An early warning system for rainfall-triggered shallow slides and debris flows. Application in Catalonia, Spain and Canton of Bern, Switzerland

2020 ◽  
Author(s):  
Rosa M Palau ◽  
Marc Berenguer ◽  
Marcel Hürlimann ◽  
Daniel Sempere-Torres ◽  
Catherine Berger ◽  
...  
Keyword(s):  
Early Warning ◽  
Debris Flows ◽  
Risk Mitigation ◽  
Regional Scale ◽  
Slope Angle ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Radar Rainfall ◽  
Susceptibility Maps ◽  
Landslide Event

<p>Risk mitigation for rainfall-triggered shallow slides and debris flows at regional scale is challenging. Early warning systems are a helpful tool to depict the location and time of future landslide events so that emergency managers can act in advance. Recently, some of the regions that are recurrently affected by rainfall triggered landslides have developed operational landslide early warning systems (LEWS). However, there are still many territories where this phenomenon also represents an important hazard and lack this kind of risk mitigation strategy.</p><p>The main objective of this work is to study the feasibility to apply a regional scale LEWS, which was originally designed to work over Catalonia (Spain), to run in other regions. To do so we have set up the LEWS to Canton of Bern (Switzerland).</p><p>The LEWS combines susceptibility maps to determine landslide prone areas and in real time high-resolution radar rainfall observations and forecasts. The output is a qualitative warning level map with a resolution of 30 m.</p><p>Susceptibility maps have been derived using a simple fuzzy logic methodology that combines the terrain slope angle, and land use and land cover (LULC) information. The required input parameters have been obtained from regional, pan-European and global datasets.</p><p>Rainfall inputs have been retrieved from both regional weather radar networks, and the OPERA pan-European radar composite. A set of global rainfall intensity-duration data has been used to asses if a rainfall event has the potential of triggering a landslide event.</p><p>The LEWS has been run in the region of Catalonia and Canton of Bern for specific rainfall events that triggered important landslides. Finally, the LEWS performance in Catalonia has been assessed.</p><p>Results in Catalonia show that the LEWS performance strongly depends on the quality of both the susceptibility maps and rainfall data. However, in both regions the LEWS is generally able to issue warnings for most of the analysed landslide events.</p>

scholarly journals Debris-flow forecasting at regional scale by combining susceptibility mapping and radar rainfall

2015 ◽  
Vol 15 (3) ◽  
pp. 587-602 ◽  
Author(s):  
M. Berenguer ◽  
D. Sempere-Torres ◽  
M. Hürlimann
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Regional Scale ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Susceptibility Assessment ◽  
Radar Rainfall ◽  
Eastern Pyrenees ◽  
Rainfall Map ◽  
Rainfall Estimates

Abstract. This work presents a technique for debris-flow (DF) forecasting able to be used in the framework of DF early warning systems at regional scale. The developed system is applied at subbasin scale and is based on the concepts of fuzzy logic to combine two ingredients: (i) DF subbasin susceptibility assessment based on geomorphological variables and (ii) the magnitude of the rainfall situation as depicted from radar rainfall estimates. The output of the developed technique is a three-class warning ("low", "moderate" or "high") in each subbasin when a new radar rainfall map is available. The developed technique has been applied in a domain in the eastern Pyrenees (Spain) from May to October 2010. The warning level stayed "low" during the entire period in 20% of the subbasins, while in the most susceptible subbasins the warning level was at least "moderate" for up to 10 days. Quantitative evaluation of the warning level was possible in a subbasin where debris flows were monitored during the analysis period. The technique was able to identify the three events observed in the catchment (one debris flow and two hyperconcentrated flow events) and produced no false alarm.

Radar Rainfall Estimates for Debris-Flow Early Warning Systems

2017 ◽  
pp. 453-465
Author(s):  
F. Marra ◽  
E. I. Nikolopoulos ◽  
J. D. Creutin ◽  
M. Borga
Keyword(s):  
Debris Flow ◽  
Early Warning ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Radar Rainfall ◽  
Rainfall Estimates

scholarly journals Quantifying the effectiveness of early warning systems for natural hazards

2016 ◽  
Vol 16 (1) ◽  
pp. 149-166 ◽  
Author(s):  
M. Sättele ◽  
M. Bründl ◽  
D. Straub
Keyword(s):  
Natural Hazards ◽  
Early Warning ◽  
Risk Mitigation ◽  
Early Warning Systems ◽  
Mitigation Measures ◽  
Management Approach ◽  
Warning Systems ◽  
Integrated Risk ◽  
Framework Approach

Abstract. Early warning systems (EWSs) are increasingly applied as preventive measures within an integrated risk management approach for natural hazards. At present, common standards and detailed guidelines for the evaluation of their effectiveness are lacking. To support decision-makers in the identification of optimal risk mitigation measures, a three-step framework approach for the evaluation of EWSs is presented. The effectiveness is calculated in function of the technical and the inherent reliability of the EWS. The framework is applicable to automated and non-automated EWSs and combinations thereof. To address the specifics and needs of a wide variety of EWS designs, a classification of EWSs is provided, which focuses on the degree of automations encountered in varying EWSs. The framework and its implementation are illustrated through a series of example applications of EWS in an alpine environment.

scholarly journals Quantifying the effectiveness of early warning systems for natural hazards

2015 ◽  
Vol 3 (7) ◽  
pp. 4479-4526 ◽  
Author(s):  
M. Sättele ◽  
M. Bründl ◽  
D. Straub
Keyword(s):  
Natural Hazards ◽  
Early Warning ◽  
Risk Mitigation ◽  
Early Warning Systems ◽  
Mitigation Measures ◽  
Management Approach ◽  
Warning Systems ◽  
Integrated Risk ◽  
Framework Approach

Abstract. Early warning systems (EWS) are increasingly applied as preventive measures within an integrated risk management approach for natural hazards. At present, common standards and detailed guidelines for the evaluation of their effectiveness are lacking. To support decision-makers in the identification of optimal risk mitigation measures, a three-step framework approach for the evaluation of EWS is presented. The effectiveness is calculated in function of the technical and the inherent reliability of the EWS. The framework is applicable to automated and non-automated EWS and combinations thereof. To address the specifics and needs of a wide variety of EWS designs, a classification of EWS is provided, which focuses on the degree of automations encountered in varying EWS. The framework and its implementation are illustrated through a series of example applications of EWS in an alpine environment.

Five years of EDuMaP for the performance analysis of territorial landslide early warning systems

2021 ◽  
Author(s):  
Luca Piciullo ◽  
Michele Calvello
Keyword(s):  
Performance Evaluation ◽  
Performance Analysis ◽  
Performance Assessment ◽  
Early Warning ◽  
Early Warning Systems ◽  
Performance Criteria ◽  
Warning Systems ◽  
Landslide Event ◽  
Landslide Early Warning ◽  
Warning Model

<p>Landslide early warning systems (LEWS) can be classified in either territorial or local systems (Piciullo et al., 2018). Systems addressing single landslides, at slope scale, can be named local LEWS (Lo-LEWS), systems operating over wide areas, at regional scale, can be referred to as territorial systems (Te-LEWS). Te-LEWS deal with the occurrence of several landslides within wide warning zones at municipal/regional/national scale. Nowadays, there are around 30 Te-LEWS operational worldwide (Piciullo et al., 2018; Guzzetti et al., 2020). The performance evaluation of such systems is often overlooked, and a standardized procedure is still missing. Often the performance evaluation is based on 2 by 2 contingency tables computed for the joint frequency distribution of landslides and alerts, both considered as dichotomous variables. This approach can lead to an imprecise assessment of the warning model, because it cannot differentiate among different levels of warning and the variable number of landslides that may occur in a time interval.</p><p>To overcome this issue Calvello and Piciullo (2016) proposed an original method for the performance analysis of a warning model, named EDuMaP, acronym of the method’s three main phases: Event analysis, Duration Matrix computation, Performance assessment. The method is centered around the computation of a n by m duration matrix that quantifies the time associated with the occurrence (and non-occurrence) of a given landslide event in relation to the different warning levels adopted by a Te-LEWS. Different performance criteria and indicators can be applied to evaluate the computed duration matrix.</p><p>Since 2016, the EDuMaP method has been applied to evaluate the performance of several Te-LEWS operational worldwide: Rio de Janeiro, Brazil (Calvello and Piciullo, 2016); Norway, Vestlandet (Piciullo et al., 2017a); Piemonte region, Italy (Piciullo et al., 2020), Amalfi coast, Italy (Piciullo et al., 2017b). These systems have different structures and warning models with either fixed or variable warning zones. In all cases, the EDuMaP method has proved to be flexible enough to successfully perform the evaluation of the warning models, highlighting critical and positive aspects of such systems, as well as proving that simpler evaluation methods do not allow a detailed assessment of the seriousness of the errors and of the correctness of the predictions of Te-LEWS (Piciullo et al., 2020).</p><p>Calvello M, Piciullo L (2016) Assessing the performance of regional landslide early warning models: the EDuMaP method. Nat Hazards Earth Syst Sc 16:103–122. https://doi.org/10.5194/nhess-16-103-2016</p><p>Guzzetti et al (2020) Geographical landslide early warning systems. Earth Sci Rev 200:102973. https://doi.org/10.1016/j.earsc irev.2019.102973</p><p>Piciullo et al (2018) Territorial early warning systems for rainfall-induced landslides. Earth Sci Rev 179:228–247. https://doi.org/10.1016/j.earscirev.2018.02.013</p><p>Piciullo et al (2017a) Adaptation of the EDuMaP method for the performance evaluation of the alerts issued on variable warning zones. Nat Hazards Earth Sys Sc 17:817–831. https://doi.org/10.5194/nhess-17-817-2017</p><p>Piciullo et al (2017b) Definition and performance of a threshold-based regional early warning model for rainfall-induced landslides. Landslides 14:995–1008. https://doi.org/10.1007/s10346-016-0750-2</p><p>Piciullo et al (2020). Standards for the performance assessment of territorial landslide early warning systems. Landslides 17:2533–2546. https://doi.org/10.1007/s10346-020-01486-4</p>

scholarly journals Debris-flow hazard assessment at regional scale by combining susceptibility mapping and radar rainfall

2014 ◽  
Vol 2 (10) ◽  
pp. 6295-6338
Author(s):  
M. Berenguer ◽  
D. Sempere-Torres ◽  
M. Hürlimann
Keyword(s):  
Debris Flow ◽  
Hazard Assessment ◽  
Regional Scale ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Radar Rainfall ◽  
Eastern Pyrenees ◽  
Hazard Level ◽  
Rainfall Map ◽  
Debris Flow Hazard

Abstract. This work presents a technique for debris flow (DF) hazard assessment able to be used in the framework of DF early warning systems at regional scale. The developed system is applied at subbasin scale and is based on the concepts of fuzzy logic to combine two ingredients: (i) DF subbasin susceptibility assessment based on geomorphological variables, and (ii) the magnitude of the rainfall situation as depicted from radar rainfall estimates. The output of the developed technique is a three-class hazard level ("low", "moderate" and "high") in each subbasin when a new radar rainfall map is available. The developed technique has been applied in a domain in the Eastern Pyrenees (Spain) from May to October 2010. The estimated hazard level stayed "low" during the entire period in 20% of the subbasins, while, in the most susceptible subbasins, the hazard level was at least moderate for up to10 days. Quantitative evaluation of the estimated hazard level was possible in a subbasin where debris flows were monitored during the analysis period. The technique was able to identify the 3 events observed in the catchment (1 debris flow and 2 hyperconcentrated flow events) and produced no false alarm.

scholarly journals Snow accumulation/melting model (SAMM) for integrated use in regional scale landslide early warning systems

2013 ◽  
Vol 17 (3) ◽  
pp. 1229-1240 ◽  
Author(s):  
G. Martelloni ◽  
S. Segoni ◽  
D. Lagomarsino ◽  
R. Fanti ◽  
F. Catani
Keyword(s):  
Early Warning ◽  
Regional Scale ◽  
Warning System ◽  
Early Warning Systems ◽  
Snow Accumulation ◽  
Point Of View ◽  
Warning Systems ◽  
Temperature Index ◽  
Landslide Early Warning ◽  
Optimal Values

Abstract. We propose a simple snow accumulation/melting model (SAMM) to be applied at regional scale in conjunction with landslide warning systems based on empirical rainfall thresholds. SAMM is based on two modules modelling the snow accumulation and the snowmelt processes. Each module is composed by two equations: a conservation of mass equation is solved to model snowpack thickness and an empirical equation for the snow density. The model depends on 13 empirical parameters, whose optimal values were defined with an optimisation algorithm (simplex flexible) using calibration measures of snowpack thickness. From an operational point of view, SAMM uses as input data only temperature and rainfall measurements, bringing about the additional benefit of a relatively easy implementation. After performing a cross validation and a comparison with two simpler temperature index models, we simulated an operational employment in a regional scale landslide early warning system (EWS) and we found that the EWS forecasting effectiveness was substantially improved when used in conjunction with SAMM.

scholarly journals Community-based early warning systems for flood risk mitigation in Nepal

2017 ◽  
Vol 17 (3) ◽  
pp. 423-437 ◽  
Author(s):  
Paul J. Smith ◽  
Sarah Brown ◽  
Sumit Dugar
Keyword(s):  
Early Warning ◽  
Risk Mitigation ◽  
Early Warning Systems ◽  
Appropriate Technology ◽  
Data Availability ◽  
Current Status ◽  
Lead Times ◽  
Warning Systems ◽  
Community Based ◽  
Probabilistic Forecasts

Abstract. This paper focuses on the use of community-based early warning systems for flood resilience in Nepal. The first part of the work outlines the evolution and current status of these community-based systems, highlighting the limited lead times currently available for early warning. The second part of the paper focuses on the development of a robust operational flood forecasting methodology for use by the Nepal Department of Hydrology and Meteorology (DHM) to enhance early warning lead times. The methodology uses data-based physically interpretable time series models and data assimilation to generate probabilistic forecasts, which are presented in a simple visual tool. The approach is designed to work in situations of limited data availability with an emphasis on sustainability and appropriate technology. The successful application of the forecast methodology to the flood-prone Karnali River basin in western Nepal is outlined, increasing lead times from 2–3 to 7–8 h. The challenges faced in communicating probabilistic forecasts to the last mile of the existing community-based early warning systems across Nepal is discussed. The paper concludes with an assessment of the applicability of this approach in basins and countries beyond Karnali and Nepal and an overview of key lessons learnt from this initiative.

scholarly journals “Waste Not, Want Not” — Leveraging Sewer Systems and Wastewater-Based Epidemiology for Drug Use Trends and Pharmaceutical Monitoring

2021 ◽  
Author(s):  
Timothy B. Erickson ◽  
Noriko Endo ◽  
Claire Duvallet ◽  
Newsha Ghaeli ◽  
Kaitlyn Hess ◽  
...  
Keyword(s):  
Early Warning ◽  
Large Scale ◽  
Illicit Drugs ◽  
Drugs Of Abuse ◽  
Regional Scale ◽  
Early Warning Systems ◽  
Drug Consumption ◽  
Warning Systems ◽  
Opioid Use ◽  
Current Application

AbstractDuring the current global COVID-19 pandemic and opioid epidemic, wastewater-based epidemiology (WBE) has emerged as a powerful tool for monitoring public health trends by analysis of biomarkers including drugs, chemicals, and pathogens. Wastewater surveillance downstream at wastewater treatment plants provides large-scale population and regional-scale aggregation while upstream surveillance monitors locations at the neighborhood level with more precise geographic analysis. WBE can provide insights into dynamic drug consumption trends as well as environmental and toxicological contaminants. Applications of WBE include monitoring policy changes with cannabinoid legalization, tracking emerging illicit drugs, and early warning systems for potent fentanyl analogues along with the resurging wave of stimulants (e.g., methamphetamine, cocaine). Beyond drug consumption, WBE can also be used to monitor pharmaceuticals and their metabolites, including antidepressants and antipsychotics. In this manuscript, we describe the basic tenets and techniques of WBE, review its current application among drugs of abuse, and propose methods to scale and develop both monitoring and early warning systems with respect to measurement of illicit drugs and pharmaceuticals. We propose new frontiers in toxicological research with wastewater surveillance including assessment of medication assisted treatment of opioid use disorder (e.g., buprenorphine, methadone) in the context of other social burdens like COVID-19 disease.

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