Development of Methodologies for Improving Water Quality Management

对水质和生态系统退化的高度关注导致人们对水质管理的兴趣增加。概括而言，水质管理的整体目标是维持或改善水体的现有状况，从而为饮用、灌溉、工业和康乐用途提供优质水。 在河流中，有两类主要因素：自然环境因素和人为变化（如土地使用和气候变化），对地表水质量有很大影响。特别是，自然过程，如水文和气象过程，也受到人类活动的影响，在地表水质量的变化中发挥重要作用。此外，支配自然过程的因素在一年中以及从一年到下一年都是高度可变的。因此，各种不同的可变过程的复杂组合产生了显著改变水质的独特机制。* 正确识别和充分了解这些高度可变和相互关联的过程是至关重要的成功的水质管理。然而，这是一个很大的挑战，以适当地占水质统计分析和建模，可以帮助从业人员在作出适当的管理决策的关键影响因素的不同作用。因此，研究新的方法，明确考虑到影响因素的不同作用并将其纳入管理战略，将为制定更负责任和更有效的水质管理做出重大和宝贵的贡献。 本研究试图以定量的方式揭示环境因素以及人类活动对水质的影响。将制定新的方法，在水质数据的统计分析中考虑水质及其主要影响因素之间的相互关系。因此，水质的空间和时间变化的影响下，多个相互作用的因素将定量描绘在一个多元设置。关键影响因素的作用随后将纳入制定更知情的水质管理，以确定降低水质的干扰。此外，还将开发基于制度的水质模型，以预测特定污染物投入在不同环境条件下的影响。点的水文依赖污染物负荷管理（例如，来自废水处理厂的流出物）和非点源（例如，还将研究污染源，以说明河流在不同流量条件下的同化能力。 拟议的研究计划将导致方法和技术，这将有助于加强我们对各种关键因素和水质变化之间的相互关系的理解。定量测量这些因素对水质的影响的方法将为正确解释复杂的水质现象提供一条可行的途径。此外，将这些因素的作用纳入管理做法对于建立更负责任和成本效益更高的水质管理至关重要。

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.