Drought is considered as one of the undeniable climatic facts of Iran, and regardless of it, any forecasting and planning will fail. The analysis of drought and understanding its features can help planners to deal with the crises that occur. In the present study, Larestan, that is located in the Fars province, was selected as a case study, and to evaluate the characteristics of drought, precipitation data of nineteen stations in the period 1368 to 1392 were used. The purpose of using indicators SPI, CZI, ZSI and RDI was to identify the various features of drought. After data analysis, it was concluded that ZSI Shows the durability of drought’s periods longer than other indices. Also, SPI refers more deterioration of  droughts. At the monthly scale, SPI  Shows more severity than other indices, but at the annual scale, reaction of RDI is greater of other indices.

A great part of our country, and one third of the world's continents are arid and semi-arid, having problems to meet their water needs. Although different factors are responsible for this aridity, the arid regions mostly suffer from water shortage in relation to the potential evaporation. Therefore aridity is a permanent character of climatic reactions in these regions.Regardless of some factors, (e.g. distance from humidity source, orography effect, water upwelling etc) we learn that the main cause of the aridity on the larger world scale is the descending of air masses and its following adiabatic warming, and strong thermodynamic stability. The result of this is often a clear and cloudless sky, and consequently the reduction of Precipitation in the summer months. In spite of this complexity in the nature of the aridity, there have been many attempts to make a formula for touching aridity and drought. As a great part of our country is covered with arid and semi -arid areas, and usually suffers from severe drought, the choice and application of a method, that could lead to more accurate knowledge about the extent and the manner of spreading drought, can help the organizers to reduce the effects of this natural disaster.In this paper, we introduce some valid and important indices for aridity and drought, and we emphasize its application to the climatic condition in Iran.

ABSTRACT Today, climate change and its obvious negative effects on ecosystems have caused concern. This research seeks to test whether vegetation changes are sensitive to climate shocks and also how the ecosystem recovery process is through this index. In this regard, by using the GEE platform, Java coding, GIS and statistical analysis, vegetation and Palmer indices were calculated and based on time series climate data, vegetation and climate changes were presented. The results of Palmer's drought index show that during the statistical period (1985-2020) the study area is facing drought or is moving towards drought. Also, the results indicate the longest period of drought in the region from 2013 to 2020. Totaly from 420 evaluated months, the NDVI index is below the change threshold in 70 months. Among these, 31 months of the study period is below the acceptable threshold in green and non-reservoir seasons, which is ecologically worrying. The distribution of the vegetation index based on hexagons in 1985 and 2005 had a normal and almost normal distribution; But in 2020, the graph deviated from the normal state and skewed towards the vegetation cover index under stress or even thin covers. According to the analysis of the indicators, it is predicted that the Gorgan region is on the border of such ecological developments and the historical ecosystem of the region is moving towards new ecosystems or being in a new equilibrium state with climatic conditions and human disturbances Extended Abstract Introduction Today, climate change and its obvious negative effects on terrestrial ecosystems have caused great concern to humans. These changes are effective on vegetation performance, plant distribution patterns, and have economic and environmental consequences. Therefore, it is important to know the behavioral pattern of vegetation changes against climate changes. Reviewing the studies of scientists in the world shows many researchers have used the NDVI index to study temporal and spatial changes in vegetation and its relationship with the climatic index of precipitation in different parts of the world. Studies have shown that NDVI follows precipitation with different time scales. Surveys showed that there are very few studies on determining the threshold of changes in the vegetation cover index in the face of climate shocks. Determining these thresholds can provide a suitable solution for evaluating the state of the ecosystem, the consequences of climate shocks and the reversibility or disturbance in the ecosystem. This study was conducted with the aim of improving our understanding of the dynamics of vegetation in the forest city of Gorgan during 1985-2020 against climatic stresses.   Methodology The current research is a comparative and monitoring research and seeks to test whether changes in vegetation cover are sensitive to climate shocks and also how the ecosystem recovery process is through this index. To achieve the gole, first, NDVI index was selected among the optimal vegetation indices and its calculation process was done as a time series in the GEE system. In parallel with those climate shocks, the main elements including temperature, precipitation and storm were calculated during the historical process of 35 years and the average and standard deviation statistical indicators were calculated for them and the trend of changes in the thresholds was determined. The results of climate plots and climate changes show that in the years before 1985, 2005 and 2020, drastic changes have occurred in climatic elements and climatic factors. Therefore, these years can be considered as the periods when the climate shock happened.. Next, the region was divided into 436 hexagons and the NDVI index for each of the hexagons was calculated and modeled for the years 1985, 2005 and 2020 as selected years affected by climate shocks. In conclusion, to analyze the trend of changes in the time series of the vegetation index and compare the behavior of its changes with climatic indices, the Palmer index was calculated.   Results and discussion The results of climate change monitoring based on the Palmer index showed that during the statistical period the study area is facing drought in most years. The most severe climatic fluctuations and drought in the region were recorded in 2018 and in the months of October to December. The longest period of drought has also prevailed in the region from 2013 to 2020. During this period, rainfall, temperature and storm fluctuations have the most changes. The results of drought monitoring show that in 270 months, the region is facing climatic drought stress, 57 months of the study period, the region is facing severe and very severe drought stress. The results of the time series of the NDVI vegetation index showed that, out of the 420 evaluated months, 70 months of the year the NDVI index is below the change threshold, 31 of which are in the green and non-accumulating seasons, the seasons when the vegetation is expected to be at its maximum. Placing below the acceptable range means crossing the ecological thresholds and challenges the recovery and restoration of the ecosystem, also the ecological performance will be affected at this point. Based on the assessment of the Palmer index, from 2014 to 2019, the situation of the Palmer index is in the extreme drought range. Also, since 2015, i.e. with a one-year time delay, NDVI index has experienced the lower limit of the equilibrium threshold of vegetation cover. These conditions are also valid for the years 2008, 2009, 2002 and 1997. In general, it can be said that the vegetation cover index is dependent on climatic changes and fluctuations and shows high sensitivity to changes. The important point in this section is that in the years when the NDVI index changes are at the lower limit of the threshold, we witness the most climate shocks and temperature changes, the occurrence of severe storms and precipitation fluctuations. The distribution of the vegetation index based on hexagons in 1985 and 2005 have a normal distribution; but in 2020, the graph has deviated from the normal state and skewed towards the vegetation cover index under stress or even thin covers. The visual interpretation done on the vegetation cover index in 1985 confirms the condition of the vegetation cover in the southern and western limits of the region in a state with suitable dense and pasture vegetation and forest cover on the edges. However, in 2005 and 2020, this cover has been changed and mainly turned into agricultural land and poor rangeland. In such a way that in 2020, the situation of the region has revealed the critical state of vegetation. The vegetation cover index in the central areas of the city has also reached from a relatively favorable situation in 1985 to a critical situation with almost no dense and stress-free vegetation cover in 2020. The results of the present studies are consistent with the studies of Visentr Serrano et al. in 2013 and confirm the relationship between NDVI vegetation and climate change. In addition, the results of the studies are consistent with the studies of Alwesabi 2012, Xiai & Moody, 2005 and Yan et al. 2001. In such a way that the present study and the aforementioned studies all confirm the influence of the vegetation index on climate fluctuations and precipitation with a one-year time difference.       Conclusion In general, the threshold is defined as a border with different conditions. After crossing the thresholds, the stability and positioning of the NDVI in the equilibrium range is often difficult, and the ecosystem is constantly spending energy to restore itself or to position itself in a new stability state. The result of the mentioned disorders is the reduction of resilience and resistance in the region, which leads the ecosystem to alternative states or crossing the threshold or being in a new equilibrium state. The results showed that the areas where green vegetation is concentrated and denser are less affected by climatic stresses and show more resilience. However, the areas that have become spots and islands due to destruction in the urban areas are more affected by climatic stress and destruction and show less tolerance against the destruction factors. The results help managers to focus their management plans for the preservation and maintenance of urban green spaces as well as forest and pasture ecotones on the edge of the city by knowing the thresholds.   Funding There is no funding support.   Authors’ Contribution Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.   Conflict of Interest Authors declared no conflict of interest.   Acknowledgments  We are grateful to all the scientific consultants of this paper.

Iran is affected by subtropical high pressure in the arid belt of the world and its annual rainfall is less than one third of the world average rainfall. Low rainfall with inappropriate temporal and spatial distribution has caused droughts. The aim of this study was to assess the vulnerability of Guilan province to drought with fuzzy GAMA, SUM and CVI models and to identify appropriate measures to reduce potential damage. The research method was spatial and applied in terms of purpose. First, the components of Guilan Province Climate Vulnerability Index in both FUZZY and CVI models, resource components (R), meteorological (W), access (A), capacity (C), economic use and productivity (U), maintaining environmental integrity ( E), geographical features (G) were determined. The variables were matched with fuzzy membership functions. In the SUM model, the highest vulnerability was in the west, center and large areas of the east of the province, Rudsar city with an area of 78. 23%. In the GAMA overlap model, large parts of the west of Talesh city and Rasht city with an area of 31. 92% were observed in a very high vulnerability class. In the study of CVI components, the CVI index of the whole province was 44. 5%. The CVI index had the highest rank in the resource component (R) 56. 12% and the lowest rank in the 36. 94% component. In the CVI model, the highest vulnerability is in the whole city of Talesh with an area of 15. 57%. High vulnerability rate of 26. 84% was observed in Rasht, Soomehsara, Rudsar and Shaft counties and Astara and Rezvanshahr counties with an area of 20. 88% were observed in very low vulnerability class.

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.

The importance of drought monitoring in a near real-time manner makes the use of remote sensing systems indispensable. In this study, a comparison between SPI and EDI climatic indices (in two time scales of 1 and 3 months) with satellite indices of NDVI, VCI and DEV is made for Tehran province. For this, satellite images of AVHRR on NOAA satellite for 6 years (from 1996 to 2001) are prepared and processed. Furthermore, the simple linear regression and dummy variables regression are applied to correlate climatic and satellite indices. The selection of variables is based on examining all possible equations and the Step by Step method. Results of regression analysis for the study area showed a more significant correlation between NDVI and SPI (3 months), while using dummy variables. Also, the correlation between the indices in regions equipped with more meteorological stations was found to be higher.

Introduction Stability of soil structure is one of the most important indicators of land degradation sensitivity and soil quality. Also, soil salinization is among of the main causes of land degradation in arid and semi-arid regions and the critical factor limiting agricultural production. Soil salinity affects plant growth and in this case, the importance of soil is determined due to increasing population growth and the emergence of new needs for more food. Drought as a natural disaster and inevitable phenomenon has been seen in a wide range of countries, especially countries located in arid and dry regions of the world. Materials and Methods In order to investigate the role of drought in intensifying soil salinity in Kashan Plain, drought periods were studied by standardized precipitation index (SPI) in six time periods in the statistical period 2000 to 2017. The results indicated that the years 2000, 2008, 2015, and 2016 were the reference years with the maximum intensity of drought. Salinity changes in reference years were analyzed using the salinity index (SI) obtained from satellite images, ETM + sensors through ENVI software (version 7. 4). Then, the ground reality map of soil salinity was obtained by field sampling, laboratory studies, and interpolation in ArcGIS software (version 10. 4. 1). According to the root-mean-square error (RMSE) criterion, the inverse distance weighting (IDW) method was selected as the most suitable interpolation method in spatial mapping of drought intensity. Results and Discussion The results of the correlation analysis showed that there is a significant relationship between the actual and intermediate salinity values at the level of 1% with a correlation coefficient of 0. 968. This suggests that the obtained model is a good estimator for soil salinity prediction. The results also showed a significant correlation at the 1% level between drought and EC using the Spearman method. The results showed that increasing drought will increase the salinity amount, although this relationship was found inverse for 2016. Conclusion The characteristic arid zone has a variable climate,so that these climatic fluctuations have made it prone to high sensitivity. Over the past few years, reduced rainfall and increased temperature in the Kashan Region have been the main causes of soil salinity. Along with the occurrence of meteorological drought, over exploitation of groundwater and the entry of solutes through precipitation are intensified the soil salinity over the study area.

Drought occurs in all climatic zones including areas with low and high rainfall. It is related to amount of rainfall decrease in a long time period such as a season or year. Dryness is one of the permanent features of climatic zones with low rainfall, but the drought is a temporary disturbance. One of the areas severely affected by drought in recent years is Kerman Province. This fact reveals need to carry out extensive research in this area. In this study, the standardized precipitation index (SPI) was applied in order to the drought zoning in Kerman province. After collecting data from 59 stations including synoptic and rain-gauge in the province from 1974 to 2004 and removing incomplete statistics, the SPI index computed in scales 1, 3, 6, 9 and 12 months. Evaluation of different interpolation methods for drought zoning using Geographic Information System (GIS) showed that Kriging method is suitable for interpolation of the drought severity. Therefore, using this method and by applying GS + software, local values of SPI index used for drought periods monitoring were extended to the areal values. We have produced maps of intensity and the same value magnitude with determination a period of dry in stations in time scale. The results showed that have more sensitivity for drought accurence a portion of west souther and west earas of kerman province, located in baft, sirjan and rabor towns. Whatever time scale goes higher then, absolute related with dryness periods get more.

Drought assessment and monitoring using traditional methods rely on rainfall data, which are limited in arid lands and often is very difficult to obtain near real time and costly. In contrast, remote sensing technology is a method for monitoring of large-scale drought. In this research, drought condition was analyzed using drought indices such as TVDI and NDVI from MODIS sensor data for the Yazd-Ardakan plain, Iran. First, relationship between the drought indices with climatic elements were detected. Coefficient of correlation between TVDI and SPI_6 and SPI_12 were 0. 68 and 0. 71, respectively. Correlation between NDVI and SPI_6 and SPI_12 were 0. 49 and 0. 51, respectively. Point correlation between TVDI and SPI_6 in 2004 (as a normal year), 2007 (dry) and 2012 (wet year), were 0. 64, 0. 78 and 0. 67 and for the SPI_12 in the above-mentioned years were 0. 65, 0. 79 and 0. 69, respectively. In other word, efficiency of the TVDI in 2007 is better than the other two years. Correlation of NDVI and SPI_6 in 2004, 2007 and 2012, were 0. 41, 0. 50 and 0. 56, respectively. The correlation between NDVI and SPI_12 in 2004, 2007 and 2012, were 0. 52, 0. 57 and 0. 59, respectively. TVDI which takes into account thermal and reflective bands, and soil moisture, is more accurate than the NDVI, which considers only amount of vegetation of the study area. Results showed that the relationship between vegetation and temperature is negative, while, the relationship between vegetation and precipitation is positive. Using of TDVI can compensate defects of the NDVI and used for identifying and monitoring drought.

In order to evaluate the impacts of climatic factors during the periods of the occurrence of wet and dry years, using a model is one of the best solutions. In this paper, drought severity was determined by using Scalogram model based on 3 climatic factors (annual precipitation, number of rainy days and amount of potential evapotranspiration) for Zabol region over 16-years period (1991-2006). The results showed that the most severe drought had not always occured in a year with the least precipitation. This is due to the role of other climatic factors. It is concluded that the occurrence of the most severe drought and the wettest year has been in 2001 and 1992, respectively. In addition, potential evapotranspiration is the most important factor affecting on occurrence of drought in the study area.