Basic Hydrology & Hydraulics: DES 601 Module 6 Regional 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 AREA SLOPE SHAPE INDICES CLIMATE INDICES Module 6

Watershed Characteristics What characteristics influence runoff? Where you are How large an area Gradient Module 6

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 Module 6

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 Module 6

Information Sources USGS quadrangle maps Aerial photos Satellite imagery NRCS soil surveys Field surveys Previous investigations Module 6

NRCS county soils surveys Module 6

Soil descriptions WEB SOIL SURVEY: usda.gov/app/HomePage.htm ical/classification/scfile/index. html Module 6

Learn More Videos that show watershed delineation, and measuring some of the watershed characteristics. Module 6

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. Module 6

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. Module 6

Regression Equations in Texas 1977 Massey and Schroeder (1977) USGS Water Resources Investigations 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 Module 6

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 Module 6

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 Module 6

MAP Module 6

OmegaEM

Regression Equations in Texas 2009 Asquith and Roussel, Texas Regression Module 6

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. Module 6