| publications-2501 |
Peer reviewed articles |
2021 |
Dionysios Nikolopoulos, Christos Makropoulos |
Stress-testing water distribution networks for cyber-physical attacks on water quality |
Urban Water Journal |
10.1080/1573062x.2021.1995446 |
Simulation & Modeling |
Irrigation Systems |
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No abstract available |
740610 |
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| publications-2502 |
Peer reviewed articles |
2021 |
Gustavo González-Granadillo, Susana González-Zarzosa, Rodrigo Diaz |
Security Information and Event Management (SIEM): Analysis, Trends, and Usage in Critical Infrastructures |
Sensors |
10.3390/s21144759 |
Data Management & Analytics |
Irrigation Systems |
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Security Information and Event Management (SIEM) systems have been widely deployed as a powerful tool to prevent, detect, and react against cyber-attacks. SIEM solutions have evolved to become comprehensive systems that provide a wide visibility to identify areas of high risks and proactively focus on mitigation strategies aiming at reducing costs and time for incident response. Currently, SIEM systems and related solutions are slowly converging with big data analytics tools. We survey the most widely used SIEMs regarding their critical functionality and provide an analysis of external factors affecting the SIEM landscape in mid and long-term. A list of potential enhancements for the next generation of SIEMs is provided as part of the review of existing solutions as well as an analysis on their benefits and usage in critical infrastructures. |
740610 |
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| publications-2503 |
Peer reviewed articles |
2021 |
Bramha Dutt Vishwakarma, Martin Horwath, Andreas Groh, Jonathan L Bamber |
Accounting for GIA signal in GRACE products |
Geophysical Journal International |
10.1093/gji/ggab464 |
Data Management & Analytics |
Irrigation Systems |
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SUMMARY The Gravity Recovery and Climate Experiment (GRACE) observes gravitational potential anomalies that include the effects of present-day surface mass change (PDSMC)- and glacial isostatic adjustment (GIA)-driven solid Earth mass redistribution. Therefore, GIA estimates from a forward model are commonly removed from GRACE to estimate PDSMC. There are several GIA models and to facilitate users in using a GIA model of their choice, both GRACE and GIA products are made available in terms of global gridded fields representing mass anomaly. GRACE-observed gravitational potential anomalies are represented in terms of equivalent water height (EWH) with a relation that accounts for an elastic solid Earth deformation due to PDSMC. However, for obtaining GIA EWH fields from GIA gravitational potential fields, two relations are being used: one that is similar to that being used for GRACE EWH and the other that does not include an elastic deformation effect. This leaves users with the possibility of obtaining different values for PDSMC with a given GRACE and GIA field. In this paper, we discuss the impact of this problem on regional mass change estimates and highlight the need for consistent treatment of GIA signals in GRACE observations. |
841407 |
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| publications-2504 |
Peer reviewed articles |
2020 |
Bramha Dutt Vishwakarma |
Monitoring Droughts From GRACE |
Frontiers in Environmental Science |
10.3389/fenvs.2020.584690 |
Uncategorized |
Precipitation & Ecological Systems |
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With ongoing climate change, we are staring at possibly longer and more severe droughts in the future. Therefore, monitoring and understanding duration and intensity of droughts, and how are they evolving in space and time is imperative for global socio-economic security. Satellite remote sensing has helped us a lot in this endeavor, but most of the satellite missions observe only near-surface properties of the Earth. A recent geodetic satellite mission, GRACE, measured the water storage change both on and beneath the surface, which makes it unique and valuable for drought research. This novel dataset comes with unique problems and characteristics that we should acknowledge before using it. In this perspective article, I elucidate important characteristics of various available GRACE products that are important for drought research. I also discuss limitations of GRACE mission that one should be aware of, and finally I shed some light on latest developments in GRACE data processing that may open numerous possibilities in near future. |
841407 |
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| publications-2505 |
Peer reviewed articles |
2021 |
Essa Q. Shahra, Wenyan Wu, Roberto Gomez |
Human Health Impact Analysis of Contaminant in IoT-Enabled Water Distributed Networks |
Applied Sciences |
10.3390/app11083394 |
Data Management & Analytics |
Irrigation Systems |
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This paper aims to assess and analyze the health impact of consuming contaminated drinking water in a water distributed system (WDS). The analysis was based on qualitative simulation performed in two different models named hydraulic and water quality in a WDS. The computation focuses on quantitative analysis for chemically contaminated water impacts by analyzing the dose level in various locations in the water network and the mass of the substance that entered the human body. Several numerical experiments have been applied to evaluate the impact of water pollution on human life. They analyzed the impact on human life according to various factors, including the location of the injected node (pollution occurrence) and the ingested dose level. The results show a significant impact of water contaminant on human life in multiple areas in the water network, and the level of this impact changed from one location to another in WDSs based on several factors such as the location of the pollution occurrence, the contaminant concentration, and the dose level. In order to reduce the impact of this contaminant, water quality sensors have been used and deployed on the water network to help detect this contaminant. The sensors were optimally deployed based on the time-detection of water contamination and the volume of polluted water consumed. Numerical experiments were carried out to compare water pollution’s impact with and without using water quality sensors. The results show that the health impact was reduced by up to 98.37% by using water quality sensors. |
765921 |
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| publications-2506 |
Peer reviewed articles |
2021 |
Haitham H. Mahmoud, Wenyan Wu, Yonghao Wang |
WDSchain: A Toolbox for Enhancing the Security Using Blockchain Technology in Water Distribution System |
Water |
10.3390/w13141944 |
Data Management & Analytics |
Water Distribution Networks |
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This work develops a toolbox called WDSchain on MATLAB that can simulate blockchain on water distribution systems (WDS). WDSchain can import data from Excel and EPANET water modelling software. It extends the EPANET to enable simulation blockchain of the hydraulic data at any intended nodes. Using WDSchain will strengthen network automation and the security in WDS. WDSchain can process time-series data with two simulation modes: (1) static blockchain, which takes a snapshot of one-time interval data of all nodes in WDS as input and output into chained blocks at a time, and (2) dynamic blockchain, which takes all simulated time-series data of all the nodes as input and establishes chained blocks at the simulated time. Five consensus mechanisms are developed in WDSchain to provide data at different security levels using PoW, PoT, PoV, PoA, and PoAuth. Five different sizes of WDS are simulated in WDSchain for performance evaluation. The results show that a trade-off is needed between the system complexity and security level for data validation. The WDSchain provides a methodology to further explore the data validation using Blockchain to WDS. The limitations of WDSchain do not consider selection of blockchain nodes and broadcasting delay compared to commercial blockchain platforms. |
765921 |
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| publications-2507 |
Peer reviewed articles |
2021 |
Alexandra E. Ioannou, Enrico F. Creaco, Chrysi S. Laspidou |
Exploring the Effectiveness of Clustering Algorithms for Capturing Water Consumption Behavior at Household Level |
Sustainability |
10.3390/su13052603 |
AI & Machine Learning |
Water Distribution Networks |
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As water scarcity becomes more prevalent, the analysis of urban water consumption patterns at the consumer level and the estimation of the corresponding water demand for water utility are expected to be among the top priorities of water companies in the near future. This study proposes a comprehensive methodology for water managers to achieve an efficient operation of urban water networks, by successfully detecting residential water consumption patterns corresponding to different household needs and behaviors. The methodology uses Self Organizing Maps as the main clustering algorithm in combination with K-means and Hierarchical Agglomerative Clustering. The objective is to create clusters in a literature dataset that includes water consumption from 21 customers located in Milford, Ohio, USA, for a 7-month period. Originally, water consumption data was recorded for every water use incident in the household, while for this analysis, the information is converted to half-hourly water consumption. Individual customers with similar consumption behavior are clustered and water-consumption curves are calculated for each cluster; these curves can be used by the water utility to obtain estimates of the spatio-temporal distribution of demand, thus giving insight into peak demands at different locations. Statistical indices of agreement are used to confirm a good agreement between the estimated and observed water use, when clustering is employed. The resulting curves show a clear improvement in capturing water consumption behavior at household level, when compared to corresponding curves obtained without clustering. This analysis offers water utilities an innovative solution that relies on real time data and uses data science principles for optimizing water supply and network operation and provides tools for the efficient use of water resources. |
734409 |
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| publications-2508 |
Peer reviewed articles |
2020 |
Alexandra Spyropoulou, Chrysi Laspidou, Kostantinos Kormas, Yannis G. Lazarou |
The Impact of Possible Mercury Source-Point Contamination in the Coastal Area of Skiathos Island |
Environmental Sciences Proceedings |
10.3390/environsciproc2020002050 |
Uncategorized |
Natural Water Bodies |
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No abstract available |
734409 |
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| publications-2509 |
Peer reviewed articles |
2021 |
Qing Zhan, Cleo N. Stratmann, Harm G. van der Geest, Annelies J. Veraart, Kristof Brenzinger, Miquel Lürling, Lisette N. de Senerpont Domis |
Effectiveness of phosphorus control under extreme heatwaves: implications for sediment nutrient releases and greenhouse gas emissions |
Biogeochemistry |
10.1007/s10533-021-00854-z |
Simulation & Modeling |
Natural Water Bodies |
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AbstractEutrophication has been identified as the primary cause of water quality deterioration in inland waters worldwide, often associated with algal blooms or fish kills. Eutrophication can be controlled through watershed management and in-lake measures. An extreme heatwave event, through its impact on mineralization rates and internal nutrient loading (phosphorus—P, and nitrogen—N), could counteract eutrophication control measures. We investigated how the effectiveness of a nutrient abatement technique is impacted by an extreme heatwave, and to what extent biogeochemical processes are modulated by exposure to heatwaves. To this end, we carried out a sediment-incubation experiment, testing the effectiveness of lanthanum-modified bentonite (LMB) in reducing nutrients and greenhouse gas emissions from eutrophic sediments, with and without exposure to an extreme heatwave. Our results indicate that the effectiveness of LMB may be compromised upon exposure to an extreme heatwave event. This was evidenced by an increase in concentration of 0.08 ± 0.03 mg P/L with an overlying water volume of 863 ± 21 mL, equalling an 11% increase, with effects lasting to the end of the experiment. LMB application generally showed no effect on nitrogen species, while the heatwave stimulated nitrification, resulting in ammonium loss and accumulation of dissolved oxidized nitrogen species as well as increased dissolved nitrous oxide concentrations. In addition, carbon dioxide (CO2)-equivalent was more than doubled during the heatwave relative to the reference temperature, and LMB application had no effect on mitigating them. Our sediment incubation experiment indicates that the rates of biogeochemical processes can be significantly accelerated upon heatwave exposure, resulting in a change in fluxes of nutrient and greenhouse gas between sediment and water. The current efforts in eutrophication control will face more challenges under future climate scenarios with more frequent and intense extreme events as predicted by the IPCC. |
722518 |
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| publications-2510 |
Peer reviewed articles |
2021 |
Saniya Behzadpour, Torsten Mayer‐Gürr, Sandro Krauss |
GRACE Follow‐On Accelerometer Data Recovery |
Journal of Geophysical Research: Solid Earth |
10.1029/2020jb021297 |
Data Management & Analytics |
GRACE-FO |
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AbstractIn Gravity Recovery and Climate Experiment (GRACE) Follow‐on (GRACE‐FO) mission, similar to its predecessor GRACE, the twin satellites are equipped with three‐axis accelerometers, measuring the non‐gravitational forces. After 1 month in orbit, during the in‐orbit‐checkout phase, the noise on GRACE‐D accelerometer measurements elevated and resulted in systematical degradation of the data. For this reason, the GRACE‐D data need to be replaced by synthetic data, the so‐called transplant data, officially generated by the GRACE‐FO Science Data System (SDS). The SDS transplant data are derived from the GRACE‐C accelerometer measurements, by applying time and attitude corrections. Furthermore, model‐based residual accelerations due to thruster firings on GRACE‐D were added, proven to improve the data quality in gravity field recovery. However, preliminary studies of GRACE‐FO data during the single accelerometer months show that the low degree zonal harmonics, in particular C20 and C30, are sensitive to the current transplant approach. In this work, we present a novel approach to recover the GRACE‐D ACT1B data by incorporating non‐gravitational force models and analyze its impact on monthly gravity field solutions. The results show the improved ACT1B data not only contributed to a noise reduction but also improved the estimates of the C20 and C30 coefficients. The application of this new approach demonstrates that the offset between Satellite Laser Ranging (SLR) and GRACE‐FO derived C30 time series can be reduced by the use of the alternative accelerometer product. |
870353 |
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