Cao, Y. and Roy, S. S.: Spatial patterns of seasonal level trends of groundwater in India during 2002–2016, Weather, 75, 123–128,
https://doi.org/10.1002/wea.3370, 2020.
a
Chen, J., Li, J., Zhang, Z., and Ni, S.: Long-term groundwater variations in
Northwest India from satellite gravity measurements, Global Planet. Change, 116, 130–138,
https://doi.org/10.1016/j.gloplacha.2014.02.007, 2014.
a
Chen, L., He, Q., Liu, K., Li, J., and Jing, C.: Downscaling of GRACE-Derived Groundwater Storage Based on the Random Forest Model, Remote Sens., 11, 2979,
https://doi.org/10.3390/rs11242979, 2019.
a,
b,
c
Dewandel, B., Caballero, Y., Perrin, J., Boisson, A., Dazin, F., Ferrant, S.,
Chandra, S., and Maréchal, J.-C.: A methodology for regionalizing 3-D effective porosity at watershed scale in crystalline aquifers, Hydrol. Process., 31, 2277–2295,
https://doi.org/10.1002/hyp.11187, 2017.
a
ESA: Climate Change Initiative,
https://www.esa-soilmoisture-cci.org, last access: 9 August 2022. a
Feng, W., Zhong, M., Lemoine, J.-M., Biancale, R., Hsu, H.-T., and Xia, J.:
Evaluation of groundwater depletion in North China using the Gravity Recovery and Climate Experiment (GRACE) data and ground-based measurements, Water Resour. Res., 49, 2110–2118,
https://doi.org/10.1002/wrcr.20192, 2013.
a
Frappart, F., Papa, F., Güntner, A., Tomasella, J., Pfeffer, J., Ramillien,
G., Emilio, T., Schietti, J., Seoane, L., da Silva Carvalho, J., Medeiros Moreira, D., Bonnet, M. P., and Seyler, F.: The spatio-temporal
variability of groundwater storage in the Amazon River Basin, Adv. Water Resour., 124, 41–52,
https://doi.org/10.1016/j.advwatres.2018.12.005, 2019.
a
Girotto, M., Lannoy, G. J. M. D., 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
Hora, T., Srinivasan, V., and Basu, N. B.: The Groundwater Recovery Paradox in South India, Geophys. Res. Lett., 46, 9602–9611,
https://doi.org/10.1029/2019GL083525, 2019.
a
Houborg, R., Rodell, M., Li, B., Reichle, R., and Zaitchik, B. F.: Drought
indicators based on model-assimilated Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage observations, Water Resour. Res., 48, W07525,
https://doi.org/10.1029/2011WR011291, 2012.
a,
b,
c
Huang, Z., Pan, Y., Gong, H., Yeh, P. J.-F., Li, X., Zhou, D., and Zhao, W.:
Subregional-scale groundwater depletion detected by GRACE for both shallow
and deep aquifers in North China Plain, Geophys. Res. Lett., 42, 1791–1799,
https://doi.org/10.1002/2014GL062498, 2015.
a
Jyolsna, P. J., Kambhammettu, B. V. N. P., and Gorugantula, S.: Application of random forest and multi-linear regression methods in downscaling GRACE
derived groundwater storage changes, Hydrolog. Sci. J., 66, 874–887,
https://doi.org/10.1080/02626667.2021.1896719, 2021.
a,
b,
c,
d,
e,
f,
g
Karunakalage, A., Sarkar, T., Kannaujiya, S., Chauhan, P., Pranjal, P., Taloor, A. K., and Kumar, S.: The appraisal of groundwater storage dwindling effect, by applying high resolution downscaling GRACE data in and around Mehsana district, Gujarat, India, Groundwater Sustain. Dev., 13, 100559,
https://doi.org/10.1016/j.gsd.2021.100559, 2021.
a,
b,
c,
d,
e,
f,
g
Lemoine, J.-M. and Mandea, M.: The MARVEL gravity and reference frame mission
proposal, in: EGU General Assembly Conference Abstracts, p. 13359,
https://ui.adsabs.harvard.edu/abs/2020EGUGA..2213359L (last access: 8 August 2022), 2020. a
Lemoine, J. M., Meyssignac, B., Mandea, M., Samain, E., Bourgogne, S.,
Blazquez, A., Balmino, G., Louise, L., and Michaud, J.: MARVEL Mission
Proposal: The Latest Update, 2020, in: AGU Fall Meeting Abstracts, G020-08,
https://ui.adsabs.harvard.edu/abs/2020AGUFMG020...08L (last access: 8 August 2022), 2020. a
Long, D., Scanlon, B. R., Longuevergne, L., Sun, A. Y., Fernando, D. N., and
Save, H.: GRACE satellite monitoring of large depletion in water storage in
response to the 2011 drought in Texas, Geophys. Res. Lett., 40, 3395–3401,
https://doi.org/10.1002/grl.50655, 2013.
a,
b
Maréchal, J. C., Dewandel, B., Ahmed, S., Galeazzi, L., and Zaidi, F. K.:
Combined estimation of specific yield and natural recharge in a semi-arid
groundwater basin with irrigated agriculture, J. Hydrol., 329, 281–293,
https://doi.org/10.1016/j.jhydrol.2006.02.022, 2006.
a,
b
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925,
https://doi.org/10.5194/gmd-10-1903-2017, 2017.
a
Massotti, L., Siemes, C., March, G., Haagmans, R., and Silvestrin, P.: Next
Generation Gravity Mission Elements of the Mass Change and Geoscience International Constellation: From Orbit Selection to Instrument and Mission Design, Remote Sens., 13, 3935–3966,
https://doi.org/10.3390/rs13193935, 2021.
a
Merlin, O., Malbéteau, Y., Notfi, Y., Bacon, S., Khabba, S. E.-R. S., and
Jarlan, L.: Performance Metrics for Soil Moisture Downscaling Methods: Application to DISPATCH Data in Central Morocco, Remote Sens., 7, 3783–3807,
https://doi.org/10.3390/rs70403783, 2015.
a,
b
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrology and Earth System Sciences, 15,
453–469,
https://doi.org/10.5194/hess-15-453-2011, 2011.
a
NASA: Measuring Earth's Surface Mass and Water Changes,
http://grace.jpl.nasa.gov (last access: 9 August 2022), 2022a. a
NASA: Welcome to AρρEEARS!,
https://appeears.earthdatacloud.nasa.gov (last access: 9 August 2022), 2022b. a
Nie, W., Zaitchik, B. F., Rodell, M., Kumar, S. V., Arsenault, K. R., Li, B.,
and Getirana, A.: Assimilating GRACE Into a Land Surface Model in the Presence of an Irrigation-Induced Groundwater Trend, Water Resour. Res., 55, 11274–11294,
https://doi.org/10.1029/2019WR025363, 2019.
a,
b,
c
Ning, S., Ishidaira, H., and Wang, J.: Statistical Downscaling of
Grace-Derived Terrestrial Water Storage Using Satellite and Gldas Products, J. Jpn. Soc. Civ. Eng. Ser. B1, 70, I_133–I_138,
https://doi.org/10.2208/jscejhe.70.I_133, 2014.
a,
b,
c,
d,
e
Papa, F., Frappart, F., Malbeteau, Y., Shamsudduha, M., Vuruputur, V., Sekhar, M., Ramillien, G., Prigent, C., Aires, F., Pandey, R. K., Bala, S., and Calmant, S.: Satellite-derived surface and sub-surface water storage in the Ganges–Brahmaputra River Basin, J. Hydrol.: Reg. Stud., 4, 15–35,
https://doi.org/10.1016/j.ejrh.2015.03.004, 2015.
a
Pascal, C., Ferrant, S., Selles, A., Maréchal, J.-C., Gascoin, S., and Merlin, O.: High-Resolution Mapping of Rainwater Harvesting System Capacity from Satellite Derived Products in South India, in: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, July 2021, Brussels, 7011–7014,
https://doi.org/10.1109/IGARSS47720.2021.9553131, 2021.
a
Rodell, M., Famiglietti, J. S., 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,
b
Sabaghy, S., Walker, J. P., Renzullo, L. J., Akbar, R., Chan, S., Chaubell, J., Das, N., Dunbar, R. S., Entekhabi, D., Gevaert, A., Jackson, T. J., Loew, A., Merlin, O., Moghaddam, M., Peng, J., Peng, J., Piepmeier, J., Rüdiger, C., Stefan, V., Wu, X., Ye, N., and Yueh, S.: Comprehensive analysis of
alternative downscaled soil moisture products, Remote Sens. Environ., 239, 111586,
https://doi.org/10.1016/j.rse.2019.111586, 2020.
a
Sahour, H., Sultan, M., Vazifedan, M., Abdelmohsen, K., Karki, S., Yellich,
J. A., Gebremichael, E., Alshehri, F., and Elbayoumi, T. M.: Statistical
Applications to Downscale GRACE-Derived Terrestrial Water Storage Data and to Fill Temporal Gaps, Remote Sens., 12, 533,
https://doi.org/10.3390/rs12030533, 2020.
a,
b,
c,
d,
e,
f,
g,
h
Schmidt, R., Flechtner, F., Meyer, U., Neumayer, K.-H., Dahle, C., König, R., and Kusche, J.: Hydrological Signals Observed by the GRACE Satellites, Surv. Geophys., 29, 319–334,
https://doi.org/10.1007/s10712-008-9033-3, 2008.
a,
b
Schumacher, M., Forootan, E., van Dijk, A. I. J. M., Müller Schmied, H.,
Crosbie, R. S., 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
Seyoum, W., Kwon, D., and Milewski, A.: Downscaling GRACE TWSA Data into
High-Resolution Groundwater Level Anomaly Using Machine Learning-Based Models in a Glacial Aquifer System, Remote Sens., 11, 824,
https://doi.org/10.3390/rs11070824, 2019.
a,
b,
c
Seyoum, W. M. and Milewski, A. M.: Improved methods for estimating local
terrestrial water dynamics from GRACE in the Northern High Plains, Adv. Water Resour., 110, 279–290,
https://doi.org/10.1016/j.advwatres.2017.10.021, 2017.
a,
b,
c,
d,
e,
f,
g
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, L09607,
https://doi.org/10.1029/2004GL019920, 2004.
a,
b,
c
Tian, S., Tregoning, P., Renzullo, L. J., v. 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
Tian, S., Renzullo, L. J., van Dijk, A. I. J. M., Tregoning, P., and Walker, J. P.: Global joint assimilation of GRACE and SMOS for improved estimation of root-zone soil moisture and vegetation response, Hydrol. Earth Syst. Sci., 23, 1067–1081,
https://doi.org/10.5194/hess-23-1067-2019, 2019.
a
Tiwari, V. M., Wahr, J., and Swenson, S.: Dwindling groundwater resources in
northern India, from satellite gravity observations, Geophys. Res. Lett., 36, L18401,
https://doi.org/10.1029/2009GL039401, 2009.
a,
b
Vishwakarma, B. D., Zhang, J., and Sneeuw, N.: Downscaling GRACE total water
storage change using partial least squares regression, Scient. Data, 8, 95,
https://doi.org/10.1038/s41597-021-00862-6, 2021.
a,
b
Vissa, N. K., Anandh, P. C., Behera, M. M., and Mishra, S.: ENSO-induced
groundwater changes in India derived from GRACE and GLDAS, J. Earth Syst. Sci., 128, 115,
https://doi.org/10.1007/s12040-019-1148-z, 2019.
a
Wada, Y., v. Beek, L. P. H., and Bierkens, M. F. P.: Nonsustainable groundwater sustaining irrigation: A global assessment, Water Resour. Res., 48, W00L06,
https://doi.org/10.1029/2011WR010562, 2012.
a
Watkins, M. M., Wiese, D. N., Yuan, D.-N., Boening, C., and Landerer, F. W.:
Improved methods for observing Earth's time variable mass distribution with
GRACE using spherical cap mascons, J. Geophys. Res.-Solid, 120, 2648–2671,
https://doi.org/10.1002/2014JB011547, 2015.
a,
b
Wiese, D. N., Landerer, F. W., and Watkins, M. M.: Quantifying and reducing
leakage errors in the JPL RL05M GRACE mascon solution, Water Resour. Res., 52, 7490–7502,
https://doi.org/10.1002/2016WR019344, 2016.
a
Yin, W., Hu, L., Zhang, M., Wang, J., and Han, S.-C.: Statistical Downscaling
of GRACE-Derived Groundwater Storage Using ET Data in the North China Plain, J. Geophys. Res.-Atmos., 123, 5973–5987,
https://doi.org/10.1029/2017JD027468, 2018.
a,
b,
c,
d,
e
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,
b,
c
Zhang, G., Zheng, W., Yin, W., and Lei, W.: Improving the Resolution and
Accuracy of Groundwater Level Anomalies Using the Machine Learning-Based Fusion Model in the North China Plain, Sensors, 21, 46,
https://doi.org/10.3390/s21010046, 2021.
a,
b,
c,
d,
e,
f
Zhang, J., Liu, K., and Wang, M.: Seasonal and Interannual Variations in
China's Groundwater Based on GRACE Data and Multisource Hydrological Models, Remote Sens., 12, 845,
https://doi.org/10.3390/rs12050845, 2020.
a
Zhang, J., Liu, K., and Wang, M.: Downscaling Groundwater Storage Data in
China to a 1-km Resolution Using Machine Learning Methods, Remote Sens., 13, 523,
https://doi.org/10.3390/rs13030523, 2021.
a,
b,
c,
d,
e,
f,
g
Zhong, D., Wang, S., and Li, J.: A Self-Calibration Variance-Component Model for Spatial Downscaling of GRACE Observations Using Land Surface Model Outputs, Water Resour. Res., 57, e2020WR028944,
https://doi.org/10.1029/2020WR028944, 2021.
a,
b,
c,
d,
e
Zuo, J., Xu, J., Chen, Y., and Li, W.: Downscaling simulation of groundwater
storage in the Tarim River basin in northwest China based on GRACE data, Phys. Chem. Earth Pt. A/B/C, 123, 103042,
https://doi.org/10.1016/j.pce.2021.103042, 2021.
a,
b,
c,
d,
e
