Sustainability is meeting the needs of the present without jeopardizing quality of life for future generations. Adaptation is adjustment of resource utilization and planning by current generations to ensure sustainability. Mitigation, for this study, narrowly refers to damage repair and restoration costs incurred after natural hazard occurrence. Climate is dynamic and ever changing. Recent observed changes in weather patterns identify that drought and intense precipitation, leading to flooding, are more likely to occur in the near future. An example dynamic probabilistic risk assessment (PRA) for flood inundation is created and applied to understand benefits to, and limitations on, PRA for sustainable water resource management. This example addresses the issue of sustainable decision making related to outdated, but historically regulatory compliant, infrastructure. The observed increase in likelihood for large floods means that many assets were designed for inapplicable conditions and are more likely to be damaged in the future. Results from this example PRA demonstrate that it provides for optimizing the degree of sustainability included in resource management and decision making. Sustainability optimization is obtained by balancing likelihood for future mitigation costs against potential cost savings garnered from present-day adaptation.

Weather attribution estimates the current and near future likelihood for a recently observed extreme weather event, like a drought or hurricane. It uses climate models, weather prediction models, and observed weather to determine how much more likely the observed event is today relative to the recent past, like the 1990s and 2000s. In this study, a statistical weather generator (WG) creates synthetic sequences of future precipitation, temperature, and potential evapotranspiration that represent the increased likelihood for three-month severe drought. An independent weather attribution study identified that three-month severe drought is five times more likely to occur today relative to recent historical conditions. The WG-simulated conditions portray a near future where historical extreme and severe drought are significantly more likely to occur. The climate description produced by this WG is representative of the weather attribution study and is significantly hotter, with lower expected soil moisture than the future climate description obtained from global circulation, i.e., climate, model (GCM) simulation results (by themselves).