A hybrid wavelet-Lyapunov exponent model for river water quality forecast

Jiang，Jiping1,2; Tang，Sijie2; Liu，Rentao3; Sivakumar，Bellie4,5; Wu，Xiaoye6; Pang，Tianrui1

2021-07-01

10.2166/hydro.2021.023

JOURNAL OF HYDROINFORMATICS   影响因子和分区

1464-7141

1465-1734

The use of spectral theory and chaos theory on river water quality modeling is reported in a very limited way. This study proposes a wavelet-maximum Lyapunov exponent (WMLE) hybrid model for river water quality dynamics, combining spectral theory and chaos theory. The methodology involves the following major steps: (1) use of wavelet transformation to filter the noisy signal in the water quality time series; (2) reconstruction of phase space to embed the water quality time series and determine the trajectory of the underlying dynamics; and (3) identification of the presence/absence of chaos and prediction using the largest Lyapunov exponent value. Case studies on the Huaihe River in China and the Potomac River in the United States, as representatives of low-frequency and high-frequency forecast, show average relative errors on weekly dissolved oxygen (DO), chemical oxygen demand (COD), and ammonia nitrogen (NH-N) data are 2.35%, 4.53%, and 18.85%, and on 15-minute based DO data are 1.185%. It also indicates that the hybrid model performs better to some extent when compared to the purely Lyapunov exponent model, ARMA model, and ANN model. This study is a proof that the combination of spectral theory and chaos theory is promising to describe and predict fluctuation of particular water quality indicators in rivers.

Chaos theory Hybrid model Lyapunov exponent Nonlinearity Water quality Wavelet

SCI

英语

通讯

WOS:000657782500001

ENVIRONMENT/ECOLOGY

2-s2.0-85110473857

Scopus

1.State Key Laboratory of Urban Water Resource and Environment,School of Environment,Harbin Institute of Technology,Harbin,150090,China
2.Shenzhen Municipal Engineering Lab of Environmental IoT Technologies,School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
3.School of Municipal Engineering Technology,Heilongjiang College of Construction,Harbin,150025,China
4.Department of Civil Engineering,Indian Institute of Technology Bombay,Powai,Mumbai,400 076,India
5.State Key Laboratory of Hydroscience and Engineering,Tsinghua University,Beijing,100084,China
6.Faculty of Civil Engineering,RWTH Aachen University,Aachen,52062,Germany

Jiang，Jiping,Tang，Sijie,Liu，Rentao,et al. A hybrid wavelet-Lyapunov exponent model for river water quality forecast[J]. JOURNAL OF HYDROINFORMATICS,2021,23(4):864-878.

Jiang，Jiping,Tang，Sijie,Liu，Rentao,Sivakumar，Bellie,Wu，Xiaoye,&Pang，Tianrui.(2021).A hybrid wavelet-Lyapunov exponent model for river water quality forecast.JOURNAL OF HYDROINFORMATICS,23(4),864-878.

Jiang，Jiping,et al."A hybrid wavelet-Lyapunov exponent model for river water quality forecast".JOURNAL OF HYDROINFORMATICS 23.4(2021):864-878.