Evaluating the Quality of the National Hydrography Dataset for Watershed Assessments in Metropolitan Regions

Sheng, Jingfen; Wilson, John P.; Chen, Ning; Devinny, Joseph S.; Sayre, Jaime M.

doi:10.2747/1548-1603.44.3.283

Cited by 12 publications

(6 citation statements)

References 5 publications

(5 reference statements)

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“…LiDAR), and what exactly constitutes the surface then becomes more problematic. Indeed, this same ambiguity is true of stream channels given that the initiation of and paths followed by these features may vary from storm to storm in upland areas Dietrich, 1989, 1992;Sheng et al, 2007). Finally, the generation of "bare earth" DEMs that is often held up as the preferred result would seem less than optimal for a number of applications, such as nonpoint source pollutant applications that seek to trace pollutants from their sources to the ocean across large metropolitan regions (Fig.…”

Section: Data Capturementioning

confidence: 94%

Digital terrain modeling

2012

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Section: Data Capturementioning

confidence: 94%

Digital terrain modeling

2012

Self Cite

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“…The US Geological Survey (USGS) NHD is a comprehensive vector dataset of surface-water features within the United States (U. S. Geological Survey 2000; Sheng et al 2007), which is displayed and distributed through The National Map website (http://nationalmap.gov/viewer. html).…”

Section: Application Of Clc To Compare Vector Hydrography and Synthetmentioning

confidence: 99%

A rapid approach for automated comparison of independently derived stream networks

Stanislawski

Buttenfield

Doumbouya

2015

Cartography and Geographic Information Science

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This paper presents an improved coefficient of line correspondence (CLC) metric for automatically assessing the similarity of two different sets of linear features. Elevation-derived channels at 1:24,000 scale (24K) are generated from a weighted flow-accumulation model and compared to 24K National Hydrography Dataset (NHD) flowlines. The CLC process conflates two vector datasets through a raster line-density differencing approach that is faster and more reliable than earlier methods. Methods are tested on 30 subbasins distributed across different terrain and climate conditions of the conterminous United States. CLC values for the 30 subbasins indicate 44-83% of the features match between the two datasets, with the majority of the mismatching features comprised of first-order features. Relatively lower CLC values result from subbasins with less than about 1.5 degrees of slope. The primary difference between the two datasets may be explained by different data capture criteria. First-order, headwater tributaries derived from the flow-accumulation model are captured more comprehensively through drainage area and terrain conditions, whereas capture of headwater features in the NHD is cartographically constrained by tributary length. The addition of missing headwaters to the NHD, as guided by the elevation-derived channels, can substantially improve the scientific value of the NHD.

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“…Accessed October 1, 2019, https://www.usgs.gov/nathydro) provides the most comprehensive classification of perennial, intermittent, and ephemeral streams (Nadeau and Rains 2007). NHD is used extensively for cartography, study design, monitoring, and modeling at local, regional, and national extents (Stoddard et al 2005; Sheng et al 2007; Stanislawski 2009; Hill et al 2016; Isaak et al 2016; USEPA 2016; Macfarlane et al 2017), and such applications frequently use the NHD stream permanence classifications (SPC; i.e., NHD “hydrographic categories” of perennial, intermittent, and ephemeral) (Roy et al 2009; Benstead and Leigh 2012). Comparison of NHD SPC to non‐NHD, in situ streamflow observations (hereafter referred to as NNO) indicate that misclassification of stream class by the NHD can be an issue, particularly for headwater streams (Nadeau and Rains 2007; Caruso and Haynes 2011; Fritz et al 2013; Nadeau et al 2015).…”

Section: Introductionmentioning

confidence: 99%

The Influence of Climate Variability on the Accuracy of NHD Perennial and Nonperennial Stream Classifications

Hafen

Blasch

Rea

et al. 2020

J American Water Resour Assoc

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National Hydrography Dataset (NHD) stream permanence classifications (SPC; perennial, intermittent, and ephemeral) are widely used for data visualization and applied science, and have implications for resource policy and management. NHD SPC were assigned using a combination of topographic field surveys and interviews with local residents. However, previous studies indicate that non-NHD, in situ streamflow observations (NNO) frequently disagree with NHD SPC. We hypothesized that differences in annual climate conditions between map creation years and the years NNO were collected contributed to disagreement between NNO and NHD SPC. We compared NHD SPC to 10,055 NNO (classified as "wet" or "dry") collected in the Pacific Northwest between 1977 and 2015. Annual climate conditions were described with the Palmer Drought Severity Index (PDSI). Stream order was added as a covariate to account for different effects along the stream network. NHD SPC agreed with 80.5% of NNO. "Dry" NNO were five times more likely to disagree with NHD than "wet" NNO (p < 0.0001). Disagreement was greatest on first-order streams. When NHD SPC were collected during a wetter period than NNO the probability of disagreement increased by a factor of 1.17 (p < 0.0001) per unit difference in PDSI. The influence of climate on disagreements between NNO and NHD SPC provides support for the continued development of dynamic models representing SPC as opposed to static NHD classifications.

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Evaluating the Quality of the National Hydrography Dataset for Watershed Assessments in Metropolitan Regions

Cited by 12 publications

References 5 publications

Digital terrain modeling

Digital terrain modeling

A rapid approach for automated comparison of independently derived stream networks

The Influence of Climate Variability on the Accuracy of NHD Perennial and Nonperennial Stream Classifications

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