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Application of Big Data Analysis in Flood Control of Small Reservoirs -A Case study of Liaoning Province, China
Author(s) -
Xi Chen,
Tong Zhang,
Zeyu Zheng,
Tianran Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1693/1/012019
Subject(s) - flood control , flood myth , china , environmental science , water resource management , big data , control (management) , period (music) , water level , hydrology (agriculture) , computer science , geography , data mining , geology , cartography , geotechnical engineering , physics , archaeology , artificial intelligence , acoustics
Small reservoirs play an important role in the safety of flood control and economic development. Their operation and management are characterized by a large number of objects and a large amount of information, which requires effective data analysis means support. Based on this, big data analysis technology has been gradually applied and popularized in the operation and management of small reservoirs. In this paper, we first set up a small reservoir flood reporting system based on the data collection and analysis of various aspects such as reservoir capacity, characteristic water level, real-time data of water and rain situation, meteorological data, and presented the results in the paper. Secondly, we analyzed the under-reporting situation during the flood control period of the reservoir, and explored the under-reporting factors and the time when the under-reporting occurred. Finally, we conduct a time series analysis on the situation of water level exceeding the limit of 50 reservoirs during the flood control period, so that we can find the key reservoirs and important time points of flood control more intuitively and provide reference for the smooth development of the management of small reservoirs.

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