Clusterization of Surface Water Quality and Its Relation to Climate and Land Use/Cover

Abstract

The quality of surface water is rapidly changing due to climatic variations, natural processes, and anthropogenic activities. The objectives of this study were to classify and analyze the surface water quality of 12 major rivers of Alberta on the basis of 17 parameters during the period of five years (i.e., 2004-2008) using principal component analysis (PCA), total exceedance model and clustering technique. Seven major principal components (PCs) with variability of about 89% were identified. These PCs were the indicators of watershed geology, mineralization and anthropogenic activities related to land use/cover. The seven dominant parameters revealed from the seven PCs were total dissolved solids (TDS), true color (TC), pH, iron (Fe), fecal coliform (FC), dissolved oxygen (DO), and turbidity (TUR). The normalized data of dominant parameters were used to develop a model for obtaining total exceedance. The exceedance values acquired from the total exceedance model were used to determine the patterns for the development of five clusters. The performance of the clusters was compared with the classes obtained in Canadian Water Quality Index (CWQI). Cluster 1, cluster 2, cluster 3, cluster 4 and cluster 5 showed agreements of 85.71%, 83.54%, 90.22%, 80.74%, and 83.40% with their respective CWQI classes on the basis of the data for all rivers during [2004][2005][2006][2007][2008]. The water quality was deteriorated in growing season due to snow melting. This methodology could be applied to classify the raw surface water quality, analyze the spatio-temporal trends and study the impacts of the factors affecting the water quality anywhere in the world.

Riverine Water Quality Response to Precipitation and Its Change

“…The elevated concentrations of the pollutant constituents associated with particulate solids (e.g., TURB) or attached to particulate solids (e.g., TP) in water bodies can be ascribed to their wash-off (mobilization and transport) from non-point source pollutants accumulated on land surface by surface runoff generated from precipitation. Same results were obtained in studies by Budai and Clement [39] and by Akbar et al [40] in Alberta rivers. A study by Delpla et al [27] also showed that DOC is also transported from soil to rivers during rainfall events from watersheds consisting of agricultural land.…”

“…The land use and/or the anthropogenic interference present variation, which could result in the variations of point and non-point source contributions along a river, might explain the spatial variation of precipitation response of water quality. The impact of land use/cover on water quality of Alberta's rivers have been confirmed in the most recent studies [40,41].…”

Development of Remote Sensing Based Models for Surface Water Quality

“…>50 NTU). The variation in the water quality for different years could be related to surface runoff from different amount of precipitations due to climatic factors like snowmelt and rainfall [6]. The impact of natural sub-regions was reflected on the river water quality classification in Tab.…”

“…During the growing season, the snowmelt wash various materials from the land surface into the rivers due to anthropogenic activities related to different types of land use/cover. Turbidity was found to be a dominant parameter associated with the deterioration in water quality during the growing season . On this basis, we considered turbidity separately besides CWQI in this study.…”

“…80–90%) against the classes of CWQI. The dominant clusters during the growing and winter seasons were used for the spatial and temporal patterns of the surface water quality of rivers .…”