water level monitoring
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2022 ◽  
Vol 14 (1) ◽  
pp. 212
Author(s):  
Shufen Zhao ◽  
Runqiang Zeng ◽  
Hongxue Zhang ◽  
Xingmin Meng ◽  
Zonglin Zhang ◽  
...  

The construction of Longyangxia Reservoir has altered the hydrogeological conditions of its banks. Infiltration and erosion caused by the periodic rise and fall of the water level leads to collapse of the reservoir banks and local deformation of the landslide. Due to heterogeneous topographic characteristics across the region, water level also varies between different location. Previous research on the influence of fluctuations in reservoir water level on landslide deformation has focused on single-point monitoring of specific slopes, and single-point water level monitoring data have often been used instead of water level data for the entire reservoir region. In addition, integrated remote sensing methods have seldom been used for regional analysis. In this study, the freely-available Landsat8 OLI and Sentinel-2 data were used to extract the water level of Longyangxia Reservoir using the NDWI method, and Sentinel-1A data were used to obtain landslide deformation time series using SBAS-InSAR technology. Taking the Chana, Chaxi, and Mangla River Estuary landslides (each having different reservoir water level depths) as typical examples, the influence of changes in reservoir water level on the deformation of three wading landslides was analyzed. Our main conclusions are as follows: First, the change in water level is the primary external factor controlling the deformation velocity and trend of landslides in the Longyangxia Reservoir, with falling water levels having the greatest influence. Second, the displacement of the Longyangxia Reservoir landslides lags water level changes by 0 to 62 days. Finally, this study provides a new method applicable other areas without water level monitoring data.


2021 ◽  
Author(s):  
Matthew Moreno ◽  
Amador Salazar ◽  
Rafael Gijon ◽  
Sangita Prajapati ◽  
Farrokh Attarzadeh ◽  
...  

2021 ◽  
Vol 183 (36) ◽  
pp. 33-39
Author(s):  
Yoice R. Putung ◽  
Josephin Sundah ◽  
Sukandar Sawidin ◽  
Ventje F. Aror

2021 ◽  
Author(s):  
Cik Ku Haroswati Che Ku Yahaya ◽  
Muhammad Hilal Hidayatullah Rosly ◽  
Meor Mohd Azreen Meor Hamzah ◽  
Murizah Kassim

2021 ◽  
Vol 1 ◽  
pp. 27-31
Author(s):  
Maulana Putra ◽  
Dyah P. Djenal ◽  
Fajar Giri Suseno ◽  
Tiven Sandro

Lake Toba is a tecto-volcanic lake located in North Sumatra Province, Indonesia. Currently, Lake Toba is 1 (one) of 5 (five) Super Priority Tourism Destinations (DPSP) prepared by the Government of Indonesia. This study made a design for a water level monitoring system in the Lake Toba region. This system design is one form of mitigation, namely an effort to reduce disaster risk. The design of the Water Level Monitoring System in the Lake Toba Region used several components, namely Data Loggers, Sensors, and supporting equipment such as power supplies and communication systems. The Water Level Monitoring System in the Lake Toba Region was built in 6 (six) locations, namely Ajibata Port, Ambarita Port, Simanindo Port, Muara Port, Sippingan Port, and Balige Port. The observation of the monitoring system in the Lake Toba region showed that the water level and data quality vary. The sensor in this system can identify changes in water level in the Lake Toba region with a small amplitude of 10-15 centimeters.


Author(s):  
Javed Dhillon ◽  
Sourov Das ◽  
Nerob Kumar Mohonto ◽  
Mehedi Hasan ◽  
Sajib Ahmed ◽  
...  

2021 ◽  
Vol 38 (4) ◽  
pp. 979-984
Author(s):  
Qiuyu Bo ◽  
Wuqun Cheng

This paper designs an intelligent groundwater level monitoring system based on image recognition and Internet of things (IoT). Image recognition technology was employed to process the water level image, and determine the water level line. The IoT was adopted to transmit the collected multimedia data accurately to the monitoring end, thereby realizing the automatic remote monitoring of real-time water level. After analyzing the image recognition technology and the key algorithm of water level recognition, the authors designed the whole process of groundwater level monitoring with two modules: water level monitoring base station, and remote monitoring management center. The water level monitoring base station is embedded with a data acquisition module to periodically collect data, including water level, videos, and images. The collected data were sent to the remote monitoring management center through the cellular network. Then, flood or low water warning could be determined according to the historical data. Finally, the proposed groundwater level monitoring system was tested. The results show that the system not only solves the problem of measurement accuracy, but also improves the work efficiency.


Measurement ◽  
2021 ◽  
pp. 110047
Author(s):  
Ganggang Bai ◽  
Jingming Hou ◽  
Yangwei Zhang ◽  
Bingyao Li ◽  
Hao Han ◽  
...  

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