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Using risk analysis for flood protection assessment
This book explores the benefits of using risk analysis techniques in the evaluation of flood protection structures, and examines the results of the environmental impact assessment for selected planned flood protection projects. The objective of the book is to propose a methodology for environmental impact assessment in water management. In more detail, flood mitigation measures are investigated with the aim of selecting the best option for the approval process. This methodology is intended to streamline the process of environmental impact assessment for structures in the field of the water management. The book?s environmental impact assessment system for water management structures analyzes the respective risks for different options. The results are intended to support the selection of future projects that pose minimum risks to the environment. Comparison of alternatives and designation of the optimal variant are implemented on the basis of selected criteria that objectively describe the characteristics of the planned alternatives and their respective impacts on the environment. The proposed Guideline for environmental impact assessment of flood protection objects employs multi-parametric risk analysis, a method intended to not only enhance the transparency and sensitivity of the evaluation process, but also successfully addresses the requirements of environmental impact assessment systems in the European Union. These modifications are intended to improve the outcomes of the environmental impact assessment, but may also be applied to other infrastructure projects. The case study proves that the primary aim? to improve transparency and minimize subjectivity in the environmental impact assessment process specific to flood protection structure projects? is met for the planned project in Kruézlov, Slovakia.
Book
Regional Flood Frequency Analysis of the Sava River in South-Eastern Europe
Regional flood frequency analysis (RFFA) is a powerful method for interrogating hydrological series since it combines observational time series from several sites within a region to estimate risk-relevant statistical parameters with higher accuracy than from single-site series. Since RFFA extreme value estimates depend on the shape of the selected distribution of the data-generating stochastic process, there is need for a suitable goodness-of-distributional-fit measure in order to optimally utilize given data. Here we present a novel, least-squares-based measure to select the optimal fit from a set of five distributions, namely Generalized Extreme Value (GEV), Generalized Logistic, Gumbel, Log-Normal Type III and Log-Pearson Type III. The fit metric is applied to annual maximum discharge series from six hydrological stations along the Sava River in South-eastern Europe, spanning the years 1961 to 2020. Results reveal that (1) the Sava River basin can be assessed as hydrologically homogeneous and (2) the GEV distribution provides typically the best fit. We offer hydrological-meteorological insights into the differences among the six stations. For the period studied, almost all stations exhibit statistically insignificant trends, which renders the conclusions about flood risk as relevant for hydrological sciences and the design of regional flood protection infrastructure.
Journal Article
Remote Sensing Methods for Flood Prediction: A Review
Floods are a major cause of loss of lives, destruction of infrastructure, and massive damage to a country’s economy. Floods, being natural disasters, cannot be prevented completely; therefore, precautionary measures must be taken by the government, concerned organizations such as the United Nations Office for Disaster Risk Reduction and Office for the coordination of Human Affairs, and the community to control its disastrous effects. To minimize hazards and to provide an emergency response at the time of natural calamity, various measures must be taken by the disaster management authorities before the flood incident. This involves the use of the latest cutting-edge technologies which predict the occurrence of disaster as early as possible such that proper response strategies can be adopted before the disaster. Floods are uncertain depending on several climatic and environmental factors, and therefore are difficult to predict. Hence, improvement in the adoption of the latest technology to move towards automated disaster prediction and forecasting is a must. This study reviews the adoption of remote sensing methods for predicting floods and thus focuses on the pre-disaster phase of the disaster management process for the past 20 years. A classification framework is presented which classifies the remote sensing technologies being used for flood prediction into three types, which are: multispectral, radar, and light detection and ranging (LIDAR). Further categorization is performed based on the method used for data analysis. The technologies are examined based on their relevance to flood prediction, flood risk assessment, and hazard analysis. Some gaps and limitations present in each of the reviewed technologies have been identified. A flood prediction and extent mapping model are then proposed to overcome the current gaps. The compiled results demonstrate the state of each technology’s practice and usage in flood prediction.
Journal Article
A review of flood damage analysis for a building structure and contents
As a natural hazard, flood can cause a significant damage to buildings. Buildings are one of the important components of an economy which are providing the necessary space for human activities. In this regard, any considerable changes to their serviceability affect living condition of people locally, regionally, and even globally. Thus, building damage analysis forms a crucial part of a flood risk analysis. This review paper provides an insight into flood damage analysis for a building structure and contents: past works, current state, and required improvements. The discussed buildings include residential, commercial, and industrial types. The methods are divided into two main categories: (1) using real data and empirical models, and (2) using what-if analysis and analytical models. Differences in damage analysis of a building structure and its contents are explained in a separate section. Flood factors influencing the damage to a building structure and its contents are presented. How a method considers some of those flood factors is described. Limitations and shortcomings of each method alongside their advantages and strength are discussed. Lack of reliable data for both model construction and validation is one of the main issues with the methods in both categories. Inability to convey the uncertainty is the other main issue identified in the literature.
Journal Article
Integration of SWAT, SDSM, AHP, and TOPSIS to detect flood-prone areas
Flood is one of the most frightening dangers in the world, which can cause a lot of human and financial losses. In this study, an attempt has been made to create a flood risk map with higher accuracy by using the combination of SWAT, SDSM, AHP, and TOPSIS models. The flood risk map helps to identify areas that have flood potential. Managers and officials can control and reduce human and financial losses caused by floods by using such maps and adopting correct policies. In this study, using the SWAT and SDSM models, the future runoff of the Kashkan basin of Lorestan Province in Iran was simulated for the period from 2049 to 2073. Simulated runoff with different return periods of 2, 5, 10, 25, 50, and 100 years was investigated. According to the obtained results, RCP2.6 was introduced as the most dangerous scenario of this watershed with a runoff forecast of 7715 cubic meters per second. With the help of the obtained flood risk map, sub-basins 22, 24, 28, and 32 representing Khorram Abad and Poldakhter cities were introduced as flood-prone areas of the study area. The simulation of the precipitation, maximum and minimum temperature of the studied basin in the period from 2006 to 2100 showed that the maximum and minimum temperatures can get warmer by 1.3–3 C, and 1 to 2 C can get colder. On the other hand, the rainfall of the entire basin will be able to decrease between 54 and 120 mm. The methods used in this study can also be used to detect flood-prone areas for other parts of the world that have been exposed to sudden floods due to climate change.
Journal Article
Permeability control and flood risk assessment of urban underlying surface: a case study of Runcheng south area, Kunming
Because of climate change and rapid urbanization, urban impervious underlying surfaces have expanded, causing Chinese cities to become strongly affected by flood disasters. Therefore, research on urban flood risks has greatly increased over the past decade, with studies focusing on reducing the risk of flood disaster. From 2012 to 2020, the impervious underlying surface has increased, and the permeable underlying surface has decreased annually in Kunming City. This study was conducted to investigate the impact of continuous changes in the urban underlying surface on flood disasters in the Runcheng area south of Kunming City from 2012 to 2020. We constructed a two-dimensional flood model to conduct flood simulations and flood risk analysis for this area. The relationship between the permeability of the underlying surface and urban flood risk was simulated and analyzed by varying the urban underlying surface permeability (0–60%). The simulation results show that the model can accurately simulate urban waterlogging, and the increase in urban waterlogging risk is related to the underlying surface permeability. Urban flood risk decreases with the increase in permeable underlying surface. The increase rate of flood risk in the part with permeability of 0–35% is greater than that the part with permeability of 35–60%, that is, when the permeability of underlying surface is lower than 35%, the flood risk rate will be higher. We demonstrated the impact of the urban underlying surface permeability on the risk of urban flood disasters, which is useful for urban planning decisions and urban flooding risk controls.
Journal Article
Flood Risk Analysis and Assessment, Applications and Uncertainties: A Bibliometric Review
Studies looking at flood risk analysis and assessment (FRA) reviews are not customary, and they usually approach to methodological and spatial scale issues, uncertainty, mapping or economic damage topics. However, most of these reviews provide a snapshot of the scientific state of the art of FRA that shows only a partial view, focused on a limited number of selected methods and approaches. In this paper, we apply a bibliometric analysis using the Web of Science (WoS) database to assess the historic evolution and future prospects (emerging fields of application) of FRA. The scientific production of FRA has increased considerably in the past decade. At the beginning, US researchers dominated the field, but now they have been overtaken by the Chinese. The Netherlands and Germany may be highlighted for their more complete analyses and assessments (e.g., including an uncertainty analysis of FRA results), and this can be related to the presence of competitive research groups focused on FRA. Regarding FRA fields of application, resilience analysis shows some growth in recent years while land planning, risk perception and risk warning show a slight decrease in the number of papers published. Global warming appears to dominate part of future FRA production, which affects both fluvial and coastal floods. This, together with the improvement of economic evaluation and psycho-social analysis, appear to be the main trends for the future evolution of FRA. Finally, we cannot ignore the increase in analysis using big data analysis, machine learning techniques, and remote sensing data (particularly in the case of UAV sensors data).
Journal Article
A Comprehensive Framework for Evaluation of Skeletonization Impacts on Urban Drainage Network Model Simulations
Urban drainage network models (UDNMs) have been widely used to facilitate flood management. Typically, a UDNM is developed using data from Geographic Information Systems (GIS), and hence it consists of many short pipes and connection nodes or manholes. To improve modeling efficiency, a GIS‐based model is generally skeletonized by removing many elements. However, there has been surprisingly a lack of knowledge on to what extent such skeletonization can affect the model's simulation accuracy, resulting in uncertainty in flood risk estimation. This paper makes the first attempt to quantitatively evaluate multidimensional impacts of different skeletonization levels on hydraulic properties of UDNMs. This goal is achieved by a new evaluation framework comprising of eight existing and new metrics that make use of hydrographs, main pipe hydraulics and flood distribution properties. A real‐life UDNM is used to illustrate the new framework under various rainfall conditions and different skeletonization levels. The new framework is also used to compare the performance of two compensation methods in mitigating impacts caused by model skeletonization. Results obtained show that: (a) model skeletonization can significantly affect the magnitude of peak flow at the outfall, with a maximum overestimation of up to 20%, (b) hydraulics in main pipes can also be affected by model skeletonization with the maximum flow increasing up to 35%, and (c) model skeletonization may significantly alter the flood distribution properties which has been largely ignored in past studies. These findings provide guidance for UDNM skeletonization, where their associated impacts should be aware in engineering practice. Key Points A comprehensive framework is proposed to quantitatively evaluates the skeletonization impacts on urban drainage network model predictions A new metric is developed to simultaneously account for flood volume and spatial range when assessing the model skeletonization errors Proposed framework is applied to assess two existing compensation methods for the mitigation of simulation errors induced by skeletonization
Journal Article