تحقیقات کاربردی علوم جغرافیایی

Monitoring and analysis of drought behavior using remote sensing data in Kermanshah province

Mohammad Hossein Nasserzadeh

Drought is one of the natural disasters whose long-term effects affect the economy and society. This phenomenon is considered a challenge in arid and semi-arid regions, including Iran. Nowadays, the use of remote sensing methods can help us in understanding the drought behavior of vegetation. In order to monitor and analyze the behavior of drought in Kermanshah province, the data of Sanjande Weathers products (VIIRS) and AVHRR data indexed by NOAA STAR were used. In this study, the Vegetation Health Index was used in the period of 1982-2021 in a seven-day format with a spatial resolution of 4 x 4 km. After extracting the data in the Kermanshah area, the vegetation drought trend was investigated on 65,387 cells using the Mann-Kendall test. The results showed that in the winter season, the trend of vegetation cover in the western areas of the province was decreasing and significant at the level of 0.05. While in the northern, central and eastern regions of the province, the trend is increasing and significant. In the spring and summer seasons, especially the months of June, July, August and September, which correspond to the dry months of the year, the size of the areas with a significant decreasing trend of vegetation cover has increased, while in the autumn season, with the beginning of the water year, the size of the areas with a decreasing trend has decreased.

Analysis of carbon footprint effects on the sustainability of Tehran metropolis

Farzaneh Sasanpour

The metropolis of Tehran has developed on the basis of modern urbanization and in the last decade, it has witnessed transformations such as the reduction of the biological capacity of the region, uncontrollable socio-economic effects, exorbitant costs in the direction of health protection and also the treatment of the diseases that have arisen. is the aim of the research being to analyze the effects of carbon footprint on the sustainability of Tehran metropolis. The current research is applied and descriptive-analytical in terms of research method. Library and field method (questionnaire) was used to collect information. The statistical population of this study is Tehran metropolis with a population of 8,693,706 people, and Cochran's formula was used to select the sample, and 384 people were determined and completed by simple random sampling. Information processing was done with SPSS software, and the results of the questionnaire were analyzed with structural equation method and PLS software. The findings of the research showed that the situation of the carbon index in Tehran is in an unfavorable situation. The highest factor loading or standardized regression coefficient for the low-carbon planning index and the lowest for the low-carbon society index is 0.218. Also, it was found that low-carbon planning had the greatest impact on carbon reduction in Tehran metropolis. After that, the indicators of low-carbon urban development, low-carbon environment, low-carbon economy, low-carbon transportation, low-carbon construction and low-carbon society in the reduction of carbon in the city of Tehran respectively have There were different effects.

Analysis of Key Drivers of Trans-regional Threats to Iran with a Futures Studies Approach

parisa .ghorbanisepehr

Extra-regional threats refer to a set of military, security, political, and economic measures or pressures exerted by countries or coalitions from outside a specific geographical region against the interests and security of a country. These threats typically exploit geographical distance, modern warfare tools, comprehensive sanctions, and the establishment of influence in neighboring countries to undermine stability and limit the regional power of the target. This research has been conducted with the aim of identifying and analyzing the key drivers affecting trans-regional threats to Iran using a future studies approach, in order to analyze the systemic structure of these threats and outline the most probable scenario ahead. The method of this research is mixed (quantitative-qualitative). For this purpose, initial indicators were extracted through multi-stage interviews with a panel of 15 experts and then screened using the Delphi method. In the next stage, a cross-impact analysis questionnaire was administered to 15 specialists and experts, and the data were structurally analyzed using MICMAC software. The distribution of variables on the influence-dependence map indicates the instability of Iran's trans-regional threats system. Among the 49 variables examined across five dimensions—political, economic, socio-cultural, defense-security, and natural-environmental—three variables were identified as the most key drivers and as dual-risk/target variables: new regional coalitions in Iran's periphery involving global powers (P3), pressure on countries party to agreements with Iran to terminate cooperation (P7), and new trans-regional political coalitions against Iran's political positions (P1). Furthermore, the variable "keeping the minds of the country's decision-makers occupied with domestic issues" (P8) ranked first in terms of direct influence. The results of the research indicate that the future of trans-regional threats to Iran can be depicted in the form of the "Intelligent Siege" scenario. In this scenario, trans-regional powers, through regional and trans-regional coalition-building and severing Iran's contractual ties with the world, drive the country toward strategic passivity and reduced room for maneuver without a full-scale military war. The paradigm shift of threats from a purely military nature to political, cognitive, and intelligent threats is the most important characteristic of the future of these threats.

Dynamical and Synoptic Characteristics of Extreme Precipitation Events in Western Iran (Case Study: Kurdistan Province)

Mohammad Darand

Extreme precipitation events pose a significant and growing threat to society, often leading to floods, landslides, and widespread socio-economic damage. Daily precipitation data collected from 9 rain gauges during 1/1/1991 to 31/12/2023. To identify days associated with heavy precipitation, the 95th-percentile threshold was employed. Days on which the recorded precipitation exceeded the long-term mean of the 95th percentile at more than half stations were classified as heavy-precipitation days for Kurdistan Province. Based on this threshold and criterion, 210 days were selected. Two data arrays with an S-mode structure were constructed for sea-level pressure and 500-hPa geopotential height. Using Principle Component Analysis (PCA) analysis, components explaining more than one percent of the variance were retained as significant modes. For sea-level pressure, nine components were identified, and for the 500-hPa geopotential height, eight components were extracted. Together, these components explained over 92% of the variance in sea-level pressure and more than 95% of the variance in the 500-hPa geopotential height over the study domain. Cluster analysis (CA) performed on the score matrix of the 17 components was then used to identify the prevailing circulation patterns.

A Comparative Evaluation of Drought Indices Using CMIP6 Climate Model Simulations: A Case Study of Semnan Province, Iran

Mohammad baaghideh

In recent years, the world has experienced more frequent droughts, largely due to climate change. This study monitors and projects drought conditions in Semnan Province, Iran, using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). It also evaluates drought characteristics under future climate scenarios. Projections of temperature and precipitation from 12 CMIP6 climate models were downscaled using Quantile Mapping. To reduce uncertainty, a Bayesian Model Averaging (BMA) ensemble was created. These projections were then used to calculate 12-month SPI and SPEI values for both the baseline and near-future period (2031–2054).
Drought characteristics—such as duration, intensity, and magnitude—were analyzed using Run theory and compared across two periods. Ensemble model projections suggest that mean temperatures in the province will rise by approximately 1.1-1.2 °C relative to the baseline period under both scenarios. Furthermore, annual average precipitation is expected to increase by 3-8% at most stations in the province, except for Shahrud station. The SPI and SPEI indices exhibited a significant positive correlation, demonstrating relatively similar performance despite minor differences. Based on both indices, drought characteristics such as duration and intensity are projected to increase significantly during the latter years of the 2031–2054 horizon compared to the baseline period. The most notable increase was observed for the SPEI index under the SSP585 scenario, where drought duration rose from 6.6 months during the baseline period to 8.9 months under the SSP245 scenario and 16 months under the SSP585 scenario. For the SPI index, drought duration decreased from 6.3 months in the baseline period to 5.6 months under the SSP245 scenario, then increased to 7.8 months under the SSP585 scenario.

Spatiotemporal Analysis and Zoning of Lightning‑Associated Thunderstorms in Tehran Province During the Last Three Solar Cycles

Hassan Lashkari

Thunderstorms are considered compound atmospheric hazards, as they simultaneously involve several hazardous phenomena such as lightning, strong and gusty winds, intense convective rainfall, and torrential precipitation. Consequently, these storms are often associated with damage to urban infrastructure and environmental impacts. The objective of this study is to analyze the spatiotemporal distribution of thunderstorms across Tehran Province over a 33‑year period corresponding to the last three solar cycles. Owing to its distinctive topographic conditions and geographical location, Tehran Province is regarded as one of the regions prone to the occurrence of this phenomenon. The data used in this research include lightning reports recorded at nine synoptic stations in Tehran Province during the period 1986–2019. To improve the accuracy of thunderstorm system identification, only events that were simultaneously recorded at a minimum of two stations and during at least two six‑hour observation intervals were selected. The analyses were conducted at monthly, seasonal, and annual scales using statistical and spatiotemporal approaches within the framework of three 11‑year solar cycles. Zoning maps of thunderstorm occurrence frequency were also produced for solar cycle 24 using a larger number of stations with an appropriate spatial distribution. The results indicate that the highest frequency of thunderstorms occurs during the spring season, particularly in May. Despite the passage of most precipitation systems during autumn and winter, the lowest thunderstorm activity was observed in winter. Approximately 70% of the systems had a one‑day duration, and more than half of the events were reported only twice per day. Spatially, Imam Khomeini station and, at a regional scale, the southwestern part of the province in most seasons and the northeastern part during summer exhibited the highest frequencies. Considering the economic and infrastructural impacts as well as aviation‑related hazards, the development of thunderstorm warning systems in Tehran Province appears to be essential.

ATTRIBUTION OF CLIMATE CHANGE TO THE EXTREME SNOW FALLS OF MAZANDARAN PROVINCE (stochastic climate modeling using Lorenz-63)

zahra hejazizadeh

The aim of this study was to do attribution of climate change to the extreme snow fall of Mazandaran province in the northern part of Iran and southern shores of the Caspian Sea in the vicinity of Alborz mountains. The area is not prone to extreme snow fall or even snow fall then this phenomenon has had great damages to the infrastructures of the region. The study is performed on the time interval of 1987-2017in winter time (DJF). Corresponding calculation is done for two parallel worlds of counterfactual i.e. without external forcing and factual with external forcing in the context of stochastic climate modeling. This is done by the chaotic dynamical 3-D model Lorenz-63. Then the two worlds of study are defined on the basis of LM-63 and SLM-63 as deterministic and stochastic climate models. Fakher- Planck equation had the role of implementing time evolution of the PDF into the modal. The conditional probability and Bayesian framework is the preliminaries of the method of this study. The model is belonging to the space state models and Bayesian recursive estimation. These all is the basis of the EnKF as nonlinear filtering approach to the nonlinear dynamical model of this study. It is tried to bring down all the related situation associated with the issue on the basis of sound mathematical, epistemological and physical foundations. All the computations are done on the environment of GIS, Matlab, Mathematica and Maple. Then causal theory of pearl (2000) is used as the evidence of verification for the whole process. The final results showed that the extreme snow of Mazandaran province is attributable to the climate forcing defined for the study 0.8978 in its PN causation, 0.1942 in its PS causation and 0.4519 in its PNS causation.

Scale-Dependent Roughness and Multifractal Behavior of Topography in a Tectonically Active West Asian Domain

Mitra Saberi

Characterizing the scaling structure of topography is essential for linking observable land-surface morphology to the processes governing landscape evolution. Conventional geomorphometric approaches often describe terrain using self-affine models parameterized by a single roughness exponent, implicitly assuming statistical homogeneity across scales. Such formulations, however, may not adequately capture landscapes shaped by the coupled action of tectonic deformation, climatic forcing, and nonlinear erosional dynamics. In this study, we evaluate the scale dependence of surface roughness using high-resolution digital elevation data from the Iranian Plateau, a morphotectonically diverse region representative of actively evolving continental domains in West Asia. Fractal analysis based on box-counting yields a dimension of Df≈2.20, while spectral analysis of elevation fields provides a Hurst-type roughness exponent of α≈0.48. The lack of agreement with the canonical self-affine relation Df=3−α indicates that the terrain cannot be characterized by a single scaling descriptor. To investigate this departure, we compute higher-order statistical measures of elevation variability, including generalized structure functions, multiscale height–height correlations, and scale-dependent curvature metrics. These analyses reveal that the scaling exponents vary systematically with statistical moment, demonstrating clear multiscaling and supporting a multifractal description of the surface. The results suggest that topographic organization in tectonically active settings reflects heterogeneous process interactions operating over a hierarchy of spatial scales, rather than uniform rough-surface behavior. This work underscores the limitations of single-exponent geomorphic parameterizations and highlights the value of multifractal diagnostics for quantitative terrain analysis, comparative morphotectonic studies, and improved representation of landscape complexity in Earth-surface models.