خشکسالی

Groundwater is the largest source of water in semi-arid regions. It is therefore very important to develop and exploit underground water resources in order to meet these needs. Rainfall is the main source of nutrients for many aquifers. Changes in rainfall and groundwater level depth are closely related.It is more difficult to quantify groundwater availability and the long-term effects of climate change on groundwater than surface water. Although groundwater resources are more resilient than surface water, they are increasingly vulnerable to overexploitation, drought, pollution and lack of permanent rainfall, leading to reduced quality and availability. The decrease in the quality and storage capacity of aquifers as a result of extractıon more than the available surplus is due to the development of urban areas, the use of water-based industries and an increase in the area under cultivation of agricultural products, which jeopardises underground water sources. Although human factors have a strong influence on groundwater, the natural hydrological cycle plays a key role in regulating the aquifer situation. In arid and semi-arid countries and regions of the world where surface water resources are relatively scarce, groundwater is often the most important or even the only source of water for regional food security, drinking water, economic development and environmental conservation.Quantitative information about groundwater resources related to wells, springs, and ghanat over 17 years was provided by relevant organizations, including the Iranian Water Resources Research Organization (Tamab) and the Yazd Regional Water Organization, as well as previous research. For a more detailed investigation, the level and depth maps of underground water were drawn for a five-year period based on the available information. The zoning map of five-year underground water changes was prepared in the Arc GIS software environment to check the amount of water level drop in the observation wells. This research considered the distribution of wells, springs, and ghanat in the region and the trend of changes in their number, discharge, and annual consumption in different parts. There are 25, 122, 0, and 11 underground water sources in the region, including semi-deep wells, deep wells, springs, and ghanat. It is worth mentioning that the statistics of the selected wells in each plain were used in the calculations and drawing of the underground water maps, which have the most complete statistics during the selected period, so the number of wells mentioned in each plain is not necessarily the same as the number of wells in the piezometric network, and the length of the statistical period used was also not necessarily the entire statistical period.According to the results, the maximum depth of underground water in the Bahadran and Shams aquifers in 2018 was 68 and 47.7 m, respectively, which reached the maximum value in the northern areas of the Bahadran and southern Shams aquifers and toward the southern areas of the Bahadran aquifer and the eastern parts. The water depth in the west of the Shams aquifer has decreased; therefore, the minimum depth of underground water in both aquifers is approximately 11.8 m. The highest level of underground water in the aquifers of the Bahadran area in 2018 was approximately 1538.91 m in the southwestern and western areas of the aquifers. Thus, in the eastern part of the Bahadran aquifer, it reached 1447.3 m and in the southern part of the Shams aquifer, it reached 1190 m this year. The level of underground water in 2013 and 2008 was higher than that in 2018, but it did not change significantly. The drop in underground water level from 2008 to 2013 and from 2013 to 2018 was approximately 13.14 and 6.68 m, respectively. Examining the changes in the underground water level during the statistical period shows that the underground water level generally has a downward trend.In this study, was investigated the level and depth of underground water sources in the Bahadran watershed in Yazd province. The results indicate an alarming drop in the underground water table. The spatial distribution of underground water resource extraction differed throughout the watershed, so some areas experienced severe decrease in the water level. In addition, due to the use of these resources, the time distribution of water level reduction may also be different in the seasons. In the absence of surface water sources due to a decrease in adequate rainfall and resulting droughts, the majority of underground water sources are extractıon for various purposes, such as increasing the area of agricultural cultivation. This amount of underground water extraction is carried out through other water wells. Therefore, it is necessary to carry out comprehensive studies to investigate the relationship between the extent of vegetation in the area and the amount of water extractıon from underground aquifers using satellite images. In addition, it is suggested to evaluate the amount of underground water resources extractıon and charge in all watersheds of the country. The results of this study provide politicians and managers with information on changes in underground water resources in aquifers, which can be used for optimal management.

In recent years, rural areas in Iran have been neglected in terms of development, with a focus on agriculture as the only means of progress. This has led to a lack of understanding among visitors about what rural areas offer as tourist destinations. The absence of a strong tourism brand for these destinations hinders potential tourists from forming a connection and incentive to visit. Due to the lack of investment and development in rural tourism services and facilities in Isfahan province, this study aims to prioritize key factors in branding rural destinations in the region. The main research question focuses on identifying the most effective variables in the slow tourism brand model for rural destinations in Isfahan province.

This study is practical in purpose and uses a descriptive-analytical method. The statistical population consists of tourists from 19 selected villages in Isfahan province. A sample size of 384 households was selected using a systematic random method. Data was collected through questionnaires, interviews, and observations.

Analysis of responses from tourists indicates that the slow tourism product in Isfahan province falls below satisfactory levels in various dimensions, including historical-cultural components, natural resources, leisure, hospitality, environment, accessibility, acceptance, services, and value for money. The decision-making level component shows a satisfactory level, while other components of the slow tourism process do not meet desired standards.

To enhance the tourism brand of rural destinations in Isfahan province, destination management organizations and planners must understand the tourism potential of these areas and prioritize key factors in branding. Strategic planning, introducing new forms of tourism, organizing festivals, and utilizing innovative advertising methods are essential for the development of slow tourism in rural areas. Success in establishing a slow tourism brand depends on effective interaction between key factors and careful consideration of future prospects.

As one of the greatest natural disasters faced by mankind since time immemorial, drought can be defined as a long period of reduced precipitation (a season or a year, for instance) occurring in almost all climate zones, including areas with high and low precipitation rates. Moreover, drought is a globally intensifying phenomenon, with no region or country in the world remaining safe from its consequences. On the other hand, the extent, frequency, intensity, and duration of drought are increasing in many parts of the world due to climate change. In addition, the phenomenon influences a diverse range of biophysical resources in catchment areas, including the discharge and sedimentation of rivers. Therefore, awareness of the drought status, prediction of drought, and zoning of its severity can significantly reduce the risk of its potential damage. 

Covering an area of ​​3516 km2, Behbahan is located in the southeast of Khuzestan province between 50˚ to 50˚ 21´ east longitude and 30˚ 30´ to ˚31 north latitude. Various indicators have so far been developed for monitoring drought, each of which considers one or more parameters contributing to drought. As a widely applied drought index worldwide, The Standardized Precipitation Index (SPI) time series can be used to describe the intensity of historical and current drought events at a site and to estimate the potential prospective magnitude of drought.Auto-correlated integrated ARIMA model is frequently used in analyzing time series. The model was first proposed by Box and Jenkins when studying time series, inspiring many related models that have since been developed and applied in various branches of geosciences. To investigate and predict drought in Behbahan City, this study sought to model annual SPI time series, six-month SPI, and nine-month SPI using the ARIMA model. 

The results indicated that the ARIMA (5,0,11) was the best choice for modeling annual drought index time series in the validation stage, with its errors being R2=0.64 and RMSE=0.81 MAE=0.66 and MAPE=213.27 errors. The ARIMA (2,0,5) was also found to be the best model for modeling the six-month SPI drought index time series, where the R2 value of the model was equal to 0.50 (greater than that of other models), and its RMSE, MAE, and MAPE errors were reports as 0.84, 0.64 and 100.31, respectively (less than those of other models). Moreover, due to the non-normality of the residuals of the selected models, a suitable model was not found for modeling the nine-month SPI time series. Therefore, other methods such as wavelet analysis are recommended to be used in this regard. Discussion and

As a complex and often underestimated phenomenon, drought strongly influences different aspects of human life. Therefore, early prediction of drought plays a crucial role in strategic planning and management of water resources. In this regard, time series models are considered a suitable tool for predicting climatic events. This study used the time series of the SPI index to model drought in Behbahan City at annual, six-month, and nine-month scales, seeking to identify appropriate models in this regard. It appears that managers and relevant decision-makers should take similar studies into account to access a clear analysis of the region and develop optimal plans for the management of water resources. This is especially important in Iran, where a large area of the country is characterized by arid and semi-arid climates. Considering that the phenomenon of drought can be predicted and managed, it is necessary to implement basic measures to reduce the adverse effects of drought in the coming years.

The main objective of this study is to assess and analyze the performance of the existing operation system under various operation scenarios and to examine the water and energy productivity in the agricultural units.

In the first step, the surface water distribution was simulated using the existing operation system under different operation scenarios. Then, spatial evaluation of surface water distribution and the calculation of groundwater extraction in 459 agricultural units were carried out. Finally, the performance of the surface water distribution process was evaluated based on the localized indicators.

The results showed that under normal operation conditions, only 43 agricultural units (9% of the network area) had surface water productivity in the good range. In contrast, 436 agricultural units (94% of the network area) had low energy productivity. Furthermore, the carbon production index indicated higher emissions in 292 agricultural units out of the total 459 units.

The findings of the study revealed that, with increased water scarcity in the second operation scenario, the situation deteriorated significantly in all indicators. These results highlight the urgent need to improve and enhance the efficiency of the operation system and alternative methods of surface water distribution within these units.

The frequency and severity of droughts are increasing due to climate changes and human activities, and they create significant risks for surface water, especially in arid and semi-arid regions. In this research, the capability of satellite data of TM sensor of Landsat 5 satellite and OLI and TIRS sensors of Landsat 8 satellite in drought monitoring of water resources of Miankale wetland was evaluated.

In this study, images from the TM sensor of Landsat 5 and the OLI and TIRS sensors of Landsat 8 were prepared for the period 1990 to 2023. Images were taken for both the wet and dry seasons to depict the variability of surface water during the seasons. May was taken for the wet season and July data was used for the dry month. The above images should be free of cloud cover. These images were downloaded from the US Geological Survey. To investigate the drought trend, multi-spectral indices of Normalized Difference of Vegetation (NDVI), Normalized Difference of Water index (NDWI), Modified Normalized Difference of Water Index (MNDWI) and Land Surface Water Index (LSWI) were calculated and the most appropriate method. It was identified for surface water detection and drought monitoring. For this purpose, the correlation relations between each of the indices with the earth surface temperature index were estimated and based on this, the regression equation was calculated and the values of drought in five categories very severe, severe, moderate, low and very low were calculated and the corresponding map was drawn.

According to the research findings, wider areas have been exposed to higher temperatures. From 1990 to 2023, areas with temperatures below 19 degrees Celsius have decreased from 645 square kilometers in 1990 to 296 square kilometers in 2023, while areas with temperatures above 29 degrees Celsius have increased from 2 square kilometers in 1990 to 320 square kilometers in 2023, mostly in the western part of the wetland and in areas that have been observed to have dried up. The reason for this is the drying of a large part of the western part of the wetland during this period. The above process has affected the vegetation of the region, and due to the drying of the western part, the widest area in this region has faced severe drought. In 1990, about 243.3 square kilometers of the region faced severe drought, which increased to 280.7 square kilometers in 2023. Of course, a slight increase was observed in this area. Significant changes have been seen in the average area, with the average aridity increasing from 52.2 km2 in 1990 to 254.1 km2, a fourfold increase.

The results showed that the MNDWI index had the highest correlation with the LST index in the years 1990 and 2023, so that the correlation values for these years are -0.83 and -0.88, respectively. This index was used to estimate drought. Based on this, it was observed that the amount of average drought has expanded the most and reached from 52.2 square kilometers to 254.1 square kilometers, which indicates the slow movement of the region towards severe drought. This incident caused the wetland area to decrease from 511 square kilometers in 1990 to 351 square kilometers in 2023.

In recent years, our country has experienced an increase in the frequency and severity of natural hazards such as floods, droughts, and pests. These changes can be attributed to shifts in climate variables. Due to its influential role in other natural hazards such as drought, climate can significantly impact the economy and people's lives. This is particularly evident in the agricultural, animal husbandry, and industrial sectors, where it can cause damage and destruction in various regions. Drought is one of the biggest climatic challenges that our country has been facing in recent years. When a drought occurs, it initially manifests as a meteorological drought. If the drought persists, it can lead to other types of droughts, including hydrogeological, agricultural, and economic droughts. Each of these droughts, as well as their cumulative impact, affects various aspects of the ecosystem within a watershed. Climatic changes cause many problems due to their impact on the temporal and spatial distribution of precipitation in various regions. Due to its gradual process and slow speed, this phenomenon has been operating for a relatively longer period. Its effects may be revealed after a few years and with a longer delay than other risks. This phenomenon has more tangible effects in rural areas because rural communities are more vulnerable. Therefore, understanding this phenomenon and analyzing and evaluating its impact on ecosystems within a watershed is crucial for effective planning and decision-making. This knowledge is necessary for the implementation of appropriate adaptation strategies.

To carry out this research, the required climatic data were first collected from the Meteorology and Regional Water Department of Mazandaran Province. The SPI (Standardized Precipitation Index) index was also used to evaluate meteorological drought. Additionally, to examine the trend of changes in flow rate, the data from existing hydrometric stations in the region, which have more comprehensive data, were utilized. Lars-WG software was used to project future climate (2023-2050) conditions under two climate scenarios: an optimistic scenario (RCP2.6) and a pessimistic scenario (RCP8.5). After preparing the current and future data, the DrinC software was used to determine drought thresholds based on the standard table for the SPI. In this research, the IHACRES hydrological model was also utilized to forecast future discharge. To achieve this objective, the future precipitation and temperature data obtained from the previous stage were utilized, along with the observed discharge data (1990-2020), to project the trend of discharge in the future (2022-2040). Subsequently, the hydrological drought of the Tajan Watershed was calculated at the outlet station (Kordkhil) using the SDI (Streamflow Drought Index) in the DrinC software. After analyzing the stream flow data and using the standard table associated with the SDI, the thresholds for hydrological drought were determined.

The results of this study showed that, based on the SPI standard table, the degree of drought in the area under investigation has fluctuated between -3.3 (indicating very severe drought) and 2.4 (indicating extremely humid conditions) in recent years. Also, the future climate was projected for a period of approximately 27 years (2023-2050) under the influence of two optimistic scenarios (RCP2.6) and one pessimistic scenario (RCP8.5) at three selected stations (Kordkhil, Soleiman Tange, Rig Cheshme). The results of the climate drought conditions and the index values for the projected period (2023-2050) at Soleiman Tange station, in 12-month steps showed that there is a possibility of a severe climate drought occurring in this region during the water year 2049-2050. Also, the results show that there is no significant difference in the future drought index between the two scenarios. The results of the climate drought situation at Rig Cheshme station indicate a high likelihood of a severe climate drought in the region during the water year 2029-2030. Additionally, the results of the climate drought condition at Kordakhil station show that the condition at Kordakhil station differs somewhat from the other two stations, which are located at higher altitudes. This difference is likely due to the proximity of this station to the Caspian Sea, as the climate in that region is influenced by the coastal humidity. It can also be expected that there will be a severe drought in the water year 2032-2033 in this region. The results of the IHACRES model showed that the comparison chart of the simulated discharge and the observed discharge is in good agreement. Additionally, the error coefficient values obtained during the two stages of evaluation and recalibration were 0.48 and 0.53, respectively. These values indicate the model's acceptable ability to simulate future discharge. The results indicate that the discharge rate of the Watershed is unlikely to undergo significant changes in the future as a result of climate change. The probable cause for this is the occurrence of intense rainfall events, which lead to flooding and subsequent increases in river discharge. Considering that these results only show the effect of climate change on discharge, there is a possibility that other factors, such as land use changes, may also contribute to changes in the amount of discharge.

Conclusion :

The results of this analysis indicate that in both climate scenarios, there is a possibility of experiencing severe droughts in some years in the future. However, it is also possible for the climate to be very wet in certain years. These changes in the state of drought over approximately 30 years indicate climate fluctuations, which are one of the signs of climate change in a region. Therefore, based on the obtained results, it cannot be concluded that we will experience either a completely dry or completely wet state in the next 30 years. Thus, it is necessary to employ adaptation strategies to mitigate the impacts of drought during certain years. The hydrological drought situation of the Tajan River in the next 20 years (2020-2040) was evaluated using both optimistic and pessimistic scenarios. The drought situation in this river has also exhibited fluctuations, with a decreasing trend of flow in some years and an increasing trend in others. These fluctuations also indicate another effect of climate change in a region, which causes heavy rains and floods, leading to increased river flow during certain times of the year. However, relying solely on the study of the flow rate of a region cannot accurately indicate the drought situation. This is because certain measures implemented in watersheds can significantly impact the flow rate of a river. Therefore, considering all the conditions and climatic factors that govern our country, it is not surprising to see such changes occurring in different periods.

This research aims to investigate the effect of flood spreading on the quantity and quality of groundwater in the Tokahour-Hashtbandi plain. For this purpose, first, SPI was calculated in time scales of 1 to 48 months for the existing rain gauge station in the region. The GRI index was calculated using the groundwater level data in the next step. Then, three wells with conventional names A1 to A3 were selected to evaluate quantitative changes. Five wells B1 to B5 were also selected for qualitative evaluation as they had the closest position to the flood spreading area. Then, using the Petit test, the time of the flood's impact on the quantitative and qualitative resources was determined. Also, by dividing the statistical period into two parts, the time before the impact of flood spreading and after the impact of flood spreading, using linear regression analysis, the slope of changes of GRI, EC, and SAR index for both times was done for the selected wells. In the next step, using correlation analysis and linear analysis, the effect of flood spreading on the sensitivity of groundwater resources to drought was evaluated. The results showed that the time of flood spreading effect on the level of three wells A1, A2, and A3 is 2009, 2009, and 2012, respectively, which is not statistically significant. Also, the time of flood spreading effect on EC values of wells B1, B2, B3, and B5 in 2007, 2009, 2013, and 2009 respectively, and on SAR values of well B1 in 2010 was determined. The results of the evaluation of the effect of flood spreading on the quantity of groundwater show the improvement of all three selected wells and the reduction of the slope of EC changes, but it did not have much effect on SAR. The results of the evaluation of the effect of flood spreading on the sensitivity of the groundwater quantity to drought showed that the flood spread has reduced the sensitivity of the GRI and EC index to drought in the selected wells, but it has not been able to reduce the sensitivity of SAR to drought.

Policy makers are faced with complex and multidimensional conditions to choose and implement water resources management policies in order to adapt to drought. On the one hand, due to the multidimensional and multiscale nature of water resources and drought management, there is a need to integrate tools for impact analysis and adaptation. On the other hand, the development of new irrigation technologies at farm level is one of the solutions and policies that are always discussed by experts and policy makers in the field of water resources management. Therefore, in the present study, a hydrological-economic model was used in order to evaluate the potential effects of drought and to develop new irrigation technologies as a solution to adapt to drought in the Kowsar dam watershed.

In this framework, a hydrological water planning and evaluation model (WEAP) and a positive mathematical programming model (PMP) were combined with the ability to evaluate socio-economic, agricultural and hydrological systems in a spatial and explicit manner. The necessary data and information are also taken from documentary studies at the basin level.

The results of the study showed that by increasing the efficiency of water consumption in the agricultural sector, the reduction of water consumption occurs without reducing the economic efficiency and quality of life. In such a way that by improving the efficiency of water consumption by 30% under drought conditions, the economic efficiency of water consumption in the entire basin will increase by about 7% compared to the basic conditions.

In other words, the development of new irrigation technologies leads to the saving of farmers' water and encouraging them to cultivate high-yield crops with high water consumption, which will improve the farmers' economic situation. Therefore, by implementing policies to improve the efficiency of water consumption without applying punitive policies in the field of preventing the planting of crops with high water consumption such as rice, it is possible to reduce water consumption without economic damage to farmers.regarding the economic growth of neighbouring countries.

Drought is one of the natural phenomena caused by the decrease in rainfall and reduces vegetation and increases dust. The common method of drought monitoring is based on observational data from meteorological stations and calculates a drought index. Knowing the amount and intensity of drought in a region and planning to reduce its effects is one of the most important principles of management in regional planning fight against drought. Monitoring and management of drought is a region using remote sensing data and satellite images as a suitable tool in the temporal and spatial monitoring of agricultural drought has always been  of interest to regional managers.

This study investigates the efficacy of remote sensing data and satellite images in delineating agricultural drought zones in the southern watershed of Kerman Province from 2001 to 2022. For the purpose, three indices, including the Vegetation Cover Index(VCI),Temperature Condition Index (TCI), and Vegetation Health Index (VHI), were extract from MODIS satellite images, and TerraClimate extracts data for growing season months based on remote sensing of vegetation cover from early March to late August (2001-2022), and the resulting indicators are compared with standard precipitation index (SPI) values. It was compared in one, three, six, nine-, twelve-, twenty-four-, and forty-eight-month time series. In this study, the correlation method between stations was employed to reconstruct the incomplete station data, and the stations with the highest correlation with the incomplete station were utilized for reconstruction. After organizing the data, the reconstructed information was entered into the SPIGenerator software as input, and the SPI indices for 1, 3, 6, 9, 12, 24, and 48 months were generated for the selected stations.

In this article, the results of calculating the SPI index in various time series based on the average data from existing stations and remote sensing data were analyzed. To this end, the values obtained from all satellite-based indices, including VCI, VHI, and TCI, were extracted and compared with the ground-based SPI index in 1, 3, 6, 9, 12, 24, and 48- month time series. In other words, the response of vegetation cover in the region to rainfall with 1, 3, 6, 9, 12, 24, and 48- month time legs was investigated. The result of this study shows that the VCI index has a significant correlation at a 1% level with the SPI index in all time series except for the 1-month series. The TCI index has a significant correlation with none of the time series except for the 1-month series. The VHI index has a significant correlation at a 1% level with all time series except for the 1-month,3-month, and 24-month series. Additionally, the drought indices TCI, VHI, and VCI have a positive significant correlation at a 1% level with rainfall and soil moisture.

The overall results of the analysis of the available data showed that among the studies indices, the VCI index has the highest correlation with SPI values in different time series during the growing season, with a significant correlation at the 0.01 level. Therefore, it is selected as the preferred satellite index for monitoring agricultural drought in southern Kerman Province. The results of this study provide a basis for a better understating and evaluation of drought conditions in southern Kerman Province, and can guide optimized management and provision of drinking water and agricultural resources, leading to increased and optimized agricultural production, and ultimately, proper environmental protection.

Soil moisture data obtained from satellites play an important role in the effective management of water resources, especially in areas susceptive to dehydration and drought. By monitoring soil moisture dynamics over time, water policymakers can develop sustainable water allocation strategies, implement water conservation measures, and reduce the adverse effects of drought on agriculture. Satellite data facilitates the identification of potential water stress points. The purpose of this study is to evaluate the accuracy of soil moisture in the GLDAS model with observational data in areas with dry, humid, and semi-humid climates, Agricultural drought monitoring using the GLDAS model and the VHI drought index and annual precipitation.

In this study, soil moisture from the GLDAS model from 2003 to 2020 in 6 agricultural areas of Oklahoma was extracted daily and with observational data recorded in 6 agricultural areas located in Oklahoma compared. To better understand the degree of difference between the GLDAS model soil moisture data with observational data, agricultural areas are divided into three dry, humid, and semi-humid areas,they were split and finally evaluated on a daily, seasonal, and annual basis with the used of two indicators of correlation coefficient CC and average RMSE root mean squares error.

The results showed that the highest average correlation of seasonal soil moisture is related to winter and autumn, and one of the reasons is more precipitation in these seasons. The highest correlation of average areas with 0/64 belonged to humid areas and the lowest average correlation of 0.47 was related to dry areas. Humid areas usually have vegetation cover more than dry areas. Vegetation cover due to the impact on microwave signals received by satellite sensors affects the accuracy of satellite soil moisture estimates. Also, the presence of dense vegetation improves the soil moisture recovery of satellite data, especially in areas with abundant vegetation. The results of RMSE (cm3/cm3) of the GLDAS model and observation data in 6 agricultural areas of Oklahoma showed the good performance of the GLDAS model. The correlation of GLDAS model data with VHI drought index and precipitation was further investigated, which correlated GLDAS model soil moisture with 17-year precipitation data equal to 0.68 the correlation of the model GLDAS and VHI was equal to 0.2. One of the reasons for the variation in the correlation between precipitation, VHI, and soil moisture of the GLDAS model is the changes in hydrological parameters such as groundwater feeding, evaporation and transpiration rates, and surface runoff, it is in different years.

According to the results, soil moisture serves as a critical intermediary between precipitation and vegetation health. While precipitation directly influences soil moisture dynamics, soil moisture, in turn, regulates plant water uptake, transpiration, and physiological processes that contribute to VHI. GLDAS model soil moisture data can be used to monitor and assess drought. GLDAS data are available at regular intervals (e.g., daily, monthly), allowing monitoring of soil moisture dynamics over time. This time resolution is crucial for tracking the start, duration, and severity of drought events. The results of this study show that GLDAS model soil moisture data can be used with confidence in monitoring agricultural drought.

Parishan Lake is one of the largest freshwater Lakes in the country, which unfortunately has dried up in recent years. Extensive agricultural activities as well as drought, are important factors in the drying up of the lake. Since there is no control over drought, managing the available water resources is the best way. In the present study, an attempt has been made to estimate the effect of water saving in the agricultural sector on revival of Parishan Lake. For this purpose, using satellite images on different dates and in order to determine the volume of water in each image, the Cut/Fill conceptual model available in the ArcGIS software environment was used. Then, the area corresponding to each volume was used from the combination of red, green and blue colors from bands 5, 4 and 3 of the Landsat satellite and created a Vector layer in the ArcGIS environment. In this way, the surface-volume curve of the lake was obtained. In the stage using the water balance equation, it was determined how much water can be saved in the agricultural sector. By having the volume of water saved and using the obtained surface-volume equation, this volume of water was converted into the area of the lake. The results showed that the lake area can be increased by 290% by deficit irrigation methods and saving 25% in water consumption in the agricultural sector.

Surface water scarcity and overexploitation of water have brought about a serious crisis in the contemporary age. Therefore, if the factors contributing to such a crisis remain unexplored and proper management is not implemented, water resource systems will face more severe problems. On the other hand, as complex systems possess their own specific elements, their analysis requires a kind of simulation that interconnects all components and phenomena within and outside the system using a specific boundary, helping to obtain more realistic results. Moreover, unlike linear thinking, the variables of a system are governed by causal relationships in dynamic thinking, indicating that changing one componential element of the system affects other components. However, the review of the related literature reveals that the majority of studies already conducted on drought have applied a linear perspective, and only a few studies have followed a dynamic approach. Moreover, it could be argued that no study has investigated the influence of long-term hydrological droughts on water resource systems with hydraulic structures on a daily scale. Therefore, when dams are constructed on water currents, it is necessary to investigate and simulate hydrological drought and the consequent changes made in downstream. This study used a dynamic perspective to simulate hydrological drought from 1991 to 2022 in the Qhorveh Dehgolan watershed in Kurdistan, Iran, on a daily basis, using the Vensim software. 

The study area included the Qhorveh Dehgolan sub-basins in Kurdistan province. The study simulated the daily dam outflow and the hydrological drought using the data regarding the river flow statistics, crop types, cultivated area, cropping patterns, irrigation requirements, precipitation, and hydrograph network from 1991 to 2022. As one of the most commonly used methods for analyzing hydrological droughts, the sequence theory, which was also applied in the current study, determines the drought index threshold, according to which the daily flow rates below the specified threshold indicate the occurrence of drought. However, there are instances where, for a short period, the flow rate exceeds the threshold level, leading to the classification of the drought period into smaller, dependent droughts. The problem mostly occurs in studies carried out on a daily basis, where small droughts with shorter durations are also counted as severe droughts. The problem can be solved by aggregating such small droughts.As the Internal Criterion method exhibits greater accuracy than other similar approaches used for aggregating small droughts, the current study used both sequence theory and the Internal Criterion method.  The primary advantage of the current research model lies in its multidimensionality, obviating the need to separately obtain the feedback and variables for all stations. This characteristic allows for the introduction of equations, feedback, and all variables for a single station without necessitating the expansion of equations and other factors to accommodate multiple stations. Another advantage of the model is that it uses feedback mechanisms to determine the drought tolerance level at each station, indicating that the model initially calculates sequences and volumes at various drought levels using the data collected from stream gauging stations. Then, through feedback loops to flow-dependent variables at each station, the model adjusts the relevant figures within permissible limits to ensure that flow rates approach the minimum flow over the statistical period without reaching zero. Accordingly, based on a long-term time series of flow rates for each station and the related dependent variables, the drought tolerance level for each station was determined, considering the fact that drought conditions at any given station do not necessarily conform to a specific level. 

While the precipitation trend was not decreasing throughout the study period, drought has significantly increased in terms of frequency and intensity during certain years. The precipitation trend in the region indicated an increase in the 1999–2001 period, concurrently accompanied by severe drought conditions, substantiating that an external factor has brought about such drought. The construction of dams and the declining outflow volumes in proportion to the entire period have affected both the slope of the flow duration curve and the drought conditions. Therefore, on a daily scale, the flow rate and its variations determine the intensity and severity of drought events. Accordingly, when flow rates are similar, droughts occur over longer durations in less severe intensity, whereas sudden changes in flow rates result in droughts with shorter durations but greater severity. For instance, at Sang Siah station, the minimum drought intensity (0.0006 MCM) with a long duration (172 days) was recorded in 2013. Similarly, at Gol Bolagh station, a drought lasting 216 days with an intensity of 0.122 MCM was recorded in 2013. However, at Shadi Abad station, which did not exhibit significantly distinct or varying flow rates, the maximum drought duration (215 days) coincided with the maximum drought intensity (0.73 MCM) in 2014. The same was true for Delbaran station, where the maximum number of dry days was recorded in 2014 (305 days), with a corresponding maximum intensity being 0.46 MCM.

This study carried out simulations in a dynamic environment, finding that according to the dam outflow rates when river flows exhibited minimal fluctuations, droughts were characterized by higher frequencies and less severe intensity. On the other hand, when flows were higher with significant variations in peak values, drought showed greater intensity and lasted for shorter periods. It can be concluded that analyzing the trend of changes made in the flow rate as a result of constructs built in the region and investigating the precipitation variations are required for investigating hydrological droughts that may occur over the dams’ inflow rates and simulating the discharge rates. This is consistent with the results found in some other studies (Hamedi and Paimozd, 2023; Alishahi Chegeni et al., 2023). The similarity of the behavior of the stations near the newly constructed dams was also notable. The Sural, Sang Siah, and Gol Bolag dams were constructed and filled in the region in 2011 and 2013, respectively, coinciding with the recorded drought events, which also resulted in rivalry over water harvesting and the development of farmlands. Hassan Khan and Dehgolan stations recorded completely different flow duration curves throughout the period. Therefore, severe and very severe drought levels in these stations will have a lower threshold compared to other stations. In this study, a simulation was designed to calculate the tolerable drought level of the station, which was achieved by employing feedback loops and flow duration curves to assess the severity of drought conditions, particularly when flow rates were low and severe drought events occurred at levels beyond those officially declared. Hassan Khan and Dehgolan stations, which were under the influence of their upstream dams, showed severe droughts in lower values than the declared average drought tolerance threshold of 25%.

This research investigates the barriers farmers face in adapting to drought. The statistical population comprises all farmers in Bavi County. Using cluster sampling with proportional assignment based on the Kerjesi and Morgan table, a sample size of 350 farmers was selected. The primary research tool was a questionnaire with a Likert scale, validated by a group of subject experts and confirmed for reliability using Cronbach's alpha coefficient and composite reliability. Data were analyzed using both descriptive and inferential statistics via SPSS and Lisrel software. The results indicated that some farmers lacked a proper understanding of drought, rainfall, and temperature patterns in the region. Moreover, "land leveling" and "use of local knowledge" emerged as the most important strategies for adapting to drought. The main obstacles identified were "lack of access to timely weather information" and "lack of access to water resources." Finally, confirmatory factor analysis classified the obstacles into economic, infrastructural, technical and informational, and social-human factors.

As a natural disaster, drought may occur in any climate. In recent decades, widespread severe droughts have continuously affected Iran, imposing detrimental effects on the country’s various economic sectors, including agriculture, environment, and water resources. Today, vegetation indices obtained from remote sensing are widely used to identify and analyze meteorological droughts. Remote sensing technology enables near-real-time monitoring of drought conditions by analyzing high-resolution spectral data, allowing for pixel-level calculations over large geographic areas. The Iranian provinces of Qom, Isfahan, Chaharmahal Bakhtiari, and Markazi are among those regions whose drought conditions have frequently been warned about within the last few years. Therefore, as the study of drought in these four provinces bears special significance due to the sensitivity of the provinces and the large population they accommodate, the current research selected the provinces as its study areas.

this study set out to investigate the correlation between SPI, NDVI, and EVI that were obtained from MODIS images from 2011 to 2020, seeking to monitor drought in central regions of Iran. To this end, changes made over a period of 10 years were identified using the images of the Modis satellite sensor and the precipitation data collected from the synoptic stations located in the study area. In this regard, four months (April, May, June, and July) were selected as sample periods by reviewing the data collected from the existing stations using the standardized precipitation index (SPI) model. This study selected MODIS Terra MOD13A2 imagery from 2011 to 2020 due to its high temporal resolution, broad spectral coverage, ease of access, and the absence of atmospheric and geometric correction requirements. This dataset was chosen to ensure the capture of both wet and dry periods. Subsequently, the Standardized Precipitation Index (SPI) was compared with the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). Moreover, the Pearson correlation coefficient was used to determine the correlation between the SPI meteorological drought index and remote sensing indices.

According to the study’s results, the correlation between SPI NDVI and EVI was found to be 0.832 and -0.149, respectively. In general, the results indicated that in areas with insufficient precipitation data and poor distribution of drought monitoring, remote sensing, and NDVI data can be used to monitor vegetation changes. Moreover, the results of drought monitoring revealed that during the ten-year study period, severe droughts occurred in some years. For instance, severe drought and extremely wet periods occurred in 2020 and 2011, respectively. On the other hand, the results of the correlation between SPI and remote sensing indices suggested that SPI had the highest correlation with NDVI at the level of 0.01. The results of this study can effectively contribute to the decisions made by decision-makers in monitoring, investigating, and resolving drought conditions.

Vegetation characteristics, the studied time period, soil characteristics, and the distribution and intensity of precipitation are important factors involved in the establishment of the highest correlation coefficient between the NDVI and the SPI during the delay period. Satellite indices show a remarkable correlation with each other in terms of detecting the magnitude of change, and the highest correlation between satellite indices and terrestrial indices is found in the NDVI-SPI pair. Therefore, the NDVI is used to monitor meteorological drought. Compared to point meteorological methods (precipitation recording stations), satellite images offer greater advantages, including the number of sampling points, wider coverage area, higher time resolution, and lower cost. Therefore, remote sensing knowledge is suggested for drought monitoring. Generally, remote sensing data and NDVI are suggested as appropriate indices to be used for monitoring vegetation changes in areas with insufficient rain gauge data and inappropriate distribution of drought monitoring.

Considering the importance and major role of medicinal plants in the agricultural economy of the country, along with the diversity of climatic conditions and the suitable potential for producing various medicinal plants, this study, aims to provide an economic analysis of the cultivation and production of cumin, which is considered one of the important medicinal plants in Khorasan Razavi province, based on relevant indicators. To this end, economic indicators such as the cost of producing cumin per unit area, the break even point of production, profit margins, and rate of return have been calculated and analyzed through field studies and data and statistics published by relevant organizations. The results indicate that based on the information and statistics obtained from the average field data in the year 2023, the breakeven point for production is equal to 232.5 kilograms per hectare. In other words, the higher the production per unit area exceeds this amount, the profit for the cumin farmer will increase. The profit margin for green cumin producers is around 980,000 rials, and the maximum rate of return for cultivating and producing cumin is about 50%. Overall, the research results indicate that cumin is economically beneficial, and given this plant's lower water requirements compared to other common crops, promoting its cultivation is advisable in the current water crisis.

In this research, multiple regression models were used to evaluate the effect of meteorological drought i and climatic variables selected crop yield in Kerman province using the Standardised Precipitation-Evapotranspiration Index (SPEI). The mean annual maximum and minimum air temperature, wind speed, relative humidity, total monthly precipitation, evapotranspiration, dew point temperature, air pressure, sunshine hours, and SPEI index, were collected/ calculated. Then these values were correlayed to selected crops yield by using during 1991-2018 period. SPEI values indicated that all study stations have experienced drought in the recent two decades and as a result the yield of crops across the study area has been significanetly affexted.The average coefficient of determination (R2) values in the best fitted regression models was observed for wheat with values of 0.39 and 0.95 (in Kerman and Anar station), for barley 0.27-0.9 (Baft and Anar), for potato 0.2- 0.75 (Jiroft and Kahnuj), for onion 0.23-0.54 (Baft and Jiroft) and alfalfa 0.31-0.98 (Kohnuj and Sirjan) were obtained. The results of this study can be used in suggesting new cropping patterns in coming decades for coping with drought and water scarcity in this province.

Rural business is one of the types of businesses that nowadays, due to the reconstruction of functional patterns of many rural areas and also the design of new tourism businesses in rural areas is one of the most dynamic aspects of entrepreneurship. Activities that are formed in tourism destinations with goals such as improving livelihoods and economic well-being sound to be the best ways to deal with these risks of economic shocks and imbalances to improve their resilience. Resilience is the capacity of society to withstand risks and abnormal conditions and return to normal conditions. Considering that tourism is an important and dominant economic sector in some countries and some destinations are dependent on this sector for growth and survival, relying on this sector has put a lot of pressure on tourism managers and planners in order to protect the business and the tourism community against crises and disasters and has led to the presentation of strategic plans to deal with its possible consequences. Therefore, in an important and growing economic activity such as tourism, it is necessary to understand and recognize the dimensions of the accident and crisis and to examine strategies to stop or limit its consequences. In this regard, business resilience and resilience planning are a comprehensive approach. To realize the development of tourist communities and reduce the possibility of instability caused by the occurrence of disruptive conditions in the normal process of these businesses, the most common perspective of resilience in tourism is on the marketing of the tourism industry and the number of incoming tourists to the destination due to the rapid change of variables caused by unexpected or predictable events and its impact on the economy and tourism businesses. In fact, the resilience of tourism may pay attention to the changes in social, environmental and economic variables that make up  tourism in an integrated way, but the ultimate goal of paying attention to it should be to create the resilience of businesses related to these variables against external fragile events.

The current research is applied in terms of its nature and descriptive-analytical in terms of survey-based method. The data collection tool for each item was through a questionnaire. The required variables of this research were selected using the study of reliable scientific sources and field study from the study area. In this research, the questions related to the variables of the questionnaire are set using a 5-option Likert scale from very high to very low. The unit of analysis in this research is the business owners related to the tourism sector in the rural areas around Urmia Lake in Shabestar city. In order to determine the reliability of the questionnaire, a number of 30 questionnaires were distributed in the region and the reliability coefficient of resilience was estimated at 0.87, which indicates that the mentioned questionnaire has adequate reliability. Also, based on Cochran's sampling formula, the sample size was 350 people from business owners related to the tourism sector. The data needed for the research was also collected through a simple random sampling method.

The descriptive findings of the research, based on 350 questionnaires distributed among the sample size, indicate that 319 were men and 31 were women. The highest frequency of respondents was 156 people in the category of 41-50 years, which accounted for 45% of the sample size. In terms of level of education, among the four levels of education, elementary and illiterate, under-diploma, post-diploma, bachelor and above, the highest frequency of respondents with 194 people, equal to 55%, was in the diploma level. One sample t-test was used to investigate the resilience of villages in four dimensions. The general results of the one-sided t-test for the resilience of the villages show an average of 1.68. Considering that the average observed resilience of the villages is less than 3, which corresponds to the average level of the Likert spectrum, so it can be said that the overall resilience situation in the studied villages is evaluated at a low level of resilience. According to the results of the one-sided t-test, the average of social capital dimension was 2.11, economic 1.22, human capital 2.16, and management institution 1.23. The significance level of all the indicators is lower than the test error level of 5% and the average of all dimensions are not at the optimal level and this issue is effective in reducing the resilience of the studied villages.

The results of the research based on the one-sided t-test indicate that the general situation of resilience is not very favorable. The general results of the one-sided t-test for the resilience status of the studied villages show an average of 1.68. Considering that the average observed resilience of the villages is less than 3, which corresponds to the average level of the Likert scale, it can be said that the overall resilience situation in the studied villages is evaluated at a very low level of resilience. Dimensions of resilience from the villagers' point of view have different averages, so that the highest average is related to the institutional and human capital (2.16) and the lowest average is related to the economic dimension (1.22). The stratification of the 7 studied villages based on Mirka's decision-making technique shows that based on the score (Q) Ali Biglo, Qara Tapeh and Kafi al-Mulk villages are at the medium resilience level, Sheikh Wali and Koushak villages are at the low resilience level and Haft Cheshme and Maraghosh Qala villages are at a very low level of resilience.

Today, the phenomenon of climate change is one of the problems that has always received attention in the world. One of the reasons for climate change is the increase of greenhouse gases, which have a significant effect on extreme phenomena. Drought forecasting is one of the management strategies that helps to plan properly for using limited water resources. It is also important to examine drought changes based on climate changes from various aspects; in many long-term plans, it is necessary to develop a vision of the future state of rainfall and drought periods for the region. The SPEI index can calculate drought in different time scales and can also include the effects of temperature changes in drought assessment and be used to monitor current and future climate changes based on climate scenarios. Also, the Standard Precipitation Index (SPI) is one of the most important indicators in drought analysis. This index is known as the most appropriate index for drought analysis due to the simplicity of calculations, the use of available rainfall data, and the ability to calculate for any desired time scale. The recent increase in droughts in the Karun 3 watershed has caused water shortages and economic and social damages. Therefore, investigating the effect of climate change and analyzing the frequency of drought is very important. In line with this goal, in this research, firstly, simulation of rainfall, maximum temperature, and minimum temperature of eight meteorological stations using three climate models EC-EARTH, CNRM-CM5, and GFDL-ESM2M under two release scenarios RCP4.5 and RCP8 5. It was forecated for the period (2055-2030).

In this research, firstly, the temperature data (maximum and minimum) and precipitation output of EC-EARTH, CNRM-CM5 and GFDL-ESM2M climate models under the CORDEX project for RCP4.5 and RCP8.5 emission scenarios with the help of CMhyd Raz software Scaled and time series of maximum, minimum and precipitation temperatures for eight meteorological stations in the future period (2055-2030) were produced. Then, the temperature and precipitation changes in the future period compared to the base period (1995-2020) were investigated. Finally, the investigation of drought (frequency and continuity) in the future period under two release scenarios of RCP4.5 and RCP8.5 by (SPI) and (SPEI) indicators in three-time scales of three, six, and twelve months using DIP software was performed. To evaluate the efficiency and accuracy of three EC-EARTH, CNRM-CM5, and GFDL-ESM2M general circulation models for simulating climate data, the monthly average of climate variables in the period (1990-2005) obtained from the output of the model was compared with the corresponding observational values. For this purpose, Nash Sutcliffe (NS), bias index and coefficient of determination (R^2) were used.

The results showed that the maximum temperature increase is related to Shushtar station. In this station, the maximum temperature will increase by 1.46 degrees Celsius in the RCP8.5 emission scenario and one degree Celsius in the RCP4.5 emission scenario compared to the base period. Masjid Sulaiman station has the highest increase in minimum temperature. At this station, the minimum temperature increase under the RCP8.5 release scenario is 2.41 degrees Celsius and under the RCP4.5 scenario, it is 1.92 degrees Celsius. Also, the rainfall in the whole range has been decreasing in the coming period. The decrease of rainfall in Kohrang in the RCP8.5 scenario is 146.3 mm and in the RCP4.5 scenario, it is 53.6 mm, which is about 11.7 and 4.3 percent, respectively. In terms of the frequency of drought in the statistical period (2055-2030) on a three-month scale, in the RCP4.5 scenario, Izeh station has the highest frequency with 14 droughts, on a six-month scale, in the RCP4.5 scenario, the maximum number of droughts in Shahrekord with 16 times and on a twelve-month scale, in the RCP4.5 scenario, Kohrang station shows the highest frequency with 15 times. In the RCP8.5 scenario, Izeh station has the highest frequency with 20 drought experiences. Also, in the upcoming period, under the RCP4.5 release scenario, on the scale of three, six, and twelve, respectively, Shahrekord, Yasouj, and Lordegan stations will have eight, 11, and 27 months, and in the RCP8.5 scenario, the drought will continue the most at Masjid Sulaiman, Shushtar, and Lordegan, respectively.

The results showed that the annual long-term average of the maximum and minimum temperature in the future period compared to the base period in all eight stations had an upward trend. Also, the results showed that the maximum temperature under the 8.5RCP scenario increases more than the 4.5RCP release scenario. Also, the results showed that the Kohrang station affected by climate change will have the largest decrease in rainfall in the study area during the coming period. Also, the results showed that in all three-time scales of three, six, and 12 months in the future period, compared to the base period, there are many fluctuations in the time series of SPI and SPEI drought indices. Also, extreme drought conditions will increase in the coming period. It is expected that in the coming period, the number of dry months will be less than the number of months with normal and wet conditions. Also, when examining the drought situation using the SPEI index, it can be seen that, like the SPI index, the pattern of changes in the drought period can be recognized in the stations. It should be mentioned that the intensity of droughts calculated using the SPEI index is rarely higher than the numerical value of two. By comparing the duration and frequency of drought in the studied stations and in different time comparisons, it was found that the SPI index shows the continuity and frequency of drought in most cases compared to the SPEI index.

Rafsanjan plain in Kerman province, which is located in the arid and semi-arid region of Iran, is one of the oldest regions in the country in the field of economic pistachio cultivation, and the majority of the economy of the residents of these areas is directly dependent on pistachio crop cultivation. Indiscriminate extraction of underground water resources, mainly for the consumption of the agricultural sector and pistachio crops, has caused a sharp decrease in the quantity and quality of underground water in the region. The quantitative and qualitative reduction of underground water as the only reliable source of water in the region has caused a decrease in the area under cultivation, the amount of production and productivity of the agricultural sector as the main source of the region's economy, and many economic, social and environmental consequences. Considering the vital importance of water in the Rafsanjan Plain, in this research, the quantitative and qualitative changes (EC) of water in this area in the last two decades have been investigated and studied. Information has been collected through interviews with experts and analysis of data available in the relevant departments. The results of the study show that along with the increase in the drilling and exploitation of wells, the underground water level has decreased, the depth of the wells and the water level have increased, and the water quality has also decreased.

Critical to human survival, water resources, including groundwater and particularly rivers, are under threat from anthropogenic pollution. The major Kashafrud River, located in northeastern Iran, is a seasonal watercourse currently encountering numerous challenges. At present, a stretch of this historic river (Parkandabad to the basin's exit) carries wastewater, comprising industrial, urban, agricultural, and even livestock effluents, transforming it into a conduit for sewage. This study reviews existing research on the challenges faced by the Kashafrud River, including pollution, climate change, and its impacts, as well as reduced runoff and drought. It outlines the crisis afflicting the river and then explores solutions to mitigate the current conditions. This research process involved reviewing previous studies on the challenges of Kashafrud, conducting field visits, engaging in discussions with local residents, and validating these findings through consultation with regional water experts responsible for overseeing this water course. Research indicates that there has been a limited focus on the pollution issue in Kashafrud, underscoring the evident necessity for comprehensive scientific inquiry aimed at presenting suitable solutions to tackle river contamination. In conclusion, through analyzing solutions proposed in previous studies and summarizing their strengths and weaknesses, 13 practical solutions were presented to provide the most effective strategies for addressing the challenges of this significant river.