نشریه خشک بوم
سال نهم شماره 2 (پاییز و زمستان 1398)

The drainage networks as the most prominent landscapes on earth are basis of many hydrological and geomorphological models. Due to the geomorphological properties of the region, the drainage network shows its own fractal properties that are saved as code in it. In fact, drainage networks are fractal phenomena with fractal behavior. Fractal dimension is a parameter used to indicate the complexity of data. The analysis of fractal dimensions of drainage networks and their morphometric properties facilitate the perdition of their behavior in the future. This paper focuses on the relationship between fractal dimensions of drainage networks and their morphometric properties of drainage networks in Yazd- Ardakan basin. Therefore, through an analysis of fractal dimension of drainage networks and its comparison with morphometric properties, the fractal behavior of these drainage networks are investigated. Results showed Pck and Ktl formations indicate highest and lowest fractal dimension respectively. The results indicated a significant relationship between fractal dimensions of drainage networks and morphometric properties. In this research, a positive relationship was observed between morphometric parameters and fractal dimension, so that the greatest correlation coefficient was found between the fractal dimension and the drainage density (0.99).

In this study, phenology of Salsola laricina as an important range species was studied for period of four years. The phonological stages were recorded at vegetative stage every two weeks and at the reproductive stage once a week. Temperature and precipitation data of the study years were used to interpret the phenology of the species. Results showed that the phenological period of Salsola laricina varied each year due to climate change. Generally, this type of vegetative growth begins in mid-March and continues until mid-July and temporary sleep begins. Flowering occurs in first decade of September and seed ripening stage begin in early November. Generally, the best time to collect seeds is November 10-30, depending on rainfall. Start growing was earlier in the dry year of 2008 (47% lower than long-term) and vegetative period was about 15 to 20 days shorter than in 2009 (16% higher than long-term). Increasing rainfall also increases the vegetative period and delay flowering and seeding about a week. Understanding the phenology of Salsola laricina is important for regulating plant utilization plans, determining the time of entry and exit of livestock, collection of seeds, prevention of untimely harvesting in the steppic rangelands.

Particle-size and their distribution are important in various sciences such as: agricultural, natural resources, and even engineering and medical engineering. Using mechanical sieves requires considerable cost and time. The purpose of this study was to investigate the capability of image processing techniques for desert pavement. Thus, random sampling of desert pavement was carried out in bare and epandage pediments. Samples were transferred to the laboratory and was grading using standard sieve series. The collected samples taken were also photographed. Photos were analyzed using Image Processing and Analysis in Java and Geological Image Analysis Softwares.Then the results of the software were compared with the values measured by the sieve series. Results, show that the values obtained for particle aggregation using Image j software have a correlation of 93% in the epandage Pediment particles and 96% in the bare Pediments with mechanical sieve. Results of correlation between mechanical sieving and GIAS software in epandage pediment have an average correlation of 91% and in bare pediment has a correlation of 96%. It can be concluded that the use of these softwares can be a good substitute for mechanical sieve in particle size distribution. Using the results of this study can be effective in reducing cost and time in perform grading.

Critical endangered Asiatic cheetah as the most charismatic carnivore of Iran, is the rarest felidae in the country. The Asiatic cheetah prey selection in the Nayebandan Wildlife Refuge was studied as the vastest protected area in Iran. We were collected all direct observations records of the cheetah hunting in Nayebandan WR during 2001 to 2016. The prey selection by the cheetah is not correlated only with the preys’ abundance and the results showed that predation by cheetah depends on the abundance of the prey and habitat structure. Medium-sized ungulates especially wild sheep are important in cheetah food habits. This study is important because of the fact that, identifying the prey selection as one of the main dimensions of the species ecology very important to the Asiatic cheetah conservation. Moreover, with the extinction of cheetah in the study area, this species will be extinct in the last remained nucleus habitat in the centre of Iran.

In order to study the effects of irrigation period and iron nano-chelate on the some morphophysiological and biochemical characteristics of Echinaceae purpurea L., a experiment was conducted as factorial based on randomized complete block design with three replications at research farm of Baharan University of Gorgan, during growing season of 2017-2018. The treatments were four levels of irrigation periods (every 3 as control, 6, 9 days and 12 days) and iron nano-chelate (INC) including four levels (0 as control, 3, 6 and 9 in liter). Results showed that the irrigation periods increasing was decreased plant height, shoot wet and dry weight, root wet and dry weight. Highest irrigation period reduced in RWC and ion linkage. The antioxidant activity and soluble sugar were gone up under irrigation period and the maximum amount was in third level of irrigation. INC has significant effect on all traits except of shoot total phenol and shoot wet weight that the most effect was in third and fourth. Interaction effect of these treatments was showed that every 6 days and 6 in liter of INC increased soluble sugar and antioxidant activity and the most amount of proline was produced in every 12 days and 9 in liter of INC. Results of this study showed that drought stress increasing decreased morphological charactristics and RWC. However, proline, soluble sugar, total phenol, ion linkage and antioxidant activity were climbed. However, INC protects E. purpurea from drought stress and reduces damage caused by drought stress. Generally, 6 in liter of INC was advised for reducing of negative effects of irrigation regimes.

The present research was carried out with the aim of identification and separation of zizyphus spina christi and Astragalus sp. species as well as providing a distribution map of the mentioned species using UltraCam-D digital images in a part of the mountainous Bushehr province. Different techniques of enhancement were applied including Texture Analysis, Principal Component Analysis (PCA) and ratio of the bands. Five band groups were selected including main bands, band set obtained from image texture analysis, main bands along with indices and the first obtained band from PCA and a collection of the best bands obtained from OIF. The training samples were produced through field method. Then, 70% of the samples were applied for various classifier pixel-based algorithms including, Mahalanobis Distance classification, Maximum Likelihood classification, Neural Net Classification, Support Vector Machine (SVM) and Random Forest classification. Verification of the results was carried out using 30% of actual ground samples. Results of assesment of images classified by various algorithm showed that the maximum overall accuracy (85.69%) and kappa coefficient (0.72) in separating the three classes of zizyphus spina christi, Astragalus sp. and soil from the other mixed vegetation cover are for classification by Mahalanobis Distance Classification algorithm applied on group of four main band, PC1, NDVI and SAVI. In general, the results of classification by pixel-based method represent proper efficiency of UltraCam-D digital data for identification and separation of desert regions species particularly zizyphus spina christi from Astragalus sp and shrub species.

Soil temperature is a key factor that controls physical, chemical and biological properties of soil and its processes. Since soil temperature is measured at synoptic stations and data availability, especially in arid lands, is limited, capability of satellite images to estimate soil temperature at different depths evaluated in the Yazd-Ardakan basin, as the study area. Daily soil temperature at 5, 10, 20, 30, 50 and 100 cm depth measured at synoptic stations of Yazd, Meybod, and Mehriz for the periods of 2014 to 2016, and Landsat 8 satellite images of were used as the main data in this research. Then, using split-window surface temperature, Land Surface Temperature (LST) maps were estimated. Temperature trend from soil surface to a depth of 100 cm were examined seasonally. Using simple linear regression and artificial neural network techniques, the relationship between temperature of surface soil and soil temperatures at different depths were predicted. Results showed that the artificial neural networks had greater accuracy than the linear regression method in all seasons. The lowest accuracy of this method is related to the soil temperature at 5 cm depth. Artificial neural networks can be used for predicting of soil temperature till depth of 100 cm, using land surface temperature obtained by Landsat 8 images. To validate the results, soil temperatures at depth of 30 cm for 16 selected points in the study area were compared with estimated soil temperature using Landsat images and artificial neural network. Absolute error of measurements show that the maximum error was observed to depth of 30 cm (3.7 ℃). Therefore, using the measured soil surface temperature by applying the split-windows and artificial neural network can be used to predict soil temperature.

With the global expansion of population, rising energy consumption and the lack of renewable energy sources that are costly and polluting, the need for clean and sustainable energy such as solar energy has been increasingly taken into consideration. To evaluate land suitability for the optimal placement of photovoltaic solar power plants in Yazd province of Iran, the analytic hierarchy process (AHP) was used. A set of climatic and environmental constrains based experts' advices prepared in nine layers, estimates the potential sites for solar park installation. These constrains based on their relative importance in site evaluation extracted from AHP method, including sunshine, humidity, rainfall, evaporation, temperature, elevation, distance to access, fault and the power post. Climatic data obtained from eleven synoptic stations including fifteen-year period (2001-2016). After final mapping, the susceptible areas of photovoltaic solar power plants were determined in Yazd province. These areas located in Yazd, Bafgh, Ardakan, Meybod, Saduq and Khatam cities. After applying the privacy layer and considering the forbidden areas by conducting the field surveys, 5% of the Yazd province was considered suitable area for the construction of photovoltaic solar power plants. These areas are located in the south and south-east of Yazd, and part of the Bafg city.

A population of Scrub Warbler with a relatively high density lives in the protected area of Baghshadi in Yazd province. During two consecutive years (springs of 2015 and 2016), the breeding habitat of this species was investigated in the study area. The number of 37 bird nests were identified in the area. The habitat variables such as type, number, percentage of vegetation and height of plant species, the distance of the nest from the nearest water source, road, human settlements, the height and diameter of the nest, and insect nest density in the presence and absence points of this bird were measured and compared. The main purpose of this study was to determine the effective variables in the habitat selection of Scrub Warbler in the protected area of Baghshadi. The results showed that this species clearly prefers the shrub Amygdalus lycioides to other plant species in the region and builds its nests mostly on these shrubs which have a higher density and height, are distant from the road and human settlements, and are closer to water sources. To provide food, insect nest density is the most important factor in the habitat selection of Scrub Warbler in the protected area of Baghshadi.

Radar interferometry technique is an efficient tool to study changes in the Earth's crust. The method is based on the phase difference between two image pairs at different time intervals. In this research, subsidence of Abarkuh plain, Yazd province investigated. The subsidence is actually the lowering of the Earth's surface due to the natural and human activities. Excessive extraction of underground resources, especially water, is a main cause of subsidence in many plains in Iran. Hydrological studies in this area show a groundwater level drop of 0.6 meters per year. According to the geological studies, karst developments and dispersive clay soils are two causes of subsidence. By the radar interferometry technique over a period of 2003 to 2005 using 12 Envisat satellite images, the average subsidence rate in the region was estimated. In Abarkouh, maximum subsidence rate is 2 to 3 cm/year and in Mehrdasht area 5 cm/year. Accurate alignment studies have been used for the accuracy of the calculations between 1985 and 2001, which are in agreement with the results obtained by radar interferometry. The reasons for this discrepancy are the inconsistency between two available data and the radar interferometry error.

Considering the widespread and cross-cultural effects of climate with different sectors of production, environment and human communities, climate change is considered as one of the most important environmental challenges. The main aim of this study was to prioritize climate change coping strategies among fisheries sector. The research was carried out using a survey and multi-criteria decision making. In this study, the research population was the fish breeders in the form of nonagricultural businesses in Khorramabad city (N = 295). The research sample was selected using Paten table. 125 individuals were selected by stratified random sampling method with appropriate assignment. In the second part, 10 experts from the field of fisheries were selected through snowball sampling. The main instrument of the study was a questionnaire whose reliability was calculated by ordinal teta coefficient. Ranking of strategies using the virock technique and the value of Q showed that among the economic strategies, the guarantee of purchasing by the government had the highest rank in terms of importance and sustainability. Turning assets into cash among fisheners is the first and fastest way to deal with droughts. The social strategies, promote the drought-resistant varieties have been more important. Breeding quantitative and qualitative of varieties among the technical strategies was of first rank in term of importance; but the combined cultivation of products in fish farming ponds was placed in the first rank in terms of achieving sustainability and feasibility.

Precipitation forecasting has important role in water resource management especially in arid regions of Iran. This study aims to explore the relationships between the seasonal precipitation and weather signals such as NINO’s SST including NINO1+2، NINO3، NINO4 و NINO3.4 and SOI as well as MEI and NAO. The correlation analysis was performed in two states involving the correlation analysis of weather signals with one year lag in seasonal precipitations and the correlation analysis without the lag. Also, precipitation forecasting was performed through using partial least squares regression (PLSR). Results showed that MEI, SOI, NINO1+2، NINO3 and NINO3.4 have the most correlations with winter seasonal precipitation when the one year lag is performed. The most correlation refers to NINO1+2 equal to +0.68. This value for the SOI is -0.61 which exhibited the inverse correlation of winter precipitation with SOI in the past year. The time series without the lag showed the most correlation between the summer and autumn NAO and winter precipitation of the same year. Also, results indicated the acceptable performance of PLSR for precipitation forecasting. With the one year lag the winter, spring, summer and autumn precipitations were estimated with the RMSE equal to 12, 9.9, 0.85 and 6.2 mm, respectively. Also, the Nash–Sutcliffe (NS) model efficiency coefficient for the mentioned seasons is 0.69, 0.22, 0.2 and 0.72, respectively. The R correlation coefficients for these time series were equal to 0.83, 0.46, 0.45 and 0.85, respectively. In general, precipitation was predicted more accurately in the cold seasons. The development and use of such prediction models could make water resource management programs more successful.