Estimating Ensemble Flood Forecasts’ Uncertainty: A Novel “Peak-Box” Approach for Detecting Multiple Peak-Flow Events

Giordani, Antonio; Zappa, Massimiliano; Rotach, Mathias W.

doi:10.3390/atmos11010002

Cited by 3 publications

(3 citation statements)

References 45 publications

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“…Therefore, Zappa et al [10] first proposed a visualization approach, called "Peak-Box", with the purpose of helping decision-making when forecasting flood events. Giordani et al [7] modified it to detect multiple peak flows. Figure 7 Left shows the "Peak-Box" visualization approach and the concept is described as follows.…”

Section: A Visualization Approach For Supporting the Interpretation O...mentioning

confidence: 99%

“…Davolio et al [5] proposed a HEPS based on multi-model ensemble QPF (quantitative precipitation forecast) along with the rainfall-runoff model TOPKAPI (TOPographic Kinematic APproximation and Integration) [6] for the Reno River basin in northern Italy. Researchers are in general agreement that HEPSs for flood warning purposes have added forecast value compared to the previously adopted deterministic forecasts [1,7].…”

Section: Introductionmentioning

confidence: 99%

“…Zappa et al [10] proposed a visualization approach to support the interpretation and verification of HEPS results. Giordani et al [7] modified the approach from Zappa et al [10] and developed another method for multiple peak flow detections. Olsson et al [12] used this approach to process the ensemble runoff forecasts for joint probabilistic visualization of peak flow runoff and timing.…”

Section: Introductionmentioning

confidence: 99%

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Development of a Hydrological Ensemble Prediction System to Assist with Decision-Making for Floods during Typhoons

Yang

Chang

et al. 2020

Sustainability

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Hydrological ensemble prediction systems (HEPSs) can provide decision makers with early warning information, such as peak stage and peak time, with enough lead time to take the necessary measures to mitigate disasters. This study develops a HEPS that integrates meteorological, hydrological, storm surge, and global tidal models. It is established to understand information about the uncertainty of numerical weather predictions and then to provide probabilistic flood forecasts instead of commonly adopted deterministic forecasts. The accuracy of flood forecasting is increased. However, the spatiotemporal uncertainty associated with these numerical models in the HEPS and the difficulty in interpreting the model results hinder effective decision-making during emergency response situations. As a result, the efficiency of decision-making is not always increased. Thus, this study also presents a visualization method to interpret the ensemble results to enhance the understanding of probabilistic runoff forecasts for operational purposes. A small watershed with area of 100 km2 and four historical typhoon events were selected to evaluate the performance of the method. The results showed that the proposed HEPS along with the visualization approach improved the intelligibility of forecasts of the peak stages and peak times compared to that of approaches previously described in the literature. The capture rate is greater than 50%, which is considered practical for decision makers. The proposed HEPS with the visualization method has potential for both decreasing the uncertainty of numerical rainfall forecasts and improving the efficiency of decision-making for flood forecasts.

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Section: A Visualization Approach For Supporting the Interpretation O...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development of a Hydrological Ensemble Prediction System to Assist with Decision-Making for Floods during Typhoons

Yang

Chang

et al. 2020

Sustainability

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A Collaborative Effort to Better Understand, Measure, and Model Atmospheric Exchange Processes over Mountains

Rotach

Serafin

Ward

et al. 2022

Bulletin of the American Meteorological Society

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In this essay, we highlight some challenges the atmospheric community is facing concerning adequate treatment of flows over mountains and their implications for numerical weather prediction (NWP), climate simulations and impact modeling. With recent increases in computing power (and hence model resolution) numerical models start to face new limitations (such as numerical instability over steep terrain). At the same time there is a growing need for sufficiently reliable NWP model output to drive various impact models (for hydrology, air pollution, agriculture, …). The input information for these impact models is largely produced by the boundary layer (BL) parameterizations of NWP models. All known BL parameterizations assume flat and horizontally homogeneous surface conditions, and their performance and interaction with resolved flows is massively understudied over mountains – hence their output may be accidentally acceptable at best. We therefore advocate the systematic investigation of the so-called ‘Mountain Boundary Layer’ (MoBL), introduced to emphasize its many differences to the BL over flat and horizontally homogeneous terrain. An international consortium of scientists has launched a research program (TEAMx: ‘Multi-scale transport and exchange processes in the atmosphere over mountains – programme and experiment’) to address some of the most pressing scientific challenges. TEAMx is endorsed by World Weather Research Programme (WWRP), and the Global Energy and Water Exchanges (GEWEX) project as a ‘cross-cutting project’. A program coordination office was established at the University of Innsbruck (Austria). This essay introduces the background to and content of a recently published White Paper outlining the key research questions of TEAMx.

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Estimating Ensemble Flood Forecasts’ Uncertainty: A Novel “Peak-Box” Approach for Detecting Multiple Peak-Flow Events

2019

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Ensemble flood forecasts are an established tool to provide information about the uncertainty of runoff predictions. However, their interpretation may not be straightforward, especially when dealing with extreme events; therefore, the development of new tools to enhance their understanding and visualization is necessary. Recently, the so-called “peak-box” approach has been developed to help decision makers in the interpretation and verification of peak-flow forecasts, receiving positive feedbacks within the hydrological community. However, this method has proven to be limited when multiple peak-flow events occur within the forecast, being unable to separate close discharge peaks. The aim of this paper is then to develop a new algorithm designed to accomplish this task. To do so, we consider runoff probabilistic forecasts obtained with a coupled hydrometeorological flood forecasting system formed by the high resolution meteorological Ensemble model COSMO-E and the hydrological model PREVAH, for the small Verzasca basin, Switzerland, during October and November 2018. The application of this new method, despite the limitation given by the small sample size considered in this study, indicates a successful implementation: the new algorithm is able to distinguish among different events and to provide sharper and more skillful forecasts, and its verification yields slightly better timing estimations compared to the former approach.

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Estimating Ensemble Flood Forecasts’ Uncertainty: A Novel “Peak-Box” Approach for Detecting Multiple Peak-Flow Events

Cited by 3 publications

References 45 publications

Development of a Hydrological Ensemble Prediction System to Assist with Decision-Making for Floods during Typhoons

Development of a Hydrological Ensemble Prediction System to Assist with Decision-Making for Floods during Typhoons

A Collaborative Effort to Better Understand, Measure, and Model Atmospheric Exchange Processes over Mountains

Estimating Ensemble Flood Forecasts’ Uncertainty: A Novel “Peak-Box” Approach for Detecting Multiple Peak-Flow Events

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