Aspects of present hydrological and water quality modelling

Recently, efforts have increased in Germany to follow international developments in water quality and hydrology modelling. The authors were asked to analyze and report on existing models in order to summarize the “state of the art” of concepts and applications in this field. Some of the conclusions from their report are presented here. Information for the study was obtained from publications, project reports, personal interviews and discussions. Some of the models or model concepts were tested at the two institutes involved in this study. Of all the models investigated, 41 from 11 different countries were examined more closely, 20 of them emphasizing hydrological aspects, 18 focussing upon water quality and 3 incorporating both hydrology and quality. A large amount of material was accumulated during the study. Accordingly, some general principles of model analysis for comparison and presentation were established. So-called “macro-elements”, comprising input, systems analysis formulation, algorithm and output, were identified. In addition, “micro-elements” were defined, denoting typical analytical units within the models, which helped to classify the models. In part A of the report, focussing upon hydrological models, three model classes were introduced according to the purpose, data requirements and model structures, viz.: computation of runoff data; optimal operation of regional water resources systems; and optimization of the design of hydraulic structures. Similarly, about 53 micro-elements were identified and subdivided into three groups: input information for hydrological models; formation of runoff processes; and system analysis formulation. Analysis of the hydrological models yielded some general observations including the following. The degree of mathematical sophistication is controlled by the available data; there is a limited number of recurring model elements; the interaction between surface and groundwater is poorly treated; and in most hydrological models environmental and economic aspects are neglected. Only a few models were equally devoted to water quality and quantity. Part B focussed upon water quality modelling, which has obtained significant impetus in the wake of increasing environmental concern. The more traditional approach of a descriptive analysis of the self-purification processes in rivers was explored in several directions, denoted by the key words: data fitting of lump-sum observations, detailed empirical formulation of processes, food-chain simulation, and stochastic water quality analysis. The need to derive planning decisions based upon complementary optimization concepts led to a reduced complexity of quality models which is also in accordance with the data availability and with the sensitivity of the model with respect to planning objectives. Objective functions are favourably stated in terms of costs, though it appears desirable to include explicitly the benefits generated by improved water quality. The evaluation and scaling of benefits in economic terms is highly controversial. Formal optimization routines employed in quality control emphasize linear, mixed-integer and dynamic programming. The trend also shows a desirable feedback between optimization and simulation. In particular, dynamic and non-steady-state conditions cannot be treated using formal optimization and have to be supplemented by simulation. In summary, mathematical modelling of hydrological and water quality phenomena has become an indispensable tool for environmental control and enhancement.