Rapid spatio-temporal flood modelling via hydraulics-based graph neural networks

Numerical modelling is a reliable tool for flood simulations, but accurate solutions are computationally expensive. In recent years, researchers have explored data-driven methodologies based on neural networks to overcome this limitation. However, most models are only used for a specific case study and disregard the dynamic evolution of the flood wave. This limits their generalizability to topographies that the model was not trained on and in time-dependent applications. In this paper, we introduce shallow water equation–graph neural network (SWE–GNN), a hydraulics-inspired surrogate model based on GNNs that can be used for rapid spatio-temporal flood modelling. The model exploits the analogy between finite-volume methods used to solve SWEs and GNNs. For a computational mesh, we create a graph by considering finite-volume cells as nodes and adjacent cells as being connected by edges. The inputs are determined by the topographical properties of the domain and the initial hydraulic conditions. The GNN then determines how fluxes are exchanged between cells via a learned local function. We overcome the time-step constraints by stacking multiple GNN layers, which expand the considered space instead of increasing the time resolution. We also propose a multi-step-ahead loss function along with a curriculum learning strategy to improve the stability and performance. We validate this approach using a dataset of two-dimensional dike breach flood simulations in randomly generated digital elevation models generated with a high-fidelity numerical solver. The SWE–GNN model predicts the spatio-temporal evolution of the flood for unseen topographies with mean average errors in time of 0.04 m for water depths and 0.004 m2 s−1 for unit discharges. Moreover, it generalizes well to unseen breach locations, bigger domains, and longer periods of time compared to those of the training set, outperforming other deep-learning models. On top of this, SWE–GNN has a computational speed-up of up to 2 orders of magnitude faster than the numerical solver. Our framework opens the doors to a new approach to replace numerical solvers in time-sensitive applications with spatially dependent uncertainties.</p

Cost-benefit analysis of flood-zoning policies: A review of current practice

One commonly proposed method to limit flood risk is land-use or zoning policies which regulates construction in high-risk areas, in order to reduce economic exposure and its vulnerability to flood events. Although such zoning regulations can be effective in limiting trends in flood risk, they also have adverse impacts on society, for instance by limiting local development of areas near the water. In order to judge whether proposed land-use or zoning policies are a net benefit to society, they should be accepted or rejected based on a societal cost–benefit analysis (CBA). However, conducting a CBA of zoning regulation is complex and comprehensive guidelines of how to do such an analysis are lacking. We offer guidelines for good practice. In order to assess the costs and benefits of zoning as a climate change adaption strategy, they should be assessed at a societal level in order to account for public good features of flood risk reduction strategies, and because costs in one area can be benefits in another region. We propose a multistep process: first, determine the spatial extent of the zoning policy and how interconnected the zoned area is to other locations; second, conduct a CBA using monetary costs and benefits estimated from an integrated hydro-economic model to investigate if total benefits exceed total costs; third, conduct a sensitivity analysis regarding the main assumptions; fourth, conduct a multicriteria analysis (MCA) of the normative outcomes of a zoning policy. A desirable policy is preferred in both the CBA and MCA

A review of ransomware families and detection methods

Ransomware has become a significant problem and its impact is getting worse. It has now become a lucrative business as it is being offered as a service. Unlike other security issues, the effect of ransomware is irreversible and difficult to stop. This research has analysed existing ransomware classifications and its detection and prevention methods. Due to the difficulty in categorizing the steps none of the existing methods can stop ransomware. Ransomware families are identified and classified from the year 1989 to 2017 and surprisingly there are not much difference in the pattern. This paper concludes with a brief discussion about the findings and future work of this research

Causes of death and demographic characteristics of victims of meteorological disasters in Korea from 1990 to 2008

<p>Abstract</p> <p>Background</p> <p>Meteorological disasters are an important component when considering climate change issues that impact morbidity and mortality rates. However, there are few epidemiological studies assessing the causes and characteristics of deaths from meteorological disasters. The present study aimed to analyze the causes of death associated with meteorological disasters in Korea, as well as demographic and geographic vulnerabilities and their changing trends, to establish effective measures for the adaptation to meteorological disasters.</p> <p>Methods</p> <p>Deaths associated with meteorological disasters were examined from 2,045 cases in Victim Survey Reports prepared by 16 local governments from 1990 to 2008. Specific causes of death were categorized as drowning, structural collapse, electrocution, lightning, fall, collision, landslide, avalanche, deterioration of disease by disaster, and others. Death rates were analyzed according to the meteorological type, specific causes of death, and demographic and geographic characteristics.</p> <p>Results</p> <p>Drowning (60.3%) caused the greatest number of deaths in total, followed by landslide (19.7%) and structural collapse (10.1%). However, the causes of deaths differed between disaster types. The meteorological disaster associated with the greatest number of deaths has changed from flood to typhoon. Factors that raised vulnerability included living in coastal provinces (11.3 times higher than inland metropolitan), male gender (1.9 times higher than female), and older age.</p> <p>Conclusions</p> <p>Epidemiological analyses of the causes of death and vulnerability associated with meteorological disasters can provide the necessary information for establishing future adaptation measures against climate change. A more comprehensive system for assessing disaster epidemiology needs to be established.</p

Neural Synchrony during Response Production and Inhibition

Inhibition of irrelevant information (conflict monitoring) and/or of prepotent actions is an essential component of adaptive self-organized behavior. Neural dynamics underlying these functions has been studied in humans using event-related brain potentials (ERPs) elicited in Go/NoGo tasks that require a speeded motor response to the Go stimuli and withholding a prepotent response when a NoGo stimulus is presented. However, averaged ERP waveforms provide only limited information about the neuronal mechanisms underlying stimulus processing, motor preparation, and response production or inhibition. In this study, we examine the cortical representation of conflict monitoring and response inhibition using time-frequency analysis of electroencephalographic (EEG) recordings during continuous performance Go/NoGo task in 50 young adult females. We hypothesized that response inhibition would be associated with a transient boost in both temporal and spatial synchronization of prefrontal cortical activity, consistent with the role of the anterior cingulate and lateral prefrontal cortices in cognitive control. Overall, phase synchronization across trials measured by Phase Locking Index and phase synchronization between electrode sites measured by Phase Coherence were the highest in the Go and NoGo conditions, intermediate in the Warning condition, and the lowest under Neutral condition. The NoGo condition was characterized by significantly higher fronto-central synchronization in the 300–600 ms window, whereas in the Go condition, delta- and theta-band synchronization was higher in centro-parietal regions in the first 300 ms after the stimulus onset. The present findings suggest that response production and inhibition is supported by dynamic functional networks characterized by distinct patterns of temporal and spatial synchronization of brain oscillations

Dirac electrons in graphene-based quantum wires and quantum dots

In this paper we analyse the electronic properties of Dirac electrons in finite-size ribbons and in circular and hexagonal quantum dots made of graphene.Comment: Contribution for J. Phys.: Cond. Mat. special issue on graphene physic

Airfoil data sensitivity analysis for actuator disc simulations used in wind turbine applications

To analyse the sensitivity of blade geometry and airfoil characteristics on the prediction of performance characteristics of wind farms, large-eddy simulations using an actuator disc (ACD) method are performed for three different blade/airfoil configurations. The aim of the study is to determine how the mean characteristics of wake flow, mean power production and thrust depend on the choice of airfoil data and blade geometry. In order to simulate realistic conditions, pre-generated turbulence and wind shear are imposed in the computational domain. Using three different turbulence intensities and varying the spacing between the turbines, the flow around 4-8 aligned turbines is simulated. The analysis is based on normalized mean streamwise velocity, turbulence intensity, relative mean power production and thrust. From the computations it can be concluded that the actual airfoil characteristics and blade geometry only are of importance at very low inflow turbulence. At realistic turbulence conditions for an atmospheric boundary layer the specific blade characteristics play an minor role on power performance and the resulting wake characteristics. The results therefore give a hint that the choice of airfoil data in ACD simulations is not crucial if the intention of the simulations is to compute mean wake characteristics using a turbulent inflow