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Precipitation is an important factor in the management of a variety of agricultural and industrial projects. This study investigated the temporal-spatial change of inter-annual precipitation of Iran from 1977 to 2007 by using the APHRODITE precipitation database. Statistical methods were applied, such as spatial auto-correlation, Global Moran's index, Local Moran's I index, and hotspots to acquire the variations in precipitation. The highest spatial anomalies belong to September (75.26) and October (45.02), based on the Dispersion index. Also, the size of the largest cluster of Iran's precipitation clusters is developed during winter, cited by the index's outputs, which indicates the relative regularity of Iran's precipitation. The results of the spatial statistics showed that inter-annual precipitation changes in Iran have an upward cluster model. The results of the Global Moran statistics showed that September, with the lowest number (0.712114), has the highest spatial precipitation anomalies throughout the year in Iran. Meanwhile, precipitation has a positive spatial autocorrelation on the Caspian Sea shores and western and south-western parts of the country (mainly Zagros highlands) and a negative spatial autocorrelation in parts of the central and south-eastern areas based on the Local Moran index and hotspots. HIGHLIGHTS This is the first research into this subject in terms of methodology in Iran.; The method of geo statistics can be applied in other regions in the Middle East.; This paper investigates rainfall changes during the last half-century.; This research can contribute to the knowledge of climate in this part of the world.; This research also can provide information on rainfall and water as a major problem in arid regions.

Atmospheric humidity has an important role in the energy balance of the planet Earth, and it is effective in explaining climate change and consequently global warming, which has been a major topic of discussion among scientists in recent decades. Therefore, in this study, the maximum and minimum annual and seasonal trends of the relative humidity of 41 synoptic stations in the country during the statistical period of 1960–2019 were evaluated. Three statistical tests were used to analyze the data trend: the Mann–Kendall statistical test, Sen's slope estimator, and linear regression. In the study area, the maximum and minimum annual humidity trends were positive for 83.26% and negative for 17.73% of the stations, respectively. The highest increase in maximum and minimum humidity values, respectively, includes Chabahar in Southeast and Dezful in Southwest stations with a rate of + 2.55 and + 2.10 °C per decade. At the seasonal scale, the highest decrease in maximum and minimum humidity was identified in the summer at Tabas station in the central part of Iran. The highest number of stations with a decreasing or negative trend in the seasonal time series of maximum and minimum humidity occurred in winter with 37 stations. In contrast, most stations had a significant increasing or positive trend in winter and fall. Overall, the results showed that although the rate of decreasing trend of humidity for the study period was higher than the rate of an increasing trend of humidity, there was a similar decreasing trend in the studied variables.

Mass displacement of materials such as landslide is considered among problematic phenomena in Baqi Basin located at southern slopes of Binaloud, Iran; since, it destroys agricultural lands and pastures and also increases deposits at the basin exit. Therefore, it is necessary to identify areas which are sensitive to landslide and estimate the significant volume. In the present study, in order to estimate the volume of landslide, information about depth and area of slides was collected; then, considering regression assumptions, a power regression model was given which was compared with 17 suggested models in various regions in different countries. The results showed that values of estimated mass obtained from the suggested model were consistent with observed data (P value= 0.000 and R = 0.692) and some of the existing relations which implies on efficiency of the suggested model. Also, relations that were created in small-area landslides were more suitable rather than the ones created in large-area landslides for using in Baqi Basin. According to the suggested relation, average depth value of landslides was estimated 3.314 meters in Baqi Basin which was close to the observed value, 4.609 m.