A Monte Carlo simulation and sensitivity analysis framework demonstrating the advantages of probabilistic forecasting over deterministic forecasting in terms of flood warning reliability

Duque, Luis-Felipe; O’Connell, Enda; O’Donnell, Greg

doi:10.1016/j.jhydrol.2023.129340

Cited by 10 publications

(2 citation statements)

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“…While a number of studies have quantified predictive uncertainty, PU, in FEWSs, refs. [27][28][29][30][31][32] demonstrated the advantages of probabilistic forecasting over deterministic forecasting in terms of flood warning reliability (32); they typically do not consider the response and impact [33]. This represents an innovative contribution from this work in the context of polder operation.…”

Section: Discussionmentioning

confidence: 99%

“…The polder rainfall-runoff simulation model is furthermore linked with an impact curve to represent the inundated area. An impact curve relates the damaging variable (water level) of a current or future flood event to the magnitude of the impact and has been used for national flood risk assessment in the UK [34] and for simulating warned and flooded properties within an MC framework [33]. This curve, which was assumed here, makes the MC framework versatile; however, for operational implementation, a real-world data-based impact curve would be needed.…”

Section: Discussionmentioning

confidence: 99%

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Evaluating the Benefits of Flood Warnings in the Management of an Urban Flood-Prone Polder Area

Duque,

O’Donnell,

Liu

et al. 2023

Hydrology

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Polders are low-lying areas located in deltas, surrounded by embankments to prevent flooding (river or tidal floods). They rely on pumping systems to remove water from the inner rivers (artificial rivers inside the polder area) to the outer rivers, especially during storms. Urbanized polders are especially vulnerable to pluvial flooding if the drainage, storage, and pumping capacity of the polder is inadequate. In this paper, a Monte Carlo (MC) framework is proposed to evaluate the benefits of rainfall threshold-based flood warnings when mitigating pluvial flooding in an urban flood-prone polder area based on 24 h forecasts. The framework computes metrics that give the potential waterlogging duration, maximum inundated area, and pump operation costs by considering the full range of potential storms. The benefits of flood warnings are evaluated by comparing the values of these metrics across different scenarios: the no-warning, perfect, deterministic, and probabilistic forecast scenarios. Probabilistic forecasts are represented using the concept of “predictive uncertainty” (PU). A polder area located in Nanjing was chosen for the case study. The results show a trade-off between the metrics that represent the waterlogging and the pumping costs, and that probabilistic forecasts of rainfall can considerably enhance these metrics. The results can be used to design a rainfall threshold-based flood early warning system (FEWS) for a polder area and/or evaluate its benefits.

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