Assessment of a Rapid Assessment of a Rapid Approach for Estimating Approach for Estimating Catchment Areas for Surface Catchment Areas for Surface Drainage Lines Drainage Lines Lawrence Stanislawski, Science Applications Lawrence Stanislawski, Science Applications International Corporation (SAIC) International Corporation (SAIC) Michael Finn, U.S. Geological Survey Michael Finn, U.S. Geological Survey E. Lynn Usery, U.S. Geological Survey E. Lynn Usery, U.S. Geological Survey Mark Barnes, U.S. Geological Survey Mark Barnes, U.S. Geological Survey ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
31
Embed
Assessment of a Rapid Approach for Estimating Catchment Areas for Surface Drainage Lines Lawrence Stanislawski, Science Applications International Corporation.
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Assessment of a Rapid Approach for Assessment of a Rapid Approach for Estimating Catchment Areas for Estimating Catchment Areas for
Surface Drainage LinesSurface Drainage Lines
Lawrence Stanislawski, Science Applications International Lawrence Stanislawski, Science Applications International Corporation (SAIC)Corporation (SAIC)Michael Finn, U.S. Geological SurveyMichael Finn, U.S. Geological SurveyE. Lynn Usery, U.S. Geological SurveyE. Lynn Usery, U.S. Geological SurveyMark Barnes, U.S. Geological SurveyMark Barnes, U.S. Geological Survey
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
Brief overview of the National Hydrography Dataset Brief overview of the National Hydrography Dataset (NHD)(NHD)
Generalization Process for NHDGeneralization Process for NHD• Pruning of Drainage NetworkPruning of Drainage Network• Preprocessing RequirementsPreprocessing Requirements
• Simplification and other generalization operations
• Symbolization
Database
Validation
• Generalization metrics
• Benchmark comparisons
Products
• Level of detail
• Graphic product
Summary report
Users
NHD FeaturesNHD Features
Areal Stream/River
Areal Lake/Pond
Areal Lake/Pond
Linear Streams
Linear Canal/Ditch
Linear Connector
Artificial Paths
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
NHD FeaturesNHD Features
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
NHD FeaturesNHD FeaturesExample surface water flow network (NHDFlowline feature class)
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
National Hydrography Dataset (NHD)National Hydrography Dataset (NHD)
• Vector data layer of The National Map representing surface waters of the United States.
• Includes a set of surface water reaches
Reach: significant segment of surface water having similar hydrologic characteristics, such as a stretch of river between two confluences, a lake, or a pond.
A unique address, called a reach code, is assigned to each reach, which enables linking of ancillary data to specific features and locations on the NHD.
Reach code from Lower Mississippi subbasin
08010100000413
region-subregion-accounting unit-subbasin-reach number
Base data: highest resolution NHD that covers desired area.
Feature pruning – removal of features that are too small for desired output scale.• select a subset of network features• select a subset of area features• remove point features associated with pruned line or area features
Feature simplification• removal of vertices• aggregation, amalgamation, merging, linearization of area features,
etc.
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
NHD GeneralizationNHD Generalization
Catchment: The area associated with a segment of a drainage network is referred to as the segment’s catchment area, or just catchment. Surface runoff in the catchment flows into the associated network segment.
Catchments (cyan) associated with each network segment (red) of a hydrographic network.
The network pruning strategy of our NHD generalization process is based on upstream drainage area, which requires catchment area estimates for each network segment.
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
NHD GeneralizationNHD Generalization
Upstream drainage area (UDA) for any network segment is the sum of all upstream catchment areas, including the segment of interest.
For instance, the UDA for the network segment marked with the green square is the yellow shaded area (~ 11.2 sq km).
MethodsMethodsComparison to elevation-derived (ED) catchmentsComparison to elevation-derived (ED) catchments
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
Each ED catchment is precisely geospatially associated to one segment of a surface drainage network that is derived from the same elevation model.
Associating ED catchments to each segment of a hydrographic network, such as that in the NHD, is a complex and imprecise process.
Thiessen-polygon derived catchments can be precisely associated with individual segments of any network regardless of how the network is derived.
1. Generate surface drainage network from an elevation model.
2. Compute ED catchments for ED network.
3. Compute TPD catchments for ED network.
4. Compare ED and TPD catchments through an overlay process.
MethodsMethods
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
Study subbasins
Subbasin name State
NHD subbasin number Regime
Physiographic division1
Upper Suwannee
FL, GA 03110201 Flat Humid
Atlantic Plain of Coastal Plain
Lower Beaver UT 16030008 Flat Dry
Intermontane Plateaus of Basin and Range
Pomme De Terre MO 10290107 Hilly Humid
Interior Highlands of Ozark Plateaus
Lower Prairie Dog Town Fork Red TX 11120105 Hilly Dry
Interior Plains of Great Plains and Central Lowland
South Branch Potomac WV 02070001
Mountainous Humid
Appalachian Highlands of Valley and Ridge
Piceance-Yellow CO 14050006
Mountainous Dry
Intermontane Plateaus of Colorado Plateaus
Six NHD subbasins that fall in one of six regimes based on climate and
topography were evaluated.
For each subbasin: A 30-meter resolution DEM was
extracted from the National Elevation Dataset.
ED Streams and catchments were derived for several (7) stream formation thresholds.
TPD catchments were generated for all ED network segments
ED catchments and TPD catchments were compared through a spatial union.
MethodsMethods
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
Catchment comparison computations:
For each TPD catchment in all networks:• percent correct, • percent omission, and • percent commission
For all TPD catchments in each stream-formation threshold:
• Mean percent correct• Mean percent omission, and• Mean percent commission• Total percent correct
For all stream-formation thresholds in each subbasin:
• Average mean percent correct• Average mean percent omission, and• Average mean percent commission• Average total percent correct
Thiessen-derived catchment (red outline) overlaying associated elevation-derived catchment (gray outline) with correct area in green, and areas of commission error in purple and omission error in pink .
MethodsMethods
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
Computations:
Coefficient of areal correspondence (CAC) is computed for any two associated areas as the area of intersection, divided by the area of union. In the figure, CAC is the computed as the green area divided by the sum of all colored (pink, purple, and green) areas.
CAC was computed for all catchments of each subbasin and stream-formation threshold, and summarized in the same manner as percent correct values.
Thiessen-derived catchment (red outline) overlaying associated elevation-derived catchment (gray outline) with correct area in green, and areas of commission error in purple and omission error in pink .
ResultsResults
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
Number of catchments computed ranged from 957 to 24,603, with catchment density increasing with decreasing stream-formation threshold.
Average Mean Percent CorrectAverage Mean Percent Commission Error
Average Mean Percent Omission Error
Between subbasin comparisons:
Averages of mean percent correct values range from about 50 to 65, with averages better than 60 on hilly and mountainous subbasins.
Average total percent correct values
•range from about 58 to 75.
•greater than average mean percent correct for all subbasins.
Average mean omission errors are about 7 percent larger that average mean commission errors.
ResultsResults
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
0
20
40
60
80
100
120
0 500000 1000000 1500000 2000000 2500000
Catchment Area (sq m)
Per
cen
t C
orre
ct
Distribution of percent correct values for all catchments from the 100-cell stream-formation threshold for the mountainous humid subbasin (WV). Mode of distribution is 71.
Distribution of percent correct values compared to catchment size for the 100-cell stream-formation threshold in the mountainous humid subbasin (WV).
ResultsResults
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
0
20
40
60
80
100
120
0 500000 1000000 1500000 2000000 2500000
Catchment Area (sq m)
Per
cent
Cor
rect
Distribution of percent correct values compared to catchment size for the 100-cell stream-formation threshold in the mountainous humid subbasin (WV).
0
20
40
60
80
100
120
0 1000 2000 3000 4000 5000 6000
Segment length (m)
Per
cent
Cor
rect
Distribution of percent correct values compared to network segment length for the 100-cell stream-formation threshold in the mountainous humid subbasin (WV).
Catchments were separated into headwater (light green) and non-headwater catchments (light blue) based on whether or not they contained a dangling node (cyan) of a stream line.
Mean percentages were recomputed for headwater and non-headwater catchments.
Headwater average, average, and non-headwater average of the mean coefficient of areal correspondence (CAC) for each formation threshold is shown for each subbasin.
SummarySummaryResults suggest that the TPD catchment process is: Less likely to fail because of hardware or software limitations than ED
process, About 5 to 10 times faster than the ED catchment process, Logistically much simpler to implement than ED process which
requires a network integrated to an elevation model.And that the: Fractional part that TPD catchments overlay ED catchments is about
½ for subbasins in flat terrain and about 2/3 for subbasins in hilly or mountainous terrain.
Headwater TPD catchments exhibit better areal correspondence (up to 17 percent) with ED catchments than do non-headwater catchments.
The lowest areal correspondence of TPD catchments to ED catchments occurs on relatively small catchments or on very short network segments.
Better than 80 percent linear correspondence can be expected between networks pruned to 1:100,000-scale or smaller using UDA based on TPD catchments and UDA based on ED catchments.
ACSM-IPLSA-MSPS 2007, March 9-12, St. Louis, MO
Questions?Questions?
Assessment of a Rapid Approach for Estimating Assessment of a Rapid Approach for Estimating Catchment Areas for Surface Drainage LinesCatchment Areas for Surface Drainage Lines
Lawrence Stanislawski, Science Applications International Lawrence Stanislawski, Science Applications International Corporation (SAIC)Corporation (SAIC)Michael Finn, U.S. Geological SurveyMichael Finn, U.S. Geological SurveyE. Lynn Usery, U.S. Geological SurveyE. Lynn Usery, U.S. Geological SurveyMark Barnes, U.S. Geological SurveyMark Barnes, U.S. Geological Survey