scholarly journals Experimental Study of Dam-Break-Like Tsunami Bore Impact Mechanism on a Container Model

2020 ◽  
Vol 27 (1) ◽  
pp. 53-59
Author(s):  
Cheng Chen ◽  
Jun Chen ◽  
Peng Lin ◽  
Chiwei Chen ◽  
Haozhe Chen
Keyword(s):  
Water Level ◽  
High Speed ◽  
Tsunami Wave ◽  
Dam Break ◽  
Water Levels ◽  
Level Gauge ◽  
Impact Mechanism ◽  
Tsunami Waves ◽  
Movement Distance ◽  
Container Model

AbstractTsunami disasters have frequently occurred in recent years. More and more researchers are focusing on this topic. To investi-gate the tsunami bore impact mechanism on a container model, a multi-functional slope-changing tsunami flume is built in this study. To simulate a tsunami bore, a dam-break wave was generated by a free-falling gate in a reservoir. A needle water level gauge and a high-speed camera were used to measure the tsunami wave heights and velocities for different storage water levels in the test flume, and the corresponding Froude numbers of tsunami waves were also calculated. The factors af-fecting the movement distance of the tsunami wave impacting the container model are explored in this experiment, and the results show that the movement distance is positively correlated with the storage water level, and negatively correlated with the container density and the coast slope.

scholarly journals Can GNSS-R Detect Abrupt Water Level Changes?

2020 ◽  
Vol 12 (21) ◽  
pp. 3614
Author(s):  
Sajad Tabibi ◽  
Olivier Francis
Keyword(s):  
Water Level ◽  
Vertical Velocity ◽  
Energy Demand ◽  
Water Surface ◽  
Spatial Scales ◽  
Satellite System ◽  
Water Levels ◽  
Level Gauge ◽  
Surface Reflection ◽  
Microwave Radar

Global navigation satellite system reflectometry (GNSS-R) uses signals of opportunity in a bi-static configuration of L-band microwave radar to retrieve environmental variables such as water level. The line-of-sight signal and its coherent surface reflection signal are not separate observables in geodetic GNSS-R. The temporally constructive and destructive oscillations in the recorded signal-to-noise ratio (SNR) observations can be used to retrieve water-surface levels at intermediate spatial scales that are proportional to the height of the GNSS antenna above the water surface. In this contribution, SNR observations are used to retrieve water levels at the Vianden Pumped Storage Plant (VPSP) in Luxembourg, where the water-surface level abruptly changes up to 17 m every 4-8 h to generate a peak current when the energy demand increases. The GNSS-R water level retrievals are corrected for the vertical velocity and acceleration of the water surface. The vertical velocity and acceleration corrections are important corrections that mitigate systematic errors in the estimated water level, especially for VPSP with such large water-surface changes. The root mean square error (RMSE) between the 10-min multi-GNSS water level time series and water level gauge records is 7.0 cm for a one-year period, with a 0.999 correlation coefficient. Our results demonstrate that GNSS-R can be used as a new complementary approach to study hurricanes or storm surges that cause abnormal rises of water levels.

scholarly journals Early warning flood detector adopting camera by Sobel Canny edge detection algorithm method

2021 ◽  
Vol 22 (3) ◽  
pp. 1796
Author(s):  
Satryo B. Utomo ◽  
Januar Fery Irawan ◽  
Rizqi Renafasih Alinra
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Detection System ◽  
Water Levels ◽  
Level Gauge ◽  
Canny Edge Detection ◽  
Canny Edge

Early warning of floods is an essential part of disaster management. Various automatic detectors have been developed in flood mitigation, including cameras. But reliability and accuracy have not been improved. Besides, the use of monitoring devices has been employed to monitor water levels in various water building facilities. The early warning flood detector was carried out with a sensor camera using an orange ball that floats near the water level gauge in a bounding box. This approach uses the integration of computer vision and image processing, namely digital image processing techniques, with Sobel Canny edge detection (SCED) algorithms to detect quickly and accurately water levels in real-time. After the water level is measured, a flood detection process is carried out based on the specified water level. According to the results of experiments in the laboratory, it has been shown that the proposed approach can detect objects accurately and fast in real-time. Besides, from the water level detection experiment, good results were obtained. Therefore, the object detection system and water level can be used as an efficient and accurate early detection system for flood disasters.

scholarly journals Study on Water Level Prediction Using Observational Data from a Multi-Parameter Phased Array Weather Radar

2021 ◽  
Vol 16 (3) ◽  
pp. 410-414
Author(s):  
Kazuhiro Yoshimi ◽  
Masakazu Wada ◽  
Yukio Hiraoka ◽  
◽  
Keyword(s):  
Water Level ◽  
Observational Data ◽  
Urban Areas ◽  
High Speed ◽  
Phased Array ◽  
Three Dimensional ◽  
Weather Radar ◽  
Water Levels ◽  
Hydrological Processes ◽  
Basic Study

A dual-polarization, phased array weather radar, also known as the multi-parameter phased array weather radar (MP-PAWR), was developed by the Japanese Cross-ministerial Strategic Innovation Promotion (SIP) Program. Since this weather radar has been made into an active phased array, three-dimensional observation of weather phenomena can be realized at high speed by means of electrical scanning in the elevation direction and mechanical scanning in the azimuth direction. This is expected to shed light on hydrological processes in river basins, such as those of urban rivers, and improve prediction accuracy. In this study, river water levels in urban areas were estimated from vertically integrated liquid (VIL) Nowcast water content results, a meteorological forecasting method based on the three-dimensional observation MP-PAWR data, using a synthesized rational formula. A runoff analysis for urban basins was carried out using the rainfall forecast results based on MP-PAWR observational data. Since it is known that this formula can be used to deliver a rapid response time for runoff phenomena in the basin, it is possible to fully exploit the features of the MP-PAWR. This study shows how MP-PAWR is used in a series of hydrological processes. In this paper, we report the results of a basic study on water level predictions based on MP-PAWR observational data and also present future prospects for the use of this technology.

Experimental Study on Dam-Break Hydrodynamic Characteristics Under Different Conditions

2017 ◽  
Vol 12 (1) ◽  
pp. 198-207 ◽  
Author(s):  
Hui Liu ◽  
◽  
Haijiang Liu ◽  
Keyword(s):  
Flow Velocity ◽  
Water Level ◽  
High Speed ◽  
Flow Characteristics ◽  
Dam Break ◽  
Hydrodynamic Characteristics ◽  
High Temporal Resolution ◽  
Initial Water ◽  
Water Head ◽  
Reservoir Length

In this study, a series of dam-break experiments was carried out to investigate the influence of the initial downstream water depth, water head settings, and upstream reservoir length on the dam-break wave movement. The instantaneous water level and flow velocity were measured at two specified downstream locations. Considering the requirements for precise data measurement with high temporal resolution, the synchronization of different instruments was realized based on high-speed camera recording. Even with the same initial water head setting, the water level and flow velocity variations of the dam-break wave propagating downstream on the wet bed show noteworthy differences in flow characteristics compared to the initial dry bed, caused by the interactions between the upstream and downstream water. Hydrodynamic formulae proposed by Lauber and Hager (1998) [1] are not applicable for the wet-bed condition, although their solution of wave profiles for the initial dry-bed condition performs well at the location farther from the gate. The non-dimensional average front velocity of the wet-bed condition, which mainly depends on the initial water head setting, is smaller than that of the dry-bed case. In addition, the maximum water level and flow velocity at the downstream location are mainly controlled by the initial water head setting, while the duration of the large values is influenced by the reservoir length.

scholarly journals APPLICATION OF A SIMPLE HYDRODYNAMIC MODEL TO ESTUARY ENTRANCE

2011 ◽  
Vol 1 (32) ◽  
pp. 42 ◽  
Author(s):  
Errol J. McLean ◽  
Jon B. Hinwood
Keyword(s):  
Water Level ◽  
Hydrodynamic Model ◽  
River Flow ◽  
River Estuary ◽  
Water Levels ◽  
Tidal Range ◽  
Level Gauge ◽  
Tidal Basin ◽  
Assessment Procedure ◽  
Eastern Australia

Tidal inlets which link a tidal basin to the sea via a constricted entrance are common on the south-east Australian coast. Closure, or even significant constriction, raises water levels but restricts tidal range within the basin, while open entrances provide regular and significant tidal exchange with the ocean. A rapid assessment procedure with minimal data requirements has been shown to be informative for monitoring and a useful component of any Decision Support System set up as part of a management structure. Such a system is presented in this paper. It is based on one permanent water level gauge inside the inlet plus the use of a simple, first-order hydrodynamic model to relate the tide range, mean water level and river flow to the inlet cross sectional area. The method is tested against data from the Snowy River Estuary in south-eastern Australia but would be suitable over a range of estuaries. In addition, the framework presented can also provide a mechanism to explore conditions over the range of expected data, thus allowing better selection of model schematization and runs in estuarine systems where the use of 2 or 3D modeling can be justified.

scholarly journals Development of Water Level Prediction Models Using Machine Learning in Wetlands: A Case Study of Upo Wetland in South Korea

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 93 ◽  
Author(s):  
Changhyun Choi ◽  
Jungwook Kim ◽  
Heechan Han ◽  
Daegun Han ◽  
Hung Soo Kim
Keyword(s):  
Machine Learning ◽  
South Korea ◽  
Water Level ◽  
Prediction Models ◽  
Wetland Management ◽  
Water Levels ◽  
Level Gauge ◽  
Support Vector ◽  
Gauge Data ◽  
Water Level Prediction

Wetlands play a vital role in hydrologic and ecologic communities. Since there are few studies conducted for wetland water level prediction due to the unavailability of data, this study developed a water level prediction model using various machine learning models such as artificial neural network (ANN), decision tree (DT), random forest (RF), and support vector machine (SVM). The Upo wetland, which is the largest inland wetland in South Korea, was selected as the study area. The daily water level gauge data from 2009 to 2015 were used as dependent variables, while the meteorological data and upstream water level gauge data were used as independent variables. Predictive performance evaluation using RF as the final model revealed 0.96 value for correlation coefficient (CC), 0.92 for Nash–Sutcliffe efficiency (NSE), 0.09 for root mean square error (RMSE), and 0.19 for persistence index (PI). The results indicate that the water level of the Upo wetland was well predicted, showing superior results compared to that of the ANN, which was used in a previous study. The results intend to provide basic data for development of a wetland management method, using water levels of previously ungauged areas.

On the Generation of Isolated Green Water Events Using Wet Dam-Break

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Jassiel V. Hernández-Fontes ◽  
Marcelo A. Vitola ◽  
Monica C. Silva ◽  
Paulo de Tarso T. Esperança ◽  
Sergio H. Sphaier
Keyword(s):  
High Speed ◽  
Offshore Structures ◽  
Dam Break ◽  
Water Levels ◽  
Green Water ◽  
Incoming Wave ◽  
Aspect Ratios ◽  
Water Problem ◽  
Different Types ◽  
Wave Trains

Green water occurs when an incoming wave exceeds the freeboard and propagates onto the deck of naval/offshore structures, such as floating production storage and offloading units and platforms. This water can affect the integrity of facilities and equipment that are installed on the deck, compromise the safety of the crew, and affect the dynamic stability of the structure. Traditionally, wave trains have been used to study the green water problem, which is a good approach to analyzing consecutive green water events. However, to carry out systematic studies that allow local details to be identified for different types of green water, an alternative method is to study isolated events generated by a single incoming wave. The purpose of this paper was to experimentally investigate the generation of different types of isolated green water events using the wet dam-break (DB) approach as an alternative to generating the incoming wave. Tests were carried out in a rectangular tank with a fixed internal structure. Different freeboard conditions were tested for two aspect ratios of the wet DB (h0/h1=0.40 and 0.6). Conventional wave probes were used to measure the water levels in the tank, and a high-speed camera was set to capture details of the generated green water events. The results demonstrated the ability of this approach to represent different types of green water, similar to those obtained with unbroken regular waves in barge-shaped fixed structures, including DB, plunging-dam-break (PDB) and hammer-fist (HF).

AUTOMATIC WATER LEVEL MONITORING WITH IOT AND LPWAN

2019 ◽  
pp. 95-103
Author(s):  
Krum Videnov ◽  
Vanya Stoykova
Keyword(s):  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Water Sources ◽  
Water Levels ◽  
Water Level Fluctuations ◽  
Level Monitoring ◽  
Water Level Monitoring

Monitoring water levels of lakes, streams, rivers and other water basins is of essential importance and is a popular measurement for a number of different industries and organisations. Remote water level monitoring helps to provide an early warning feature by sending advance alerts when the water level is increased (reaches a certain threshold). The purpose of this report is to present an affordable solution for measuring water levels in water sources using IoT and LPWAN. The assembled system enables recording of water level fluctuations in real time and storing the collected data on a remote database through LoRaWAN for further processing and analysis.

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