جستجوی مقالات مرتبط با کلیدواژه « sistan » در نشریات گروه « آب و خاک »

Evaporation, the process by which water molecules escape a surface after absorbing sufficient energy to overcome vapor pressure, is a major contributor to water scarcity, especially in arid and semi-arid regions where heat readily facilitates this escape. Accurately estimating evaporation losses is crucial for effective water resource management, crop water demand prediction, and irrigation scheduling. Machine learning (ML) has emerged as a powerful tool for tackling the complex and stochastic nature of environmental problems. ML models excel at identifying relationships between predictor variables and outcomes (predictands), often surpassing traditional methods. However, their performance can vary depending on input factors and climatic conditions. Recently, hybrid techniques that combine multiple models have gained traction in climate and hydrology studies. These techniques leverage the strengths of different approaches within a single algorithm, potentially capturing more complex patterns in data series. This research will explore the potential of various individual ML models and propose a novel hybrid approach for estimating pan evaporation in Sistan and Baluchistan Province.

This study investigates pan evaporation simulation and prediction in Sistan and Baluchistan Province, Iran. Synoptic station data (1980-2019) served as model inputs, while pan evaporation measurements from these stations provided the observed values. In this research, in the approach of individual performance of data mining models, eight data mining models were used to simulate and predict evaporation from the pan. In addition to the individual performance approach, the combined VEDL approach was used to provide a hybrid model (a combination of the mentioned eight individual models of deep learning). In this hybrid approach to regression issues, the estimators of all models are averaged to obtain an estimate for a set called vote regressors (VRs). There are two approaches to awarding votes: average voting (AV) and weighted voting (WV). In the case of AV, the weights are equivalent and equal1. A disadvantage of AV is that all of the models in the ensemble are accepted as equally effective; however, this situation is very unlikely, especially if different machine learning algorithms are used. WV specifies a weight coefficient for each ensemble member. The weight can be a floating-point number between Zero and one, in which case the sum is equal to one, or an integer starting at one denoting the number of votes given to the corresponding ensemble member. the weight of each model was selected based on the accuracy of the model's performance using the evaluation criteria obtained from the training implementation section of individual models. the model’s performance was assessed using statistical measures, including R2, RMSE, MAE, and Taylor diagram.

The results showed that all the models had very good results in both the training and testing stages. All models exhibited excellent performance during training and testing. The Artificial Neural Network (ANN) achieved the highest accuracy in both phases at the Zahedan station (R² = 0.89, RMSE = 45.95 in training; R² = 0.96, RMSE = 44.18 in validation). It emerged as the best model for monthly pan evaporation prediction at this station. Other models also performed well, with the Support Vector Machine (SVM) and Random Forest (RF) models achieving R² values of 0.89 and 0.88 in training, respectively. Notably, the BART model ranked second in validation (R² = 0.96). The Tree Model (TM) had the lowest accuracy (R² = 0.84 and 0.93 in training and validation, respectively). Across all stations, ANN, SVM, and RF consistently delivered the best results in both training and testing. In the test phase, the SVM model outperformed others in Khash, Iranshahr, and Chabahar stations (R² = 0.94, 0.96, and 0.94, respectively). At the Saravan station, the RF model achieved the highest R² (0.94) during testing. To develop a hybrid data mining model, the Voting Ensemble for Deep Learning (VEDL) technique was employed with weighted voting in the training stage. The combined model significantly improved upon the best individual model. RMSE decreased from 45.95 to 33.1, R² increased from 0.89 to 0.94, and MAE improved from 32.92 to 23.9. Evaluation using the Taylor diagram further confirmed the superior performance of the VEDL model compared to the individual ANN model.

The results showed that among all the models, ANN, SVM, and RF models had the best performance in the two stages of training and verification. In the validation stage, the SVM model with R2 values equal to 0.94, 0.96, and 0.94 performed best in the Khash, Iranshahr, and Chabahar stations. At the Saravan station, in the Sensji validity stage, the RF model with an R2 value of 0.94 had the best performance among the models. The excellent performance of the models in the two stages of training and validation is another finding of the research, These results are consistent with the results of researchers who have expressed the appropriate efficiency of machine learning models in estimating evaporation/evaporation and transpiration in different climatic regions of Iran. The results of the combined model showed that the combined model improved the results compared to the best individual model so that the RMSE values increased from 45.95 to 33.1, the R2 values increased from 0.89 to 0.94, and the MAE value improved from 32.92 to 23.9. The use of the VEDL approach to estimate evaporation from the pan was a new approach that has not been used in past studies. Therefore, according to the results of this research, the proposed deep sensing model is proposed to estimate the evaporation of arid and semi-arid areas for water resources management and agricultural planning.

In the last two decades, Sistan region has been suffering from drought conditions. The fluctuation of the Hirmand River and the incorrect management of water resources in this region have caused the water crisis to intensify. In this situation, one of the solutions that can help to get out of the critical water situation is cooperative irrigation. Therefore, in this research, the feasibility of establishing water harvesting cooperatives in drought conditions in Sistan region with an entrepreneurial approach is considered. To achieve the mentioned goal, the model of similarity to the ideal option of the fuzzy logic bed has been used. To collect the necessary information, experts, experts and farmers were used through interviews and questionnaires. MCDMSolver 2018 software was used for modeling and solving the model. In this research, based on three economic, social, and attitudinal indicators, the sub-indices were divided into 12 items, and finally, the three options examined, the traditional system, the production cooperative system, and the rural cooperative system were prioritized and ranked. The results of the research showed that the production cooperative system with a weight of 0.56 was placed in the rejection rank. In the second place is the rural cooperative system with a weight of 0.40 and the traditional system with a weight of 0.29 is in the last place. According to the obtained results, water cooperative system should be given special attention in the form of production and rural systems.

In this research, two categories were used to investigate the effect of the change of clarion surface water of Khash plain. The data on 2010 to 2020 obtained from the Liz Hydrometer Station on the Syanjah River Khash Plain, on the other hand, the base rainfall data was obtained from the Khash Station. Based on the measured regression model, the base period of the relationship between Dubai and precipitation at the Khash basin level was modeled. With the implementation of the SDSM statistical microscale model, the simulated rainfall values were obtained in the statistical period of 2020-2040, under two lines of release 4.5 and 8.5, which was used as an input to the regression model for remodeling in the climate change period. The results showed that in the period of climate change 2040-2020, despite the fact that the rainfall of the Khash basin has increased in the cold months of the year, the simulated runoff of the period 2040-2020, in both RCP4.5 release trajectories and RCP8.5, has had a decreasing trend. The results indicated that the climate change period 2020-2040, in the RCP4.5 release, had reduced about 0.02 cubic meters per second to the base period, and in the RCP8.5 release track, this was a decrease of 0.016 cubic meters per second.

Water is one of the most important issues in the world, which plays a significant role in people's lives. Due to progress in all parts of the community, especially advances in socioeconomic, industrial and socioeconomic sectors, as well as the growth of the population, the need for water has increased. A general look at recent experience and global experiences suggests that the limitations of water resources are not due to lack of resources, but because of lack of resource management. In this regard, management of water resources in dry and semi-arid areas such as Sistan, which faces a drought, is very important. Therefore, in this study, using multi-index gray technique, the evaluation and prioritization of water resource development plans has been addressed with regard to various management aspects. According to the results, based on four economic, social, technical and environmental approaches, one of the most important findings of the research from the experts' point of view is the reduction of water losses (reduction of evaporation by 50%), irrigation efficiency of 50% in agriculture and reduction of irrigation losses (reduction of evaporation to 30%) are ranked first to third respectively. Water transfer to Zabol lands is also a priority. Also from the farmers' point of view, the most important results of this study are water loss reduction (evaporation reduction of 50%), irrigation efficiency of 50% in agriculture and irrigation efficiency of 70% in agriculture, respectively, in the first to third priority respectively.

Intake canals of off-stream reservoirs, play a key role in achieving reservoir goals. Chahnimeh reservoirs have been constructed to store and use water optimally for drinking, agricultural development and play a complementary role to flood control. The Sistan plain in the southeast of Iran is highly dependent on surface water resources. The HEC RAS model is a well-known one-dimensional software for flow and sediment simulation. In this study, HEC RAS 6.0.0 was used to simulate sedimentation in feeder 2 canal under maximum conditions as well as minimum water level conditions of Chahnimeh reservoirs. Flow simulation in the model was performed quasi-unsteady using the standard step-by-step method by a flood hydrograph with a volume of one billion cubic meters. According to the simulation results, in maximum water level Conditions, Feeder 2 canal Sedimentation volume is equal to 54,200 m^3 which increases the bed level by 4.1m. Also, in minimum water level Conditions, sedimentation is equal to 52,700 m^3, which increases the bed level by 3.84 m. Comparison of the results in the two scenarios shows that in the case of maximum water level, volume of sediment per unit of length of Sistan River is equal to 6.5 m^3⁄L_River while in minimum water level volume of erosion is equal to 2.2m^3⁄L_River of Sistan River. Although feeder 2 canal in minimum water level conditions increases the inflow from the Hirmand river due to the decrease in the river bed level of sistan river but will act as a sedimentation canal in all conditions.

Water is a critical input for agricultural production and plays an important role in the sustainable development of the agricultural sector and the economic development of other sectors. Water shortage is one of the major challenges that most countries in the world are struggling with. The great importance of determining the optimal cropping pattern of crops and irrigation allocation planning in the water shortage conditions prevailing in Iran's watersheds is not hidden from anyone. This study aimed to optimize water allocation and determine the optimal cropping pattern of crops in five cities of the Sistan region under different management scenarios.

In this study, a model with a two-level planning approach, the Stackelberg game framework, and a genetic algorithm, was developed to optimize the water allocation between irrigated areas and crops, as well as to determine the optimal cropping area in 5 cities of Sistan region (including Hamon, Hirmand, Zahak, Nimroz and Zabol) to confront different water conditions. Selected products include wheat, barley, onion, melon, watermelon and alfalfa. The problem was solved in the form of nine scenarios, including three scenarios of irrigation efficiency, three scenarios of climatic conditions, and three scenarios of low irrigation conditions, and compared with the baseline scenario.

For water allocation among the studied regions in the baseline scenario, the most and least water was allocated to Zahak and Hirmand areas, respectively. Among the studied crops, the most water was allocated to the melon due to its low water requirement and high economic value compared to other crops, and the least amount of water was allocated to the alfalfa due to its high water requirement; also the melon with 13503.5 ha had the highest cropping area and alfalfa with 4.85 ha had the lowest cropping area in a total of five cities. The total cropping area obtained by the model was 18240.32 ha. The value of the Gini coefficient was 0.0053, which is small and close to zero, indicating that the water allocation between the regions was fair. The total interest rate obtained in the baseline scenario was 5.06 ×1013, which by applying irrigation efficiency scenarios of 50 and 70 percent, the amount of profit has increased by 12% and 34%, respectively, and the cultivated area by 27% and 47% compared to the baseline scenario. And in normal and wetyear conditions, the amount of total profit has increased by 28% and 54%, respectively, and the cultivated area by 40% and 65% compared to the baseline scenario. By applying the low irrigation scenario, the interest rate decreases compared to the baseline scenario, associated with the saving of a large volume of irrigation water, which leads to an increase in the cropping area of crops with higher economic efficiency. Therefore, by applying various scenarios, the cropping pattern moves towards crops with less water requirement and higher economic value.

According to the results, more water has been allocated to crops with higher economic value and less water requirement. Therefore, if crops with less interest rate compared to their water use and crops with high water requirement are removed from the cropping pattern and crops with higher economic efficiency and less water requirement are replaced in the cropping pattern, it can be a good solution to confront water shortage conditions. The increase in irrigation efficiency increased the total interest, thus it is recommended to save water used by plants through the improvement of irrigation technology and increase irrigation efficiency. The proposed model in this study can be employed for correct and efficient planning for agriculture and water resource management in various conditions.

Soil and water scarcity has become the main challenge encountering human, especially in arid and semi-arid regions of the world. In addition, due to economic limitations in developing countries, region prioritization for developing and modernization of irrigation and drainage networks should be considered. In this study cultivated lands of the Miankangi Plain in Hirmand County located in Sistan-o-Baluchestan Province has been prioritized, in order to irrigation system network development. At first, questionnaires were designed and more than 120 of them were completed by experts and researchers, then weighted based on statistical indicators. After that, based on the available reports, field research, preliminary studies and data analysis, the effective parameters were selected. Effective parameters for this scope have been divided to technical and socioeconomic groups. These parameters had different efficiency. Among technical factors in different climatic conditions, fertility and soil quality with 34 points (out of 100) and among socioeconomic factors population density with 25 points had the most weights (efficiencies) for classification. Eventually cultivated lands were classified and prioritized to 11 groups. Villages such as Alimorad, Poodineh and Rudini were located in the first priority and Dahmarde, Molla Abdollah with the lowest points in the last priority. It is suggested to use this method to better understand the effective factors in nearby villages for the development of irrigation and drainage network.

Frequent droughts in the Sistan region have caused a severe crisis in the agricultural sector of this region. Meanwhile, the agricultural sector plays a significant role in the economy of this region. Therefore, determining the crop program and cultivation pattern, taking into account water constraints, is especially necessary to maximize the profits of the agricultural sector in this region. For this purpose, in this study, to determine the crop program, shade price and final value with emphasis on optimizing water consumption in the three main agricultural sectors in Sistan region (Zabol, Zahak and Miangangi) and on five strategic crops (wheat, barley). , Potatoes, onions and tomatoes). The analysis was performed based on 3 scenarios: 1) current cultivation, 2) maximizing profits by considering the water and land requirements, and 3) maximizing profits according to the constraints including land and area consumption constraints. The results showed that due to the application of water and land restrictions (Scenario 2) in the mentioned areas, wheat and barley crops are removed from the cultivation pattern, but other crops increase their area under cultivation and by applying all restrictions (Scenario 3) Barley crop will be removed from the cultivation pattern, but other crops for the mentioned areas will change their cultivated area. Therefore, considering that Sistan region is facing a shortage of water resources, therefore, it is suggested that optimization models and the results of this study can be used as a suitable tool to reduce water consumption and increase production in water resources management community plans.

According to statistics, Sistan region is one of the arid and low water areas. And the issue of water shortage and drought is one of the crises that threaten the Sisan region in the near future. Water and poverty are closely linked, so a strong assessment of water stress is essential to identify areas in need and develop appropriate interventions to reduce poverty. The Water Poverty Index (WPI) is a tool for assessing water stress by linking physical estimates of available water levels with socioeconomic incentives for poverty. It is also a comprehensive tool for managing and evaluating water resources. This study presents the application of water poverty index (WPI) to estimate and compare water stress levels in 5 cities of Sistan region in 2021-2022. The results of the study show that the average poverty index in the cities of Sistan region in the same weight condition is 0.48 and, in the weight, according to AHP method is 0.43. The water poverty index varies from 0.60 to 0.23 among the cities of Sistan. hirmand city has more water stress compared to other cities. In order to deal with water poverty in Sistan region, management and optimal use of water resources, especially in drought conditions, is very important.

Societal needs elicit focus to new water sources including water extraction and developing adaptation to indigenous, climatic, economic and social conditions. The initial step in developing water extraction from humidity was determining optimal extraction areas with appropriate conditions. For this purpose, humidity and temperature criteria were collected utilizing satellite imagery which included soil type, surface wind speed, and 50 cm deep soil temperature data. Subsequently, criterion was mapped out based upon the role and importance of each factor obtained using hierarchical analysis in a GIS v10.2 environment. Employing linear phase functions, the information layer was phased and layers were subsequently combined using the 0.9 gamma phases function. Resultant findings of water extraction from humidity utilizing a condensing system revealed ~13.1 percent of Sistan and Baluchestan southern provinces (along Makran and Chabahar coasts), and its western Deligan region laid in very appropriate and appropriate areas. Conversely, about 83.9 percent of northern and eastern province areas were determined to lay in inappropriate extraction areas.

Sistan and Baluchestan Province, in southeast of Iran, is covering about 11 percent of the whole space of the country but is one of the driest provinces in Iran and its average annual rainfall is about 110 mm. The purpose of this study was to identify large-scale atmospheric circulation patterns causing extreme and widespread rainfalls during the warm seasons (spring and summer) in southeast of Iran (Sistan and Baluchestan province).Data and Precipitation data of 6 synoptic stations of Sistan and Baluchestan province during a 30-year statistical period (1979-1998) were obtained from Meteorological Organization of Iran (IRIMO). The intensity of precipitation based on 90th percentile threshold and widespread precipitation index of at least ≥50% of the studied area were calculated. To identify the synoptic patterns of the upper atmosphere, the ERA5 data of the ECMWF European Center of Med-Latitude Weather Forecast with spatial resolution of 0.25° × 0.25° were obtained. The collected atmospheric parameters included mean sea level pressure (mslp), geopotential height (z), specific humidity (q), zonal (U) and meridional (V) wind components, relative vorticity (rv) and omega (w) and maps of the upper atmosphere were drawn at different levels using Gards software in the domain of 10 to 70E and 10 to 90N. Regarding the two selected characteristics, three events of heavy and widespread precipitation were determined. By analyzing the daily rainfall data over a period of 30 years (2018-1988) during the warm months of the year, the number of days with torrential and widespread rainfall in Sistan and Baluchestan province were determined. According to the index the previously defined floods and mudslides were obtained for 3 days with torrential and widespread floods that often occur in the spring, which are categorized to three main patterns including: 1- Gono Tropical Storm 2- Omega Blocking and 3 – 500 hpa trough system. The results showed that during the maximum 24-hour precipitation, in the first synoptic pattern, the southern cities of the province received the maximum precipitation due to the proximity of the storm’s core, but gradually from southern to northern latitudes, the rainfall declined considerably so that Chahbahar station had the maximum rainfall and Zabol station recorded zero rainfall. The storm is expected to move eastward as it moves to higher latitudes, but the high pressure formed on the Indian subcontinent acted as a barrier and directed the storm to the west, thus affecting the southern regions of Iran. In the second and third pattern, the location of Sistan and Baluchestan province in front of the trough axis and advection of cold weather of the northern latitudes were the main causes of instability that lead to heavy rainfall. The moisture of these rainfalls was obtained from Oman, Arabian Sea and Indian Ocean respectively. In the second pattern, the anticyclonic clockwise motions of the Arabian Sea has provided the moisture for extreme precipitation events. Common points of all three precipitation patterns are atmospheric moisture reduction in all three levels of the earth, 850 and 700 hectopascals from south to north of the province. This is mainly due to the distance from moisture sources as well as the arrangement and height of the roughness of Sistan and Baluchestan province, which has caused moisture trapping and prevented the transfer of sufficient moisture for the occurrence of torrential rains. In the second model, the amount of moisture reduction from south to north is less, which indicates the activity of the Arabian Sea high pressure and the power of this high pressure in moisture transfer. In general, with increasing altitude towards the northern regions, mainly rainfall systems have lost their moisture and unevenness has prevented the proper distribution of moisture in the province. In southeastern Iran, the spatial distribution of precipitation is strongly influenced by the proximity to the sea and the location of the topographic features. Upper air levels turbulences are the most common cause of air mass rise. The main factor in reducing heavy rainfalls in northern areas of Sistan and Baluchestan is the lack of sufficient water vapor to reach these areas. Extreme rainfall is more likely to occur in spring than in summer due to the appropriate thermal gradient in southeastern Iran. Finally, the results of the study showed that the possibility of precipitation in spring compared to summer due to the appropriate temperature gradient in southeastern Iran and the activity of Siberian and Northern European high pressure, the conditions for fronting in these areas are provided. Since the humidity of the southern oceans through atmospheric rivers has been effective in the occurrence of heavy rainfall in southeastern Iran, rising temperatures in the southern oceans due to global warming can strengthen moisture flows in the future and from this route to affect the intensity of rainfall in southeastern Iran.

Sustainable land management is defined as as “the use of land resources, including soils, water, animals and plants, for the production of goods to meet changing human needs, while simultaneously ensuring the long-term productive potential of these resources and the maintenance of their environmental function”. Undoubtedly, achieving comprehensive land management requires effective and coordinated communication, cooperation and synergy of all key stakeholders and stakeholders who have common goals but distinct tasks. The aim of this study is to investigate challenges and strategies for managing and combating dust storm using participatory appraisal among Sistan Institutional Stakeholders Network.

The aim of this research is participatory appraisal of challenges and strategies for managing, controlling and combating the dust phenomenon among 27 invited relevant key institutional stakeholders of Sistan network. Comprehensive studies of Sistan dust conducted by the Research Institution of Forest and Rangeland, and the considered challenges and strategies for managing, controlling and combating dust storm was assessed using a brainstorming technique in a collaborative way. So, the participants have been divided into 5 working groups, including Water-Agriculture, Economics-Development-Infrastructure, Environment-Natural Resources, Cultural-Social-Political, and Law-Policy Making. The challenges and solutions have been investigated.

some challenges stated by the groups are: limitation of water resources, depletion of groundwater table and the lack of optimal decision-making regarding the management of watersheds in western Sistan, the destruction of vegetation in northwestern Sistan, the lack of organizational cohesion and integrated attitude by land management authorities, the lack of communication between research and implementation, migration, insecurity due to the depopulation of villages, increasing poverty and unemployment, weak Iranian diplomacy regarding the Hamoon Wetland, strong dependence of the Sistan region on water resources and agricultural economy, lack of integrated management regarding the maintenance of wetlands. The presented solutions are: determining the extent of urban development based on the volume of available water, modifying the pattern of drinking water consumption, predicting the use of treated municipal effluents to control fine source of dust, the optimal use of precipitation to stabilize eroded areas, improve the Sistan river pathways, forming the Sistan Dust Working Group, evaluating the effectiveness of executive projects on watershed management, and education in schools.

In general, the challenges raised by various institutions indicate a weakness in comprehensive planning, integrated management and good governance based on community-based participatory management.

Sistan and Baluchestan province is one of the water-scarce regions of Iran with hot, dry climate and very little rainfall, and water shortage is one of the most common problems in this province. Sistan and Baluchestan University is one of the water consumers in the region, which spends a lot of money annually to water consumption. In this regard, a study was conducted to investigate water supply facilities and water consumption in the dormitories of Sistan and Baluchestan University. As an example, dormitory No. 5 was selected from the Efaf and Hejab Dormitory Complex of Sistan and Baluchestan University and field studies and objective observations were performed. The results of the observations indicate problems such as broken and old valves and their connections, old heads, improper siphons, improper use of water by people living in dormitories and improper irrigation of green space. The above are important factors in wasting a large volume of water. In this study, replacing dormitory valves with lever valves was suggested as the main solution. In order to investigate the effect of the proposed solution, the dormitory water supply network with two types of normal and lever valves was simulated with WaterGEMS software. The simulation results showed that the use of lever valves reduces water consumption by about 23% and can have a significant impact on reducing water consumption and water costs. Therefore, it can be concluded that replacing lever valves, while being practical and economical will significantly reduce water consumption.

The purpose of this research is to present a method based on global and experimental algorithms for estimating relative humidity in Sistan and Baluchestan province. For this purpose, Terra MODIS images and products (MOD05, MOD07) of 10-years (1-Jan-2009 to 31-Des-2018) under cloudless conditions were used as selected data. To validate the obtained layers (near ground surface temperature, ground surface pressure, total perceptible water, TPW, and relative humidity), the ground station and the radio sound data were used. The R2 and REMS values of the recorded layers from the sensor and the ground data were acceptable and the sensed data were in good agreement with ground station measurements. Results show that the altitude factor play an important role in temperature measurement. The minimum amount of TPW has been recorded to be 6 mm in the Khash, Mir Java and Saravan regions in the cold season and the maximum amount of TPW has been recorded to be 49 mm in the coastal areas in the warm season. The average relative humidity in the province is in equilibrium in the cold season, while it is out of equilibrium in the hot season, so that it is above 60% on the coast of Oman and less than 10% in the central province (Khash, Mir Java and Zahedan).

This study aimed to investigate the vulnerability of Sistan plain to fluctuations and Water Scarcity in Hirmand River using the vulnerability framework, by applying the resilience approach. The socioeconomic and biophysical components presented in this framework were embedded in a set of subsystems of the System Dynamics (SD) model. According to this, four levels of reference resilience were defined based on the annual flow from the Hirmand River, and the system attributes of concern were identified under the existing structure until 2050. Then, the proposed strategies to the socio-economic structure of the model were applied under two critical conditions of water scarcity and fluctuations of the river flow. The values associated to the system attributes of concern of the two mentioned conditions were compared with the reference resilience levels. The results showed the efficiency of the policy option in reducing water scarcity and the importance of the environmental impacts of the biophysical component. For example, the two modes of water scarcity and water inflow fluctuations had the revenues of 9490 and 5100 billion IRR (annual income according to the base price of 2011), but they had the same population and residentchr('39')s utility, which was related to receiving 117 and 600 MCM of the environmental demand, respectively. Management, development and continuous support of the industrial sector can provide a "Success to the Successful" archetype for the socio-economic section of Sistan Plain.

The drying of Hamoon international wetlands and dust storms caused by these wetlands bed in the past two decades have been considered as one of the main environmental concerns of the eastern part of Iran. The purpose of this study was to investigate the relationship between meteorological variables of temperature, rainfall and discharge of the entrance water of the Hirmand River with the amount of land degradation in the Hamoon in a 21-year (1996- 2016) interval. For this purpose, weather data of temperature and precipitation were obtained at three synoptic stations of Kandahar, Farah and Zabol, and TRMM rainfall data and ERA temperature data were obtained from the related website. Land degradation based on the MEDALUS model and five criteria of wind erosion, soil quality, climate quality, management quality and vegetation was evaluated in Hamoon basin. The correlation between temperature, precipitation and discharge data was determined to land degradation statue. Investigations showed that the inflow of Hirmand River inlet to the Hamoon bed has been decreasing during this period, and the land degradation class has increased very drastically in all working units from the middle class to the severe class. Also the correlation of temperature data with inlet water discharge and land degradation were -0.558 (moderate level) and 0.735 (strong level) respectively, while the correlation of discharge with precipitation was 0.666. Correlations between precipitation and discharge with land degradation were found to be strong at 0.901 and 0.843, respectively. The results showed that the land degradation in the bed of the Hamoon has a good correlation with temperature changes, precipitation and inflow discharge. This correlation is such that it shows the indirect relationship between the amount of land degradation with the amount of inflow discharges and recorded precipitation and the temperature is correlated with each other. Between 1996 and 2002, the rate of land degradation increased and reached a very severe level with increasing temperature, decreasing precipitation and consequently reducing the inflow rate of the Hirmand River to the Hamoon. In 2003, with temperature decrease and the increase in precipitation, the inflow rate of the Hirmand River increased and finally the intensity of land degradation was reduced in the medium to high intensity units. In 2004 to 2016, the amount of rainfall in the Hirmand basin declined, with the result that the amount of discharge to the Hamoon wetlands declines again and the intensity of land degradation in the work units is at a very high level.

In water scarcity conditionals, water resources management and accurate use of available water for sustainable production of required products in arid and semi-arid areas are essential. To achieve this management, the evapotranspiration plays a very important role that is one of the main components of the hydrological cycle and successes of water projects and sustainable production depends on the correct estimation of that. Determination of the water requirement of crops and gardens will increase the irrigation efficiency and improve water management in the field. In order to estimate the evapotranspiration, it is necessary to accurately calculate reference evapotranspiration. So far, many experimental methods have been proposed to estimate the reference evapotranspiration. The penman montieth fao method is one of the most precise methods to determine of that and limitations of using that is calibrating for areas that will be used.Over the last few years, the uses of learning tools and innovative methods have been widely used to estimate the reference evapotranspiration. Therefore, it is necessary to check the correctness of these models and methods for different regions.

Sistan is one of the fertile regions of Iran, which, unfortunately, over the years, the phenomenon of drought has been swept away the active farming in the area and destroyed a boom in agricultural production in this region. Nevertheless, the main occupation of rural people in this region is still agriculture. Any neglect on the water category in this area, can be a serious damage to it. Winds for more than 120 days are main climate feature of this region that has extremely been increase the evaporation. Therefore, it is necessary to extract the highest efficiency from the limited water in the area. So, in this research, the effective climatic parameters to calculate of daily reference evapotranspiration in Sistan plain were identified and analyzed using different scenarios of the combination of meteorological parameters. These scenarios were used as inputs models of decision trees, random forest and deep learning. The best scenario was extracted by results of models. Then, the accuracy of the results was compared with the experimental method of penman montieth fao as the basis method. Scenarios were M1 - M25. Used data in these scenarios were max, min and average of two temperature and humidity parameters, rainfall, sunshine, wind speed and pan evaporation. The data were provided from the Zabul meteorological stations for 2009-2018. 80% of the data have been use for training and the remaining 20% for testing the models.

Results of these models were compared with the estimated results by the penman montieth fao model and shown, in decision tree model, M10 scenario with the lowest error rate ( RMSE=1.003 ) and the highest correlation coefficient ( R=0.983 ) was the best scenario. In random forest model, M10 scenario with the lowest error rate ( RMSE=1.003 ), MAE=0.8 and the highest correlation coefficient ( R=0.983 ) was the best scenario. In deep learning model, M5 scenario with the lowest error rate ( RMSE=0.517 ), MAE=0.399 and the highest correlation coefficient ( R=0.996 ) was the best scenario. In results of the supporting machine model and selecting the best model, by evaluating the comparison of decision tree and deep learning models, it was shown that a specific pattern can be introduced for Sistan region with proper accuracy for estimating daily reference evapotranspiration and should introduce a superior scenario for each model. In order to deliberation the importance of various meteorological parameters in the results of the mention models, among all the parameters have used in decision tree model, average temperature, wind speed, maximum temperature and minimum temperature, respectively, had the most importance. In random forest model, maximum temperature, wind speed, average temperature and pan evaporation, respectively, had the most importance. Finally in deep learning model, average temperature, maximum temperature, wind speed and minimum humidity, respectively, had the most effect on calculation of daily reference evapotranspiration in case study region. As a general conclusion can say, deep learning model is the best model among selected models and M5 scenario in deep learning with the highest correlation coefficient ( R = 0.996 ) and the lowest error ( RMSE=0.517 ), had a good accuracy to modeling of daily reference evapotranspiration.

In the recent decades dust storms have become serious natural hazards in the world. Although dust storms have been investigated in various aspects variation in wind speed and visibility and the frequency of dust storms requires more investigation. In this study, diurnal, monthly and yearly variation of parameters including wind speed, visibility and PM10 (particulate matter 10 micrometers or less in diameter) and frequency of dust storms is studied in the Sistan region for the twenty seven-year period.

The Sistan in the southeast part of Iran is considered as the study area. Sistan has an arid and semi-arid climate with very low precipitation (59 mm) and air humidity and high evaporation (nearly 4820 mm) and annual temperature (22°C). To analysis the diurnal, monthly and yearly variation of wind speed and visibility, the collected data at the Zabol meteorological station were obtained from the Iran Meteorological Organization for study period. DDI (Dusty Days Index; the days with wind speed more than 15 m/s and visibility less than 1000 m) and DSI (Dusty Index) were applied in this study to analysis the monthly and yearly frequency of dust storms during 1991-2018. Furthermore, the hourly concentration of PM10 was received from the meteorological and environmental stations of the respective centers during 2013-2018.

The results show similar diurnal, monthly and yearly patterns of wind speed, visibility and PM10 variation in all months during study period. The highest PM10 concentration and lowest visibility were observed at 10:30 am in accords with highest wind speed. The lowest PM10 and highest visibility occurred at 7:30 pm in accord with lowest wind speed. The greatest values of DDI, DSI and PM10 were observed in June. Furthermore, the greatest values of DDI, DSI and PM10 were observed in 2001 during study period. The period of 1999-2004 is dusty than the periods of 1990-1999 and 2005-2018 as DSI is 14, 174 and 66 days respectively. A strong correlation was observed between wind speed and visibility, wind speed and PM10 concentration and, visibility and PM10. These result show that either PM10 concentration or visibility depend on wind speed. Furthermore, a positive relationship was observed between PM10 and DSI and DDI.

In stud period, the Sistan region is dusty than other regions of Iran due to having greater frequency and intensity of dust storm. As the dustiness of Sistan is highly dependent on the situation of Hamoun lake, lake recovery is critical to reduce the intensity and frequency of dust storms.

Freshwater crisis and soil salinity are the most important factors that limiting agriculture in arid areas. In these conditions, cultivation of medicinal plants with considering environmental aspects can be an intelligence strategy for these areas. For this purpose, a field experiment with four treatments and three replications was conducted in randomized complete blocks design in Zahak city during 2016-2017. The treatments were consisted of full irrigation with fresh water (F.FI), partial root zone drying with fresh water (F.PRD), partial root zone drying with saline water (S.PRD) and partial root zone drying with saline and fresh water (SF.PRD). The highest values of plant height (46.1 cm), number of umbel per plant (42), number of branches per plant (10), 1000-seed weight (0.86 gr) and seed yield (293 kg ha-1) were observed in F.FI. There were non-significant differences between F.PRD, FI and SF.PRD in most traits. Results illustrated that application of PRD with alternate fresh and saline water was the best option for decreasing fresh water usage in arid climate of Sistan region.

Potassium occurs in soils in various forms. The behavior of potassium in soil can be difficult due to its interaction with the intrinsic properties of the soil. Although most soils contain large quantities of potassium, but most soils are not able to provide proper amounts for plant nutrition, so that the equilibrium reactions occurring between different forms of potassium have a profound effect on potassium nutrition. This research was carried out with the aim of investigating the relationship between different forms of potassium (soluble, exchangeable, non- exchangeable and construction) with physical and chemical properties of soils in citrus areas of Iranshahr and Khash towns in Sistan and Baluchestan province.

First, according to previous studies, 30 samples of soils in Iranshahr and Khash towns with different characteristics. Then samplings were taken from depths of 0 to 30 cm. Physical and chemical properties of soil and various forms of potassium (soluble, exchangeable, non- exchangeable and construction) with total potassium were measured and relationship between different forms of potassium with each other and physical and chemical properties of soil were investigated.

Soils were in general light in texture, non-saline and calcareous. Organic carbon values in soils ranged from 0.6 to 1.6 percent, cation exchange capacity ranged from 7.0 to 10.5 centimoles per kilogram, and the pH ranged from 7.0 to 7.4. The amounts of different forms of potassium in the city of Iranshahr, potassium soluble ranged from 1.4 to 20.4, exchangeable from 122 to 315, non- exchangeable from 177 to 388, construction from 5709 to 13987 and a total 8420 to 14200 mg kg-1 soil. In Khash city, potassium soluble ranged from 5.7 to 14.3, exchangeable from 129 to 273, non- exchangeable from 293 to 493, construction from 5412 to 14085 and a total 9892 to 13850 mg kg-1 soil. Correlation test showed that there was a significant positive correlation between soluble potassium and sand (r= 0.5*) and negative correlation with silt (r= -0.5*). There was a significant positive correlation between exchangeable potassium and organic matter (r= 0.7*), significant positive correlation with clay (r= 0.5*) and significant positive correlation with cation exchange capacity (r= 0.7*). Between non- exchangeable potassium and calcium carbonate there was a significant negative correlation (r= -0.8*). Significant positive relationships among various fractions of soil K indicated existence of a dynamic equilibrium between different forms of K.

The amount of potassium available in the plant (soluble, exchangeable, non- exchangeable potassium) is good in citrus growing areas in Sistan and Balouchestan province of Iranshahr and Khash, and therefore does not require potassium fertilizers in these two regions