Mise en œuvre de la méthode de cartographie du ruissellement IRIP pour l'analyse des risques lies aux écoulements sur l'infrastructure ferroviaire

Dehotin, J.; Chazelle, Blandine; Laverne, Guillaume; Hasnaoui, Ahlem; Lambert, Lucie; Breil, Pascal; Braud, Isabelle

doi:10.1051/lhb/20150069

Cited by 6 publications

(4 citation statements)

References 5 publications

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“…Defrance et al (2014) and Javelle et al (2014) used impact data to evaluate the performance of their flash-flood warnings. The IRIP method has also been evaluated by comparison with impact data on roads (Lagadec et al, 2016b) and on railways (Dehotin et al, 2015b;Lagadec et al, 2016a). During these evaluation tests, good probabilities of detection were obtained but also high false-alarm ratios because numerous areas where identified as susceptible to surface runoff but no impact has been recorded.…”

Section: Scientific Issuesmentioning

confidence: 99%

A surface runoff mapping method for optimizing risk assessment on railways

et al. 2018

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Railways are critical infrastructures for the transportation of people and goods and network failures must be controlled in order to maintain safety and to limit economic losses. The railway network is exposed to natural hazards and particularly to intense pluvial runoff. Due to the complexity of the phenomenon, management of risks induced by pluvial runoff raises technical and scientific issues. An innovative method for runoff susceptibility mapping, called IRIP for "Indicator of Intense Pluvial Runoff", has been created and adapted to the railway context. The objective of this paper is to evaluate the relevance of the mapping method and to provide application advice. The mapping method is evaluated by comparison with the results of a hydraulic diagnosis, on a 20 km railway line, using quantitative and qualitative comparisons. On the basis of contingency tables, probabilities of detection (POD, railway sections exposed and detected by IRIP) and false alarm ratios (FAR, railway sections detected by IRIP whereas they are not exposed) are computed. POD range from 94 to 100% and FAR range from 20 to 26%. Then spatial information provided by the maps is compared with field observations and recommendations. It is shown that the mapping method can bring substantial contribution to risk identification and that the IRIP method can allow pushing forward the current risk reduction methods. Thus, the surface runoff maps open up new opportunities to manage surface runoff, such as targeting mitigation actions at the origin of the hazard in partnership with the other territory stakeholders.

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Section: Scientific Issuesmentioning

confidence: 99%

A surface runoff mapping method for optimizing risk assessment on railways

et al. 2018

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“…In other works, risk regulatory zonings of surface runoff and soil erosion as well as post-event survey data of impacts on infrastructures and transport networks such as roads and railways were used to evaluate the IRIP model on several case studies in France [23][24][25]. IRIP was also applied in the same context to other regions (near Antibes in [26] and the Bayonne area in [27]). Recently, Braud et al [6] suggested a robust and generic method to evaluate the IRIP susceptibility maps using runoff-related proxy data in the railway context.…”

Section: Introductionmentioning

confidence: 99%

Proxy Data of Surface Water Floods in Rural Areas: Application to the Evaluation of the IRIP Intense Runoff Mapping Method Based on Satellite Remote Sensing and Rainfall Radar

Cerbelaud

Breil

Blanchet

et al. 2022

Water

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Along with fluvial floods (FFs), surface water floods (SWFs) caused by extreme overland flow are one of the main flood hazards occurring after heavy rainfall. Using physics-based distributed hydrological models, surface runoff can be simulated from precipitation inputs to investigate regions prone to soil erosion, mudflows or landslides. Geomatics approaches have also been developed to map susceptibility towards intense surface runoff without explicit hydrological modeling or event-based rainfall forcing. However, in order for these methods to be applicable for prevention purposes, they need to be comprehensively evaluated using proxy data of runoff-related impacts following a given event. Here, the IRIP geomatics mapping model, or “Indicator of Intense Pluvial Runoff”, is faced with rainfall radar measurements and damage maps derived from satellite imagery and supervised classification algorithms. Six watersheds in the Aude and Alpes-Maritimes departments in the South of France are investigated over more than 2000 km2 of rural areas during two flash-flood events. The results of this study show that the greater the IRIP susceptibility scores, the more SWFs are detected by the remote sensing-based detection algorithm. Proportions of damaged plots become even larger when considering areas which experienced heavier precipitations. A negative relationship between the mean IRIP accumulation scores and the intensity of rainfall is found among damaged plots, confirming that SWFs preferably occur over potentially riskier areas where rainfall is lower. Land use and soil hydraulic conductivity are identified as the most relevant indicators for IRIP to define production areas responsible for downslope deteriorations. Multivariate logistic regression is also used to determine the relative weights of upstream and local topography, uphill production areas and rainfall intensity for explaining SWF occurrence. This work overall confirms the relevance of IRIP methodology while suggesting improvements to its core framework to implement better prevention strategies against SWF-related hazards.

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“…Some studies in hydrology use proxy data to evaluate models, such as flooded road reports (Naulin et al, 2013;Versini et al, 2010aVersini et al, , 2010b, observations of gravitational hazards in mountainous areas (Defrance, 2014), and post-event surveys (Javelle et al, 2014;Ortega et al, 2009). Concerning the IRIP method evaluation, few comparisons have been performed with proxy data such as surface runoff impact locations on railways (Dehotin et al, 2015b) and natural disaster declaration locations from the Gaspar French database (Dehotin and Breil, 2011a). However, these tests have been performed for few case studies and remain qualitative.…”

Section: Introductionmentioning

confidence: 99%

Description and evaluation of a surface runoff susceptibility mapping method

Lagadec

Patrice

Braud

et al. 2016

Journal of Hydrology

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Please cite this article as: Lagadec, L-R., Patrice, P., Braud, I., Chazelle, B., Moulin, L., Dehotin, J., Hauchard, E., Breil, P., Description and evaluation of a surface runoff susceptibility mapping method, Journal of Hydrology (2016), doi: http://dx. AbstractSurface runoff is the hydrological process at the origin of phenomena such as soil erosion, floods out of rivers, mudflows, debris flows and can generate major damage. This paper presents a method to create maps of surface runoff susceptibility. The method, called IRIP (Indicator of Intense Pluvial Runoff, French acronym), uses a combination of landscape factors to create three maps representing the susceptibility (1) to generate, (2) to transfer, and (3) to accumulate surface runoff. The method input data are the topography, the land use and the soil type. The method aims to be simple to implement and robust for any type of study area, with no requirement for calibration or specific input format. In a second part, the paper focuses on the evaluation of the surface runoff susceptibility maps. The method is applied in the Lézarde catchment (210 km², northern France) and the susceptibility maps are evaluated by comparison with two risk regulatory zonings of surface runoff and soil erosion, and two databases of surface runoff impacts on roads and railways.Comparison tests are performed using a standard verification method for dichotomous forecasting along with five verification indicators: accuracy, bias, success ratio, probability of detection, and false alarm ratio. The evaluation shows that the susceptibility map of surface runoff accumulation is able to identify the concentrated surface runoff flows and that the susceptibility map of transfer is able to identify areas that are susceptible to soil erosion. Concerning the ability of the IRIP method to detect sections of the transportation network susceptible to be impacted by surface runoff, the evaluation tests show promising probabilities of detection (73 to 90%) but also high false alarm ratios (77 to 92%). However, a qualitative analysis of the local configuration of the infrastructure shows that taking into account the transportation network vulnerability can explain numerous false alarms. This paper shows that the IRIP method can be a valuable tool to facilitate field analysis and perform surface runoff zonings and opens interesting prospects for the use of the IRIP method in a context of risk management.3

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Mise en œuvre de la méthode de cartographie du ruissellement IRIP pour l'analyse des risques lies aux écoulements sur l'infrastructure ferroviaire

Cited by 6 publications

References 5 publications

A surface runoff mapping method for optimizing risk assessment on railways

A surface runoff mapping method for optimizing risk assessment on railways

Proxy Data of Surface Water Floods in Rural Areas: Application to the Evaluation of the IRIP Intense Runoff Mapping Method Based on Satellite Remote Sensing and Rainfall Radar

Description and evaluation of a surface runoff susceptibility mapping method

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