نشریه مهندسی اکوسیستم بیابان
پیاپی 27 (تابستان 1399)

Drought is an atmospheric phenomenon that affects different components of the environment. Caused mainly by the lack of precipitation, It is considered as the most dangerous natural phenomenon. All regions of the world may occasionally be affected by droughts, but it is more common in areas that are climatically and accidentally influenced by different climatic systems. Although groundwater resources are normally affected by drought, they are not much accounted for in relevant studies. Delayed meteorological droughts in one place could lead to hydrological droughts that are caused by stress to water resources. Groundwater resources are among the environmental phenomena which are highly affected by drought. In the last decade, numerous studies have been conducted on meteorological and groundwater droughts, indicating a significant relationship between meteorological and hydrogeological drought indices. In arid and semi-arid regions, reduction of the level of the groundwater table water and degradation of its chemical quality (due to increased solute concentration) play a key role in causing secondary soil salinity, surface water salinity, soil fertility decline, etc. Considering the importance of meteorological and groundwater droughts in recent decades and their impact on the salinity of Yazd Ardakan plain and consequently the vegetation of the region, the present research is a prospective study that uses data mining methods for salinity modeling. It was conducted over an 18-year common statistical period (1998-2016). So far, the relationship between drought and soil salinity has not been investigated in this plain.

The study area was Yazd-Ardakan plain. Having an area of 15950.70 km, Yazd-Ardakan plain is located in the northern part of Yazd province and covers roughly 24.9% of the total area of the province. The average precipitation at many intersections of the plain is less than 65 mm per year. Yazd-Ardakan plain includes vast cities such as Mehriz, Yazd, Ashkezar, Meybod, and Ardakan. The plain is bounded on the west and southwest by Shirkouh Mountains, and on the east by Kharnaq Mountains. To perform this study, precipitation data were first collected from the relevant database of the Weather Meteorological Organization. Moreover, the groundwater data were gathered from 38 wells which were located in the area which belongs to the Organization of Regional water of Yazd. Having carefully examined the data regarding 18 years of precipitation in the region (1376-1394), it was considered as a common statistical period for all the stations from which the required data were obtained. Standard Precipitation Index (SPI) and the Groundwater Resource Index (GRI) were used to assess the meteorological drought in the region. Salinity data were also obtained from 84 sites of Yazd-Ardakan plain in 2014 from the Soil Database of the region. Then, the weighted distance interpolation method was used to map drought severity in the ArcGIS software. Satellite images were also used to extract the auxiliary parameters. Landsat 7 and 8 satellite bands for the summers of 2006, 2010, 2014 (bands 1 to 5, and bands 7) were downloaded from the USGS site. This study sought to investigate the temporal and spatial variations of drought and their effect on soil salinity in Yazd –Ardakan plain. The vegetation index (NDVI) was also obtained, using the aforementioned images. Then, using the artificial neural network to find the relationship between the soil salinity parameter in 2014 and the environmental variables (satellite image data, SPI and GRI drought indices, vegetation index, and digital elevation model), the soil salinity was determined for the study area. Moreover, soil salinity maps were prepared for the years 2006, 2010, and 2014. To model the salinity, the optimal structure of the network was determined after the initial preprocessing of raw data.

Having studied the SPI and GRI zoning maps of the year 2006, the highest drought rates were found in both the central and southern plains. The mean SPI index was 0.08 and the GRI index was 0.21. In terms of the SPI index, drought was almost normal and the GRI status was mild. In 2010, the highest meteorological drought in the eastern part of the Yazd Ardakan plain was reported as being -0.04, indicating an almost normal type of drought this year. The average Groundwater index in the central, eastern, and northwestern parts of the plain was 0.49, which is considered as a mild groundwater drought. In 2014, the highest meteorological drought was observed in the northern and southern parts of the plain, and the highest rate for the groundwater index was found in the northern part of the basin. The average SPI and the GRI indices for the same year were 0.07 and 0.52 respectively, which are considered as normal drought for the plain. The vegetation index map showed the average vegetation index to be 0.28, 0.30, and 0.29 for 2006, 2010, and 2014 respectively. Soil electrical conductivity in 2014 varied from 35 to 197.30 dS/m and its coefficient of variation was 121.2%, indicating a high variability of salinity in the study area. The model successfully predicted the salinity value with acceptable accuracy. Consequently, salinity values for 2010 and 2006 were predicted, using the neural network model. The average salinity of the region was 56.17, 58.73, 59.48 dS/m in 2006, 2010, and 2014 respectively, suggesting an increasing trend in soil salinity.

The results showed that the average salinity in the area had been increasing over the three years studied, reaching an average of 56.57 dS/m in 2006 and 59.58 dS/m in 2014. Most of the soil salinity in 2014 was found in the northeast and east of the basin, and parts of the center were saline from the north to the south. The results also indicated that the neural network method could well predict salinity values in previous years, using input variables such as satellite imagery, digital elevation model, meteorological and groundwater drought indices, and vegetation index. As found by the correlation reports, it could be concluded that the salinity increased in the area with increasing severity of meteorological drought and consequently increasing groundwater drought and decreasing vegetation.

All watershed-related issues including water management, drought, and other matters should be addressed in an integrated, simultaneous, and interconnected manner based on a comprehensive management model. One of the causes of intensification and development of dust centers Khuzestan province, especially throughout the last decade, has been the occurrence of successive droughts in the upstream and downstream of those basins including the outlet area of the three Great Basins, Great Karun, Karkheh, and Jarahi-Zohre.Drought profiles were used to evaluate the potential spatial and temporal variations of drought and wet events. Moreover, SPI and SPEI drought profiles were also applied. In the year 2008, a severe and widespread drought occurred in Iran. A large drought cycle occurred in the three studied basins from 1986 to 2017. Water supplies of Khuzestan dam reservoirs have been decreased by 65% over the last decade. Water reserves in Dam Province reservoirs have decreased by 58% while the drought peaked in 2017. Drought indices were used to evaluate the severity, frequency, duration, and magnitude of the drought. To identify the intensity and magnitude of the drought, indices of meteorological drought occurrence could be divided into SPI indices in terms of speed, and SPIE indices in terms of accuracy and temperature conditions considered via the evaporation parameter which has risen due to increasing global temperature.

Drought indices are used to assess the quality and quantity of drought phenomena. These indicators have different applications depending on the area and purpose of the study. To investigate the trend of decade-long drought changes in the Karun watershed, 44 * 44 km grid precipitation data have been used. Since in addition to precipitation values, evapotranspiration values are required to calculate SPIE indices, evapotranspiration values were, in this study, calculated through mean temperature data and the Torrent-White method. Temperature, evapotranspiration, and transpiration data were also interpolated from daily synoptic and meteorological climatology data and Iranian Water Resources Management Meteorological and Evaporation stations. Data were extracted and analyzed for a 50-year statistical period, and the SPI and SPEI drought indices were collected for each decade. Drought and wetland indices for 79 points were analyzed by bad zone kriging method and spatial distribution of drought and wetland potentials based on the two indices mentioned.

According to the SPI drought index, during the first decade, an extreme and severe drought occurred at the boundary between the two surgical watersheds of Jarahi-Zohre and Karoun Basin, especially in the upstream of the drought basin. Large sections of the two basins were found to be affected by moderate to weak drought, whereas in the Karkheh Basin, especially at its wetlands, extreme drought had occurred. According to the SPEI index, drought intensity in all basins was low. Taking the SPI index into account, during the second decade all three watersheds mostly experienced moderate to weak droughts, and large parts of the watersheds had normal and near-normal conditions. But according to the SPEI drought index, due to the moderating role of temperature in this decade, most parts of all three basins had normal conditions, and the lower part of all three basins faced weak humidity.Within the third decade, all three basins faced humid-to-normal conditions on both indices. In this decade, the range of dust bogs faced weak to normal-humid conditions. In the fourth decade, the basins had near-normal conditions based on SPI. Large sections of the Karun and Karkheh basins had been mildly degraded based on the SPEI index, which may indicate a gradual increase in temperature and evaporation. According to the SPI index, moderate and weak droughts affect most of the area in the fifth decade, with severe drought in the downstream of the Karkheh basin and two core upstream of the Karoun Basin in the Jarahi-Zohre watershed where most foci Walnut specks of dust are located due to the rising temperatures in the SPEI index over a large area of the three watersheds which had been hit by severe and very severe drought. Accordingly, as found by the SPEI, more than 95% of the watersheds faced severe droughts in this decade.

Drought is rooted in the general circulation of the atmosphere, and the effects of climate change have increased in recent decades as global warming has intensified regional-scale droughts. Increasing atmospheric CO2 causes global warming which in turn leads, according to the findings of many studies, into wider and more severe droughts. As a natural and inseparable part of the climate, drought may occur in any climate, desert, or even forest. This natural disaster is particularly severe in arid and semi-arid climates with severe constraints on water resources. In the first two decades of the study period when the temperature did not increase significantly, the drought events were, based on the SPEI index, less severe in all basins than the SPI index. However, the downstream of the watersheds and the range of dust bins were much more intense, particularly in terms of the SPEI index, in the last decade due to the increase in temperature and consequently the increase in evapotranspiration and drought intensity.

Water is crucial for survival and development. Long-term access to water resources provides the ground for scientific and technological developments. Geographically, Iran is located in an arid part of the world. Water scarcity and mismanagement could create a water crisis in the world, and that droughts may exacerbate different environmental and socio-economic aspects of life. As revealed in a report issued by the United Nations’ Environment Programme, 80 percent of the world’s population currently live in places with no water security, and that 1.5 billion people throughout the world are facing anhydrous risk. As Iran has, in recent years, been affected by drought, access to water for agricultural, industrial, and drinking purposes is now of great concern for inhabitants of the country’s drylands. According to the reports issued by the World Bank, mismanagement and inefficiency of irrigation systems are the main reasons for water insecurity in the world. In recent years, mismanagement of available water resources in the arid region has followed by the destruction of natural ecosystems that are dependent on water resources. As a result, changes in land use over a long period and the expansion of desert areas have led to environmental degradation. Sistan is located in an arid region in Iran where difficulty to access surface water resources due to drought in recent years has brought about environmental degradation in the region. Low precipitation (50mm), high temperature (48o), high transpiration (5000mm), and 120-day winds are among the specific climatic conditions that characterize the region. Sistan is also hit by floods for a limited period when the Hirmand river flows as a result of torrential rainfall in Afghanistan, providing the required water for its 120,000 ha agricultural land.

This study sought to investigate the environmental impacts of hydrological drought and traditional utilization of floods streams on Land Degradation and Desertification in Sistan. Located at the southeastern border of Iran and Afghanistan, Sistan forms part of the Dasht-e-Lut desert land, possessing an extreme arid climatic regime. The region is a roughly flat and featureless arid plain with an average height of 475–500m ASL in its eastern parts. To realize the purpose of the research, the hydrological drought status of the Hirmand river was investigated. Using the Streamflow Drought Index (SDI), the hydrological drought was then calculated for 22 years. The distribution and utilization of flood streams in the Sistan area were examined via Infield operation. On the other hand, the Irrigation system of the area was examined through library studies and the factors affecting the circulation of surface water resources were identified. Weighting these variables via Analytic Hierarchy Process (AHP) and integration of data layers, access priority map of sectors to the water resource was estimated. The land-use map of the years when the hydrological drought occurred and didn’t occur were extracted through the Landsat satellite images of the years 2002 and 2018. The identification of changes in the region was then carried out by assessing the accuracy of the images and their classification, using the comparison approach. Moreover, the land-use change maps were overlapped whit the access priority map of sectors to the water resource to investigate the effect of the utilization method on desertification and land degradation.

The findings of this study showed that the severity of drought in Sistan has increased over the past 18 years. On the other hand, the findings for the areas with years of hydrological drought indicated that barren land had increased by 41 percent, and that agricultural, residential, and water zone areas had decreased by 61, 31, and 84 percent respectively. It was also found that the distribution and transmission of incoming floods to the Sistan area lead to limited access to these surface waters in areas such as Hirmand (Gregory sector), Nimroz (post ab sector), and Zabul (Central sector) because of their seasonality and uncertain continuity. The most land-use changes were found to be the conversion of water zone, (equivalent to 12581 hectares) agricultural lands (equivalent to 3073/22 ha), and poor rangelands (equivalent to 4495/8 hectares) into barren lands where access to floodwaters is limited.

This study proved the clear environmental effects of hydrological drought and traditional utilization of water resources on the Sistan region. Reduction of streamflow in the Hirmand river due to the recent occurrence of hydrological droughts and limited access to water resources because of the irrigation system and the traditional methods of utilizing water resources led to the land-use change as a result of the destruction of water-dependent ecosystems, increasing the desert areas and critical points in the Sistan area accordingly. Having said that, breaking the drought, improving environmental conditions, and using efficient production methods require new approaches for proper utilization and management of water resources in the Sistan area.

SWAT is a continuous-time model that operates on a daily time step at the basin scale. The objective of such a model is to predict the long-term impacts of management and the timing of agricultural practices within a year (i.e., crop rotations, planting and harvest dates, irrigation, fertilizer, and pesticide application rates and timing) on large basins. It could, at the basin scale, be used to simulate the water and nutrients cycle of landscapes whose dominant land use is agriculture. It could also help assess the environmental efficiency of best management practices and alternative management policies. The SWAT model uses a two-level disaggregation scheme: a preliminary sub-basin identification is carried out based on topographic criteria followed by further discretization, using land use and soil type considerations. Areas with the same soil type and land use form a Hydrologic Response Unit (HRU), a basic computational unit assumed to be homogeneous in hydrologic response to land cover changes.The development of the digital computer has added a new dimension to hydrology. Previously, finding solutions for different problems took hours with a pen and pencil method, but now it takes seconds with modern computers. Moreover, much more complex methods of analysis are now feasible because of the speed of the solution-finding provided by the computer. The impact of the computer has been particularly great in the area of rainfall-runoff modeling. As flood routing and unit hydrograph analysis are mathematical modeling’s, surface-water hydrology is, historically, concerned with modeling. Due to the climate type and the spatial and temporal inconsistency of rainfall in Iran, large floods cause many damages in different parts of the country annually, as the Mediterranean climate and different weather conditions throughout a year provide the ground for the majority of short-term atmospheric rainfall.

Karkheh Basin is one of the main watersheds of Iran which has a Mediterranean climate whose level increases during the spring due to simultaneous rains and snowmelt. As one of the most important hydrological processes of the watershed for better understanding the hydrological issues of flood control structures for long-term planning, applying best management practices and making better use of their potentials, Runoff simulation plays an important role in water resources studies. Thus, to calibrate the model, select sensitive parameters were used in the sensitivity analysis step. Having imported the sensitive parameters into SWAT-CUP software, they were repeated 500 times with the SUFI2 algorithm, and finally, the optimal value for each parameter was determined.

At Hamidiyeh station, the Nash Sutcliffe coefficient was -0.19 and -0.04 in both calibration and validation periods, respectively, and was 0.76 and 0.77 in Chamangir Station, respectively. The coefficients of determination for the Hamidiyeh station in the calibration and validation periods were 0.02 and 0.22, respectively, and for the Chamangir station, they were 0.88 and 0.75, respectively.This study investigated simulated runoff, using the SWAT model based on the meteorological data regarding the Karkheh watershed. A comparison of simulated runoff results with observational runoff at the hydrometric stations was performed automatically by the SWAT_CUP software package SUFI2 algorithm. Correlation between observed and simulated data was calculated based on the Nash Sutcliffe coefficient and the determination coefficient at different stations of the basin. Nash coefficient - Sutcliffe and coefficient of determination at all hydrometric stations except for the five stations which differed in their calibration and validation periods, were found to be close to their optimum values.

The coefficient - Sutcliffe of the other 6 stations was more than 0.5, indicating that the model was capable of simulating runoff. In the mirage stations of Sarab Seyed Ali, Pulchehr, and Noorabad, the SWAT model failed to simulate runoff well, which could be due to the location of these stations in the elevated areas of the basin and its branches that were snowy. The lack of proper distribution of meteorological stations in these areas makes the model unable to simulate well the snow runoff. In Hamidiyeh and Pai-Paul stations, the SWAT model was could not establish a reliable relationship between the observed and simulated runoff due to the impact of the construction of the Shahid Abbaspour Dam on the river flow hydraulics.

The times of seed collection and storage have significant impacts on seed viability. This information is vitally needed for the management of seed production stations.

Effects of two methods of cultivating maternal plants (irrigation or rainfed), five times of seed harvesting (early September, November, October, December, and January), two seed coat treatments (seed coat removal or control), and two types of seed storage (5°C and room temperature) were studied on seed germination of Salsola rigida, a semi-shrub species found in Neyshabur Seed Station, Khorasan Razavi Province. In each experiment, four replications of 25 seeds were tested in a germinator 14/10 hours of day/night. The germination test lasted for 20 days, and the total experiment duration lasted about 5 months. Seed germination percent was initially increased by increasing time from September to October. however, it was reduced towards zero in December and January. 

it was found that methods of maternal cultivation, time of seed harvesting, and seed storage conditions had significant effects on seed germination of S. rigida. The seeds which were collected from the rain fed cultivation and those which were kept in a cold room (4 ℃) showed higher germination percentages than those collected from the irrigated cultivation and ambient storage.

According to the results of this study, it is suggested that Salsola rigida seed be collected from Ashgabat station in Neyshabur in early November, and if they need to be stored, they should be kept under cod room conditions (4 ℃).

One of the most important environmental problems in the south of Kerman is the influx of fluids into man-made structures and residential areas, requiring careful consideration and a practical solution. Ammodendron Persicum is a local species of Divdal, firewood, lumber, sand, tree, sand, and thistle and is native to Qaen and Taybad in Khorasan province. Being a sub-family of the butterfly (Papilionaceae), it belongs to the legume family (Fabaceae). Divdal is a shrub-like species with a height of 6.8 m whose critical activity generally begins in the second half of March. Moreover, it flowers in mid-May and sows until late June. It generally grows in a rainfall rate of 70 mm, but the species grows well in 150 mm rainfall, being highly drought-resistant as a result. Horizontal and vertical expansion of the roots of this plant is one of the reasons for its drought resistance. Divdal regeneration in the arena occurs in the form of seed and branch. It has a particular dependence on anthropogenic sand, as it only germinates on these habitats. Overall, due to the Divdal ecological features, the species is suitable for germination on sand dunes, reduces wind speed, and has good prospects for use in other areas.

To identify susceptible areas of Divdal species (Ammodendron persicum) in southern Kerman through the Hierarchical Analysis (AHP) method, all factors affecting Divdal species growth were identified as layers of precipitation, altitude, geomorphology, Salinity, and land use (Fig. 2). Then, all layers were processed and evaluated in the same GIS environment using the same reference system with the same scale and the same cell size. To determine the significance of the indices, the relative importance of each criterion was determined via a hierarchical analysis model, using the Expert Choice software. Each criterion was then fuzzed by ArcGIS software and was numerically zero to one. Next, by integrating the AHP and Fuzzy models, all the standardized layers in each of the weights were obtained from the hierarchical analysis model. They were multiplied and thus transformed into fuzzy weighted layers. In the next step, multiplication and fuzzy multiplication operators were performed on the layers and overlapping layers, and finally, by fuzzy map classification, the final map of Divdal species susceptible areas was prepared.The hierarchical analysis process begins by identifying the elements of decision making and prioritizing them. In the placement process, evaluations are made after defining the overall goal and identifying the criteria that are effective in reaching the right place.

In this study, the results of the AHP model showed that out of the five main criteria in locating Divdal species susceptible areas, land use, precipitation, elevation are ranked among the top three with their relative importance being 0.38, 0.25, and 0.18 respectively. Also, geomorphology and salinity ranked fourth and fifth in this regard, with relative importance reported as 0.11 and 0.08, respectively.

Geomorphologically speaking, the Divdal species prefers mostly plain as its growth site. Moreover, erosional, mountainous, and lowland areas were identified as suitable grasslands for this plant. accordingly, erosion and impoundment with the relative importance of 0.54 and 0.26 are of most importance in the establishment of Divdal species, and covered plain, mountain, and plain with the relative importance of 0.11, 0.05, and 0.02 are respectively at the lowest level of significance. In terms of annual precipitation, it could be argued that Divdal species grows in low-rainfall areas, but the higher the precipitation rate is, the better growth would come about. Analysis of the questionnaires revealed that precipitation greater than 180 mm/year was identified as the most important and precipitation less than 70 mm/year as the least important areas for Divdal growth. In this regard, precipitation of more than 180 and 180-100 mm are ranked first and second with significance levels of 0.56 and 0.26, respectively. On the other hand, precipitation rates that fall in 70-100 and less than 70 class with the relative importance of 0.11 and 0.05 are considered less suitable for Divdal growth. In terms of its resistance to salinity, the salinity of 0 to 4 dS /m was selected as the best growth area for this species, as with an increase in salinity, the importance of this sub-criteria decreased. Thus, the salinity of 0-4 dS/ m has the relative importance of 0.71, and salinity classes of 4-16, 16-32, and more than 32 dS/m have the significance of 0.14, 0.08, and 05, respectively. As for the suitable height for Divdal species growth, altitudes greater than 800 m with the relative importance of 0.66 was selected as a suitable height for growth of this species, considering the fact that Divdal is a cold-resistant species. Also, areas less than 800 meters high with a significant rate of 0.33 are less important in this regard. In terms of land-use, since the Divdal is a completely sandy species (Psammophyte), land use was, therefore, divided into two sections of sand and non-sand dunes, and the use of sand dunes with relative importance. 0.9 is considered as the most important, with other land-uses having relative importance of 0.1. The results of this study indicated that AHP was a very convenient and easily applicable method for locating suitable areas for the cultivation of various plant species and its integration with powerful tools such as GIS enhanced its efficiency. According to the research findings, it could be argued that the use of a hierarchical analysis method in environmental planning is very important and could help planners put a natural problem into a hierarchical structure and then quickly and accurately find a solution for it.

Nowadays, the municipal solid waste landfill is one of the major disposal methods used in many countries of the world including Iran. Like any other engineering projects, landfill site selection requires precise information and clear planning. Considering various factors involved in selecting a suitable place for a landfill and the extensive connections between them, experts are, thus, led to a system like GIS that measures different impacts of those factors and analyzes their mutual relationships with sufficient accuracy and speed. As a decision-making model, GIS is capable of managing and organizing various environmental criteria and manage the relevant collected data (Chitazan et al., 2013). From among the multiple decision-making methods, AHP is applied in management science (Mokhtari et al., 2015). Another model is the Topics Fuzzy method which is based on the selection of an option that has the minimum distance with the ideal positive solution and the maximum distance with the ideal negative solution. another model is the ordered weighted average (OWA) which is also another decision-making issue and a risk-taker and risk-avoider method in which a risk-taker emphasizes the good and bad properties of an option, and a risk-avoider emphasizes its bad properties (Yager, 1988).

Kashan is the second largest city of Isfahan province with an area of 4,392 km2 and a population of 364482 people. By studying environmental and health guidelines as well as the status of the target area, 12 effective criteria were identified for landfill site location (Sydikai et al., 1996 and Gyor Salanguch, 2012). Due to the incompatibility of factors, standardization was carried out by the fuzzy method. To determine the significance of the factors (weight), the criteria were compared with each other. Each score was also scored from 1 to 9 and weights were calculated via Expert Choice software. (Rajabi et al., 2011). Then, the OWA method was used to overlay the effective criteria. The weighted average method is a sequence of multivariate functions which consists of two groups: standard weights and ordered weights. Subsequently, to prioritize suitable sites, they were ranked by the fuzzy TOPSIS method concerning the fourth scenario as an example. The basis of the fuzzy TOPSIS method is to choose an option that has the least distance from the ideal positive solution and the maximum distance from the ideal negative one (Asgharpour, 2006; Moeineddin et al., 2010). Finally, the proximity coefficient of each option is obtained by considering the positive and negative ideal points according to the following equation: 

By studying environmental and health guidelines as well as the status of the target area, a suitable landfill site was selected and determined according to their 12 effective criteria. The weights assigned to each of the criteria effective in locating was calculated by the AHP method. These weights showed that groundwater depth and distance from wells and springs and agricultural areas are the most important criteria and distance from roads industrial areas have are the least important criteria in locating solid waste landfills in Kashan, respectively. After standardizing the information layers according to fuzzy logic, the OWA method was used to choice choose the appropriate landfill sites according to seven scenarios with different degrees of risk. Prioritization of the three suitable locations based on the fourth scenario corresponding to the weighted linear combination was done through the fuzzy TOPSIS method. The results showed the preference of site three over the other two ones. The final location map was based on different scenarios and in this study, the fuzzy TOPSIS method was used to rank the appropriate areas. In this study, the ranking of suitable areas was considered in the fourth scenario, which corresponds to the linear combination method.

The importance of groundwater depth and distance from wells and spring compared to other factors indicate the possible role of landfills in the contamination of water resources. In this study, the weighted averaging method was used to select the appropriate landfill for solid wastes. One of the most important features of this method is its degree of risk-taking which has a high ability to solve complex decision-making problems. In addition to its ability in identifying suitable locations for sanitary landfills, the OWA method also prioritizes options with varying degrees of risk. The methods used in this study could be applied to similar cases that need to be decided on environmental issues and water resources, but it should be noted that the criteria and their boundaries are influenced by problems and conditions in each area. Also, the existence of suitable locations for the sanitary landfill in Kashan is a good opportunity for the municipality or related entities to consider landfilling of solid waste in these areas, taking into account their social, political, economic, cultural, and environmental conditions, while taking action to avoid the current complications of solid waste.

Estimation of evapotranspiration at a regional level is an important element in efficient management of water resources. Evapotranspiration includes the evaporation from the surface of soil and water and also, the transpiration by the plant that is very important in arid and semi-arid areas. There are many empirical methods for evapotranspiration estimation of reference plants, but these methods donchr('39')t produce the same results for all areas. Lysimeter studies are carried out to determine the most suitable method in each area.

The study area in this research is located in Kashan University, based in the center of Kashan plain with geographical coordinates of ° 45 ′21 ° 51 east longitude and ″ 18 ′00 ° 34 northern latitudes. Then, to measure the evapotranspiration of the reference grass plant, three drained lysimeters of the grass plant and one control lysimeter were made and used in the research site for 6 months within the statistical year of 2012-2013. Moreover, empirical methods of evapotranspiration estimation and evaporation pan were compared based on lysimeter data.

Using lysimeter in the project area, the estimation results for monthly evapotranspiration were reported as being 24.49, 38.39, 51.52, 73.87, 119.77, and 180 mm in January, February, March, April, May, and June, respectively. Moreover, from among the methods investigated, Thornthwaite turned out to be the most accurate ones with R2 = 0.95, R=0.97, NSC= 0.986, RMSE=4.29, and MBE= -1.15, being considered as the most suitable method for evapotranspiration estimation in the study area. After that, modified Jensen Hayes, Blaney –Criddle, Jensen-Hayes, Hargreaves-Samani, evaporation pan, and FA0-Penman-Monteith were considered as other useful methods in that regard though with lower accuracy. Finally, the Penman method with R2 = 0.58 was found to have the least accuracy from among the relevant methods considered.

Kashan is one of Iran’s arid regions which faced a severe shortage of water resources. Therefore, careful planning and efficient management of water resources is required to avoid any serious problem in providing water for different purposes. The evapotranspiration parameter is considered as an important criterion in determining the extent of drought in different areas. Experimental methods for estimating evapotranspiration including the Penman and FAO-Penman-Monteith require many meteorological parameters. Penman method has been introduced for humid climates of England and is not suitable for the arid and semi-arid conditions of Kashan. As it considers a large number of climatic parameters in its calculation of evapotranspiration, this method has acceptable accuracy, but as all the required information is not calculated, it cannot provide a good estimate. In this study, the appropriate evapotranspiration method for the Kashan region was obtained, using the data gathered over six months in the statistical year of 2012-2013. Therefore, to ensure the accuracy of the results obtained, it is recommended that this research continues for at least the next two or three years. On the other hand, due to a possible error in the drainage lysimeter when calculating the actual evapotranspiration, it is recommended that the research get conducted in the region via accurate weight lysimeters so that it could identify the most appropriate method of estimating evapotranspiration in Kashan more accurately.

The worldwide climate researches have generated large-scale models and shared their results to increase the accuracy of various models in working with big datasets. Among the various statistical approaches, empirical downscaling methods are the most commonly used ones due to their ease of implementation. Several empirical downscaling approaches have been proposed which need to be assessed as to which method contributes (or not) to the overall climate change uncertainty. Therefore, this research sought to investigate the effects of climate variation on temperature and precipitation in different seasons, using two Emission scenarios of 4.5 and 8.5 in Bandar Abbas city which is located in southern Iran.

The coastal city of Bandar Abbas is located in the south of Iran. In this study, the data collected from the Synoptic Station of Bandar Abbas were used. The historical observational data for the basic period from 1982 to 2005 included the daily temperature and precipitation. As for future data, the period considered was from 2016 to 2075. As this study sought to investigate the role of temperature and precipitation in the future average and bad conditions of the region, The Emission scenarios of 4.5 and 8.5 were taken into account. To investigate the effects of climate variation, the output of CMIP5 models was used. During the model selection in the CMIP5 project, the models which included the daily data were determined. In this study, three models were used to evaluate the temperature and precipitation. Considering the fact BC-Mean and variation Factor-Variance were the selected methods of the study, four GCM daily temperature and precipitation downscaling methods were used at the station scale. To evaluate the efficiency of the downscaling methods, a mean relative error (MRE) was, in addition to RMSE and MAE statistical coefficients, applied to determine the experimental similarity quantity between the observations and the downscaling.

Based on the results obtained from the downscaling of each model, the MPI-ESM-MR model was found to have the least error rate and the most similarity with the synoptic station under study. From among the downscaling methods, the BC method proved to make more mistakes in limit values than the CF method (Chisanga et al, 2017). Based on the results obtained from four downscaling methods, CF-Variance and BC-Mean were selected for downscaling the precipitation and the temperature in this study, as they had the min error in terms of MRE, RMSE, and MAE, and possessed the max, average, and min amounts in comparison with those of the station; a result which is consistent with the findings of Wang et al (2016). Based on the 4.5 scenarios, it could be argued that from 2016 through 2045, the increase in precipitation variations has been low, and this is evident especially in those months with high rates of precipitation, with the maximum increase reported as 0.26 percent for May- June precipitation. As found by the Emission scenario of 8.5, during both time intervals of 2016- 2045 and 2046- 2075, the percentage of the rainfall variations from February to June was low and limited. In the time interval of 2016- 2045, an increasing trend of 2.34, 9.89, and 3.8 percent were found in January, September, and October, respectively. Therefore, the amount of precipitation during both time intervals indicated a reduction in precipitation in May and March, which are normally considered as high rainfall months, while an increase in precipitation forecast percentage was observed in September and October. The findings also suggested that based on scenario 4.5 and 8.5, the chances for an increase in precipitation in rainy seasons (autumn and winter) are minimized, and in seasons with normally least amount of least rain, the chances are maximized. It was also found that based on scenario 4.5, most of the changes occurred during those two time periods in the minimum temperature (-2.2 and -1.2 C), average temperature (0.4 and 1.04 C), and maximum temperature (0.1 and 0.6 C) respectively. According to scenario 8.5, most of the changes in temperature parameter occurred in the maximum temperature (13 and 13.8 C), average temperature (11.6 and 12.3 C), and minimum temperature (7.7 and 8.2 C) respectively during those periods.

Taking the results of the study regarding climate in both scenarios, an increasing trend in temperature parameter was observed. As suggested by findings of the studies carried out by Tavousi (2016), Masoompour Samakosh et al (2016), Alijani et al (2007), Alijani (1995), and Najar Salighe (2006), precipitation in the southern district of Iran is partly influenced by the monsoon low-pressure tabs of India which starts at the beginning of June and continues to the beginning of October. The first day of these rainfalls is different each year. It could, therefore, be argued that the reason behind the increase in precipitation rate in those months which are typically characterized by low precipitation rate is an increase in the monsoon low-pressure system of India during the future time interval. This is consistent with the findings of a study carried out by Turner (2013) who found that the amount of India monsoon rainfall would increase in the future. Thus, it could be said that the percentage of the rainfall variations in July is, according to scenario 4.5, related to the time shift of the monsoon systems. As the findings of Schewe and Levermann (2012) indicated, the temperature is predicted to increase by the end of the 21st century and early 22nd century, and these frequent variations would lead to a 70% reduction in precipitation under the normal level of Indian summer monsoon system. Moreover, the begging of the monsoon system in southeast Asia may have 15 days shift in the future (Ashfaq et al, 2009؛ Loo et al, 2015). According to scenario 8.5, the results found for the variation trend of the time and precipitation parameters are in line with the findings reported by Schewe and Levermann (2012), and Loo et al (2015). Therefore, in studies on the effects of climate variation which are only based on one scale decline method, we should be careful in interpreting the results, a fact which is consistent with what Chen et al (2011) and Sarr et al (2015) found in their studies. Thus, in studies on climate variation, each result belongs only to the district studied, and their suggestive downscaling method may not fit other districts.