Flood Risk Mitigation Research Articles

Examining the determinants of flood risk mitigation measures at the household level in Bangladesh

Floods are the most common hazard in Bangladesh adversely affecting the lives and livelihoods of millions of riverine people. Flood-affected households adopt a variety of post-disaster mitigation measures, to the best of their ability, in recognition that similar events are likely to occur again in the future. However, little is known about what drives a household to adopt risk mitigation measures after experiencing a severe flood. The objective of this study was to investigate the determinants of households' decisions on the implementation of flood risk mitigation measures, following the severe flood in 2017 in northern Bangladesh. The data used for this study were collected from the right bank of the Teesta River in Bangladesh through a survey of 377 households and six key informant interviews. Most of the households (83.3%) adopted at least one risk mitigation measure from either structural or nonstructural categories after the 2017 flood. Binary logistic regression models provide useful insights into the determinants of the implementation of mitigation measures and intention to implement mitigation measures in future. The results showed that the perceived probability of flood, perceived preparedness, flood experience, exposure to flood, membership, household head's sex, income source, and landownership significantly influenced households to implement mitigation measures in the post-disaster period. Additionally, the intention to implement mitigation measures was influenced by the membership and education of households. This study contributes in terms of useful information about the determinants of post-disaster mitigation measures in riverine areas of Bangladesh. These findings can be used to target specific households to promote disaster risk reduction interventions.

Participatory Approaches to Urban Flood Risk Mitigation and Adaptation Strategies Projects: A Scoping Review of the Global South Evidence

Participatory approaches to urban flood risk adaptation initiatives have been prominent amongst developed countries, particularly in Europe, since the 2000s and are now steadily on the rise in the Global South. In this article we focus on how international examples of community-based participatory research and practice have managed flooding risk mitigation and adaptation strategies, specifically in the Global South. While top-down resistance-based approaches that include infrastructure, technology, laws and regulations offer invaluable information for urban planners and policy-makers they however fall short on revealing the perceptions and behaviours that shape individual, household and community adaptation decision-making process. In addition, these top-down approaches tend to take a long-term view of change with new programmes or policies, implemented over time, failing to tackle current challenges. The aim of this scoping review is therefore to map out the key concepts underpinning this research area and the main sources of evidence addressing community-based flooding monitoring, mitigation and adaptation strategies to uncover practices that facilitate participatory models of working between researchers, urban developers/designers, government institutions, and local communities. Finally, this evidence-based synthesis serves as background to the presentation of a Mexican case-study in which a community-based participatory approach is employed to support a co-production process for the identification of local flood risk management options.

Overview of an early warning system for Glacial Lake outburst flood risk mitigation in Dudh-Koshi Basin, Nepal

Overview of an early warning system for Glacial Lake outburst flood risk mitigation in Dudh-Koshi Basin, Nepal

The Jakarta society’s perspectives on Architechnopreneurship design

Building architecture in urban areas is very important, especially for settlements that are at risk of flooding. Architechnopreneurship is a residential architectural design concept that can provide comfort even in a flooded area, has a concept that utilizes technology, provides insight into entrepreneurial values and provides education for residents in mitigating flood risk. This study aims to obtain an overview of the Jakarta society’s perspectives on architechnopreneurship design. The research method used is the Neuroresearch method, a mixed method which has three stages of research, namely exploratory, explanatory, and confirmatory research. The results showed that the Architechnopreneur building design concept presented was still not in accordance with the views of the people of Jakarta significantly at α <0.05. These results provide input for changes and improvements to architechnopreneurship design in accordance with community expectations.

High-resolution flood risk approach to quantify the impact of policy change on flood losses at community-level

Communities are changing the way they manage flood risk as a result of climate change which increases both the flood hazard intensity and frequency and therefore results in more flood exposure for the built environment. Quantifying the feasibility of policy changes requires a standardized approach that can allow a risk-informed decision. The current body of flood risk mitigation research is populated with a host of qualitative approaches to reduce flood risk at the building- and community-level. However, quantitative effects on physical infrastructure within the community at a detailed level, i.e. component- and building-level, are needed to provide decision-support for policymakers. In this study, a high-resolution quantitative approach is developed to determine the effect of policy change on flood losses at the community-level by integrating building information models with the community topology. This approach uses a portfolio of building archetypes to model flood vulnerability at the community-level. For each archetype within this portfolio, a systematic approach was developed to propagate uncertainties in the flood damage for each component within the building and thereby providing the total building damage in terms of exceedance probability of a set of prescribed damage states. The developed approach was used to investigate an array of community-level mitigation options that could control both the flood hazard and flood exposure. The analysis of an example community revealed that one mitigation policy is not enough to provide efficient flood protection and a suite of diverse mitigation techniques working in concert is more effective for major flood protection.

Controlling invasive alien shrub species, enhancing biodiversity and mitigating flood risk: A win–win–win situation in grazed floodplain plantations

The high nature conservation value of floodplain ecosystems is severely threatened by invasive alien species. Besides adversely affecting native biodiversity, these species also pose a major threat from a wider socio-ecological perspective (e.g. ‘roughness’ increases flood risk). Finding options to control dense shrub layers consisting of invasive alien species is therefore of high priority for multipurpose management. We studied cattle grazing impacts on the cover, composition and diversity of the herb and shrub layers in floodplain poplar plantations along the Tamiš river, Serbia. Non-grazed, moderately grazed, intensively grazed and resting place stands were sampled in five locations in three sampling points. Non-grazed stands had substantially higher cover of invasive alien shrub species (on average 65%) than moderately and intensively grazed stands, and resting places (5.17, 0.02 and 0.00%, respectively), but without considerable differences between the grazing intensity categories. The number of invasive alien species in the shrub layer decreased considerably from non-grazed to intensively grazed stands. Species composition in the herb layer changed from non-grazed to intensively grazed stands, while resting places differed substantially from the other categories. Total species richness, richness of native generalist herbaceous grassland species, and the cover of palatable grasses were the highest in moderately and intensively grazed stands. Our results suggest that cattle grazing in floodplains is effective at controlling invasive alien shrub species. Furthermore, continuous moderate or intensive grazing would contribute to multifunctional management of invaded floodplains by enhancing local biodiversity, reducing flood risk, and providing additional grazing areas for the local community.

A catalogue of the flood forecasting practices in the Danube River Basin

AbstractFloods are one of the most devastating natural disasters that can cause large economic damage and endanger human lives. Flood forecasting is one of the flood risk mitigation measures serving to protect human lives and social estate. The Danube River Basin (DRB) is the world's most international river basin, flowing through the territory of 19 countries, covering more than 800,000 km2. The frequency of floods in the DRB increased in the last decades, urging the need for a more effective and harmonized regional and cross‐border cooperation in the field of flood forecasting. Reliable and comprehensive hydrologic data are the basis of flood forecasting. This paper provides an overview of the national flood forecasting systems in the DRB. Detailed information about meteorological and hydrological measurements, flood modelling, forecasting, and flood warnings is provided for 12 countries that cover almost 95% of the total DRB area. Notably, significant differences exist among the countries in terms of the measuring network density, the models used as well as forecasting and warnings methodology. These differences can be attributed to the geographical and climatological setting, political situation, historical forecasting development, etc. It can be seen that there is still much room left for improvements of measurement networks (e.g., density, measured parameters) and models used that could be improved to enhance the flood forecasting in the DRB.

A Conceptual Framework for Flood Impact Mitigation Through Transboundary River Management

It is acknowledged that for successful mitigation of flood risk there is a need for an integrated, basin-wide approach. This is particularly important in transboundary river basins that cross administrative borders where the actions of multiple stakeholders must be coordinated from source to mouth. The Ciliwung River, Indonesia, presents an example of a complex urban basin that crosses multiple administrative borders. The increasing frequency and severity of floods in the downstream capital city of Jakarta has highlighted the urgent need for more effective governance arrangements to tackle flooding. However, it is not clear what form these arrangements should take to be effective. In order to understand how transboundary river management arrangements can be improved to mitigate flood hazard impacts, it is first important to identify the nature of the existing management arrangements and how they relate and interact with the flood hazard. To do this, a conceptual framework was developed. The framework firstly outlines the flood hazard itself in terms of drivers and impacts. It then goes on to establish the associated transboundary governance and river management arrangements and seeks to identify any interdependencies. Key concepts were drawn from a review of the literature, conducted using online databases and search engines. The review included published journal and conference papers as well as reports published by organisations which were identified through online searches. The framework highlights multiple interrelated drivers of flood risk, both human and physical. There are also a range of governance issues related to capacities, coordination of institutions and fragmentation of plans and policies identified within the river basin, which need to be overcome. Due to the complexities of flood risk and river management, this conceptual framework provides much needed clarity to facilitate future research on transboundary management in relation to flood risk in urban and peri-urban river basins. It sets a framework for the development of improved transboundary management arrangements in the Ciliwung River Basin.

Role of forested land for natural flood management in the UK: A review

AbstractNatural flood management (NFM) is the use of natural processes and environments to mitigate flood risk by reducing and delaying peak flood. This review introduces the concept and history of NFM and looks at the current state of research into the potential for using different types of woodland to fulfill the aims of NFM. Four woodland types (catchment, cross‐slope, floodplain, and riparian) are discussed with reference to studies carried out, mainly in the United Kingdom, to determine the relative merits of each type and their effectiveness in mitigating flood risk. We then discuss how trees interact with the hydrological cycle, along with a discussion of modeling methods which seek to determine the amount of water intercepted by different types of forest cover. We find that while there is some evidence that carefully planned and managed woodland can mitigate flood risk, the published data for this evidence base is somewhat sparse. This may be either due to the long timescales needed for comprehensive studies or the relative infancy of the research on NFM. More research needs to be carried out in each of the four woodland types, especially in the UK, as policy makers are increasingly looking towards nature based solutions to mitigate the potential impacts of climate change. The concept of a combined canopy/hydrological model which can be scaled from stand to watershed level and incorporate different types of woodland is suggested as it would be beneficial in guiding woodland creation policy in the future, both at the local and regional scales.This article is categorized under: Science of Water &gt; Water Extremes Water and Life &gt; Conservation, Management, and Awareness

A nature-based approach to mitigate flood risk and improve ecosystem services in Shiga, Japan

The increased frequency of extreme rain events due to climate change has garnered attention in Japan. In 2018, the country enacted the Act of Climate Change Adaptation to formulate plans at national and local levels. The government has suggested the use of nature-based solutions (NBSs) across the country to address the increased risk of natural disasters. This study employs scenario analysis to examine the effectiveness of NBSs for the mitigation of flood risk and their implications on the provision of ecosystem services (ESs). Shiga prefecture in Japan enacted its own ordinance in 2015. This ordinance considers existing land use and building regulations to mitigate flood risk. The quantitative analysis assumes nine scenarios up to the year 2050, combining the current policy of Shiga and our original assumption of advance policy options to evaluate the future flood risk and ES. The analysis revealed that land use management can partially mitigate the flood risk by banning new residences and relocating residential land from flood-prone areas to safer areas and converting residential land into forest and paddy fields. It also suggests that both flood risk mitigation and provision of ESs can be further improved if local governments introduce a residence growth management strategy.

Experimental Flash Floods Assessment Through Urban Flood Risk Mitigation (UFRM) Model: The Case Study of Ligurian Coastal Cities

Cities are vulnerable to extreme weather events, particularly by considering flash flood risk as a result of even more short-duration intensive rainfall. In the context of climate change, compound flooding due to simultaneous storm surges and increased runoff may further exacerbate the risk in coastal cities, and it is expected to be frequent and severe across several European urban areas. Despite this increasing evidence, the spatial knowledge of the hazardous events/vulnerabilities through modelling scenarios at the urban level is quite unexplored. Moreover, flood-prone areas often do not correspond to the traditional flood risk classification based on predicted return-period. The result that huge impacts (human losses and damages) occur everywhere throughout the city. Consequently, this new challenge requires stormwater flooding mitigation strategies to adapt to cities while mainstreaming urban flood resilience. In this paper, we considered the Urban Flood Risk Mitigation model through the employment of the open-source tool—Integrated Evaluation of Ecosystem Services and Trade-off (InVEST)—developed by the Natural Capital Project, integrated into a GIS environment. The model application in the three urban coastal territory of the Liguria Region (Italy) estimated the amount of runoff due to two extreme rainfall events for each watershed considered. These index calculation results help define examples of Natural Water Retention Measures (NWRM) per land-use type as resilient solutions by addressing site-specific runoff reduction. Local sensitivity analysis was finally conducted to comprehend the input parameter's influence of rain variation on the model.

Urban expansion and enhanced flood risk in Africa: The example of Lagos

ABSTRACT The world is increasingly characterised by uncertainty, complexity and rapid change while vulnerability to potential disasters is equally increasing. The situation is more dire in countries where governments are unable to manage land use and development in rapidly growing towns and cities. Lagos, a major city in Nigeria, is notorious for flooding, owing to its being lowland, and this is compounded by inadequate planning and uncoordinated physical development. A systematic study of urban expansion in Lagos was done using Landsat ETM, OLI and Google Earth imageries for 2000, 2013 and 2019 to analyse land use and land cover change, and pattern of encroachment of physical development into vegetation cover and flood plains in Lagos. The comparison of the three Land Use Land Cover Change (LU/LC) schemes, indicates that built-up areas accounted for about 50.0% of land use in Lagos in 2019. The increase is almost thrice the extent recorded in the year 2000. As the pace of growth quickens, new structures deplete vegetation and fuels lateral expansion into marginal land. Adherence to land use planning regulation, vertical expansion and flood-plain-buy-back were recommended as strategies to mitigate flood risk.

Assessment of renaturation measures for improvements in ecosystem services and flood risk mitigation

The present paper offers a contribution to the research on social acceptance of interventions aimed at water ecosystem improvement and flood risk mitigation through renaturation measures. A CE study has been implemented to assess trade-offs between attributes of alternative projects, including social costs deriving from proposed actions of renaturation of river flows. The aim of our approach is to investigate the role of attitudinal factors in the valuation of costs and benefits generated by renaturation measures. A Hybrid Latent Class (HLC) model is applied to the data, revealing the existence of two distinct groups, characterised by different valuations of the attributes of the project. It is found that class membership depends on latent attitudes toward environmental protection and risk perception. Our study confirms the fruitfulness of the HLC modelling approach in stated preference studies regarding ecosystems valuation, as it provides a richer understanding of public preferences and allows more finely targeted policy indications.

A new soft computing model for daily streamflow forecasting

Accurate stream flow quantification and prediction are essential for the local and global planning and management of basins to cope with climate change. The ability to forecast streamflow is crucial, as it can help mitigate flood risks. Long-term stream flow data records are needed for hydropower plant construction, flood prediction, watershed management, and long-term water supply use. An accurate assessment of streamflow is considered as very challenging and critical tasks. A new predicting model is developed in this research, combining the technique of sunflower optimization (SFA) as an evolutionary algorithm with the multi-layer perceptron (MLP) algorithm to predict streamflow in Malaysia's Jam Seyed Omar (JSO) and Muda Di Jeniang (MDJ) stations. Principal component analysis (PCA) was performed on Q (t) (t: the number of the current day) before model creation to pick essential inputs for a maximum of 6 lags. With the classical MLP and two other hybrid MLP models (MLP-particle swarm optimization (MLP-PSO) and MLP-genetic algorithm (MLP-GA)), the results of the MLP-sunflower algorithm (SFA) were benchmarked. As compared to other models, the MLP-SFA could be able to reduce the Root Mean Square Error (RMSE) by a value of between 12 and 21% at the JSO station and between 8 and 24% at the MDJ station. In conclusion, this research found that combining MLP with optimization algorithms improved the precision of the stand-alone MLP model, with SFA integration being the most efficient.

An Indicator-Based Approach for Micro-Scale Assessment of Physical Flood Vulnerability of Individual Buildings

The current trends of floods event in many countries are alarming. Hence, managing flood and the associated risk are crucial in order to reduce the loss and to be well prepared for the combined impact of urbanization and climate changes. The best approach to manage flood activities is a risk-based approach, where the vulnerability of elements at risk is reduced to a minimum. There is a significant number of studies that use an indicator-based approach for flood vulnerability assessment with focus on the macro-scale. However, this paper assesses physical flood vulnerability of buildings at micro-scale using an indicator-based method in Kota Bharu, Malaysia. The region is one of the most flood affected regions in Malaysia. Micro-scale vulnerability assessment considers damages for individual buildings at risk, rather than in aggraded manner. In this study, the methodology adopted involve the use of 1D-2D SOBEK flood modelling, the selection and weightage of indicators, development of spatial based building index and, production of building vulnerability maps. The findings demonstrate the physical pattern of flood vulnerability of buildings at a micro-scale. The approach can assist in flood management planning and risk mitigation at a local scale

Real-time reservoir flood control operation enhanced by data assimilation

Real world reservoir operations are usually not fully automatic based on computer models; instead, reservoir operators conduct the operations based on their experiences, professional justification, as well as modeling support. In this paper, we propose a human-machine interactive method, namely Real-time Optimization Model Enhanced by Data Assimilation (ROMEDA) tested with simple but reasonable rules for direct interaction between operators and a computer model for reservoirs which have complex storage and stage relations (e.g. long and narrow reservoirs). ROMEDA couples 1) an optimization model to search for optimal releases, 2) a reservoir storage-stage simulation and data assimilation schedule to update the storage based on real-time reservoir stage observations, and 3) reservoir operators’ choices based on the optimization model solutions, as well as their experiences, knowledge, and behaviors. For every time period and based on the updated storage, ROMEDA provides optimal releases as recommendations and adopts actual releases made by operators. ROMEDA does not assume that operators strictly accept the recommendations, and the storage will be updated based on the actual release at each time period via a data assimilation procedure, which plays a key linkage between human and machine in ROMEDA. Via a case study on-channel reservoir, it is found that for both small and large flood events, ROMEDA, which integrates the advantages of both machine and human, shows better performance on flood risk mitigation and water use (hydropower) benefit than the case with historical operation records (HOR) or optimization with single/multi-objective. ROMEDA is one of the first attempts of a human-machine interactive method for online use of an optimization model for real-time reservoir operation based on integrated modeling, observation, and operators’ choice.

Values influence public perceptions of flood management schemes

Natural Flood Management (NFM) is now well established as a paradigm for reducing flood risk. It is characterised by adopting a catchment-wide hydrological perspective and implementing solutions that work with natural processes such as wetlands, riparian vegetation and river channel rehabilitation. However, despite substantial attention in the river science literature and growing appreciation for NFM among environmental managers, little research has been conducted on how the public perceives NFM. This study explored preferences for a variety of flood risk management schemes through an online survey of the UK public, and assessed how different characteristics of these schemes contribute to preferences via Q-method utilising an array of photographs. Relationships between survey respondents' underlying transcendental values and their preferences for NFM schemes were also studied. Results revealed that while NFM approaches were appreciated for their appearance and wildlife benefits, traditional grey engineering – particularly dams – was seen as more effective in ameliorating flood risk. Q-sorts of photographs revealed three factors that characterised participants' preferences: (i) “Engineered - Natural”, (ii) “Messy - Neat” and (iii) “Grey - Green”. Finally, transcendental values were significantly related to flood scheme preferences, with ‘Self-Transcendence’ values positively correlated with preferences for tree planting and wetlands and negatively with dams and weirs. ‘Conservative’ values were positively correlated with preferences for dredging and weirs and negatively with wetlands. These findings emphasise the plurality of public perceptions related to NFM and the diverse value orientations within which they are grounded. River and catchment managers seeking to promote NFM solutions should focus on addressing public concerns about the efficacy of NFM for mitigating flood risk, and consider how to communicate solutions in ways that resonate with a diverse set of public values.

Multi-step rainfall forecasting using deep learning approach.

Rainfall prediction is immensely crucial in daily life routine as well as for water resource management, stochastic hydrology, rain run-off modeling and flood risk mitigation. Quantitative prediction of rainfall time series is extremely challenging as compared to other meteorological parameters due to its variability in local features that involves temporal and spatial scales. Consequently, this requires a highly complex system having an advance model to accurately capture the highly non linear processes occurring in the climate. The focus of this work is direct prediction of multistep forecasting, where a separate time series model for each forecasting horizon is considered and forecasts are computed using observed data samples. Forecasting in this method is performed by proposing a deep learning approach, i.e, Temporal Deep Belief Network (DBN). The best model is selected from several baseline models on the basis of performance analysis metrics. The results suggest that the temporal DBN model outperforms the conventional Convolutional Neural Network (CNN) specifically on rainfall time series forecasting. According to our experimentation, a modified DBN with hidden layes (300-200-100-10) performs best with 4.59E−05, 0.0068 and 0.94 values of MSE, RMSE and R value respectively on testing samples. However, we found that training DBN is more exhaustive and computationally intensive than other deep learning architectures. Findings of this research can be further utilized as basis for the advance forecasting of other weather parameters with same climate conditions.

Integrated management of surface water and groundwater to mitigate flood risks and water scarcity in arid and semi‐arid regions

AbstractWater scarcity in arid and semi‐arid regions represents a significant obstruction to social and economic development. Also, flood hazards affect the life of many people in these areas. This study aims to develop a new model for integrated management of surface water and groundwater, which involves rainwater harvesting and recharge to groundwater aquifers. Integrated hydrological models, including geographic information system (GIS), watershed modelling system (WMS) and groundwater modelling system (GMS) were used. This research provides an integrated vision for exploiting the rainwater in Wadi Watier, South Sinai, Egypt and shows new insights on how to protect these areas from flood risks and store water to solve the water scarcity in this region. Based on physical properties of sub‐basins and soil properties, fourteen dams were suggested and designed to protect the study area from flood risks; five dams were used for storage and nine dams for groundwater recharge. The results showed that the dams could collect about 160.72 million m3 of rainwater which can be stored or recharged into groundwater aquifers. This will increase the national income and provide stability for residents in these areas that suffer from water shortage. Decision‐makers can use these models for sustainable flood management in similar areas.

Blue\u2013Green Infrastructure for Flood and Water Quality Management in Southeast Asia: Evidence and Knowledge Gaps

In Southeast Asia, projections of rapid urban growth coupled with high water-related risks call for large investments in infrastructure—including in blue–green infrastructure (BGI) such as forests, parks, or vegetated engineered systems. However, most of the knowledge on BGI is produced in the global North, overlooking the diversity of urban contexts globally. Here, we review the literature on BGI for flood risk mitigation and water quality improvement in Southeast Asian cities to understand the scope of practical knowledge and identify research needs. We searched for evidence of local types of BGI in peer-reviewed and grey literature and assessed the performance of BGI based on hydrological, societal, and environmental metrics. The body of literature on BGI in Southeast Asia is small and dominated by wealthier countries but we found evidence of uptake among researchers and practitioners in most countries. Bioretention systems, constructed wetlands, and green cover received the most attention in research. Evidence from modelling and laboratory studies confirmed the potential for BGI to address flooding and water quality issues in the region. However, practical knowledge to mainstream the implementation of BGI remains limited, with insufficient primary hydrological data and information on societal and environmental impacts. In addition, the performance of BGI in combination with grey infrastructure, under climate change, or in informal settlements is poorly studied. Future research and practice should focus on producing and sharing empirical data, ultimately increasing the regional knowledge base to promote efficient BGI strategies.