Philippe Gourbesville

Spatial Global Sensitivity Analysis of High Resolution classified topographic data use in 2D urban flood modelling

This paper presents a spatial Global Sensitivity Analysis (GSA) approach in a 2D shallow water equations based High Resolution (HR) flood model. The aim of a spatial GSA is to produce sensitivity maps which are based on Sobol index estimations. Such an approach allows to rank the effects of uncertain HR topographic data input parameters on flood model output. The influence of the three following parameters has been studied: the measurement error, the level of details of above-ground elements representation and the spatial discretization resolution. To introduce uncertainty, a Probability Density Function and discrete spatial approach have been applied to generate 2,000 DEMs. Based on a 2D urban flood river event modelling, the produced sensitivity maps highlight the major influence of modeller choices compared to HR measurement errors when HR topographic data are used. The spatial variability of the ranking is enhnaced. Sobol index maps produced by a spatial GSA rank in space the weight of each uncertain parameter on the variability of output parameter of interest.The weight of the modeller choices, with respect to the influence of HR dataset accuracy is enhanced.Added value is for modeller to better understand limits of his model.Requirements and limits for this approach are related to subjectivity of choices and to computational cost.

Citywide multi-grid urban flood modelling: the July 2012 flood in Beijing

Global flood management is a major issue for most cities which have to deal with worsening factors such as climate change and fast urban growth. Computer models have been used to model and understand urban flooding on a local scale in cities (25–50 km2). It has been practically impossible to model bigger cities in one go in sufficiently high resolution due to the heavy computations involved. The present paper describes a new modelling approach for urban flooding which allows modelling on large city scale (1000 km2) while keeping sufficient resolution, e.g. 5 m or 10 m grid. The multicell approach is applied for the city of Beijing for July 21st, 2012 flood event. Model results are compared to testimonials from the 2012 event. Comparison to traditional 2D urban flood computations shows that the multicell approach is much faster than standard detailed models while keeping a suitable level of precision.

On the Design of an Intelligent Sensor Network for Flash Flood Monitoring, Diagnosis and Management in Urban Areas Position Paper☆

Abstract We propose an intelligent sensor system based on a new sensing methodology, relying also on 3D map reconstruction techniques, for computing with high precision, in real-time and without human intervention the parameters needed for stream-flow computa- tion: water levels, morphology of the streams of all potentially flooded areas by each controlled stream. The collected data will be continuously transmitted, through a communication infrastructure, to software agents designed to compute the stream-flow and to quantify the spatial distribution of flood risk for each controlled watershed. The computed risks, together with other data coming from other sources (barometric sensors, camera operators of public organizations, emergency agencies, private citizens), will be analyzed by a diagnostic decision system implementing a risk-alert scheduling strategy. This system will be able to diagnose the health state of the controlled environment and to define specialized alarm levels for each potentially interested area that will be used to alert all citizens (ubiquity) locally present (alerting locality).

Hydro-meteorological drought assessment under climate change impact over the Vu Gia–Thu Bon river basin, Vietnam

ABSTRACT Hydro-meteorological drought was assessed with respect to climate change over an estuary catchment Vu Gia-Thu Bon in Central Vietnam, which economy is dependent on agriculture. The fully-distributed hydrological model MIKE SHE was used to simulate river flow over the study region for the period 1991–2010. Drought were assessed using the Standardized Precipitation Index and the Standardized Runoff Index. The future climate was studied using the regional climate model Weather Research and Forecasting by downscaling an ensemble of three global climate models – CCSM3.0, ECHAM5 and MIROC-medium resolution over current (1961–1990) and future climates (2011–2040), under the A2 emissions scenario. The results suggest that, despite hotter and wetter future climate, the area is likely to suffer more from severe and extreme droughts, increasing about 100% in the median range for drought characteristics. Thus, there is a need for proper adaptation and planning for water resources management in this region.

Xynthia Flood, Learning from the Past Events—Introducing a FRI to Stakeholders

Extreme flood events in recent years create a need to better understand the risks. Local communities are vulnerable to extreme flooding and more often they are looking on how to learn from past events. This provides them a way to be more prepared and to reduce flood damage. The FP7 PEARL R&D project (http://www.pearl-fp7.eu/about-pearl/) case study Châtelaillon-Plage, located at the Atlantic coast of France, is a very good example of how local community could increase flood resilience and be more prepared for the future coastal submersion events. For the case study, an analysis of extreme storm surge event Xynthia (occurred on February 27–28, 2010) is performed in order to define a generic, new index characterizing a resilience to flood. Here, the Flood Resilience Index (FRI) is employed as a new communication tool with local stakeholders. The tool enables mapping of evaluated flood resilience for each building in the case study area. In this way, the existing flood maps are overlapped with evaluated resilience in different dimensions of urban system. The simulation scenarios take into account the protection structures constructed as a part of the Plan of Measures implemented after the event. For this purpose, the new flood maps are created and new FRI are evaluated. In this paper, the authors will present the importance of analysis of past events, the usability of FRI in the stakeholder communication and compare flood resilience of case study before and after new structural measures. The research focuses also on examination of present flood management strategies and their effectiveness in decreasing flood damage and evaluation of flood resilience.

Global Sensitivity Analysis with 2D Hydraulic Codes: Application on Uncertainties Related to High-Resolution Topographic Data

Technologies such as aerial photogrammetry allow production of 3D topographic data including complex environments such as urban areas. Therefore, it is possible to create High-Resolution (HR) Digital Elevation Models (DEM) incorporating thin above-ground elements influencing overland flow paths. Although this category of “big data” has a high level of accuracy, there are still errors in measurements and hypothesis under DEM elaboration. Moreover, operators look for optimizing spatial discretization resolution in order to improve flood model computation time. Errors in measurement, errors in DEM generation, and operator choices for inclusion of this data within 2D hydraulic model, might influence the results of flood model simulations. These errors and hypothesis may influence significantly the flood modeling results variability. The purpose of this study is to investigate uncertainties related to (i) the own error of high-resolution topographic data and (ii) the modeler choices when including topographic data in hydraulic codes. The aim is to perform a Global Sensitivity Analysis (GSA) which goes through a Monte-Carlo uncertainty propagation, to quantify impact of uncertainties, followed by “Sobol” indices computation, to rank influence of identified parameters on result variability. A process using a coupling of an environment for parametric computation (Promethee) and a code relying on 2D shallow water equations (FullSWOF_2D) has been developed (P-FS tool). The study has been performed over the lower part of the Var river valley using the estimated hydrograph of a 1994 flood event. HR topographic data has been made available for the study area, which is 17.5 km2, by Nice municipality. Three uncertain parameters were studied: the measurement error (var. E), the level of details of above-ground element representation in DEM (buildings, sidewalks, etc.) (var. S), and the spatial discretization resolution (grid cell size for regular mesh) (var. R). Parameter var. E follows a probability density function, whereas parameters var. S and var. R are discrete operator choices. Combining these parameters, a database of 2,000 simulations has been produced using P-FS tool implemented on a high-performance computing structure. In our study case, the output of interest is the maximal water surface reached during simulations. A stochastic sampling on the produced result database has allowed to perform a Monte-Carlo approach. Sensitivity index have been produced at given points of interest, enhancing the relative weight of each uncertain parameters on variability of calculated overland flow. Perspectives for Sobol index maps production are brought to light.

Deterministic Hydrological Model For Flood Risk Assessment Of Mexico City

Mexico City is facing problems of flooding in some areas at certain times of the year, causing important losses and damages on properties and residents including some casualties. Therefore, it is important to carry out a flood risk assessment in the catchment of Mexico City and estimate damages of probable flood events. However, limited data of observed discharges and water depths in the main rivers of the city are available, and this represents an obstacle for the understanding of flooding in Mexico City. The premise of this study is that with the limited data and resources available, the catchment can be represented to an acceptable degree by the construction of a deterministic hydrological model of the Mexico City basin. The objective of the developed tool is to provide an efficient support to management of the flood processes by predicting the behavior of the catchment for different rainfall events and flood scenarios. The capability of a model based on MIKE SHE modeling system for the Mexico City catchment was evaluated by comparing the observed data and the simulation results during a year after a careful development based on the most important parameters for characterizing the processes. Significant and operational results (>0.75 for Nash Sutcliffe coefficient) have been obtained on one of the major sub-catchments of the Mexico basin. These results demonstrate the interest to implement a deterministic hydrological model for assessing flood risks in a dense urban environment where data availability is limited. The developed model can be used for assessing the risks and designing some protection measures.

Use of Standard 2D Numerical Modeling Tools to Simulate Surface Runoff Over an Industrial Site: Feasibility and Comparative Performance Survey Over a Test Case

Intense pluvial generated surface flow over an industrial facility represents a flood risk requiring an appropriated approach for risk assessment. Runoff over industrial site might have flow regime changes, wild flooding/drying extend, as well as small water deep properties. This makes standard bidimensional (2D) numerical surface flow models use particularly challenging. Indeed, numerical treatment of these properties might not be specifically supported by models. Furthermore, it gets close by their traditional application domain limits. Accordingly, an assessment of this group of numerical tool use for such a purpose needs to be in detailed studied to evaluate feasibility, performance, and relevance of their use in this context. This chapter aims to focus on common 2D numerical modeling tools use for application over an industrial plant test case to simulate surface runoff scenarios. Feasibility of such an approach is hereby studied. Performances and relevance of this attempt are evaluated. Our test case has specificities of real industrial plants in terms of domain extend, topography, and surface drainage structures. Tested scenarios state a uniform net 100 mm 1 h long rainfall event in a context of storm water sewer pipe failure. Selected tested models were a 2D finite differences diffusive wave model and an array of different 2D shallow water equation [2D shallow water equations (SWEs)]–based models. Comparison has been conduced over computed maximal water depth and water deep evolution. Results reveal a feasibility of these tools application for the studied specific purpose. They underline the necessity of a highly fine spatial and temporal discretization. Tested categories of average 2D SWEs–based models show in a large extend similar results in water depth calculation. Used indicator of results reliability estimation did not point out major critical aspects in calculation. Limits inherent of these categories of models use for this domain of application are underlined. Relevance of this approach is raised up.

Coastal current prediction using CMA evolution strategies

We propose a data-driven evolutionary approach to the modeling of marine currents in the Bay of Monaco. The CMA (Covariance Matrix Adaptation) evolution strategy is used to optimize the parameters of a predictive model that may be used as a surrogate of expensive and time-consuming finite-element simulations. The models obtained are reasonably accurate and easy to interpret.

Flood Risk Assessment: A View of Climate Change Impact at Vu Gia Thu Bon Catchment, Vietnam

Vietnam is located in the region of the Southeast Asia monsoon. Most of the population work in agriculture and inhabitants essentially concentrate on the coastal plain, Vietnam is one of the countries most heavily affected by the consequences of climate change. For these reasons, predicting the potential damages due to extreme flood events, especially under climate change impact is mighty necessary for the coastal area in this country. This paper will present the potential risk maps in Vu Gia Thu Bon catchment, the largest river system in Viet Nam central. These flood risk maps were built with tree GCMs under A2 scenario at the end of the twenty-first century by overlapping the flood hazard and land use map in 30 m resolution. The result is hoped to provide adequate scientific evidence to help local authority make suitable strategies for adapting with the variation of climate in the future.