Potential of Modern Data Types for Future Water Resources Management

Abstract

Presently a change of paradigm in the field of planning and operation of water management schemes can be observed. The introduction of the principle of sustainable development by the United Nations and the principle of integrated river basin management postulated by the European Union play a major role in this context. Introduction of these new principles requires development of new planning tools, which in turn require a much better data basis than available hitherto. This paper deals with new data types already partly available now, partly to be expected to be developed in the medium-range future. The present data situation is discussed, along with the obvious deficits of conventional data. New data types will not be limited to point measurements, but rather must comprise information covering large areas with a higher resolution in time and space than presently available. Remote sensing data will play a more important role in the future. Furthermore, digital maps, digital elevation models, etc. are also of growing importance and will be processed, together with remote sensing and other data, within Geographical Information Systems of future generations also exposing the potential for working with multi-temporal imagery. In the paper it is shown that in the future more accurate data will be available, not only in terms of data quality, but also resolution in time and space. It is shown how the new types of hydrometeorological data postulate new types of hydrological models. Here, distributed system models are of growing importance. Furthermore, it is shown how the combination of remote sensing with other information leads to new data types that allow integrated planning of water resources systems. The potential of real time data is highlighted, particularly in the context of real time operation of water resources systems, especially for flood control. The potential of large-scale data schemes in the context of regional and continental water management schemes is discussed. Global atmospheric models coupled to hydrological models are discussed, and their potential to consider long-distance effects of certain phenomena (e.g., El Niño) are mentioned. For sustainable development of water resources, the potential of long-term data prediction scenarios is evaluated, and an example of this principle for planning future water supply systems is presented. The paper ends with a vision of future developments in planning water management schemes on the basis of new data types     

A Comparison of Modelling Systems for the Development and Revision of Water Resources Management Plans

In this paper, two modelling systems used for the simulation of water resources management are compared. These modelling systems can be used in the implementation of the European Water Framework Directive or to perform any other kind of integrated assessment with regard to water resources management. In such investigations the use of models is inevitable, as integrated water resources management demands the survey of large areas as well as the inclusion of the different functions of the water cycle and water utilisation processes. Water quantity data provides important input for hydro-chemical, hydro-ecological or hydro-economic models. If no significant water resources management activities are realised in the basin under study, these data can be provided by simple rainfall-runoff models. If significant water resources management activities are realised or planned, the effects of these water resources management activities must be taken into consideration. Then, however, the use of water resources management models becomes necessary. Two such modelling systems, WRAP and WBalMo, are compared. Both have been designed for the development and revision of water resources management plans. Due to different approaches regarding the modelling routines the models lead to different results in the calculation of water quantities. By tracking the simulation algorithms, an understanding of the detected differences becomes possible. By adapting the spatial configuration of the modelled system, equivalent results can be obtained.