Efficient pan-European river flood hazard modelling through a combination of statistical and physical models

Mapping Intimacies ◽

10.5194/nhess-2017-4 ◽

2017 ◽

Cited By ~ 1

Author(s):

Dominik Paprotny ◽

Oswaldo Morales-Nápoles ◽

Sebastiaan N. Jonkman

Keyword(s):

Return Period ◽

Flood Hazard ◽

Physical Models ◽

Geographical Information ◽

Computational Time ◽

Joint Research ◽

Simplified Approach ◽

The Future ◽

Prone Area ◽

Flood Prone Area

Abstract. Flood hazard is being analysed with ever-more complex models on national, continental and global scales. In this paper we investigate an alternative, simplified approach, which combines statistical and physical models in order to carry out flood mapping for Europe. Estimates of extreme river discharges made using a Bayesian Network-based model from a previous study are employed instead of rainfall-runoff models. Those data provide flood scenarios for simulation of water flow in European rivers with a catchment area above 100 km2. The simulations are performed using a one-dimensional steady-state hydraulic model and the results are post-processed using geographical information system (GIS) software in order to derive flood zones. This approach is validated by comparison with Joint Research Centre's (JRC) pan-European map and five local flood studies from different countries. Overall, both our and JRC's maps have similar performance in recreating flood zones of local maps. The simplified approach achieved similar level of accuracy, while substantially reducing the computational time. The paper also presents the summarized results from the flood hazard maps, including future projections. We find that relatively small changes in flood hazard are observed (increase of flood zones area by 2–4 %). However, when current flood protection standards are taken into account, there is a sharp increase in flood-prone area in the future (28–38 % for a 1000 year return period). This is because in many parts of Europe river discharge with the same return period is projected to increase in the future, thus making the protection standards insufficient.

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Efficient pan-European river flood hazard modelling through a combination of statistical and physical models

Natural Hazards and Earth System Science ◽

10.5194/nhess-17-1267-2017 ◽

2017 ◽

Vol 17 (7) ◽

pp. 1267-1283 ◽

Cited By ~ 8

Author(s):

Dominik Paprotny ◽

Oswaldo Morales-Nápoles ◽

Sebastiaan N. Jonkman

Keyword(s):

Return Period ◽

Flood Hazard ◽

Physical Models ◽

Geographical Information ◽

Computational Time ◽

Joint Research ◽

Simplified Approach ◽

Run Off ◽

The Future ◽

Prone Area

Abstract. Flood hazard is currently being researched on continental and global scales, using models of increasing complexity. In this paper we investigate a different, simplified approach, which combines statistical and physical models in place of conventional rainfall-run-off models to carry out flood mapping for Europe. A Bayesian-network-based model built in a previous study is employed to generate return-period flow rates in European rivers with a catchment area larger than 100 km2. The simulations are performed using a one-dimensional steady-state hydraulic model and the results are post-processed using Geographical Information System (GIS) software in order to derive flood zones. This approach is validated by comparison with Joint Research Centre's (JRC) pan-European map and five local flood studies from different countries. Overall, the two approaches show a similar performance in recreating flood zones of local maps. The simplified approach achieved a similar level of accuracy, while substantially reducing the computational time. The paper also presents the aggregated results on the flood hazard in Europe, including future projections. We find relatively small changes in flood hazard, i.e. an increase of flood zones area by 2–4 % by the end of the century compared to the historical scenario. However, when current flood protection standards are taken into account, the flood-prone area increases substantially in the future (28–38 % for a 100-year return period). This is because in many parts of Europe river discharge with the same return period is projected to increase in the future, thus making the protection standards insufficient.

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Analysis of the exposure of Polish lakes to flood risk

Limnological Review ◽

10.2478/limre-2015-0005 ◽

2015 ◽

Vol 15 (1) ◽

pp. 39-50

Author(s):

Anna Pasiecznik-Dominiak ◽

Andrzej Tiukało ◽

Grzegorz Dumieński

Keyword(s):

Flood Risk ◽

Flood Hazard ◽

Risk Level ◽

Resilience Theory ◽

Risk Area ◽

The Social ◽

Prone Area ◽

Extreme Hazards ◽

Flood Prone Area

Abstract Flooding constitutes one of the main natural hazards in Poland, which causes enormous social, economic and environmental losses. The main causes of the occurrence of floods include intensive rainfall, rapid melting of snow and ice cover, as well as strong gusts of wind from the sea. Based on the resilience theory (resistance, elasticity), which constitutes an efficient tool for the description of the social-ecological system capability or components thereof to mitigate the effects of dangerous events, as well as the capability of reconstructing and adapting the system to new conditions, the authors have analysed the exposure of Polish lakes to flood risks with a probability of occurrence Q0.2%, Q1% and Q10%. In order to determine the level of exposure of lakes to the risk of flooding by flood waters, studies were conducted using the flood hazard and flood risk maps which were developed under the Project entitled “IT System of the Country’s Protection against Extreme Hazards”. The result of the efforts of the group of authors is the determination of the number of lakes, which are located in the flood risk area Q0.2%, Q1% and Q10%, including division into risk level groups (low, moderate and high). The results presented in the paper may constitute a contribution to further, more detailed studies concerning assessment of the vulnerability of Polish lakes located in the flood prone area.

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Machine-Learning blends of geomorphic descriptors: value and limitations for flood hazard assessment across large floodplains

10.5194/nhess-2021-253 ◽

2021 ◽

Author(s):

Andrea Magnini ◽

Michele Lombardi ◽

Simone Persiano ◽

Antonio Tirri ◽

Francesco Lo Conti ◽

...

Keyword(s):

Machine Learning ◽

Decision Tree ◽

Recent Literature ◽

Flood Hazard ◽

Open Problems ◽

Prone Area ◽

Tree Models ◽

Multivariate Approaches ◽

Flood Prone Area ◽

Flood Prone Areas

Abstract. Recent literature shows several examples of simplified approaches that perform flood hazard (FH) assessment and mapping across large geographical areas on the basis of fast-computing geomorphic descriptors. These approaches may consider a single index (univariate) or use a set of indices simultaneously (multivariate). What is the potential and accuracy of multivariate approaches relative to univariate ones? Can we effectively use these methods for extrapolation purposes, i.e. FH assessment outside the region used for setting up the model? Our study addresses these open problems by considering two separate issues: (1) mapping flood-prone areas, and (2) predicting the expected water depth for a given inundation scenario. We blend seven geomorphic descriptors through Decision Tree models trained on target FH maps, referring to a large study area (≈105 km2). We discuss the potential of multivariate approaches relative to the performance of a selected univariate model and on the basis of multiple extrapolation experiments, where models are tested outside their training region. Our results show that multivariate approaches may (a) significantly enhance flood-prone area delineation (overall accuracy: 93 %) relative to univariate ones (overall accuracy: 84 %), (b) provide accurate predictions of expected inundation depths (determination coefficient ≈0.7), and (c) produce encouraging results in extrapolation.

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Urban Flood Control in Sringin Catchment, Semarang City, Central Java Province, Indonesia

Journal of the Civil Engineering Forum ◽

10.22146/jcef.33886 ◽

2018 ◽

Vol 4 (2) ◽

pp. 191

Author(s):

Ngo Pheaktra ◽

Istiarto Istiarto ◽

Rachmad Jayadi

Keyword(s):

Return Period ◽

Flood Control ◽

Flow Analysis ◽

Drainage System ◽

Urban Flood ◽

Central Java ◽

Design Rainfall ◽

Prone Area ◽

Lowland Area ◽

Flood Prone Area

Sringin is the lowland area located in Semarang city which has been vulnerable to rob flooding from the Java Sea along with flood triggered by the intense amount of rainfall. The case study will further discuss the hydrological analysis, transformation of rational method into flow hydrograph with the design rainfall of 25-year return period, and unsteady flow analysis by HEC-RAS 5.0.3 under existing condition and design condition. The result shows that the design rainfall of 25-year return period measures 173 mm in vertical length and data collected from the office of public work, Semarang city can be used to implement the design scenario with normalization of drainage system and the increase of levee with the freeboard up to 0.75 m is proved to be the solution to the flood inundation in that flood-prone area while the flood under existing condition has caused excessive discharge at downstream up to 9 hours.

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GIS Based Method for Flood Hazard Assesment in Kobe River Watershed - North Maluku Province

E3S Web of Conferences ◽

10.1051/e3sconf/202132804019 ◽

2021 ◽

Vol 328 ◽

pp. 04019

Author(s):

Nani Nagu ◽

A. Latif Lita ◽

H Bebi ◽

Nurhalis Wahiddin

Keyword(s):

Flood Hazard ◽

Vulnerability Index ◽

Hazard Map ◽

Flood Vulnerability ◽

Flood Susceptibility ◽

Flood Hazard Map ◽

Prone Area ◽

Flood Prone Area ◽

Hierarchy Process ◽

Selection Of

The objectives of this study are to mapping the hazard-prone area and to analyse the flood vulnerability index in Kobe Watershed, Central Halmahera District. In order to determine the optimal selection of weights for the factors that contribute to flood risk, GIS and multi-criteria decision analysis (MCDA) were used in conjunction with the application of the analytical hierarchy process (AHP) method to create the flood hazard map. The flood hazard map was generated by using selected hazard factors including land use, topography, slope, and rainfall pattern. The result shows that the Kobe River basin is a flood-prone area, with 77.46 percent of its land classified as less prone to flooding and 21.41 percent classified as flood-prone. However, only 21.41 percent of its land is classified as flood-prone. Only 1.13 percent of the land is protected from the danger of floods, compared to the whole country. The altitude factor is the most important element influencing flood susceptibility in Weda District, where the majority of the land (16.34 percent) is located at or below sea level, making it particularly vulnerable to flooding.

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PEMETAAN BAHAYA BANJIR LAHAN SAWAH DI KABUPATEN KARAWANG

Jurnal Ilmu Tanah dan Lingkungan ◽

10.29244/jitl.19.1.41-45 ◽

2019 ◽

Vol 19 (1) ◽

pp. 41-45

Author(s):

Tommi Tommi ◽

Baba Barus ◽

Arya Hadi Dharmawan

Keyword(s):

Paddy Field ◽

Flood Hazard ◽

The Other ◽

Flood Mapping ◽

Flood Events ◽

Soil Drainage ◽

Prone Area ◽

High Flood ◽

Flood Prone Area ◽

Hazard Level

Flooding is one of the natural disasters that frequently hit several countries, including Indonesia. Data from the BNPB show of the year 1815 - 2013 ranks first flood disaster events most of the other disasters that as many as 5,394 events. Karawang District was ranked 3rd highest number of flood events in West Java. Nationally data from BNPB show Karawang ranks 8th flood-prone area. The purpose of this study to analyze the level of hazard of flooding the paddy field in Karawang. The method used in analyzing the level of hazard of flooding is done by overlaying and scoring from the paddy fields map, rainfall maps, soil drainage maps, and flood events maps. The results of this study indicate the paddy field in Karawang District which has a high flood hazard level contained in the Telukjambe West, East Telukjambe, and Jayakerta Sub Disctrict. Keywords: Hazard, flood, mapping

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Effects of minor drainage networks on flood hazard evaluation

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-364-192-2014 ◽

2014 ◽

Vol 364 ◽

pp. 192-197 ◽

Cited By ~ 2

Author(s):

A. Domeneghetti

Keyword(s):

Preferential Flow ◽

Flood Hazard ◽

Numerical Models ◽

Drainage System ◽

Hazard Evaluation ◽

Correct Identification ◽

Drainage Network ◽

Drainage Networks ◽

Prone Area ◽

Flood Prone Area

Abstract. Scientific literature reports a plethora of numerical tools of different complexity (e.g. 1D, 2D raster-based or full 2D models) for flood hazard and flood risk evaluation. The correct identification of the appropriate model still represents a key aspect in the overall flood hazard process even though the potential of these modelling instruments are increased by the availability of high computational resources and by the amount of high-resolution topographic data provided by recent survey techniques. Given this context the present analysis investigates the effects of minor drainage networks on the estimation of flood hazard in a flood-prone area along the Enza River, close to the village of Sorbolo a Levante (RE, northern Italy). By means of a full 2D hydraulic model (Telemac-2D), the effects of the drainage system is analysed using three unstructured meshes with different degrees of complexity: (1) the minor drainage system allows the possibility to convey water outside the study area (REF); (2) the drainage system is reproduced only in terms of preferential flow-paths (REF-noFlow); (3) the drainage network is completely neglected (REF-noDN). The analysis indicates that the maximum flood extent seems not to be influenced by the mesh schematization, while water depths and the total volume are significantly related to the model schematization. Even if this analysis refers to a specific case study and further investigations are needed, it shows the fundamental role of the drainage network in controlling water depth distribution and the duration of the inundation, which should be accurately reproduced by numerical models.

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Multi-Criteria Decision Making for Vulnerability Mapping of Flood Hazard: A Case Study of Pune City

10.21523/gcj5.18020105 ◽

2019 ◽

Vol 2 (1) ◽

pp. 41-52

Author(s):

Nitin Mundhe

Keyword(s):

Decision Making ◽

Flood Hazard ◽

Geographical Information ◽

Multi Criteria Decision Making ◽

Flood Hazards ◽

Very High Frequency ◽

Flood Vulnerability ◽

Natural Risk ◽

The Town

Floods are natural risk with a very high frequency, which causes to environmental, social, economic and human losses. The floods in the town happen mainly due to human made activities about the blockage of natural drainage, haphazard construction of roads, building, and high rainfall intensity. Detailed maps showing flood vulnerability areas are helpful in management of flood hazards. Therefore, present research focused on identifying flood vulnerability zones in the Pune City using multi-criteria decision-making approach in Geographical Information System (GIS) and inputs from remotely sensed imageries. Other input data considered for preparing base maps are census details, City maps, and fieldworks. The Pune City classified in to four flood vulnerability classes essential for flood risk management. About 5 per cent area shows high vulnerability for floods in localities namely Wakdewadi, some part of the Shivajinagar, Sangamwadi, Aundh, and Baner with high risk.

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Return Period Evaluation of the Largest Possible Earthquake Magnitudes in Mainland China Based on Extreme Value Theory

Sensors ◽

10.3390/s21103519 ◽

2021 ◽

Vol 21 (10) ◽

pp. 3519

Author(s):

Yanbing Bai ◽

Ning Ma ◽

Shengwang Meng

Keyword(s):

Earthquake Engineering ◽

Return Period ◽

Extreme Value Theory ◽

Threshold Model ◽

Mainland China ◽

Value Theory ◽

Extreme Value ◽

Geographical Information ◽

Geographical Regions ◽

The Right

The largest possible earthquake magnitude based on geographical characteristics for a selected return period is required in earthquake engineering, disaster management, and insurance. Ground-based observations combined with statistical analyses may offer new insights into earthquake prediction. In this study, to investigate the seismic characteristics of different geographical regions in detail, clustering was used to provide earthquake zoning for Mainland China based on the geographical features of earthquake events. In combination with geospatial methods, statistical extreme value models and the right-truncated Gutenberg–Richter model were used to analyze the earthquake magnitudes of Mainland China under both clustering and non-clustering. The results demonstrate that the right-truncated peaks-over-threshold model is the relatively optimal statistical model compared with classical extreme value theory models, the estimated return level of which is very close to that of the geographical-based right-truncated Gutenberg–Richter model. Such statistical models can provide a quantitative analysis of the probability of future earthquake risks in China, and geographical information can be integrated to locate the earthquake risk accurately.

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