Flood Risk Mitigation Research Articles

Rice farming business risk analysis in Padang City

Based on the Area Sample Framework (KSA) results, rice production in West Sumatra has decreased by 6 per cent from 2019 to 2020. This shows that rice farming still faces various risks affecting its production and productivity. As the main farming actors, farmers receive the most significant impact and risk due to climate-related disasters. Farmers must bear risks in production, price, market, financial, technological, social, legal, and human risks. Production risk occurs due to yield fluctuations due to various factors that are difficult to predict (climate change, extreme weather, floods, droughts, and pest attacks). This study aims to (1) identify the risks of rice farming in Padang City and (2) measure the magnitude of rice farming risks faced by farmers in Padang City. Data were collected using questionnaires from 30 farmers. The results showed that the risks faced by farmers were the risk of land management, the risk of flooding, risk of drought and the risk of pest and disease attacks. The risk faced by farmers in their farming business as a whole is low. The risk of flooding and drought has a large percentage of greater risk. The flood risk mitigation carried out by farmers, in general, is to let their land be flooded, while farmers carry out drought risk management by looking for water sources.

Integrating multi-sensor observations and rainfall-runoff inundation modeling for mapping flood extents over the Nile River basin: example from the 2020 flooding in Sudan

Understanding the dynamics of flooding events is crucial to mitigate flood risks, particularly in developing nations like Sudan. This study combines multi-sensor approaches with Rainfall-Runoff-Inundation (RRI) modeling to predict flood inundation extent over the Nile River Basin (NRB). Building upon the RRI model, we firstly simulated the streamflow over the Blue Nile basin and the White Nile basin. Our results show a good agreement between the observed and the simulated streamflow at both daily and monthly scales, e.g. NSE = 0.72 and R2 = 0.85 for daily simulations at Khartoum station. Further, we compared the inundation extents from the RRI model with derived inundation maps from different satellite images (Sentinel-1, Sentinel-2, Landsat-8, and MODIS). The results indicate the potential to overcome the limitation of data scarcity in developing regions and hence provide a supportive assessment tool for flood risk maps in the NRB.

Locating real-time water level sensors in coastal communities to assess flood risk by optimizing across multiple objectives

Coastal communities around the world are experiencing increased flooding. Water level sensors provide real-time information on water levels and detections of flood risk. Previous sensor installations, however, have relied on qualitative judgments or limited quantitative factors to decide on sensor locations. Here, we provide a method to optimally place real-time water level sensors across a community. We utilize a multi-objective optimization approach, including traditional measures of sensor network performance such as coverage and uncertainty, and new flood-specific parameters such as hazard estimations (flood likelihood, critical infrastructure exposure), serviceability (sensor accessibility), and social vulnerability (socio-economic index, vulnerable residential communities index). We propose a workflow combining quantitative analyses with local expertise and experience. We show the method is able to reduce the set of possible new sensor locations to just 1.3% of the full solution set, supporting effective and feasible community decision-making. The method also supports sequential expansion of a sensor network, creating a network that provides detailed and accurate real-time water level information at the hyperlocal level for flood risk assessment and mitigation in coastal communities.

Characterising the coincidence of soil moisture – precipitation extremes as a possible precursor to European floods

Studies around the world have shown that increases in extreme precipitation are not directly resulting in reported instances of flooding. Despite the evidence that antecedent soil moisture conditions play a significant role in regulating the runoff response during extreme storm events, fewer works have tried to understand the spatial and temporal dynamics of such coupled interactions. In the present work, we aim to improve our understanding of the dominant spatiotemporal patterns of soil moisture (SM) – precipitation (P) dependence over Europe. Using an event-based, non-parametric Event Coincidence Analysis (ECA) approach, we first quantified the probability of SM preceding P by the precursor coincidence rate. We also examined the statistical precursor relationship between SM-P joint episodes and reported annual flood events using the conditional precursor coincidence rate. The results show that seasonality is a major driving force in the spatiotemporal dynamics of SM-P coupling over Europe. The conditional precursor coincidence rates are in line with previous flood hazard studies over Europe and show the importance of considering such diverse interdependencies in flood risk mitigation. Our work has implications for understanding the occurrence of preconditioned compound events worldwide and provides a vital starting point for characterising the major processes that need to be accounted for in comprehensive state of the art flood risk assessment studies.

Integrating Critical Infrastructure Networks into Flood Risk Management

Critical infrastructure (CI) networks are essential for the survival and functionality of society and the economy. Disruptions to CI services and the cascading effects of these disruptions are not currently included in flood risk management (FRM). The work presented in this study integrates CI into every step of FRM, including flood risk analysis, risk mitigation and risk communication. A CI network modelling technique enables the flood consequences for CI to be quantified as part of the flood risk analysis. The CI consequences derived from this analysis include spatial overviews and the temporal succession of CI disruptions. The number of affected CI end-users and the duration of the disruption are arranged in a risk matrix and in a decision-making matrix. Thus, the total flood risk is extended with CI consequences. By integrating CI and CI network characteristics into the flood risk assessment and the mitigation steps, a wider range of measures for action can be considered. Additionally, the continuous participation of CI operators is introduced as beneficial for every step of the FRM. A case study in Accra, Ghana proves the benefits of CI integration for all FRM steps. During participatory CI stakeholder engagements for this study six CI sectors were identified for the assembly of the CI network. The backbone of the analysis is a multisectoral, layered CI network model with 433 point elements, 1216 connector elements and 486 polygon elements.

Quality of Stormwater Infrastructure Systems in Vulnerable Communities: Three Case Studies from Texas.

A properly functioning local stormwater drainage system is essential for mitigating flood risks. This study evaluates the quality of roadside drainage channels in three underserved communities in Texas: the Sunnyside neighborhood in Houston (Harris County), a neighborhood in the City of Rockport (Aransas County), and the Hoehn colonia (Hidalgo County). These communities have a history of flooding, are highly socially vulnerable, and rely on roadside ditches as their principal stormwater drainage system for runoff control. Mobile lidar (Light Detection and Ranging) measurements were collected for 6.09 miles of roadside channels in these communities. The raw lidar measurements were processed to evaluate drainage conditions based on the channel's geometric properties, hydraulic capacity, and level of service. The assessment results are linked to a Geographic Information System (GIS) tool for enhanced visualization. Finally, the paper provides insights regarding the quality of stormwater infrastructure in the study communities and discusses their practical implications.

Integrated intra-storm predictive analysis and real-time control for urban stormwater storage to reduce flooding risk in cities

Urban stormwater management has become an important aspect affecting the sustainable development of cities. Real-time control (RTC) of storage facilities is generally considered a cost-effective structural method for flood risk mitigation, but the capacity of storage is often limited by the available land space or local regulations. This study addresses the issue of integrating intra-storm predictive analysis and real-time control for enhancing the peak outflow reduction of a relatively small storage tank. A modified optimization-based approach is presented that utilizes the predicted peak inflow to quantify the required storage volume and subsequently determine the intra-storm release. A sponge city community in Shenzhen, China is selected as a demonstration study case. Numerical experiments based on historic rainfall events indicate that when the storage capacity is 43.9 m3/ha, the modified predictive RTC performs better in peak outflow reduction than an existing predictive RTC and rule-based RTC, with an improvement up to 22.7% and 58.2%, respectively. The modified approach also enhances system performance when storage capacities and rainfall depths vary from the base value. These findings highlight the potential of using the modified predictive RTC to sustainably reduce flood peaks even if the storage capacity is limited.

Mapping of Groundwater, Flood, and Drought Potential Zones in Neom, Saudi Arabia, Using GIS and Remote Sensing Techniques

Neom is expected to face climate and environmental challenges, including the provision of water and the mitigation of flood and drought risks. The field data for identifying the potential risk zones are limited. I utilized remote sensing data and geographic information system (GIS) techniques to identify such zones. The datasets used here included drainage density, lineament density, precipitation, elevation, lithology, slope, soil, and land use/land cover. These data were analyzed using a weighted overlay analysis in a GIS environment. The analysis successfully mapped the potential groundwater, flood, and drought zones in Neom. The zone with a good potential for groundwater covered 515 km2 of Neom, whereas 11,562, 10,616, and 289 km2 of land had a moderate, poor, and very poor chance of having groundwater, respectively. The area with the lowest flood danger covered only 195 km2, whereas the areas with a low, moderate, and high flooding risk covered 4355, 13,542, and 4910 km2 of land, respectively. The results of the overlay analysis showed that low and very low drought risks were associated with 4322 and 44 km2 of land, respectively. In turn, 10,615 and 8266 km2 of the region were at a moderate and high drought risk, respectively.

Public-private flood management: Who should pay and when?

We provide a theoretical and empirical analysis of an efficient sharing of public and private flood-risk mitigation. Our analysis examines how individuals in a floodplain can best protect their property, given the interdependence between the public offering of structural measures and a private offering of insurance. A key theoretical finding is a separation of the risk space: under a given damage threshold, the public sector mitigates all risk, while above the threshold, the private sector offers insurance. We estimate this theory based on the Lake Champlain and Richelieu River data. We show how a public and private mix increases welfare gains and reduces overall spending on risk mitigation measures.

Flood hazard assessment using design rainfall under climate change scenarios in the Kelantan River Basin, Malaysia

Purpose The present study aims to evaluate the effect of climate change on the flood hazard potential in the Kelantan River Basin using current and future scenarios. Design/methodology/approach The intensity-duration-frequency (IDF) was used to estimate the current 50- and 100-year return period 24-h design rainfall, and the climate change factor (CCF) was used to compute the future design rainfall. The CCF was calculated from the rainfall projections of two global climate models, CGCM1 and CCSM3, with different pre-processing steps applied to each. The IDF data were used in the rainfall-runoff-inundation model to simulate current and future flood inundation scenarios. Findings The estimated CCF values demonstrate a contrast, whereby each station had a CCF value greater than one for CGCM1, while some stations had a CCF value of less than one for CCSM3. Therefore, CGCM1 projected an aggravation and CCSM3 a reduction of flood hazard for future scenarios. The study reveals that topography plays an essential role in calculating the CCF. Originality/value To the best of the author’s knowledge, this is the first study to examine flood projections in the Kelantan River Basin. It is, therefore, hoped that these results could benefit local managers and authorities by enabling them to make informed decisions regarding flood risk mitigation in a climate change scenario.

Assessing the co-benefits of urban greening coupled with rainwater harvesting management under current and future climates across USA cities

Globally, urban areas face multiple challenges owing to climate change. Urban greening (UG) is an excellent option for mitigating flood risk and excess urban heat. Rainwater harvesting (RWH) systems can cope with plant irrigation needs and urban water management. In this study, we investigated how UG and RWH work together to mitigate environmental risks. By incorporating a new RWH module into the urban ecohydrological model Urban Tethys-Chloris (UT&C), we tested different uses of intervention approaches for 28 cities in the USA, spanning a variety of climates, population densities, and urban landscapes. UT&C was forced by the latest generation convection-permitting climate model simulations of the current (2001–2011) and end-of-century (RCP8.5) climate. Our results showed that neither UG nor RWH, through the irrigation of vegetation, could significantly contribute to mitigating the expected strong increase in 2 m urban canyon temperatures under a high-emission scenario. RWH alone can sufficiently offset the intensifying surface flood risk, effectively enhance water saving, and support UG to sustain a strong urban carbon sink, especially in dry regions. However, in these regions, RWH cannot fully fulfill plant water needs, and additional measures to meet irrigation demand are required to maximize carbon sequestration by urban vegetation.

Comparative evaluation of the material of the artificial levees

Artificial levees have major importance in protecting human lives and infrastructure as they are essential elements of the flood protection measures. Nevertheless, the lack of the necessary information about their structure and internal composition might cause high risks. To monitor their stability, integrated surveys are needed, including geophysical and geotechnical methods. Levees along the rivers in Hungary were constructed more than 150 years ago, and they were heightened several times; therefore, investigations are required to assure their performance in flood risk mitigation. Our investigation aimed to utilise non-invasive geophysical techniques, primarily electrical resistivity imaging, with the validation of geotechnical investigations to map and compare the compositional and structural variations of two very different levee sections along River Tisza and River Maros. Integrating the analysed drilling data with ERT profiles showed that the main composition of the investigated Tisza levee section is fine and medium silt with an average resistivity 30 Ωm, however, the investigated section of Maros levee was built of not only of fine and medium silt but also of medium and coarse sand exhibiting higher resistivity values reaching up to 2200 Ωm. Several physical parameters were measured to study the nature of constituting levee materials like moisture content, grain-size, porosity, bulk-density, saturated hydraulic conductivity, and resistivity. It was found that most of them show a connection with resistivity, but the hydraulic conductivity did not show a direct connection, however the latter could exhibit the aquitard nature of Tisza levee materials and the non-aquitard nature of Maros levee materials.

Effect of urban neighbourhood layout on the flood intrusion rate of residential buildings and associated risk for pedestrians

Urban neighbourhood layouts affect the flood intrusion rate towards residential buildings through various kinds of damaged openings (doors, windows, gates and shafts) and the associated risk for pedestrians within the urban building complex and ultimately the safety of indoor and outdoor pedestrians in urban flooding events. This study adopts computational fluid dynamics (CFD) to quantify the flood intrusion discharge towards residential buildings and evaluate the flood hazard rating of pedestrians within urban areas of divergent configurations in conjunction with a laboratory flume experiment regarding the stability/instability behaviour of a dummy model that represents a human body in a quasi-natural state. Five types of urban building layouts with three different building densities under three various floodwater conditions, including a determinant type A (see the graphic abstract hereafter), a point group type B, an enclosed type C, a hybrid type D and a new hybrid type E, are examined. The results show that the determinant type A and hybrid type D have a similar trend in terms of the flood intrusion discharge distributions towards each row of buildings and discharge variation with respect to urban building spacing, whereas other urban layouts exhibit different characteristics. Strong floodwater leads to an increased flood risk for pedestrians both outdoors and even indoors within various urban configurations: pedestrians are the most prone to toppling instability on the streets, in turn, behind the building and within the interior of the building. For both determinant type A and hybrid type D, the more pedestrians lie behind the building approaching the upstream, the safer the pedestrians become, while for point group type B, enclosed type C and new hybrid type E, the trend is reversed. The experimental results also offer a novel valuable dataset for the validation of other urban flooding numerical models. This study could be referred to by local authorities and stakeholders to take effective measures to improve the safety of pedestrians and mitigate flood risk in the context of urban planning and urban flood emergency management, such as strengthening flood-resilient urban facility designs and devising optimal routines for emergent evacuation of outdoor pedestrians.

Mapping the Link between Climate Change and Mangrove Forest: A Global Overview of the Literature

Mangroves play a crucial role in maintaining the stability of coastal regions, particularly in the face of climate change. To gain insight into associations between climate change and mangroves, we conducted bibliometric research on the global indexed database of the Web of Knowledge, Core Collection. A total of 4458 literature were analyzed based on bibliometric information and article metadata through a scientometric analysis of citation analysis as well as a cluster analysis. Results suggest that coastal countries such as the USA, Australia, China, India, and Brazil are showing the recent influential mangrove-related keywords such as blue carbon and carbon stock. Interestingly, the “carbon stock”, “Saudi Arabia”, “range expansion” and “nature-based flood risk mitigation” is among the top cluster networks in the field of climate change and mangrove forest. The present research is expected to attract potential leaders in research, government, civil society, and business to advance progress towards mangrove sustainability in the changing climate meaningfully.

Comprehensive Flood Risk Assessment: State of the Practice

A comprehensive assessment of flood hazards will necessitate a step-by-step analysis, starting with hydrometeorological examinations of runoff and flow, followed by an assessment of the vulnerability of those at risk. Although bodies of knowledge about these topics are large, flood risk assessments face data challenges such as climate change, population growth, and shifting land uses. Recent studies have provided comprehensive reviews of advances in the water sciences arena, and in a complementary way, this paper reviews the state of the practice of assessing flood risk, include flood scenarios, hydrometeorology, inundation modeling, flood frequency analysis, interrelationships with water infrastructure, and vulnerability of people and places. The research base for each of these topics is extensive. Some of the tools in these areas, such as hydrologic modeling, have research advances that extend back decades, whereas others, such as numerical weather prediction, have more room to evolve. It’s clear from all studies that data is crucial along the progression from atmospheric conditions to the impact on flood victims. How data are provided and shared and how they are used by stakeholders in flood risk reduction continue to evolve. Improved availability of data and uses of emerging tools of data science and machine learning are needed to assess and mitigate flood risks. Continued the development of key tools is also required, especially to improve the capability to assemble them effectively on user platforms.

Particle swarm optimization based LSTM networks for water level forecasting: A case study on Bangladesh river network

Floods are one of the most catastrophic natural disasters. Water level forecasting is an essential method of avoiding floods and disaster preparedness. In recent years, models for predicting water levels have been developed using artificial intelligence techniques like the artificial neural network (ANN). It has been demonstrated that more advanced and sequenced-based deep learning techniques, like long short-term memory (LSTM) networks, are superior at forecasting hydrological data. However, historically, most LSTM hyperparameters were based on experience, which typically did not produce the best outcomes. The Particle Swarm Optimization (PSO) method was utilized to adjust the LSTM hyperparameter to increase the capacity to learn data sequence characteristics. Utilizing water level observation data from stations along Bangladesh's Brahmaputra, Ganges, and Meghna rivers, the model was utilized to estimate flood dynamics. The Nash Sutcliffe efficiency (NSE) coefficient, root mean square error (RMSE), and MAE were used to assess the model's performance, where PSO-LSTM model outperforms the ANN, PSO-ANN, and LSTM models in predicting water levels in all stations. The PSO-LSTM model provides improved prediction accuracy and stability and improves water level forecasting accuracy at varying lead times. The findings may aid in sustainable flood risk mitigation in the study region in the future.

Growing Safely or Building Risk?

Problem, research strategy, and findings Limiting housing and infrastructure in flood-prone places has long been recognized as critical to managing long-term risk. However, due to the difficulty of tracking development at small spatial scales, little empirical research has been conducted to explain differences between communities’ floodplain development patterns. We analyzed new construction across 5 million parcels in the state of North Carolina to develop standardized measures of floodplain development and evaluated the relationships between flood risk management effort and development outcomes. Statewide, for every property removed through buyouts from 1996 to 2017, more than 10 new residences were built in floodplains. At the community level, indicators of flood risk management effort (participation in the Community Rating System and use of buyouts) did not consistently align with floodplain development outcomes. Based on a sample of urban and suburban counties, we found more than 75,000 acres of vacant floodplain land currently zoned for development. Although we did not capture the full range of flood risk mitigation practices, results indicate that local development policies often run counter to efforts to limit long-term risk. Takeaway for practice Land use planning and floodplain management have the potential to play a larger role in flood risk mitigation. Modifying federal programs to more strongly disincentivize floodplain development could enhance local regulation and minimize future flood exposure. Given extensive undeveloped floodplain land and projected climate change, additional effort to manage development is needed to limit increases in flood risk.

Enhancing Flood Risk Assessment and Mitigation through Numerical Modeling: A Case Study

Evaluation of dike-break-induced flood risk has been a worldwide concern due to its enormous economic, environmental, and societal importance. The mitigation of flood risk in detention basins is a complex decision making process that could span multiple engineering and scientific disciplines. In this paper, an integrated dike-break-induced flood modeling, analysis, and management framework is proposed. The MIKE21-based numerical approach is first adopted to model the flood routing process in detention basins. With the physical behavior of the flood well understood, physics-informed approaches are proposed to better quantify the dike-break-induced flood risks, e.g., human life, economic and environmental losses, offering valuable information for engineers and policymakers to formulate targeted contingency plans. The Zhuhu detention basin in the Poyang Lake district in China is investigated using the proposed framework. The flood movement in the detention basin is first numerically simulated using the MIKE21-based model. Based on the results, i.e., inundation area, water depth, flow velocity, and arrival time of flood peak, the detention basin is divided into several flood disaster zones. The induced flood risks are then estimated for the different zones. Customized emergency evacuation plans are also formulated for the different flood disaster zones. The study of the Zhuhu detention basin confirms that the proposed framework effectively fuses numerical modeling, physics-informed analysis, and management of flood events, providing an integrated and enhanced decision making process for flood warning and risk mitigation in flood detention basins or at other places.

Climate and Human Impacts on Hydrological Processes and Flood Risk in Southern Louisiana

AbstractSatellite observations of coastal Louisiana indicate an overall land loss over recent decades, which could be attributed to climate and human‐induced factors, including sea level rise (SLR). Climate‐induced hydrological change (CHC) has impacted the way flood control structures are used, altering the spatiotemporal water distribution. Based on “what‐if” scenarios, we determine relative impacts of SLR and CHC on increased flood risk over southern Louisiana and examine the role of water management, via flood control structures, in mitigating flood risk over the region. Our findings show that CHC has increased flood risk over the past 28 years. The number of affected people increases as extreme hydrological events become more exceptional. Water management reduces flood risk to urban areas and croplands, especially during exceptional hydrological events. For example, currently (i.e., 2016–2020 period), CHC‐induced flooding puts an additional 73 km2 of cropland under flood risk at least half of the time (median flood event) and 65 km2 once a year (annual flood event), when compared to a past period (1993–1997). A 10‐ to 20‐fold increase relative to SLR‐induced flooding. CHC also increases population vulnerability in southern Louisiana to flooding; additional 9,900 residents currently live under flood risk at least half of the time, and that number increases to 27,400 for annual flood events. Residents vulnerable to SLR‐induced flooding is lower (6,000 and 3,300 residents, respectively). Conclusions are that CHC is a major factor that should be accounted for flood resilience and that water management interventions can mitigate risks to human life and activities.

Dynamic adaptive engineering pathways for mitigating flood risks in Shanghai with regret theory

Uncertainty in sea level rise and future extreme climate events presents a great planning challenge for flood defence in coastal mega cities like Shanghai. While academic literature has largely focused on uncertainty analysis, engineering solution design requires effective uncertainty management. Here we incorporate the regret theory of economics and decision science into the dynamic-adaptation-pathways framework and assess the impacts of high rates of changes on the flood defence systems in Shanghai. Specific options are developed to manage flooding on the Huangpu River from tidal water levels, river flows, rainfall, drainage inflows and combinations of these flood sources including sea level rises of up to 3 m. Dynamic adaptation pathways are developed where the timing of tipping points from one intervention to the next depends on the actual changes in sea level, rainfall and other variables that affect the future design. This framework is potentially applicable for planning ‘no regrets’ flood-defence systems in other low-lying coastal cities.