Search Results (87)

Understanding aeolian sediment transport and wind erosion enhances our knowledge of desert dune formation and sand migration. The Makran region of southern Sistan and Baluchistan is prone to wind-driven erosion alongside frequent sand and dust storms (SDSs). Hourly wind data from two meteorological stations spanning 1994–2020 were analyzed to study erosive winds and sand transport. Wind energy analysis using drift potential (DP) indicated low energy (DP < 200 in vector unit) and minimal spatial variation across the Makran dune fields. The effective winds transporting sand particles were towards the east from November to May, and in the northwestern direction from June to October. The DP showed a gradual decline in the study area from 1990 to 2022, with no significant temporal trends. The sand dune morphology analysis indicates that bimodal wind regimes primarily form linear dunes and sand sheets, while crescentic, transverse, and topographic dunes are also present. Full article

The rapid expansion of the petrochemical industry has led to significant environmental issues, including groundwater and soil contamination from hydrocarbon spills. This study investigates the movement and dispersion of hydrocarbon contaminants in the Rey industrial area in Tehran (Iran) using a two-dimensional finite element model. The results indicate that the oil plume exhibits slow migration, primarily due to low soil permeability and high hydrocarbon viscosity, leading to localized contamination. High-density pollution zones, such as TORC and REY7, are characterized by persistent hydrocarbon accumulation with minimal lateral migration. The findings emphasize the limited effectiveness of natural attenuation alone, highlighting the need for targeted remediation measures in high-density zones to accelerate contamination reduction. This study provides insights into the dynamics of hydrocarbon pollution and supports the development of effective remediation strategies. Full article

Dust is one of the most important problems of human societies in arid and semi-arid areas. This study analyzed the rising and propagation of the dust storm occurring from 21 to 23 May 2016 in Isfahan province (Central Iran) by using the WRF-Chem and HYSPLIT models. The dust storm was visualized using visible imagery and coarse-mode aerosol optical depth data from satellite sensor data, and dust emission and transport were simulated for Central Iran by using WRF-Chem with the AFWA and GOCART schemes. The results show that the dust concentration in Sistan and Baluchistan province and the Persian Gulf was as high as 2000 µg/m³, and both schemes estimate the highest amount of dust emissions from the central parts of Iran and the eastern part of Isfahan province. PM10 data of Yazd station was used to verify the model outputs, which showed that the AFWA dust scheme has a higher correlation coefficient with observations (0.62) than the GOCART dust scheme. This case study suggests that WRF-Chem dust schemes simulate dust rising and propagation in Central Iran with reasonably good reliability, though further determination and enhancement are still required for an accurate prediction of dust concentration and extents. Full article

A novel 4-to-2 photonic crystal encoder is proposed by modulating the intensity of four input optical signals, and four distinct output states are achieved. Nonlinear rods are employed to couple input waves into resonant cavities, directing the light to the desired output waveguides. The proposed design, with a footprint of 114 µm², demonstrates efficient encoding operation at a wavelength of 1550 nm and is highly suitable for integrated photonics applications. A comprehensive comparative analysis revealed that the proposed 4-to-2 encoder exhibits a time response 176 fs faster than previously presented encoders. Furthermore, the contrast ratio of the designed structure is as high as 13.78 dB to distinguish between logic 0 and 1. These advancements hold significant potential for enhancing the performance of compact, high-speed digital circuits. Full article

Studying the current range of species presence is crucial for ecologists and related scientists to understand potential habitats and the influence of environmental factors on species distribution. In this study, we used species distribution modeling (SDM) to look into where the yellow-bellied gecko, also known as the northern house gecko (Hemidactylus flaviviridis Rüppell, 1835), lives in Iran. We achieved this by combining four machine learning algorithms: Random Forest (RF), the Support Vector Machine (SVM), Maximum Entropy (Maxent), and the Generalized Linear Model (GLM). We utilized 19 historical bioclimatic variables, the Digital Elevation Model (DEM), slope, aspect, and the Normalized Difference Vegetation Index (NDVI). After calculating their correlations, we selected variables for modeling with a variance inflation factor (VIF) of less than 10. The findings indicate that the variables “Precipitation of the Coldest Quarter” (BIO19) and “Mean Temperature of Wettest Quarter” (BIO8) have the most significant influence on the species’ distribution. The gecko primarily inhabits low elevations and slopes, particularly those below 400 m above sea level with slopes less than 8 degrees, primarily in southern Iran. Additionally, we found that the NDVI had a minimal impact on the distribution of the species. Therefore, we identify the provinces of Khuzestan, Bushehr, Hormozgan, and Fars, along with parts of the coastal strip of Sistan and Baluchistan, as suitable areas for the current presence of this species. Full article

Linkage disequilibrium (LD) maps are fundamental tools for exploring the genetic basis of traits of interest in any species. Quantifying LD patterns in cattle breeds has been made possible due to the availability of huge quantities of SNPs through modern sequencing technology. The present research aims to determine and compare linkage disequilibrium levels at different distances on the genome of Sistani domestic cattle and subspecies of Bos taurus and Bos indicus based on genome SNP data. A total of 60 Bos indicus Sahiwal (dairy) and Nellore (beef), Bos taurus Hereford (beef) and Holstein (dairy), and Sistani cattle were sampled and genotyped using Illumina Bovine HD 770 k chip. To ensure the caliber of the sequencing, 10 samples (genetically sequenced cattle) were randomly chosen among all breeds represented. LD was evaluated at distances of 1–50 Kb, 50–100 Kb, 100–500 Kb, and 0.5–1 Mb, and average r² values for all autosomes were calculated within distance classes. For all breeds, the average r² was over 0.2 at distances less than 100 Kb, while for Sistani, Nellore, and Sahiwal, the average r² was above 0.2 between 100 and 500 Kb. Furthermore, for all breeds, the average r² exceeding 0.3 was noted at distances smaller than 50 Kb, while this amount for Holstein and Hereford was observed at distances between 50 and 100 Kb. In various breeds, greater changes in LD levels were observed (at <10 Kb distance). In this study, the Sistani breed showed LD decay patterns similar to indicine cattle (Nellore and Sahiwal), which may be due to the geographic proximity of the Sistan and Baluchestan province to Pakistan, the origin of indicine breeds (they may have had genetic or kinship relationships over a long historical period), or due to ascertainment bias in the SNP chips used. Full article

Drought is a natural phenomenon that has adverse effects on agriculture, the economy, and human well-being. The primary objective of this research was to comprehensively understand the drought conditions in Sistan and Balouchestan Province from 2002 to 2017 from two perspectives: vegetation cover and hydrology. To achieve this goal, the study utilized MODIS satellite data in the first part to monitor vegetation cover as an indicator of agricultural drought. In the second part, GRACE satellite data were employed to analyze changes in groundwater resources as an indicator of hydrological drought. To assess vegetation drought, four indices were used: Vegetation Health Index (VHI), Vegetation Drought Index (VDI), Visible Infrared Drought Index (VSDI), and Temperature Vegetation Drought Index (TVDI). To validate vegetation drought indices, they were compared with Global Land Data Assimilation System (GLDAS) precipitation data. The vegetation indices showed a strong, statistically significant correlation with GLDAS precipitation data in most regions of the province. Among all indices, the VHI showed the highest correlation with precipitation (moderate (0.3–0.7) in 51.7% and strong (≥0.7) in 45.82% of lands). The output of vegetation indices revealed that the study province has experienced widespread drought in recent years. The results showed that the southern and central regions of the province have faced more severe drought classes. In the second part of this research, hydrological drought monitoring was conducted in fifty third-order sub-basins located within the study province using the Total Water Storage (TWS) deficit, Drought Severity, and Total Storage Deficit Index (TSDI Index). Annual average calculations of the TWS deficit over the period from April 2012 to 2016 indicated a substantial depletion of groundwater reserves in the province, amounting to a cumulative loss of 12.2 km³ Analysis results indicate that drought severity continuously increased in all study basins until the end of the study period. Studies have shown that all the studied basins are facing severe and prolonged water scarcity. Among the 50 studied basins, the Rahmatabad basin, located in the semi-arid northern regions of the province, has experienced the most severe drought. This basin has experienced five drought events, particularly one lasting 89 consecutive months and causing a reduction of more than 665.99 km³. of water in month 1, placing it in a critical condition. On the other hand, the Niskoofan Chabahar basin, located in the tropical southern part of the province near the Sea of Oman, has experienced the lowest reduction in water volume with 10 drought events and a decrease of approximately 111.214 km³. in month 1. However, even this basin has not been spared from prolonged droughts. Analysis of drought index graphs across different severity classes confirmed that all watersheds experienced drought conditions, particularly in the later years of this period. Data analysis revealed a severe water crisis in the province. Urgent and coordinated actions are needed to address this challenge. Transitioning to drought-resistant crops, enhancing irrigation efficiency, and securing water rights are essential steps towards a sustainable future. Full article

The scientific goal of this study was to investigate the effects of various parameters on cavitation-induced erosion, with the aim to enhance the understanding and assessment of cavitation resistance in hydraulic systems. Cavitation erosion poses significant challenges to the durability and efficiency of hydraulic components, such as those found in hydropower plants and pumping stations. Prompted by the need to improve the reliability of cavitation testing and material assessment, this research conducted a comprehensive sensitivity analysis of a cavitation jet apparatus (CJA). This study employed an experimental platform that consisted of a vertical cylindrical test tank, a submerged nozzle, and an aluminum sample. By examining a range of orifice diameters, this research identified that smaller diameters led to increased erosion intensity, with the most pronounced effects observed at a diameter of 2 mm. Furthermore, various standoff distances (SoDs) were tested, which revealed that shorter distances resulted in greater erosion, with the highest impact noted at an SoD of 5 cm. This study also evaluated different nozzle geometries, where it was found that a 132° conical sharped edges nozzle, combined with an orifice diameter of 2 mm and an SoD of 5 cm, produced the most severe erosion. Conversely, chamfered edges nozzles and a commercial nozzle (MEG2510) with an SoD of 10 cm or greater showed reduced erosion. These results highlight that by standardizing the testing duration to 1200 s, the CJA could reliably assess the cavitation resistance of materials. This study established a clear relationship between increased pressure and higher impact forces, which led to more severe erosion. The findings underscore the effectiveness of the CJA in evaluating material resistance under various cavitation conditions, thus addressing a critical need for reliable cavitation testing tools. Full article

Dust storms are one of the important natural hazards that affect the lives of inhabitants all around the world, especially in North Africa and the Middle East. In this study, wind speed, wind direction, and air temperature patterns are investigated in one of the dustiest cities in Sistan Basin, Zahedan City, located in southeast Iran, over a 17-year period (2004–2020) using a WRF model and ground observation data. The city is located near a dust source and is mostly affected by local dust storms. The World Meteorology Organization (WMO) dust-related codes show that the city was affected by local dust, with 52 percent of the total dust events occurring during the period (2004–2021). The city’s weather station reported that 17.5% and 43% were the minimum and maximum dusty days, respectively, during 2004–2021. The summer and July were considered the dustiest season and month in the city. Since air temperature, wind speed, and wind direction are important factors in dust rising and propagation, these meteorological factors were simulated using the Weather Research and Forecasting (WRF) model for the Zahedan weather station. The WRF model’s output was found to be highly correlated with the station data; however, the WRF simulation mostly overestimated when compared with station data during the study period (2004–2020). The model had a reasonable performance in wind class frequency distribution at the station, demonstrating that 42.6% of the wind was between 0.5 and 2, which is in good agreement with the station data (42% in the range of 0.5–2). So, the WRF model effectively simulated the wind class frequency distribution and the wind direction at Zahedan station, despite overestimating the wind speed as well as minimum, maximum, and average air temperatures during the 17-year period. Full article

Water is an irreplaceable commodity with a high economic value. Today, water scarcity is the biggest challenge in the world, and the crises arising from lack of freshwater resources are serious threats to sustainable environmental development and human health and welfare. As the problems grow in complexity and dimensions, it becomes less possible to solve them with conventional optimization methods or explicit computational methods in a proper amount of time and with the currently limited computation memory, making it very difficult to achieve an optimal absolute solution. In this regard, metaheuristic algorithms that are generally inspired by nature are used in complex optimization problems. The Pishin Dam is an important dam in the eastern basin of Iran in the south of Sistan and Baluchestan province. This region faces severe water stress due to very low precipitation and very high evaporation on the one hand and the growing increase in urban, agricultural, and industrial demand on the other hand. The water development plans executed by the Ministry of Energy in the studied region influence water supply and demand profoundly. This research investigated the optimal allocation of water resources of this dam under management scenarios using the metaheuristic technique of the ant colony optimization algorithm (ACO). The results showed that the best value of the objective function was 82.3658 million m³. When applying the scenario of developing the cultivation area, the best value was obtained at 67.1258, which was significantly different from the base state. The results show that the ACO algorithm is suitable for the water resources of the Pishin Dam and can be used in planning and policymaking. Full article

Urbanization without planning causes concerns about biodiversity loss, congestion, housing, and ecosystem sustainability in developing countries. Therefore, resilience and regeneration following urbanization are critical to city planning and sustainable development. Integrating multi-criteria decision-making methods (MCDM) with geographic information systems (GIS) can be a promising method for analyzing city resilience and regeneration. This study aims to use two MCDMs, the Analytic Network Process (ANP) and the Best–Worst Method (BWM), to evaluate the resilience of metropolitan neighborhoods in Tehran. Fourteen criteria were selected to represent the city’s resilience, and the weights of two models were evaluated for their spatial patterns using GIS. The results showed that the building age was the most important criterion in both methods, while the per capita green space was the least important criterion. The weights of the most important criterion, the building age, for the ANP and BWM, were 19.56 and 18.98, respectively, while the weights of the least important criterion, the per capita green space, were 2.197 and 1.655, respectively. Therefore, the MCDM with GIS provides an approach for assessing city resilience and regeneration priority. Full article

Carbonate reservoirs, influenced by depositional and diagenetic processes and characterized by features like faults and vugs that impact storage capacity, require more than traditional Borehole Imaging logs ($BHIs$) for accurate porosity data. These data are essential for geological assessments, production forecasting, and reservoir simulations. This work aims to address this limitation by developing methods to measure and monitor the sustainability of carbonate reservoirs and exploring the application of sustainability principles to their management. The study integrates $BHIs$ and conventional logs from two wells to classify porosity-based facies within the Barra Velha Formation ($BVF$) in the Santos Basin. The methodology involves four steps: (i) analyzing conventional logs; (ii) segmenting BHI logs; (iii) integrating conventional and segmented BHI logs using Self-Organizing Maps ($SOM$); and (iv) interpreting the resulting classes. Matrix porosity values and non-matrix pore sizes categorize the porosity into four facies: (A to D). The results of this research indicate the following: Facies A has high non-matrix porosity with 14,560 small megapores, 5419 large megapores, and 271 gigapores (71.9%, 26.76%, and 1.34% of the 20,250 pores, respectively). Facies B shows moderate non-matrix porosity with 8,669 small megapores, 2642 large megapores, and 33 gigapores (76.42%, 23.29%, and 0.29% of the 11,344 pores, respectively) and medium matrix porosity. Facies C exhibits low non-matrix porosity with 7749 small megapores, 2132 large megapores, and 20 gigapores (78.27%, 21.53%, and 0.20% of the 9901 pores, respectively) and medium matrix porosity. Facies D has low non-matrix porosity with 9355 small megapores, 2346 large megapores, and 19 gigapores (79.82%, 20.02%, and 0.16% of the 11,720 pores, respectively) and low matrix porosity. The results of this research reveal the effectiveness of a semiautomatic methodology that combines $BHI$ and conventional well logs to distinguish between matrix and non-matrix-related pore spaces, thus enabling a preliminary classification of reservoir facies based on porosity. This study advances our understanding of carbonate reservoir sustainability and heterogeneity, thus offering valuable insights for robust, sustainable reservoir characterization and management in the context of global environmental and geological changes. The novelty of this work lies in integrating data from two sources to classify porosity across the presalt reservoir interval, thus serving as a proxy for preliminary lithofacies identification without core data. Full article

Desertification in semi-arid environments poses a significant risk to the archaeology within arid and semi-arid regions. Due to multiple political and physical barriers, accessing desertification-prone areas is complex, complicating pathways towards generating a hands-on understanding of the time–depth and distribution of archaeology throughout these regions. This research developed a remote sensing methodology to determine the areas of Sistan experiencing the highest levels of desertification and the threat of that desertification to known and potential archaeology. As desertification processes are occurring rapidly, this work’s methodology is straightforward and efficient. In a region of vast archaeological value, desertification threatens to prevent archaeologists from potential insight and discovery. This work showcases the opportunity for remote sensing to work as a tool for accessing archaeology in physically inaccessible desertification-prone regions. Full article

Surveys on the optimum seismic design of structures reveal that many investigations focus on minimizing initial costs while satisfying performance constraints. Although reducing initial costs while complying with earthquake design codes significantly ensures occupant safety, it may still cause considerable economic losses and fatalities. Therefore, calculating potential earthquake damages over the structure’s lifetime is essential from an optimal Life-Cycle Cost (LCC) design perspective. LCC analysis evaluates economic feasibility, including construction, operation, occupancy, maintenance, and end-of-life costs. The population-based, meta-heuristic Ideal Gas Molecular Movement (IGMM) algorithm has proven effective in solving highly nonlinear mono- and multi-objective engineering problems. This paper investigates the LCC-based mono- and multi-objective optimum design of a 3D four-story concrete building structure using the Endurance Time (ET) method, which is employed for its efficiency in estimating structural responses under varying seismic hazard levels. The novelty of this work lies in integrating the ET method with the IGMM algorithm to comprehensively address both economic and performance criteria in seismic design. The results indicate that the proposed technique significantly reduces minor injury costs, rental costs, and income costs by 22%, 16%, and 16%, respectively, achieving a total reduction of 10% in all structural Life-Cycle Costs, which is considered significant. Full article