Traditional top-down methods for resource management ask first what future conditions will be, then identify the best action(s) to take in response to that prediction. Even when acknowledging uncertainty about the future, standard approaches ( a) characterize uncertainties probabilistically, then optimize objectives in expectation, and/or ( b) develop a small number of representative scenarios to explore variation in outcomes under different policy responses. This leaves planners vulnerable to surprise if future conditions diverge from predictions. In this review, we describe contemporary approaches to decision support that address deep uncertainty about future external forcings, system responses, and stakeholder preferences for different outcomes. Many of these methods are motivated by climate change adaptation, infra-structure planning, or natural resources management, and they provide dramatic improvements in the robustness of management strategies. We outline various methods conceptually and describe how they have been applied in a range of landmark real-world planning studies.

Standards-based levee design aims to protect against events with specific probabilities, for example eliminating overtopping from a storm surge with a 1% annual exceedance probability (i.e., a "100-year" event). This allows levee segments to be analyzed independently but ignores interior dynamics and overall risk. We present and implement a framework for calculating optimal riskinformed design heights. Using this design paradigm and multi-objective evolutionary algorithms, we identify levee and floodwall design heights that minimize the total system cost and expected flood losses over 50 years. With our model, decision makers may feasibly evaluate hundreds or thousands of alternative designs over a large ensemble of future states of the world. Comparing to the existing design elevations of the Larose to Golden Meadow Hurricane Protection Project in coastal Louisiana, over multiple climate change scenarios, we identify system configurations of similar cost that reduce the expected value of discounted residual risk of 26%-73% ($8-85 million). We also achieve the same residual risk at 90%-97% of the cost of the existing system (saving $19-73 million).climate change, coastal flood risk, levee design standards, risk analysis, storm surge | INTRODUCTIONCoastal flood risk management efforts in the United States commonly adopt a standards-based approach (Interagency Levee Policy Review Committee, 2006;Montz & Tobin, 2008). Analysts estimate a standard design load, such as the 100-year storm surge (a peak surge elevation with a 1-in-100 chance of occurring or being exceeded in a given year). Structural protection systems (e.g., levees, floodwalls) are then designed with crest heights that withstand the design load with some specified level of performance. For example, the U.S. Army Corps of Engineers (USACE) might set crest heights using a design criterion specifying that "the [maximum] overtopping rate should be less than 0.1 cfs/ft with 90 percent assurance" (U.S. Army Corps of Engineers, 2009). USACE guidance formally regards this kind of "level of protection" as a legacy term and requires risk assessment of any design alternatives under consideration (U.S. Army Corps of Engineers, 2000Engineers, , 2019. However, in practice, communities requesting feasibility studies for structural protection often opt for a 100-year, standards-based design as providing minimal protection to be considered "outside of the designated floodplain" and avoid requirements of the

Standards-based levee design aims to protect against events with specific probabilities, for example eliminating overtopping from a “1-in-100-year” storm surge. This allows levee segments to be analyzed independently but ignores interior dynamics and overall risk. We present and implement a framework for calculating optimal risk-informed design heights. Using this design paradigm and multi-objective evolutionary algorithms, we identify levee and floodwall design heights that minimize the total system cost and expected flood losses over 50 years. With our model, decision makers may feasibly evaluate hundreds or thousands of alternative designs. Comparing to the existing design elevations of the Larose to Golden Meadow Hurricane Protection Project in coastal Louisiana, over multiple climate change scenarios, we identify system configurations of similar cost that reduce the expected value of discounted residual risk of 26–73% ($8–85 million). We also achieve the same residual risk at 90–97% of the cost of the existing system (saving $19–73 million).

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