scholarly journals Energy-Efficient Routing Control Algorithm in Large-Scale WSN for Water Environment Monitoring with Application to Three Gorges Reservoir Area

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yuanchang Zhong ◽  
Lin Cheng ◽  
Liang Zhang ◽  
Yongduan Song ◽  
Hamid Reza Karimi
Keyword(s):  
Three Gorges Reservoir ◽  
Large Scale ◽  
Water Environment ◽  
Maximum Energy ◽  
Base Station ◽  
Three Gorges Reservoir Area ◽  
Three Gorges ◽  
Environment Monitoring ◽  
Cluster Heads ◽  
Node Energy

The typical application backgrounds of large-scale WSN (wireless sensor networks) for the water environment monitoring in the Three Gorges Reservoir are large coverage area and wide distribution. To maximally prolong lifetime of large-scale WSN, a new energy-saving routing algorithm has been proposed, using the method of maximum energy-welfare optimization clustering. Firstly, temporary clusters are formed based on two main parameters, the remaining energy of nodes and the distance between a node and the base station. Secondly, the algorithm adjusts cluster heads and optimizes the clustering according to the maximum energy-welfare of the cluster by the cluster head shifting mechanism. Finally, in order to save node energy efficiently, cluster heads transmit data to the base station in single-hop and multihop way. Theoretical analysis and simulation results show that the proposed algorithm is feasible and advanced. It can efficiently save the node energy, balance the energy dissipation of all nodes, and prolong the network lifetime.

scholarly journals The Big Data Processing Algorithm for Water Environment Monitoring of the Three Gorges Reservoir Area

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Yuanchang Zhong ◽  
Liang Zhang ◽  
Shaojing Xing ◽  
Fachuan Li ◽  
Beili Wan
Keyword(s):  
Water Quality ◽  
Three Gorges Reservoir ◽  
Clustering Algorithm ◽  
Water Environment ◽  
Three Gorges Reservoir Area ◽  
Three Gorges ◽  
Environment Monitoring ◽  
Reservoir Area ◽  
The Three Gorges Reservoir ◽  
The Three Gorges

Owing to the increase and the complexity of data caused by the uncertain environment, the water environment monitoring system in Three Gorges Reservoir Area faces much pressure in data handling. In order to identify the water quality quickly and effectively, this paper presents a new big data processing algorithm for water quality analysis. The algorithm has adopted a fast fuzzy C-means clustering algorithm to analyze water environment monitoring data. The fast clustering algorithm is based on fuzzy C-means clustering algorithm and hard C-means clustering algorithm. And the result of hard clustering is utilized to guide the initial value of fuzzy clustering. The new clustering algorithm can speed up the rate of convergence. With the analysis of fast clustering, we can identify the quality of water samples. Both the theoretical and simulated results show that the algorithm can quickly and efficiently analyze the water quality in the Three Gorges Reservoir Area, which significantly improves the efficiency of big data processing. What is more, our proposed processing algorithm provides a reliable scientific basis for water pollution control in the Three Gorges Reservoir Area.

A Design and Implementation of Water Surveillance System Based on Wireless Sensor Networks

2014 ◽  
Vol 602-605 ◽  
pp. 2305-2307
Author(s):  
Shan Hong Zhu ◽  
Pei Tang
Keyword(s):  
Water Temperature ◽  
Monitoring System ◽  
Large Scale ◽  
Ph Value ◽  
Water Environment ◽  
Base Station ◽  
Wireless Sensor ◽  
Environment Monitoring ◽  
Artificial Lake ◽  
Environmental Monitoring System

A water environmental monitoring system based on a wireless sensor network is proposed. It consists of three parts: data monitoring nodes, data base station and remote monitoring center. This system is suitable for the complex and large-scale water environment monitoring, such as for reservoirs, lakes, rivers, swamps, and shallow or deep ground waters. This paper is devoted to the explanation and illustration for our new water environment monitoring system design. The system had successfully accomplished the online auto-monitoring of the water temperature and pH value environment of an artificial lake. The monitoring system thus promises broad applicability prospects. The system's measurement capacity ranges from 0 to 90 °C for water temperature, with an accuracy of ±0.5 °C; from 0 to 16 on pH value, with an accuracy of ±0.05 pH units. Sensors applicable to different water quality scenarios should be installed at the nodes to meet the monitoring demands for a variety of water environments and to obtain different parameters.

scholarly journals Novel Model for Manoeuvrability of Ships Advancing in Landslide-Generated Tsunamis

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Peiyin Yuan ◽  
Pingyi Wang ◽  
Yu Zhao
Keyword(s):  
Water Level ◽  
Three Gorges Reservoir ◽  
Large Scale ◽  
Three Gorges Reservoir Area ◽  
Physical Model Test ◽  
Three Gorges ◽  
Reservoir Area ◽  
The Three Gorges Reservoir ◽  
The Three Gorges ◽  
Scale Ratio

The rock and soil on the shore of the bank are unsteady and slide in a poor environment, affecting the water body in the river channel and forming landslide-generated tsunamis. This directly impacts the navigation of vessels in the river. In this study, the river course and sailing ships in the Wanzhou section of the Three Gorges Reservoir area were taken as the research objects. Through a physical model test with a large scale ratio, the variation of the water level at the monitoring points in the channel was determined, and the variation law of the water level in the whole channel was derived and converted into a prototype through the scale ratio. A model of the ship’s manoeuvring motion was established, and the ship’s manoeuvring motion characteristics in still water were verified. The correlations between the maximum roll angle and the navigation position, sailing speed, and rudder angle were investigated in detail. A safety risk response theory of navigation in the area of landslide-generated tsunamis was proposed, and a scientific basis was provided for the safe navigation of ships in the Three Gorges Reservoir area.

scholarly journals Evaluation of ESV Change under Urban Expansion Based on Ecological Sensitivity: A Case Study of Three Gorges Reservoir Area in China

2021 ◽  
Vol 13 (15) ◽  
pp. 8490
Author(s):  
Hongjie Peng ◽  
Lei Hua ◽  
Xuesong Zhang ◽  
Xuying Yuan ◽  
Jianhao Li
Keyword(s):  
Three Gorges Reservoir ◽  
Urban Expansion ◽  
Urban Land ◽  
Three Gorges Reservoir Area ◽  
Three Gorges ◽  
Ecological Sensitivity ◽  
Reservoir Area ◽  
Green Development ◽  
Source Data

In recent years, ecosystem service values (ESV) have attracted much attention. However, studies that use ecological sensitivity methods as a basis for predicting future urban expansion and thus analyzing spatial-temporal change of ESV are scarce in the region. In this study, we used the CA-Markov model to predict the 2030 urban expansion under ecological sensitivity in the Three Gorges reservoir area based on multi-source data, estimations of ESV from 2000 to 2018 and predictions of ESV losses from 2018 to 2030. Research results: (i) In the concept of green development, the ecological sensitive zone has been identified in Three Gorges reservoir area; it accounts for about 35.86% of the study area. (ii) It is predicted that the 2030 urban land will reach 211,412.51 ha by overlaying the ecological sensitive zone. (iii) The total ESV of Three Gorges Reservoir area showed an increasing trend from 2000 to 2018 with growth values of about USD 3644.26 million, but the ESVs of 16 districts were decreasing, with Dadukou and Jiangbei having the highest reductions. (iv) New urban land increases by 80,026.02 ha from 2018 to 2030. The overall ESV losses are about USD 268.75 million. Jiulongpo, Banan and Shapingba had the highest ESV losses.

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