نشریه خشک بوم
سال دهم شماره 2 (پاییز و زمستان 1399)

Drought is a complex multivariate phenomenon that cannot be investigated using conventional univariate indices. In the current study, the meteorological drought has been assessed based on multivariate statistical and probability indices in Hormozgan province during 1986-2016. Therefore, the MSPI standardized multivariate precipitation index was calculated using Principal Component Analysis (PCA) and JDI using Kendall's empirical function. Next. the drought characteristics were extracted to compare the efficiency of the two indices. The results showed: 1) In drought monitoring of the study period, MSPI estimated the maximum intensity values more than JDI, 2) In assessment of a historical drought in 2001, the MSPI provided a more realistic image of the drought than JDI, 3) The correlation between drought characteristics (severity, duration, and magnitude) in most cases in MSPI was higher than JDI, which means that the correlation structure is better than the joint functions, and 4) Estimates of the frequency of drought classes from mild to extreme showed that MSPI was better at these classes and was more accurate than the drought classes. Finally, the MSPI is capable to provide a realistic image of the drought for a multivariate drought assessment.

Develop of sustainable green spaces in cities will lead to unsustainability, if this development is done without evaluating the factors affecting the resilience of plant species and applying inappropriate planting pattern due to ignore the aforementioned factors. The main purpose of this study is to evaluate factors affecting the resilience of plant species for the development of urban green space in Qom and providing a list of plant species compatible with specific semi-arid environmental conditions. This study tries to quantify the qualitative indicators of plant species characteristics to evaluate their comparison in relation to resilience criteria. For this purpose, beforehand the criteria and sub-criteria of plant resilience were determined based on related literature and the authors’ experiences. Then, according to the criteria of plant resilience to soil, water, climatic conditions, urban pollution and ecological conditions of the region, plant species is properly evaluated and prioritized by Fuzzy Hierarchical Analysis (FAHP) and FTOPSIS. Consistent findings indicate that from the experts' point of view, the most crucial factors affecting plant resilience in green space of Qom are, water (0.273), soil (0.254), climate (0.199), Ecological conditions (0.180) and urban pollution (0.092) accordingly. Moreover, plants' resistance to soil salinity (0.075), resistance to evapotranspiration conditions (0.069), resistance to water shortage (0.067), resistance to water salinity (0.067) and resistance to adverse environmental factors (0.063), were promptly recognized as the most relevant sub-criteria of plant resilience. Finally, tree species including Tamarix gallica, Populus euphratica, Eucalyptus globules, Aianthus altissima, Pistacia chinensis, Pinus Mugo and black pine and Pinus nigra are determined as resilient species. The allocated proximity coefficient is 0.90, 0.89, 0.88, 0.86, 0.85, 0.85 and 0.84 respectively. As result, aforementioned species can be widely used in urban green spaces based on the local facilities and conditions of each area of the city.

Optimal design of groundwater monitoring network that is capable of providing accurate and informative data is crucial to improve our understanding of complex groundwater systems. In this study, a geostatistical method to optimize a groundwater quality monitoring network in Shamil-Takht plain, Hormozgan province were used. This study uses the spatial variance of collected data from the field to identify areas that are not covered and lack information. The kriging variance and the vulnerability maps were combined and the final map was used to design the optimum network. Selection of the best-fitted model was based on the values of the RMSE. This approach has been used to assess the electrical conductivity (EC)-as the representative of the most important quality parameters- monitoring network. The results show that 23 wells can be removed from the primary sampling network with 44 wells. On the other hand, 15 wells have been added to cover areas without information. As a result, the number of wells in low density areas has increased. Based on contaminant sources available in the plain, six new sites have been proposed to monitor the potential contamination from cemeteries, health centers, food and livestock industries.

Today, the tourism industry has been accepted as an important and influential issue in the global economy. In the meantime, geotourism is one of the new attitudes to the presentation of Geomorphologic landforms that includes all the natural and human features of an area. Everything worth seeing and is always seeking to introduce and conservation of capacity and capabilities of landforms tourism. Bajestan Playa is located southwest of Khorasan Razavi province and south of Khalil Abad and Bardaskan city, as well as west and northwest of Gonabad, Ferdows and Bajestan city, It seems to be worthy and capable of tourism. This research is a descriptive-analytic study and using the field observations data and using the Paralong method, the geomorphotouristic capabilities of landforms of Bajestan playas were evaluated. The results show that the total value of the tourism potential of the Bajestan Playa is 0.45, which indicates the average tourism value of this salt playa. The highest score is related to socioeconomic value with 0.55 and scientific value with 0.47. Calculating the value of productivity and the quality of productivity indicates the low level of productivity capability of Bejestan Playa.

The crown ratio is one of the most important attributes of trees for modeling growth and evaluating the competitive environment in forest stands. This research was carried out to determine the crown ratio for wild pistachio. Continuous transect sampling was carried out with the counting limit of 5-cm diameter at breast height. In each transect, the total height of the tree, the height of the crown, the diameter at breast height (DBH) and the elevation were measured. To study the type and severity of the relationship between elevation and DBH with crown ratio, correlation analysis was conducted. For modeling using linear regression analysis techniques, the curve estimation (including simple linear, second, third, linearized logistic, exponential, inverse and power) and nonlinear models (logistic, Richard, Weibull, and exponential) were used. The results showed that the linear model fitted to DBH data in order to predict crown ratio was statistically significant but the R-square was not noticeable (R2 = 0.33). Nonlinear models explained a maximum of 34% of variations in crown ratio with high precision. Elevation from the sea level was not a suitable predictor for the crown ratio. In this study, due to the low stand density, lack of effective competition between trees and the uniformity of the competitive environment, the crown ratio was less affected by independent variables such as DBH. Accordingly, it seems that in the low density forests of the Iran-Touranian region, the development of powerful models to predict the crown ratio will have little success.

It is necessary to determine the appropriate probability distribution for fitting the flood data. There are several methods for estimating the parameters of probability distribution functions. In the present study, L-moments approach is used for flood frequency analysis in Gavkhouni Basin, Abarkouh- Sirjan Basin and Yazd- Ardakan Basin. Some stations were selected and their data were analyzed to find out peak discharge. Then, Hosking and Wallis homogeneity criterion were used to identify the homogeneous region. Examining the homogeneity criterion closely shows the discordant region. Eliminating and transferring some selected stations, leads to determining a homogeneous region of flood frequency. Parameters of the regional frequency distribution were evaluated using L-moment, moments, and maximum likelihood methods. The results of this analysis were compared using RMSE, R, and RRMSE statistics. The goodness of fit tests such as Chi-square, Kolmogorov-Smirnov were applied for checking the adequacy of fitting of probability distributions to the recorded data. The study reveals that the Pearson Type-3 distribution (using LMM) is better suited amongst the ten distributions used in estimating the peak flood. In general, the L-moment method estimated the peak flood for return periods of 10, 25, 50, and 100-year, and moments method at return periods of 2 and 5-year.

This study was conducted in the aeolian dust sources of the southeast of Ahvaz to determine the best survival method for planted seedlings. Full calipering method (%100 inventory) used for 16.2 hectares planted seedling. Sampling sample-line methods were performed with a fixed number of trees (in intensities of 10 and 13%) and a sample plot with a fixed area in five sampling networks with different dimensions of the sample plot and three intensities of 5, 10, and 13%. Then, a one-sample t-test was used to compare the mean of each method with the percentage of survival in the %100 sampled method at a significance level of %95. According to the results of %100 statistics, the survival rate of seedlings planted in the field was %72.9. The results indicated that the sample-line method with an intensity of 13% (average of 80 holes per sample line) had the closest estimate (71.8%) to the percentage of real survival. Also, the 30×30 m sample plot method with 13% intensity and 70×100 m network dimensions showed the closest estimate (72.1%) to the real survival percentage. Results of the single sample t-test showed that the sample-line method with sampling intensity below 13% was not significantly different from the control. Among the studied methods, only methods E (10% fixed area with 90 ×100 grid dimensions) and G (13% fixed area with 90×100 grid dimensions) differed from the control. The lowest percentage of standard errors belonged to H (13% fixed area with 70×100 grid dimensions) and I (13% fixed area with 35×100 grid dimensions). The lowest percentage of standard errors belonged to H (13% fixed area with 70×100 grid dimensions) and I (13% fixed area with 35×100 grid dimensions). Totally, this study showed, the area sampling method is superior to the sample-line methods estimate the percentage of survival in the planted areas, and in general. It is suggested to use the H method (fixed area 13% with 70×100 grid dimensions) in forestry areas.

Due to the limited water resources used in the agricultural sector, water is considered an economic commodity and should be planned for consumption. The use of government policies can lead to the conservation of water resources to reallocate this natural resource. In this study, the economic value of agricultural water is calculated using the production function, and For this purpose, the required information from pistachio producers in Ardakan County was collected by completing 300 questionnaires using the multistage cluster sampling method in 2019-2020. After reviewing the results of various production functions, the generic quadratic production function was selected as the appropriate production function. The water elasticity was the highest among other outputs, equal to 0.54, which indicates that if the water supply increases by 1%, the production increases by 0.54%. The economic value of water per cube meter was calculated at 38790 tomans. The results of the contingent valuation method indicated that farmers will to pay for each cubic meter of water, a sufficient supply of water per cubic meter, and for one more cubic meter of water, 43.50, 113.64 and 26.458 tomans, respectively; they are also willing to receive 1215.30 tomans regardless of their cubic meter of consumption water. Therefore, there is no possibility of forming a market in this region.

The aim of this study is modeling and predicting the monthly wind speed of Dezful. Therefore, SARIMA model, threshold nonlinear time series model (SETAR), SARIMA-SETAR hybrid model, and also artificial neural networks were used. In addition, the PMI algorithm was used for selecting the effective input variables in predicting wind speed for the neural network model. Using the Hempel criterion and the AIC information criterion monthly relative humidity in the previous two months RH (t-2), monthly in the previous month evaporation (t-1), the average monthly temperature in the previous three months Tave (t-3) and maximum monthly temperature in the previous month Tmax (t) as effective input variables for modeling and predicting monthly wind speed were identifie .TO validate the SARIMA and SETAR models and the fitted SARIMA-SETAR hybrid model, the functions of autocorrelation, partial autocorrelation and the residual independence test of the model (Ljung-Box) were used. The superiority models ware determined based on the minimum numerical value of Schwartz and AIC statistics. For modeling and predicting wind speed with neural network, linear function was used for input and output layer and different stimulus functions with different training algorithms were used for the hidden layer.The neural network model with topology (1-3-5) with sigmoid tangent stimulus function and Levenberg-Marquardt training algorithm was found to have better performance in predicting the monthly wind speed of Dezful synoptic station compared to SARIMA linear and SETAR nonlinear models. The results of the models showed that the SARIMA-SETAR hybrid model (2, 2, 3) had better performance compared to other models. It has acceptable accuracy in predicting the monthly wind speed of the Dezful synoptic, with a coefficient of determination of 0.91 and a root of mean squares 72.

Capper (Capparis spinosa) is a resistant plant with remarkable sustainability to adverse environmental conditions. It has special importance from the side of soil conservation and it’s a suitable species for bio-restoration in arid and semi-arid regions. Weak germination and seed dormancy in capper is an obstacle to inclusive use in restoration projects. In the current study, with the aim of investigating the effects of chemical, mechanical, and biological priming on germination and primary growth in plants, an exam was designed. The experiment performed in two conditions: 1) In a petri dish, 2) Seedling tray both under completely randomized design. Chemical priming included Salicylic Acid and Giberlic Acid in three levels of 1000, 2000, and 3000 ppm. The 24 kHz wavelength of the ultrasonic device was applied as mechanical priming for 5 minutes. Bio-priming Included Azotobacter chroococcum, Flavobacterium F-40, Azospirillum lipoferum, Bacillus megaterium, and Pseudomonas fluorescens. Results showed a significant level (p <0.01) on seed germination percentage, root and shoot length, seedling growth, root and shoot fresh weight, and root and shoot dry weight in petri dish test. In seedling tray test, root length, shoot length, root length to shoot length ratio, seedling growth, root dry weight, fresh and dry weight of shoot and leaf and leaf number at 1%, and root fresh weight at 5 percent were significant. In the Petri dish test, ultrasonic treatment increased shoot length compared to control treatment. Bacillus megaterium and GA3 (Gibberellic Acid 3000ppm) in Petri dish test and GA1 and GA2 in seedling tray test had a more positive effect on germination characteristics than other treatments. Bacillus megaterium had a 25 percent positive effect on germination percentage in comparision with control treatment. Using bio-priming, several waves of ultrasonic treatment, and different Gibberellic Acid concentrations could be a proper solution to solve the problem and develop C. spinosa implantation.

In recent years, there has been a growing demand for solar energy, as one of the cleanest and most innovative energy sources in the world. South Khorasan province is one of the less developed regions of Iran that the transfer of energy carriers to this province is costly. On the other hand, the development of agricultural farms in South Khorasan province is facing a serious challenge due to the lack of water resources in arid and desert climate. Therefore, the development of solar farms can be a good alternative for the development of agricultural farms, especially irrigated and non-strategic crops. The purpose of this study is to identify the optimal locations for the development of solar farms in South Khorasan province. The different stages of this research have been done in six steps. First, the criteria affecting the location of solar farms were identified by the Delphi method. In the second step, with the help of experts and environmentalists, the criteria were coded and screened. In the third step, the spatial database of effective criteria was established. In the fourth step, the weight of the effective criteria was calculated through the Analytic Hierarchy Process (AHP). In the fifth step, the layers of effective criteria were classified and coded. In the final step, the weighted fuzzy layers with gamma fuzzy operator was overlapped. The results showed that in South Khorasan province, the cities of Tabas (387.4 km2), Nehbandan (120.4 km2) and Sarayan (119.6 km2) are sites with very high optimality for the development of solar farms in the province, respectively. The optimal area by the cities of the province at the average, desirable and very desirable level for operation in different conditions was presented. The current results and even changing the existing conditions by re-implementing the proposed approach can consciously lead managers' decisions towards the wise development of the region, the use of environmental capacities and new energies.

In order to evaluate the drought tolerance of safflower cultivars using some drought tolerance indices, an experiment was carried out as split plot in complete randomize block design with three replications in the research field of Payame Noor University of Khash, during the growing season of 2015-2016. Experimental treatments were consisted of four drought stress levels included cutting-off irrigation at stages of flowering, beginning capsule, ripening stage and no cutting-off irrigation as main factor, and five safflower cultivars included domestic cultivars of Golmehr, Padideh and Faraman; and foreign cultivars of Yut and Nebraska 10 as sub factor. The results showed that the highest seed yield was obtained from treatment of no cutting-off irrigation and Yut cultivar, and the lowest seed yield was related to irrigation cut-off treatment in the flowering stage and Padideh cultivar. Correlation coefficients between drought tolerance indices and seed yield under the conditions of all three stresses showed that MP, GMP, STI, RDI and YI indices had a positive and significant correlation in all three stress conditions with seed yield under control and stress conditions. Therefore, they can be used for better selecting of safflower tolerant cultivars. In addition, the correlation between MP, GMP, STI, RDI and YI indices in all three stress conditions were positive and significant, which due to their correlation with seed yield in all three conditions increases the desirability of simultaneous use of these indices in the selection of cultivars. In general, for safflower cultivars, indices of MP, GMP and STI were the most appropriate indices to evaluate drought stress tolerance in different treatments studied. Based on these indices, as well as biplot diagram and cluster analysis, Yut cultivar was identified as the most tolerant and Padideh cultivar was identified as the most sensitive in all three drought stress conditions.