Considering the fact that evaporation affects the planning and operations of water resources as a key process in the hydrologic cycle, predicting its magnitude and patterns, particularly in arid, semi-arid, and hyper-arid environments such as Sistan plain (in northern Sistan-Baluchistan Province, Iran) is of great importance. On the other hand, as accurate estimation of Pan evaporation is regarded as one of the main aspects of water management in such regions, it is crucially important to accurately simulate the pan evaporation based on the available regional meteorological parameters. Therefore, this study sought to investigate the capabilities of soft computing techniques for estimating monthly evaporation in Sistan plain. The results of the study could be helpful for the management of water resources in the Sistan area, allowing the policymakers to develop future projects of water resource management/development plans for the region based on Evaporation estimations.

 various meteorological parameters, including maximum, minimum, and average temperature rates, relative humidity, wind speed, and precipitation rate were used to predict monthly Evaporation using the consistent and uninterrupted historical time series data (1994–2021) collected from three meteorological stations (Zabol, Zahak, and Chahnimeh).
The main purpose of this study was to assess the performance of a soft computing model in simulate pan evaporation. To this end, nine soft computing models, including Model Tree (MT), Random Forest (RF), Support Vector Machines (SVM), Bayesian Ridge Regression (BRR), Gaussian Process (GP), Extreme Gradient Boosting (XGB), Artificial Neural Network (ANN), and Multivariate Adaptive Regression Splines (MARS) were used to predict evaporation at the meteorological stations selected for this research.
On the other hand, the model’s performance was assessed using statistical measures, including coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and Taylor diagram. Moreover, to construct predictive models, the dataset was divided into training (70%) and validation (30%) data. Then, eight combinations of input parameters were selected for Zabol and Zahak sites based on the Pearson correlation coefficient between the individual input parameters and evaporation. Finally, the best input combination and the optimal values for different models were determined using the R programming language.

 The different input combinations were determined for the two sites independently based on the inclusion of the weather parameters with the highest coefficient Pearson with evaporation. Then, each model was run using various fixed sets of parameters. For the Zabol station, the minimum temperature rate indicated the greatest correlation coefficient with (0.96), followed by average temperature (0.95) and smallest by rainfall (-0.42). It was also found that the outputs of Zabol and Zahak stations were very close and similar to each other, which could partly be attributed to the proximity of the two stations and their same topography and climatic conditions in the Sistan plain.
On the other hand, the results of assessing the models’ performance indicated that in the validation stage, MT (whose R2 = 0.97 and RMSE=57.3) delivered the best performance in Zabol station under Scenario 1, RF (with its R2 and RMSE being 0.98 61.7, respectively) performed the best under Scenario 2, MT with its R2 and RMSE being 0.97 and 61.27, respectively, showed the best performance under Scenario 3, the ANN and MT (whose R2 and RMSE reported as being 0.96 and 59.9, respectively) put in the best performance under Scenario 4 , and RF with R2 = 0.97 and RMSE=59, 59.24, 58.23, and 58.3 delivered the best performance under scenarios 5 to 8, respectively.
Moreover, the results suggested that adding the number of input variables to the models made no difference in their accuracy level. It was also found that out of eight scenarios investigated in this study, the RF model delivered the performance under five scenarios (2, 5, 6, 7, and 8), and that the MT performed well under two scenarios (1 and 3). Therefore, RF and MT could be introduced as the best soft computing models for simulating and estimating the pan evaporation of the Sistan plain.

 The results showed that with increasing the input of variables to the model, there was not much difference in the accuracy of the models. For example, R2 of scenario 1 with only the minimum monthly temperature input is equal to scenario 8 with eight inputs equal to 0.98 in the validation stage. Therefore, the findings showed that the model with only the minimum monthly temperature input has the same performance as the model with eight inputs The main contribution of this study was introducing a soft computing model to accurately estimate the pan evaporation of the Sistan plain using a meteorological parameter (minimum monthly temperature).

In the third millennium B.C., the inhabitable zones in the southern part of Sistan Plain were confined to the deltaic lands around the Rud-i Biyaban River. One of the main climatological characteristics of that time was the abundance of water resources in the Hilmand basin. The formation and dynamism of human settlements in this region have always been related to the water fluctuations of the Hilmand River, so that a shift in the water courses has always led to changes in human agglomerations. The main purposes of this research are first of all, to find out more about the vegetation around Tepe Taleb Khan and second, to provide more information on the use of these vegetal resources by the local inhabitants in that era. Two phases of archaeobotanical analysis are included in this research: namely field operation (sampling and extracting techniques of plant remains), and laboratory studies on the data coming from the sixth season of archaeological excavations at Tepe Taleb Khan. These studies have been done on the plant remains obtained from 25 samples related to various archaeological contexts such as soil deposit, ashy layer, burnt soil, fireplaces and their contents, plaster and soil deposit, msoil and debris deposit, soil and ash deposit, mudbrick debris and floor (dated back to the third millennium BCE/2500-2300 BCE). By flotation of 316 liter of sediments, collected from these contexts, approximately 1900 mL plant remains including seeds, rachis segments, fruits and charcoals were extracted. The carpological studies on 2045 seeds, rachis segments and fruits, led to the identification of various vegetal groups with different relative frequencies in the archaeological contexts including cultivated plants (such as cereals, oil seeds, fruits, cucurbits, cultivated pulses) and non-cultivated plants (like wild fruits, wild pulses, wild grasses and wild plants). The results indicated the presence of different crops such as emmer wheat (Triticum dicoccum), free threshing wheat (T. durum/aestivum),  bread wheat (T. aestivum), club wheat (T. compactum), spelt (T. spelt), free threshing barley (Hordeum vulgare var.nudum), lentil (Lens culinaris), vetches (Vicia), vetchlings (Lathyrus), pea (Pisum sativum), flax (Linum usitatissimum), grape (Vitis vinifera) and cucurbits (cucurbitaceae), testifying a subsistence economy based on agriculture. At the same time, anthracological studies done on 948 charcoal fragments led to the identification of diffrent trees and shrubs like goosefoots (Chenopodiaceae), tamaris (Tamarix sp.), palm (Phoenix dactylifera) and poplar (Populus sp.). According to the previous archaeobotanical evidence at Shahr-i Sokhta, these taxa are present in the anthracological spectra of the Bronze Age vegetation of the southern Sistan Plain. Based on the archaeobotanical data, Tepe Taleb Khan inhabitants used goosefoots and tamaris wood to meet their fuel needs due to the soft texture and rapid flammability of these species. Nowadays, due to the unfavorable environmental conditions of Sistan, tamaris and goosefoots (as xeric and halophytic plants) are the dominant species in the region. The continued presence of these plants from the third millennium B.C., up to now indicates more or less the durability of ecological conditions in the region. The poorness of current vegetation in Sistan has undoubtedly been influenced by environmental and human factors over the time.

 With recent advances in satellite remote sensing productions in past few decades, several indices have been provided for the study of vegetation dynamics, and especially for the assessment of drought impacts. Among these, two vegetation indices -Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) - have gained the attention of various researchers. Therefore, the present study aims to investigate the reaction of these two vegetation indices (i.e. NDVI and EVI) to dry and wet years in a dry plain in Iran (i.e. Sistan plain in eastern Iran).

To assess the sensitivity of these indices to dry and wet years, two different databases were required. First, NDVI and EVI image base received from Terra satellite (MODIS sensor) for April, May and June 2000-2014, and downloaded from EOS website. Second, daily data base of Zabol synoptic meteorological station (for a statistical period of 30-years 1985-2014) received from Iran Meteorological Organization. After data acquisition, separate vegetation dynamics maps (for April, May and June) were produced for the study area based on the information derived through processing of MODIS sensor images (Terra satellite) using NDVI and EVI. Effective drought index (EDI) was used to determine the frequency of dry and wet years in Sistan plain.

Mapping of vegetation dynamics based on images received from MODIS sensor (Terra satellite) for a 15-year statistical period (2000 to 2014: April, May, and June) indicated that NDVI and EVI had significant differences in exhibiting the dynamics of vegetation in the study area. These differences were obvious in areas with average amount of vegetation (0.4-0.5 in both NDVI and EVI) and also in areas with sparse dispersed vegetation (0.3-0.4 in both NDVI and EVI). In average levels of vegetation, total area of vegetation calculated by EVI is​​ much higher than what is calculated by NDVI, while in sparse and dispersed vegetation, total area of vegetation calculated by NDVI is almost higher than EVI. Subsequently by selection of a dry (2010-2011) and a wet year (2005-2006), we compared changes in total area of vegetation (average and sparse) calculated by NDVI and EVI. Regarding the response of these two indices to dry and wet years, it was concluded that NDVI shows a better and more logical response during droughts, while EVI provides better results in wet years. However, it should be noted that the mean annual precipitation of Sistan plain is so low (59 mm per year) and its evapotranspiration is so high (4800 mm per year) that precipitation does not play a significant role in vegetation dynamics of this plain. Therefore, water flow in Helmand River, which is the lifeblood of this desert, is much more important than this limited precipitation in Sistan plain; hence, we can conclude that meteorological drought monitoring indices cannot reflect the relationship between drought and vegetation dynamics in Sistan plain, and this makes it difficult to compare NDVI and EVI in the region.

In general, it can be concluded that NDVI is a more suitable index for dynamics of vegetation in plains such as Sistan, whose life depends not on precipitation but on water running in the river. Because of the computational nature of EVI, it responds better in areas with dense vegetation. According to the vegetation type obtained from MODIS sensor images and field visits, NDVI is a better index for these types of plains.

The aim of this study was investigating the effects of incoming floods from Afghanistan on the quantitative and qualitative changes of groundwater resources in Sistan plain. For this purpose, first by determining the direction of flood flow in Sistan plain, 16 wells drilled near the flood flow were selected. Estimates of reservoir volume changes as well as comparison of rainfall in the region in the same period. In the following, Using groundwater balance equations and single hydrograph equations before and after flood entry, quantitative changes in groundwater resources in Sistan region over a period of 4 years (1394-1398) were investigated. The qualitative changes in aquifer with sampling of observation wells during the balance and investigation of time changes in water quality parameters such as electrical conductivity (EC) and acidity (pH) was analyzed. The data shows that the floods increased the water level in the wells by an average of 0.39 meters the process of change has a high correlation (R² = 0.85) with the volume of floods in the region. Also, the hydrographic survey of the plain unit indicates significant changes in groundwater level before and after the flood in the area. As, during the 4-year period, the average water level is 2.16 meters higher than before Floods have increased. With the flooding amount of 20.66202 million cubic meters during the balance period, the reservoir volume has been naturally increased. Due to the low rainfall in the region, the nutrition of groundwater aquifers is affected by low rainfall.

The occurrence of drought in the Sistan region and the drying up of the Hamon Lake, as well as the 120-day winds, have created suitable conditions for wind erosion and caused a lot of damage to the natural and human life of the region. These factors have caused the movement of loose sand in the region at a high speed and the sand dunes to expand a lot. Field studies indicate that during frequent droughts in the Sistan region, the movement of sand dunes has been so great that it has caused the burial of a large number of rural houses and the loss of agricultural land, which has led to the migration of the natives of the region in recent years. has followed The dangers caused by the displacement of sand dunes at the level of villages include threats to the health of residents, burial of villages, destruction of soil and public infrastructure, etc. Several factors such as strong and permanent winds, the low slope and low complexity of the plain, the fineness of the soil, successive droughts and the lack of vegetation play a role in the amount of sand movement in the Sistan plain. The aim of this study is to investigate the changes in the sand dunes of Sistan plain by using time series mineralogy and using Landsat satellite data and to propose some solutions to reduce the movement of sand dunes and in turn, reduce its destructive effects on the lives of the residents of the area. The research was conducted using Landsat satellite images with resolution of 30 meters from 1997 to 2020 to investigate the changes of sand dunes in the Sistan plain. According to the results, the extent of sand dunes in August increased from 8.23% in 1997 to 11% in 2020, and in July from 8.83% to 12.9% of the total area of the studied basin, which is almost the trend. It shows a significant increase. Also, the changes in the area of Hamon Lake from 1997 to 2020 show that the lake's water volume has decreased greatly, and this indicates that the expansion of sand dunes in different years is directly related to the changes in the lake level in different times, and the reason for the displacement of sand dunes is the erosive winds of the region. Which have a north to northwest direction with an angle of 330 to 360 degrees (the 120-day wind of Sistan) and the most important facies of harvesting are the saline and puffy areas of the Hamun lake bed and the northern plains.On a global scale, the occurrence of storms and floods are among the most destructive natural hazards (Vesterb and et all, 2022), as most accidents are caused by these two hazards (Yakshin and et all, 2022). Hazards mean natural events that potentially cause danger to humans and what is valuable to them. Hazard has the potential to cause damage, for human health, human, economic, educational activity, damage to property, damage to the environment, loss of flora and fauna, pollution and insecurity of natural disasters are dangerous (Rahimi Harabadi, 2019). The active and dynamic nature of the sand dunes causes the movement of sands towards the settlements to be more frequent and creates many dangers such as threats to the health of residents, burial of villages, destruction of soil and public facilities, and causes financial losses, migration of residents, and finally, a human disaster. (Jadidoleslami, 2019). Therefore, in order to plan fundamentally to solve the problem, it is necessary to analyze the origin of the sands, the role of the morphometric parameters of the sand dunes in the extent of their displacement, and considering the fact that the area is residential, the risks of the sands are identified and solutions are provided to reduce the risks. Sand dunes in the realm of the wind process are considered to be one of the most dynamic geomorphic phenomena on the earth's surface, which are affected by the characteristics of wind speed, direction and frequency on the one hand, and on the other hand by the characteristics of the earth's surface and sedimentary materials (Abbasnejad and Zahab Nouri, 2013). The results of studies on a scale of 1:250,000 show that the sand dunes of Iran include 11 sand seas and 39 hill fields that cover approximately 1.1 million hectares (Abbasi et al., 2019). Sandstorms are one of the most important weather phenomena that spread in many deserts and dry areas of the world, and in recent years, they have received a lot of attention, and every year these incidents cause a lot of damage and casualties in all parts of the world.In order to carry out this research, first, with direct field observations and field operations, to determine the harvesting areas, sampling was done from the transport areas and possible harvesting areas, and based on the mineralogical characteristics and the examination of the genetic relationship of the samples, the primary origin of the sediments was investigated. In order to identify the harvesting areas, sampling was done from the place of accumulation of sands, from different points of possible harvesting areas, and the genetic relationship (similar properties) of the three areas (harvesting, transportation and sedimentation) was investigated through the physical and chemical analysis of the sediments. Took Also, four synoptic stations (Zabol-Zahak-Hirmand-Hamon) were also studied.According to the presented results, the level of heavy metals in the air of Enqelab Street is not hazardous to the health of the residents. Therefore, there is no need to spend enormous expenses in this area. Nevertheless, the health of permanent and temporary residents is threatened by chromium and arsenic due to their high rate of carcinogenesis. The outcome of these investigations indicates that despite recording few different values in some places, the air pollution levels are equal in whole the area, from Enqelab Square to Imam Hossein Square. However, the air pollution level of ValiasCr rossroads is relatively considerable. This difference only has resulted from high volume of traffic in the crossroads. Unfortunately, traffic of students in this area is so heavy that solving Valiasr Crossroad’s traffic issues are considered as an important priority.