Chapter 3 Decision Support Model (IUWS-DSM) - Tubdok

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Chapter 1 · General Introduction 5 50 years of researches result in that many different scientific branches of DSS have been developed and crossed over. Arnott and Pervan (2005) traced the evolution of the DSS field from its radical beginnings to a complex disciplinary structure of partially connected subfields (Figure 2). Figure 2: The evolution of the DSS field (Arnott and Pervan, 2005) Power (2004) categorised DSS into five broad groups: communications-driven, datadriven, document-driven, knowledge-driven and model-driven decision support systems. Especially, model-driven DSS use limited data and parameters provided by decision makers to aid decision makers in analyzing a situation, but in general large data bases are not needed for model-driven DSS (Power 2002), so it is chosen for building up our model. Regarding the generic architecture of DSS, Holsapple (2008) identified four essential components, i.e. 1. language system, 2. presentation system, 3. knowledge system, and 4. problem-processing system, which together structure the DSS. Subsequently, different types of DSS are derived (Figure 3).
6 New Conception and Decision Support Model for IUWS Figure 3: Basic architecture for decision support systems (Holsapple 2008) 1.2.2 Application to urban water systems In the last two decades, DSS have been applied to the urban water systems more and more. Poch et al. (2003) reported that more than 600 references related to environmental DSS are found in scientific literature since the 1990s, where 25% is about water management, 11% is connected to risk assessment. Initially, the focus lay on different branches, such as water demand prediction (e.g. An et al. 1996, Lertpalangsunti et al. 1999, Froukh 2001), water supply systems (e.g. Shepherd 1998, Davis 2000, Tillman et al. 2001), wastewater systems (e.g. Nemetz and Margolick 1984, Fenner and Sweeting 1999, Roda et al. 2000), and rainwater management (e.g. Kluck et al. 2005, Mbilinyi et al. 2005, Barraud et al. 1999). Later on, the water reuse was intensively in the focus, e.g. Ahmed et al. 2003, Dinesh and Dandy 2003, Sipala et al. 2003, Zhang 2004, and Joksimovic et al. 2006, etc. Recently, the total urban water systems as a whole are paid attention to and the corresponding DSS are investigated and developed. Cheng et al. (2003) developed an expert system with the purpose of improving the urban water quality and enhancing urban environment management. Starkl and Brunner (2004) scrutinized the decision making procedures in urban water management considering both water supply and wastewater disposal systems. Focusing on the hazardous substances, Malmqvist and Palmquist (2005) created one decision support tool for urban water and wastewater systems. By comparison, the DSS for the total urban water systems are still rare, which further promotes this research work.
Page 2 and 3: New Conception and Decision Support
Page 4 and 5: Acknowledgements By this chance, I
Page 6 and 7: Contents Indices I TABLES .........
Page 8 and 9: Indices III 3.6 Realisation Method
Page 10 and 11: Indices V Table 32: Sheet of averag
Page 12 and 13: Indices VII Figure 31: Cost estimat
Page 14 and 15: Definitions term definition & expla
Page 16: Abstract Indices XI Traditionally,
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Appendix.Figure 8: 3-D map of the c
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WUU WUC type area [ha] popul. [capi
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