Nowadays, with a growing population and the increasing trend of recent droughts, scientific attention to the mentioned drought phenomenon is inevitable. In this study the Stream flow Drought Index (SDI) was used for analyzing the hydrological droughts over the last three decades in the northwest of Iran (Ardebil province). The periods of 3, 6, 9, and 12 months and also 5 and 10 years were selected for the spatiotemporal monitoring of the hydrological droughts. The temporal drought analysis showed that the most of drought events over the reference periods have occurred in the last 15 years. In other words, there was an approximately normal status in the most of stations in the first study period of 15 years. The most severe hydrological droughts occurred in the Poleh Almas and Poleh Soltani on the Balokhlo-Chai and Khiav-Chai gauging stations, respectively, at the 3- and 6-month scales in 2010. The results revealed that the most severe hydrological drought periods occurred in 2010.

Drought is a natural phenomenon that has a significant impact on human life, and examining its temporal and spatial changes can be effective in dealing with the effects of this phenomenon. The aim of this study is to investigate the meteorological drought trend using the index (SPI) and the Mann-Kendall test at the level of Lorestan province. Using the index (SPI), the precipitation data of 9 synoptic stations and 23 rain gauge stations in the statistical period (1377-1397) were analyzed at the province level. The results showed that, in general, the province faced drought in 1987 and 1978. The results of the Mann-Kendall test showed that the trend of changes in the drought index of Seleseh city was significant and incremental at the probability level of 95, and the rest of the cities were not significant. Also, considering the number of drought categories in different years for selected stations, the driest station, Kohdasht station and the wettest station, Noorabad station were introduced.

Spatial and temporal variations of contamination in groundwater resources, necessitate long-term monitoring (LTM) at a given site. In this study, several groundwater quality parameters (EC, SAR, TH, TDS, pH, K, Na+, Ca2+, Mg2+, SO42-, HCO3-, and Cl-) for 113 samples sites clustered based on the particle swarm optimization (PSO) algorithm to significantly decrease cost and save time in LTM. The optimization of the clustering process was carried out according to the Silhouette index. For verification and validation of the results, Geology, soil order, land use, hydrological network, and TDS maps were used. According to the results, the best number of clusters was 5. An acceptable agreement was obtained between land conditions and clusters represented by the PSO algorithm. Consequently, it can be inferred that the clustering of the groundwater quality using the PSO algorithm and the Silhouette index optimizer could 70% decrease the number of spatio-temporal sampling in LTM.

Iran, due to its geographical location, has low rainfall and is considered a dry land. As a result, different regions of the country grapple with drought. The presence of water management systems, such as aqueducts and reservoirs, in most parts of the country, along with a variety of methods for conserving water for irrigation, may contribute to this claim. Considering that drought is an inherent phenomenon in Iran's climate, people have invented and used numerous methods to combat it and store water. The aim of this study is to monitor and evaluate drought in Iran. In order to realize this goal, precipitation data from synoptic, rain gauge, and climatology stations were extracted over a 51-year period, from 1970 to 2020. The results obtained from examining drought occurrences in five ten-year periods reveal that, with the exception of the third decade (1991 to 2000), drought has prevailed in the majority of Iran's regions compared to other decades. On the other hand, in the recent decades leading to 2020, the intensity of drought occurrences, especially in the Middle Zagros, has intensified, which has consistently been among the regions with the highest rainfall in Iran after the Caspian region. This situation can cause concern in Iran, a country where its agricultural production hub is established along the Zagros mountain range. Moreover, the fluctuating behavior of Iran's droughts, with return periods of 2 to 5 years, has complicated the management strategies for these types of hazards. These conditions appear to have created numerous issues in many areas of Iran, particularly in the agricultural sector of the western provinces, due to the lack of conformity with these types of occurrences.

Gavkhuni Basin has a vital role in Iran's poetry, biomass, agriculture, industry and tourism, faced with drought problems. Clustering approach can be a management approach to reduce drought risk impacts which groups the members with regard to the division based on the Euclidean Distance of stations. In this research, the approach of determining the spatial-temporal distribution of drought clusters in watersheds is used to express variations based on precipitation precipitation index (SPI) parameters of stations, which depends on the probability of precipitation for any time scale. Since the maximum spatial distribution of the meteorological stations in the region and the maximum time period of the long-term and possible long-term statistical period were considered the same, the data of 26 stations from 12 years (2003 to 2014) was used as reference data. In this regard, the12 months SPI index was first calculated. Then, the 12-month SPI index, which ended in December, was used for cluster analysis of the SPI, and then 144 data were clustered into four groups. Further, zoning analysis was performed on data clusters. Then, the relationship between elevations as an effective landform factor in drought with SPI drought index cluster was investigated using correlation of variables. SPI correlation with mean height of each cluster stations was studied and the results were compared and analyzed. The results of the SPI drought fluctuation chart showed a very severe drought in 2008 and 2009 and 2010, and severe drought in 2010 and mild drought in 2003, 2005 and 2013. Also, 12-month SPI drought data showed a high and negative correlation with height data. Consequently, spatial-temporal monitoring of drought indicators clusters is recommended as a way to manage the impacts of drought risk.