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.