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Terrestrial water storage has a significant impact on the water balance of river basins. The analysis of its changes in the European part of Russia (EPR) using the GRACE (Gravity Recovery and Climate Experiment) data showed that its reduction was approximately150 mmfor 2002-2015 for the south of EPR, especially the Don basin, which is caused rather by a decline in the storages of surface and ground waters then to changes in soil waters. Quasilinear relation between the values of terrestrial water storages and a river runoff for the period of a summer low water level for a number of rivers has been revealed.

About the Authors

Vadim Yu. Grigoriev
Water problems institute of Russian Academy of Science
Russian Federation
Junior researcher

Natalia L. Frolova
Lomonosov Moscow State University
Russian Federation
DSc in Geography, Professor of the Department of Hydrology of the Lomonosov Moscow State University. Member of the IAHS, a Member of the Hydrological Comission of the International Geographical Union


1. Albergel C., De Rosnay P., Balsamo G., Isaksen L., Muñoz-Sabater J. (2012). Soil Moisture Analyses at ECMWF: Evaluation Using Global Ground-Based In Situ Observations. Journal of Hydrometeorology, 13(5), pp. 1442-1460. DOI:

2. Andrew, R., Guan, H., Batelaan, O. (2017). Estimation of GRACE water storage components by temporal decomposition. Journal of Hydrology, 552, pp. 341-350. DOI:

3. Babkin V.I., Vuglinsky V.S. (1982). Water balance of river basins. Leningrad: Hydrometeoizdat (in Russian).

4. Chambers D. P., Cazenave A., Champollion N., Dieng H., Llovel W., Forsberg R., Schuckmann K., Wada Y. (2017). Evaluation of the Global Mean Sea Level Budget between 1993 and 2014. Surveys in Geophysics. 38(1), pp. 309-327. DOI:

5. Chen X., Long D., Hong Y., Zeng C., Yan D. (2017 a). Improved modeling of snow and glacier melting by a progressive two-stage calibration strategy with GRACE and multisource data: How snow and glacier meltwater contributes to the runoff of the Upper Brahmaputra River basin? Water Resour. Res., 53(3), pp. 2431-2466. DOI:10.1002/2016WR019656.

6. Chen J. L.,Wilson C. R.,Tapley B. D., Save H., Cretaux J. F.(2017 b). Long-termandseasonal Caspian Sea level change from satellite gravity and altimeter measurements. Journal of Geophysical Research - Solid Earth, 122(3), pp. 2274-2290. DOI:

7. Demchenko P. F., Kislov A. V. (2010). Stochastic Dynamics of Natural Objects. Brownian Motion and Geophysical Applications. Moscow: GEOS. (in Russian).

8. Deng H., Chen Y. (2017). Influences of recent climate change and human activities on water storage variations in Central Asia. Journal of Hydrology, 544, pp. 46-57. DOI:

9. Dobslaw H., Bergmann-Wolf I., Dill R., Poropat L., Thomas M., Dahle C., Esselborn S., Konig R., Flechtner F. (2017). A new high-resolution model of non-tidal atmosphere and ocean mass variability for de-aliasing of satellite gravity observations: AOD1B RL06. Geophysical Journal International, 211(1), pp. 263-269. DOI:

10. Dolgonosov B. M. (2009). Nonlinear dynamics of ecological and hydrological processes. Moscow: LIBROKOM, p. 440. (in Russian).

11. Dzhamalov R. G., Frolova N. L., Kireeva M. B., Rets E. P., Safronova T. I., Bugrov A. A., Telegina I. A., Telegina E. A. (2015). Modern resources of underground and surface waters of the European Russia: formation, distribution, use. Moscow: GEOS, p. 315. (in Russian).

12. Eom J., Seo K.-W., Ryu D. (2017). Estimation of Amazon River discharge based on EOF analysis of GRACE gravity data. Remote Sens. Environ., 191, pp. 55-66. DOI:

13. Forman B. A., Reichle R. H., Rodell M.(2012). Assimilationofterrestrialwaterstoragefrom GRACE in a snow-dominated basin. Water Resour. Res., 48(1), W01507. DOI: 10.1029/2011WR011239.

14. Forootan E., Safari A., Mostafaie A., Schumacher M., Delavar M., Awange J. L. (2016). Large- Scale Total Water Storage and Water Flux Changes over the Arid and Semiarid Parts of the Middle East from GRACE and Reanalysis Products. Surveys in Geophysics, 38(3), pp 591-615. DOI:

15. Frolov A. V. (2011). Discrete dynamic-stochastic model of long-term river runoff variations. Water Resources, 38(5), pp. 583-592. DOI: 10.1134/S0097807811040051.

16. Frolov A. V. (2014). Estimation of the statistical characteristics of long-term fluctuations in evaporation from large river catchments. Doklady Earth Sciences, 458(1), pp. 1183-1186. DOI: 10.1134/S1028334X1409027X.

17. Frolova N., Belyakova P., Grigoriev V., Sazonov A., Zotov L. V., Jarsjö J. (2017). Runoff fluctuations in the Selenga river basin. Regional Environmental Change, 17(7), pp. 1965–1976. DOI:

18. Girotto M., De Lannoy G. J. M., Reichle R. H., Rodell M., Draper C., Bhanja S. N., Mukherjee A. (2017). Benefitsand pitfalls of GRACEdataassimilation: Acasestudyofterrestrialwaterstorage depletion in India. Geophys. Res. Lett., 44(9), pp. 4107–4115. DOI:10.1002/2017GL072994.

19. (2017). JPL data page. [online]. Available at: https://grace.jpl.nasa. gov/data/grace-months/. [Accessed 20 Oct. 2017].

20. Khaki M., Hoteit I., Kuhn M., Awange J., Forootan E., van Dijk A., Schumacher M., Pattiaratchi C. (2017). Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model. Advances in Water Resources, 107, pp. 301-316.

21. Klemes V. (1974). The Hurst phenomenon— a puzzle? Water Resources Research, 10(4), pp. 675-688.

22. Klemes V. (1978). Physically based stochastic hydrologic analysis, Advances in Hydroscience, 11, 285– 356.

23. Klemes, V. (1978), Physically based stochastic hydrologic analysis, Adv. Hydrosci., 11, 285–356.

24. Klemes, V. (1978), Physically based stochastic hydrologic analysis, Adv. Hydrosci., 11, 285–356.

25. Kumar S. V., Zaitchik B. F., Peters-Lidard C. D. et al. (2016). Assimilation of Gridded GRACE Terrestrial Water Storage Estimates in the North American Land Data Assimilation System. Journal of Hydrometeorology, 17(7), pp. 1951-1972. DOI: jhm-d-15-0157.1.

26. Li Q., Zhong B., Luo Z. C., Yao C. L. (2016). GRACE-based estimates of water discharge over the Yellow River basin. Journal of Geodesy and Geodynamics, 7(3), pp. 187-193. DOI:

27. Lin P., Wei J., Yang Z.-L., Zhang Y., Zhang K. (2016). Snow data assimilation-constrained land initialization improves seasonal temperature prediction. Geophysical Research Letters, 43(21), 11,423-11,432. DOI: 10.1002/2016GL070966.

28. Liu Y. C., Hwang C. W., Han J. C., Kao R., Wu C. R., Shih H. C., Tangdamrongsub N. (2016). Sediment-Mass Accumulation Rate and Variability in the East China Sea Detected by GRACE. Remote Sensing, 8(9), 777. DOI:

29. Lorenz C., Kunstmann H., Devaraju B., Tourian M.J., Sneeuw N., Riegger N. (2014). Large- Scale Runoff from Landmasses: A Global Assessment of the Closure of the Hydrological and Atmospheric Water Balances. Journal of Hydrometeorology, 15(6), рp. 2111-2139. DOI: 10.1175/JHM-D-13-0157.1.

30. Naydenov V. I. (2004). Nonlinear dynamics of surface waters. Moscow: Nauka, p. 318 (in Russian).

31. Sakumura C., Bettadpur S., Bruinsma S. (2014). Ensemble prediction and intercomparison analysis of GRACE time-variable gravity field models. Geophys. Res. Lett. 41(5). pp. 1389- 1397. DOI:10.1002/2013GL058632

32. Save H., Bettadpur S., Tapley B. D. (2016). High-resolution CSR GRACE RL05 mascons. Journal of Geophysical Research-Solid Earth, 121(10), pp. 7547-7569. DOI:

33. Savin I.Y., Markov M. L., Ovechkin S. V., Isaev V. A. (2016). Trend in total terrestrial water storage at the European Russia detected based on GRACE DATA. Bulletin of V.V. Dokuchaev Soil Science Institute, 82, pp. 28-41. (in Russian with English abstract and title). DOI: 10.19047/0136-1694- 2016-82-28-41.

34. Schlegel N. J., Wiese D. N., Larour E. Y., Watkins M. M., Box J. E., Fettweis X., van den Broeke M. R. (2016). Application of GRACE to the assessment of model-based estimates of monthly Greenland Ice Sheet mass balance (2003-2012). Cryosphere, 10(5), pp. 1965-1989. DOI:

35. Seo J. Y., Lee S.-I. (2017). Total discharge estimation in the Korean Peninsula using multi- satellite products. Water, 9(7), 532. DOI:

36. Shiklomanov I. A. (ed.). Water resources of Russia and their use. (2008). St. Petersburg: State Hydrological Institute (in Russian)

37. Springer A., Eicker A., Bettge A., Kusche J., Hense A. (2017). Evaluation of the Water Cycle in the European COSMO-REA6 Reanalysis Using GRACE. Water, 9(4), 289. DOI:10.3390/w9040289.

38. Tangdamrongsub N., Steele-Dunne S. C., Gunter B. C., Ditmar P. G., Sutanudjaja E. H., Sun Y., Xia T., Wang Z. (2017). Improving estimates of water resources in a semi-arid region by assimilating GRACE data into the PCR-GLOBWB hydrological model. Hydrol. Earth Syst. Sci., 21(4), pp. 2053-2074. DOI:

39. Tian S., Tregoning P., Renzullo L. J., van Dijk A., Walker J. P., Pauwels V. R. N., Allgeyer S. (2017). Improved water balance component estimates through joint assimilation of GRACE water storage and SMOS soil moisture retrievals. Water Resour. Res., 53(3), pp. 1820-1840. DOI:10.1002/2016WR019641.

40. Wahr J., Burgess E., Swenson S. (2016). Using GRACE and climate model simulations to predict mass loss of Alaskan glaciers through 2100. Journal of Glaciology, 62(234), pp. 623- 639. DOI:

41. Xie Z. Y., Huete A., Ma X., Restrepo-Coupe N., Devadas R., Clarke K., Lewis M. (2016). Landsat and GRACE observations of arid wetland dynamics in a dryland river system under multidecadal hydroclimatic extremes. Journal of Hydrology, 543, pp. 818-831. DOI:

42. Zaitchik B. F., Rodell M., Reichle R. H. (2008). Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model: Results for the Mississippi River Basin. Journal of Hydrometeorology, 9(3), рp. 535-548. DOI: 10.1175/2007JHM951.1

43. Zhang Y. F., Yang Z. L. (2016). Estimating uncertainties in the newly developed multi-source land snow data assimilation system. Journal of Geophysical Research-Atmospheres, 121(14), pp. 8254-8268. DOI:

44. Zotov L., Frolova N., Grigoriev V., Kharlamov M. (2015). Application of the satellite system of the Earth’s gravity field measurement (GRACE) for the evaluation of water balance in river catchments. Moscow University Herald. Geography, (4), pp. 27-33. (in Russian with English abstract).

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