An Analysis of Spatiotemporal Variations of Water Quality in the Little River Watershed and Their Connection with Land-cover Patterns

An Analysis of Spatiotemporal Variations of Water Quality in the Little River Watershed and Their Connection with Land-cover Patterns
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Total Pages : 119
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ISBN-10 : OCLC:440685493
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Download or read book An Analysis of Spatiotemporal Variations of Water Quality in the Little River Watershed and Their Connection with Land-cover Patterns written by and published by . This book was released on 2008 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Little River supplies drinking water to Blount County, Tennessee, and supports several state and federally listed species. The upper, southeastern area of the Little River watershed is fed by protected sources originating in the Great Smoky Mountains National Park. In the lower, northwestern part, however, the watershed has been affected by anthropogenic land-cover and land-cover change in recent years. These changes may have impacted water quality in the Little River watershed over the past 20 years. The objectives of this study were: (1) to elucidate the spatiotemporal patterns of water quality, (2) to understand the Little River watershed's land-cover patterns, and (3) to quantify the relationships between land-cover patterns and water quality. Existing water quality data for the past 20 years from different sources were compiled and analyzed using multivariate statistical analysis. Principal component analysis (PCA) was used to identify the associations among water quality parameters. Cluster analysis (CA) was used to group sampling sites with respect to water quality pattern. Discriminant analysis (DA) was used to identify which water quality indicators best represent the differences between the clusters derived from CA. Land-cover data were analyzed to determine types and proportions of different land-cover types upstream from water quality sampling sites. The results of the analyses were visualized using Geographic Information Systems (GIS). The results show that specific conductance, turbidity, and ammonia nitrogen best reflect the processes influencing data set variability (dissolved solids, seasonal influences, and nutrients, respectively). The results also suggest that water quality differs between samples from the upper and lower parts of the watershed and that the four parameters dissolved oxygen, total phosphorus, ammonia nitrogen, and total suspended solids define spatial groups of sample sites with similar water qualities. There is a spatial relationship between patterns of land cover and patterns of water quality. Higher proportions of anthropogenic land cover (e.g., urban) occur within the same sub-watershed as degraded water quality measures. The results suggest that anthropogenic land cover influences spatial variations of water quality in the Little River.


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