ECOPERSIA
Volume:5 Issue: 1, Winter 2017

Landsat data for 1992, 2000, and 2013 land use changes for Ekbatan Dam watershed was simulated through CA-Markov” model. Two classification methods were initially used, viz. the maximum likelihood (MAL) and support vector machine (SVM). Although both methods showed high overall accuracy and Kappa coefficient, visually MAL failed in separating land uses, particularly built up and dry lands.Therefore, the results of SVM were used for Markov Chain Model and “CA” filter to predict land use map for 2034. In order to assess the ability of “CA Markov” model, simulation for 2013was performed. Results showed that simulated map was in agreement with the existing map for2013 at 84% level. The land use map prediction showed that built up area of 0.8298 km2 in 2013 will increase to 1.02113 km2 in 2034. In contrast, irrigated agriculture will decrease from 17.33 km2 to 17.16 km2, and rain fed agriculture from 45.07 km2 to 44.49 km2. Results of this research proved the application of “CA Markov” model in simulating the land use changes.

The optimal allocation of the Chahnimeh water resources among different sectors, viz. domestic, agricultural and environmental consumptions, was determined using the goal programming method in GAMS, based on the present condition in the area. Results showed an increase of 15.4, 44.5 and 230% in allocation of water to domestic, agriculture and environment sectors, respectively, in this method as compared to the present allocation. Besides, implementation of the second water transferring line to Zahedan city would resultin a 66% increase in the water transferring rate to this city without any change in water supply for domestic sector in Zabol city and the surrounding villages. The scenario of 20% reduction in water per capita consumption led to about 5.9 million cubic meters saving in water supply from Chahnimeh reservoirs to the domestic sector. According to the projected population growth for 2025 in the study area, water consumption in domestic sector will increase by 15.9%. Results showed that the goal programming can be applied as a useful tool to analyze the effect of different scenarios on water demand and supply management and, hence, to allocate water for different sectors in a most appropriate way.

The effect of soil and topographic features on distribution of Amygdalus scoparia in Nehbandan (Iran) was investigated. Slope, aspect and altitudinal maps were overlaid to prepare a working map unit. Quantitative and qualitative traits, including height, number, collar diameter of sprout with the highest diameter, crown diameter and trunk health were recorded in 1000 m2 plots (27 plots). In each plot, soil was sampled at depth 0-30 cm. The regression model of the traits with topographical and edaphic factors showed that 70% of variations of A.scoparia sprout height was explained with calcium carbonate, 50% variations of the number of sprouts was explained with clay, and 77% variations of the crown diameter was explained with calcium carbonate. Correlation results revealed that some soil properties such as clay, potassium, organic matter, sand, acidity and lime accounted for A.scoparia distribution. Future work on other indicating factors will help us to determine the optimum range of these factors for this plant species.

Finding a minimum allowable radius length of a circle horizontal curve is essential to reduce earthwork cost or damage to the forest ecosystem, as well as make driving more comfortable. The present study is conducted i) to analyze different radius lengths of circle horizontal curves using an integrated approach consists of a Civil3D in concert with the field surveys, and ii) to propose a set of geometric design criteria which are more consistent with the existing condition of forest road network in Hyrcanian forest, north of Iran. Depth of the rutting (i.e., machine footprint) and soil mechanical properties are examined for a total of 36 existing horizontal curves with different radius lengths. Further, technical characteristics (i.e., stopping sight distance, horizontal sight line offset and turning speed) and a few parameters on pavement damage are included and incorporated into the research objective. No-statistical differences between radius lengths of the horizontal curve for classes of 10-15 and 16-20 m may associate with dissimilarity in the soil mechanical properties and in the dimension of the rut depth. These findings confirmed that it is therefore possible to shorten allowable radius length of a circle horizontal curve to at least 12 m under a longitudinal slope of 5% for forest road network in the north of Iran.

The socio-economic factors affecting land use changes in the Maraveh Tappeh region was determined from the viewpoint of beneficiaries and experts. The items of questionnaires designed as rating scale based on the five options Likert. Reliability of questionnaires was determined by Cronbach's alpha. Two sets of questionnaires were designed for beneficiaries and experts. Reliability of beneficiaries and experts questionnaires obtained 0.75 and 0.80, respectively. A total of 310 beneficiaries and 42 experts responded to the questionnaires. Mann-Whitney non-parametric test was used to compare the mean between the experts and beneficiaries. The reality amount of significant difference was obtained from the effect size. Rating average was used for each item and its priority. In ten items, significant difference at the 0.01 level between the viewpoints of beneficiaries and experts was observed. The high cost of living, low income of rural families and unemployment in rural areas were the top three priorities from the viewpoint of beneficiaries. The low income of rural household, the high cost of living and increasing the price of farmland were the most effective factors from the viewpoint of experts. Economic factors were the key priorities of land use change in viewpoint of both beneficiaries and experts, indicating that experts had the necessary experience and understanding of beneficiaries’ condition and were positive and important notes for policy making and management issues.

The effects of different climatic, soil, geometric, and management factors on soil organic carbon (SOC) degradation and sequestration potential was evaluated in the semi-arid zone of Mereg watershed, west of Iran. Two nonparametric methods, viz. Classification and Regression Tree (CART) and feed forward back propagation Artificial Neural Network (ANN) were compared with parametric Multivariate Linear Regression (MLR) in estimation of SOC content. Soil sampling was conducted using randomized systematic method in work unit map by overlying soil, aspect and slope maps. Results indicated that linear models had higher prediction errors. The CART with all variables (physical and management) and the ANN with 31-2-1 topology carried the highest predictive capability, explaining 81% and 76% of SOC variability, respectively. ANN models overestimated SOC content and showed a higher capability to detect the effects of management factors on SOC variations. In all the methods, management factors dominantly controlled SOC stock sequestration or degradation in different land use.

Pedological criterion affecting desertification in alluvial fans was investigated, for which the map of units was prepared by crossing maps of land use, geology, slope classes and grid layer created by the extension of ET Geo-Wizards in ArcGIS 10.3. Three indices of salinity, erodibility, and permeability of soil were considered and classified. Weights of criteria and consistency ratio were calculated by the AHP method and ELECTRE I method was used to prioritize the options. After creating the weighted super matrix and calculating the concordance and discordance matrix, the difference between dominance and defeat values were calculated. The results showed that the difference in values obtained from AHP-ELECTRE I technique varied from -15 to 16. The alluvial fans were classified into three classes of I, III, and IV from the viewpoint of pedological criterion affecting desertification by using AHP-ELECTRE I technique. Results showed that 71.99% of the area was in the low desertification potential, while 2.19% and 25.82% were in the high and very high desertification potential, respectively.