Gravity recovery and climate experiment (GRACE) and GRACE Follow-On (GRACE-FO) are Earth's gravity satellite missions with hydrological monitoring applications. However, caused by measuring instrumental problems, there are several temporal missing values in the dataset of the two missions where a long gap between the mission dataset also exists. Recent studies utilized different gap-filling methodologies to fill those data gaps. In this article, we employ a variety of singular spectrum analysis (SSA) algorithms as well as the least squares-harmonic estimation (LS-HE) approach for the data gap-filling. These methods are implemented on six hydrological basins, where the performance of the algorithms is validated for different artificial gap scenarios. Our results indicate that each hydrological basin has its special behaviour. LS-HE outperforms the other algorithms in half of the basins, whereas in the other half, SSA provides a better performance. This highlights the importance of different factors affecting the deterministic signals and stochastic characteristics of climatological time series. To fill the missing values of such time series, it is therefore required to investigate the time series behaviour on their time-invariant and time-varying characteristics before processing the series.

Drought is one of the most complex and threatening disasters, defined as a period of drier-than-normal conditions which results in water-related problems. In addition to climate variation, human activities can cause or intensify drought through groundwater overextraction, unsupervised expansion of agricultural lands, etc. One prime example of such drought has been observed in the Zayandehrud River basin in central Iran. We investigate the long-term (1986 to 2019) drought of the Zayandehrud River basin using meteorological, hydrological, and agricultural drought indices. The main focus of this research is to explore the impact of the irrigated area expansion in the upstream sub-basins on the agricultural drought of the downstream. To this end, different drought indices are employed over the whole basin and its sub-basins. The results indicate that the long-term precipitation index and snow reserves do not show a long-term trend during the study period, while the combined precipitation-evapotranspiration index and groundwater storage decline. The research concludes that the expansion of the agricultural lands in the river upstream, rising air temperature, and increasing population and industrial activities in the basin are most likely the driving forces to intensify the agricultural drought in the midstream and downstream parts of the basin.