Time Aware F-Score for Cybersecurity Early Detection Evaluation

[Abstract]: With the increase in the use of Internet interconnected systems, security has become of utmost importance. One key element to guarantee an adequate level of security is being able to detect the threat as soon as possible, decreasing the risk of consequences derived from those actions. In this paper, a new metric for early detection system evaluation that takes into account the delay in detection is defined. Time aware F-score (TaF) takes into account the number of items or individual elements processed to determine if an element is an anomaly or if it is not relevant to be detected. These results are validated by means of a dual approach to cybersecurity, Operative System (OS) scan attack as part of systems and network security and the detection of depression in social media networks as part of the protection of users. Also, different approaches, oriented towards studying the impact of single item selection, are applied to final decisions. This study allows to establish that nitems selection method is usually the best option for early detection systems. TaF metric provides, as well, an adequate alternative for time sensitive detection evaluation.This work was supported in part by the Ministry of Economy and Competitiveness of Spain and Fondo Europeo de Desarrollo Regional (FEDER) Funds of the European Union under Project PID2019-111388GB-I00; and in part by the Centro de Investigación de Galicia—Centro de Investigación en Tecnologías de la Información y las Comunicaciones (CITIC) Funded by Xunta de Galicia and the European Union (European Regional Development Fund–Galicia 2014-2020 Program), under Grant ED431G 2019/01.Xunta de Galicia; ED431G 2019/0

Multiscale flood risk assessment under climate change: the case of the Miño river in the city of Ourense, Spain

[Abstract:] River floods, which are one of the most dangerous natural hazards worldwide, have increased in intensity and frequency in recent decades as a result of climate change, and the future scenario is expected to be even worse. Therefore, their knowledge, predictability, and mitigation represent a key challenge for the scientific community in the coming decades, especially in those local areas that are most vulnerable to these extreme events. In this sense, a multiscale analysis is essential to obtain detailed maps of the future evolution of floods. In the multiscale analysis, the historical and future precipitation data from the CORDEX (Coordinated Regional Downscaling Experiment) project are used as input in a hydrological model (HEC-HMS) which, in turn, feeds a 2D hydraulic model (Iber+). This integration allows knowing the projected future changes in the flow pattern of the river, as well as analyzing the impact of floods in vulnerable areas through the flood hazard maps obtained with hydraulic simulations. The multiscale analysis is applied to the case of the Miño-Sil basin (NW Spain), specifically to the city of Ourense. The results show a delay in the flood season and an increase in the frequency and intensity of extreme river flows in the Miño-Sil basin, which will cause more situations of flooding in many areas frequented by pedestrians and in important infrastructure of the city of Ourense. In addition, an increase in water depths associated with future floods was also detected, confirming the trend for future floods to be not only more frequent but also more intense. Detailed maps of the future evolution of floods also provide key information to decision-makers to take effective measures in advance in those areas most vulnerable to flooding in the coming decades. Although the methodology presented is applied to a particular area, its strength lies in the fact that its implementation in other basins and cities is simple, also taking into account that all the models used are freely accessible.Xunta de Galicia; ED431C 2021/44FEDER; 0034_RISC_ML_6_EXunta de Galicia; ED481B-2021-10

Comparison of machine learning techniques for reservoir outflow forecasting

Número especial: Advances in machine learning for natural hazards risk assessment[Abstract:] Reservoirs play a key role in many human societies due to their capability to manage water resources. In addition to their role in water supply and hydropower production, their ability to retain water and control the flow makes them a valuable asset for flood mitigation. This is a key function, since extreme events have increased in the last few decades as a result of climate change, and therefore, the application of mechanisms capable of mitigating flood damage will be key in the coming decades. Having a good estimation of the outflow of a reservoir can be an advantage for water management or early warning systems. When historical data are available, data-driven models have been proven a useful tool for different hydrological applications. In this sense, this study analyzes the efficiency of different machine learning techniques to predict reservoir outflow, namely multivariate linear regression (MLR) and three artificial neural networks: multilayer perceptron (MLP), nonlinear autoregressive exogenous (NARX) and long short-term memory (LSTM). These techniques were applied to forecast the outflow of eight water reservoirs of different characteristics located in the Miño River (northwest of Spain). In general, the results obtained showed that the proposed models provided a good estimation of the outflow of the reservoirs, improving the results obtained with classical approaches such as to consider reservoir outflow equal to that of the previous day. Among the different machine learning techniques analyzed, the NARX approach was the option that provided the best estimations on average.FEDER; 0034_RISC_ML_6_EXunta de Galicia; ED431C 2021/44Xunta de Galicia; ED481B-2021-108Universidade de Vigo; 0000 131H TAL 64

O cambio climático

Os cambios no clima sucedéronse ao longo da historia do noso planeta debido a mecanismos naturais. Sen embargo, o cambio climático actual ten a singularidade de estar tamén afectado polo ser humano. Este efecto antropoxénico potencia o quecemento global, incrementando a velocidade dos cambios e limitando a capacidade de adaptación das especies ás novas condicións. Así, incluso variacións pequenas, como décimas de grao na temperatura, poden ser desfavorables para moitas especies, levando á extinción dalgunhas delas. O coñecemento dos cambios climáticos, tanto os pasados coma o actual, permite desenvolver ferramentas de mitigación e adaptación para enfrontarse aos cambios futuros do mellor xeito posible

Towards an automatic early warning system of flood hazards based on precipitation forecast: the case of the Miño River (NW Spain)

[Abstract:] An early warning system for flood prediction based on precipitation forecast is presented. The system uses rainfall forecast provided by MeteoGalicia in combination with a hydrologic (Hydrologic Modeling System, HEC-HMS) and a hydraulic (Iber+) model. The upper reach of the Miño River and the city of Lugo (NW Spain) are used as a study area. Starting from rainfall forecast, HEC-HMS calculates the streamflow and Iber+ is automatically executed for some previously defined risk areas when a certain threshold is exceeded. The analysis based on historical extreme events shows that the system can provide accurate results in less than 1 h for a forecast horizon of 3 d and report an alert situation to decision makers.We especially thank Carlos Ruiz del Portal Florido, Head of the Hydrological Planning Office, Hydrographic Confederation of Miño-Sil River for helpful discussions and for providing access to real data within the context of INTERREG-POCTEP Programme project RISC_ML (Code: 0034_RISC_ML_6_E). This work was partially supported by the Water JPI-WaterWorks Programme under project Improving Drought and Flood Early Warning, Forecasting and Mitigation (IMDROFLOOD, code: PCIN-2015-243) and by Xunta de Galicia under project ED431C 2017/64-GRC “Programa de Consolidación e Estructuración de Unidades de Investigación Competitivas (Grupos de Referencia Competitiva)”.European Regional Development Fund (ERDF); 0034_RISC_ML_6_EXunta de Galicia; ED431C 2017/64-GR

Analysis of two sources of variability of basin outflow hydrographs computed with the 2D shallow water model Iber: Digital Terrain Model and unstructured mesh size

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract:] Modelling hydrological processes with fully distributed models based on the shallow water equations implies a high computational cost, which often limits the resolution of the computational mesh. Therefore, in practice, modellers need to find a compromise between spatial resolution, numerical accuracy and computational cost. Moreover, this balance is probably related to the accuracy and resolution of the underlying Digital Terrain Model (DTM). In this work, it is studied the effect of the DTM resolution and the size of the computational mesh on the results and on the runtime of a hydrological model based on the 2D shallow water equations. Seven rainfall events in four different basins have been modelled using 3 DTMs and 3 different mesh resolutions. The results obtained highlight the relevance of the vertical accuracy versus the horizontal resolution of the DTMs. Furthermore, it has been observed that mesh resolutions greater than 25 m, together with LiDAR-based DTMs with horizontal resolution greater than 25 m, provide comparable outflow hydrographs.Xunta de Galicia; ED481B-2021-108Xunta de Galicia; ED431C 2021/44Xunta de Galicia; ED431C 2018/56Fondo Europeo de Desarrollo Regional (FEDER); 0034_RISC_ML_6_

Numerical simulation of the deadliest flood event of Portugal: Unravelling the causes of the disaster

The flood event of November 25 and 26, 1967 corresponds to the deadliest storm affecting Portugal in recent centuries being responsible for >500 fatalities. The main trigger was the heavy rain that fell in just a few hours, provoking a rapid increase in river flows, although other concurrent circumstances had to occur to reach the dramatic water levels estimated in some affected places. However, even today, several important uncertainties related to water levels achieved and timing of floods remain. Here we aim to clarify some of the pending issues by applying suitable high performance numerical tools to elucidate the main conditioning factors that played a key role in the intensification of this dramatic flood. In particular, the analysis has been focused on Quintas village, the location most affected, where >100 fatalities were recorded, close to 2/3 of its total population at the time. The main conclusion provided by the numerical simulations was that a plugging of water flow downstream of Quintas village, favoured by a poor terrain maintenance coupled with the bottleneck created by topographic features, caused the critical over-elevation of water levels. Simulations also corroborate the rapid increase in water levels in Quintas village, with an estimated rise of >2 m in just two hours, as well as the occurrence of the flood during the night, preventing many people to be aware of the extreme danger they were facing and safeguarding themselves.Universidade de Vigo/CISU

How to mitigate flood events similar to the 1979 catastrophic floods in the lower Tagus

[Abstract:] The floods that struck the lower Tagus valley in February 1979 correspond to the most intense floods in this river and affected the largest number of people in a river flow event in Portugal during the last 150 years. In fact, the vast area affected significantly impacted circa 10 000 people in the lower Tagus sector (and an additional 7000 in other regions of Portugal), including thousands of people evacuated or made homeless. In this context, the present study focuses on an in-depth analysis of this event from a hydrodynamic perspective by means of the Iber+ numerical model and on developing strategies to mitigate the flood episodes that occur in the lower section of the Tagus River using the exceptional floods of February 1979 as a benchmark. In this sense, dam operating strategies were developed and analyzed for the most important dam along the Tagus River basin in order to propose effective procedures to take advantage of these infrastructures to minimize the effect of floods. Overall, the numerical results indicate a good agreement with watermarks and some descriptions of the 1979 flood event, which demonstrates the model capability to evaluate floods in the area under study. Regarding flood mitigation, results obtained indicate that the frequency of floods can be reduced with the proposed strategies, which were focused on providing optimal dam operating rules to mitigate flooding in the lower Tagus valley. In addition, hydraulic simulations corroborated an important decrease in water depth and velocity for the most extreme flood events, and also a certain reduction in the flood extension was detected. This confirms the effectiveness of the proposed strategies to help in reducing the flood impact in the lower Tagus valley through the efficient functioning of dams.This research has been partially supported by Xunta de Galicia, Consellería de Cultura, Educación e Universidade, under project ED431C 2021/44 “Programa de Consolidación e Estructuración de Unidades de Investigación Competitivas”. This research has also been partially supported by the European Regional Development Fund under the Interreg POCTEP project RISC_PLUS (code: 0031_RISC_PLUS_6_E). This research has also been partially funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/UIDB/50019/2020), UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020). Diego Fernández-Nóvoa was supported by Xunta de Galicia through a post-doctoral grant (ED481B-2021-108). Alexandre M. Ramos was supported by the Helmholtz “Changing Earth – Sustaining our Future” program. Cristina Catita was supported by EEA Financial Mechanism 2014–2021 and the Portuguese Environment Agency through Pre-defined Project 2 National Roadmap for Adaptation XXI (PDP-2). Orlando García-Feal was funded by the Spanish Ministerio de Universidades and European Union – NextGenerationEU – through a Margarita Salas post-doctoral grant. Ricardo M. Trigo was supported by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES, through project AMOTHEC – DRI/India/0098/2020 (https://doi.org/10.54499/DRI/India/0098/2020).Xunta de Galicia; ED431C 2021/44Xunta de Galicia; ED481B-2021-108European Regional Development Fund (ERDF); 0031_RISC_PLUS_6_EPortugal. Fundação para a Ciência e a Tecnologia (FCT); UIDB/50019/2020Portugal. Fundação para a Ciência e a Tecnologia (FCT); UIDP/50019/2020Portugal. Fundação para a Ciência e a Tecnologia (FCT); LA/P/0068/2020Portugal. Fundação para a Ciência e a Tecnologia (FCT); DRI/India/0098/202

The Rivillas flood of 5–6 November 1997 (Badajoz, Spain) revisited: an approach based on Iber+ modelling

Financiado para publicación en acceso aberto: Universidade de Vigo/CISUGThe flash flood registered in November 1997 in the city of Badajoz (Spain) in the basin of Rivillas river is analysed by means of the numerical code Iber+. This event constitutes one of the most destructive flash-floods registered in an urban area in the Iberian Peninsula. Starting from precipitation data obtained from rain stations, the runoff of the entire river basin was simulated to obtain the discharge of the Rivillas river in Badajoz. The flood maps obtained with Iber+ reproduce accurately the field data registered during the actual event. Likewise, the numerical time evolution of the flood and water depths are in accordance with testimonies of the witnesses. Once the capability of Iber+ to reproduce the event was assessed, several scenarios were considered in order to analyse the main causes of the event. In particular, simulations show that the catastrophic magnitude of the flood was mainly due to the blockage of bridges. Different hypothetical scenarios were simulated to analyze the role of rain intensity and bridge maintenance, concluding that similar floods can occur under much lower rainfall but with poor bridge maintenance.Xunta de Galicia | Ref. ED431C 2021/44Xunta de Galicia | Ref. ED481B-2021-10

The Rivillas flood of 5–6 November 1997 (Badajoz, Spain) revisited: An approach based on Iber+ modelling

[Abstract:] The flash flood registered in November 1997 in the city of Badajoz (Spain) in the basin of Rivillas river is analysed by means of the numerical code Iber+. This event constitutes one of the most destructive flash-floods registered in an urban area in the Iberian Peninsula. Starting from precipitation data obtained from rain stations, the runoff of the entire river basin was simulated to obtain the discharge of the Rivillas river in Badajoz. The flood maps obtained with Iber+ reproduce accurately the field data registered during the actual event. Likewise, the numerical time evolution of the flood and water depths are in accordance with testimonies of the witnesses. Once the capability of Iber+ to reproduce the event was assessed, several scenarios were considered in order to analyse the main causes of the event. In particular, simulations show that the catastrophic magnitude of the flood was mainly due to the blockage of bridges. Different hypothetical scenarios were simulated to analyze the role of rain intensity and bridge maintenance, concluding that similar floods can occur under much lower rainfall but with poor bridge maintenance.This research was partially supported by under project RISC_ML (Code: 0034_RISC_ML_6_E) co-funded by the European Regional Development Fund (ERDF) and by Xunta de Galicia under Project ED431C 2021/44 “Programa de Consolidación e Estruturación de Unidades de Investigación (Grupos de Referencia Competitiva)”. DFN was supported by Xunta de Galicia through a post-doctoral grant (ED481B-2021-108). JMV was supported by the Economy and Infrastructure Counselling of the Junta of Extremadura through project IB20080 and grants GR21080 (co-financed by the European Regional Development Fund). The aerial pictures used in this work are courtesy of the Spanish IGN (Instituto Geográfico Nacional) and part of the PNOA (Plan Nacional de Ortofotografía Aérea) program.Xunta de Galicia; ED431C 2021/44Xunta de Galicia; ED481B-2021-108Junta de Extremadura; IB20080Junta de Extremadura; GR21080European Regional Development Fund (ERDF); 0034_RISC_ML_6_