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Entropy Spectral Analyses for Groundwater Forecasting
Cui, Huijaun1; Singh, Vijay P.2
2017-07-01
Source PublicationJOURNAL OF HYDROLOGIC ENGINEERING
ISSN1084-0699
Volume22Issue:7Pages:8
Corresponding AuthorCui, Huijaun(cuihj@igsnrr.ac.cn)
AbstractForecasting of monthly and annual groundwater levels is important for water resources management, irrigation, and assessment of climate change. This study employs entropy spectral analysis for forecasting monthly groundwater levels. For spectral analysis, the domain of consideration for defining entropy is the frequency domain, in which three types of entropies are known: Burg entropy, configurational entropy, and relative entropy. These entropies lead to three types of spectral analysis: (1)Burg entropy spectral analysis (BESA), (2)configurational entropy spectral analysis (CESA), and (3)relative entropy spectral analysis (RESA). BESA, CESA, and RESA are employed to analyze spectra and forecast monthly groundwater levels, and then they are compared to determine which spectral analysis method better forecasts the monthly groundwater level. Monthly and annual groundwater data were obtained from South Carolina to verify the three methods. Both monthly and annual groundwater level data showed significant decreasing trends at almost all stations. It was found that relative entropy yielded the highest resolution in determining the spectral density, while for simulating groundwater levels, all three methods fitted the observed values well. This was indicated by the average value of Nash-Sutcliffe efficiency (NSE) for BESA, CESA, and RESA being 0.69, 0.70, and 0.70, respectively.
KeywordEntropy theory Spectral analysis Burg entropy Relative entropy Configurational entropy Groundwater level
DOI10.1061/(ASCE)HE.1943-5584.0001512
WOS KeywordMINIMUM RELATIVE ENTROPY ; STATISTICAL-MECHANICS ; INFORMATION-THEORY ; UNIVARIATE MODEL ; GAZA-STRIP ; HYDROLOGY ; INVERSION ; REDESIGN
Indexed BySCI
Language英语
Funding ProjectKey Research Program of the Chinese Academy of Sciences[ZDRW-ZS-2016-6-4]
Funding OrganizationKey Research Program of the Chinese Academy of Sciences
WOS Research AreaEngineering ; Environmental Sciences & Ecology ; Water Resources
WOS SubjectEngineering, Civil ; Environmental Sciences ; Water Resources
WOS IDWOS:000399912900008
PublisherASCE-AMER SOC CIVIL ENGINEERS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/62590
Collection中国科学院地理科学与资源研究所
Corresponding AuthorCui, Huijaun
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, 11A Datun Rd, Beijing 100101, Peoples R China
2.Texas A&M Univ, Dept Biol & Agr Engn, Zachry Dept Civil Engn, Water Engn, 321 Scoates Hall, College Stn, TX 77843 USA
Recommended Citation
GB/T 7714
Cui, Huijaun,Singh, Vijay P.. Entropy Spectral Analyses for Groundwater Forecasting[J]. JOURNAL OF HYDROLOGIC ENGINEERING,2017,22(7):8.
APA Cui, Huijaun,&Singh, Vijay P..(2017).Entropy Spectral Analyses for Groundwater Forecasting.JOURNAL OF HYDROLOGIC ENGINEERING,22(7),8.
MLA Cui, Huijaun,et al."Entropy Spectral Analyses for Groundwater Forecasting".JOURNAL OF HYDROLOGIC ENGINEERING 22.7(2017):8.
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