Powiadomienia systemowe
- Sesja wygasła!
Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
This study discusses how to model the noise in a Gravity Recovery and Climate Experiment (GRACE)-Mascon derived Equivalent Water Thicknesses (EWT) time-series. GRACE has provided unique information for monitoring variations in EWT of continents in regional or basin scale since 2002. To analyze a GRACE EWT time-series, a standard harmonic regression model is used, but usually assuming white noise-only stochastic model. However, like almost all kinds of geodetic time-series, it has been shown that the GRACE EWT time-series contains temporal correlations causing colored noise in the data. As well known in geodetic modelling studies, neglecting these correlations leads to underestimating the uncertainties, and so misinterpreting the significancy of the parameter estimates such as trend rate, amplitudes of signals etc. In this study, autoregressive noise modeling, which has some advantageous compared to the approaches and methods frequently applied in geodetic studies, is considered for GRACE EWT time series. For this aim, three important basins, namely theYangtze, Murray–Darling and Amazon basins have been examined. Among some applied autoregressive models, the ARMA(1,1) model is obtained as the best-fitting noise model for analyzing the EWT changes in each basin. The obtained results are discussed in terms of forecasting, significancy and consistency with GRACE-FO mission.
Wydawca
Czasopismo
Rocznik
Tom
Strony
art. no. e25, 2022
Opis fizyczny
Bibliogr. 54 poz., rys., tab., wykr.
Twórcy
autor
- Yildiz Technical University, Istanbul, Turkey
autor
- Yildiz Technical University, Istanbul, Turkey
Bibliografia
- 1. Ahmed, M., Sultan, M., Elbayoumi, T. et al. (2019). Forecasting grace data over the African watersheds using artificial neural networks. Remote Sens., 11(15), 1769. DOI: 10.3390/rs11151769.
- 2. Baur, O. (2012). On the computation of mass-change trends from GRACE gravity field time-series. J. Geodyn., 61, 120–128. DOI: 10.1016/j.jog.2012.03.007.
- 3. Becker, M., Meyssignac, B., Xavier, L. et al. (2011). Past terrestrial water storage (1980–2008) in the Amazon Basin reconstructed from GRACE and in situ river gauging data. Hydrol. Earth Syst. Sci., 15(2), 533–546. DOI: 10.5194/hess-15-533-2011.
- 4. Birylo, M., Rzepecka, Z., Kuczynska-Siehien, J. et al. (2018). Analysis of water budget prediction accuracy using ARIMA models. Water Sci. Technol. Water Supply, 18(3), 819–830. DOI: 10.2166/ws.2017.156.
- 5. Boergens, E., Kvas, A., Eicker, A. et al. (2022). Uncertainties of GRACE-Based Terrestrial Water Storage Anomalies for Arbitrary Averaging Regions. J. Geophys. Res. Solid Earth, e2021JB022081. DOI: 10.1029/2021JB022081.
- 6. Box, G.E.P., Jenkins, G.M., Reinsel, G.C. et al. (2015). Time-series analysis: Forecasting and control. (5th ed.). New Jersey: John Wiley & Sons.
- 7. Brockwell, P.J., and Davis, R.A. (2016). Introduction to time-series and forecasting (3rd ed.). New York: Springer.
- 8. Brown, N.J., and Tregoning, P. (2010). Quantifying GRACE data contamination effects on hydrological analysis in the Murray–Darling Basin, southeast Australia. Aust. J. Earth Sci., 57(3), 329–335. DOI: 10.1080/08120091003619241.
- 9. Cazenave, A., and Chen, J. (2010). Time-variable gravity from space and present-day mass redistribution in the earth system. Earth Planet. Sci. Lett., 298, 263–274. DOI: 10.1016/j.epsl.2010.07.035.
- 10. Chao, N., and Wang, Z. (2017). Characterized flood potential in the Yangtze River basin from GRACE gravity observation, hydrological model and in-situ hydrological station. J. Hydrol. Eng., 22(9), 05017016. DOI: 10.1061/(ASCE)HE.1943-5584.0001547.
- 11. Chao, N., Jin, T., Cai, Z. et al. (2021). Estimation of component contributions to total terrestrial water storage change in the Yangtze River basin. J. Hydrol., 595, 125661. DOI: 10.1016/j.jhydrol.2020.125661.
- 12. Chatfield, C. (2003). The analysis of time series: An introduction (6th ed.). London: Chapman and Hall CRC.
- 13. Chen, J.L., Wilson, C.R., and Tapley, B.D. (2010). The 2009 exceptional Amazon flood and interannual terrestrial water storage change observed by GRACE. Water Resour. Res., 46(12). DOI: 10.1029/2010WR009383.
- 14. Chen, J., Tapley, B., Rodell, M. et al. (2020). Basin scale river runoff estimation from GRACE gravity satellites, climate models, and in situ observations: A case study in the Amazon basin. Water Resour.Res., 56(10), e2020WR028032. DOI: 10.1029/2020WR028032.
- 15. Chen, J., Cazenave, A., Dahle, C. et al. (2022). Applications and Challenges of GRACE and GRACE Follow-On Satellite Gravimetry. Surv. Geophys., 1–41. DOI: 10.1007/s10712-021-09685-x.
- 16. Crowley, J.W., Mitrovica, J.X., Bailey, R.C. et al. (2008). Annual variations in water storage and precipitation in the Amazon Basin. J. Geod., 82(1), 9–13. DOI: 10.1007/s00190-007-0153-1.
- 17. Davis, J.L., Wernicke, B.P., and Tamisiea, M.E. (2012). On seasonal signals in geodetic time series. J. Geophys. Res. Solid Earth, 117(B1). DOI: 10.1029/2011JB008690.
- 18. Dobslaw, H., Bergmann-Wolf, I., Dill, R. et al. (2017). Product Description Document for AOD1B Release 06, GRACE 327-750, GFZ German Research Centre for Geosciences, Department 1: Geodesy and Remote Sensing. Retrieved from https://podaac-tools.jpl.nasa.gov/drive/files/allData/gracefo/docs/AOD1B_PDD_RL06_v6.1.pdf.
- 19. Famiglietti, J.S., and Rodell, M. (2013). Water in the balance. Science, 340(6138), 1300–1301. DOI: 10.1126/science.1236460.
- 20. Fasullo, J.T., Boening, C., Landerer, F.W. et al. (2013). Australia’s unique influence on global sea level in 2010-2011. Geophys. Res. Lett., 40(16), 4368–4373. DOI: 10.1002/grl.50834.
- 21. Ferreira, V.G., Gong, Z., He, X. et al. (2013). Estimating total discharge in the Yangtze River Basin using satellite-based observations. Remote Sens., 5(7), 3415–3430. DOI: 10.3390/rs5073415.
- 22. Forsberg. R., Sørensen, L., and Simonsen, S. (2017). Greenland and Antarctica ice sheet mass changes and effects on global sea level. Surv. Geophys., 38(1), 89–104. DOI: 10.1007/s10712-016-9398-7.
- 23. Frappart, F., Papa, F., da Silva, J.S. et al. (2012). Surface freshwater storage and dynamics in the Amazon basin during the 2005 exceptional drought. Environ. Res. Lett., 7(4), 044010. DOI: 10.1088/1748-9326/7/4/044010.
- 24. Frappart, F., and Ramillien, G. (2018). Monitoring groundwater storage changes using the Gravity Re-covery and Climate Experiment (GRACE) satellite mission: A review. Remote Sens., 10(6), 829. DOI: 10.3390/rs10060829.
- 25. Frappart, F., Papa, F., Güntner, A. et al. (2019). The spatio-temporal variability of groundwater storage in the Amazon River Basin. Adv. Water Resour., 124, 41–52. DOI: 10.1016/j.advwatres.2018.12.005.
- 26. Gao, Z., Long, D., Tang, G. et al. (2017). Assessing the potential of satellite-based precipitation estimates for flood frequency analysis in ungauged or poorly gauged tributaries of China’s Yangtze River basin. J. Hydrol., 550, 478–496. DOI: 10.1016/j.jhydrol.2017.05.025.
- 27. Guo, X., Zhao, Q., Ditmar, P. et al. (2018). Improvements in the monthly gravity field solutions through modeling the colored noise in the GRACE data. J. Geophys. Res. Solid Earth, 123(8). DOI: 10.1029/2018JB015601.
- 28. Heimhuber, V., Tulbure, M.G., Broich, M. et al. (2019). The role of GRACE total water storage anomalies, streamflow and rainfall in stream salinity trends across Australia’s Murray–Darling Basin during and post the Millennium Drought. Int. J. Appl. Earth Obs. Geoinf., 83, 101927. DOI: 10.1016/j.jag.2019.101927.
- 29. Huang, Y., Salama, M.S., Krol, M.S. et al. (2015). Estimation of human induced changes in terrestrial water storage through integration of GRACE satellite detection and hydrological modeling: a case study of the Yangtze River basin. Water Resour Res. 51, 8494–8516. DOI: 10.1002/2015WR016923.
- 30. Huang, P., Song, J., Cheng, D. et al. (2021). Understanding the intra-annual variability of streamflow by incorporating terrestrial water storage from GRACE into the Budyko framework in the Qinba Mountains. J. Hydrol., 603, 126988. DOI: 10.1016/j.jhydrol.2021.126988.
- 31. Hyndman, R.J., and Athanasopoulos, G. (2018). Forecasting: principles and practice (2nd ed.). OTexts.
- 32. King, M.A., and Watson, C.S. (2020). Antarctic surface mass balance: Natural variability, noise, and detecting new trends. Geophys. Res. Lett., 47(12), e2020GL087493. DOI: 10.1029/2020GL08749.
- 33. Loomis, B.D., Luthcke, S.B., and Sabaka T.J. (2019). Regularization and error characterization of GRACE mascons. J. Geod., 93(9), 1381–1398. DOI: 10.1007/s00190-019-01252-y.
- 34. Loomis, B.D., Rachlin, K.E., Wiese, D.N. et al. (2020). Replacing GRACE/GRACE-FO with satellite laser ranging: Impacts on Antarctic Ice Sheet mass change. Geophys. Res. Lett., 47(3). DOI: e2019GL085488.
- 35. Luthcke, S.B., Sabaka, T.J., Loomis, B.D. et al. (2013). Antarctica, Greenland and Gulf of Alaska landice evolution from an iterated GRACE global mascon solution. J. Glaciol., 59(216), 613–631. DOI: 10.3189/2013JoG12J147.
- 36. Mandelbrot, B., and Van Ness, J. (1968). Fractional brownian motions, fractional noises and applications. SIAM Rev., 10, 422–437.
- 37. Pellet, V., Aires, F., and Yamazaki, D. (2021). Coherent satellite monitoring of the water cycle over the Amazon. Part 2: Total water storage change and river discharge estimation. Water Resour. Res., 57, e2020WR028648. DOI: 10.1029/2020WR028648.
- 38. Peltier, W.R., Argus, D.F., and Drummond, R. (2015). Space geodesy constrains ice-age terminal deglaciation: The global ICE-6G C (VM5a) model. J. Geophys. Res. Solid Earth, 120, 450–487. DOI: 10.1002/2014JB011176.
- 39. Rahaman, M.M., Thakur, B., Kalra, A. et al. (2019). Modeling of GRACE-derived groundwater information in the Colorado River Basin. Hydrology, 6(1), 19. DOI: 10.3390/hydrology6010019.
- 40. Ran, J., Ditmar, P., Klees R. et al. (2018). Statistically optimal estimation of Greenland ice sheet mass variations from GRACE monthly solutions using an improved mascon approach. J. Geod., 92(3), 299–319. DOI: 10.1007/s00190-017-1063-5.
- 41. Ries, J., Bettadpur, S., Eanes, R. et al. (2016). The Combined Gravity Model GGM05C. GFZ Data Services. DOI: 10.5880/icgem.2016.002.
- 42. Scanlon, B.R., Rateb, A., Anyamba, A. et al. (2022). Linkages between GRACE water storage, hydrologic extremes, and climate teleconnections in major African aquifers. Environ. Res. Lett., 17(1), 014046. DOI: 10.18738/T8/HLXCMY.
- 43. Schumacher, M., Forootan, E., van Dijk, A.I. et al. (2018). Improving drought simulations within the Murray–Darling Basin by combined calibration/assimilation of GRACE data into the WaterGAP Global Hydrology Model. Remote Sens. Environ., 204, 212–228. DOI: 10.1016/j.rse.2017.10.029.
- 44. Sun, Z., Zhu, X., Pan, Y. et al. (2017). Assessing terrestrial water storage and flood potential using GRACE data in the Yangtze River basin, China. Remote Sens., 9(10), 1011. DOI: 10.3390/rs9101011.
- 45. Tapley, B.D., Bettadpur, S., Watkins, M. et al. (2004). The gravity recovery and climate experiment: Mission overview and early results. Geophys. Res. Lett., 31(9). DOI: 10.1029/2004GL019920.
- 46. Tapley, B.D., Watkins, M.M., Flechtner, F. et al. (2019). Contributions of GRACE to understanding climate change. Nat. Clim. Change., 9(5), 358–369. DOI: 10.1038/s41558-019-0456-2.
- 47. Wahr, J., Swenson, S., and Velicogna, I. (2006). Accuracy of GRACE mass estimates. Geophys. Res. Lett., 33(6). DOI: 10.1029/2005GL025305.
- 48. Wang, L., Chen, C., Ma, X. et al. (2020). Evaluation of GRACE mascon solutions using in-situ geodetic data: The case of hydrologic-induced crust displacement in the Yangtze River Basin. Sci. Total Environ., 707, 135606. DOI: 10.1016/j.scitotenv.2019.135829.
- 49. Welch, P.D. (1967). The use of fast fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE trans. audio electroacoust. 15(2), 70–73. DOI: 10.1109/TAU.1967.1161901.
- 50. Williams, S.D.P., Moore, P., King, M.A. et al. (2014). Revisiting GRACE Antarctic ice mass trends and accelerations considering autocorrelation. Earth Planet. Sci. Lett., 385, 12–21. DOI: 10.1016/j.epsl.2013.10.016.
- 51. Xie, Z., Huete, A., Restrepo-Coupe, N. et al. (2016). Spatial partitioning and temporal evolution of Australia’s total water storage under extreme hydroclimatic impacts. Remote Sens. Environ., 183, 43–52. DOI: 10.1016/j.rse.2016.05.017.
- 52. Yin, H., and Li, C. (2001). Human impact on floods and flood disasters on the Yangtze River. Geomorphology, 41(2-3), 105–109. DOI: 10.1016/S0169-555X(01)00108-8.
- 53. Zhang, Y., He, B.I.N., Guo, L. et al. (2019). Differences in response of terrestrial water storage components to precipitation over 168 global river basins. J. Hydrometeorol., 20(9), 1981–1999. DOI: 10.1175/JHM-D-18-0253.1.
- 54. Zhou, Y., Jin, S., Tenzer, R. et al. (2016). Water storage variations in the Poyang Lake Basin estimated from GRACE and satellite altimetry. Geod. Geodyn., 7(2), 108–116. DOI: 10.1016/j.geog.2016.04.003.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0c0077e0-e411-496a-a9da-9edbe10e4d56