4 DISCUSSION
4.1 Literature comparison of the main attribution
results
The main attribution of changes in AET and TWSA in the EIB were
semi-quantified based on the water balance in the closed basin. The main
contribution to the decrease in the TWSA was the increase in the AET.
The incremental AET consumption of other water sources and the
precipitation increase contributed approximately 70% and 30% to the
increased AET, respectively. Although few studies have focused on the
entire EIB, there have been many studies focusing on the attribution to
changes in TWSA at the basin scale; these results were compared with the
results from this study. For example, the Caspian Sea level has been
gradually decreasing over the past 20 y. Some studies have attributed
this decrease to meteorological factors (van Dijk, Renzullo, Wada, &
Tregoning, 2014), while others suggest that evaporation from the sea is
the main impact factor (Chen, et al., 2017). Other studies have
suggested that it is these two factors combined with agricultural
irrigation diversions (Rodell et al., 2018). According to the water
balance of the closed basins, this study demonstrates that the main
factor causing the decreasing sea level was the increase in AET. The
increase mainly includes an increase in water surface evaporation and
agricultural irrigation diversion. For example, the Volga River delivers
roughly 80% of its runoff to the Caspian Sea; however, there are 11
dams located in the basin that ensures a steady water supply for crop
irrigation (Avakyan, 1998; Rodell et al., 2018). There was a negligible
correlation between crop production and precipitation, suggesting that
irrigation effectively mitigates the impact of drought. Based on the
long-term observation data from 1961 to 2020, there was a clear dry
period over the past 20 y (Figure 6). Therefore, the runoff into the
Caspian Sea has decreased due to the inevitable increase in agricultural
irrigation diversion throughout this dry period. In addition, the
reservoir capacity of dams in the CSB exceeds 75% of the total inflow,
and the total capacity of reservoirs is 223 km3; these
dams mostly occur in the Volga River basin (Akbari et al., 2020).
Although precipitation in the headwaters of the Volga River is
increasing, the impact of increased precipitation on runoff into the sea
may be weakened as a result of water storage regulation of reservoirs
during the dry seasons. Therefore, the precipitation increase in the
headwaters has a limited impact on the Caspian Sea level.
The extent to which the increase in AET has contributed to the TWSA
decline in the ASB from 2002 to 2020 was greater than the decreasing
precipitation; this is consistent with the conclusions of previous
studies (Yang et al., 2020). The increase in the AET consumption of
other water sources contributed >90% to the increase in
AET, while the precipitation increase contributed <10%. The
increase in AET consumption of other water sources largely involves the
increase in water surface evaporation caused by higher evaporation rates
and the increase in AET from irrigation diversion. Although the impact
of agricultural irrigation diversion on the water storage of the basin
has been gradually weakening post-2005 (Wang et al., 2020), agricultural
irrigation diversion remains the most important water resource problem
in this region. There is a still a need to improve the irrigation
efficiency, crop use efficiency, and water resource management in this
region. The precipitation decrease was the main impact factor driving
the decrease of the TWSA in the IIRB; this is consistent with previous
studies (Khaki et al., 2018).
The significant increasing trend in the TWSA for the QB and QPB was
consistent with previous studies (Bibi et al., 2019; Meng et al., 2019;
Liu et al., 2019); however, the main causes attributed to this trend
differ from those identified in previous studies. The increasing TWSA in
the QB is mainly caused by the precipitation increase, which contributes
>90 % to the increase in AET. In the QPB, the increasing
TWSA has largely been attributed to the decrease in AET.
Similar to the ASB results, the increase in AET was also the main cause
for the decrease in the TWSA for the TaRB; this differs from the results
of previous studies (Yang et al., 2017; Xu et al., 2019). The extent to
which the increase in AET consumption of other water sources contributed
to the increasing AET (>90%) was much higher than that of
precipitation (<10%). The increase in the AET consumption of
other water sources was mainly due to the elevated consumption of water
resources by human activities and the increase in melt water from
glacier retreat.
There were non-significant decreasing trends in the TWSA of the BLB and
ISB for 2002–2020; this is contrary to the rising water levels in
Balkhash Lake and Issyk-Kul Lake reported in previous studies
(Alifujiang et al., 2017; Duan et al., 2020) and may be due to the
differences in the study period. These two study periods for the
previous works ended in 2012 and 2013, respectively, while this study
period ended in 2020. The precipitation decrease and the increase in the
AET consumption of other water sources from elevated evaporation rates
accounted for approximately half of the AET changes in the BLB and ISB.
Based on the results of five GRACE TWSA products, there was a
significant decreasing trend in the TWSA for the GHC for 2002–2020.
This differed from the results obtained at other time periods when only
one product was used (Cao et al., 2018; Wang et al., 2020). Similar to
the EIB and most of its closed basins, the decreasing TWSA of the GHC
was mainly due to the increase in AET; >60% of the
precipitation increase contributed to the AET increase.
4.2 GRACE TWSA products and
uncertainties
It was difficult to determine which product was more suitable for the
EIB because of the lack of observational data for validation. However,
the area of the Caspian Sea is sufficiently large and thus, may be
considered a typical region to evaluate TWSA products. Chen et al.
(2017) found that the observed level of the Caspian Sea decreased by
-67.2 cm/10a for 1996–2015. This was more consistent with the two
mascon products (JPL-v2 and GFSC-v1), compared to the three spherical
harmonic coefficients products (CSR-v3, GFZ-v3, and JPL-v3). This was
because the TWSA of the Caspian Sea from the two mascon products
decreased by >-60 cm/10a for 2002–2020, as consistent with
the observed decrease. The TWSA of the three other products was
<-33 cm/10a, which is much lower than the observed value; this
indicates that the mascon products in the Caspian Sea region outperforms
the spherical harmonic coefficients products. Some studies have also
highlighted the many advantages of the mascon products for hydrologic
studies (Scanlon et al., 2016; Rodell et al., 2018). Overall, the five
TWSA products showed high consistency in most other regions of the EIB.
The uncertainties associated with the AET simulation were mainly due to
uncertainties in the input data and during simulation processes. As the
input precipitation and TWSA data were grid data, the actual basin
boundary did not coincide with the grid boundary. In this study, the
area weighting of the basin in the boundary grids was used to reduce the
uncertainty caused by the lack of alignment with the two boundaries.
Many studies have shown that GPM precipitation products have high
accuracy at regional scales
(Tang,
Ma,
Long,
Zhong,
&
Hong,
2016;
Le,
Lakshmi,
Bolten,
&
Bui,
2020;
Islam,
Yu, &
Cartwright,
2020); this was also the case in this study, in which the GPM
precipitation products were highly consistent with the station
observations in the EIB. Although the five TWSA products were generally
highly consistent in the EIB, there were still some differences (e.g.,
Figures 8(c) and 8(d)). This study used the mean value series of five
TWSA products to simulate the monthly AET series, causing uncertainties
in the simulated AET. In addition, we also compared the median value
series of the five products, finding marginal differences between the
mean and median series. Monthly AET series simulated by the two series
were also highly consistent. The accuracy of GRACE TWSA data directly
determined the accuracy of the related applications. As such, further
research on GRACE TWSA inversion is required for hydrology and water
resource applications.
In the simulation of monthly AET, ΔS represents the change in the water
storage over a month (i.e., the difference between the water storage at
the end and beginning of the month). However, the GRACE TWSA data
represents the mean water storage in the month. In this study, the
difference between the TWSA of the previous month and the next month was
used to represent the ΔS in the basin; this may also have caused
uncertainties. This study simulated the monthly AET series for a closed
basin, in which the runoff process within the basin was ignored;
however, for a finer temporal scale or an exorheic basin, the runoff
process within the basin must be considered.