Formulation and use of practical models for river-quality assessment

Abstract

ENVIRONMENTAL AWARENESS and new laws such as pl 92-500 have estab lished improved river quality as a major goal of overall river basin planning. River quality may be defined as the physical, chemical and biological character of a river with regard to its suitability for a specified purpose. In this context, river quality con cerns not only the observed quality of water in a river, but also implies a con sideration of the causative phenomena, in cluding environmental processes occurring on land, water, and in air, that are respon sible for the observed quality. To achieve improved river quality with a minimum of environmental, social, and economic cost, it is imperative that basin planning decisions and. the need for river quality management facilities be based on scientific assessment rather than on arbi trary edicts and assumptions. Thus, the objective of river quality assessment is to evaluate, before the fact, the beneficial or adverse environmental impacts of planning alternatives on the quality of the river. Once the environmental impacts have been examined, social and economic costs may be weighed and compared for each plan ning alternative. The complexities inherent in the scientific study of large rivers, coupled with the need for quantitative description of river quality behavior, have created great interest in mathematical models (referred to hereafter as river quality models) as tools for simu lating the response of river quality vari ables to alternative basin planning pro posals. The study of dissolved oxygen (do)-biochemical oxygen demand (bod) relationships by Streeter and Phelps1 is generally considered to be the pioneering effort in applied river quality modeling. Although do continues to be the subject of a majority of river quality models, other variables and processes are receiving in creasing attention. The subjects range in complexity from relatively simple variables such as temperature to highly complex, long-term processes such as eutrophication (Figure 1). In concept, river quality models provide a great potential for problem solving to resource planners and managers, pollution control officers, and government decision makers. In general, however, this group has not only failed to accept river quality models as a practical tool, but often views mathematical modeling with considerable mistrust. The authors have concluded that this failure to accept and trust models stems from the fact that many river quality models have not been formulated on the basis of sound data nor effectively applied to planning and management situations. Similar conclusions have been cited by several other investigators, including Mar,2 Lombardo,3 Weber et al.* and Velz.5