مجله مدیریت بیابان
پیاپی 5 (بهار و تابستان 1394)

Groundwater is known as one of the most valuable natural resources which play an important role in providing water supply in arid areas. In this study, multi-criteria decision-making (MCDA) methods were used for sensitivity analysis of the effective parameters in groundwater potential prediction based on the lithology, annual rainfall, drainage density, lineament density and land slope parameters in Ghorveh-Dehgolan plain as a case study. The normalized weights of the parameters were determined based on the paired comparisons of AHP approach. After preparing the groundwater potential prediction map, validation of the model was conducted by using the pumping tests data of 20 wells in the study area. Sensitivity analysis of the effective parameters in groundwater potential prediction was measured using the elimination method and finally accuracy of the maps was evaluated. The results of the sensitivity analysis showed that all parameters have a positive impact on the accuracy of the groundwater potential prediction while the best accuracy was obtained by combination of all layers (85%), and the worst accuracy resulted when the lithology was eliminated from the decision layers (60%). Therefore, the lithology parameter through effects on physical properties such as density of lineaments and faults, porosity and permeability has the highest impacts on the accuracy of groundwater potential prediction. The results also revealed that rainfall and slope variables, in despite of their little changes in a plain, are effective in accuracy of groundwater potential prediction.

Environmental pollution as technologic desertification factor is the most important challenging issue in industrialized and developing societies. Due to the presence of several mineral sites in Bafgh, the most important reason of desertification is pollution caused by industries and mines. This study aims to determine the emissions effluent from processing iron ore in the Bafgh region. Totally, 16 samples of effluent were taken over the period 2008- 2013, and 18 parameters were measured in the laboratory. After testing the related data normality and variance analysis, index of PI, IPI and MCd were determined for the collected data. The results showed that 27.7% of the parameters are without non-significant year changing while 72.3% of the parameters have significant annual changes. The results for the PI index showed that 66.6% of the parameters show less contamination level and 33.4% of the parameters are at moderate to high contamination level. According to the results obtained for the IPI and MCd index, Nitrate (NO3) and Sulfate (SO4) classified at the moderate and high levels of pollution and determined as the contaminants of effluent from processing. Considering desert ecosystems are sensitive and fragile, it is suggested to determine the concentration of pollutants in the wastewater processing parameters with deposited sediments to study the feasibility of removing contaminants by phytoremediation. It might be useful to determine desertification intensity in Central Iron Ore Company marginal and desert regions in Bafgh with the conventional models and taking into account the environmental pollution, Nitrate and Sulfate indices.

The aim of this study was to evaluate the efficiency of artificial neural networks in supplying predictive maps of plant species habitats distribution in Qum province rangelands, Iran. For this purpose, soil and vegetation sampling was done after determination of homogenous unit by combining of slope, aspect and elevation maps and environmental variables maps were prepared using geostatistics and GIS. To prepare the artificial neural network models, the best network structure, was determined following required data preprocessing (normalizing data and partitioning of data into three sets, training, test and validation), improving adjustable parameters (such as transfer function, learning rule, the number of hidden layers, number of hidden layer neurons) and using statistical parameters calculated in the test phase (MSE). After selecting the optimal network, simulations were performed to estimate the probability of the presence or absence of the species and continuous probability maps of the presence or absence was prepared at each species habitat using Arc GIS. Then the optimal threshold was determined using equal sensitivity and specificity method and the compliance between predicted and actual maps were examined by calculating kappa. Based on the results, the most accurate prediction models were obtained for all habitats using sigmoid transfer function and the Levenberg Marquardt algorithm. The results also showed that habitat predictive and actual maps of Artemisia sieberi, Halocnemum strobilaceum, Tamarix passerinoides, Seidlitzia rosmarinus and Artemisia sieberi have excellent, very good, good, fair and poor compliance, respectively. These results indicate that the multilayer perceptron has acceptable accuracy in the modeling and estimation of the geographical distribution of the studied species habitat and if the network input variable be chosen properly, the network can simulate presence or absence of plant species with high accuracy.

Land surface changes accurate and timely detection provides a basis to better understand the relationships and interactions between human and natural phenomena for appropriate management and optimal use of resources. Trend of environmental issues such as land degradation, ecosystem potential reduction and desertification can be realized by monitoring land use changes in temporal intervals. The current study is aimed to monitor land use changes of Daryacheh Namak area to recognize desertification in a 36 year period using Landsat satellite data, remote sensing and GIS techniques. The results of land use changes monitoring shows that Kavir-e-Namak land use area had little changes and has increased about 5.26 km2. The area of salty and bare lands has increased (457.13 km2), rangeland area decreased (380.3km2), sand dune area decreased completely linear (194.57 km2), and finally the area of agricultural land has increased (118.35 km2). Final results showed that satellite images are of unique potential in extracting land uses. It also became clear that Landsat satellite imagery with a spatial resolution of 10 meters have the required ability of land use maps extraction in the regional scale.

Mulch is one of the most common materials for soil stabilization which prevents wind erosion and dust emissions. In this respect, the sustainability of mulches against corrosive environmental factors is important for selection. In this study, the resistance of some abiotic mulches was examined in simulated desert conditions against pressure by pocket penetrometer at different temperatures. Also, to evaluate the amount of surface leaching, the mulches were tested against spraying water as well. Treatments include 13 types of mulches, nano-polymer mulch, sand, stone powder, sludge and clay soils. Two types of eroded soils including moderate and severe soil erosion and three levels of temperature including ambient temperature, 50 ºC, 60 ºC all of them with three replications were studied. The results showed that sprayed polymers on severe soil erosion and under both 50 ºC and 60 ºC temperatures had the maximum compressive strength. Also the results of spraying water on the treatments showed that polymeric mulch was more resistant against leaching than others.

In this study, the groundwater level depletion and electrical conductivity (EC) were chosen to assess the water quality and quantity changes in Kashan plain, Iran. The relevant hydrographs were drawn using Thiessen polygons based on the piezometric data. Moreover, the groundwater depletion, the elevation contour line and iso- electrical conductivity maps were provided using GIS. Also, the relation between EC and Anions and Cations (such as Ca2+, Mg2+, K+, Cl-, Na+, SO42-, HCO3-) were determined. The calculated Standard Index of Annual Precipitation (SIAP) in five meteorological stations showed that normal precipitation has the most percentage of frequency. Also, the results of drawn maps showed that the groundwater flows from south of the plain towards the Kavir in the north part of the plain. The most depletion of groundwater level and the withdrawal have also occurred in the south and south-eastern parts of the plain mainly due to the concentration of agricultural lands. Electrical conductivity has direct relation with concentration of ions in all cases, except bicarbonate. According to the hydrographs; the average level of groundwater has decreased 10.02 meters over 19 years and the groundwater level depletion has consequently decreased poor water quality.