Thematic issue on evolutionary algorithms in water resources

Special Issue on Evolutionary Algorithms.H.R. Maier, Z. Kapelan, J. Kasprzyk, L.S. Matot

Sustainability assessment of housing developments : a new methodology

Afin de combattre la dégradation rapide des écosystèmes mondiaux ainsi que l'épuisement des ressources naturelles, les gouvernements et les autorités de planification recherchent des formes de développement plus durables. La nécessité d'évaluer la «soutenabilité» des propositions de développement est ainsi de grande importance pour la politique et les décideurs. Cependant, des méthodes efficaces pour évaluer la durabilité globale des développements de logement (proposés ou existants) ne sont pas encore établies. Les objectifs de ces recherches adressent ce problème en présentant une nouvelle méthodologie conçue pour évaluer la durabilité des systèmes complexes de développement de logement. Une méthode pour évaluer des indicateurs de durabilité sur une «échelle de soutenabilité», basée sur des centiles d'une population avec l'utilisation de ressource audessus d'un seuil soutenable, a été développée. Cette méthode a été couplée à une technique pour modéliser les systèmes de développement complexes de logement en utilisant la simulation multi-agent. La méthodologie a été mise en pratique dans un cas d'étude du groupe de logements, Christie Walk, situé au centre-ville d'Adélaïde en Australie. Les résultats de cette évaluation ont demontré que Christie Walk est plus soutenable que la plupart de la zone métropolitaine d'Adélaïde. Les resultats des analyses de scénario montrent aussi l'importance d'une bonne infrastructure et conception des développements pour réduire les impacts du comportement humain sur la durabilité des logements. On envisage que cette nouvelle méthodologie, qui couple l'évaluation de la durabilité avec une technique de modélisation integrée, fournira une base fondementale pour résoudre plusieurs des défis auxquels font actuellement face les chercheurs en développement durable, les décideurs et les autorités de planification des environnements urbains en Australie et dans le reste du monde. / In order to combat the rapid degradation of the world's ecosystems and depletion of natural resources, governments and planning authorities are searching for more sustainable forms of development. The need to assess the sustainability of development proposals is thus of great importance to policy and decision makers. However, effective methods of assessing the overall sustainability of housing developments (proposed or existing) have yet to be established. This research aims to address this problem by presenting a new methodology to assess the sustainability of housing development systems. The methodology uses indicators with a common Sustainability Scale which is derived from percentiles of a population with resource use above a predetermined sustainable level, and has been coupled with a technique for modelling complex housing development systems using multiagent based simulation. The methodology was shown to be operational in the case study application of the Christie Walk housing development in inner-city Adelaide, Australia. The results of the assessment showed that the development compared favourably to the rest of the Adelaide metropolitan area. The case study also highlighted, through behavioural scenario analyses, the importance of good infrastructure and design in reducing the impacts of human behaviour on housing development sustainability. It is envisaged that this new methodology of combining sustainability assessment with an integrated modelling technique will provide the basis for a solution to many of the challenges currently facing sustainability researchers, policy makers and planning authorities of urban environments both in Australia and world wide

A framework for engaging stakeholders in solving real-world water resources management problems

Multi-objective evolutionary algorithms (MOEAs) are becoming increasingly popular for solving environmental and water resources optimisation problems. In the past, the focus of these studies has generally been on methodological issues related to the optimisation algorithm, while the incorporation of stakeholder preferences in the MOEA solution process has largely been ignored. In recent years, there has been increased recognition of the need to apply these approaches to real-world problems to facilitate the realisation of their full potential. However, in most of these studies, stakeholder input was only used to direct the optimisation search process or select the final optimal solution(s), while the contribution of stakeholder input to other important components of the problem solving process was not considered. The reason for this is that the full consideration of stakeholder input in solving environmental and water resources optimisation problems requires the development of a more holistic approach, which involves a range of additional challenges. To address these challenges, a framework for including stakeholder input in real-world optimisation problems has been developed as part of the Optimal Water Resources Mix (OWRM) project initiated by the South Australian Government through the Goyder Institute for Water Research. The framework includes a conceptual framework (Figure 1) and a procedure for its implementation. The framework was applied to an urban water supply security study for Adelaide, South Australia. A summary of the framework and how it was implemented to identify optimal water sourcing options for the Adelaide case study is presented in this paper. This study highlights the important role of stakeholder input at the various stages of the problem formulation and optimisation process, analysis and results, although it can be expensive and time consuming to do so. It is recommended that adequate resources be made available for stakeholder engagement in project plans and budgets, as there needs to be clear and ongoing communication between stakeholder groups throughout the project. It also demonstrates that the use of MOEAs as the optimisation engine, together with appropriate stakeholder input, provides a combination that is well-suited to solving real-world water resources problems.W. Wu, H. R. Maier, G. C. Dandy, R. Leonard c, K. Bellette, S. M. Cuddy and S. Maheepal

Project Summary and Evaluation: GRUMP - Gawler River UNHARMED Mitigation Project

Hedwig van Delden, Roel Vanhout, Graeme Riddell, Elco Koks, Douglas Radford, Graeme C. Dandy, Eike Hamers, Holger R. Maier, Aaron C. Zecchi

Integrated Assessment of Flood Mitigation Options: GRUMP - Gawler River UNHARMED Mitigation Project

Hedwig van Delden, Roel Vanhout, Graeme Riddell, Elco Koks, Douglas Radford, Graeme C. Dandy, Eike Hamers, Holger R. Maier, Aaron C. Zecchi

Evaluation Document: GRUMP - Gawler River UNHARMED Mitigation Project

Hedwig van Delden, Roel Vanhout, Graeme Riddell, Elco Koks, Douglas Radford, Graeme C. Dandy, Eike Hamers, Holger R. Maier, Aaron C. Zecchi

Pathways Document for Integrated Flood Risk Management: GRUMP - Gawler River UNHARMED Mitigation Project

Hedwig van Delden, Roel Vanhout, Graeme Riddell, Elco Koks, Douglas Radford, Graeme C. Dandy, Eike Hamers, Holger R. Maier, Aaron C. Zecchi

Uncertainty, sensitivity and scenario analysis: how do they fit together?

Session J5. Advances and applications in decision making in the face of multiple plausible futuresDealing with uncertainty is becoming increasingly important in model-based decision support. Various methods have been developed in order to do this, including uncertainty, sensitivity and scenario analysis. Although these different methods serve their purpose, the availability of a large number of methods can make it difficult for practitioners to understand the similarities and differences between them and when the use of one is more suitable than another, resulting in confusion. In addition, researchers often identify with belonging to a group dealing with a particular approach, which can lead to a lack of crossfertilisation and understanding. In order to assist with bridging the gap between researchers working on different approaches to dealing with uncertainty and eliminate confusion for practitioners, the objective of this paper is to examine the relationship between uncertainty, sensitivity and scenario analysis in the context of model-based decision support, and to take the first steps towards establishing common ground between these methods and assess the contexts under which they are most suitable. This is achieved by conceptualising the various methods as different approaches to “sampling” the hyperspace of model inputs, although this is done from different perspectives and for different ends (Figure 1). It is therefore also necessary to think about the assumptions each method is making about the space being explored, and there are benefits to be gained in thinking about how best to sample the space for each purpose. The approaches identified in this conference paper provide a first level of coarse characterisations. Further refinements in categorisation is possible (with the differentiation between narrative and stress testing scenarios as a first example), and likely to be useful. There are connections to be made to other disciplines, such as philosophy and decision theory, regarding the assumptions each method makes.H.R. Maier, J.H.A. Guillaume, C. McPhail, S. Westra, J.H. Kwakkel, S. Razavi, H. van Delden, M.A. Thyer, S.A. Culley and A.J. Jakema

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Copyright © 2014 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Environmental Modelling and Software. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environmental Modelling and Software Vol. 62 (2014), DOI: 10.1016/j.envsoft.2014.09.013The development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g. model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts