From Design to Application of a Decision-support System for Integrated River-basin Management

Jean-Luc de Kok 0 1 2 3 4 Sebastian Kofalk 0 1 2 3 4 Jrgen Berlekamp 0 1 2 3 4 Bernhard Hahn 0 1 2 3 4 Herman Wind 0 1 2 3 4 0 S. Kofalk German Federal Institute of Hydrology (BfG) , PO Box 200253, 56002 Koblenz, Germany 1 J.-L. de Kok Water Engineering & Management Group, University of Twente , PO Box 217, 7500 AE, Enschede, The Netherlands 2 H. Wind Infram, PO Box 16, 8316 ZG, Marknesse, The Netherlands 3 B. Hahn Research Institute of Knowledge Systems , PO Box 463, 6200 AL , Maastricht, The Netherlands 4 J. Berlekamp Institute for Environmental Systems Research, Department of Mathematics and Computer Science, University of Osnabrck , 49076 Osnabrck, Germany During the last two decades several integrated tools have been developed to make the existing scientific knowledge available to river managers and assist them with the formulation and evaluation of alternative combinations of measures. Yet, few practical examples of embedding of these instruments in river management organizations can be observed so far. This paper identifies the possible organizational, technical, and scientific factors that may form an obstacle for the design and application of a Decision-Support System (DSS) for river-basin management by analyzing the interaction between the different participants in the Elbe DSS - project. In particular attention is paid to the software engineering aspects of the design process. In order to start an integrated approach to deal with conflicting river strategies a project to develop a prototype tool for integrated management of the Elbe catchment was initiated, which includes functionalities related to inland navigation, water quality, flood safety, and vegetation ecology. The problems faced in the German part of the Elbe catchment range from poor navigation conditions and flooding vulnerability to a need to restore and maintain the natural state of the floodplains. Several river engineering works such as large-scale dike shifting, channel dredging, and large-scale retention are in a planning or implementation stage. From the beginning of the project onwards attention was paid to the involvement of potential end-users and key stakeholders in the design process. The experience of the project is that internal consistency of models and data, effective communication, and functional flexibility are essential to warrant a proper balance between scientific standards, the availability of models, and the requirements of users. This facilitates the design process and improves the chance of successful implementation. 1 Introduction With the adoption of the EU Water Framework Directive (EU 2000; Moss 2004) all European countries have committed themselves to a river-basin approach. The formulation and implementation of Integrated River Basin Management (IRBM) strategies in accordance with both the national legislation and the EU directive is not a straightforward task. Finding a proper balance between the interests of different stakeholders requires understanding the effects of combined measures on multiple river functions. Uncertain future conditions related to, for example, changing political priorities, economic development and climate change, influence the outcome of proposed alternatives, and thereby their ranking. Although the decisions are inherently a political matter there is a growing awareness that plans need scientific underpinning and the support of local stakeholders prior to implementation. To help bridge the gap between the scientific knowledge and demand for information it is desirable to combine a wide range of expertise and data and make it available for the analysis and presentation of promising strategies for IRBM. A DSS for river basin management enablesfor different scenariosthe comparison of river strategies based on the effects on multiple objectives. It can be used to support the planning and implementation of measures (Giupponi 2007; Volk et al. 2007) and the communication between the stakeholders and between the researchers involved. The different purposes of a DSS for IRBM include: analysis of different management alternatives, communication, education, and knowledge management (Loucks 1995; Hahn and Engelen 2000; Zhu and Dale 2000; Westmacott 2001; De Kok and Wind 2003; Legris et al. 2003; Maurel et al. 2007; Giupponi 2007). During the last decades a variety of tools were developed to assist water managers with strategic planning tasks (Berlekamp et al. 2005; Giupponi 2007). Many of these instruments take an integrated perspective on problems by combining scientific knowledge from multiple disciplines to understand the relevant processes and effects of different combinations of measures. Recently, some interesting examples were presented of the crosslinkage between process analysis and software design of a DSS for IRBM (Castelletti and Soncini-Sessa 2007; Castelletti et al. 2007; Dietrich et al. 2007). Despite of the involvement of potential users during the design and effort spent on generic frameworks for integrated water management (Van Waveren et al. 1999; Mysiak et al. 2005; Refsgaard et al. 2005; Giupponi et al. 2007; Scholten et al. 2007) there are still few practical examples of river organizations that use these instruments for policy analysis and communication purposes (Gourbesville 2008). Walker (2002) examined the failure of decision-support projects in the field of rural resource management and attributes the lack of acceptation of DSS by users to inflexibility, inaccessibility, irrelevance of the instruments, a lack of confidence, or institutional and political barriers. Many of these problems have been reported elsewhere in the literature (Ubbels and Verhallen 2000; Westmacott 2001; De Kok and Wind 2003; Legris et al. 2003; Uran and Janssen 2003; Mysiak et al. 2005; Borowski and Hare 2007; Brugnach et al. 2007; Olsson and Andersson 2007) in one form or another and were also experienced with the development of a pilot DSS for the Elbe river. Here, the different roles and interaction of all participants in DSS design are examined in detail for a concrete case study in order to arrive at practical guidelines for the complete DSS life cycle. In particular attention is paid to the software engineering aspects of the design process. The paper is organized as follows. To provide a basis for the user perspective Section 2 analyzes the potential role of a DSS to support decision making related to integrated river-basin management. Section 3 describes the design process and structure of the Elbe-DSS in more detail. Section 4 discusses the procedural and technical aspects of the software engineering approach that was followed to design the DSS in comparison to other approaches. Section 5 takes the design history of two key components of the DSS, the risk assessment model (De Kok and Huang 2005) and point-source pollution model GREAT-ER (Matthies et al. 2001; Berlekamp et al. 2007), to illustrate the problems that can be experienced wh (...truncated)