addressing climate change adaptation in regional transportation plans

Addressing Climate Change Adaptation in Regional Transportation PlansA Guide for California MPOs and RTPAsThe magnitude of consequences needs to be measured in some fashion. Thepreferred measure of magnitude may be very qualitative or fairly quantitative, orcombine qualitative and quantitative measures. A uniform unit (for example“dollars of direct and indirect losses”) is not necessary, and can complicate theanalysis (an exception, for regions conducting benefit-cost analyses, is describedbelow). Nor is it necessary, or always realistic, to develop precise estimates ofmagnitude; ranges or orders of magnitude will suffice for most assessmentefforts. The right measure and level of precision will be a matter of preferenceand measurement resources. For example, disruption to a facility may bemeasured in time (minutes, hours, days – or, when coupled with damage,potentially months or even years), by detour costs (AADT * detour length * traveltime and/or vehicle costs), by congestion effects on the greater system, or usinganother metric important to the region.Regions with a constrained list of top tier assets may opt to employ the climateriskadjusted benefit-cost analysis technique developed for Climate ChangeAdaptation and the Highway System (NCHRP, forthcoming). In this application,full range of consequences is monetized, and becomes, in effect the “benefit” sideof the equation – as risks that were expected to affect the asset but are mitigatedby adaptation activities (the marginal resources expended in the cause ofadaptation become the “cost” side of the equation).The final step of the consequences pathway is to pair the expected magnitudes ofconsequence with the likelihood of occurrence. The basis for the consideration oflikelihood was established in Module 3, which accounted for expected stressoroccurrence at threshold levels to which infrastructure is vulnerable, according torules of thumb. Revisiting likelihood permits the adjustment of these rules ofthumb for determining susceptibility, if needed. Starting with the likelihood ofstressor occurrence (from Module 2b), this exercise suggests assessing thelikelihood of the range of correlated consequences. For example, the assessmentteam might have identified “major damage/disruption” and “moderate damage/disruption” as expected consequences of a one-percent chance flood event. Byemploying knowledge of past consequences, professional knowledge about theasset, and estimates of future condition, “major damage/disruption” might bedeemed “highly unlikely/very rare,” for instance, whereas “moderate damage/disruption” might be considered more probable. This stage can also beconducted prior to the measurement of consequences as a means of screening outconsequences of extremely low probability.This process yields a screened list of risks that are priorities for adaptation.Although mathematical representation is rarely possible, and not necessarilydesirable, the concept is best illustrated as a function of [(stressor likelihood *impact likelihood) * magnitude of impact]. To populate this equation with somehypothetical values, perhaps the stressor likelihood is 50 percent (in a given timeperiod – year, decade, even century). For each occurrence of the stressor, thelikelihood of “major damage” is thought to be 1 percent, and the likelihood of“moderate damage” is 50 percent (the matrix of impacts and likelihoods could12-8 Cambridge Systematics, Inc.