Regional analysis of streamflow chemical quality in Texas

Abstract

Thirty‐one streamflow water quality stations in Texas, with long‐term historical records ranging from 7 to 28 years, were selected for statistical analyses of the annual mean concentrations of the major chemical constituents. A statewide multiple regression analysis using frequency characteristics of annual mean water quality constituents as dependent variables and selected basin characteristics as independent variables was investigated as a means of regionalizing information on annual water quality characteristics. For the two different regression models investigated, a single independent variable, generally stream discharge or average basin rainfall, explained a significant part of the variance of the dependent water quality variables. Areal analysis of residuals of the statewide regression models indicated two distinct regional patterns. Correlation coefficients for the concentration‐rainfall regional models ranged from 0.80 to 0.97 and the standard errors of estimate were between 26 and 99% of the means of the dependent variables. An analysis of various concentration‐conductance relationships for the statewide data also gave favorable results, and provided an alternate method for obtaining estimates of streamflow chemical quality characteristics.

Monitoring, assessment and modelling using water quality data in the Saale River Basin, Germany

“…Regarding water quality, indicator variables consist of specific conductance, nitrate concentration, and zinc concentration. Specific conductance commonly serves as a useful indicator of major ions (that is, calcium, magnesium, sodium, and potassium as cations and bicarbonate (alkalinity), sulphate, and chloride as anions) (Steele 1980;Steele and Jennings 1972).…”

A BIVARIATE-REGRESSION MODEL FOR ESTIMATING CHEMICAL COMPOSITION OF STREAMFLOW OR GROUNDWATER / Modèle de régression bivarié pour l'évaluation de la composition chimique de l'écoulement total ou des eaux souterraines

“…DISCUSSION AND SUMMARY As given in the case studies, graphic and regression analyses of chemical quality data serve as useful techniques for characterizing possible interrelationships between variable pairs and for assessing the feasibility of reduced data-collection strategies for providing continuing information on chemical quality conditions. Through resultant regression coefficients, techniques may be proposed for graphically depicting chemical quality conditions and regionalizing these coefficients with respect to basin characteristics, including quantification of lithological regimes in a catchment (Steele and Jennings, 1972). Much additional research should be carried out in this area.…”

“…In practice, bivariate-regression models are commonly found to apply, the regression coefficients of which may be determined at a sampling site from detailed historical data at that site or estimated using regionalization (Steele, 1971;Steele and Jennings, 1972). Specific conductance is preferred to stream discharge as the independent variable because the former is an inherent measure of ionic activity of an aqueous solution (Steele, 1970).…”

Regional analysis of the effects of land use on stream-water quality; methodology and application in the Susquehanna River Basin, Pennsylvania and New York

“…) Similar studies have related water-quality characteristics to basin characteristics. (See for example Branson and Owen, 1970;Flaxman, 1972;Hindall, 1976;and Steele and Jennings, 1972. ) The multiple-regression approach provides a means of estimating waterquality characteristics at unsampled stream sites and of estimating the general effects of natural and cultural aspects of drainage basins on water quality.…”