Compound flood impact forecasting: Integrating fluvial and flash flood impact assessments into a unified system

Abstract. Floods can arise from a variety of physical processes. Although numerous risk assessment approaches stress the importance of taking into account the possible combinations of flood types (i.e. compound floods), this awareness has so far not been reflected in the development of early warning systems: Existing methods for forecasting flood hazards or the corresponding socio-economic impacts are generally designed for only one type of flooding. During compound flood events, these flood type-specific approaches are unable to identify the overall hazards or impacts. Moreover, from the perspective of the end-users (e.g. civil protection authorities), the monitoring of separate flood forecasts – with potentially contradictory outputs – can be confusing and time-consuming, and ultimately impede an effective emergency response. To enhance the decision support, this paper proposes the integration of different flood type-specific approaches into one compound flood impact forecast. This possibility has been explored by combining the simulations of two impact forecasting methods (representing fluvial and flash floods) for a recent catastrophic episode of compound flooding: the DANA event of September 2019 in Southeast Spain. The combination of the two methods identified well the overall compound flood extents and impacts reported by various information sources. For instance, the simulated economic losses amounted to about 670 million Euros against 425 million Euros of reported insured losses. Although the compound impact estimates were less accurate at municipal level, they corresponded significantly better to the observed impacts than those generated by the two methods applied separately. This demonstrates the potential of such integrated approaches for improving the decision support.

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The Role of Seismological Networks in Civil Protection in Low and High Seismic Hazards

Periodica Polytechnica Civil Engineering ◽

10.3311/ppci.17508 ◽

2021 ◽

Author(s):

Erzsébet Győri ◽

Arman Bulatovich Kussainov ◽

Gyöngyvér Szanyi ◽

Zoltán Gráczer ◽

Kendebay Zhanabilovich Raimbekov ◽

...

Keyword(s):

Early Warning ◽

Early Warning Systems ◽

Economic Losses ◽

Civil Protection ◽

Warning Systems ◽

Ground Shaking ◽

Research Areas ◽

Seismic Networks ◽

Strong Ground

Earthquakes are one of the most devastating natural disasters on Earth, causing sometimes huge economic losses and many human casualties. Since earthquake prediction is not yet possible, the purpose of civil protection is to reduce damage and protect human lives, in which the seismological networks of different countries play a very important role. Special applications of seismic networks are the early warning systems that can be used to protect vulnerable infrastructures using automated shutdown procedures, to stop high velocity trains and to save lives if the general public is notified about imminent strong ground shaking. In this paper, we describe the aims and operation of seismological networks, covering in more detail the early warning systems. Then we delineate the seismotectonic settings and seismicity in Hungary and Kazakhstan, furthermore, describe the operating seismological networks and the related scientific research areas with emphasis on civil protection. Hungary and Kazakhstan differ not only in the size of their territory, but also in their seismicity, therefore, in addition to the similarities, there are also significant differences between the aims and problems of their seismological networks.

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Assessment of Flood Early Warning Systems with Social Media

10.5194/egusphere-egu21-8816 ◽

2021 ◽

Author(s):

Thierry Hohmann ◽

Judit Lienert ◽

Jafet Andersson ◽

Darcy Molnar ◽

Peter Molnar ◽

...

Keyword(s):

Social Media ◽

Performance Assessment ◽

Early Warning ◽

Early Warning Systems ◽

Probability Of Detection ◽

Economic Losses ◽

Warning Systems ◽

Flood Events ◽

Spatial Coverage ◽

De Bruijn

IntroductionFlood early warning systems (FEWS) can reduce casualties and economic losses (UNEP, 2012). The EC Horizon 2020 project FANFAR (www.fanfar.eu) aims to co-develop a FEWS in West Africa together with stakeholders, predicting streamflow and return period threshold exceedance (Andersson et al., 2020). A Multi-Criteria Decision Analysis (MCDA) indicated, that stakeholders find information accuracy especially important, among a broad set of fundamental objectives (Lienert et al., 2020). Social media have the potential to support accuracy assessment by detecting flood events (Lorini et al., 2019; de Bruijn et al., 2019) due to their large spatial coverage (Restrepo-Estrada et al., 2018). We investigated the potential of social media to assess FANFAR forecast accuracy.&#160;Research ApproachFANFAR forecasts are based on HYPE, which is a semi-distributed land-cover and sub-catchment based hydrological model (Arheimer et al., 2020). We lumped the forecasted flood risk (FFR) on a country scale and compared it to flood events detected on Twitter, using an algorithm (FEDA) developed by de Bruijn et al. (2019). FEDA detects flood-related tweet bursts based on regionally and temporally adjusted thresholds (de Bruijn et al., 2019). We compared FEDA detected events with floods from the disaster database EM-DAT (https://www.emdat.be/), to find if tweets indicate flooding. We also compared FEDA to the lumped FFR to identify false positives (FP), false negatives (FN), and true positives (TP), from which we deduced the probability of detection (POD) and false alarm rate (FAR). We further calculated the correlation of single flood-related tweets with the lumped FFR and investigated seasonality, lag, and the influence of rainfall.&#160;FindingsThe detailed findings are described in Hohmann (2021). FEDA (i.e., tweets) and EM-DAT events (i.e., floods) mostly occurred in the same period. However, FEDA detected shorter and more frequent events than EM-DAT. In the Upper Niger, PODFEDA and FARFEDA (deduced from FEDA) were of similar order of magnitude as the PODS and FARS (deduced from streamflow) but were different in the Lower Niger region. This suggests that tweets can be employed additionally to e.g. streamflow timeseries as a complementary way to evaluate accuracy. Correlation analysis between single flood-related tweets and the lumped FFR showed no relationship. We also did not find a systematic influence of seasonality or a lagged response between tweets and FFR. The correlation coefficients between tweets and rainfall ranged from 0.1-0.9, but were mostly non-significant. This suggests that a performance assessment based on single tweets is not (yet) adequate. Also, since FEDA does not differentiate between pluvial and fluvial floods, it is less suited to assess the accuracy of FANFAR. Our findings suggest the need for inclusion of other factors into the performance assessment of FEWSs, such as regional thresholds to identify TP, FP, and FN. Also, rainfall causing pluvial flooding must be considered. Finally, our approach is limited to Twitter. Further research should assess the potential of e.g. Facebook to be included in FEWS performance assessment. The question whether social media, FEWSs, or EM-DAT are correct remains, and is in our opinion best addressed by employing multiple data sources.

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Flash Flood Impact Assessment in Jeddah City: An Analytic Hierarchy Process Approach

Hydrology ◽

10.3390/hydrology7010010 ◽

2020 ◽

Vol 7 (1) ◽

pp. 10 ◽

Cited By ~ 4

Author(s):

Umar Lawal Dano

Keyword(s):

Analytic Hierarchy Process ◽

Flash Flood ◽

Productivity Loss ◽

Flood Hazards ◽

Analytic Hierarchy ◽

Flood Impacts ◽

Impact Reduction ◽

Flood Impact ◽

The Government ◽

Hierarchy Process

Floods are among the most destructive natural hazards that cost lives and disrupt the socioeconomic activities of residents, especially in the rapidly growing cities of developing countries. Jeddah, a coastal city situated in Saudi Arabia, has experienced severe flash flood events in recent years. With intense rainfall, extensive coastal developments, and sensitive ecosystems, the city is susceptible to severe flash flood risks. The objective of this article is to apply an Analytic Hierarchy Process (AHP) model to explore the impacts of flash flood hazards and identify the most effective approaches to reducing the flash flood impacts in Jeddah using expert’s opinions. The study utilizes experts’ judgments and employs the AHP for data analyses and modeling. The results indicated that property loss has the highest probability of occurrence in the events of a flash flood with a priority level of 42%, followed by productivity loss (28%). Injuries and death were rated the least priority of 18% and 12%, respectively. Concerning flood impact reduction alternatives, river management (41%) and early warning system (38%) are the most favorable options. The findings could assist the government to design appropriate measures to safeguard the lives and properties of the residents. The study concludes by underscoring the significance of incorporating experts’ judgments in assessing flash flood impacts.

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Critical Analysis of the Value of Drought Information and Impacts on Land Management and Public Health

Water ◽

10.3390/w12041064 ◽

2020 ◽

Vol 12 (4) ◽

pp. 1064

Author(s):

Tingting Liu ◽

Kelly Helm Smith ◽

Richard Krop ◽

Tonya Haigh ◽

Mark Svoboda

Keyword(s):

Public Health ◽

Land Management ◽

Critical Analysis ◽

Public Information ◽

Weather Forecast ◽

Economic Loss ◽

Early Warning Systems ◽

Economic Losses ◽

Warning Systems ◽

Bureau Of Land Management

This paper reviews previous efforts to assign monetary value to climatic or meteorological information, such as public information on drought, climate, early warning systems, and weather forecast information. Methods and tools that have been explored to examine the benefits of climatic and meteorological information include the avoided cost, contingent valuation, choice experiments, benefit transfer, and descriptive approaches using surveys. The second part of this paper discusses specific considerations related to valuing drought information for public health and the Bureau of Land Management. We found a multitude of connections between drought and the land management and health sectors in the literature. The majority of the papers that we summarized only report biophysical change, because the economic losses of drought are not available. Only a few papers reported economic loss associated with drought. To determine the value of drought information, we need to know more about the role it plays in decision making and what sources of drought information are used in different sectors. This inventory of methods and impacts highlights opportunities for further research in valuing drought information in land management and public health.

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International Severe Weather and Flash Flood Hazard Early Warning Systems—Leveraging Coordination, Cooperation, and Partnerships through a Hydrometeorological Project in Southern Africa

Water ◽

10.3390/w8060258 ◽

2016 ◽

Vol 8 (6) ◽

pp. 258 ◽

Cited By ~ 5

Author(s):

Robert Jubach ◽

A. Tokar

Keyword(s):

Southern Africa ◽

Early Warning ◽

Flash Flood ◽

Flood Hazard ◽

Early Warning Systems ◽

Severe Weather ◽

Warning Systems

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Climate Risk and Early Warning Systems: Adaptation Strategies for the Most Vulnerable Communities

Journal of Science Policy & Governance ◽

10.38126/jspg180201 ◽

2021 ◽

Vol 18 (02) ◽

Author(s):

Jessica Bhardwaj ◽

Atifa Asghari ◽

Isabella Aitkenhead ◽

Madeleine Jackson ◽

Yuriy Kuleshov

Keyword(s):

Early Warning ◽

Climate Adaptation ◽

Early Warning Systems ◽

Adaptation Strategies ◽

Climate Risk ◽

Economic Losses ◽

Natural Environments ◽

Warning Systems ◽

Vulnerable Communities ◽

Policy And Planning

Climate risk and resultant natural disasters have significant impacts on human and natural environments. It is common for disaster responses to be reactive rather than proactive due to inadequate policy and planning mechanisms—such reactive management responses exacerbate human and economic losses in times of disaster. Proactive disaster responses maximize disaster resilience and preparation efforts in non-disaster periods. This report focuses on proactive, localized, and inclusive adaptation strategies for addressing impacts of three natural hazards: drought, floods, and tropical cyclones. Four key synergistic climate adaptation strategies are discussed—Post Disaster Reviews, Risk Assessments, Early Warning Systems and Forecast-based Financing. These strategies are further supported with a number of case studies and recommendations that will be of assistance for policymakers in developing evidence-based adaptation strategies that support the most vulnerable communities in the transition towards regarding disaster as a risk as opposed to a crisis.

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Towards Landslides Early Warning System With Fog - Edge Computing And Artificial Intelligence**

Journal of Ubiquitous Systems and Pervasive Networks ◽

10.5383/juspn.15.02.002 ◽

2021 ◽

Vol 15 (02) ◽

pp. 11-17

Author(s):

Olivier Debauche ◽

Meryem Elmoulat ◽

Saïd Mahmoudi ◽

Sidi Ahmed Mahmoudi ◽

Adriano Guttadauria ◽

...

Keyword(s):

Artificial Intelligence ◽

Early Warning ◽

Large Scale ◽

Prediction Models ◽

Warning System ◽

Early Warning Systems ◽

Economic Losses ◽

Warning Systems ◽

Large Scale Data ◽

Set Up

Landslides are phenomena that cause significant human and economic losses. Researchers have investigated the prediction of high landslides susceptibility with various methodologies based upon statistical and mathematical models, in addition to artificial intelligence tools. These methodologies allow to determine the areas that could present a serious risk of landslides. Monitoring these risky areas is particularly important for developing an Early Warning Systems (EWS). As matter of fact, the variety of landslides’ types make their monitoring a sophisticated task to accomplish. Indeed, each landslide area has its own specificities and potential triggering factors; therefore, there is no single device that can monitor all types of landslides. Consequently, Wireless Sensor Networks (WSN) combined with Internet of Things (IoT) allow to set up large-scale data acquisition systems. In addition, recent advances in Artificial Intelligence (AI) and Federated Learning (FL) allow to develop performant algorithms to analyze this data and predict early landslides events at edge level (on gateways). These algorithms are trained in this case at fog level on specific hardware. The novelty of the work proposed in this paper is the integration of Federated Learning based on Fog-Edge approaches to continuously improve prediction models.

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Benchmarking an operational procedure for rapid risk assessment in Europe

10.5194/nhess-2016-338 ◽

2016 ◽

Author(s):

Francesco Dottori ◽

Milan Kalas ◽

Peter Salamon ◽

Alessandra Bianchi ◽

Lorenzo Alfieri ◽

...

Keyword(s):

Risk Assessment ◽

Emergency Response ◽

Flood Hazard ◽

Early Warning Systems ◽

Economic Damage ◽

Warning Systems ◽

Hazard Maps ◽

Flood Events ◽

Operational Procedure ◽

Flood Hazard Maps

Abstract. The development of methods for rapid flood mapping and risk assessment is a key step to increase the usefulness of flood early warning systems, and is crucial for effective emergency response and flood impact mitigation. Currently, flood early warning systems rarely include real–time components to assess potential impacts generated by forecasted flood events. To overcome this limitation, this work describes the benchmarking of an operational procedure for rapid flood risk assessment based on predictions issued by the European Flood Awareness System (EFAS). Daily streamflow forecasts produced for major European river networks are translated into event-based flood hazard maps using a large map catalogue derived from high-resolution hydrodynamic simulations. Flood hazard maps are then combined with exposure and vulnerability information, and the impacts of the forecasted flood events are evaluated in terms of flood prone areas, economic damage and affected population, infrastructures and cities. An extensive testing of the operational procedure is carried out by analysing the catastrophic floods of May 2014 in Bosnia-Herzegovina, Croatia and Serbia. The reliability of the flood mapping methodology is tested against satellite-based and report-based flood extent data, while ground-based estimations of economic damage and affected population are compared against modelled estimates. Finally, we evaluate the skill of risk estimates derived from EFAS flood forecasts with different lead times and combinations of probabilistic forecasts. Results show the potential of the real-time operational procedure in helping emergency response and management.

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An operational procedure for rapid flood risk assessment in Europe

Natural Hazards and Earth System Science ◽

10.5194/nhess-17-1111-2017 ◽

2017 ◽

Vol 17 (7) ◽

pp. 1111-1126 ◽

Cited By ~ 20

Author(s):

Francesco Dottori ◽

Milan Kalas ◽

Peter Salamon ◽

Alessandra Bianchi ◽

Lorenzo Alfieri ◽

...

Keyword(s):

Risk Assessment ◽

Emergency Response ◽

Flood Hazard ◽

Early Warning Systems ◽

Economic Damage ◽

Warning Systems ◽

Flood Risk Assessment ◽

Hazard Maps ◽

Flood Events ◽

Operational Procedure

Abstract. The development of methods for rapid flood mapping and risk assessment is a key step to increase the usefulness of flood early warning systems and is crucial for effective emergency response and flood impact mitigation. Currently, flood early warning systems rarely include real-time components to assess potential impacts generated by forecasted flood events. To overcome this limitation, this study describes the benchmarking of an operational procedure for rapid flood risk assessment based on predictions issued by the European Flood Awareness System (EFAS). Daily streamflow forecasts produced for major European river networks are translated into event-based flood hazard maps using a large map catalogue derived from high-resolution hydrodynamic simulations. Flood hazard maps are then combined with exposure and vulnerability information, and the impacts of the forecasted flood events are evaluated in terms of flood-prone areas, economic damage and affected population, infrastructures and cities.An extensive testing of the operational procedure has been carried out by analysing the catastrophic floods of May 2014 in Bosnia–Herzegovina, Croatia and Serbia. The reliability of the flood mapping methodology is tested against satellite-based and report-based flood extent data, while modelled estimates of economic damage and affected population are compared against ground-based estimations. Finally, we evaluate the skill of risk estimates derived from EFAS flood forecasts with different lead times and combinations of probabilistic forecasts. Results highlight the potential of the real-time operational procedure in helping emergency response and management.

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