Basic Hydrology & Hydraulics: DES 601
Module 6Regional Analysis
Regional Regression Analysis• Regional analysis refers to the construction of
regression equations for a region by analyzing historical discharges on many streams within that region.
• These equations are statistical models of discharge based on certain explanatory variables, typically
AREASLOPESHAPE INDICESCLIMATE INDICES
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Watershed Characteristics• What characteristics influence runoff?
• Where you are• How large an area• Gradient
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Watershed Characteristics• What characteristics influence runoff?
• Width, shape• Elevation: minimum, maximum + slope• Roughness: Channels, overbanks• Geology and soils• Climate• Vegetation• Land use, including urbanization and
imperviousness• Controls: Dams, gates, diversions, channel
rectification
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Watershed Delineating• Topographic maps
• Hands-on methods• Marking directly on
map• Tracing using light
table• Computerized methods
• DEMs• GIS software• Semi-automated
delineation• Fully automated
delineation• Automated
measurements should always be verified
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Information Sources• USGS quadrangle maps• Aerial photos• Satellite imagery• NRCS soil surveys• Field surveys• Previous investigations
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NRCS county soils surveys
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Soil descriptions
WEB SOIL SURVEY:
http://websoilsurvey.nrcs.usda.gov/app/HomePage.htm
http://soildata.tamu.edu/
http://soils.usda.gov/soils/technical/classification/scfile/index.html
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Learn More
Videos that show watershed delineation, and measuring some of the watershed characteristics.
http://ww.rtfmps.com/hec-hms-movies/Module-2/Video-2/
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Regional Regression Analysis• The equations are constructed by first fitting an
appropriate probability distribution to observations at a gaged location (station flood frequency).
• Then the station flood frequency curves are used as surrogate observations (at a specified AEP) to relate discharge to select geomorphic variables
• The “betas” are obtained by trying to make “epsilon” small, the AREA, SLOPE, and other watershed characteristics are the explainatory variables.
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(v Q AEP − β0 − β1
v A − β2
v S 0L )2 =
v ε
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General forms of regional equations
• The resulting equations are then expressed in a power-law form for actual application
• Equation suites for some regions have been chronically problematic (produce inexplicable or inconsistent results)
• Traditional regionalization is probably unwise in Texas – too much variation in climate and terrain, too little data.
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QAEP ,Estimate = β0(AREA)β 1 (SLOPE)β 2 (MAP)β 3
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Regression Equations in Texas• 1977 Massey and Schroeder (1977) USGS Water
Resources Investigations 77-110 Open File Report• 6 Regions and some undefined areas• Region 6 (trans-pecos Texas) used AREA and
MEAN ANNUAL PRECIPITATION as explanatory variables
• Region 3 (west-central Texas) used area as the only explanatory variable
• Analysis done using the “Bulletin 17B” process, which has since shown to perform erratically in much of Texas
• Variables used are AREA, SLOPE, and SHAPE, but their use is inconsistent within a suite of equations in some cases.
• Depreciated Method
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Regression Equations in Texas
• 1996 Asquith and Slade in• 11 Regions• 16 sets of equations (some regions are
broken at 32 square miles) 96 equations total
• Number of stations used for developing equations varies from 27 to 66
• SEE varies from 28% to 160%, with a mean of 66%.
• Depreciated Method
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Regression Equations in Texas
• 2009 Asquith and Roussel• Documented in HDM• 7 Equations for different AEP• Mean annual precipitation to account for
climatic variability• OmegaM used to account for location
(mapped value)• Area and Slope
• Current (2011) Suggested Method
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MAP
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OmegaEM
Regression Equations in Texas• 2009 Asquith and Roussel, Texas Regression
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Summary
• Regional analysis uses watershed characteristics obtained from maps, reports, etc. to estimate discharge at a location.
• Watershed characteristics are obtained from map and other sources – required a way to measure areas, lengths, etc.
• Regression equations relate these characteristics in a region to a discharge (and an AEP value).
• In Texas location is conveyed by the OmegaM parameter and climatic effect through the mean annual precipitation.
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