Online monitoring and sampling analysis of siltation in the middle route of the south-to-north water diversion project

Abstract

The middle route project (MRP) of the South to North Water Diversion Project is a significant infrastructure and alleviating water scarcity in Northern China. MRP suffered from untraditional siltation problems. Obvious siltation occurred in the regulating reservoir at the end of the channel and some locations with weak hydrodynamic conditions in the channel when the mineral siltation concentration in the flow is very low. To study the characteristics of the siltation and the siltation time period, an IoT based automatic siltation monitoring system using cloud was installed at the outlet of the inverted siphon project on Xiao River. Three years of online monitoring data since 2018 and the siltation samples at five sites for particle size analysis were collected. The monitoring data shows that siltation mainly occurs during March to October, and almost no siltation occurs in winter. The maximum siltation speed can reach 390 mm per day. The particle size of the siltation gradually increases from upstream to downstream, which mainly occurs in the range above 100 m. The organic matter contained in the siltation shows a significant increase from 40.3 to 86.4% at upstream and downstream sampling position, respectively. Monitoring results shows the main body of the siltation in the MRP is not the traditional siltation but the remnants of the algae that proliferate in large numbers. During March to October, the temperature is suitable for the proliferation of algae which attaches to the sediment particles and gradually grows downstream with the flow.

IoT Innovations in Sustainable Water and Wastewater Management and Water Quality Monitoring: A Comprehensive Review of Advancements, Implications, and Future Directions

“…The reviewed literature has also extensively covered the use of sensors and their performance in real-world settings. Researchers have utilized varying levels of experimentation, validation, and reliability testing to evaluate the accuracy and reliability of sensor readings [64], [134], [135], [138], [140]. In this regard, Wong et al [141] conducted a calibration and validation study on turbidity and ultrasonic water level sensors.…”

“…For example, Ahmed et al [139] compared 16 different ML algorithms for potability prediction and found that a onedimensional convolutional neural network (CNN) performed significantly better than other classifiers. However, while ML algorithms are gaining popularity, traditional statistical methods remain prevalent in water quality monitoring research [135], [148]. For instance, Al-Khashab et al [143] used MATLAB to analyze and display the collected data, while Zakaria et al [149] utilized statistical methods such as coefficient of variation, standard deviation, and mean for data analysis.…”

“…These methods vary based on the research objectives and system features. Commonly used methods include prediction accuracy, real-time data collection, and anomaly detection [57], [140], [142]. For instance, Chen and Han [138] reported the effectiveness of their system in providing real-time and high-frequency water quality data.…”

Length-Weight Relationships of Eight Fish Species in the World’s Largest Water Diversion Project

“…Te development of fsh community function is lagging behind, and the top-down efects of the ecosystem is weak. Terefore, it is very necessary to explore fsh diversity, biology, and population dynamics for better conservation in this project [3,4].…”

Biomanipulation of Periphytic Algae in the Middle Route of South–North Water Diversion Project Canal: An In Situ Study in the Lushan Section

“…As it travels through North China, the main canal crosses two climate zones, the subtropical monsoon humid climate zone and the temperate monsoon climate zone, with an average annual precipitation of 542-1173 mm and a multi-year air temperature of 14.6-21.2 • C. The project officially began supplying water in December 2014, providing water resources for domestic, industrial, and agricultural water consumption for four provinces or municipalities along the main canal, including Henan Province, Hebei Province, Tianjin Municipality, and Beijing Municipality. By the end of 2022, the MSNWDP had supplied over 60 billion m 3 of water to more than 20 cities, directly benefiting more than 70 million people [1,2].…”