Watershed boundary dataset

hydrologic unit code 02040104

. . .

Figure 2. Intersection of Watershed Boundary Dataset Hydrologic Unit Code 12 boundaries and the Hancock Narrows, Middle River, and Trenton Group reaches of the Delaware River.
6 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 

lidar bathymetry, successful inland lidar bathymetry data collection and extraction of useful synthetic flowpaths depends 

on site conditions. Lidar bathymetric mapping is limited by 

site conditions such as geomorphology, variable rock grain 

size that can develop rough or uneven river beds, water depth, 

turbidity (a measure of relative water clarity), and vegetation 

that may cause dispersion or loss of signals (Feurer and others, 

2008; Guenther and others, 2000; Hohenthal and others, 2011; 

Kinzel and others, 2013; National Park Service, 2011). The 

inclusion of data to attribute these physical parameters as part 

of lidar bathymetric and topobathymetric survey information 

is important for better understanding and relating site conditions that affect the quality of lidar bathymetric and topobathymetric data collection and processing. 

From the northern section of the survey near Hancock, 

N.Y., to the southern end of the Middle River Group, the river 

flows through the Appalachian Plateau and Valley and Ridge 

Province(s) (not shown) and the river bed consists of fine to 

coarse grained clastics and compacted clastics forming siltstone, sandstone, and shale and conglomerates (U.S. Geological Survey, 2013b). South of the Middle River Group, the river 

channel flows through the Delaware Water Gap. This region 

includes a suite of folded and faulted rock layers (Pennsylvania Department of Natural Resources, 2014; U.S. Geological Survey, 2003; National Park Service, 2012) and was not 

included as part of the lidar survey. Beginning at the northern 

end of the Trenton Group and continuing to the southern end 

at Trenton, N.J., the Delaware River flows through the Piedmont Province. This section of the river channel bed includes 

a mix of clastic and compacted sedimentary rocks, as well as 

some swamp deposits (U.S. Geological Survey, 2013b). 

Water depths for the Delaware River are variable. In 

the Hancock Narrows Group at Narrowsburg, N.Y., (fig. 1) 

the river bed depth has been measured as 33 m (White and 

Kratzer, 1993) The National Park Service indicates some pools 

are 30 or 35 m deep (National Park Service, 2012). Based on 

using river stage data, which the USGS Water Science School 

reports to approximate water depths (U.S. Geological Survey, 

2016a), there are also many places where the river channel is 

very shallow. For example, in places such as Lordville, N.Y., 

the Delaware Water Gap, N.J., and Trenton, N.J., water depths 

can be less than 1 m to about 2 m (U.S. Geological Survey, 

2017).

The EAARL-B system includes shallow and deep water 

receivers designed to collect bathymetric data at reported 

Delaware River bed depth ranges. The shallow water channel receiver can map optically shallow, clear water ranging 

in depth from 0 to approximately 20 m, and the deep water 

channel receiver can collect bathymetric data at depths ranging 

from 15 to 44 m (Wright and others, 2016). Because of this 

wide range of depth collection, the survey system is suited 

for targeting the Delaware River bottom and receiving quality 

return signals.

Turbidity is measured in nephelometric turbidity units 

(NTUs). NTUs less than 10 indicate clear water (U.S. Geological Survey, 2016a). Compiled water quality data, including 

turbidity measurements for the Delaware River from Hancock, N.Y., to the Delaware River Water Gap, include values 

ranging between about 2 and 4 NTUs (Delaware River Basin 

Commission, 2013). Water data for sections of the Delaware 

River include values ranging from less than 3 NTUs on the 

Pennsylvania side of the river at Trenton, N.J., and as high as 

9.5 NTUs at a streamgage between Riegelsville, Pennsylvania, 

and Stockton, N.J. (U.S. Geological Survey, 2017). All values 

are within the range of clear water NTU values.

Lidar Bathymetric and Topobathymetric 

Data

The USGS contracted the EAARL-B sensor system 

survey in 2014 to collect bathymetric and topobathymetric 

elevation data for more than 280 km of the Delaware River 

channel corridor between Hancock, N.Y., and Trenton, N.J. 

(fig. 1). Based on measurements of the lidar bathymetric 

survey DEMs, the main river channel averages about 100 m 

wide. The width of the lidar DEM footprint centered along the 

main river channel varied between 300 and 500 m. Data are 

spatially referenced to the World Geodetic System 1984 spheroid and projected in Universal Transverse Mercator Coordinate System, Zone 18. The aggregate nominal pulse spacing (ANPS) is 0.61 m, 0.62 m, and 0.71 m for the Hancock 

Narrows, Middle River, and Trenton Groups, respectively. All 

aggregate nominal pulse density values meet the USGS lidar 

specification for quality level (QL) 2 of greater than or equal 

to 2.0 points per square meter (Heidemann, 2014). 

The USGS Coastal National Elevation Database Applications Program processed the bathymetric and topobathymetric 

lidar data using Airborne Lidar Processing software. Delaware 

River bathymetric and topobathymetric lidar DEMs were provided to the National Geospatial Program (NGP) in laser data 

(las) file format and tagged image file format (tiff) for three 

survey groups. The Hancock Narrows Group is the northern group that runs from the confluence of the East Branch 

Delaware River and West Branch Delaware River at Hancock, 

N.Y., to Narrowsburg, N.Y.; raster tile coverage is 859 square 

kilometers. The Middle River Group covers the river corridor from northwest of Port Jervis, N.Y., to south of Buck 

Bar Island, N.J. This group covers 800 square kilometers. The 

southern survey group is the Trenton Group. This group covers 

the river from Whippoorwill Island, Pa., to Trenton, N.J., just 

north of the National Oceanic and Atmospheric Administration 

Harbor Chart for the Delaware River (National Oceanic and 

Atmospheric Administration, National Ocean Service, 2012).
Method for Developing Synthetic Flowpaths 7

Method for Developing Synthetic 

Flowpaths

Bathymetric and topobathymetric lidar DEMs for the 

Delaware River Hancock Narrows, Middle River, and Trenton 

Groups were provided at 1-meter resolution and resampled at 

5-meter and 10-meter resolution to evaluate results for developing synthetic flowpaths at different grid spacing. Synthetic 

flowpaths from the three lidar DEM resolutions were extracted 

by creating stream segments based on specifying a minimum flow accumulation threshold (FAC) for grid cells using 

ArcHydro program routines (tools) implemented in Esri GIS 

software (Djokic, 2008).Varying the grid spacing and the FAC 

created synthetic flowpaths at different densities and distributions, providing simple to more complex synthetic flowpath 

geometries.

The flow direction grid (FDR) application is the fundamental tool for developing synthetic flowpaths, referred to as 

drainlines in the ArcHydro software program (fig. 3). Depending on topographic relief, different software applications 

are used to manipulate elevation data to minimize extracted 

synthetic flowpath (ESF) termination in elevation grid low 

points, or to control the synthetic flowpath and successfully 

develop an FDR. The Fill Sinks tool is commonly used for 

treating dendritic flowline networks and was used in this study 

to derive hydrography from the dendritic Delaware River lidar 

survey DEMs. The Fill Sinks tool fills depressions (sinks) 

based on an automatic or user-specified Z-limit, which is the 

maximum difference in elevation between the local pour point 

and depth of a cell of interest. When the Z-limit is larger than 

the elevation difference, the depression will be filled; when 

the Z-limit is smaller, the sinks will not be filled because the 

depth exceeds the difference and is considered a valid sink

(Esri, 2014). Without filling sinks, the FDR tool used to assign 

flow away from each grid cell to one of eight neighboring cells 

incorrectly creates a grid with additional flow directions and 

cannot be used as input to the subsequent routine. 

Other ArcHydro software functions that can be used 

to treat a DEM that depicts other drainage systems prior to 

implementing the sequence of routines include the Prescreen 

Sinks, Level DEM, Reconditioning, Stream Burning, and 

Building Walls applications. These functions are designed 

to better derive synthetic flowpaths in deranged terrain that 

contains only depressions (sinks), in terrain that is a combination of dendritic and deranged types, or for other topographical conditions that may make it hard to identify changes in 

the slope between neighboring grid cells, which is the basis 

for developing flow directions (Esri, 2014; Esri, 2011; 2013; 

Merwade, 2012).

Flow direction grid.—FDRs depict the calculated flow 

direction out of each raster grid cell. Initially, ArcHydro and 

the Terrain Analysis Using Digital Elevation Models (TauDEM) software program were used in trial runs to derive the 

FDR using the D8 tool flow model solution developed by Jenson and Dominque (1988).The D8 tool is used to calculate the 

steepest slope from each DEM grid cell to all eight neighboring cells to solve for the primary direction of flow (Merwade, 

2012). TauDEM also implements the D-Infinity solution that 

was used in the trial runs. This method for creating an FDR 

calculates a flow direction as a single angle defined for the 

steepest downward slope on eight triangular facets centered at 

each grid point (Tarboton, 1991).

In a comparison of the results for ArcHydro D8 and TauDEM D-Infinity flow direction tools used to extract synthetic 

flowpaths in different terrains and at different resolutions in 

North Carolina, Colson and others (2006) calculated accuracies for the two stream-extraction techniques and concluded 

there was little or no differences in results where accuracies 

were calculated as the number of survey points within a 3-m 

buffer for the stream reaches of interest. The differences that 

were identified were attributed to the different flow routing 

algorithms used by each solution (Colson and others, 2006) 

but overall TauDEM did provide better accuracies. Results for 

the Colson and others (2006) study indicated that the TauDEM 

software consistently developed flowlines with better accuracy 

for the 1.52-m resolution DEMs. For 6-m resolution DEMs, 

TauDEM had significantly better accuracy for one site and 

was 7 percent better or comparable for the other three sites. 

TauDEM flowlines for 10-m resolution DEMs had accuracies comparable to the ArcHydro stream extraction tool. For 

both stream-extraction tools, accuracies dropped as the DEM 

cell size increased. Also for both tools, accuracies were best 

in irregular plain topography with a physiography of low 

rounded ridges and shallow ravines. The worst accuracies 

were calculated for low-relief plains. 

During the initial stage of the stream extraction evaluation described in this report, the TauDEM D-Infinity tool was 

used for a section of the Delaware River and compared with 

the results for running the ArcHydro D8 tool for synthetic 

flowpath extraction. Synthetic flowpaths derived using the 

D-Infinity tool showed more realistic channel or tributary curvature than those derived using the D8 solution; however, for 

this site the geometry for flowlines developed using D-Infinity 

appeared similar to the geometry for flowlines derived using 

ArcHydro D8 functionality. Because the initial evaluation of 

lidar hydrography was done using the ArcHydro D8 application and because results from the two processes are similar, the 

D8 solution is used in this project. However, testing to develop 

a quantitative comparison between ArcHydro and TauDEM 

stream extraction techniques is recommended to be confident 

that the software program used for lidar synthetic flowpaths 

will produce the best results for accurate, valid delineation of 

hydrographic features.

Flow accumulation and stream definition.—The FDR is 

input to a flow accumulation tool that calculates the number 

of upstream cells flowing into a downstream cell and creates 

a flow accumulation grid. Next, the Stream Definition tool is 

used to create stream segments (synthetic flowpaths) from the 

flow accumulation grid. 

The stream definition value is the number of upslope 

cells required to flow into a grid cell for the receiving cell 
8 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 

75°16'

41°54'

41°53'

0 0.5 KILOMETER

0 0.5 MILE

Fill sinks Draining

process

D8 flow direction

Flow accumulation

Stream definition

Stream segments

Catchment grid

Catchment polygon

Flow accumulation 

threshold—

Number of grid 

cells that must 

flow to a cell for 

the receiving cell 

to be a stream 

segment

Bathymetric light detection and ranging 

digital elevation model

D8 flow direction grid

Delaware River bank

East

Southeast

South

Southwest

West

Northwest

North

Northeast

EXPLANATION

.

Figure 3. Synthetic flowpath extractions from light detection and ranging (lidar) digital elevation models.

to qualify as a stream segment of a synthetic flowpath, and is 

better known as the flow accumulation threshold FAC. Using 

ArcHydro, the Stream Definition tool automatically provides 

1 percent of the maximum FAC (MaxFAC) value, which is 

the maximum number of cells calculated to flow to a receiving cell in a DEM as the default stream definition value. For 

the Delaware River system, using 1 percent of the MaxFAC 

extracted the main river channel. The FAC to develop the main 

river channel and additional, associated stream/river (tributary) 

features is a smaller percentage of the MaxFAC value. The 

percent of the MaxFAC value that will be used to create the 

most useful synthetic flowpath network will depend on site 

conditions and resolution and the density of synthetic flowpaths 

required for user needs. The size of a watershed also affects 

synthetic flowpath development, and another approach for 

evaluating stream definition is to calculate FACs as the area 

upstream from receiving cells in order to analyze or model 

surface-water flow (L. Stanislawski, U.S. Geological Survey, 

written commun., 2017).
Comparison of Synthetic Flowpaths and National Hydrography Dataset High Resolution Flowlines 9

Stream segment and subsequent routines.—Once the 

Stream Definition is complete, the sequence of ArcHydro 

applications to develop synthetic flowpaths is Stream Segment, Catchment Delineation, Catchment Polygon, and 

Flowline Processing routines. The two catchment tools are not 

needed to develop synthetic flowpaths but are necessary for 

creating watersheds. Capabilities for developing watersheds 

that use flowlines and catchments in ArcHydro were tested; 

however, compared with the scale of the HR NHD Watershed 

Boundary HUC 12 polygons, the relatively narrow corridor for 

the lidar bathymetric/topobathymetric survey, which resulted 

in narrow watersheds confined to the limits of the surveyed 

areas, did not allow a useful evaluation of lidar watersheds and 

HR NHD WBDs. 

Bathymetric lidar synthetic flowpaths created from different lidar DEM resolutions and at different FAC values are 

overlain with HR NHDFlowline network HUC 8 datasets 

(U.S. Geological Survey, 2013a) to evaluate similarities and 

differences. Using 1 percent of the MaxFAC usually develops 

synthetic flowpaths that correlate with the main Delaware 

River channel depicted in the HR NHDFlowline network as 

Artificial Path vector data. Smaller MaxFAC percentages used 

to develop smaller FACs create synthetic flowpaths in addition to the main river channel delineation. These synthetic 

flowpaths represent tributaries or first order stream equivalents 

identified as HR NHDFlowline network stream/river feature 

types.

Synthetic flowpaths were further evaluated and validated 

by overlaying with 3D Elevation Program (3DEP) 10-m 

resolution DEMs, which for this region are all derived from 

lidar data (U.S. Geological Survey, 2016c), and 2013 to 2015 

orthoimagery at 1-meter resolution available from the National 

Agricultural Imagery Program (NAIP) (Esri, 2015). Synthetic 

flowpaths that were not included in the HR NHDFlowline 

network are assessed to see if these could be used to enhance 

the density, distribution, and connectivity of the HR NHDFlowline network feature types. 

Comparison of Synthetic Flowpaths 

and National Hydrography Dataset 

High Resolution Flowlines

In the HR NHDFlowline network, the Artificial Path feature type is used to delineate the Delaware River channel flowlines. Artificial Paths are surrogates for the general flow direction of HR NHDFlowline network stream/river feature types. 

Single-line Artificial Paths represent stream/river feature types 

12.2 m wide but less than 183 m that approximate the center 

line for assumed and generalized flow through a 2-dimensional feature such as a lake or a wide double-banked (polygon) stream/river features (U.S. Geological Survey, 2016b). 

Stream/river features greater than that are 12.2 m (40 feet) 

wide and continuous for at least 183 m (600 feet) are doubleline Artificial Paths (U.S. Geological Survey, 2016b). Artificial 

paths also are used to approximate the center line for closed 

water bodies that either fall on a streamline, or closed water 

bodies that are the origin or source of a flow path. Tributaries 

and creeks are categorized as stream/river feature types. Other 

flowline feature types in the study area include canal/ditches 

(constructed open waterways), pipelines (closed conduits), 

and connectors that are nonvisible lines used to connect two 

nonadjacent network segments.

Bathymetric Lidar Synthetic Flowpaths for the 

Delaware River

The combined length of channels extracted from lidar 

BDEMs for the Hancock Narrows, Middle River, and the 

Trenton Groups depends on the FAC values and the resolution 

of the lidar BDEM. Total lengths of synthetic flowpaths resulting from 1-meter grid spacing are always greater than for the 

other resolutions at the same FAC. Generally, resulting lengths 

are similar for 5- and 10-m resolutions at the same FAC. For 

1-, 5-, and 10-meter resolution DEMs, using 1 percent of the 

MaxFAC, which creates the main river channel, the total combined length of synthetic flowpaths for the three study groups 

ranged between 223 and 283 km (table 1). Using 0.05 percent 

of the MaxFAC for the three DEM resolutions, the combined 

lengths for the three survey groups vary between about 744 

and 1,317 km. These totals include the extracted river channel and additional synthetic flowpaths that are distributed 

along the length of the survey and within the surveyed river 

corridor. Review of table 2 which presents the FAC areas for 

the Hancock Narrows, Middle River, and Trenton Group(s) 

at different FAC values shows an increase in the FAC area 

with an increase in grid cell size, even though the number of 

cells decreases (table 3). This means that synthetic flowpaths 

extracted from a 1-meter resolution lidar bathymetric DEM 

will be more densely distributed but cover less area than the 5- 

or 10-m resolution lidar bathymetric DEM. Which lidar DEM 

resolution is best may depend on site conditions that can affect 

how well created stream segments connect to develop continuous synthetic flowpaths, and on individual user needs. 

The geometries for synthetic flowpaths extracted at different resolutions can be similar but offset from one another.
10 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 

Table 1. Survey lengths for three resolutions and flow accumulation threshold values.

[FAC, flow accumulation threshold; lidar, light detection and ranging; MaxFAC, maximum flow accumulation; %, percent] 

Delaware River bathymetry lidar survey group lengths

Hancock Narrows Group Middle River Group Trenton Group

FAC

(percent of 

MaxFAC)

Grid cell size, in meters Grid cell size, in meters Grid cell size, in meters

1 5 10 1 5 10 1 5 10

Length, in meters Length, in meters Length, in meters

1% 81,068 79,261 78,761 74,154 56,130 55,381 127,932 87,465 89,650

0.05% 336,879 232,548 211,551 423,856 278,308 284,924 556,276 269,325 247,192

Table 2. Relation of change in area of flow accumulation threshold to create synthetic flowpath segments and grid-cell size.

[FAC, flow accumulation threshold; MaxFAC, maximum flow accumulation; %, percent] 

Area of flow accumulation threshold to create flowpath segment

Hancock Narrows Group Middle River Group Trenton Group

FAC

(percent of 

MaxFAC)

Grid cell size, in meters Grid cell size, in meters Grid cell size, in meters

1 5 10 1 5 10 1 5 10

Area, in square meters Area, in square meters Area, in square meters

1% 136,289 248,650 275,200 27,445 57,825 59,000 87,006 357,600 362,300

0.15% 20,443 37,275 141,300 4,116 8,675 8,400 13,051 53,625 153,400

0.05% 6,814 12,425 13,700 1,372 2,875 2,900 4,305 17,875 18,100
Comparison of Synthetic Flowpaths and National Hydrography Dataset High Resolution Flowlines 11

Table 3. Density and distribution of Hancock Narrows Group synthetic flowpaths at variable resolutions and flow accumulation 

thresholds 

[lidar, light detection and ranging; MaxFAC, maximum flow accumulation]

Comparison of synthetic flowpath extraction at three solutions for the Hancock Narrows Group

1-meter resolution 

lidar-derived drainlines 

5-meter resolution 

lidar-derived drainlines

10-meter resolution

lidar-derived drainlines

Flow 

accumulation 

threshold

MaxFAC 13,628,908 cells MaxFAC 994,642 cells MaxFAC 227,286 cells

Synthetic flowpath distribution

1-percent

 MaxFAC

River channel discontinuous along some 

reaches and around in-channel islands.

63 extracted flowlines

River channel discontinuous along some 

reaches and around in-channel islands.

22 extracted flowlines

River channel continuous except 

around in-channel islands.

21 extracted flowlines.

0.05-percent 

MaxFAC

River channel continuous. Additional 

flowline correlations with NHDHR 

Many additional isolated and connected flowlines 

Trellis patterns

2,565 extracted flowlines

River channel continuous except at inchannel islands. Additional flowline 

correlations with NHDHR. Additional 

connected and isolated flowlines 

Trellis patterns

1,292 extracted flowlines

River channel continuous Additional flowlines correlations with 

NHDHR Additional connected and 

some isolated flowlines 

Trellis-patterned flowlines

1,143 extracted flowlines.

Synthetic Flowpaths Extracted Using Different 

Flow Accumulation Thresholds

For 1-, 5-, and 10-m resolution lidar BDEMs, using 1 

percent of the MaxFAC usually creates the synthetic flowpath 

representing the main Delaware River channel though for 

1-meter resolution additional synthetic flowpaths sometimes 

develop. Decreasing the FAC from 1 percent of the MaxFAC 

to smaller values creates additional stream/river feature types 

delineating tributaries and other surface-water flowlines. 

Decreasing the FAC often creates additional synthetic flowpaths that extend those created at higher FAC values, but also 

creates isolated or disconnected synthetic flowpaths. Testing a 

range of FACs showed that using 0.05 of the MaxFAC consistently developed synthetic flowpaths representing the Delaware River channel, Delaware River tributaries, new synthetic 

flowpaths connected to the river, and other additional synthetic 

flowpaths proximal to HR NHDFlowline network that could 

be further assessed for enhancing the distribution and connectivity of surface-water flowline features. 

Results for a section of the Trenton Group 10-m resolution data show how creating synthetic flowpaths at 1 percent 

of the MaxFAC delineates the Delaware River channel along 

the lowest extracted river channel bathymetry, representing 

part of the current or a previous thalweg position (fig. 4). Lowering the FAC to 0.05 percent of the MaxFAC created a denser 

and more continuous network of synthetic flowpaths that 

extend the main river channel and stream/river features created 

at the larger FAC, and also developed synthetic flowpaths that 

match with tributaries identified as HR NHDFlowline network 

stream/river features (fig. 4). The total length of ESFs using 

1 percent is 89 km and using 0.05 percent, it is 247 km.

In some places, synthetic flowpaths extracted from lidar 

BDEMs form trellis-patterned flowlines (fig. 5). Formation 

of trellis-patterned flowlines can happen in flat-bottomed or 

near to flat-bottomed river reaches, or in river sections behind 

(upstream from) human-made or natural obstructions that alter 

downstream directed flow. The trellis-patterned flowlines also 

may develop in areas where a downstream river reach has a 

higher channel bottom with a shallower water depth than a 

proximal upstream reach, such as what is shown in figure 5 

when 0.05 percent of the MaxFAC was used to create synthetic flowpaths. At this site a weir has changed the expected 

downstream flow direction of the synthetic flowpath and a 

trellis pattern with multiple parallel lineaments depicting 

synthetic flowpaths developed upstream from the weir. Crosssection profiles indicate that the lidar BDEM depicts several 

quasi-parallel shallow (less than 1 m) elevation changes in a 

ridge-trough type surface for the upstream river bed bathymetry and that the software solution did not identify any of the 

troughs as synthetic flowpaths. Under the altered flow conditions, the software algorithm fills or raises the upstream, 

deeper pool and creates a flat surface where the trellis pattern 

forms. At the site in figure 5, changing the FAC from 0.05 percent to 0.15 percent and 1.0 percent of the MaxFAC simplifies 

the synthetic flowpath pattern, creating only the outer limbs of 

the trellis pattern using 0.05 percent. The outer lineament on 

the east delineates the deepest synthetic flowpath or potential 

thalweg and the outer, western lineament overlies a ditch or 

canal depicted as an HR NHDFlowline network Artificial 

Path. Although using the bigger FAC values can avoid the 
12 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 

75°

40°24'

0 0.9 KILOMETER

0 0.9 MILE

1 percent of the maximum flow accumulation threshold value

U.S. Geological Survey, The National Map

75°

40°24'

0 0.5 1 KILOMETER

0 0.25 0.5 1 MILE

0.15 percent of the maximum flow accumulation threshold value

U.S. Geological Survey, The National Map

EXPLANATION

Synthetic flowpaths for 

10-meter grid-spacing

1.0 percent of flow 

accumulation threshold

0.15 percent of flow 

accumulation threshold

0.05 percent of flow 

accumulation threshold

River bank

Trenton Group elevation, 

in meters

176.806

158.74

140.673

122.607

104.54

86.4739

68.4075

50.3411

32.2746

14.2082

−3.8582

.

.

. 0.05 percent of the maximum flow accumulation threshold value

75°

40°24'

0 0.9 KILOMETER

0 0.9 MILE

U.S. Geological Survey, The National Map

Figure 4. Distribution of 

Trenton Group synthetic 

flowpaths for different flow 

accumulation threshold values 

at 10-meter grid-spacing.
Comparison of Synthetic Flowpaths and National Hydrography Dataset High Resolution Flowlines 13

74°57'

40°21'15"

Map image is the intellectual property of Esri and is used herein under 

license. Copyright © 2017 Esri and its licensors. All rights reserved

.

0 0.2 0.4 KILOMETER

0 0.2 0.4 MILE

EXPLANATION

Synthetic flowpaths

0.05 percent of maximum 

flow accumulation (MaxFAC) 

Figure 5. Trellis patterned synthetic flowpaths for 10-meter resolution Trenton Group at 0.05 percent of the 

maximum flow accumulation value. 
14 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 

trellis pattern, lowering the FAC decreases the density and 

distribution of potentially useful synthetic flowpaths in other 

river reaches. If the modeler prefers using the smaller FAC, 

steps can be taken to improve extracted channel delineations, 

such as burning a trench through the center of the obstruction. 

In this case, burning a trench through the weir or directing the 

flowline through the lock located on the left side of this feature 

will improve results for channel extraction. 

Bathymetric Lidar Synthetic Flowpaths at 

Different Resolutions 

To choose the most useful FACs, choosing the best 

resolution of lidar DEMs to extract synthetic flowpaths may 

depend on site conditions that obstruct and alter the primary 

flow direction detected in the FDR process or conditions such 

as where low topographic relief makes it difficult for the FDR 

function to create the flow grid needed to develop the stream 

definition. The difference in results using different resolutions is clearly shown where an in-channel island obstructs 

the flow direction at a section of the Trenton Group (fig. 6). 

West of and upstream from the in-channel island, the synthetic 

flowpaths extracted from 1-meter resolution geodata using 1 

percent of the MaxFAC create a continuous main river channel 

and additional synthetic flowpaths that depict part of a parallel 

river channel and canal. To the west side of the island, the synthetic flowpath developed for the main river channel becomes 

discontinuous until about halfway around the island, where 

synthetic flowpaths on either side of the island are created and 

then merge on the east side of the island. Continuing east of 

the island, the 1-meter resolution lidar BDEM created additional, false channels. In NAIP orthoimagery, these features 

delineated a canal and a tree line lineament (fig. 6). 

In contrast to results extracted from 1-m resolution data, 

synthetic flowpaths extracted from the 5-m (not shown) and 

10-m resolution lidar BDEM represent continuous river channels around the northern side of the in-channel island, but 

results are discontinuous on the south side for the 1-m resolution. The 1-m resolution FDR shows that grid cells in the area 

west (upstream) of the in-channel island are multidirectional, 

which seems to have affected the FAC requirement for developing stream segments and limited the stream segment connectivity (fig. 6). The FDR for the 10-m (and 5-m) resolution 

lidar BDEM shows dominant east-directed flow. 

Synthetic flowpaths created at another section of the 

Trenton Group using 1-, 5-, and 10-meter resolution lidar 

BDEMs provide another example of differences for results 

that seem to be due to site conditions (fig. 7). In this case, the 

Delaware River flow path is disrupted by an in-channel island 

at a bend where the river is bordered by a low-relief river 

terrace. West of the in-channel island, the 1-m resolution lidar 

BDEM depicts isolated synthetic flowpaths for the east- and 

southeast-flowing Delaware River until about midsection of 

the island. These disconnected synthetic flowpaths correspond 

in position with the continuous synthetic flowpaths created 

from 5- and 10-m resolution lidar BDEMs. At about the 

middle of the island, the 1-m resolution synthetic flowpaths 

on the north and south side merge to represent the main river 

channel (fig. 7). The 10-m (and 5-m) resolution lidar BDEM 

depicts the Delaware River as a single river channel on the 

south side of the island. Similar to results for the site previously described and shown as figure 6, the 1-m resolution lidar 

BDEM develops additional isolated synthetic flowpaths not 

included in the results for the two other lidar BDEM resolutions. In this case, one of the synthetic flowpaths is south of 

the main river channel in a shallow water body where the FDR 

indicates a uniform west-directed flow, which is opposed to 

the general eastward flow direction. 

The HR NHDFlowline network Artificial Path of the river 

shown in figure 7 delineates the river centerline. Synthetic 

flowpaths derived from the 5- and 10-meter resolution lidar 

BDEMs cross back-and-forth over the NHDHR Artificial Path 

and in some areas the synthetic flowpaths and the artificial 

path are offset about 85 m. A cross-section profile (not shown) 

indicated the river bottom is almost flat. 

The FDR created for the 1-m resolution lidar BDEM 

developed highly variable flow directions (fig. 7). There are no 

obvious obstructions to alter the general easterly flow direction 

and in this case the low-relief river bathymetry identified in 

the 1-m resolution lidar BDEM is thought to prevent development of a dominant flow direction. Conversely, in the same 

survey area the FDR for the 10-m (and 5-m) lidar BDEM 

developed a distinct easterly flow direction (fig. 7). These 

results show that although the 1-m lidar BDEM delineates 

some additional synthetic flowpaths, the FAC does not develop 

connected stream segments and the larger resolution lidar 

BDEMs are more useful for developing a main river channel. 

A recommended solution for developing more continuous 

synthetic flowpaths when the lateral extent of bathymetric/

topobathymetric lidar surveys is limited is to develop better 

flow accumulations for river systems by including surrounding DEMs (Stanislawski, 2017). Future analyses could include 

trial runs to assess results using this technique for extending 

lidar bathymetric synthetic flowlines.

Results for extracting synthetic flowpaths at a river bend 

in the Hancock Narrows Group show another example of how 

site conditions can have different effects on FDRs created for 

different resolutions (fig. 8). In this case, using 0.05 percent 

of the MaxFAC as the FAC, the 1-m resolution lidar BDEM 

synthetic flowpath representing the Delaware River channel is discontinuous just north of an in-channel island, but 

upstream from the island the 1-m resolution lidar BDEM 

forms a continuous river channel where the 5- and 10-m 

resolution lidar BDEMs form trellis patterns (fig. 8). Another 

difference between results at different resolutions was found 

at the river terrace located south of the river bend where a 

tributary identified in the HR NHDFlowline network that is 

delineated in the 1-m resolution lidar BDEM as a continuous 

lineament is not completely developed for synthetic flowpaths 

extracted from 5- and 10-m lidar BDEMs (fig. 8). These differences also are attributed to the FDRs created at different 
Comparison of Synthetic Flowpaths and National Hydrography Dataset High Resolution Flowlines 15

75°

40°24'

.

U.S. Geological Survey, The National Map

U.S. Geological Survey, The National Map

1-meter grid spacing

75°

40°24'

.

0 0.25 0.5 KILOMETER

0 0.25 0.5 MILE

0 0.25 0.5 KILOMETER

0 0.25 0.5 MILE

10-meter grid spacing

EXPLANATION

Trenton Group flow direction grid

East

Southeast

South

Southwest

West

Northwest

North

Northeast

River bank

Figure 6. Flow direction grids for 1-meter and 10-meter resolution bathymetric light detection and 

ranging (lidar) digital elevation models.
16 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 

40°34'30"

. Trenton Group 10-meter grid spacing

40°34'30"

Trenton Group 1-meter grid spacing

.

U.S. Geological Survey, The National Map

U.S. Geological Survey, The National Map

0 0.5 1 KILOMETER

0 0.5 1 MILE

0 0.5 1 KILOMETER

0 0.5 1 MILE

EXPLANATION

Synthetic flowpaths for 1 percent

of maximum flow accumulation

(MaxFAC)

10 percent of MaxFAC

flowpath

River banks

Flow direction grid

East

Southeast

South

Southwest

West

Northwest

North

Northeast

Figure 7. Synthetic flowpaths in flat terrain for Trenton Group at 1-meter and 10-meter resolution bathymetric digital elevation 

models.
Comparison of Synthetic Flowpaths and National Hydrography Dataset High Resolution Flowlines 17

75°16'30"

41°53'30"

μ

1-meter bathymetric digital elevation model resolution 

U.S. Geological Survey, The National Map 0 0.1 0.2 KILOMETER

0 0.1 0.2 MILE

75°16'30"

μ

5-meter bathymetric digital elevation model resolution

75°16'30"

μ

10-meter bathymetric digital elevation model resolution

EXPLANATION

Synthetic flowpaths for 0.05 percent of maximum flow accumulation

Synthetic flowpath Hancock Narrows, 1-meter resolution

Value

High : 420.426Low : 198.706

Hancock Narrows, 5-meter resolution

Value

High : 420.197Low : 199.227

Hancock Narrows, 10-meter resolution

Value

High : 420.205Low : 199.31

River bank

Figure 8. Synthetic flowpaths for Hancock Narrows Group at 0.05 percent of the maximum flow accumulation for 1-meter, 5-meter, and 10-meter bathymetric light detection and ranging (lidar) resolutions.
18 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 

resolutions. South-southeast directed flow was created for 1-m 

grid cells but in the same area 5- and 10-m resolution lidar 

BDEMs created the disconnected tributary lineament. FDRs 

show south and southwest trending flow directions that would 

prevent flow accumulation from developing continuous stream 

segment geometries (fig. 9). Lidar BDEMs at all resolutions 

created a synthetic flowpath for a long, narrow topographic 

low adjacent to the river channel.

Lidar Synthetic Flowpaths and National 

Hydrography Dataset High Resolution Flowline 

Network Correspondence

Alignment of lidar BDEM synthetic flowpaths delineating the Delaware River with the HR NHDFlowline network 

Artificial Path indicates synthetic flowpath extraction using 

1 percent and 0.05 percent of the MaxFAC value can provide baseline digital data as a resource for enhancing major 

river flowpaths in the HR NHDFlowline network. Although 

the bathymetric survey lidar DEMs do not reach more than 

a couple of hundred meters landward of the Delaware River 

banks, overlaying synthetic flowpaths using 0.05 percent of 

the MaxFAC with NAIP orthoimagery and the HR NHDFlowline network shows places along the Delaware river corridor 

where synthetic flowpath positions correspond with or connect 

to the HR NHDFlowline network Artificial Path and stream/

river features that extend upslope of the river banks (fig. 10). 

Places such as shown in figure 10 where there is good 

correspondence with the HR NHDFlowline network feature types indicate that synthetic flowpaths derived at the 

0.05-percent MaxFAC value for 5-m resolution data could 

serve as a baseline for evaluating potential updates to enhance 

the accuracy, density, and geographic distribution of the HR 

NHDFlowline network. Additional synthetic flowpaths that 

do not match up with HR NHD flowlines would need to be 

validated using NAIP orthoimagery, 3DEP DEMs, or other 

resources to help decide whether these could be integrated 

to improve the density, distribution, and connectivity of the 

HR NHDFlowline network. As an example, U.S. Topo maps 

show that some of the ESFs that do not connect with or extend 

HR NHDFlowline network stream/river features occur where 

V-shaped contour patterns depict either valleys or streams that 

seem to be connected to the river channel. Synthetic flowpaths 

connected to these contour patterns could be further evaluated 

to see if the synthetic flowpaths represent valid stream/river 

features that could be used to enhance density and connectivity in the HR NHDFlowline network; however, heavily forested slopes, such as those in this study area, can hide the bare 

earth so that the potential tributaries may not be validated in 

orthoimagery. Although using 0.05 percent of the MaxFAC for 

1-meter resolution lidar bathymetric DEMs for the same area 

created an almost continuous river channel and some synthetic 

flowpath features that agreed with HR NHDFlowline network 

stream/river feature types representing tributaries, many additional drainlines that were not connected to the river channel 

or the HR NHDFlowline network were extracted, and patterns formed in some reaches of the river trellis. These results 

again show that there can be tradeoffs for using one resolution 

instead of another.

Compatibility of Lidar Topobathymetry and 3D 

Elevation Program Digital Elevation Models

Compatibility between the Delaware River bathymetric 

lidar survey model and 3DEP DEMs is assessed by evaluating profiles across bankslope to river bed transitions depicted 

in the contoured Delaware River lidar BDEM, and difference 

analyses that reveal correspondence and some differences. 

Using the Hancock Narrows Group as an example, differences 

between the lidar BDEM and 3DEP DEMs are concentrated 

on the outside of river bends and range between 0 and 2 m.

Cross-section profiles that are created from the contoured 

bathymetric lidar DEM and depict bank slope to river bottom 

elevations show that the lidar BDEM creates seamless boundaries by presenting smooth elevation transitions from moderately and steeply sloping river banks, through the topographicbathymetric interface, and to the river channel bottom without 

gaps (fig. 11). The uninterrupted slope surfaces indicate the 

lidar survey sensor system and processing techniques used 

to collect and develop the Delaware River bathymetry and 

topobathymetric components of the Delaware River corridor 

survey are able to successfully merge the two (green and nearinfrared) lidar waveforms.

Although the results for the bathymetric/topobathymetric lidar sensor system create a seamless boundary for the 

merged bathymetric-topographic elevation model, this does 

not ensure agreement between the lidar BDEM and 3DEP 

DEMs. To assess agreement between the Delaware River 

lidar survey DEMs and 3DEP DEM raster datasets, the 3DEP 

DEM was extracted using the footprint of the lidar survey 

tiles for the Hancock Narrows Group and the resulting 3DEP 

DEM raster dataset was differenced with the Hancock Narrows Group. Differences between the lidar survey elevations 

and 3DEP DEMs were contoured at 2-m intervals and these 

results were evaluated for variability between the two model 

types (fig. 12). Contours for 0-m differences line both river 

banks and in general, there is good agreement. In contrast, 

other resulting difference contours for this comparison show 

dense contour patterns parallel to the river bank and extending 

upslope from the shoreline that correspond to a smooth elevation transition up the steep river banks. 

Using the sum of difference-contour lengths for a subset 

of the Hancock Narrows Group in this area, most of the differences between the bathymetric lidar survey results and 3DEP 

DEMs are 0 to 6 m. There were 0-m difference contours for 

about 25 percent of the comparison, 2-m difference contours 

for another 30 percent, and 4-m difference contours for 19 

percent. In the same region there are differences of 4 or 6 m 

that account for another 25 percent of the comparison. The 

distribution of comparison results is similar to that for analysis 
Comparison of Synthetic Flowpaths and National Hydrography Dataset High Resolution Flowlines 19

.

1-meter resolution flow direction grid

0 0.04 0.08 KILOMETER

0 0.04 0.08 MILE

.

10-meter resolution flow direction grid

41°53'30"

U.S. Geological Survey, The National Map

75°16'

41°53'30"

.

 U.S. Geological Survey, The National Map

Enlarged 1-meter 

and 10-meter areas

(shown in yellow)

EXPLANATION

D8 flow direction grid

East

Southeast

South

Southwest

West

Northwest

North

Northeast

Synthetic flowpath

River bank

Figure 9. Hancock Narrows Group D8 flow direction grid for 1-meter and 10-meter bathymetric light detection and ranging (lidar) 

digital elevation model resolution.
20 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 

EXPLANATION

Synthetic flowpath and High Resolution 

National Hydrography Dataset 

Flowline network feature correlation 

5-meter Hancock Narrows synthetic flowpath

5-meter Hancock Narrows

bathymetric surface

Meters

420.197

398.1

376.003

353.906

331.809

309.712

287.615

265.518

243.421

221.324

199.227

High Resolution National Hydrography Dataset Flowline

network feature type

Artificial path

Stream/river

U.S. Geological Survey, The National Map

75°06'

41°48'

0 0.5 1 MILE

0 0.5 1 KILOMETER

μ

Figure 10. Correspondence between bathymetric light detection and ranging (lidar) synthetic flowpaths and the 

High Resolution National Hydrography Dataset Flowline network.
Comparison of Synthetic Flowpaths and National Hydrography Dataset High Resolution Flowlines 21

EXPLANATION

Hancock Narrows 

bathymetric surface Meters

420.426

398.706

348.706

298.706

248.706

198.706

Line of profile

75°16'

41°52'30"

41°52'

®

U.S. Geological Survey, The National Map

0 0.15 0.3 MILE

0 0.15 0.3 KILOMETER

Delaware River cross-section profile

Bathymetric surface, in meters

Hancock Narrows Group, 1-meter resolution

0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 Elevation, in meters

270

268

266

264

262

260

35-percent surface slope

Water surface

Figure 11. Bank slope to river channel bottom without gaps derived from light detection and ranging (lidar) bathymetric/

topobathymetric digital elevation model.
22 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 75°04'30" 41°48'

μ

U.S. Geological Survey, The National Map

EXPLANATION

Elevation difference, 

in meters

28.120820.79213.46336.13448-1.1943-8.52307

River bank

0 0.25 0.5 KILOMETER0 0.25 0.5 MILE

0 0.5 1 KILOMETER0 0.5 1 MILE

41°48'

μ

U.S. Geological Survey, The National Map

River bank

EXPLANATION

1-meter resolution 

Hancock Narrows 

Value

High : 420.426Low : 198.706

Enlarged area

Figure 12. Elevation difference by subtracting 3D Elevation Program digital elevation models from bathymetric light detection and ranging (lidar) digital elevation models.
Discussion 23

of the entire Hancock Narrows Group. When all of the Hancock Narrows Group is evaluated for correspondence with 

3DEP DEMs, there are no differences for about 33 percent of 

compared elevations, 2-m differences for about 30 percent, 

and 4-m differences for about 15 percent. For the subset of the 

Hancock Narrows Group, the largest differences between the 

two model types are concentrated as two clusters of grouped 

outliers forming at the edge of the lidar survey tiles on the 

north and south side of a river reach (not shown). Large differences also occur as clusters of outliers in the steep, heavily 

treed terrain upslope from the river bank or at the edges of the 

lidar survey. 

Calculated elevation differences farther upslope of the 

river banks indicate there are issues that may need to be 

resolved for new lidar topobathymetric geodata to seamlessly 

merge with 3DEP DEMs. As an example, a comparison of 

elevation profiles across the two model datasets in an area 

where the lidar BDEM covers steep, forested valley slopes 

shows that the upper and lower elevations for the two profiles 

are the same, but the contour patterns between the two profiles 

are different (fig. 13). Also, the topobathymetric lidar BDEM 

data created a ridge-valley type profile where the 3DEP DEM 

elevation contours reflect a smoothly sloping terrain. Overlaying orthoimagery and the lidar BDEM elevation contours 

showed the lidar BDEM delineates tree tops or gaps between 

trees instead of bare earth topography. 

The lidar data provided for this analysis were not classified, and where the river survey extends to include terrain 

elevations upslope from the river, the data were not processed 

to provide a bare earth surface terrain. Classification of 

EAARL-B lidar BDEMs and other bathymetric or topobathymetric lidar survey products to identify bare earth, structures, 

vegetation, and water features will help to understand and 

resolve the described differences. Otherwise, the 3DEP DEM 

provides the superior source.

Discussion

Overlaying results for synthetic flowpaths extracted from 

bathymetric lidar models with the HR NHDFlowline network, 

NAIP orthoimagery, and USGS Topo maps shows places 

where synthetic flowpath delineations agree with the HR 

NHDFlowline network and where valid additional synthetic 

flowpaths may enhance density, distribution, and connectivity 

of the HR NHDFlowline network. Synthetic flowpaths are not 

categorized as perennial, intermittent, or ephemeral stream/

river feature types though for the Delaware River, stream/river 

features proximal to a main river channel are expected to be 

perennial. 

At all resolutions and for all Delaware River survey 

groups, using 1 percent of the MaxFAC consistently developed synthetic flowpaths delineating the main river channel. 

Overlaying synthetic flowpaths with NAIP orthoimagery 

and 3DEP DEMs shows that these synthetic flowpaths often 

delineate river thalwegs. In the HR NHDFlowline network, the 

Delaware River is an Artificial Path feature type, and in some 

river reaches, the HR NHDFlowline network Artificial Path is 

offset from the river channel delineated in NAIP orthoimagery. 

The Artificial Path feature type is intrinsic to the NHD, providing delineation of major rivers and other HR NHD flowlines 

12.2 m wide or larger. However, developing a new feature 

class or type to acquire and maintain channel thalweg data 

could provide a geospatial database for 3-dimensional river 

channel geodata that could supplement HR NHDFlowline 

network Artificial Path feature types to provide river channel 

geometries important for accurate analyses and modeling.

Synthetic flowpaths created from several trial runs using 

both ArcHydro and TauDEM software applications were similar, although using the D-Infinity tool sometimes developed 

streamlines with curvature that better resembled natural stream 

geometry. Both tools developed trellis patterns for areas where 

the natural river flow direction was obstructed. An evaluation of results from using both tools in a subsample from lidar 

DEMs for locations with different site conditions can provide 

a more quantitative comparison between ArcHydro and TauDEM stream extraction techniques than was done in this study. 

Based on results for the Delaware River lidar survey lidar 

BDEMs, using 0.05 of the MaxFAC created the best results 

for evaluating benefits or issues for using bathymetric lidar 

synthetic flowpaths as a source for enhancing the density, 

distribution, and (or) connectivity of the HR NHDFlowline 

network stream/river feature type. In some areas, apparently 

valid synthetic flowpaths that are not included in the HR 

NHDFlowline network could be integrated to enhance the 

density, distribution, and/or connectivity of the HR NHDFlowline network. Valid synthetic flowpaths may not be in the 

HR NHD geodata because requirements for including data at 

the 1:24,000 map scale precluded these stream/river features, 

or because the hydrographic features were inadvertently or 

purposefully omitted. Another reason for omission may be that 

geologic and (or) hydrologic site conditions may have changed 

surface-water feature patterns over time. 

Depending on lidar DEM resolutions and (or) FAC 

values, uniformly filling low points or sinks in the bathymetric 

surface using the default Fill Sink function created realistic 

and continuous synthetic flowpaths for the dendritic river 

system; initial tests using different Fill Sink depth values did 

not seem to improve results. Reconditioning to align extracted 

channels with the flowline network was not required and 

hydro-enforcement was not used. However, in addition to the 

Fill Sinks function, tools or techniques to improve disconnected or discontinuous synthetic flowpaths should be further 

tested for providing improved results without altering the natural surface-water system geometry in flat areas or areas where 

flow is interrupted.

Understanding site conditions that can cause poor 

synthetic flowpath extraction is important for developing 

successful survey plans. These site conditions need to be 

considered when selecting appropriate geodata resolutions or 

FACs and when choosing techniques or software applications 
24 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 75°16'15" 41°53'50" 41°53'50"

μ

μ

U.S. Geological Survey, The National Map

μ

Elevationprofilelocation

Elevation

profile

Elevationprofile

3D Elevation Programdigital elevation model profile

Distance, in meters

140 120 100 80 60 40 20 0

340330320310300290280270

Bathymetric light detection and ranging digital elevation model profile

Hancock Narrows Group

150 140 130 120 110 100 90 80 70 60 50 40 30 20 10 0

sr et e mn i , noit avel E 340

330320310300290280270

Figure 13. Differences in topobathymetric light detection and ranging (lidar) and 3D Elevation Program digital elevation model surfaces.
Discussion 25

to overcome obstacles for successful extraction of synthetic 

flowpaths. Changes in geomorphology that control river 

channel geometries can present natural limitations for developing accurate representations of channel configurations. At 

some locations along the Delaware River corridor, synthetic 

flowpaths depicting the potential river thalweg did not correlate with the HR NHDFlowline network Artificial Path for 

the river, and the FDR developed stream segments for stream/

rivers or canals running parallel to the main channel. At other 

sites, neither the Artificial Path nor the extracted river channel synthetic flowpath correspond with the deepest part of the 

main river channel potentially representing the river thalweg. 

For both cases, the lack of correspondence could be expected 

because river footprints can be modified by storms or changes 

in flow volumes that cause changes in river bedform stability. 

Within the river and along river banks, in NAIP imagery 

neither submerged aquatic nor land-surface vegetation that 

might impede or diminish the quality of bathymetric or topographic laser waveform returns were seen; however, in some 

areas, tree lines just landward of river banks were sometimes 

interpreted as stream/river lineaments, or a ring of trees surrounding an exposed land surface was developed as an elevation data polygon surrounding a depression. The lidar topobathymetric survey and the 3DEP 10-m lidar DEMs depicting 

bare earth elevations merged well in the areas immediately 

adjacent to river banks. Notwithstanding, the lidar topobathymetric survey data were not classified and upslope from the 

river banks the topographic elevations seem to identify tree 

tops or other ground cover. Without classification of the lidar 

topobathymetric data, 3DEP DEMs provide better topographic 

elevations. 

Site conditions such as flat terrain, pool riffles, or inchannel islands affect the FDR application and cause apparent 

altered flow directions that generate isolated, disconnected, 

or invalid synthetic flowpaths, which can mean that the right 

FAC for creating useful synthetic flowpaths in some parts of a 

river reach may not provide good results in other river reaches. 

Altered flow that happens in areas upstream from human-made 

obstructions such as weirs also can prevent developing useful 

flow direction grids. Problems extracting synthetic flowpaths 

where flow is altered, or in areas of low-relief topography and 

bathymetry indicate software tools could be modified or developed to create improved FDRs for where these site conditions 

exist.

The lidar BDEMs created from bathymetric and topobathymetric lidar DEMs for the Delaware River provide examples for how lidar BDEMs could be a viable and beneficial 

data source for the HR NHDFlowline network. The results of 

this analysis are specific to the Delaware River corridor where 

the water is clear and the river flowpath is usually confined 

in a steep-walled river valley. Where surveyed, the river is 

not braided but in many sections in-channel islands or rough 

river bottom surfaces altered the flow direction, preventing 

synthetic flowpaths from developing. Poor flow direction grids 

also developed where the river corridor includes naturally 

flat river terraces or flood plain terrain. Synthetic flowpath 

extraction from lidar bathymetry and topobathymetry for 

rivers flowing in unconfined conditions would benefit from 

improved techniques to better define flow directions. 

This investigation focused on evaluating synthetic flowpaths extracted from bathymetric lidar DEMs as a source for 

enhancing the HR NHDFlowline network. Although results 

support this approach for enhancing the HR NHDFlowline 

network, further investigation is needed to better determine 

criteria for selecting appropriate survey sites and for understanding software routine limitations for extracting synthetic 

flowpaths from lidar bathymetry. The lateral extent of the 

Delaware River bathymetric lidar survey pre-empted analysis of catchments or watersheds for comparison with the HR 

NHD WBD HUCs. To assess this approach for enhancing the 

delineation of HR NHD catchments or watersheds, a project 

to prototype development of catchments or watersheds created 

by connecting lidar synthetic flowpaths with lineaments analogous to synthetic flowpaths that could be extracted from 3DEP 

DEMs is recommended. 

Results of the investigation indicate lidar synthetic flowpaths can help provide the following:

• Enhanced delineation of HR NHDFlowline network 

features types and geometries.

• Improved connectivity within the HR NHDFlowline 

network.

• Slope to river bottom transitions without gaps for 

coastal zone and inland surface-water features.

• River channel thalweg delineations as a new geospatial feature to supplement HR NHDFlowline 

network Artificial Paths. 

• The third-dimension need to develop 3-dimensional 

river channel models where water clarity and depth 

permit.

• Support to the NGP long term goal to better integrate 

elevation and hydrography and to provide 3-dimensional representations of natural and constructed 

features.

The NGP is still building a foundation of knowledge 

regarding use of lidar hydrography and is not committed to 

formalizing use of this technology. The level of effort for 

using synthetic flowpaths as a data source would depend on 

needed resources and requirements to improve the distribution, density, and (or) connectivity of the HR NHDFlowline 

network. 

As a next step in developing an understanding of the 

beneficial use of lidar hydrography, bathymetric lidar DEMs 

for different river geometries under variable site conditions 

is recommended. This analysis would help to determine 

the appropriate use of pre-extraction reconditioning tools 

and to identify river systems as candidates for bathymetric 

lidar surveys. Inland to coastal bathymetric lidar surveys are 

increasingly being considered for mapping surface-water 
26 Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines 

features. Communications or outreach to USGS Water Science 

Centers and other entities acquiring bathymetry could also 

provide survey systems and information about available data 

to help assess appropriate targets or site conditions that hinder 

development of valid hydrography. Another recommendation 

is to develop a database for river channel bathymetry to collect lidar BDEMs that include major river thalwegs as a new 

HR NHDFlowline network feature type. Developing this data 

source will help to provide accurate hydrographic data for HR 

NHDFlowline networks s and water bodies that are fundamental to hydrologic and hydraulic analyses and modeling used in 

water resource management and other fields such as environmental or aquatic habitat protection programs or flood plain 

management.

Summary

Extracted synthetic flowpaths (ESFs) for the Delaware 

River Survey were compared with the High Resolution 

National Hydrography Dataset (HR NHD) Flowline network 

to see how these geospatial data could be used to update 

the hydrographic geospatial dataset. Main river channel 

and stream/river features were created using different flow 

accumulation threshold values (the number of cells or area 

needed to create an ESF) for 1-, 5-, and 10-meter (m) resolution bathymetric/topobathymetric light detection and ranging (lidar) digital elevation models (DEMs) to determine the 

ESF results that best correspond with the HR NHDFlowline 

network and results that created additional stream/river feature 

types that could be used to improve the density, distribution, or 

connectivity in the HR NHDFlowline network. ESFs depicting 

additional stream/river features were compared with National 

Agriculture Imagery Program orthoimagery, U.S. Topo Maps, 

and 3D Elevation Program DEMs to evaluate whether the 

ESFs represented real flowpaths or if these lineaments delineated other linear features such as canals, tree lines, roads, or 

linear topographic depressions. 

The total length of the Delaware River is around 320 

kilometers. From north to south, the lidar bathymetry/topobathymetry survey data includes the Hancock Narrows, 

Middle River, and Trenton Group(s). Using 1 percent of 

the MaxFAC value as the FAC for grid cells at 1-, 5-, and 

10-meter resolution created a combined length of 223 to 283 

kilometers of ESFs that correspond to the main river channel 

and potentially represent the river thalweg. These results suggest a potential for enhancing the HR NHDFlowline network, 

perhaps as a supplemental data source, by delineating the river 

thalweg in places where the Delaware River area is depicted 

as an Artificial Path feature type in the HR NHDFlowline 

network. Using 0.05 percent of the maximum flow accumulation at the 1-, 5-, and 10-m resolutions extracted a total of 744 

to 1,317 kilometers of ESFs, with 780 kilometers representing 

the main river channel and additional synthetic flowpaths. At 

each resolution, decreasing the FAC from 1 percent to 0.05 

percent increased the resulting length of synthetic flowlines 

by a factor of 3 to 4 for the Hancock Narrows and Trenton 

Group(s), and by a factor of 5 for the Middle River Group. 

The cause for the larger difference for the Middle River Group 

is not known. One explanation may be that the Hancock Narrows and Trenton Group(s) are continuous, but the Middle 

River Group is discontinous and the lower FAC was needed to 

successfully develop denser, connected ESFs. We found that 

using FAC values greater than 0.15 percent of the MaxFAC, 

results were similar to those for using 1 percent. Using less 

than 0.05 percent of the MaxFAC created significantly more 

ESFs that were not useful for this analysis.

Calculating the area covered by ESFs based on the DEM 

resolution and FAC values, for all survey groups and for all 

three DEM resolutions, changing the FAC from 1 to 0.05 

percent of the MaxFAC consistently increased the area covered by a factor of 20. For the Hancock Narrows and Middle 

River Group(s), the area for an ESF created using the 1 and 

0.05 percent MaxFAC values for 1-m resolution geodata was 

about one-half the area covered by an ESF created using 10-m 

resolution bathymetric/topobathymetric lidar DEMs. Using 

the 1 and 0.05 percent MaxFAC values for the Trenton Group, 

the 1-m resolution ESF covered about one-quarter the area 

covered by the 10-m resolution ESF. Understanding the difference for results can help to plan and refine ESF projects based 

on the area of interest.

The Delaware River is a dendritic drainage system where 

the river channel is often cradled by steep-sided valley walls. 

Based on the results of this analysis, site conditions for the 

Delaware River corridor did not affect the quality of lidar 

bathymetry survey data. However, for some river reaches 

in-channel landforms obstruct flow, and at other places within 

the Delaware River corridor low-relief topographic or bathymetric surfaces impede software tool derivation of the flow 

direction. For these conditions the software flow direction tool 

did not calculate a primary flowpath for the river channel. The 

effect of these site conditions on synthetic flowpath extraction depended on the lidar DEM resolution. We found that 

synthetic flowpaths extracted from 1-m resolution lidar DEMs 

exhibited more varied flow directions around in-channel landforms than ESFs extracted from 5- or 10-m resolution lidar 

DEMs. As a result the 1-m resolution DEM created some isolated or discontinuous ESF segments where the 5- and 10-m 

DEMs developed more continuous flowpaths adjacent to the 

in-channel island. Upstream of the in-channel landform ESFs 

delineating a potential river thalweg were extracted from the 

1-m resolution DEM. However, in the same area the software 

tool solved for the flow direction by flattening the bathymetric 

surface which resulted in parallel trellis-patterned ESFs for the 

river bed in the 5- and 10-m resolution DEMs. Under different 

site conditions at an abandoned, low-relief river flood plain the 

flow direction grid for the 1-m resolution DEM developed a 

continuous ESF corresponding to a HR NHD stream/river but 

the larger resolution lidar DEMs created isolated or disconnected ESFs. These two examples are representative of results 

for similar site conditions in other reaches of the Delaware 
References 27

River and indicate that using basic terrain preprocessing tools, 

a) 1-m resolution lidar DEMs were not as good at developing 

ESFs around in-channel obstructions as the coarser resolution DEMs, and b) 1-m resolution lidar DEMs may provide 

more continuous ESFs in low-relief areas than the 5- and 10-m 

resolution lidar DEMs.

Synthetic flowpaths extracted using 0.05 percent of the 

MaxFAC provide ESFs that best correspond to the HR NHDFlowline network and that provide additional stream/river feature types which could enhance the HR NHDFlowline network 

with a minimal amount of effort required for revisions to existing HR NHDFlowline network geometries. With the caveat 

that results are affected by site conditions, we suggest that the 

community of users could test this FAC value as a starting 

place for developing ESFs from DEMs to evaluate benefits 

for using ESFs to enhance the HR NHDFlowline network. In 

order to extend ESFs into areas where the HR NHDFlowline 

network is sparse, we also suggest prototype testing to extract 

synthetic flowpaths from bathymetric/topobathymetric lidar 

DEMs merged with 3DEP DEMs. Moreover, extending the 

ESFs could be useful for developing HR NHD catchments and 

watersheds important in water resource analysis and modeling. 

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Miller-Corbett—Synthetic Flowpaths Derived from Light Detection and Ranging Topobathymetric Data and High Resolution Flowlines —Open-File Report 2018–1058

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