Terrain Analysis Tools for Routing Flow and Calculating Upslope Contributing Areas John P. Wilson...
-
Upload
chad-johns -
Category
Documents
-
view
223 -
download
5
Transcript of Terrain Analysis Tools for Routing Flow and Calculating Upslope Contributing Areas John P. Wilson...
Terrain Analysis Tools for Terrain Analysis Tools for Routing Flow and Calculating Routing Flow and Calculating Upslope Contributing AreasUpslope Contributing Areas
John P. WilsonJohn P. Wilson
Terrain Analysis for Water Resources Terrain Analysis for Water Resources Applications Symposium 2002Applications Symposium 2002
Today’s TopicsToday’s Topics
Guiding principlesGuiding principles Proposed flow routing algorithmsProposed flow routing algorithms Flow routing methods implemented in Flow routing methods implemented in
TAPES-GTAPES-G Sensitivity of computed topographic Sensitivity of computed topographic
attributes to choice of flow routing attributes to choice of flow routing methodmethod
Key decisions, problems, and Key decisions, problems, and challengeschallenges
Scales / Processes / Scales / Processes / RegimesRegimes
Global
Meso
Topo
Micro
Nano
Cloud cover and CO2 levels control primary energy inputs to climate and weather patterns
Prevailing weather systems control long-term mean conditions; elevation-driven lapse rates control monthly climate; and geological substrate exerts control on soil chemistry
Surface morphology controls catchment hydrology; slope, aspect, horizon, and topographic shading control surface insolation
Vegetation canopy controls light, heat, and water for understory plants; vegetation structure and plant physiognomy controls nutrient use
Soil microorganisms control nutrient recycling
Water Flow on HillslopesWater Flow on Hillslopes
Land Surface ShapeLand Surface Shape
Courtesy Graeme Aggett 2001
Terrain Shape …Terrain Shape …
Terrain shape / drainage structure Terrain shape / drainage structure important at toposcaleimportant at toposcale
Locally adaptive gridding procedures Locally adaptive gridding procedures work well with contour and stream line work well with contour and stream line datadata
Need filtering / interpolation methods Need filtering / interpolation methods that respect surface structure for that respect surface structure for remotely sensed elevation sourcesremotely sensed elevation sources
Choose resolution based on data sources Choose resolution based on data sources / quality and not the application at hand/ quality and not the application at hand
Flow Direction / Catchment Flow Direction / Catchment AreaArea
Flow direction shows Flow direction shows path of water flow …path of water flow …
Upslope contributing Upslope contributing area A is area of land area A is area of land upslope of a length of upslope of a length of contour lcontour l
Specific catchment Specific catchment area is A/larea is A/l
Proposed Flow Routing Proposed Flow Routing AlgorithmsAlgorithms
Vary depending on granularity with Vary depending on granularity with which aspect is computed and whether which aspect is computed and whether single or multiple flow paths are single or multiple flow paths are allowedallowed
Single flow direction algorithmsSingle flow direction algorithms D8 (O’Callaghan and Mark 1984)D8 (O’Callaghan and Mark 1984) Rho4 / Rho8 (Fairfield and Leymarie 1991)Rho4 / Rho8 (Fairfield and Leymarie 1991) Aspect-driven (Lea 1992)Aspect-driven (Lea 1992)
… … Flow Routing Algorithms (2)Flow Routing Algorithms (2)
Multiple flow direction algorithmsMultiple flow direction algorithms FD8 (Quinn et al. 1991)FD8 (Quinn et al. 1991) FMFD (Freeman 1991; Holmgren 1994)FMFD (Freeman 1991; Holmgren 1994) DEMON (Costa-Cabral and Burges 1994)DEMON (Costa-Cabral and Burges 1994) R.flow (Mitasova and Hofierka 1993; R.flow (Mitasova and Hofierka 1993;
Mitasova et al. 1995, 1996)Mitasova et al. 1995, 1996) D∞ (Tarboton 1997)D∞ (Tarboton 1997) Form-based method (Pilesjo et al. 1998)Form-based method (Pilesjo et al. 1998)
Courtesy Qiming Zhou and Xuejun Liu 2002
TAPES-G AlgorithmsTAPES-G Algorithms
Single-flow-direction D8 methodSingle-flow-direction D8 method Randomized single-flow-direction Randomized single-flow-direction
Rho8 methodRho8 method Multiple-flow-direction FD8 and Multiple-flow-direction FD8 and
FRho8 methodsFRho8 methods DEMON stream-tube methodDEMON stream-tube method
TAPES-G InputsTAPES-G Inputs
Square-grid DEMSquare-grid DEM Important decisions about extent Important decisions about extent
of study area and how to handle of study area and how to handle edge effects, spurious sinks or pits, edge effects, spurious sinks or pits, etc.etc.
Interested in hydrologic Interested in hydrologic connectivity of topographic surfaceconnectivity of topographic surface
TAPES-G OutputsTAPES-G OutputsAttributes Units Definition
1,2 X, Y Usually metres X and Y coordinates as determined from the DEM
3 Flow direction None Computed using D8 or Rho8 algorithm4 Z Usually metres Elevation as read from the DEM
5 Contributing area Square metres or number of cells
Area draining out of each cell
6 Flow width Multiple of cell width Width associated with flow leaving the cell7 Slope Percent Slope in the steepest downslope direction8 Aspect Degrees clockwise from north The direction of the steepest downslope slope9 Profile curvature Radians per 100 metres Curvature of the surface in the direction of
steepest descent10 Plan curvature Radians per 100 metres Curvature of contour drawn through the grid
point11 Tangent curvature Radians per 100 metres Plan curvature multiplied by sine of slope angle12 Elevation residual Usually metres Difference between original DEM and
depressionless DEM13 Flow path length Usually metres The longest flow path from the catchment
divide or edge of DEM to the cell14 d(As)/ ds None Rate of change of specific catchment area
along the flow path
Final Cottonwood Creek Final Cottonwood Creek DEMDEM
Aspect / Primary Flow Aspect / Primary Flow Direction?Direction?
Shows aspect Shows aspect computed using computed using finite difference finite difference methodmethod
Poor choice of Poor choice of scale bar?scale bar?
Primary Flow Direction Primary Flow Direction (FLOWD)(FLOWD)
Approximate surrogate for aspect since it Approximate surrogate for aspect since it identifies direction to the nearest identifies direction to the nearest neighbor with maximum gradientneighbor with maximum gradient
FLOWD = 2FLOWD = 2jj - 1 - 1
where where jj = arg max = arg max ii = 1,8 = 1,8
The approximate aspect corresponding to The approximate aspect corresponding to this flow direction is this flow direction is ΨΨD8D8 = 45 = 45jj
)(9
ih
zz i
D8 SFD AlgorithmD8 SFD Algorithm
Does well in valleysDoes well in valleys Produces many Produces many
parallel flow lines parallel flow lines and problems near and problems near catchment boundarycatchment boundary
Cannot model flow Cannot model flow divergence in ridge divergence in ridge areasareas
D8 SFD AlgorithmD8 SFD Algorithm
Diagram shows detail Diagram shows detail near catchment near catchment boundaryboundary
Dark cells not located Dark cells not located on boundary – due to on boundary – due to subtle change in subtle change in aspect as it swifts aspect as it swifts from south to from south to southeastsoutheast
Rho8 SFD AlgorithmRho8 SFD Algorithm
Breaks up parallel Breaks up parallel flow paths / flow paths / produces mean flow produces mean flow direction equal to direction equal to aspectaspect
More cells with no More cells with no upslope connectionsupslope connections
Produces unique Produces unique result each timeresult each time
FD8 MFD AlgorithmFD8 MFD Algorithm
Distributes flow on Distributes flow on hillslopes to each hillslopes to each downslope neighbor downslope neighbor on a slope-weighted on a slope-weighted basisbasis
Specify cross-Specify cross-grading threshold to grading threshold to disable this feature disable this feature in valleysin valleys
FD8 Flow Dispersion WeightsFD8 Flow Dispersion Weights
DEMON AlgorithmDEMON Algorithm
Flow generated at each source pixel Flow generated at each source pixel and routed down a stream tube and routed down a stream tube until edge of DEM or a pit is until edge of DEM or a pit is encounteredencountered
Stream tubes constructed from Stream tubes constructed from points of intersections of a line points of intersections of a line drawn in gradient direction and a drawn in gradient direction and a grid cell edgegrid cell edge
DEMON Stream-Tube DEMON Stream-Tube AlgorithmAlgorithm
Three variants Three variants used in TAPES-G – used in TAPES-G – related to …related to … Choice of DEMChoice of DEM Use of grid Use of grid
centroids in place centroids in place of verticesof vertices
Definition of aspectDefinition of aspect
Upslope Contributing AreaUpslope Contributing Area
Computed with Computed with contour-based contour-based stream tubes stream tubes in northern in northern part of part of catchment …catchment …
TAPES-C Element NetworkTAPES-C Element Network
Contour DEM ElementsContour DEM Elements Set of elements formed Set of elements formed
by contours and flow by contours and flow lineslines
Proceeding uphill, flow Proceeding uphill, flow lines are terminated (A) lines are terminated (A) and added (B, C) to and added (B, C) to maintain even spacingmaintain even spacing
Lines are constructed Lines are constructed using either a minimum using either a minimum distance (BD) or distance (BD) or orthogonal (CE) criterionorthogonal (CE) criterion
Specific Catchment AreaSpecific Catchment Area
Percentage of 30 m Cells With Values in Ranges IndicatedMedian <40 40-70 70-110 110-180 >180
D8 57.2 30.9 27.6 13.3 13.7 14.6Rho8 41.1 39.3 28.2 11.8 10.6 10.2FRho8 88.9 13.0 24.9 18.7 23.1 20.3DEMON 105.4 11.7 22.1 20.1 20.2 25.9
105 km105 km22 Squaw Creek catchment in Squaw Creek catchment in Gallatin National Forest, MontanaGallatin National Forest, Montana
Results derived from 30 m DEMS Results derived from 30 m DEMS for 3 USGS 1:24,000 scale map for 3 USGS 1:24,000 scale map quadranglesquadrangles
Specific Catchment Area MapsSpecific Catchment Area Maps
Secondary Topographic Secondary Topographic AttributesAttributes
Secondary Topographic Secondary Topographic AttributesAttributes
Sediment Transport Capacity Sediment Transport Capacity IndexIndex
Percentage of 30 m Cells With Values in Ranges IndicatedMean 0-10.0 10.1-20.0 20.1-30.0 30.1-40.0 >40
D8 19.4 33.7 32.5 17.3 8.0 8.4Rho8 16.1 43.6 32.4 13.2 5.3 5.6FRho8 20.3 28.1 31.2 21.6 11.3 7.9DEMON 21.9 25.9 30.4 21.8 11.6 10.4
Grid ComparisonsGrid Comparisons
Flow routing algorithm D8 Rho8 FRho8 DEMOND8 XRho8 56.5 XFRho8 55.7 50.9 XDEMON 54.0 49.3 70.6 X
Key Decisions and ChallengesKey Decisions and Challenges
Methods can be distinguished based Methods can be distinguished based on equation used to estimate aspect on equation used to estimate aspect and whether or not they permit flow and whether or not they permit flow to two or more downslope cellsto two or more downslope cells
Most of the results produced thus far Most of the results produced thus far relate to coarse resolution DEM relate to coarse resolution DEM productsproducts
Sensitivity analysis results are Sensitivity analysis results are difficult to extrapolate to new study difficult to extrapolate to new study sitessites
New Data SourcesNew Data Sources
Several presentations about SAR Several presentations about SAR and LIDAR technology data at this and LIDAR technology data at this conferenceconference
Must develop and/or find methods Must develop and/or find methods for filtering and interpolation that for filtering and interpolation that respect surface structure for these respect surface structure for these remotely sensed elevation sourcesremotely sensed elevation sources
Interpolation ResultsInterpolation ResultsTIN IDW
Thin plate spline TOPOGRID
Surf.tps (GRASS)
Courtesy Graeme Aggett 2001
Better Sensitivity Analyses? Better Sensitivity Analyses?
Topographic AttributesTopographic Attributes
ElevationElevation SlopeSlope Profile curvatureProfile curvature Plan curvaturePlan curvature Distance from ridge linesDistance from ridge lines Incident solar radiationIncident solar radiation Topographic wetness indexTopographic wetness index Sediment transport capacity indexSediment transport capacity index
Fuzzy ClassificationFuzzy Classification
Split study area into three equal partsSplit study area into three equal parts Took stratified random sample and Took stratified random sample and
extracted topographic attributesextracted topographic attributes Performed several fuzzy k-means Performed several fuzzy k-means
classificationsclassifications Calculated confusion index and F and H Calculated confusion index and F and H
parameters and generated fuzzy and parameters and generated fuzzy and crisp landform class mapscrisp landform class maps
Final Landform ClassesFinal Landform Classes
Valley bottomsValley bottoms Main drainage linesMain drainage lines Lower slopesLower slopes Steep, shaded north-facing slopesSteep, shaded north-facing slopes Narrow ridge linesNarrow ridge lines Steep, south-facing, drier upper Steep, south-facing, drier upper
slopes and broad ridgesslopes and broad ridges
Cluster Centers and Cluster Centers and RangesRanges
Input data C1 C2 C3 C4 C5 C6ELEV 2094 2175 2316 2522 2540 2599SLOPE 1.97 5.04 9.26 21.61 13.10 22.18PROFC 0.01 -1.03 0.00 -0.47 2.58 -0.44PLANC -0.15 1.00 -0.24 0.01 -1.34 0.13RDPRX 6.23 6.04 5.54 5.40 0.10 5.48SOLAR 9.44 9.22 9.18 6.79 8.72 10.42WET20 13.17 16.92 12.02 11.32 10.77 11.47SED20 3.30 6.64 5.13 6.24 4.77 6.34
Input data C1 C2 C3 C4 C5 C6ELEV 1840-2731 1781-2749 1807-2962 1929-3118 1972-3101 2029-3223SLOPE 0-8.5 0-22.4 2.2-27.2 8.9-34.3 1.8-32.4 8.1-41.3PROFC -1.1-1.0 -5.2-0.8 -3.0-1.4 -4.5-1.7 1.0-6.6 -4.1-1.1PLANC -1.5-1.3 -0.6-8.1 -5.2-2.3 -5.2-3.4 -5.0-2.1 -3.9-5.8RDPRX 4.6-8.3 4.6-8.1 4.6-7.2 4.6-7.1 0.0-4.6 4.6-7.1SOLAR 8.7-10.2 7.4-10.6 7.6-10.3 3.5-8.8 4.7-11.2 8.7-11.9WET20 11.0-17.4 13.0-22.2 9.8-14.4 9.6-14.5 9.6-12.2 9.5-14.4SED20 1.7-5.4 4.5-9.1 3.5-6.8 5.4-7.4 2.9-6.0 5.1-8.4
Summary Data for Six ClassesSummary Data for Six Classes
Topo-climatic class Area (km2) Area (%)1. Valley bottoms 930.31 26.182. Drainage channels 369.81 10.413. Lower slopes 1048.33 29.514. N-facing steep slopes 370.85 10.445. Ridges 260.27 7.336. S-facing steep slopes 519.33 14.62Lakes 53.53 1.51
Final Map?Final Map?
Closing CommentsClosing Comments
Several graduate students working on Several graduate students working on new data sources and fuzzy new data sources and fuzzy classification of landscapesclassification of landscapes One is looking at performance of five flow One is looking at performance of five flow
routing algorithms in different landform routing algorithms in different landform classes with 5 m SAR DEM for exampleclasses with 5 m SAR DEM for example
May be able to answer one or two May be able to answer one or two questions if there is time availablequestions if there is time available