Development of Methodologies for Improving Water Quality Management

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Heightened concerns over water quality and ecosystem degradation have led to increased interest in water quality management. Broadly speaking, the overall objective of water quality management is to maintain or improve the existing condition of water bodies, thereby providing quality water for potable consumption, irrigation, and industrial and recreational uses. In rivers, two types of major factors: natural environmental factors and human-induced changes (e.g. changes in land use and climate), considerably influence surface water quality. In particular, the natural processes, such as hydrological and meteorological processes, which are also affected by human activities, play a significant role in the variability of surface water quality. Furthermore, the factors that govern natural processes are highly variable throughout the year and from one year to the next. The complex combination of a variety of different variable processes consequently results in distinct mechanisms that substantially alter water quality. Correct identification and sufficient understanding of these highly variable and interlinked processes are of crucial importance to successful water quality management. It is, however, a great challenge to appropriately account for the varying roles of the key influencing factors in water quality statistical analysis and modeling that can assist practitioners in making proper management decisions. Research on new approaches, where the varying roles of the influencing factors are explicitly considered and integrated in management strategies, would hence provide a significant and valuable contribution towards developing more responsible and effective water quality management. This research attempts to uncover what and how environmental factors as well as anthropogenic activities affect water quality in a quantitative way. New approaches will be developed to take into account the interconnections between water quality and its key influencing factors into the statistical analysis of water quality data. As a result, the spatial and temporal variations of water quality under the influence of multiple interacting factors will be quantitatively delineated in a multivariate setting. The role of the key influencing factors will subsequently be incorporated into developing a better-informed water quality management to identify the disturbances that degrade water quality. Moreover, regime-based water quality models will be developed to predict the effects of given inputs of pollutants under varying environmental conditions. Hydrologically dependent pollutant loading management for point (e.g., effluent from wastewater treatment plants) and non-point (e.g., storm water runoff) sources of pollution will also be developed to account for the assimilation capacity of streams under varying flow conditions. The proposed research program will result in methods and techniques that will help strengthening our understanding of the interrelationship between various key factors and water quality variations. The developed approaches for quantitatively measuring the effects of these factors on water quality will present a viable path to correctly explain the complex water quality phenomena. Furthermore, the integration of the roles of these factors into management practices will be essential for establishing more responsible and cost-effective water quality management.