Screening robust water infrastructure investments and their trade-offs under global change: A London Example

We propose an approach for screening future infrastructure and demand management investments for large water supply systems subject to uncertain future conditions. The approach is demonstrated using the London water supply system. Promising portfolios of interventions (e.g., new supplies, water conservation schemes, etc.) that meet London’s estimated water supply demands in 2035 are shown to face significant trade-offs between financial, engineering and environmental measures of performance. Robust portfolios are identified by contrasting the multi-objective results attained for (1) historically observed baseline conditions versus (2) future global change scenarios. An ensemble of global change scenarios is computed using climate change impacted hydrological flows, plausible water demands, environmentally motivated abstraction reductions, and future energy prices. The proposed multi-scenario trade-off analysis screens for robust investments that provide benefits over a wide range of futures, including those with little change. Our results suggest that 60 percent of intervention portfolios identified as Pareto optimal under historical conditions would fail under future scenarios considered relevant by stakeholders. Those that are able to maintain good performance under historical conditions can no longer be considered to perform optimally under future scenarios. The individual investment options differ significantly in their ability to cope with varying conditions. Visualizing the individual infrastructure and demand management interventions implemented in the Pareto optimal portfolios in multi-dimensional space aids the exploration of how the interventions affect the robustness and performance of the system.

[1]  D. Wheatley Water in life , 1993, Nature.

[2]  S. Jackson,et al.  Principles and guidelines for good practice in Indigenous engagement in water planning , 2012 .

[3]  D. Finegold Book and Resource Reviews , 2005 .

[4]  Andrea Castelletti,et al.  Many‐objective reservoir policy identification and refinement to reduce policy inertia and myopia in water management , 2014 .

[5]  M. Hulme,et al.  Assessing the robustness of adaptation decisions to climate change uncertainties: A case study on water resources management in the East of England , 2007 .

[6]  Jonathan D. Herman,et al.  How should robustness be defined for water systems planning under change , 2015 .

[7]  Avi Ostfeld,et al.  State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management , 2010 .

[8]  Wolfgang Rauch,et al.  Exploring critical pathways for urban water management to identify robust strategies under deep uncertainties. , 2014, Water research.

[9]  Matthew D. Collins,et al.  UK Climate Projections Science Report: Climate Change Projections , 2009 .

[10]  Jery R. Stedinger,et al.  Water Resources Systems Planning And Management , 2006 .

[11]  Joseph R. Kasprzyk,et al.  Many-objective optimization and visual analytics reveal key trade-offs for London's water supply , 2015 .

[12]  G. Meehl,et al.  Near-term climate change:projections and predictability , 2013 .

[13]  D. H. Marks,et al.  A review and evaluation of multiobjective programing techniques , 1975 .

[14]  Avi Ostfeld,et al.  Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions , 2014, Environ. Model. Softw..

[15]  Claudio Arena,et al.  A simulation/optimization model for selecting infrastructure alternatives in complex water resource systems. , 2010, Water science and technology : a journal of the International Association on Water Pollution Research.

[16]  Joseph R. Kasprzyk,et al.  Many objective robust decision making for complex environmental systems undergoing change , 2012, Environ. Model. Softw..

[17]  J. Harou,et al.  Selecting Portfolios of Water Supply and Demand Management Strategies Under Uncertainty—Contrasting Economic Optimisation and ‘Robust Decision Making’ Approaches , 2013, Water Resources Management.

[18]  Patrick M. Reed,et al.  Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design , 2005 .

[19]  Stephane Hallegatte,et al.  Strategies to adapt to an uncertain climate change , 2008 .

[20]  M. Holland,et al.  Near-term climate change:Projections and predictability , 2014 .

[21]  Holger R. Maier,et al.  Adaptive, multiobjective optimal sequencing approach for urban water supply augmentation under deep uncertainty , 2015 .

[22]  David E. Rosenberg,et al.  Blended near‐optimal alternative generation, visualization, and interaction for water resources decision making , 2015 .

[23]  P. Reed,et al.  Managing population and drought risks using many‐objective water portfolio planning under uncertainty , 2009 .

[24]  B. Vogel,et al.  Studying local climate adaptation: A heuristic research framework for comparative policy analysis , 2015 .

[25]  E. D. Brill,et al.  Modeling to Generate Alternatives: The HSJ Approach and an Illustration Using a Problem in Land Use Planning , 1982 .

[26]  R. Wilby,et al.  A framework for assessing uncertainties in climate change impacts: Low‐flow scenarios for the River Thames, UK , 2006 .

[27]  George Kuczera,et al.  Optimizing Urban Water Supply Headworks Using Probabilistic Search Methods , 2003 .

[28]  Li Chen,et al.  Optimizing the reservoir operating rule curves by genetic algorithms , 2005 .

[29]  P. Reed,et al.  Navigating financial and supply reliability tradeoffs in regional drought management portfolios , 2014 .

[30]  L. Papageorgiou,et al.  Least Economic Cost Regional Water Supply Planning – Optimising Infrastructure Investments and Demand Management for South East England’s 17.6 Million People , 2013, Water Resources Management.

[31]  Patrick S. Garrison State of California The Resources Agency , 2002 .

[32]  Daniel P. Loucks,et al.  A computationally efficient open-source water resource system simulator - Application to London and the Thames Basin , 2011, Environ. Model. Softw..

[33]  Li-Chiu Chang,et al.  Multi-objective evolutionary algorithm for operating parallel reservoir system , 2009 .

[34]  A. Deletic,et al.  Diagnosing transformative change in urban water systems: Theories and frameworks , 2013 .

[35]  Yakov Ben-Haim,et al.  Robust rationality and decisions under severe uncertainty , 2000, J. Frankl. Inst..

[36]  Olive Heffernan Adapting to a warmer world: No going back , 2012, Nature.

[37]  Wei-Chen Cheng,et al.  Optimization and capacity expansion of a water distribution system , 2008 .

[38]  Julien J. Harou,et al.  Using many-objective trade-off analysis to help dams promote economic development, protect the poor and enhance ecological health , 2014 .

[39]  George Kuczera,et al.  Multiobjective optimization of urban water resources: Moving toward more practical solutions , 2012 .

[40]  Per Ole Iversen,et al.  [Water--for life]. , 2003, Tidsskrift for den Norske laegeforening : tidsskrift for praktisk medicin, ny raekke.

[41]  Allan McConnell Policy Success, Policy Failure and Grey Areas In-Between , 2010 .

[42]  F. Knight The economic nature of the firm: From Risk, Uncertainty, and Profit , 2009 .

[43]  Nigel W. Arnell,et al.  Adapting to climate change impacts on water resources in England—An assessment of draft Water Resources Management Plans , 2011 .

[44]  Ben Gouldby,et al.  Adaptive Flood Risk Management Under Climate Change Uncertainty Using Real Options and Optimization , 2014, Risk analysis : an official publication of the Society for Risk Analysis.

[45]  George Kuczera,et al.  Optimizing water supply headworks operating rules under stochastic inputs: Assessment of genetic algorithm performance , 2005 .

[46]  Warren E. Walker,et al.  Developing dynamic adaptive policy pathways: a computer-assisted approach for developing adaptive strategies for a deeply uncertain world , 2015, Climatic Change.

[47]  François Bousquet,et al.  Modelling with stakeholders , 2010, Environ. Model. Softw..

[48]  Julie Brown,et al.  Benchmarking sustainability in cities: The role of indicators and future scenarios , 2012 .

[49]  J. Hall,et al.  Risk‐based water resources planning: Incorporating probabilistic nonstationary climate uncertainties , 2014 .

[50]  Andrew Barkwith,et al.  Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain , 2013 .

[51]  Gary B. Lamont,et al.  Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.

[52]  Warren E. Walker,et al.  Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world , 2013 .

[53]  Pamela S. Naden,et al.  CLASSIC: a semi-distributed rainfall-runoff modelling system , 2007 .

[54]  Jan H. Kwakkel,et al.  An exploratory approach for adaptive policymaking by using multi-objective robust optimization , 2014, Simul. Model. Pract. Theory.

[55]  Joseph R. Kasprzyk,et al.  Evolutionary multiobjective optimization in water resources: The past, present, and future , 2012 .

[56]  Julien J. Harou,et al.  Robust Decision Making and Info-Gap Decision Theory for water resource system planning , 2013 .

[57]  Joseph R. Kasprzyk,et al.  Many-objective de Novo water supply portfolio planning under deep uncertainty , 2012, Environ. Model. Softw..

[58]  Michael Frankfurter,et al.  Water Resources Systems Planning And Management , 2016 .

[59]  Warren E. Walker,et al.  Adapt or Perish: A Review of Planning Approaches for Adaptation under Deep Uncertainty , 2013 .

[60]  P. Reed,et al.  Beyond optimality: Multistakeholder robustness tradeoffs for regional water portfolio planning under deep uncertainty , 2014 .

[61]  David King,et al.  Involving stakeholders in integrated river basin planning in England and Wales , 2006 .

[62]  C. Pahl-Wostl,et al.  A conceptual framework for analysing adaptive capacity and multi-level learning processes in resource governance regimes , 2009 .

[63]  S. Merrett,et al.  The Thames catchment : a river basin at the tipping point , 2007 .