Hasil untuk "River protective works. Regulation. Flood control"

Fengling Yu, Junyang Ma, Zhaoquan Huang et al.

Deep insight into the spatialtemporal composition and distribution dynamics of suspended particulate organic carbon (POC) and sedimentary total organic carbon (TOC) within the mountainous river-estuary-bay continuum provides us with a unique perspective for examining the impact of estuarine flow on the material cycle within the river-estuary-bay systems. In this study, we conducted a comparative analysis of the river-estuary-bay continuum of two subtropical mountainous rivers, the Jiulong River (JLR) and the Zhangjiang River (ZJR), southern China. Seasonal samples of suspended particles and surface sediments were collected from the lower river reaches, estuaries, and bay areas. Both suspended and sedimentary samples were analyzed for organic content and their isotopic signatures (δ13C), and C/N ratios. The results reveal notable differences between the two systems. The JLR system exhibits stronger seasonal and spatial variations in POC sources compared to the ZJR system. In contrast, the estuary and bay of the ZJR system show more pronounced marine POC signals than those of the JLR system. In the sediments of the estuary and bay, soil organic matter and C3 plants contribute to over 60 % of the total organic matter in the JLR system, whereas in the ZJR system, marine organic matter and soil are the two most significant contributors. This study identifies that estuarine hydraulic conditions control the provenance, dynamics, and fate of particulate organic matter (POM). River discharge plays a pivotal role in regulating the dispersion of terrestrial organic matter in the estuary; Estuarine circulation and the position of the turbidity maximum zone govern the temporal and spatial distribution of sedimentary organic matter. Moreover, high soil contribution to the estuarine and bay sediment organic matter suggests strong soil erosion of adjacent land, likely attributed to human activities. Our findings highlight the high sensitivity of POC composition and dynamics in these mountainous river-estuary-bay systems to changes in river discharge, tidal current, and maybe wave conditions. The results of this study will deepen our understanding of the dynamics and fate of POM from different sources within the mountainous river-estuary-bay continuum and provide vital information for the effective management of these highly dynamic and sensitive ecosystems.

Jayesh Parmar, Subhankar Karmakar, Cheng Zhang et al.

ABSTRACT China has complex topography, diverse flood mechanisms, and high population exposure, making it highly vulnerable to flooding, highlighting the need for robust national‐scale hazard assessments to identify flood‐prone regions. However, most existing hazard studies are limited to regional scales or rely on empirical indicator‐based methods that overlook flood dynamics. While some global‐scale studies use physics‐based modeling, they offer little insight into China and rarely consider reservoir operations. This study advances national‐scale flood hazard mapping for China using the hydrodynamic Global Flood Model, CaMa‐Flood (v4.2). Simulations driven by ERA5‐Reanalysis runoff showed stronger agreement with observed streamflow than ERA5‐Land. Flood frequency analysis identified the nonparametric Kernel Density Estimator as the most suitable approach. The resulting 0.05° flood hazard maps reveal that nearly half of mainland China faces some level of 1‐in‐100‐year flood hazard, with 26% in the high to very high category. Incorporating reservoir operations reduced the number of national high hazard areas by up to 31%, underscoring their vital role in mitigation. The derived hazard, population exposure, and GDP‐based analysis provide a data‐driven foundation for national and provincial flood risk management, offering a scalable framework for robust hazard assessment and improved exposure and flood risk evaluation.

Emmanuel Junior Wafo Wembe, Adnane Saoud

In this paper, we revisit the computation of controlled invariant sets for linear discrete-time systems through a trajectory-based viewpoint. We begin by introducing the notion of convex feasible points, which provides a new characterization of controlled invariance using finitely long state trajectories. We further show that combining this notion with the classical backward fixed-point algorithm allows us to compute the maximal controlled invariant set. Building on these results, we propose two MPC schemes that guarantee recursive feasibility without relying on precomputed terminal sets. Finally, we formulate the search for convex feasible points as an optimization problem, yielding a practical computational method for constructing controlled invariant sets. The effectiveness of the approach is illustrated through numerical examples.

Qingcheng Yu, Colin D. Rennie, Jonathan M. Slaney

Zhufeng Li, Haixing Liu, Zeyu Fu et al.

ABSTRACT Rainfall‐driven urban surface water flooding is one of the most common natural disasters that lead to traffic disruption, economic loss, and even casualties. Assessing its hazards is critical not only for flood management but also for urban and territorial planning. Physics‐based models can simulate hydrological and hydraulic processes to predict floods; however, they are computationally expensive for large‐scale and high‐resolution simulations. This study presents a U‐Net‐based deep learning method for assessing the hazard levels of urban surface water flooding. The approach adopts three methods to improve the baseline U‐net model: (1) Squeeze‐and‐Excitation Blocks that enhance feature representation; (2) Focal Loss, a loss function that mitigates the influence of data imbalance; and (3) Random Cutout, a data augmentation method that prevents overfitting. Catchment data are used as input to train the deep learning model against flood hazard targets under three different levels of annual exceedance events. The results showed that the models are capable of identifying mid and high hazards. The proposed three methods mutually constrained each other and can reduce the influence of data imbalance. The proposed model demonstrates potential for practical flood management through rapid and accurate identification of high‐risk areas.

Danny Otto, Zora Reckhaus, Christian Kuhlicke

ABSTRACT Previous research has indicated the important role of social infrastructures during and after flood events. While struggling to uphold their caring responsibilities, they are also deemed relevant for coping and rebuilding after a disaster. We revisit this line of argument for the 2021 flood event in western Germany to deepen the understanding of the societal dimension of caring, coping and rebuilding (CCR) in and after flood events. Based on 21 semi‐structured interviews in three case study regions, we analyse how social infrastructures were affected during the flood, their contribution to resilience in the acute and rebuilding phases, and factors influencing their response to extreme events. Moving beyond the conventional focus on technical solutions for flood management, our study examines the significant societal aspects of responding to and recovering from flood events. Our research empirically underscores the critical role of social infrastructure during and after flood events. Recognising the assistance provided by these infrastructures, our findings offer a basis for policy recommendations. Ensuring sufficient financial and political support for social infrastructures is crucial, as is actively involving them in rebuilding initiatives. These measures are vital for facilitating the expansion of social infrastructure and enhancing its resilience potential during flood events.

Weronika Warachowska, Gábor Ungvári, András Kis et al.

Abstract The implementation of nature‐based solutions that involve natural processes to mutually decrease flood risk and protect natural ecosystems can be an answer to the demand for resilient flood risk management (FRM). As an example of a nature‐based solution, flood polders have the potential to deliver those benefits; however, a need for innovation is observed in the field of redefining, combining, and reformulating existing approaches to improve the welfare and wellbeing of individuals and communities. This article aims to investigate polder implementation and management processes, perceived as a potential introduction of social innovation in Poland and Hungary, where social innovation in FRM is required but where the introduction of innovative solutions stalls at different stages. Based on a comparative analysis, a set of factors for effective social innovation was formulated regarding formal and legal conditions and economic and social aspects of polder management and implementation. Each of identified factors can either allow or hinder public engagement and successful social innovation.

Nathalia Silva‐Cancino, Leonardo Alfonso

Abstract Off‐stream reservoirs are artificial water storage structures that increase the flood risk of an area. In some places, related risk reduction plans are based on a risk classification of these structures, which follows local water resource management regulations. These classification methods typically follow deterministic qualitative guidelines that do not account for uncertainties. This study introduces a fourth‐step probabilistic approach that accounts for uncertainties related to simultaneous breach formation and breaking point location of off‐stream reservoirs, and proposes an alternative visualisation for their classification. The methodology is applied to a set of Spanish off‐stream reservoirs that are classified according to the Spanish normative. Results show that different breaking points and breach formations generate diverse classifications that can affect risk reduction plans. Additionally, we demonstrate that the proposed visualisation can be used for various purposes, including the case of the evolution of the categorisation in time, due to land use changes, which could be used by decision‐makers to understand which off‐stream reservoir requires a category update. These findings introduce a novel approach to managing uncertainties, which is crucial for developing resilient flood management strategies and contributes to the innovation discourse in flood risk management.

Linda Sainio, Lauri Hooli, Msilikale Msilanga et al.

ABSTRACT Urban flooding is a major socio‐economic challenge in many cities of the Global South. Inadequate and unequal urban planning often excludes the poor majority, while rapid urban change makes it difficult to obtain reliable, up‐to‐date data for flood management. This study investigates changes in the river channel and informal settlements along the Msimbazi River in Dar es Salaam, one of the world's fastest‐growing cities, which faces increasingly severe annual flooding. We use high‐resolution satellite imagery, open elevation data, and a relative elevation model approach to map flood‐prone areas and analyze flood‐induced transformations between 2013 and 2022. Our findings show that even a small change in the Msimbazi River's water level leads to significant shifts in flood zones, with risk areas evolving during each flood event. During the study period, flooding also triggered substantial geomorphological changes in areas not included in existing flood risk maps. These changes would have remained undetected without high‐resolution imagery or field investigations. Informal settlements underwent considerable spatial shifts following floods, disproportionately affecting the most vulnerable populations. Informal settlements were also expanding further away from the city center, where flood risks are primarily geomorphological rather than driven by overbank flooding and thus overlooked in the local flood risk assessments. The results of this study emphasize the need to integrate geomorphological insights and vulnerability indicators into flood risk assessments and to engage civil society in the process. Additionally, they highlight the importance of making high‐resolution satellite data widely accessible, ensuring that its benefits extend beyond wealthier groups.

Juliette Godet, Olivier Payrastre, Qifan Ding et al.

ABSTRACT Due to climate change and rapid urbanisation, flash floods are becoming increasingly threatening, making real‐time flash flood monitoring and early warning systems a crucial adaptation measure. In France, the Vigicrues Flash system, operational since 2017, uses a simplified rainfall‐runoff model to issue short‐range flood warnings for small‐to‐medium ungauged basins, covering about 10,000 municipalities. Seven years on, we assess its performance on a large spatio‐temporal scale, using a multi‐indicator approach. First, hydrological validation is conducted using discharge data from gauging stations and post‐event campaigns, applying a contingency‐based approach with flood thresholds from 2‐ to 1000‐year return periods. Results show promising flood detection rates (mean CSI: 40%–70%) and indicate that expanding the system's coverage is feasible without reducing performance. Next, we evaluate its capacity to detect damaging events using the French CatNat database of natural disaster decrees. Finally, we document a survey of system users to capture their perception of its effectiveness and operational value. However, the high number of false alarms in the impact‐based assessment highlights the urgent need for impact‐oriented forecasts and warnings.

Thanin Quartz, Maxwell Fitzsimmons, Jun Liu

We show that the existence of a strictly compatible pair of control Lyapunov and control barrier functions is equivalent to the existence of a single smooth Lyapunov function that certifies both asymptotic stability and safety. This characterization complements existing literature on converse Lyapunov functions by establishing a partial differential equation (PDE) characterization with prescribed boundary conditions on the safe set, ensuring that the safe set is exactly certified by this Lyapunov function. The result also implies that if a safety and stability specification cannot be certified by a single Lyapunov function, then any pair of control Lyapunov and control barrier functions necessarily leads to a conflict and cannot be satisfied simultaneously in a robust sense.

Elias Niepötter, Adrian Grimm, Torbjørn Cunis

As the relevance of control systems capable of dealing with multiple objectives rises (e.g. being economic while maintaining a certain performance), multi-objective Switched Model Predictive Control combines all the advantages of Model Predictive Control while dealing with multiple objectives. We propose two novel frameworks, a nominal and a robust framework to guarantee recursive feasibility of each Model Predictive Controller under arbitrary switching and assure asymptotic stability of the closed-loop system applying the nominal framework and Input-to-State stability using the robust framework. The presented frameworks employ methods from switched systems, enabling the utilization of a supervisor control instance which allows for complex objectives and multi-objective control. Our numerical example confirms the superior performance of our proposed frameworks compared to a standard Model Predictive Control approach.

Leroy D'Souza, Yash Vardhan Pant, Sebastian Fischmeister

Improving the predictive accuracy of a dynamics model is crucial to obtaining good control performance and safety from Model Predictive Controllers (MPC). One approach involves learning unmodelled (residual) dynamics, in addition to nominal models derived from first principles. Varying residual models across an environment manifest as modes of a piecewise residual (PWR) model that requires a) identifying how modes are distributed across the environment and b) solving a computationally intensive Mixed Integer Nonlinear Program (MINLP) problem for control. We develop an iterative mapping algorithm capable of predicting time-varying mode distributions. We then develop and solve two tractable approximations of the MINLP to combine with the predictor in closed-loop to solve the overall control problem. In simulation, we first demonstrate how the approximations improve performance by 4-18% in comparison to the MINLP while achieving significantly lower computation times (upto 250x faster). We then demonstrate how the proposed mapping algorithm incrementally improves controller performance (upto 3x) over multiple iterations of a trajectory tracking control task even when the mode distributions change over time.

Mochammad Danara Indra Pradigta, Sony Susanto, Herlan Pratikto

This study aims to analyze the potential for flooding in the Konto River, Gudo District, Jombang Regency, this study uses the Gumbel and Log Pearson III statistical methods. Floods in this area often occur due to rainwater flow from the surrounding mountains which causes damage to infrastructure and settlements. Maximum daily rainfall data from 2013 to 2023 are used in this analysis. The Gumbel method is a statistical technique that is often used to analyze extreme rainfall data. The Gumbel and Log Pearson III methods are applied to estimate the design rainfall based on the flood return period, which is useful in infrastructure planning and flood mitigation. The calculation results show that the design rainfall increases with the increase in the return period. Compared to the Log Pearson III method, the Gumbel method provides higher design rainfall results, making it more suitable for estimating extreme rainfall in this area. These results are important in efforts to manage water resources and control flooding in the Konto River. The design rainfall will increase with the longer return period. This means that the higher the design rainfall, the smaller the possibility of it happening again. The results of the calculations show that the three methods can be used to calculate the planned rainfall, because the differences between one method and another are not much different, but the most suitable method to use is the gumbell method because the planned rainfall value is greater.

Yusuke Hiraga, Yoshihiko Iseri, Michael D. Warner et al.

Abstract This study proposes a model‐based methodology to estimate design precipitation for long durations during the winter and spring seasons (October to June) through its application to the drainage areas of two dams in the Columbia River Basin, United States. For basins with large reservoir storage or snowpack, design precipitation and floods need to be estimated based on long‐duration processes rather than focusing only on flood peaks or single storm durations. This study used the advanced research version of weather research and forecasting (WRF) model to maximize the target precipitation over the drainage areas by means of the Atmospheric Boundary Condition Shifting and Relative Humidity Perturbation with relaxed moisture flux thresholds. The greatest cumulative basin‐average precipitation depths during Oct–Jun were estimated to be 1220.5 and 1595.4 mm for the drainage areas of Bonneville and Libby Dams, respectively. The 95% confidence interval (CI) of the exceedance probabilities of the estimated design precipitation depths were found to range from 10−3 to 10−5 at Bonneville Dam's drainage area. Those orders were found to be comparable with the documented exceedance probabilities of PMP/PMF in the US. The estimated design precipitation and corresponding atmospheric/land‐surface fields together will drive a physical model to estimate the design flood.

F. Monger, D. V. Spracklen, M. J. Kirkby et al.

Abstract Woodlands can reduce downstream flooding, but it is not well known how the extent and distribution of woodland affects reductions in peak flow. We used the spatially distributed TOPMODEL to simulate peak flow during a 1 in 50 year storm event for a range of broadleaf woodland scenarios across a 2.6 km2 catchment in Northern England. Woodland reduced peak flow by 2.6%–15.3% depending on the extent and spatial distribution of woodland cover. Cross slope and riparian woodland resulted in larger reductions in peak flow, 4.9% and 3.3% for a 10‐percentage point increase in woodland cover respectively, compared to a 2.7% reduction for woodland randomly located across the catchment. Our results demonstrate that increased woodland cover can reduce peak flows during a large storm event and suggest that targeted placement of woodland can maximise the effectiveness of natural flood management interventions.

Abreham Birhane Kassay, Abraham Woldemichael Tuhar, Mihret Dananto Ulsido

Abstract Hawassa is a rapidly developing city in Lake Hawassa watershed of Ethiopia. Analyzing the effect of land cover dynamics on surface runoff remains imperative to adaptive urban stormwater management. This study quantified spatial variation of land cover and sensitivity of stormwater management response. Historical 30 years of daily annual rainfall, three satellite imageries, DEM, and hydrological soil group data were analyzed. A statistical‐based combined approach of geospatial techniques and Soil Conservation Service‐Curve Number (SCS‐CN) model was employed. CN and surface runoff depth for the delineated urban watersheds were determined. The result revealed that the built‐up area increased by 30.9 km2, where the rate varies spatially. The variation of impervious land cover explains 58.6% of change in CN with coefficient of 0.352. While CN is inversely correlated with agricultural and vegetation land cover variations. The finding suggests CN explains 96.78% of the change in surface runoff with a significant correlation coefficient of 3.91. The proposed integrated model approach justifies the potential to reorganize the relationship between the spatial effect of land cover variation on surface runoff at the urban watersheds. Thus, suitable local‐specific solutions can be devised for effective management of flood risk and optimize the drainage system of urban areas.

Cédric Join, Emmanuel Delaleau, Michel Fliess

Algebraically speaking, linear time-invariant (LTI) systems can be considered as modules. In this framework, controllability is translated as the freeness of the system module. Optimal control mainly relies on quadratic Lagrangians and the consideration of any basis of the system module leads to an open-loop control strategy via a linear Euler-Lagrange equation. In this approach, the endpoint is easily assignable and time horizon can be chosen to minimize the criterion. The loop is closed via an intelligent controller derived from model-free control, which exhibits excellent performances concerning model mismatches and disturbances. The extension to nonlinear systems is briefly discussed.

Fatima Azhar, Valentijn R. N. Pauwels, Ha H. Bui

Abstract This study combines laboratory experiments and numerical modelling in a novel manner to assess vehicle stability. Assessing vehicle stability forms the basis of hazard classification criteria, which in turn helps in forming safety guidelines for stream crossings and planning of evacuation routes in times of floods. These criteria are based on theoretical and physical model studies carried out on different vehicle models. This article demonstrates the application of a numerical method to determine the vehicle stability threshold so that the need for a physical model study for each kind of vehicle may be avoided. The numerical investigation is performed using smoothed particle hydrodynamics (SPH) with the vehicle oriented perpendicular to the flow direction, as this is the most critical orientation. A physical model study is also performed and its results are used to validate the SPH model. The results confirm the current Australian Rainfall and Runoff (ARR) safety criteria for stationary vehicles. It also suggests that the ARR stability curve can shift depending on the road conditions that affect the vehicle's sliding mechanism.

Francesca Ceccato, Paolo Simonini

Abstract This article discusses the levee failure that occurred on 6 December 2020 at Castelfranco Emilia, near Modena (Italy), showing that it cannot be explained without assuming the presence of local heterogeneities or a small cavity. The possible presence of these defects is supported by evidence derived from historical data and site observations. Fully coupled hydromechanical finite element simulations prove that the river embankment assumed without any deficiency had a sufficient level of safety for the considered event, thus it is necessary to hypothesize the presence of a local defect. The presence of a small cavity, in hydraulic communication with the river and buried at shallow depth, is assumed. This could be, for example, a new den, an old animal burrow repaired only partially, or a rotten plant root. Numerical analysis shows that the increase in water pressure within the cavity can trigger local failure of the landside slope, thus starting concentrated erosion. In highly erodible soils, this mechanism can lead very rapidly to the opening of the breach. A new analytical expression for the factor of safety of the soil wedge between the cavity and the surface is proposed. This approach is very simple and easily applicable, for example, to the assessment of levee vulnerability to animal burrows at a large scale. The results of the study are relevant for the management of water retaining structures.