Abstract

The threat that climate change poses to water resource systems has led to a significant and growing number of impact studies. These studies tend to follow two general methodological approaches: (1) top-down, process-based studies driven by projections of future climate change supplied by downscaled general circulation models (GCMs), and (2) bottom-up, vulnerability-based studies driven by exploratory scenarios. Top-down studies generate realistic climate scenarios, but computational burdens limit the ensemble size. As a result, critical vulnerabilities may be left unexplored. Bottom-up approaches make it possible to assess a wide range of scenarios, but usually without connection to physically plausible climate processes, limiting their utility in adaptive planning. This study develops process-informed exploratory scenarios that bridge the gap between top-down and bottom-up methods. This hybrid approach yields several advantages. First, emerging vulnerabilities associated with non-linear hydrologic changes are linked to thermodynamic and dynamic climate drivers modeled in the GCMs with differential likelihoods and plausible ranges of change. This provides a transparent link between stakeholder defined vulnerabilities and climate processes that is often missing in bottom-up assessments. Second, non-linear shifts in vulnerability are directly linked to specific climate drivers, through the systematic perturbation of process informed climate variables. Making this connection in top-down assessments is difficult since the climate response to an emissions scenario is modeled as part of an endogenous process. The hybrid approach developed by this study is presented with a case study in the Tuolumne River watershed; through which thermodynamic and dyanamically guided climate scenarios were created by a process-informed stochastic weather generator to evaluate flood and drought related performance vulnerabilities at the New Don Pedro Dam near the watershed’s outlet. This case study finds that flood and drought performance at the dam is more sensitive to process-informed climate drivers than less theoretically grounded delta shifts precipitation, and non-linear system responses to climate drivers are revealed through the systematic perturbation process-informed climate variables.

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