scholarly journals Self-sustainable early warning system in river currents

2017 ◽  
Vol 22 (2) ◽  
pp. 69-88
Author(s):  
Jauder Alexander Ocampo Toro ◽  
Juan Pablo Alzate Sanchez ◽  
Ángel David Chancy Villa ◽  
Sebastián Valencia Cardona
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Text Messaging ◽  
Alternative Energy ◽  
High Speed ◽  
Warning System ◽  
Water Levels ◽  
Advanced Technology ◽  
Effective Response ◽  
Rapid Communication

Half of the natural disasters are due to floods of all kinds, leaving thousands dead and injured, as well as costly material damages. An early warning system (EWS) is a vital tool to reduce disaster risk but requires components that allow rapid communication and effective response of people at risk. Contribution of advanced technology has been fundamental in the prevention of catastrophes, but unfortunately, its high cost, among other factors, does not allow its coverage to reach developing countries or to communities in areas of higher vulnerability. This was evident in Colombia, where EWS exists for large-scale phenomena, but where river floods in poor municipalities meant the country's greatest tragedies in recent years. Hence the importance of designing the self-sustaining early warning system in river currents, since it combines state-of-the-art but low-cost technological elements, allowing it to operate autonomously from alternative energy sources, continuously and accurately measure the current fluvial level, and send real-time alert signals via high-speed and efficient wireless communication protocols. Construction of a prototype of the system made it possible to test and verify the functionality and efficiency of the monitoring stations, both in accuracy and speed in measures of increasing water levels, as well as in the rapid communication of alerts to an end-user, through cell phone text messaging.

scholarly journals Can an early warning system help minimize the impacts of coastal storms? A case study of the 2012 Halloween storm, Northern Italy

2015 ◽  
Vol 3 (5) ◽  
pp. 3409-3448 ◽  
Author(s):  
M. D. Harley ◽  
A. Valentini ◽  
C. Armaroli ◽  
L. Perini ◽  
L. Calabrese ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Numerical Models ◽  
Warning System ◽  
Northern Italy ◽  
Water Levels ◽  
Storm Event ◽  
Forecast Performance ◽  
High Hazard ◽  
Key Sites

Abstract. The Emilia-Romagna Early Warning System (ER-EWS) is a state-of-the-art coastal forecasting system that comprises a series of numerical models (COSMO, ROMS, SWAN and XBeach) to obtain a daily three-day forecast of coastal storm hazard at eight key sites along the Emilia-Romagna coastline (Northern Italy). On the night of 31 October 2012, a major storm event occurred that resulted in elevated water levels (equivalent to a 1-in-20 to 1-in-50-year event) and widespread erosion and flooding. Since this storm happened just one month prior to the roll-out of the ER-EWS, the forecast performance related to this event is unknown. The aim of this study was to therefore reanalyse the ER-EWS as if it had been operating a day before the event and determine to what extent the forecasts may have helped reduce storm impacts. Three different reanalysis modes were undertaken: (1) a default forecast (DF) mode based on three-day wave and water-level forecasts and default XBeach parameters, (2) a "perfect" offshore (PO) forecast mode using measured offshore values and default XBeach parameters; and (3) a calibrated XBeach (CX) mode using measured offshore values and an optimized parameter set obtained through an extensive calibration process. The results indicate that while a "code red" alert would have been issued for the DF mode, an underprediction of the extreme water levels of this event limited high-hazard forecasts to only two of the eight ER-EWS sites. Forecasts based on measured offshore conditions (the PO mode) more-accurately indicate high hazard conditions for all eight sites. Further considerable improvements are observed using an optimized XBeach parameter set (the CX mode) compared to default parameters. A series of what-if scenarios at one of the sites show that artificial dunes, which are a common management strategy along this coastline, could have hypothetically been constructed as an emergency procedure to potentially reduce storm impacts.

An early warning system for detecting GSM-R wireless interference in the high-speed railway infrastructure

2010 ◽  
Vol 3 (3-4) ◽  
pp. 140-156 ◽  
Author(s):  
Gianmarco Baldini ◽  
Igor Nai Fovino ◽  
Marcelo Masera ◽  
Marco Luise ◽  
Vincenzo Pellegrini ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
High Speed ◽  
Warning System ◽  
High Speed Railway ◽  
Wireless Interference ◽  
Railway Infrastructure

scholarly journals Can an early-warning system help minimize the impacts of coastal storms? A case study of the 2012 Halloween storm, northern Italy

2016 ◽  
Vol 16 (1) ◽  
pp. 209-222 ◽  
Author(s):  
M. D. Harley ◽  
A. Valentini ◽  
C. Armaroli ◽  
L. Perini ◽  
L. Calabrese ◽  
...  
Keyword(s):  
Water Level ◽  
Early Warning ◽  
Early Warning System ◽  
Numerical Models ◽  
Warning System ◽  
Northern Italy ◽  
Water Levels ◽  
Storm Event ◽  
Forecast Performance ◽  
High Hazard

Abstract. The Emilia-Romagna early-warning system (ER-EWS) is a state-of-the-art coastal forecasting system that comprises a series of numerical models (COSMO, ROMS, SWAN and XBeach) to obtain a daily 3-day forecast of coastal storm hazard at eight key sites along the Emilia-Romagna coastline (northern Italy). On the night of 31 October 2012, a major storm event occurred that resulted in elevated water levels (equivalent to a 1-in-20- to 1-in-50-year event) and widespread erosion and flooding. Since this storm happened just 1 month prior to the roll-out of the ER-EWS, the forecast performance related to this event is unknown. The aim of this study was to therefore reanalyse the ER-EWS as if it had been operating a day before the event and determine to what extent the forecasts may have helped reduce storm impacts. Three different reanalysis modes were undertaken: (1) a default forecast (DF) mode based on 3-day wave and water-level forecasts and default XBeach parameters; (2) a measured offshore (MO) forecast mode using wave and water-level measurements and default XBeach parameters; and (3) a calibrated XBeach (CX) mode using measured boundary conditions and an optimized parameter set obtained through an extensive calibration process. The results indicate that, while a "code-red" alert would have been issued for the DF mode, an underprediction of the extreme water levels of this event limited high-hazard forecasts to only two of the eight ER-EWS sites. Forecasts based on measured offshore conditions (the MO mode) more-accurately indicate high-hazard conditions for all eight sites. Further considerable improvements are observed using an optimized XBeach parameter set (the CX mode) compared to default parameters. A series of what-if scenarios at one of the sites show that artificial dunes, which are a common management strategy along this coastline, could have hypothetically been constructed as an emergency procedure to potentially reduce storm impacts.

scholarly journals Threshold Definition for Monitoring Gapa Landslide under Large Variations in Reservoir Level Using GNSS

2021 ◽  
Vol 13 (24) ◽  
pp. 4977
Author(s):  
Shuangshuang Wu ◽  
Xinli Hu ◽  
Wenbo Zheng ◽  
Matteo Berti ◽  
Zhitian Qiao ◽  
...  
Keyword(s):  
Water Level ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Early Warning Systems ◽  
Water Levels ◽  
Deformation Model ◽  
Warning Systems ◽  
Velocity Threshold ◽  
Landslide Deformation

The triggering threshold is one of the most important parameters for landslide early warning systems (EWSs) at the slope scale. In the present work, a velocity threshold is recommended for an early warning system of the Gapa landslide in Southwest China, which was reactivated by the impoundment of a large reservoir behind Jinping’s first dam. Based on GNSS monitoring data over the last five years, the velocity threshold is defined by a novel method, which is implemented by the forward and reverse double moving average of time series. As the landslide deformation is strongly related to the fluctuations in reservoir water levels, a crucial water level is also defined to reduce false warnings from the velocity threshold alone. In recognition of the importance of geological evolution, the evolution process of the Gapa landslide from topping to sliding is described in this study to help to understand its behavior and predict its potential trends. Moreover, based on the improved Saito’s three-stage deformation model, the warning level is set as “attention level”, because the current deformation stage of the landslide is considered to be between the initial and constant stages. At present, the early warning system mainly consists of six surface displacement monitoring sites and one water level observation site. If the daily recorded velocity in each monitoring site exceeds 4 mm/d and, meanwhile, the water level is below 1820 m above sea level (asl), a warning of likely landslide deformation accelerations will be released by relevant monitoring sites. The thresholds are always discretely exceeded on about 3% of annual monitoring days, and they are most frequently exceeded in June (especially in mid-June). The thresholds provide an efficient and effective way for judging accelerations of this landslide and are verified by the current application. The work presented provides critical insights into the development of early warning systems for reservoir-induced large-scale landslides.

scholarly journals A GIS-based monitoring and early warning system for cover-collapse sinkholes in karst terrane in Wuhan, China

2017 ◽  
Author(s):  
Li Xueping ◽  
Xiao Shangde ◽  
Tang Huiming ◽  
Peng Jinsheng
Keyword(s):  
Plastic Zone ◽  
Water Level ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Underground Water ◽  
Water Levels ◽  
Monitoring Data ◽  
Karst Collapse ◽  
Warning Model

Abstract. To reduce disastrous losses caused by karst collapse especially in urban areas, it is important to establish an early warning system utilizing monitoring data. Three major aspects have been monitored based upon engineering geological conditions and characteristics of karst collapse processes in Wuhan, China: changes in surface soil, soil deformation, and groundwater levels. Measurements have been recorded of: (1) soil pressure, (2) ground-penetrating radar images, (3) underground water levels, (4) ground water levels, (5) rainfall, (6) cracking, (7) ground deformation, and (8) water level in monitored wells. This paper has selected geological radar cross-sectional data and underground water level monitoring data to obtain criteria for hydraulic gradient warning, geological radar warning and plastic zone warning based upon these monitoring data and wider knowledge of karst collapse in Wuhan. A comprehensive warning system has been developed on a MAPGIS platform, employing monitoring data in Microsoft Excel format and Microsoft Visual C++ development tools. Three warning levels are adopted by the system: safe, becoming dangerous, and dangerous; indicated in green, yellow and red respectively on hazard maps. The system automatically undertakes processes of data management and model calculation leading to geo-hazard warning map generation. Using monitoring data collected in the first six months of 2011 at Wuhan, the system has established a hydraulic gradient model, plastic zone warning model, geological radar warning model, and a comprehensive early warning model; and has been shown to be an effective method of providing karst collapse warning.

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