3.2 GLDAS data sets
It gives soil moisture data. This data are downloaded from Goddard Earth Science Data and Information Services Center (GES DISC). For, the present study, GLDAS_NOAH 2.1 is used to estimate soil dampness from the surface up to 200cm depth. GRACE and GLDAS data should be in same spatial (10) and temporal (month) scale. The obtained GLDAS data set denotes four data sets of soil moisture as 0-10cm, 10-40cm, 40-100cm and 100-200cm. The sum of these data sets gives total soil moisture of specific area and month. To compare any data with GRACE data sets, the data to be consistent with mean time baseline which is used for TWS data sets. To obtain soil moisture change of particular month, the average soil moisture of January 2004 to December 2009 is deducted from soil moisture of that particular month (Y.B. Katpatal et al. 2017).
ΔSM = SM - SMavg (2004-2009) (1)
Here,
ΔSM = soil moisture variations at time
SM = soil moisture at time
SMavg (2004-2009) = avg. soil moisture (Jan 2004 to Dec 2009)
All the data sets which are mentioned above are processed using Panoply 4.10.3 software. Finally, using GRACE dependent evaluations of terrestrial water storing (TWS) variations and GLDAS based soil moisture variations, the groundwater storing (GW) variations were estimated as per (Rodell et al. 2007, 2009; Chinnasamy et al. 2013)
∆GWSGRACE = ∆TWS - ∆SM (2)
Here,
∆GWSGRACE – variations in groundwater storing obtained from GRACE
∆TWS – variations in terrestrial water storing
∆SM – variations in soil moisture content
GRACE data as a NC (NetCDF) file and GLDAS data as NC4 file for the period from January 2004 to January 2017 is downloaded. To read and understand these data set files we use the panoply 4.10.3 software. The TWS variations of January 2011, June 2011, May 2012, October 2012, March 2013, August 2013, September 2013, February 2014, July 2014, December 2014, June 2015, October 2015, November 2015, April 2016, September 2016 and October 2016 are missed in the GRACE data. Then analysis of the remaining 95 months TWS data is done.