Articles | Volume 18, issue 18
https://doi.org/10.5194/gmd-18-6195-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-6195-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
23 Sep 2025
Development and technical paper |
| 23 Sep 2025
| 23 Sep 2025
PyGLDA: a fine-scale python-based global land data assimilation system for integrating satellite gravity data into hydrological models
Geodesy Group, Department of Sustainability and Planning, Aalborg University, 9000 Aalborg, Denmark
School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China
Maike Schumacher
Geodesy Group, Department of Sustainability and Planning, Aalborg University, 9000 Aalborg, Denmark
Leire Retegui-Schiettekatte
Geodesy Group, Department of Sustainability and Planning, Aalborg University, 9000 Aalborg, Denmark
Albert I. J. M. van Dijk
Fenner School of Environment & Society, College of Science, Australian National University, 2600 Canberra, Australia
Ehsan Forootan
Geodesy Group, Department of Sustainability and Planning, Aalborg University, 9000 Aalborg, Denmark
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Cited articles
A, G., Wahr, J., and Zhong, S.: Computations of the viscoelastic response of a 3-D compressible Earth to surface loading: an application to Glacial Isostatic Adjustment in Antarctica and Canada, Geophys. J. Int., 192, 557–572, https://doi.org/10.1093/gji/ggs030, 2013. a
Benedict, I., van Heerwaarden, C. C., Weerts, A. H., and Hazeleger, W.: An evaluation of the importance of spatial resolution in a global climate and hydrological model based on the Rhine and Mississippi basin, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2017-473, 2017. a
Boergens, E., Kvas, A., Eicker, A., Dobslaw, H., Schawohl, L., Dahle, C., Murböck, M., and Flechtner, F.: Uncertainties of GRACE-Based Terrestrial Water Storage Anomalies for Arbitrary Averaging Regions, J. Geophys. Res.-Solid, 127, https://doi.org/10.1029/2021JB022081, 2022. a, b
Caron, L., Ivins, E. R., Larour, E., Adhikari, S., Nilsson, J., and Blewitt, G.: GIA Model Statistics for GRACE Hydrology, Cryosphere, and Ocean Science, Geophys. Res. Lett., 45, 2203–2212, https://doi.org/10.1002/2017gl076644, 2018. a
Castellazzi, P., Martel, R., Rivera, A., Huang, J., Pavlic, G., Calderhead, A. I., Chaussard, E., Garfias, J., and Salas, J.: Groundwater depletion in Central Mexico: Use of GRACE and InSAR to support water resources management, Water Resour. Res., 52, 5985–6003, https://doi.org/10.1002/2015WR018211, 2016. a
Castle, S. L., Reager, J. T., Thomas, B. F., Purdy, A. J., Lo, M.-H., Famiglietti, J. S., and Tang, Q.: Remote detection of water management impacts on evapotranspiration in the Colorado River Basin, Geophys. Res. Lett., 43, 5089–5097, https://doi.org/10.1002/2016GL068675, 2016. a
Chen, J., Wilson, C. R., and Seo, K.-W.: Optimized smoothing of Gravity Recovery and Climate Experiment (GRACE) time-variable gravity observations, J. Geophys. Res.-Solid, 111, https://doi.org/10.1029/2005JB004064, 2006. a
Chen, J., Wilson, C. R., Li, J., and Zhang, Z.: Reducing leakage error in GRACE-observed long-term ice mass change: a case study in West Antarctica, J. Geod., 89, 1432–1394, https://doi.org/10.1007/s00190-015-0824-2, 2015. a, b
Chen, J., Cazenave, A., Dahle, C., Llovel, W., Panet, I., Pfeffer, J., and Moreira, L.: Applications and Challenges of GRACE and GRACE Follow-On Satellite Gravimetry, Surv. Geophys., 43, 305–345, https://doi.org/10.1007/s10712-021-09685-x, 2022. a
Daras, I., March, G., Pail, R., Hughes, C. W., Braitenberg, C., Güntner, A., Eicker, A., Wouters, B., Heller-Kaikov, B., Pivetta, T., and Pastorutti, A.: Mass-change And Geosciences International Constellation (MAGIC) expected impact on science and applications, Geophys. J. Int., 236,1288–1308, https://doi.org/10.1093/gji/ggad472, 2023. a, b, c, d
Decharme, B., Delire, C., Minvielle, M., Colin, J., Vergnes, J.-P., Alias, A., Saint-Martin, D., Séférian, R., Sénési, S., and Voldoire, A.: Recent Changes in the ISBA-CTRIP Land Surface System for Use in the CNRM-CM6 Climate Model and in Global Off-Line Hydrological Applications, J. Adv. Model. Earth Syst., 11, 1207–1252, https://doi.org/10.1029/2018MS001545, 2019. a
Deggim, S., Eicker, A., Schawohl, L., Gerdener, H., Schulze, K., Engels, O., Kusche, J., Saraswati, A. T., van Dam, T., Ellenbeck, L., Dettmering, D., Schwatke, C., Mayr, S., Klein, I., and Longuevergne, L.: RECOG RL01: correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes, Earth Syst. Sci. Data, 13, 2227–2244, https://doi.org/10.5194/essd-13-2227-2021, 2021. a
de Graaf, I. E., van Beek, R. L., Gleeson, T., Moosdorf, N., Schmitz, O., Sutanudjaja, E. H., and Bierkens, M. F.: A global-scale two-layer transient groundwater model: Development and application to groundwater depletion, Adv. Water Resour., 102, 53–67, https://doi.org/10.1016/j.advwatres.2017.01.011, 2017. a
Eicker, A., Schumacher, M., Kusche, J., Döll, P., and Schmied, H. M.: Calibration/data assimilation approach for integrating GRACE data into the WaterGAP Global Hydrology Model (WGHM) using an ensemble Kalman filter: First results, Surv. Geophys., 35, 1285–1309, https://doi.org/10.1007/s10712-014-9309-8, 2014. a
Eicker, A., Forootan, E., Springer, A., Longuevergne, L., and Kusche, J.: Does GRACE see the terrestrial water cycle “intensifying”?, J. Geophys. Res.-Atmos., 121, 733–745, https://doi.org/10.1002/2015JD023808, 2016. a
Evensen, G.: Data assimilation: the ensemble Kalman filter, vol. 2, Springer, https://doi.org/10.1007/978-3-642-03711-5, 2009. a
Felsberg, A., Lannoy, G. J. M. D., Girotto, M., Poesen, J., Reichle, R. H., and Stanley, T.: Global Soil Water Estimates as Landslide Predictor: The Effectiveness of SMOS, SMAP, and GRACE Observations, Land Surface Simulations, and Data Assimilation, J. Hydrometeorol., 22, 1065–1084, https://doi.org/10.1175/JHM-D-20-0228.1, 2021. a
Forman, B. A. and Reichle, R. H.: The spatial scale of model errors and assimilated retrievals in a terrestrial water storage assimilation system, Water Resour. Res., 49, 7457–7468, https://doi.org/10.1002/2012WR012885, 2013. a
Forootan, E., Khaki, M., Schumacher, M., Wulfmeyer, V., Mehrnegar, N., van Dijk, A., Brocca, L., Farzaneh, S., Akinluyi, F., Ramillien, G., Shum, C., Awange, J., and Mostafaie, A.: Understanding the global hydrological droughts of 2003–2016 and their relationships with teleconnections, Sci. Total Environ., 650, 2587–2604, https://doi.org/10.1016/j.scitotenv.2018.09.231, 2019. a
Forootan, E., Mehrnegar, N., Schumacher, M., Schiettekatte, L. A. R., Jagdhuber, T., Farzaneh, S., van Dijk, A. I., Shamsudduha, M., and Shum, C.: Global groundwater droughts are more severe than they appear in hydrological models: An investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance model, Sci. Total Environ., 912, 169476, https://doi.org/10.1016/j.scitotenv.2023.169476, 2024. a, b
Gerdener, H., Kusche, J., Schulze, K., Döll, P., and Klos, A.: The global land water storage data set release 2 (GLWS2.0) derived via assimilating GRACE and GRACE-FO data into a global hydrological model, J. Geod., 97, 73, https://doi.org/10.1007/s00190-023-01763-9, 2023. a, b, c
Girotto, M., De Lannoy, G. J. M., Reichle, R. H., and Rodell, M.: Assimilation of gridded terrestrial water storage observations from GRACE into a land surface model, Water Resour. Res., 52, 4164–4183, https://doi.org/10.1002/2015WR018417, 2016. a, b
Gouweleeuw, B. T., Kvas, A., Gruber, C., Gain, A. K., Mayer-Gürr, T., Flechtner, F., and Güntner, A.: Daily GRACE gravity field solutions track major flood events in the Ganges-Brahmaputra Delta, Hydrol. Earth Syst. Sci., 22, 2867–2880, https://doi.org/10.5194/hess-22-2867-2018, 2018. a
Han, S.-C., Shum, C. K., Jekeli, C., Kuo, C.-Y., Wilson, C., and Seo, K.-W.: Non-isotropic filtering of GRACE temporal gravity for geophysical signal enhancement, Geophys. J. Int., 163, 18–25, https://doi.org/10.1111/j.1365-246X.2005.02756.x, 2005. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thěpaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hoch, J. M., Sutanudjaja, E. H., Wanders, N., van Beek, R. L. P. H., and Bierkens, M. F. P.: Hyper-resolution PCR-GLOBWB: opportunities and challenges from refining model spatial resolution to 1 km over the European continent, Hydrol. Earth Syst. Sci., 27, 1383–1401, https://doi.org/10.5194/hess-27-1383-2023, 2023. a
Horvath, A., Murböck, M., Pail, R., and Horwath, M.: Decorrelation of GRACE time variable gravity field solutions using full covariance information, Geosciences, 8, 323, https://doi.org/10.3390/geosciences8090323, 2018. a
Jasechko, S., Seybold, H., Perrone, D., Fan, Y., Shamsudduha, M., Taylor, R. G., Fallatah, O., and Kirchner, J. W.: Rapid groundwater decline and some cases of recovery in aquifers globally, Nature, 625, 715–721, https://doi.org/10.1038/s41586-023-06879-8, 2024. a
Jekeli, C.: Alternative methods to smooth the Earth's gravity field, Report No. 327, Reports of the Department of Geodetic Science and Surveying, Ohio State Univ. Columbus, OH, USA, https://earthsciences.osu.edu/sites/earthsciences.osu.edu/files/report-327.pdf (last access: 1 May 2024), 1981. a
Khaki, M., Schumacher, M., Forootan, E., Kuhn, M., Awange, J. L., and van Dijk, A. I.: Accounting for spatial correlation errors in the assimilation of GRACE into hydrological models through localization, Adv. Water Resour., 108, 99–112, https://doi.org/10.1016/j.advwatres.2017.07.024, 2017. a, b, c
Klees, R., Zapreeva, E. A., Winsemius, H. C., and Savenije, H. H. G.: The bias in GRACE estimates of continental water storage variations, Hydrol. Earth Syst. Sci., 11, 1227–1241, https://doi.org/10.5194/hess-11-1227-2007, 2007. a
Klees, R., Revtova, E. A., Gunter, B. C., Ditmar, P., Oudman, E., Winsemius, H. C., and Savenije, H. H. G.: The design of an optimal filter for monthly GRACE gravity models, Geophys. J. Int., 175, 417–432, https://doi.org/10.1111/j.1365-246X.2008.03922.x, 2008. a
Kusche, J.: Approximate decorrelation and non-isotropic smoothing of time-variable GRACE-type gravity field models, J. Geod., 81, 733–749, https://doi.org/10.1007/s00190-007-0143-3, 2007. a, b
Kusche, J., Schmidt, R., Petrovic, S., and Rietbroek, R.: Decorrelated GRACE time-variable gravity solutions by GFZ, and their validation using a hydrological model, J. Geod., 81, 903–913, https://doi.org/10.1007/s00190-009-0308-3, 2009. a, b
Kvas, A. and Mayer-Gürr, T.: GRACE gravity field recovery with background model uncertainties, J. Geod., 93, 2543–2552, https://doi.org/10.1007/s00190-019-01314-1, 2019. a
Kvas, A., Behzadpour, S., Ellmer, M., Klinger, B., Strasser, S., Zehentner, N., and Mayer-Gürr, T.: ITSG-Grace2018: Overview and evaluation of a new GRACE-only gravity field time series, J. Geophys. Res.-Solid, 124, 9332–9344, https://doi.org/10.1029/2019JB017415, 2019. a
Landerer, F. W. and Swenson, S. C.: Accuracy of scaled GRACE terrestrial water storage estimates, Water Resour. Res., 48, https://doi.org/10.1029/2011WR011453, 2012. a, b
Landerer, F. W., Flechtner, F. M., Save, H., Webb, F. H., Bandikova, T., Bertiger, W. I., Bettadpur, S. V., Byun, S. H., Dahle, C., Dobslaw, H., Fahnestock, E., Harvey, N., Kang, Z., Kruizinga, G. L. H., Loomis, B. D., McCullough, C., Murböck, M., Nagel, P., Paik, M., Pie, N., Poole, S., Strekalov, D., Tamisiea, M. E., Wang, F., Watkins, M. M., Wen, H.-Y., Wiese, D. N., and Yuan, D.-N.: Extending the Global Mass Change Data Record: GRACE Follow-On Instrument and Science Data Performance, Geophys. Res. Lett., 47, https://doi.org/10.1029/2020GL088306, 2020. a
Li, B., Rodell, M., Kumar, S., Beaudoing, H. K., Getirana, A., Zaitchik, B. F., de Goncalves, L. G., Cossetin, C., Bhanja, S., Mukherjee, A.,Tian, S., Tangdamrongsub, N., Long, D., Nanteza, J., Lee, J., Policelli, F., Goni, I. B., Daira, D., Bila, M., de Lannoy, G., Mocko, D., Steele-Dunne, S. C., Save, H., and Bettadpur, S.: Global GRACE data assimilation for groundwater and drought monitoring: Advances and challenges, Water Resour. Res., 55, 7564–7586, https://doi.org/10.1029/2018WR024618, 2019. a, b, c, d
Liu, S., Yang, F., and Forootan, E.: SAGEA: A toolbox for comprehensive error assessment of GRACE and GRACE-FO based mass changes, Comput. Geosci., 196, 105825, https://doi.org/10.1016/j.cageo.2024.105825, 2025. a, b
Longuevergne, L., Scanlon, B. R., and Wilson, C. R.: GRACE Hydrological estimates for small basins: Evaluating processing approaches on the High Plains Aquifer, USA, Water Resour. Res., 46, https://doi.org/10.1029/2009wr008564, 2010. a
Loomis, B. D., Rachlin, K. E., Wiese, D. N., Landerer, F. W., and Luthcke, S. B.: Replacing GRACE/GRACE-FO With Satellite Laser Ranging: Impacts on Antarctic Ice Sheet Mass Change, Geophys. Res. Lett., 47, https://doi.org/10.1029/2019gl085488, 2020. a, b, c
Mayer-Gürr, T., Behzadpur, S., Ellmer, M., Kvas, A., Klinger, B., Strasser, S., and Zehentner, N.: ITSG-Grace2018-monthly, daily and static gravity field solutions from GRACE, https://doi.org/10.5880/ICGEM.2018.003, 2018. a
Mehrnegar, N., Jones, O., Singer, M. B., Schumacher, M., Bates, P., and Forootan, E.: Comparing global hydrological models and combining them with GRACE by dynamic model data averaging (DMDA), Adv. Water Resour., 138, 103528, https://doi.org/10.1016/j.advwatres.2020.103528, 2020. a, b, c, d
Mehrnegar, N., Jones, O., Singer, M. B., Schumacher, M., Jagdhuber, T., Scanlon, B. R., Rateb, A., and Forootan, E.: Exploring groundwater and soil water storage changes across the CONUS at 12.5 km resolution by a Bayesian integration of GRACE data into W3RA, Sci. Total Environ., 758, 143579, https://doi.org/10.1016/j.scitotenv.2020.143579, 2021. a
Mehrnegar, N., Schumacher, M., Jagdhuber, T., and Forootan, E.: Making the Best Use of GRACE, GRACE-FO and SMAP Data Through a Constrained Bayesian Data-Model Integration, Water Resour. Res., 59, https://doi.org/10.1029/2023WR034544, 2023. a
Meyer, U., Jean, Y., Kvas, A., Dahle, C., Lemoine, J.-M., and Jäggi, A.: Combination of GRACE monthly gravity fields on the normal equation level, J. Geod., 93, 1645–1658, https://doi.org/10.1007/s00190-019-01274-6, 2019. a
Müller Schmied, H., Cáceres, D., Eisner, S., Flörke, M., Herbert, C., Niemann, C., Peiris, T. A., Popat, E., Portmann, F. T., Reinecke, R., Schumacher, M., Shadkam, S., Telteu, C. E., Trautmann, T., and Döll, P.: The global water resources and use model WaterGAP v2.2d: model description and evaluation, Geosci. Model Dev., 14, 1037–1079, https://doi.org/10.5194/gmd-14-1037-2021, 2021. a
Müller Schmied, H., Trautmann, T., Ackermann, S., Cáceres, D., Flörke, M., Gerdener, H., Kynast, E., Peiris, T. A., Schiebener, L., Schumacher, M., and Döll, P.: The global water resources and use model WaterGAP v2.2e: description and evaluation of modifications and new features, Geosci. Model Dev., 17, 8817–8852, https://doi.org/10.5194/gmd-17-8817-2024, 2024. a
Ngo-Duc, T., Laval, K., Ramillien, G., Polcher, J., and Cazenave, A.: Validation of the land water storage simulated by Organising Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) with Gravity Recovery and Climate Experiment (GRACE) data, Water Resour. Res., 43, https://doi.org/10.1029/2006WR004941, 2007. a
Niu, G.-Y., Yang, Z.-L., Dickinson, R. E., Gulden, L. E., and Su, H.: Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data, J. Geophys. Res.-Atmos., 112, https://doi.org/10.1029/2006JD007522, 2007. a
Patel, C. R.: Analyzing and Monitoring GRACE-FO Star Camera Performance in a Changing Environment, MS thesis, The University of Texas at Austin, https://doi.org/10.26153/tsw/10143, 2020. a
Reichle, R. H. and Koster, R. D.: Assessing the Impact of Horizontal Error Correlations in Background Fields on Soil Moisture Estimation, J. Hydrometeorol., 4, 1229–1242, https://doi.org/10.1175/1525-7541(2003)004<1229:ATIOHE>2.0.CO;2, 2003. a, b, c, d
Richard Peltier, W., Argus, D. F., and Drummond, R.: Comment on “An Assessment of the ICE-6G_C (VM5a) Glacial Isostatic Adjustment Model” by Purcell et al., J. Geophys. Res.-Solid, 123, 2019–2028, https://doi.org/10.1002/2016JB013844, 2018. a, b
Rodell, M. and Reager, J. T.: Water cycle science enabled by the GRACE and GRACE-FO satellite missions, Nat. Water, 1, 47–59, https://doi.org/10.1038/s44221-022-00005-0, 2023. a
Rodell, M., Famiglietti, J., Wiese, D. N., Reager, J. T., Beaudoing, H. K., Landerer, F. W., and Lo, M. H.: Emerging trends in global freshwater availability, Nature, 557, 651–659, https://doi.org/10.1038/s41586-018-0123-1, 2018. a
Save, H., Bettadpur, S., and Tapley, B. D.: High-resolution CSR GRACE RL05 mascons, J. Geophys. Res.-Solid, 121, 7547–7569, https://doi.org/10.1002/2016JB013007, 2016. a
Scanlon, B. R., Faunt, C. C., Longuevergne, L., Reedy, R. C., Alley, W. M., McGuire, V. L., and McMahon, P. B.: Groundwater depletion and sustainability of irrigation in the US High Plains and Central Valley, P. Natl. Acad. Sci. USA, 109, 9320–9325, https://doi.org/10.1073/pnas.1200311109, 2012. a
Scanlon, B. R., Zhang, Z., Save, H., Sun, A. Y., Müller Schmied, H., Van Beek, L. P., Wiese, D. N., Wada, Y., Long, D., Reedy, R. C., et al.: Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data, P. Natl. Acad. Sci. USA, 115, E1080–E1089, https://doi.org/10.1073/pnas.170466511, 2018. a, b
Schellekens, J., Dutra, E., Martínez-de la Torre, A., Balsamo, G., van Dijk, A., Sperna Weiland, F., Minvielle, M., Calvet, J.-C., Decharme, B., Eisner, S., Fink, G., Flörke, M., Peßenteiner, S., van Beek, R., Polcher, J., Beck, H., Orth, R., Calton, B., Burke, S., Dorigo, W., and Weedon, G. P.: A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset, Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, 2017. a
Schumacher, M., Kusche, J., and Döll, P.: A systematic impact assessment of GRACE error correlation on data assimilation in hydrological models, J. Geod., 90, 537–559, https://doi.org/10.1007/s00190-016-0892-y, 2016. a, b
Schumacher, M., Forootan, E., van Dijk AIJM, Müller Schmied, H., Crosbie, R., Kusche, J., and Döll, P.: 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, https://doi.org/10.1016/j.rse.2017.10.029, 2018. a, b, c
Sheffield, J., Ferguson, C. R., Troy, T. J., Wood, E. F., and McCabe, M. F.: Closing the terrestrial water budget from satellite remote sensing, Geophys. Res. Lett., 36, https://doi.org/10.1029/2009GL037338, 2009. a
Springer, A., Karegar, M. A., Kusche, J., Keune, J., Kurtz, W., and Kollet, S.: Evidence of daily hydrological loading in GPS time series over Europe, J. Geod., 93, 2145–2153, 2019. a
Stagl, J. C. and Hattermann, F. F.: Impacts of Climate Change on the Hydrological Regime of the Danube River and Its Tributaries Using an Ensemble of Climate Scenarios, Water, 7, 6139–6172, https://doi.org/10.3390/w7116139, 2015. a
Sutanudjaja, E. H., van Beek, R., Wanders, N., Wada, Y., Bosmans, J. H. C., Drost, N., van der Ent, R. J., de Graaf, I. E. M., Hoch, J. M., de Jong, K., Karssenberg, D., López López, P., Peßenteiner, S., Schmitz, O., Straatsma, M. W., Vannametee, E., Wisser, D., and Bierkens, M. F. P.: PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model, Geosci. Model Dev., 11, 2429–2453, https://doi.org/10.5194/gmd-11-2429-2018, 2018. a, b
Swenson, S. and Wahr, J.: Post-processing removal of correlated errors in GRACE data, Geophys. Res. Lett., 33, https://doi.org/10.1029/2005GL025285, 2006. a, b
Swenson, S., Chambers, D., and Wahr, J.: Estimating geocenter variations from a combination of GRACE and ocean model output, J. Geophys. Res.-Solid, 113, https://doi.org/10.1029/2007jb005338, 2008. a
Tapley, B. D., Bettadpur, S., Watkins, M., and Reigber, C.: The gravity recovery and climate experiment: Mission overview and early results, Geophys. Res. Lett., 31, https://doi.org/10.1029/2004GL019920, 2004. a
Tian, S., Tregoning, P., Renzullo, L. J., van Dijk, A. I. J. M., Walker, J. P., Pauwels, V. R. N., and Allgeyer, S.: Improved water balance component estimates through joint assimilation of GRACE water storage and SMOS soil moisture retrievals, Water Resour. Res., 53, 1820–1840, https://doi.org/10.1002/2016WR019641, 2017. a, b, c, d
van Dijk, A.: AWRA Technical Report 3, Landscape Model (version 0.5) Technical Description, CSIRO Water for a Healthy Country Flagship, https://www.researchgate.net/publication/233757155_AWRA_Technical_Report_3_Landscape_Model_version_05_Technical_Description (last access: 1 July 2023), 2010. a, b, c, d, e, f
van Dijk, A. I. J. M., Renzullo, L. J., Wada, Y., and Tregoning, P.: A global water cycle reanalysis (2003–2012) merging satellite gravimetry and altimetry observations with a hydrological multi-model ensemble, Hydrol. Earth Syst. Sci., 18, 2955–2973, https://doi.org/10.5194/hess-18-2955-2014, 2014. a
Vishwakarma, B. D., Devaraju, B., and Sneeuw, N.: What Is the Spatial Resolution of GRACE Satellite Products for Hydrology?, Remote Sens., 10, https://doi.org/10.3390/rs10060852, 2018. a, b
Voss, K. A., Famiglietti, J. S., Lo, M., De Linage, C., Rodell, M., and Swenson, S. C.: Groundwater depletion in the Middle East from GRACE with implications for transboundary water management in the Tigris-Euphrates-Western Iran region, Water Resour. Res., 49, 904–914, https://doi.org/10.1002/wrcr.20078, 2013. a
Wahr, J., Molenaar, M., and Bryan, F.: Time variability of the Earth's gravity field: Hydrological and oceanic effects and their possible detection using GRACE, J. Geophys. Res.-Solid, 103, 30205–30229, https://doi.org/10.1029/98jb02844, 1998. a, b
Wahr, J., Swenson, S., and Velicogna, I.: Accuracy of GRACE mass estimates, Geophys. Res. Lett., 33, https://doi.org/10.1029/2005GL025305, 2006. a
Webber, R. J. and Morzfeld, M.: Localized covariance estimation: A Bayesian perspective, arXiv preprint, https://doi.org/10.48550/arXiv.2301.04828, 2023. a
Yang, F.: PyGLDA: Python-based Global Land Data Assimilation, Zenodo [code and data set], https://doi.org/10.5281/zenodo.12206756, 2024. a, b, c
Yang, F., Kusche, J., Forootan, E., and Rietbroek, R.: Passive‐ocean radial basis function approach to improve temporal gravity recovery from GRACE observations, J. Geophys. Res.-Solid, 122, https://doi.org/10.1002/2016JB013633, 2017. a
Yang, F., Forootan, E., Schumacher, M., Shum, C., and Zhong, M.: Evaluating non-tidal atmospheric products by measuring GRACE K-band range rate residuals, Geophys. J. Int., 215, 1132–1147, https://doi.org/10.1093/gji/ggy340, 2018. a
Yang, F., Forootan, E., Wang, C., Kusche, J., and Luo, Z.: A New 1-Hourly ERA5-Based Atmosphere De-Aliasing Product for GRACE, GRACE-FO, and Future Gravity Missions, J. Geophys. Res.-Solid, 126, e2021JB021926, https://doi.org/10.1029/2021JB021926, 2021. a
Yang, F., Liang, L., Wang, C., and Luo, Z.: Attitude Determination for GRACE-FO: Reprocessing the Level-1A SC and IMU Data, Remote Sens., 14, https://doi.org/10.3390/rs14010126, 2022a. a
Yang, F., Luo, Z., Zhou, H., and Kusche, J.: On study of the Earth topography correction for the GRACE surface mass estimation, J. Geod., 96, https://doi.org/10.1007/s00190-022-01683-0, 2022b. a
Yang, F., Forootan, E., Liu, S., and Schumacher, M.: A Monte Carlo Propagation of the Full Variance-Covariance of GRACE-Like Level-2 Data With Applications in Hydrological Data Assimilation and Sea-Level Budget Studies, Water Resour. Res., 60, e2023WR036764, https://doi.org/10.1029/2023WR036764, 2024a. a, b, c, d, e
Yang, F., Liu, S., and Forootan, E.: A spatial-varying non-isotropic Gaussian-based convolution filter for smoothing GRACE-like temporal gravity fields, J. Geod., 98, 66, https://doi.org/10.1007/s00190-024-01875-w, 2024b. a
Zaitchik, B. F., Rodell, M., and Reichle, R. H.: Assimilation of GRACE terrestrial water storage data into a land surface model: Results for the Mississippi River basin, J. Hydrometeorol., 9, 535–548, https://doi.org/10.1175/2007JHM951.1, 2008. a
Zhang, Z.-Z., Chao, B. F., Lu, Y., and Hsu, H.-T.: An effective filtering for GRACE time-variable gravity: Fan filter, Geophys. Res. Lett., 36, https://doi.org/10.1029/2009GL039459, 2009. a
Zhou, H., Zheng, L., Pail, R., Liu, S., Qing, T., Yang, F., Guo, X., and Luo, Z.: The impacts of reducing atmospheric and oceanic de-aliasing model error on temporal gravity field model determination, Geophys. J. Int., 234, 210–227, https://doi.org/10.1093/gji/ggad064, 2023. a
Short summary
Satellite gravimetry enables direct measurement of total water storage (TWS), a capability that was previously unattainable. In this study, we present an open-source land data assimilation system with global hydrological model, which temporally, vertically, and laterally dis-aggregates satellite-based TWS. This study provides a practical framework establishing operational water management with current and future satellite gravity missions.
Satellite gravimetry enables direct measurement of total water storage (TWS), a capability that...
