Open AccessResearch on groundwater system identification in use of hydrological signals processing technique
Author(s) -
Chenxu Luo,
Zhu Bin,
Jianhua Wu
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/344/1/012101
Subject(s) - infinite impulse response , finite impulse response , groundwater , impulse response , identification (biology) , computer science , nonlinear system , impulse (physics) , system identification , scale (ratio) , aquifer , signal processing , wiener filter , water table , algorithm , data mining , filter (signal processing) , geology , mathematics , digital filter , geotechnical engineering , digital signal processing , geography , mathematical analysis , biology , quantum mechanics , computer vision , measure (data warehouse) , botany , physics , cartography , computer hardware
Filtering techniques can be applied in processing hydrological signal identifying groundwater system. A series of groundwater table observation sequences in a coalmine was dealt with by use of recursive (IIR, Infinite Impulse Response) and non-recursive (FIR, Finite Impulse Response) filtering. The responding characteristics and dynamic patterns on the groundwater system were recognized by the correlation analysis. An identification model based on the Hammerstein-Wiener was applied to fit the data of measurement. The study shows that: (1) Three types of aquifer are divided according to their corresponding characteristics to the precipitation. Comparing the IIR and FIR filtering, the features of different scale filtering are summerized. (2) In nonlinear Hammerstein-Wiener model, the best fitting between simulation and measurement is up to 94.9%. The application of signals processing technique is a efficient approach to identify the groundwater system’s characteristics and patterns.