Study on Intelligent Cleaning of Hydro-logical Data in the Main Canal of the Middle Route of the South-to-North Water Diversion Project

DOI

10.2991/978-94-6463-650-5_7How to use a DOI?

Keywords

Middle Route of the South-to-North Water Diversion Project; data cleaning; water dispatching; particle swarm optimization algorithm; exponential weighted moving average model

Abstract

Real-time hydro-logical data such as water level and flow of the main canal of the Middle Route of the South-to-North Water Diversion Project are the basis for decision-making of water conveyance scheduling. Due to the influences of external disturbance, measurement system error and other factors, the ill-conditioned hydro-logical data will cause the calculation distortion of the scheduling models, and even lead to calculation failure. Therefore, cleaning the hydro-logical data is necessary. In this paper, aiming at the logical errors in the upstream and downstream flow data space and the jump of the time series of water level data, the water balance model based on particle swarm optimization and the exponential weighted moving average model are established respectively, and the ill-conditioned water regime data is cleaned horizontally and vertically in space and time. Taking the channel section between the Chuanhuang control gate and the Zhang River control gate as a typical research interval, the flow inversion point is automatically identified. The flow data of 12 control gates and 26 water diversion points involved in the channel section are uniformly corrected to realize the rationality of upstream and downstream logic. At the same time, the Yan River control gate in the research section is selected as the representative. Under the basic stable state of operation within 48 hours, the water level data sequence in front of the gate every 2 hours is analyzed, and the jump data is automatically identified and reasonably corrected. The results show that the model established in this paper can automatically identify the ll-conditioned water data and carry out intelligent cleaning. The processed data can better meet the needs of water transfer scheduling analysis and decision-making, and has the value of popularization and application.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xiaonan Chen
AU  - Yilin Wang
AU  - Qihao Gu
AU  - Yanguo Jin
AU  - Chunqing Duan
PY  - 2025
DA  - 2025/01/31
TI  - Study on Intelligent Cleaning of Hydro-logical Data in the Main Canal of the Middle Route of the South-to-North Water Diversion Project
BT  - Proceedings of the 2024 7th International Conference on Civil Architecture, Hydropower and Engineering Management (CAHEM 2024)
PB  - Atlantis Press
SP  - 56
EP  - 74
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-650-5_7
DO  - 10.2991/978-94-6463-650-5_7
ID  - Chen2025
ER  -