Water resource managers are required to develop comprehensive water resources plans based on severely uncertain information of the effects of climate change on local hydrology and future socio-economic changes on localised demand. In England and Wales, current water resources planning methodologies include a headroom estimation process separate from water resource simulation modelling. This process quantifies uncertainty based on only one point of an assumed range of deviations from the expected climate and projected demand 25 years into the future. This paper utilises an integrated method based on Information-Gap decision theory to quantitatively assess the robustness of various supply side and demand side management options over a broad range of plausible futures. Findings show that beyond the uncertainty range explored with the headroom method, a preference reversal can occur, i.e. some management options that underperform at lower uncertainties, outperform at higher levels of uncertainty. This study also shows that when 50 % or more of the population adopts demand side management, efficiency related measures and innovative options such as rainwater collection can perform equally well or better than some supply side options The additional use of Multi-Criteria Decision Analysis shifts the focus away from reservoir expansion options, that perform best in regards to water availability, to combined strategies that include innovative demand side management actions of rainwater collection and greywater reuse as well efficiency measures and additional regional transfers. This paper illustrates how an Information-Gap based approach can offer a comprehensive picture of Water Resour Manage (2013)
Urban emissions represent approximately 40% of Canada's current GHG emissions and the need to implement Integrated Community Energy Solutions (ICES) is now broadly recognized. A more consistent approach for characterizing energy and emissions opportunities in communities and the provision of more accurate and comprehensive information to planning processes is required. Integrated Community Energy Models (ICEMs) employ Geographical Information Systems (GIS) to integrate spatial information on a community's land use, building stock, transportation and energy systems and socioeconomic characteristics. Using future scenarios, ICEMs support the prioritization of opportunities for energy efficiency and renewable and district technology integration, better enabling planning, policy development and investment decisions. This paper describes organizations forwarding ICES and ICEM development and selected enabling provincial legislation. Three case-studies are presented: the Energy Density Mapping Strategy for the cities of Guelph and Hamilton, Ontario, the Spatial Community Energy Carbon and Cost Characterization (SCEC 3) model for the City of Prince George, British Columbia and the Energy Asset Mapping project in the Strait-Highlands Region, Nova Scotia. For each, core model aspects, required data, highlighted results and their integration into community planning processes are discussed. The article concludes with next steps for implementation and future research and development of ICEMs in Canada.
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