Assessment of GRACE satellite data for estimating the groundwater level changes in Qazvin province

Document Type : Research Article


1 MSc. in Irrigation and Drainage, University of Guilan, Rasht, Iran

2 Assistant Professor, Department of Water Engineering, Imam Khomeini International University, Iran

3 Assistant Professor, Department of Water Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran


Given that Qazvin Province is ranked as the seventh dry place in the country, it is necessary  to manage vast water resources in this province. Water storage estimation methods have been developed over the years and observation of changes in the gravitational field by satellite GRACE is one of these methods. This satellite produces a series of water storage changes data with spatial resolution of 1 ° on a regional scale. This study aimed to evaluate data from GRACE satellites in Qazvin province to find a comprehensive solution for quick and easy access to water resources. To validate the GRACE satellite data, land surface model data (GLDAS) and wells data in the region were used. The results show that the GRACE satellites as a Gravity satellite just produced to estimate changes in Earth's water supply, give a good estimate of the changes in the ground water storage and groundwater level changes. Statistical analysis showed that RMSE =5.54, MAE = 4.16 and MBE = 1.5 the seasonal scale in millimetre between groundwater level data from the GRACE satellites and observation wells, and RMSE =2.92, MAE = 4.24 and MBE =0.184 month scale in centimetre between the data changes in land water storage from GRACE satellite and GLDAS model. Also, the correlation between changes in water storage data from the GRACE satellite and GLDAS model and groundwater level changes from GRACE satellite and observational data is significant at the 99% probability level. The results showed that GRACE satellite shows terrestrial water storage changes better than GLDAS model.


Main Subjects


    1. Moiwo JP, Yang Y, Tao F, Lu W, Han S. Water storage change in the Himalayas from the Gravity Recovery and Climate Experiment (GRACE) and an empirical climate model. Water Resources Research. 2011b; 47: W07521. DOI: 10.1029/2010WR010157
    2. Moiwo JP, Yang Y, Li H, Han S, Hu Y. Comparison of GRACEwith in situ hydrological measurement data shows storage depletion inHai River basin, Northern China. Water SA. 2009 ;35: 663–670
    3. Sean Swenson, Pat J.-F. Yeh, John Wahr, and James Famiglietti. A comparison of terrestrial water storage variations from GRACE with in situ measurements from Illinois".GEOPHYSICAL RESEARCH LETTERS.2006; VOL. 33, L16401, doi: 10.1029/2006GL026962.
    4. Wahr J, Swenson SC, Zlotnicki V, Velicogna I. 2004. Time-variable gravity from GRACE: first results. Geophysical Research Letters 31:L11501. DOI: 10.1029/2004GL019779
    5. Rodell M, Houser P. R, Jambor U, Gottschalck J, Mitchell K,Meng C,et al. The Global Land Data Assimilation System. Bulletin of the American Meteorological Society.2004;85(3): 381-394.
    6. Chen JL, Wilson CR, Tapley BD, Yang ZL, Niu GY. drought event in the Amazon River basin as measured by GRACE and estimated by climate models. Journal of Geophysical Research. 2009; 114: B05404. DOI: 10.1029/2008JB006056
    7. Lemoine J-M, Bruinsma S, Loyer S, Biancale R, Marty J-C, Perosanz F, Balmino G. Temporal gravity field models inferred from GRACE data. Advances in Space Research.2007; 39: 1620–1629.
    8. Zaitchik BF, Rodell M, Reichle RH. Assimilation of GRACE terrestrial water storage data into a land surface model: results for the Mississippi river basin. Journal of Hydrometeorology.2008; 9: 535–548
    9. Ramillien G, Famiglietti JS, Wahr J. Detection of continental hydrology and glaciology signals from GRACE: a review. Surveys in Geophysics. 2008;29: 361–374. DOI: 10.1007/s10712-008-9048-9.

    10. Longuevergne L, Scanlon BR, Wilson CR. GRACE hydrological estimates for small basins: evaluating processing approaches on the High Plains Aquifer, USA. Water Resources Research.2010;46: W11517.DOI: 10.1029/2009WR008564.

    11. Moiwo JP, Yang Y, Tao F, Lu W. Analysis of satellite-based and in situ hydro-climatic data depicts water storage depletion in North China Region. Hydrological Processes.2012; DOI: 10.1002/hyp.9276

    12. Ferreira, V., Z. Gong, X. He, Y. Zhang. Estimating Total Discharge in the Yangtze River Basin Using Satellite-Based Observations." Remote Sensing.2013; 5(7): 3415-3430.

    13. Lee S, Seo J, Lee SK. Validation of Terrestrial Water Storage Change Estimates Using Hydrologic Simulation. Journal of Water Resources and Ocean Science. 2014;3( 1): 5-9.

    1. 14.  Chen Q, Shen Y, Chen W, Zhang X, Hsu H. An improved GRACE monthly gravity field solution by modeling the non-conservative acceleration and attitude observation errors. Springer-Verlag Berlin Heidelberg.2016; 90:503–523.

    15. Farokhnia A,Morid S. Assessmentof GRACE and GLDAS capabilities forestimationofwater. Iran-Water Resources Research.2014;10(1):52-61. (In Persian)

    16. Sharifi M.A, Akhoondzadeh M, Shahrisvand M, Sanatgar M.Drought monitoring in Iran by GRACE satellite data and GLDAS hydrologic model.Proceedings of the Sixteenth Conference of Iran Geophysics.2014;35-39.(In Persian)

    17. Ashrafzade A, Judaki GH, SHarifi M. Iran's groundwater resources assessment using data from the GRACE satellite gravity survey. Journal of Research Science and Technology Mapping.2015;5(4):73-84. (In Persian)

    18. Sharifi1M.A, NajafiAlamdari, Mokhtari,E.A comparison of Gaussian and Wiener filters to suppress GRACE data errors.Journal of Geophysics of IRAN. 2011;5(4):57-73. (In Persian)

    19. Broqhani M, Moradi H.R, Zangane M.A. Zoning and determine the best indicator of drought in Khorasan Razavi. Geographical Studies of Arid Zones.2015; 5(16):70-84. (In Persian)

    20. SokutiOskooi, R. Mahdian, M. MahmoudI, Sh. Compared the performance of some geostatistical methods to predict the spatial distribution of soil salinity, Urmia plain case study. Journal of Research and Construction. 2007; No. 74. (In Persian)

    21. Gao, Y., Long, D., Li, Z. Estimation of daily evapotranspiration from remotely sensed data under complex terrain over the upper Chao river basin in north China. International Journal of Remote Sensing.2008; 29(11):3295-3315.

Volume 4, Issue 2
June 2017
Pages 463-476
  • Receive Date: 07 December 2016
  • Revise Date: 11 February 2017
  • Accept Date: 15 March 2017
  • First Publish Date: 22 June 2017
  • Publish Date: 22 June 2017