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Bridging the Terrestrial Water Storage Anomalies between the GRACE/GRACE-FO Gap Using BEAST + GMDH Algorithm.

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Title: Bridging the Terrestrial Water Storage Anomalies between the GRACE/GRACE-FO Gap Using BEAST + GMDH Algorithm.
Authors: Qian, Nijia1 (AUTHOR) nijiaqian@cumt.edu.cn, Gao, Jingxiang1 (AUTHOR) jxgao@cumt.edu.cn, Li, Zengke1 (AUTHOR) zengkeli@yeah.net, Yan, Zhaojin2 (AUTHOR) yanzhaojin@cumt.edu.cn, Feng, Yong1 (AUTHOR) tb24160017a41@cumt.edu.cn, Yan, Zhengwen3 (AUTHOR) yanzw2019@mail.sustech.edu.cn, Yang, Liu4 (AUTHOR) ylliuyang@yeah.net
Source: Remote Sensing. Oct2024, Vol. 16 Issue 19, p3693. 16p.
Subjects: GMDH algorithms, Spectrum analysis, Reference values, Hydrologic models, Statistical correlation
Abstract: Regarding the terrestrial water storage anomaly (TWSA) gap between the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on (-FO) gravity satellite missions, a BEAST (Bayesian estimator of abrupt change, seasonal change and trend)+GMDH (group method of data handling) gap-filling scheme driven by hydrological and meteorological data is proposed. Considering these driving data usually cannot fully capture the trend changes of the TWSA time series, we propose first to use the BEAST algorithm to perform piecewise linear detrending for the TWSA series and then fill the gap of the detrended series using the GMDH algorithm. The complete gap-filling TWSAs can be readily obtained after adding back the previously removed piecewise trend. By comparing the simulated gap filled by BEAST + GMDH using Multiple Linear Regression and Singular Spectrum Analysis with reference values, the results show that the BEAST + GMDH scheme is superior to the latter two in terms of the correlation coefficient, Nash-efficiency coefficient, and root-mean-square error. The real GRACE/GFO gap filled by BEAST + GMDH is consistent with those from hydrological models, Swarm TWSAs, and other literature regarding spatial distribution patterns. The correlation coefficients there between are, respectively, above 0.90, 0.80, and 0.90 in most of the global river basins. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Bridging the Terrestrial Water Storage Anomalies between the GRACE/GRACE-FO Gap Using BEAST + GMDH Algorithm.
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  Data: <searchLink fieldCode="AR" term="%22Qian%2C+Nijia%22">Qian, Nijia</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> nijiaqian@cumt.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Gao%2C+Jingxiang%22">Gao, Jingxiang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jxgao@cumt.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Zengke%22">Li, Zengke</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zengkeli@yeah.net</i><br /><searchLink fieldCode="AR" term="%22Yan%2C+Zhaojin%22">Yan, Zhaojin</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> yanzhaojin@cumt.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Feng%2C+Yong%22">Feng, Yong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> tb24160017a41@cumt.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Yan%2C+Zhengwen%22">Yan, Zhengwen</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> yanzw2019@mail.sustech.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Liu%22">Yang, Liu</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> ylliuyang@yeah.net</i>
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  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Oct2024, Vol. 16 Issue 19, p3693. 16p.
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  Data: <searchLink fieldCode="DE" term="%22GMDH+algorithms%22">GMDH algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Spectrum+analysis%22">Spectrum analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Reference+values%22">Reference values</searchLink><br /><searchLink fieldCode="DE" term="%22Hydrologic+models%22">Hydrologic models</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+correlation%22">Statistical correlation</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Regarding the terrestrial water storage anomaly (TWSA) gap between the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on (-FO) gravity satellite missions, a BEAST (Bayesian estimator of abrupt change, seasonal change and trend)+GMDH (group method of data handling) gap-filling scheme driven by hydrological and meteorological data is proposed. Considering these driving data usually cannot fully capture the trend changes of the TWSA time series, we propose first to use the BEAST algorithm to perform piecewise linear detrending for the TWSA series and then fill the gap of the detrended series using the GMDH algorithm. The complete gap-filling TWSAs can be readily obtained after adding back the previously removed piecewise trend. By comparing the simulated gap filled by BEAST + GMDH using Multiple Linear Regression and Singular Spectrum Analysis with reference values, the results show that the BEAST + GMDH scheme is superior to the latter two in terms of the correlation coefficient, Nash-efficiency coefficient, and root-mean-square error. The real GRACE/GFO gap filled by BEAST + GMDH is consistent with those from hydrological models, Swarm TWSAs, and other literature regarding spatial distribution patterns. The correlation coefficients there between are, respectively, above 0.90, 0.80, and 0.90 in most of the global river basins. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3390/rs16193693
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        Text: English
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      – SubjectFull: GMDH algorithms
        Type: general
      – SubjectFull: Spectrum analysis
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      – SubjectFull: Reference values
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      – SubjectFull: Hydrologic models
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      – SubjectFull: Statistical correlation
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      – TitleFull: Bridging the Terrestrial Water Storage Anomalies between the GRACE/GRACE-FO Gap Using BEAST + GMDH Algorithm.
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            NameFull: Qian, Nijia
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              M: 10
              Text: Oct2024
              Type: published
              Y: 2024
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