depressional wetland mapping in the prairie pothole …application example ... Øsaga gis, whitebox...
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Depressional Wetland Mapping in the Prairie Pothole Region
Esri User Conference, San Diego, CA
Qiusheng Wu a,
a CSS-Dynamac c/o U.S. EPA, Cincinnati, Ohio
Charles Lane b,
b U.S. Environmental Protection Agency, Cincinnati, Ohio
Office of Research and DevelopmentNational Exposure Research Laboratory July 22, 2015
The views expressed in this presentation are those of the author[s] and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.
Heather Golden b,
Grey Evenson b, Ellen D’Amico a
Outline• Research Background• Numerical Representation of Surface Depressions • Graph Theory-based Contour Tree Method• Application Example• Conclusions
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Outline• Research Background• Numerical Representation of Surface Depressions • Graph Theory-based Contour Tree Method• Application Example• Conclusions
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Surface Depressions and Wetland Landscape§Natural processes§Anthropogenic processes
Detention basins Reservoirs
Mining Quarrying
Volcanic craters Karst sinkholes
Vernal pools Prairie potholes
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Surface Depressions in Hydrologic Modeling
Flow
Time
Time Series
Hydrograph
The Water CycleFloodplain mapping
GIS data layers
Source: U.S. EPA Office of Water
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Surface Depressions as Analyses Problems
Depressions in digital elevation model (DEM)
Depressionless DEM
Discontinuous streams
Continuous streams6
Methods for Surface Depression Filling• Early method by O'Callaghan and Mark (1984)• The most widely-used algorithm, by Jenson and Domingue (1988)ØArcGIS, GRASS, TOPOZ,
River Tools …• The priority-flood algorithm by Wang and Liu (2006)ØSAGA GIS,
Whitebox GAT …
Ele
vatio
n
Spill Elevation
c0ci-1cici+1cn
Longitudinal profile7
Disadvantages of Traditional Methods• Do not distinguish between real and artifact depressions• Do not fully exploit high-resolution topographic data (LiDAR,
IFSAR, etc.)• Do not consider dynamic fill-and-spill hydrological processes• Do not derive quantitative information about nested
hierarchical structure
1-m resolution LiDAR DEM LiDAR DEM shaded relief 1-m resolution aerial imagery
Vernal pools 1-m resolution aerial imagery
Prairie potholes
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Outline• Research Background• Numerical Representation of Surface Depressions • Graph Theory-based Contour Tree Method• Application Example• Conclusions
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Numerical Representation of Surface Depressions A simple surface depression A compound surface depression
Longitudinalprofile
Contourrepresentation
Longitudinalprofile
Contourrepresentation
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Outline• Research Background• Numerical Representation of Surface Depressions • Graph Theory-based Contour Tree Method• Application Example• Conclusions
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Graph Theory-based Contour Tree Method§NodeØContour lines
§LinkØAdjacency
(topology)§Node attributesØArea, shape, etc.
(geometry)
Plan view of contour representation
Contour tree graph
Root node
Leaf nodes
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Contour Tree Representation of Depressions
A simple surface depression A composite surface depression
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Key Concepts§Sink point§Pour point§Seed contour§Pour contourØQuasi-pour
contourØTrue-pour contour
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Simplification of Contour Trees §Single-branch contour
treeØOnly root node left
§Multi-branch contour treeØSmaller compact tree
§Simplified contour tree ØDepression tree
Single-branchcontour tree
Multi-branchcontour tree
Simplifiedcontour tree
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Computation Procedures and Pseudo Codes
Pseudo codesArcToolbox
• Implemented using C++, Python, and ArcGIS• Fully automated
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Outline• Research Background• Numerical Representation of Surface Depressions • Graph Theory-based Contour Tree Method• Application Example• Conclusions
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Application ExampleEstimation of depression
storage capabilityPipestem Watershed,
North Dakota
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Hydrologic Connectivity of Prairie Potholes
LiDAR DEM shaded relief
LiDAR intensity imagery
Aerial photographs
National Wetlands Inventory
2003 2005 2006 2009 2012 2014
Nov. 2011 Nov. 2011 Jul. 2012 1980s
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Identification of Surface DepressionsDetected depression polygons vs.
National Wetlands Inventory polygonsContour tree method
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Depression Storage Capability§Below-water volume
§Above-water volume
4742.125.0 AVbw =
2)( RSCZVaw ´-´=
Empirical function fitting
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Outline• Research Background• Numerical Representation of Surface Depressions • Graph Theory-based Contour Tree Method• Application Example• Conclusions
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Conclusions• Detection, delineation, and characterization of surface depressions across scales
• Derivation of geometric and topological properties• Simulation of filling-merging-spilling hydrological processes
• Functionally effective and computationally efficient
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Charles LaneOffice of Research and Development
U.S. Environmental Protection [email protected]
Qiusheng WuCSS-Dynamac c/o U.S. EPA