@article{
 title = {Quantifying the influence of climate change to priorities for infrastructure projects},
 type = {article},
 year = {2014},
 identifiers = {[object Object]},
 keywords = {Deep uncertainty,infrastructure systems,risk analysis,robust decision making,transportation planning},
 volume = {44},
 id = {3ba75c96-3050-3f1b-aa48-ade3963e3f50},
 created = {2017-04-05T20:07:35.322Z},
 file_attached = {false},
 profile_id = {e8040203-c11c-3363-86bd-965654e2d309},
 last_modified = {2018-09-13T01:47:57.554Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 folder_uuids = {17293817-4518-4cc3-98b5-c3863056f0f3},
 private_publication = {false},
 abstract = {Uncertainties of climate change and other nonprobabilistic and structural uncertainties need to be addressed in strategic planning and priority setting for infrastructure systems. Traditional economic analysis and risk analysis of particular uncertainties can be prohibitive due to sparse data, complex models, and unforeseen interactions of climate change with other stressors. Nevertheless, planners need to proceed in the near term and may be asked to allocate resources to these deep uncertainties. This paper identifies and quantifies the influence of climate change combining with other sources of uncertainty to the priority order of projects in a portfolio of infrastructure investments. A demonstration for the Hampton Roads region of Virginia proceeds as follows. First, we apply traditional multicriteria analysis to generate a baseline prioritization of over 93 transportation projects. Next, we identify the following scenarios: climate conditions combined with economic conditions, wear and tear, ecological conditions, and traffic-demand conditions, and climate conditions alone. Next, we adjust a multicriteria value function for each scenario. We then quantify the sensitivity of the priority order of projects to the scenarios. Last, we identify the scenarios that are disruptive to the baseline prioritization. This approach is widely applicable to strategic planning for infrastructure systems that are subject to uncertainties of emergent and future conditions. © 2013 IEEE.},
 bibtype = {article},
 author = {You, H. and Lambert, J.H. and Clarens, A.F. and McFarlane, B.J.},
 journal = {IEEE Transactions on Systems, Man, and Cybernetics: Systems},
 number = {2}
}

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