Benefits and Limitations of Real Options Analysis for the Practice of River Flood Risk Management

Abstract

Decisions on long‐lived flood risk management (FRM) investments are complex because the future is uncertain. Flexibility and robustness can be used to deal with future uncertainty. Real options analysis (ROA) provides a welfare‐economics framework to design and evaluate robust and flexible FRM strategies under risk or uncertainty. Although its potential benefits are large, ROA is hardly used in todays' FRM practice. In this paper, we investigate benefits and limitations of a ROA, by applying it to a realistic FRM case study for an entire river branch. We illustrate how ROA identifies optimal short‐term investments and values future options. We develop robust dike investment strategies and value the flexibility offered by additional room for the river measures. We benchmark the results of ROA against those of a standard cost‐benefit analysis and show ROA's potential policy implications. The ROA for a realistic case requires a high level of geographical detail, a large ensemble of scenarios, and the inclusion of stakeholders' preferences. We found several limitations of applying the ROA. It is complex. In particular, relevant sources of uncertainty need to be recognized, quantified, integrated, and discretized in scenarios, requiring subjective choices and expert judgment. Decision trees have to be generated and stakeholders' preferences have to be translated into decision rules. On basis of this study, we give general recommendations to use high discharge scenarios for the design of measures with high fixed costs and few alternatives. Lower scenarios may be used when alternatives offer future flexibility.

Investing in climate change adaptation and mitigation: A methodological review of real-options studies

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Risk management in distributed wind energy implementing Analytic Hierarchy Process

“…Previous publications implement Real Options Analysis (ROA), Failure Modes and Effects Analysis (FMEA) or Fuzzy Neural Networks to assess the operational and financial risks in wind power project (Muñoz, et al, 2011;Shafiee & Dinmohammadi, 2014;Pinson & Kariniotakis, 2003;Munoz, et al, 2009). However, the ROA method is complicated for managers to gather data that can support the assumption (Kind, et al, 2018). FMEA needs to consider the Risk-Priority-Number (RPN) values.…”

Construction and Application of Reservoir Flood Control Operation Rules Using the Decision Tree Algorithm

“…The DT algorithm has the advantages of being easier to understand, being easier to implement, and requiring relatively less workload than other approaches. Therefore, it has been widely used to address water conservation problems such as flood forecasting [46,47], flood or drought risk assessment [48][49][50][51][52][53], flood or drought classification [54,55], water quality prediction [56,57], inter-basin water transfer dispatching [58], water level prediction [59,60], and hydropower station power generation dispatching [61]. Noymanee and Theeramunkong [46] adopted the boosted decision tree regression to forecast flood water levels in a real-time manner and achieved high forecasting accuracy.…”