Jérémy Rohmer

French Geological Survey | BRGM · Direction Risques et Prévention

Machine learning (ML) models have become key ingredients for digital soil mapping. To improve the interpretability of their predictions, diagnostic tools such as the widely used local attribution approach known as SHapley Additive exPlanations (SHAP) have been developed. However, the analysis of ML model predictions is only one part of the problem,...

Beside climate‐change‐induced sea‐level rise (SLR), land subsidence can strongly amplify coastal risk in flood‐prone areas. Mapping and quantifying contemporary vertical land motion (VLM) at continental scales has long been a challenge due to the absence of gridded observational products covering these large domains. Here, we fill this gap by using...

We generalize the additive constrained Gaussian process framework to handle interactions between input variables while enforcing monotonicity constraints everywhere on the input space. The block-additive structure of the model is particularly suitable in the presence of interactions, while maintaining tractable computations. In addition, we develop...

The vulnerability of small islands in the Lesser Antilles to coastal erosion and submersion is particularly pronounced, due to their occasional exposure to tropical storms and hurricanes. These meteorological events unleash energetic waves and increase water levels, with substantial modifications of the coastline playing a crucial role in the long-...

This article introduces funGp, an R package which handles regression problems involving multiple scalar and/or functional inputs, and a scalar output, through the Gaussian process model. This is particularly of interest for the design and analysis of computer experiments with expensive-to-evaluate numerical codes that take as inputs regularly sampl...

Malawi, a landlocked country characterized by its mountainous terrain crisscrossed by the Great Rift Valley and Lake Malawi, is facing an increasing threat of landslides primarily triggered by heavy rainfall from tropical cyclones and depressions. While there are general landslide susceptibility maps available on a global and continental scale, Mal...

Coastal erosion and flooding are projected to increase during the 21 st century due to sea-level rise (SLR). To prevent adverse impacts of unmanaged coastal development, national organizations can apply a land protection policy, which consists of acquiring coastal land to avoid further development. Yet, these reserved areas remain exposed to floodi...

Machine learning (ML) models have become key ingredients for digital soil mapping. To improve the interpretability of their prediction, diagnostic tools have been developed like the widely used local attribution approach known as ‘SHAP’ (SHapley Additive exPlanation). However, the analysis of the prediction is only one part of the problem and there...

The estimation of mixture models is a key to understanding and visualizing the distribution of multivariate data. Most approaches to learning mixture models involve likelihoods and are not adapted to distributions with finite support or without a well-defined density function. This study proposes the Augmented Quantization method, which is a reform...

Quantization summarizes continuous distributions by calculating a discrete approximation. Among the widely adopted methods for data quantization is Lloyd's algorithm, which partitions the space into Vorono\"i cells, that can be seen as clusters, and constructs a discrete distribution based on their centroids and probabilistic masses. Lloyd's algori...

In the context of underground construction projects such as large-scale linear projects, knowledge of subsoil geotechnical properties is of major importance. An effective way to analyze and represent the variability of these properties is to use geostatistical methods. Despite the good performance of such methods, their use is not yet widespread in...

Given recent scientific advances, coastal flooding events can be modelled even in complex environments. However, such models are computationally expensive, preventing their use for forecasting. At the same time, metamodelling techniques have been explored for coastal hydrodynamics, showing promising results. Developing such techniques for predictin...

Purpose Fine sediment deposition is an important component of the catchment sediment budget and affects river morphology, biology, and contaminant transfer. However, the driving factors of fine sediment deposition remain poorly understood at the catchment scale, limiting our ability to model this process. Methods Fine sediment deposition and river...

Visualization is an essential operation when assessing the risk of rare events such as coastal or river floodings. The goal is to display a few prototype events that best represent the probability law of the observed phenomenon, a task known as quantization. It becomes a challenge when data is expensive to generate and critical events are scarce, l...

In the context of underground construction projects, the knowledge of the urban subsoil is of major importance. This article focuses on the development of a 3D geostatistical modelling of the pressuremeter tests applied on a section of the Grand Paris Express. The spatial variability of the geotechnical behavior is studied through a comparison betw...

Metamodelling techniques (also referred to as surrogate modelling) have shown high performance to overcome the computational burden of numerical hydrodynamic models for fast prediction of key indicators of marine flooding (e.g. total flooded area). To predict flood maps (e.g. spatial distribution of maximum value of water depth during a flood event...

Land reclamation in the Maldives is widespread. Current land reclamation practices, however, lack a systematic approach to anticipate sea-level rise and do not account for local flood risk differences to inform location and design choices. To address these limitations, this paper applies two decision-support tools: a hazard threshold analysis, and...

The metamodel-based approach (also referred to as the surrogate approach) is commonly applied to overcome the computational burden of numerical models that are used to simulate the evolution of reservoir fluids and pressures in response to any production scheme. In this study, we propose an adaptation of this approach for aquifer thermal energy sto...

Metamodelling techniques have shown high performance to overcome the computational burden of numerical hydrodynamic models for fast prediction of key indicators of marine flooding (e.g. total flooded area). To predict flood maps (e.g. spatial distribution of maximum value of water depth during a flood event), a commonly-used approach is to rely on...

Process-based projections of the sea-level contribution from land ice components are often obtained from simulations using a complex chain of numerical models. Because of their importance in supporting the decision-making process for coastal risk assessment and adaptation, improving the interpretability of these projections is of great interest. To...

We provide a computationally-efficient scheme for the estimation of joint extremes of significant wave height (Hs) and wind speed (U) for tropical cyclones. The method incorporates the simple spatial extremes method (STM-E) of Wada et al., 2019 (for spatial extremes of each of Hs and U) and the conditional extremes model of Heffernan and Tawn, 2004...

Getting a deep insight into the role of coastal flooding drivers is of great interest for the planning of adaptation strategies for future climate conditions. Using global sensitivity analysis, we aim to measure the contributions of the offshore forcing conditions (wave–wind characteristics, still water level and sea level rise (SLR) projected up t...

Visualization is an essential operation when assessing the risk of rare events such as coastal or river floodings. The goal is to display a few prototype events that best represent the probability law of the observed phenomenon, a task known as quantization. It becomes a challenge when data is expensive to generate and critical events are scarce. I...

Process-based projections of the sea-level contribution from land ice components are often obtained from simulations using a complex chain of numerical models. Because of their importance in supporting the decision-making process for coastal risk assessment and adaptation, improving the interpretability of these projections is of great interest. To...

Coastal communities are currently facing the challenge of climate change and coastal retreat. While scientists are moving towards ensemble-modelling approaches to address uncertainties on shoreline evolution predictions, they rarely account for the stochastic nature of wave conditions across a variety of temporal scales (e.g., daily, weekly, season...

This contribution focuses on the methodology adopted during the GEMMAP[*] project to assess landslide hazard at national scale (i.e. 1:250,000) for Malawi, a landlocked country in southeastern Africa. This country is characterized by a large diversity of landscape and a topography composed of mountains, hills and plateaus, crossed by the Great Rift...

Coastal communities are currently facing the challenge of climate change and coastal retreat. While scientists are moving towards ensemble-modelling approaches to address uncertainties on shoreline evolution predictions, they rarely account for the stochastic nature of wave conditions across a variety of temporal scales (e.g., daily, weekly, season...

Model uncertainties are generally integrated in environmental long-running numerical simulators via a categorical variable. By focusing on Gaussian process (GP) models, we show how different categorical kernel models (exchangeable, ordinal, group, etc.) can bring valuable insights into the correlation of the simulator output values computed for dif...

Fault zones (FZ) in porous reservoirs used for diverse underground activities are complex and heterogeneous geological systems generally constituted of one (or several) fault cores (FC) surrounded by damage zones (DZ). The latter compartment is characterized by a distribution of fractures, which can strongly affect the sustainable injection pressur...

Occurrences of tropical cyclones at a location are rare, and for many locations, only short periods of observations or hindcasts are available. Hence, estimation of return values (corresponding to a period considerably longer than that for which data are available) for cyclone-induced significant wave height (SWH) from small samples is challenging....

Occurrences of tropical cyclones at a location are rare, and for many locations, only short periods of observations or hindcasts are available. Hence, estimation of return values (corresponding to a period considerably longer than that for which data is available) for cyclone-induced significant wave height (SWH) from small samples is challenging....

As low-lying coastal areas can be impacted by flooding caused by dynamic components that are dependent on each other (wind, waves, water levels—tide, atmospheric surge, currents), the analysis of the return period of a single component is not representative of the return period of the total water level at the coast. It is important to assess a join...

Le groupe MEZAP (Méthode d’Evaluation du Zonage de l’Aléa chute de Pierres), pour le compte du Ministère de l’Ecologie propose une évolution des méthodes d’évaluation de l’aléa rocheux dans le cadre de PPR (Plan de Prévention des Risques) ou de PAC (Porté à connaissance). Dans ce cadre, une importante base de données (BdD) d’évènements documentés a...

Getting a deep insight into the role of coastal flooding drivers is of high interest for the planning of adaptation strategies for future climate conditions. Using global sensitivity analysis, we aim to measure the contributions of the offshore forcing conditions (wave/wind characteristics, still water level and sea level rise (SLR) projected up to...

Given recent scientific advances, coastal flooding events can be properly modelled. Nevertheless, such models are computationally expensive (requiring many hours), which prevents their use for forecasting and warning. In addition, there is a gap between the model outputs and information actually needed by decision makers. The present work aims to d...

Surrogate models are often used to replace costly-to-evaluate complex coastal codes to achieve substantial computational savings. In many of those models, the hydrometeorological forcing conditions (inputs) or flood events (outputs) are conveniently parameterized by scalar representations, neglecting that the inputs are actually time series and tha...

Surrogate models are often used to replace costly-to-evaluate complex coastal codes to achieve substantial computational savings. In many of those models, the hydrometeorological forcing conditions (inputs) or flood events (outputs) are conveniently parameterized by scalar representations, neglecting that the inputs are actually time series and tha...

Sandy shorelines morphodynamics responds to a myriad of processes interacting at different spatial and temporal scales, making shoreline predictions challenging. Shoreline modeling inherits uncertainties from the primary driver boundary conditions (e.g., sea‐level rise and wave forcing) as well as uncertainties related to model assumptions and/or m...

Global mean sea level rise and its acceleration are projected to aggravate coastal erosion over the 21st century, which constitutes a major challenge for coastal adaptation. Projections of shoreline retreat are highly uncertain, however, namely due to deeply uncertain mean sea level projections and the absence of consensus on a coastal impact model...

Non-stationary extreme value analysis is a powerful framework to address the problem of time evolution of extremes and its link to climate variability as measured by different climate indices CI (like North Atlantic Oscillation NAO index). To model extreme sea levels (ESLs), a widely-used tool is the non-stationary Generalized Extreme Value distrib...

The Maldives, with one of the lowest average land elevations above present-day mean sea level, is among the world regions that will be the most impacted by mean sea-level rise and marine extreme events induced by climate change. Yet, the lack of regional and local information on marine drivers is a major drawback that coastal decision-makers face t...

Predicting long-term beach morphodynamics is one of the largest challenge for Coastal Scientists. Limited knowledge of physical processes, modelling assumptions, lack of data, prediction of the future forcing factors, and future climate scenarios make model predictions hardly reliable. Probabilistic approaches allow quantifying the level of confide...

Occurrences of tropical cyclones at a location are rare, and for many locations, only short periods of observations or hindcasts are available. Hence, estimation of return values (corresponding to a period considerably longer than that for which data is available) for cyclone-induced significant wave height (SWH) from small samples is challenging....

Global scale assessments of coastal flood damage and adaptation costs under 21st century sea-level rise are associated with a wide range of uncertainties, including those in future projections of socioeconomic development (shared socioeconomic pathways (SSP) scenarios), of greenhouse gas concentrations (RCP scenarios), and of sea-level rise at regi...

The treatment of uncertainty using extra-probabilistic approaches, like intervals or p-boxes, allows for a clear separation between epistemic uncertainty and randomness in the results of risk assessments. This can take the form of an interval of failure probabilities; the interval width W being an indicator of "what is unknown". In some situations,...

Motivated by risk assessment of coastal flooding, we consider time-consuming simulators with a spatial output. The aim is to perform sensitivity analysis (SA), quantifying the influence of input parameters on the output. There are three main issues. First, due to computational time, standard SA techniques cannot be directly applied on the simulator...

Global mean sea-level rise and its acceleration are projected to aggravate coastal erosion over the 21st century, which constitutes a major challenge for coastal adaptation. Projections of shoreline retreat are highly uncertain, however, namely due to deeply uncertain mean sea-level projections and the absence of consensus on a coastal impact model...

Expert judgment is widely used to inform forecasts (e.g. using the 5th, 50th and 95th percentile of some variable of interest) for a large variety of applications related to environment systems. This task can rely on Cooke’s classical model (CM) within the probabilistic framework, and consists in combining expert information after a preliminary ste...

In 2017, Irma and Maria highlighted the vulnerability of small islands to cyclonic events and the necessity of advancing the forecast techniques for cyclone-induced marine flooding. In this context, this paper presents a generic approach to deriving time-varying inundation forecasts from ensemble track and intensity forecasts applied to the case of...

Chronic erosion of sandy coasts is a continuous potential threat for the growing coastal communities worldwide. The prediction of shoreline evolution is therefore key issue for robust decision making worldwide, especially in the context of climate change. Shorelines respond to various complex processes interacting at several temporal and spatial sc...

Increasing our capacity to predict extreme storm surges is one of the key issues in terms of coastal flood risk prevention and adaptation. Dynamically forecasting storm surges is computationally expensive. Here, we focus on an alternative data-driven approach and set up a weather-type statistical downscaling for daily maximum storm surge (SS) predi...

A key point of landslide hazard assessment is the estimation of their runout. Empirical relations linking angle of reach to volume can be used relatively easily, but they are generally associated with large uncertainties as they do not consider the topographic specificity of a given study site. On the contrary, numerical simulations provide more de...

Pre-existing faults cross-cutting caprock formations constitute potential leakage pathways during geological CO2 sequestration. When the fault filling material is calcite-rich, dissolution of the fault minerals is expected to occur causing the mechanical weakening of the fault or, even worse, its reactivation. In turn, these chemical-mechanical pro...

Coastal floods are driven by many hydro-meteorological forcing factors, among which are mean sea levels, tides, atmospheric storm surges, and waves. Depending on these conditions, wave overtopping may occur and, in some cases, lead to a significant flood. In the present study, we investigate the effect of the stochastic character of waves on the fl...