Desert
Volume:16 Issue: 1, Winter - Spring 2011

One of the characters in Iranian Model of Desertification Potential Assessment (IMDPA) is soil. Since soil is very important in the degradation of land, so some indices were determined for this character in order to evaluate desertification potential of arid, semi-arid and dry sub humid areas of Iran. The indices included soil texture, deep gravel percentage, soil depth, and EC. To calibrate the soil character of the IMDPA, above mentioned indices were assessed in Segzi Pediment as arid region. To do this, in first stage, map of the study area was prepared based on slope, land use and geological maps. Scores of indices were recorded in different study units. At last, using the formula, SI=, final score of soil indicator (SI) was determined in the study area based on IMDPA. In this model, desertification potential classes are low, moderate, high and very high. The map showed that 1.5%, 20% and 78.5% of the study area are considered as medium, high and very high desertification intensity classes, respectively. More over, there wasnt low class based on vegetation character.

Water erosion is a major environmental problem in many parts of the world. Majority of semi-arid countries are concerned because of their specific climate and soils sensitivity, but also because of the recent intensification of human activities and agricultural practices. Accurate estimation of water erosion for various land-use and climate scenarios is so an important key to define sustainable management policies. In the last decades, several studies have been carried out to build models suitable for quantifying sedimentation. Among these models, the Water Erosion Prediction Project (WEPP), is a physically based, distributed-parameter model that has been developed and mainly validated in America. Only few studies have investigated its applicability to environmental conditions that differs from those where the model was developed. The aim of this work is to test the efficiency of WEPP model to predict runoff and sediment yield at catchment scale in a semi-arid area. Continuous simulations have been conducted between 1996 and 2005 in Orazan Watershed. Comparison between predictions and measurements indicates that WEPP under-estimates sediment volumes of 23% and over-estimates runoff volumes of 27%. Results shows that sediment yield and Runoff outputs are relatively well predicted but lack of input data to run WEPP model is an important challenge in Iran conditions.

Increasing level of carbon dioxide CO2 due to industrial activity is primarily cause of global warming. Planting Artoplex lentiformis can help to reduce atmospheric CO2 buildup partly replacing use of fuels and by carbon storage. The objective of this study was to determine the effects of row spacing on carbon storage. A split- plot design with three replications included three row spacing (2×2, 4×4, and 6×6m) was applied. Some laboratory samples were taken from aerial and root biomass of Artoplex, and soil for determination of carbon storage. Results showed the values of carbon storage of aerial and root biomass among row spacing was significant different (p=0/o5%). The highest carbon storage was related to 2×2 m row spacing, reached 74583.6 and 6862.5 kg/ha in aerial and root biomass respectively. The carbon amount of soil had no significant differences (p=0/o5%) between treatments. The ranking of the plantation carbon storage by row spacing was 2×2 m > 4×4 m > and 6×6m and by components was aerial carbon> root carbon > soil carbon

Biological diversity and species richness have been declined throughout the world as a result of human activities. Measuring species richness is important in rangeland conservation to evaluate the status and trends of native plant species, detecting non-native species invasion and monitoring rare species. However, heterogeneity in plant distribution makes inventories difficult. In this study two methods of measuring species richness, Whittaker and Modified-Whittaker plots, were compared to see how well they captured the species diversity. This was carried out on grassland and shrubland vegetation types using three replicates in Salook National Park in Esfaraien, Iran. The result of this study showed that there is a significant difference between the two methods in estimating species richness for both vegetation types where greater species richness was found in Modified-Whittaker plot. The regression model for species-area relationship was significant for both methods in each vegetation type but explaining more variation (91%) in Modified-Whittaker plot. There was no significant difference between the two methods according to the sampling time except for 1 m2 sub-plots; however, the Modified-Whittaker plot is more convenient for establishing and measuring in the field.

Desertification refers to land degradation phenomenon in arid, semi-arid and dry sub-humid areas, resulting from various factors including climate variation and human activities. For evaluation and mapping of desertification many research have been conducted leading to regional and local models. In this research, among different existing methods IMDPA‌ was selected and desertification intensity was evaluated on the basis of 2 criteria and 8 indices including: soil (soil depth, Electrical Conductivity, texture and gravel percentage) and water (groundwater table decrease, EC, Cl concentration, Sodium Absorption Ratio). Each criterion was assessed based on the selected indices which result in qualitative mapping of each criterion cased on geometric average of the indices. Finally, sensitive map of region was extracted using geometric average of all criteria. Thematic databases, with a 1:50000 scale resolution, were integrated and elaborated in a GIS based on arc/info8, arc view3.2 and especially ILWIS. Analysis of desertification criteria in Jarghooyeh region showed that among study criteria, soil criterion is a major problem in the study area with a geometric average of 2.25 which shows medium class while water criterion with a weighted average of 1.14 stands in low class of desertification. Also, the results showed that that Electrical Conductivity index with quantitative value of 3.54 classified in very high class of degradation, and ground water recession with quantitative value of 0.05 classified in low class of desertification were the most and the least effective factor on land degradation among studied indices respectively.

The relative impacts of different types of land use on the surface water quality are yet to be ascertained and quantified. In this paper, the influence of different types of land use on surface water quality is investigated. Rain events samples from different land use in the central plateau, Iran, were analyzed for major ions. Statistical analyses were employed to examine the statistical relationships of land use and water quality on a regional scale in Iran central plateau. Principal component analysis was used to investigate the processes controlling the effects of land use on the water quality in this area. The higher correlations of range than other land uses with major ion, specifically pH and HCO3, were showed and it's maybe reflecting the effects of the season the samples were taken.

In recent decades artificial neural networks (ANNs) have shown great ability in modeling and forecasting non-linear and non-stationary time series and in most of the cases especially in prediction of phenomena have showed very good performance. This paper presents the application of artificial neural networks to predict drought in Yazd meteorological station. In this research, different architectures of artificial neural networks as well as various combinations of meteorological parameters including 3-year precipitation moving average, maximum temperatures, mean temperatures, relative humidity, mean wind speed, direction of prevalent wind and evaporation from 1966 to 2000, have been used as inputs of the models. According to the results taken from this research, dynamic structures of artificial neural networks including Recurrent Network (RN) and Time Lag Recurrent Network (TLRN) showed better performance for this application (due to higher accuracy of its out puts). Finally TLRN network with only one hidden layer and hyperbolic tangent transfer function was the most appropriate model structure to predict 3-year moving average precipitation of the next year. In facts, by prediction of the precipitation 12 months before its occurrence, it is possible to evaluate drought characteristics in advance. Results indicated that the combination of precipitation and maximum temperature are the most suitable inputs of the models to get the most outputs accuracy. In general, it was found that ANN is an efficient tool to model and predict drought events.

In this paper trends of precipitation and stream flow are analyzed in the Atrak River basin in the North Khorasan province. Normal score linear regression, Mann-Kendall, and Seasonal Kendall trend tests were adopted. Three precipitation variables and two stream flow variables including total precipitation, maximum daily precipitation, and number of rainy days, mean discharge and peak discharge were studied. Annual, seasonal, and monthly trends of these variables were examined during a 35-year period starting from 1971 in six hydroclimatological stations. The results with all tests showed that despite no evidence of significant trend for the precipitation variables, trends for the hydrologic variables found to be significant. Whereas for most of the stations significant downward trend was observed for mean discharge, and for one third of the stations significant upward trend was observed for peak discharge. The results of seasonal trend analyses indicated that downward trends in the mean discharge are almost completely homogeneous across the seasons and significant for autumn, winter and spring flows in most of stations. Overall, although the precipitation pattern is considered as the major driving variable for the river discharge regime, but it is not the only possible cause and other causes such as landscape, land use changes and increased evapotranspiration due to higher temperature may play a role

In order to study of hydropriming and halopriming on germination and early growth stage of wheat (Triticum aestivum L.) an experiment was carried out in laboratory of the Department of AgroNomy and Plant breeding, Shahrood University of Technology. Seed treatments consisted of T1: control (untreated seeds), T2: soaking in distilled water for 18 h (hydropriming). T3: soaking in -1.2 MPa solution of CaSO4 for 36 h (halopriming). Germination and early seedling growth were studied using distilled water (control) and under osmotic potentials of -0.4, -0.8 and -1.2 MPa for NaCl and polyethylene glycol (PEG 6000), respectively. Results showed that Hydroprimed seeds achieved maximum germination seedling dry weight, especially during the higher osmotic potentials. Minimum germination was recorded at untreated seeds (control) followed by halopriming. Under high osmotic potentials, hydroprimed seeds had higher GI (germination index) as compared to haloprimed or untreated seeds. Interaction effect of seed treatment and osmotic potential significantly affected the seedling vigour index (SVI).

The main goal of this paper is to propose a new practical method for hydrologic soil group estimation in surface runoff process based on geomorphology facieses and slop. The determination of CN based on this method can reduce the time and cost of project. In this research the upstream rivers of Glinak Watershed have been used as a case study to examine the efficiency of proposed method with a comparison with CN method, the Rational and Creager methods. The results show that RSS of estimated flood based on - CN method with proposed and tradition CN and Rational to calibrated Creager's method are 31.5, 103.85 and- 11.39-, respectively. With these results, the new method can be proposed in various climatic conditions to estimate initial curve number in flood modeling and calibration.