فهرست مطالب

Desert - Volume:23 Issue: 1, Winter - Spring 2018

Desert
Volume:23 Issue: 1, Winter - Spring 2018

  • تاریخ انتشار: 1397/03/30
  • تعداد عناوین: 15
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  • M.A. Hakimzadeh, A.R. Vahdati Pages 1-8
    Current study monitored Electerical Conductivity (EC) as soil salinity index and Organic Matter (OM) in the area of Harat in Yazd, Iran, through remote sensing technology with high spatial and spectral resolution. The images were selected from IRS, LISS III satellites between the years 2008 and 2012. After preprocessing and analyzing the images, the relationship between parameters of (EC) and (OM) spectral reflections were determined, and both two-satellite images were classified using maximum likelihood method. Results showed that during the period (2008-2012) organic matter content of all farmlands increased and the area of saline land decreased. This trend showed that agriculture activities help reduction of desertification. Accuracy classification and coefficient kappa obtained for salinity map in 2008 were equal to 82% and 0.73, and in 2012, were equal to 84% and 0.70 respectively. Accuracy of classification and coefficient kappa obtained for Organic matter map in 2008 were equal to 85.5% and 0.76 and in 2012, were equal to 84% and 0.74 respectively. This research indicates that remote sensing data, especially IRS-LissIIIimages, have high efficiency for detection of soil salinity and organic matter changes and natural resources management.
    Keywords: Agricultural activity, Harat, IRS-LissIII satellites, organic matter, soil salinity
  • M. Ranjpisheh, M. Karimpour Reihan, Gh.R. Zehtabian, H. Khosravi Pages 9-19
    Management of groundwater quality is very important in arid and semi-arid areas. In this study, satellite images from TM, ETM and OLI sensors were used to evaluate the impacts of land use changes on groundwater quality for 1990, 2007 and 2015 in Shabestar basin. After processing and analyzing images, the basin was classified into five land use classes including pasture, bare land, farming, garden and residential. Motivate averages of 3, 5 and 7 years were used to determine precipitation changes trends and identifying wet and drought periods. Zoning maps of qualitative parameters including EC, SAR, TH, Cl and Na for 40 wells in a decade (2002 to 2012) were plotted using geostatistical methods to evaluate changes in groundwater quality. The obtained results from motivating average graph showed that drought was occurred during the first period 1997 to 2003 due to lack of rainfall, the worst drought was occurred in year 1999. Overall, the quality of groundwater was improving over the period. So that water quality was low in the first period (2002-2005) due to coinciding with the drought period and water quality was improving due to coinciding with wet periods in the second and third period (2006-2009 and 2010-2012). The amount of water quality parameters has increased in the southern and western parts of the region where located in the vicinity of Lake Urmia and water in these areas aren’t suitable for farming and drinking. It can be due to overuse of groundwater affected by land use changes in this parts of the region.
    Keywords: Precipitation, Wilcox classification, Qualitative parameters, Remote sensing, GIS
  • M. Heshmati, M. Gheitoury, M. Hosseini, M. Arabkhedri, Y. Parvizi Pages 21-28
    The forest soils are the key parts of the Earth system that are globally degraded through anthrop induced deforestation, mainly converting to other landuses. The present study was conducted in Gazafolya village located in Merek watershed, Kermanshah, Iran, in which the soil quality of the forest and converted forest (rainfed lands) with the same topographic and geologic conditions were compared. To achieve the study purposes, soil sampling was carried out from the surface soil layers (0-20 cm) at the forest and its adjacent rainfed lands and analyzed in the lab. The data were described and geo-statistically analyzed using the SAS and GS softwares. The findings showed that there is no significant difference between soil fractions (sand, silt and clay) in two studied land uses. Bulk density (BD) in the forest and rainfed lands were 1.26and 1.32 gr-1cm-3 respectively, indicating significant (p
    Keywords: Aggregate Stability, Gazafolya, Improper Tillage, Rainfed Lands, Zagros Forest
  • A. Jahanshahi, K. Shahedi Pages 29-43
    Drought as a natural phenomenon characterized by a significant decrease of water availability during a period of time and over a large area. In recent years, droughts and its frequent in arid and semi-arid regions like Iran on the one hand, and water demand has been rising on the other hand and, as a result, their impacts are being aggravated. Therefore, the meteorological and hydrological droughts are receiving much more attention. This research focused on the Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI) and Groundwater Resources Index (GRI) to investigate the correlation between these indices and overlapping periods of 3 to 48-months in the centeral Iran over the period of 1970–1971 to 2014–2015. Furthermore, the driest year based on the SPI were 2007–2008 and 2011-2012, while they were detected to be 1999–2000 and 2003-2004 based on the SDI and GRI, respectively. The decreasing time series trends using Spearman’s rho and Kendall’s tau tests were more evident for the all three indices at most of the years. SPI on time scales of 18, 24 and 48-months, with SDI and GRI showed a significant relationship in 0.01 and 0.05 percent levels that it can be confirmed directly affected by a groundwater drought in the plains. The Spearman correlation analysis indicated a strong correlation between SPI on time intervals of 18, 24 and 48-months, with SDI and GRI that showed a significant relationship in 0.01 and 0.05 percent levels that it can be confirmed directly affected by a groundwater drought in the plain. In general, the results showed that the study area suffered from the meteorological drought more than the other two types of droughts. Moreover, the results revealed that the study area has become drier over the last three decades.
    Keywords: Meteorological drought, SPI, Hydrological drought, SDI, Groundwater resources drought, GRI, Correlation coefficient
  • M. Sookhtanlou Pages 45-55
    In this study was examined the factors affecting the unwillingness to adopt pressurized irrigation methods among farmer's groups (with different levels of drought) in Ardabil province (Iran). Mixed method (Qualitative – Quantitative paradigm) was used for doing this research. First, by drought zoning of Ardabil province (by SPI method and GIS), three regions included the mild, moderate and severe drought levels were selected. In the second stage, using multi-stage cluster sampling from regions with pressurized irrigation methods implemented, non-adopter farmers of pressurized irrigation methods were selected from three regions of study (n= 290). The ordered logistic regression (OLR) (by STATA software) was used to determine the effective and distinctive factors of farmer's groups. The findings showed that 54.5% of farmers had moderate level of unwillingness to adopt pressurized irrigation systems. According to the results of OLR model and marginal effects, farmers in different levels of drought had significant difference in terms of unwillingness to adopt pressurized irrigation systems. Moreover, from among 18 factors of study, only 7 factors of education level, farm income, awareness of pressurized irrigation systems, the effect of local weather conditions, the distrust towards the optimizing of pressurized irrigation systems, non-efficiency of pressurized irrigation methods on farm yield and costs of pressurized irrigation systems were significant and it had been the ability to differentiate among farmers in different levels of drought. This study indicated that improving farm income and awareness of pressurized irrigation systems, compared with other effective factors, create the biggest variations in the probability of placing farmers in different levels of drought.
    Keywords: Drought, Standardized Precipitation Index (SPI), Pressurized irrigation systems, Farmers, Ardabil province
  • D. Akhzari, N. Kalantari, Sh. Mahdavi Pages 57-62
    As an herbaceous, perennial, and evergreen plant, Vetiver Grass (Chrysopogon zizanioides L.) can be used for the improvement and development of arid and semi-arid rangelands. To assess the interaction effect of organic and biological fertilizers on the growth and physiological traits of Vetiver grass, the dry weight of shoots and roots, essential oils, chlorophyll, carotenoids, and proline content were measured. A completely randomized design in factorial layout with three replications was performed in Malayer University’s greenhouse in 2016. The treatments were mycorrhizal fungi on two inoculated (M1) and non-inoculated (M2) levels and vermicompost organic fertilizer in six levelsof (0) (control), 10, 20, 40, 60, and 80% (V1, V2, V3, V4, V5 and V6), which were added to each pot. The results showed that the interaction between different levels of vermicompost and mycorrhiza had a significant (P
    Keywords: Biofertilizer, Rangeland, Improvement, Development, Synergistic effect
  • Gh. Mahtabi, F. Taran Pages 63-73
    Climatic conditions have a major influence in attracting tourists to a city in different months. In this study, the potential of Isfahan and Rasht as arid and humid cities, respectively, was investigated in terms of attracting tourists during a year. For this purpose, the Holiday Climate Index (HCI), which has been designed based on daily climate information, was used. The results showed that in Isfahan, with rising air temperature and reducing air humidity in March, April and May, the mean value of HCI is more than 69 and climatic condition is "very good". Also, from September 14, the value of HCI reaches above 69 and shows "very good" condition and this condition continues until the end of October. Therefore, these two periods are the best times for presence of tourists in Isfahan. In Rasht, in April and May, because of climate variables suitability (sunshine hours, cloudiness, and weather temperature) in comparison to other months, the mean value of HCI is equal to 66 (acceptable). It seems that the stable climate condition and therefore HCI value provide a suitable period for tourism in Rasht. In other months, because of high humidity and precipitation, the value of HCI is less than 60.
    Keywords: Air humidity, Air temperature, Climate, Index, Thermal comfort
  • F. Kazemi, N. Safari Pages 75-84
    Mulches are relatively new landscape components and are becoming recognized for their environmental and aesthetic outcomes on urban landscapes especially in arid environments. However, the effects of mulches on landscape plants have not been extensively discussed. This study examined the effects of organic and inorganic mulches on the performance of a widely used herbaceous drought tolerant flowering plant, Zinnia elegans, toward low maintenance landscaping. This study was designed as a randomized complete block design with three replications. Four widely commercially available and utilized mulches, including wood chips, pine needles, scoria (volcanic stone) and black polyethylene were used as the treatment mulches. The study contained plots with only bare soil as the control. The results showed that utilizing the selected mulches demonstrated positive effects on the plant growth, and increased the fresh and dry weight of shoots (p
    Keywords: Flowering plants, Mulch, Green space, Drought stress, Zinnia
  • A. Zeinadini Meymand, M. Bagheri Bodaghabadi, A. Moghimi, M.N. Navidi, F. Ebrahimi Meymand, M. Amir Pour Pages 85-95
    This study was conducted to rate the land characteristics of corn in hot areas based on artificial neural networks and regression models. For this purpose, 63 corn fields were selected in southern Iran. In each farm, a pedon was excavated, described and sampled. A questionnaire was completed for each farm. A stepwise regression model was used to study the relationship between land characteristics and corn yield. A characteristic-function curve was used to rate the land characteristics. Finally, crop requirements were prepared by artificial neural network and regression models and verified by comparing the actual and predicted performance levels. The results of regression analysis showed that soil salinity, exchangeable sodium percentage, sand, clay, phosphorous, gypsum and potassium recorded the highest effect on yield and according to the artificial neural network, the exchangeable sodium percentage, soil salinity, soil texture and cation exchange capacity are the most important. Based on regression and artificial neural network methods, the threshold limit and break even production for soil salinity were 4, 2.5, 12, and 10 dS m-1, respectively, but for exchangeable sodium percentage the values were 18, 14, 35, and 30, respectively. The coefficient of determination (R2) between the actual and predicted yield based on the regression model was 0.88, but it was 0.945 (training data) and 0.837 (testing data) for the artificial neural network. Also, the results of the verification of the prepared crop requirements tables showed that the correlation of determination between the land index and the yield in the regression method was 0.78 but it was 0.81 for the artificial neural network, these results are acceptable in both methods.
    Keywords: Critical production, Crop requirements, Land suitability, Corn, Threshold limit, Very hot region
  • M. Rahmati, N. Hamzehpour Pages 97-106
    Data reduction is used to aggregate or amalgamate the large data sets into smaller and manageable information pieces in order to fast and accurate classification of different attributes. However, excessive spatial or spectral data reduction may result in losing or masking important radiometric information. Therefore, we conducted this research to evaluate the effectiveness of the different spectral data reduction algorithms including Principle Component Analysis (PCA) and Minimum Noise Fraction (MNF) transformation, Pixel Purity Index (PPI), and n Dimensional Visualizer (n-DV) algorithms on accuracy of the supervised classification of the salt-affected soils applying ETM data beside 188 ground control points. Results revealed that data reduction caused around 20 to 30 % decreases in classification results compared to none reduced data. It seems that applying spectral data reduction algorithm in small study areas is not only supportive, but also has negative effects on classification results. Therefore, it may better to not to use the algorithms in small areas.
    Keywords: Modeling, Regression modeling, Salt-affected soils, Salinity, Satellite images
  • M. Gholamnia, R. Khandan, A. Darvishi Boloorani, S. Hamzeh, M. Gharaylou, S. Duan, S.K. Alavi Panah Pages 107-121
    Diurnal air temperature modeling is a beneficial experimental and mathematical approach which can be used in many fields related to Geosciences. The modeling and spatio-temporal analysis of air Diurnal Temperature Cycle (DTC) was conducted using data obtained from 105 synoptic stations in Iran during the years 2013-2014 for the first time; the key variable for controlling the cosine term in DTC modeling known as β was analyzed and considered both as monthly and annual parameter. The effect of environmental variables of humidity, pressure, diurnal air temperature range, and wind speed were analyzed on β. The results showed that there is no significant difference between considering β as monthly (dynamic) or annual (constant) parameter through the year. The RMSE of approach with dynamic β was 2.1 °C and with constant 2.2 °C at 95% percent of whole data in all stations. The analysis of environmental variables showed that humidity had an indirect effect on β. Low pressure areas showed higher β values but high pressure areas showed higher variability in β and lower mean values. In areas with high air diurnal temperature range, lower β values with less standard deviation were observed. High wind areas showed positive effect on β values.
    Keywords: Air temperature, DTC model, Humidity, Pressure, Wind, Spatio-temporal
  • Phytoremediation of soils polluted by heavy metals using Vetiver grass and Tall Fescue
    S. Ghadiri, M.H. Farpoor, M. Hejazi Mehrizi Pages 123-132
    Phytoremediation is a biological method to improve soils contaminated with heavy metals. The objective of the present research was to study the capability of Vetiver grass and Tall Fescue in refining and reducing pollution of Cd, Cu and Zn from contaminated soils. The research was implemented in greenhouse during two separate tests (Vetiver grass and Tall Fescue) in a completely randomized design including seven levels of pollution (0, 50, 100, 200, 400, 600, 800 mg kg-1 soil) from three heavy metal types (Cd, Cu and Zn) in three replications. The effects of different levels of heavy metals on the growth characteristics (fresh and dry weights) of Vetiver were not significant. Besides, the effect of cadmium levels on shoot dry weight, the effect of Zn levels on shoot fresh and dry weights and the effect of Cu levels on shoot and root fresh and dry weights in Fescue were not significant compared to the control treatment. The maximum Cd, Cu and Zn concentrations in Vetiver related to 800 mg kg-1 treatment were found as 591, 298 and 356 mg kg-1. The maximum content of Cd (96 mg kg-1), Cu (27 mg kg-1) and Zn (37 mg kg-1) in Fescue was also measured at soils polluted with 800 mg kg-1. Among different pollution treatments, Cd had the highest uptake and accumulation rate in shoot and root of plants. The results showed the higher capability of Vetiver compared to Fescue for remediation of environments contaminated with heavy metals especially Cd in Iran.
    Keywords: Cadmium, Growth characteristics, Pollution, Remediator plants
  • M.J. Nematolahi, S. Kaboli, M.R. Yazdani, Y. Mohammadi Pages 133-139
    One of the goals of the International Carbon Sequestration Project in South Khorasan Province is to study the sustainability of natural resources, especially in the rehabilitated areas, by reducing the reliance of villagers to the natural resources of the region, creating alternative livelihoods with job empowerment and solving the problems of villagers in the region, especially rural women. The purpose of this study was to predict the rural women’ empowerment who received microcredits during the project. The research was done through a descriptive-correlational method. Statistical sample includes 188 rural women who were members of the microcredit Fund. The validity of the questionnaire was confirmed by panel of research committee experts and the reliability was confirmed by calculating Cronbach's alpha coefficient to 0.95. The results of study showed that there is positively a significant correlation between rural women empowerment and variables of Membership Years, Loan Amount, and Loan adequacy, Age, Literacy Level and Income per month. But rural women empowerment could be predicted by three variables of Loan adequacy, Literacy Level and women Age. Also, Loan adequacy was known as the most powerful predictor of rural women empowerment. Given the positive impact of microcredits on rural women empowerment, as well as rural women empowerment to reduce pressure on ecosystems and improve carbon sequestration, it is proposed to increase the microcredit program and its amount.
    Keywords: Carbon Sequestration Project, Microcredit, Loan, Rural women
  • F. Amiraslani, D. Dragovich, A. Caiserman Pages 141-151
    Desertification was recognized in Iran several decades ago. This phenomenon has gradually affected half the provinces in the country, where droughts exacerbate problems in these drylands. In response, the government has been active in providing considerable funds and human resources to halt desertification through investing in national research and executive projects over the last fifty years. Iran is an excellent case study at the global level for assessing anti-desertification and associated cost-benefit aspects as its climate, society and environment are very similar to the other 17 developing countries in the Middle East and North Africa region. In addition, the country has fifty years of experience in anti-desertification activities which have improved livelihoods through dry-farming, animal husbandry, fisheries, bee-keeping, and market gardening, leading to reverse migration from urban areas to stabilized rural areas. Based on several reliable national reports and case studies as well as two international datasets, an exploratory evaluation is provided for the monetary value of benefits from Iran’s anti-desertification programs. The pivotal premise of the paper is based on the economic valuation of preserved infrastructure and ecosystem services as a result of implementation of anti-desertification plans. Although a cost/benefit analysis was not applied to human resources, this paper also considered other indirect benefits to anti-desertification plans including job creation, improved health conditions, and increased levels of agricultural and industrial activity. This cost/benefit evaluation of anti-desertification programs in Iran is estimated to provide a high and positive contribution equivalent to about 3.75% of the country’s annual GDP.
    Keywords: Cost-benefit, Anti-desertification plans, Iran, long-term, National
  • A. Goudie Pages 153-164
    In drylands, both dust storms and ephemeral salt lakes (playas) are common. Observations using remote sensing and ground studies have shown that these playas can be major sources of saline dust storms. Some basins have recently become desiccated as a result of water abstraction by humans, and these have become significant sources of dust. The timing and amounts of dust emissions depends on such factors as rainfall and drought events, the availability of sediment, and the nature of surface crust materials.
    Keywords: Dust, Salt, Playas, Sodium sulphate, Deflation