River morphology holds significant importance in the fields of geomorphology and river management and engineering. The marginal sections of rivers have consistently undergone changes in their riverbeds due to various social and economic factors. The Dare Ourt River, located in the Ardabil province, represents a permanent river that has experienced frequent floods and alterations in its channel morphology in recent periods. In this study, the Dare Ourt river was thoroughly analyzed using the Rosegen model at levels one and two. To conduct this study effectively, detaied data such as 1:2000 river topographic maps, hydrometric data, and boundary conditions from the Ardabil Regional Water Authority were collected and utilized. Furthermore, the HEC-RAS hydrodynamic model was employed to extract the primary indices of the Rosegen model with greater accuracy. The outcomes revealed that the majority of the river sections exhibit a C6c type, characterized by an alluvial substrate. Additionally, other dominant types observed within the four examined ranges include B6c, E6b, F6, and D. Field visits also confirmed a transition in the river type from C to F within range 4, which presents challenges for the reconstruction and restoration of the river in type F. As a recommendation, it is advised to implement restrictions to prevent the river from transitioning into type F.

Ancient cities have always possessed inherent distinctions from contemporary cities, which are evident in their physical structures and overall layouts, allowing them to be easily differentiated from their modern counterparts. These distinctions, influenced by economic, political, cultural, and social conditions, have resulted in varying degrees of change in the urban structure and have given rise to two types of urban growth. Organic growth is characterized by a continuous and coherent expansion that prioritizes form in relation to function, in stark contrast to the fragmented and discrete nature of global cities in the modern era. This study seeks to address whether it is feasible to apply the characteristics and developmental patterns of ancient cities in today's world by examining the evolution of urban form throughout history up to the present day. Alternatively, can a favorable outcome be achieved by integrating certain characteristics of ancient cities into contemporary urban environments? Based on this objective, the study explores the evolution of urban form across three historical periods - pre-Islamic, post-Islamic, and the modern era - with a particular focus on the establishment of governmental centers in the central desert of Iran. The comparative method of induction is employed to discuss the subject matter in line with the research assumptions. The findings indicate that the first and second hypotheses have yielded more significant results in a greater number of unsuccessful experiments. Conversely, the third hypothesis has been more successful in a wider range of experiments with diverse outcomes. Moreover, considering the success rate of 0.100 and the absence of unsuccessful experiences for the Kerman experiment, it can be argued that this hypothesis is relatively superior and preferable for assessing the success rate of related projects.

By employing urban growth and development modeling, it is feasible to delineate a developmental trajectory that aligns with the specific circumstances of a city, considering environmental factors, natural elements, and population dynamics. The aim of this research is to propose an urban development model for Shushtar, which can serve as a valuable tool for analyzing the intricate processes of urban transformations. To accomplish this objective, two datasets were utilized: urban land use maps (including educational spaces, healthcare facilities, residential areas, etc.) and Landsat satellite imagery for key land uses such as rivers, barren lands, and forests, spanning three time periods: 1991, 2004, and 2014. These datasets were processed using GIS and MATLAB software. Existing urban land use maps were digitized and subsequently updated using Landsat satellite imagery. Subsequently, influential parameters in urban development were introduced as inputs to the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm. After training the model for the years 1991 and 2004, the predicted results of urban development using the algorithm were compared with the actual situation in 2014, demonstrating a high accuracy of 93.7%. The land use change map, resulting from the change detection process, can be generated based on multi-temporal remote sensing images and their integration with urban land use maps, enabling an analysis of the associated consequences. The use of intelligent algorithms in this research has facilitated modeling with a high level of accuracy. The obtained results are deemed acceptable, and this development has also been predicted for the upcoming years.

Urbanization and the increase in urban populations, resulting from both natural population growth and rural-to-urban migration, have led to the concentration of significant material and spiritual human capital within urban settlements. Concurrently, various natural and human-induced crises pose threats to these capitals. Urban management has initiated a range of programs to address these crises, with a contemporary focus on enhancing the resilience of cities. The concept of resilience can be examined across various dimensions, including physical, economic, social, and environmental aspects.
The present study adopts a descriptive-analytical approach with the objective of assessing the physical resilience of metropolitan areas in Tabriz and determining their status relative to one another. To achieve this goal, multi-criteria decision-making methods (MADM) and the Analytic Hierarchy Process (AHP) have been employed. Additionally, three models—Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VIKOR, and Complex Proportional Assessment (COPRAS)—have been utilized to rank the regions in terms of physical resilience. Ultimately, the Copeland model was applied to integrate the results from the aforementioned models. The findings indicate that regions 2, 8, and 9 collectively exhibit the highest levels of physical resilience, followed by regions 1, 10, 3, 7, 5, 4, and, lastly, region 6, respectively.

This study investigates the impact of the OLR MJO Index (OMI) and the Real-time Multivariate MJO (RMM) of the Madden-Julian Oscillation on the frequency of dust storms in the stations of Abadan, Ahvaz, Bostan, Bandar Mahshahr, Dezful, Ramhormoz, and Masjed Soleiman, located in Khuzestan province, during the period from April to September 1987-2021. Pearson correlation coefficients were computed to assess the relationship between dust data and the indices, and the findings were depicted through zoning maps. Subsequently, the frequency percentage of each index for both positive and negative phases was quantified. The results indicate a direct and significant correlation between the positive and negative phases of the indices and dust occurrences (with the exception of Dezful station), particularly during the positive phase of the OMI and the negative phase of the RMM. The highest correlation coefficients, ranging from 0.77 to 0.72, were observed for Bandar Mahshahr and Dezful stationsduring the positive phase of the RMM index. Analysis of the relationship between the Madden-Julian Oscillation and dust storms revealed that between 51% and 59% of dust storms in Khuzestan province occurred in the negative phase of the OMI index, while 40% to 49% occurred in the positive phase. In the case of the RMM index, 56% to 63% of dust storms were associated with its negative phase, in contrast to 37% to 50% linked to its positive phase. Notably, the negative phase of the RMM index exhibited a higher percentage of dust storms compared to the negative phase of the OMI index. According to the results of the Monte Carlo test, the displacement of the positive and negative phases of the RMM index significantly contributes to the occurrence of dust storms at most stations in Khuzestan province. Furthermore, tracking the pathways of dust entering Khuzestan province using the HYSPLIT model indicates the movement of particles originating from Iraq, Arabia, and the eastern regions of Syria toward Khuzestan province..

Drought is a natural hazard that annually causes significant economic, social, environmental, and life-threatening damage in vast areas of the Earth. The damages caused by this phenomenon are intangible but very extensive and costly.  In many circomstancs, modern remote sensing techniques can be a useful tool in monitoring drought due to high temporal accuracy, wide spectral coverage, ease of access, no need for atmospheric correction and ground referencing. In recent years, the province of Hamedan has faced many problems due to frequent droughts. Therefore, the present study focused on investigating and monitoring drought in Hamedan province using the Temperature Condition index and its impact on the vegetation cover of the province using Advanced Very High Resolution Radiometer (AVHRR) and National Oceanic and Atmospheric Administration (NOAA) remote sensing data. First, the relevant data was extracted from the Nova star database, and finally, the spatiotemporal behavior of the vegetation cover drought index was examined on 1528 pixels in Hamedan province. The spatial resolution of the data used in this study is 4 kilometers. First, the relevant data were extracted from the Navstar database and ultimately, the spatiotemporal behavior of the drought index and vegetation cover was examined. The results indicate that drought has significantly increased the vegetation cover of Hamedan province based on remote sensing data. Kendall's coefficients indicate the presence of decreasing trends in vegetation cover at a 95 Percent confidence level. Only in May, June, and December has there been a slight decrease in vegetation cover within the extent of drought in the province. The spatial behavior analysis of the drought index on vegetation cover showed that February, March, as well as April have experienced more severe droughts within Hamedan province.

Urban development strategy represents a contemporary approach in urban planning and management, offering a framework for achieving sustainable urban development through poverty reduction, citizen participation, and increased investment. Like many cities in Iran, Ardabil faces numerous challenges, including inadequate governance, deteriorating infrastructure, substandard housing, weak public utilities, and insufficient social and health services. These issues underscore the necessity of strategic planning to address urban development effectively. This study aims to evaluate the indicators of urban development strategy in Ardabil. Employing a descriptive-analytical methodology, the research is grounded in field investigations. A sample size of 230 participants was determined using Sample Power software. Data analysis was conducted using one-sample T-tests and structural equation modeling (SEM) in AMOS Graphics software. The results of the one-sample T-test revealed that the status of urban development strategy indicators—livability, good governance, bankability, and competitiveness—in Ardabil is suboptimal, with mean scores of 2.21, 2.6, 2.62, and 2.15, respectively. Second-order factor analysis indicated that among the dimensions of urban development strategy, competitiveness, with a factor weight of 0.93, exerts the most significant influence, while bankability, with a factor weight of 0.62, has the least impact. Furthermore, the findings demonstrated that an improvement in the good urban governance index leads to a 0.55 increase in bankability, a 0.76 increase in livability, and a 0.86 increase in competitiveness. These results highlight the interconnectedness of governance quality with other dimensions of urban development, emphasizing the need for integrated strategies to enhance Ardabil's urban sustainability.