{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T05:09:29Z","timestamp":1736140169321,"version":"3.32.0"},"reference-count":36,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2017,11,7]],"date-time":"2017-11-07T00:00:00Z","timestamp":1510012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Fund in China","doi-asserted-by":"crossref","award":["No. 91425302","No. 51279166","No. 51409222"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Fundamental Research Funds for the Central University","award":["No. 2452016069"]},{"name":"Doctoral Program Foundation ofNorthwest A & F University","award":["No. 2452015290"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"Monthly streamflow has elements of stochasticity, seasonality, and periodicity. Spectral analysis and time series analysis can, respectively, be employed to characterize the periodical pattern and the stochastic pattern. Both Burg entropy spectral analysis (BESA) and configurational entropy spectral analysis (CESA) combine spectral analysis and time series analysis. This study compared the predictive performances of BESA and CESA for monthly streamflow forecasting in six basins in Northwest China. Four criteria were selected to evaluate the performances of these two entropy spectral analyses: relative error (RE), root mean square error (RMSE), coefficient of determination (R2), and Nash\u2013Sutcliffe efficiency coefficient (NSE). It was found that in Northwest China, both BESA and CESA forecasted monthly streamflow well with strong correlation. The forecast accuracy of BESA is higher than CESA. For the streamflow with weak correlation, the conclusion is the opposite.<\/jats:p>","DOI":"10.3390\/e19110597","type":"journal-article","created":{"date-parts":[[2017,11,7]],"date-time":"2017-11-07T16:46:01Z","timestamp":1510073161000},"page":"597","source":"Crossref","is-referenced-by-count":4,"title":["Comparison of Two Entropy Spectral Analysis Methods for Streamflow Forecasting in Northwest China"],"prefix":"10.3390","volume":"19","author":[{"given":"Zhenghong","family":"Zhou","sequence":"first","affiliation":[{"name":"College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China"}]},{"given":"Juanli","family":"Ju","sequence":"additional","affiliation":[{"name":"College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China"}]},{"given":"Xiaoling","family":"Su","sequence":"additional","affiliation":[{"name":"College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China"}]},{"given":"Vijay","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Biological & Agricultural Engineering and Zachry Department of Civil Engineering, Texas A&M University, 2117 TAMU, College Station, TX 77843, USA"}]},{"given":"Gengxi","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,11,7]]},"reference":[{"key":"ref_1","unstructured":"Box, G.E., and Jenkins, G.M. 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