Groupwise modeling study of bacterially impaired watersheds in Texas: Clustering analysis

被引:13
作者
Paul, Sabu
Srinivasan, Raghavan
Sanabria, Joaquin
Haan, Patricia K.
Mukhtar, Saqib
Neimann, Kerry
机构
[1] Tetra Tech Inc, Fairfax, VA 22030 USA
[2] Texas Agr Expt Stn, Spatial Sci Lab, College Stn, TX 77845 USA
[3] Texas A&M Univ Syst, Blackland Res Ctr, Temple, TX 76502 USA
[4] Texas A&M Univ, Dept Biol & Agr Engn, College Stn, TX 77843 USA
[5] Texas Commiss Environm Qual, Austin, TX 78753 USA
来源
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION | 2006年 / 42卷 / 04期
关键词
nonpoint source pollution; water quality; statistical analysis; total maximum daily load (TMDL); coliform bacteria; cluster analysis;
D O I
10.1111/j.1752-1688.2006.tb04511.x
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Under the Clean Water Act (CWA) program, the Texas Commission on Environmental Quality (TCEQ) listed 110 stream segments in the year 2000 with pathogenic bacteria impairment. A study was conducted to evaluate the probable sources of pollution and characterize the watersheds associated with these impaired water bodies. The primary aim of the study was to group the water bodies into clusters having similar watershed characteristics and to examine the possibility of studying them as a group by choosing models for total maximum daily load (TMDL) development based on their characteristics. This approach will help to identify possible sources and determine appropriate models and hence reduce the number of required TMDL studies. This in turn will help in reducing the effort required to restore the health of the impaired water bodies in Texas. The main characteristics considered for the classification of water bodies were land use distribution within the watershed, density of stream network, average distance of land of a particular use to the closest stream, household population, density of on-site sewage facilities (OSSFs), bacterial loading from different types of farm animals and wildlife, and average climatic conditions. The climatic data and observed instream fecal coliform bacteria concentrations were analyzed to evaluate seasonal variability of instream water quality. The grouping of water bodies was carried out using the multivariate statistical techniques of factor analysis/principal component analysis, cluster analysis, and discriminant analysis. The multivariate statistical analysis resulted in six clusters of water bodies. The main factors that differentiated the clusters were found to be bacterial contribution from farm animals and wildlife, density of OSSFs, density of households connected to public sewers, and land use distribution.
引用
收藏
页码:1017 / 1031
页数:15
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