Ahmad Mokhtari; kourosh shirani; Navid Moslemzadeh
Abstract
Extended abstractIntroductionSegzai plain, 40 kilometers from Isfahan city, with an area of about 40,000 ha, is considered a serious threat to this historical city. This plain, which until a few decades ago was a relatively prosperous reed and meadow, has now become a huge danger in terms of nature destruction ...
Read More
Extended abstractIntroductionSegzai plain, 40 kilometers from Isfahan city, with an area of about 40,000 ha, is considered a serious threat to this historical city. This plain, which until a few decades ago was a relatively prosperous reed and meadow, has now become a huge danger in terms of nature destruction and environmental pollution. Two natural and human factors play a role in the desertification of this region. Among the natural factors are low rainfall, high evaporation, the presence of limiting layers in the soil and strong winds and from human factors, excessive grazing and overgrazing of livestock as well as bush-cutting, rapid population growth and excessive exploitation of existing resources decline Underground water and most importantly, exploitation of surface mines, especially gypsum mines, can be mentioned. The main goal of this research was to evaluate the effectiveness of the SEBAL model for estimating the actual evaporation and transpiration of the Segazi Plain, considering the arid and semi-arid location of the region using the landsat 8 image. Materials and methodsTo do this research, first, landsat 8 images were processed. Extraction of required information from satellite images in this research was done during three main stages, i.e. pre-processing, processing and post-processing. In other words, in the pre-processing stage, after performing atmospheric, geometric and other necessary corrections, the image was referred to the ground. In the area of data processing, different highlighting methods and statistical analyzes and remote sensing were done in order to achieve the information layers of the plan. In order to evaluate the results in the image processing stage, the post-processing of the data based on various analyzes was used to evaluate the reliable layers in terms of accuracy and precision. After that, the SEBAL algorithm was implemented. first the amount of net radiation (Rn) was calculated according to the temperature of the earth's surface and vegetation and the amount of energy reaching the earth, then the heat flux of the soil (G) was obtained to determine the amount of transfer capability The heat into the soil was determined, then it was determined to calculate the amount of sensible heat flux (H), which determines the loss of energy from the soil to space. Finally, after determining the sensible heat flux, evaporation and transpiration were calculated. The SEBAL algorithm calculates the energy balance equation in order to calculate the actual evaporation and transpiration of the plant. Results and discussionSurface albedo parameters (the highest and lowest weighted values are around 0.85 and 0.16), soil surface temperature (the highest and lowest weighted values are around 326 and 299 degrees Kelvin), NDVI vegetation index (the highest and lowest weight values related to areas with good vegetation close to +1 and related to water and water bodies close to -1), the amount of net energy reaching the surface of the earth (the highest and lowest weight values are about 703 and 210 Wm-2, soil heat flux (the highest and lowest weight values are about 130 and 35 Wm-2), sensible heat flux (the highest and lowest weight values are about 323 and 23 Wm-2 , momentary evaporation and transpiration (the highest and lowest weight values are about 0.842 and 0.225 mm) and daily transpiration evaporation (the highest and lowest weight values are about 20.2 and 5.4 mm) are among the most important effective parameters in this Sabal algorithm which were investigated in this research. Changes in actual transpiration evaporation (the highest weight values about 0.85 mm and the lowest weight values about 0.16 mm). The obtained results showed that the SEBAL model has well predicted evaporation and transpiration in areas that have vegetation, mostly agriculture and gardens, so that the amount of water loss through evaporation has been predicted close to the values found in the eastern synoptic station of Isfahan (airport Shahid Beheshti) is registered. ConclusionThe amount of error obtained in SEBAL calculation was 0.1%. The amount of real momentary evaporation and transpiration has been calculated in the range between 0.22 and 0.84 mm, according to the weather conditions of the region and the temperature of the air near the surface (27 to 50 degrees) and the amount of evaporation and transpiration recorded by the Penman-Monteith equation (30.0 mm in the east of Isfahan synoptic station), this value is in a reasonable range. Comparing the outputs of Sabal model with the amount of evaporation and transpiration obtained in the same station, which shows the root mean square error (RMSE) value of 0.1, indicates the suitability of this algorithm in calculating evaporation and transpiration in Segazi region. Considering the growing need of the country to prevent the wastage or excess consumption of water in the agricultural sector, either through changing the cultivation pattern or changing the irrigation methods, the application of the developed tool of the Sabal algorithm in this research can provide valuable information to the experts and managers of the water sector put agriculture. The results obtained from this implementation of this research showed that remote sensing has a good potential for estimating actual evapotranspiration (ETA) by having different algorithms such as SEBAL algorithm and minimum ground information.
Atefeh Davari Dolatabadi; Akbar Ghazifard; Kourosh Shirani; Farzad Heidari Morche khorti
Abstract
East of Isfahan City, especially around Segzi Plain is one of the desert areas of the country that due to the flatness and soils sensitivity to wind erosion, there is high susceptibility to wind erosion. The aim of this study is to evaluate the possibility of using saline water of Segzi Plain and its ...
Read More
East of Isfahan City, especially around Segzi Plain is one of the desert areas of the country that due to the flatness and soils sensitivity to wind erosion, there is high susceptibility to wind erosion. The aim of this study is to evaluate the possibility of using saline water of Segzi Plain and its effect on the soil strength properties, crust formation and its stability against wind erosion. In order to conduct this research, five soil samples with different textures were collected from top soil surface and were transferred to the laboratory along obtained saline water sample from surface aquifer. After determining some of the physical and chemical properties of samples, they were examined in wind tunnel with specified velocity for soil erosion tests. The first soil sample was flooded with saline water and the rest were treated with either spraying of undiluted saline water or spraying of diluted saline water with 2 to 1, 1 to 1 and 1 to 2 ratios of saline water to water. In this regard, parameters such as salinity of saline water, erosion threshold velocity of dried treated soil samples, maximum dry density, thickness, strength and sieve analysis of the crusts were determined. The results indicated that, as the salinity of saline water increases, the strength, thickness and maximum dry density of forming crust and wind erosion threshold velocity also increases in the model. Analysis of variance used to investigate the effects of soil texture, salinity of saline water, crust thickness and threshold velocity to control wind erosion showed significant difference in 1% level. Sample C1 with the highest percentage of fine grains had threshold velocity of 11 m.s-1, but sampleE1 with the lowest percentage of fine grains had threshold velocity 6.23 m.s-1. The presence of a high amount of sodium makes restrictions on the possibility of using saline water as mulch scientifically and practically but the results showed that the use of saline water can increase the density of dirt roads.
Kourosh Shirani; Farzad Heydari; Alireza Arabameri
Abstract
Landslides are major natural hazards which not only cause damages to human life but also provide economic losses on infrastructures. In order to determination of the most important method of estimation recognizing appropriate method to estimate landslide, in this research, the efficiency of two ...
Read More
Landslides are major natural hazards which not only cause damages to human life but also provide economic losses on infrastructures. In order to determination of the most important method of estimation recognizing appropriate method to estimate landslide, in this research, the efficiency of two methods of landslide hazard zonation including methods of Artificial Neural Network and Multivariate regression were compared. Therefore, in this research, first, landslide inventory map was obtained using aerial photos interpretation, satellite images processing, geology maps review and field surveying. Also, the 9 important effective factors are in occurrence of landslide including lithology, land use, slope angle, slope aspect, elevation, precipitation, distance to fault, distance to road, density of drainage were determined using inspect of field and literature review. After producing of layers and weighting to effective factors using inventory map, landslide hazard zonation was made by Artificial Neural Network and Multivariate regression models. From 200 landslides identified, 140 (≈70%) locations were used for the landslide susceptibility maps, while the remaining 60 (≈30%) cases were used for the model validation. The quality sum (Qs) and precision (P) indices for Artificial Neural Network model are 0.15, 0.08 and for Multivariate regression model are 0.14, 0.05 respectively. This results show that artificial Neural Network is the better model in landslide hazard zonation in this area, therefore an accurate landslide hazard zonation map can be prepared by selecting and applying the proper method.
Alireza Arabameri; Kourosh Shirani
Abstract
Landslides are major natural hazards and adopting a regional strategy is very necessary to reduce its damages and maintains natural and human resources. The purposes of this study are the recognition of effective factors in landslide and the zonation and assessment of in terms of the occurrence of this ...
Read More
Landslides are major natural hazards and adopting a regional strategy is very necessary to reduce its damages and maintains natural and human resources. The purposes of this study are the recognition of effective factors in landslide and the zonation and assessment of in terms of the occurrence of this phenomenon using the Dempster-Shafer theory and GIS technique. In this research with integration of Landslide map and effective factors maps such as lithology, land use, slope angle, slope aspect, elevation, precipitation, distance to fault, distance to road, and density of drainage were done analysis of hazard. Finally, landslide occurrence zones were recognized from very low risk to very high risk. Total area of region is 1780516, 12/66 percentage of area (237259) existed in very high risk,12/78 percentage of area (239045) existed in high resk, 21/24 percentage of area (397316) existed in medium,29/33 percentage of area (548649) existed in low and 23/96 percentage of area (448247) existed in very low class. Model evaluated using one to third of landslide points, Frequency Ratio (FR), Seed Cell Area Index (SCAI) and ROC. The results show that Frequency Ratio and Seed Cell Area Index indicate appropriate accuracy of classification to 5 class. Also accuracy of ROC in Dempster-Shafer theory with AUC (%73) indicate high correlation between Risk map and Landslide hazard map and good evaluation of model.The results of these studies can be used as fundamental information by environmental managers and planners.
