دانشگاه خوارزمی Journal of Spatial Analysis Environmental hazarts 2423-7892 2588-5146 12 4 2025 12 1 Detection and analysis of land cover forcing evapotranspiration in Karun basin using MODIS sensor products 0 0 FA Mohammad Hossein Nasserzadeh Kharazmi University nasserzadeh@khu.ac.ir Y Parviz Ziaian Firouzabadi Kharazmi University zeaiean@khu.ac.ir N zahra Hejazizadeh Kharazmi University hejazizadeh@khu.ac.ir N shirin Moradjani Kharazmi University shirin@khu.ac.ir N This study investigates the spatio-temporal dynamics of evapotranspiration (ET) and its modulation by biophysical variables and land use/land cover (LULC) changes in the Karun River Basin, southwestern Iran, from 2000 to 2023. The basin, spanning 67,257 km² and characterized by diverse topography, experiences significant annual water loss (72% of 413 billion m³ national precipitation) due to ET, leading to salt and sediment accumulation. Data from MODIS products (MCD12Q1, MOD13A1, MCD43A3, MOD11A2, MOD16A3, CHIRPS) provided land cover, NDVI, albedo, LST, precipitation, and ET at 500-meter resolution, supplemented by Landsat imagery (30-meter resolution) for validation. Multiple regression and Geographically Weighted Regression (GWR) analyses revealed a 39.5% ET increase (31.48 to 43.92 mm/year), a 32.78% NDVI rise (0.18 to 0.239), and a 16.35% LST decrease (33.52°C to 28.05°C), correlated with a 6.90% agricultural decline (6,939,225 to 6,460,335 ha), a 6.94% rangeland increase (3,840,375 to 4,106,780 ha), and a 42.76% forest expansion (156,000 to 222,700 ha). GWR (AdjR² > 0.97, peak 0.9887 in 2010) identified spatial non-stationarity, with overprediction in mountainous northeast regions and underprediction in agricultural southwest plains, reflecting LULC influences. Landsat-derived false color composites and classifications (overall accuracy 85–90%, Kappa 0.85–0.90) validated a 2,477 km² forest loss to high-ET rangelands/agriculture, driving warm-season ET elevation. Results emphasize the need for integrated hydrological models incorporating irrigation data and high-resolution analyses to enhance sustainable water management in this water-stressed region. Detection, Land Cover, Evapotranspiration, Karun Basin, MODIS Sensor http://jsaeh.khu.ac.ir/article-1-3493-en.html http://jsaeh.khu.ac.ir/article-1-3493-en.docx

دانشگاه خوارزمی Journal of Spatial Analysis Environmental hazarts 2423-7892 2588-5146 12 4 2025 12 1 Risk Modeling of Land Subsidence Using the Random Forest Algorithm (Case Study: Eshtehard Plain) 0 0 FA rana norouzi ra.norouzi@yahoo.com Y Sayyd Morovat Eftekhari Eftekhari@khu.ac.ir N Ali Ahmadabadi ahmadabadi@khu.ac.ir N Objective: Over the past two decades, land subsidence has emerged as a significant geomorphological hazard and one of the most critical environmental crises in Iran, causing irreversible damage to many plains each year. Among its primary current causes is the excessive and unregulated extraction of groundwater. The Eshtehard Plain, recognized as one of the industrial and agricultural hubs of Alborz province, is no exception. Due to severe groundwater depletion, it has been officially declared a critical zone by the Ministry of Energy. The objective of this study is to model the risk of land subsidence in this plain using the Random Forest algorithm and to analyze the contributing factors influencing its occurrence Methods: In this study, twelve independent spatial layers were utilized, including: digital elevation model (DEM), distance to rivers, distance to qanats, distance to wells, distance to faults, groundwater depth, drainage density, soil type, lithology, land use, topographic wetness index (TWI), and solar radiation. The dependent layer consisted of subsidence zones. The Random Forest model was implemented in the R software environment. Two key importance measures—Mean Decrease Accuracy and Mean Decrease Gini—were employed to rank, assess the significance of, and assign weights to the contributing factors of land subsidence. Finally, model performance was evaluated using three complementary metrics: Accuracy, Kappa, and AUCResults: The results demonstrated that the Random Forest model achieved high accuracy in classifying land subsidence risk. Model evaluation showed strong performance with an overall accuracy of 0.963, a Kappa coefficient of 0.611, and an AUC value of 0.955, indicating that the model is highly effective for spatial risk zoning of land subsidence. The most influential variables in subsidence occurrence were identified as groundwater depth, distance to wells, geology, and land use. Furthermore, more than 65% of the study area was categorized as high-risk and very high-risk, reflecting the critical condition of the Eshtehard Plain. Notably, the share of urban land use has shown a steady increase from 2011 to 2023, with a significant spike in 2023, where increased population concentration has placed additional pressure on groundwater resources, leading to an intensification of subsidence in affected areas Conclusions: The Random Forest algorithm successfully modeled the spatial distribution of land subsidence risk with high accuracy. This method can serve as an effective tool for informed decision-making in groundwater resource management, sustainable development planning, and hazard mitigation in similar regions.   Eshtehard Plain, Random Forest, land subsidence, modeling http://jsaeh.khu.ac.ir/article-1-3505-en.html http://jsaeh.khu.ac.ir/article-1-3505-en.docx

دانشگاه خوارزمی Journal of Spatial Analysis Environmental hazarts 2423-7892 2588-5146 12 4 2025 12 1 Analysis of Synoptic Patterns and Modeling of Dust Transport and Dispersion Pathways in Kerman Province 0 0 FA Saeedeh zaboli saeedeh.zaboli@tabrizu.ac.ir N Saeed Jahanbakhsh Asl s_jahan@tabrizu.ac.ir Y Ali Mohammad Khorshiddoust khorshid@tabrizu.ac.ir N Mahmood Khosravi Khosravi@Gep.usb.ac.ir N Dust storms rank among the most significant natural hazards in the world’s arid and semi-arid regions, inflicting irreparable damage across multiple sectors each year. Given the rising frequency of dust storms in Kerman Province and other desert and arid areas of Iran, it is imperative to undertake a study aimed at identifying the synoptic patterns that precipitate dust events and at determining their source regions as well as their transport and dispersion pathways. In this research, the conditions and origins of dust storm formation over the 2000–2023 period were examined using synoptic and remote-sensing methods. The HYSPLIT model was applied to track airflow trajectories, and factor analysis together with cluster analysis were used to identify the synoptic patterns responsible for dust generation. Finally, the principal source regions of dust were delineated. The results revealed that 63% of the province’s dust storms originate from domestic sources, whereas 37% originate from other areas. Three main atmospheric patterns were identified as drivers of dust activity in Kerman Province: 1. The co-advection of simultaneous low-pressure and high-pressure systems; 2. A lower-tropospheric cutoff low pressure in conjunction with the Siberian high; 3. A pressure-gradient regime featuring a core of elevated wind speeds. Modeling of transport and dispersion pathways indicated that 60% of externally sourced dust is advected from the Arabian Peninsula, while 55% of dust emitted disperses southward, impacting the Makran coast and the Sea of Oman. Analysis of source regions further showed that the desert areas of Saudi Arabia, Iraq, Syria, and Jordan, as well as those of North Africa, together with internal sources such as the dried Jazmourian wetland, the Lut Desert, the Hamun region, and the Tabas Desert, contribute most substantially to the dust events observed in Kerman Province.   Cluster Analysis, Factor Analysis, Kerman, Dust, Synoptic Analysis http://jsaeh.khu.ac.ir/article-1-3501-en.html http://jsaeh.khu.ac.ir/article-1-3501-en.doc

دانشگاه خوارزمی Journal of Spatial Analysis Environmental hazarts 2423-7892 2588-5146 12 4 2025 12 1 Analysis of the june(2024) flood in Ardabil Province with an emphasis on synoptic patterns 0 0 FA nafiseh rahimi zanjan uni rahimi.nafiseh2@gmail.com Y abdo faraj zanjan uni abfaraji@znu.ac.ir N Objective: in recent decades, population growth, urbanization development, and change in land use have led flooding as one of the most destructive natural disasters in the world. Therefore, our goal is to identify flood areas and the synoptic patterns that lead to it, which are among the most important issues in preventing and reducing the effects of flooding and dealing with it. Methods: In this study, in order to prepare a map of flooded areas, the extent of the floodwater that occurred in June (2024) in Ardabil province, were processed SAR radar images before and after the flood. Then, to identify synoptic patterns, daily maps of geopotential height at 500 hectopascals, sea level pressure at 1000 hectopascals, omega pressure at 500 hectopascals, and relative humidity at 700 hectopascals with a spatial resolution of 2.5 degrees in 2.5 degrees latitude were received and analyzed from the National Center for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) of the United States. Results: The flood area study indicated that in the studied province, Bilehsavar city with an area of 593 hectares, Parsabad city with 505 hectares, Meshkin-shahr with 245 hectares, and Germi city with 192 hectares were flooded due to the waterlog. The analysis of the flood zones also showed that the largest volume of flood entering Ardabil Province during the studied period was related to the northern cities of the province, where the provision of all moisture conditions and instability at the full depth of the troposphere layer led to the occurrence of heavy flood-causing rainfall in these areas. Conclusions: The results of this study indicate that the use of radar data, due to its outstanding capabilities, is a useful tool in detecting and continuously monitoring of floods. Therefore, by detecting flood-prone areas and synoptic conditions that produce floods, executive managers can make the best decisions to deal with possible future floods.   Ardabil Province, Flood, June 2024, Radar Images, Synoptic Patterns, http://jsaeh.khu.ac.ir/article-1-3443-en.html http://jsaeh.khu.ac.ir/article-1-3443-en.doc

دانشگاه خوارزمی Journal of Spatial Analysis Environmental hazarts 2423-7892 2588-5146 12 4 2025 12 1 Survey the surface temperature of the earth in relation to land use using satellite images and remote sensing (case study of Bukan city). 0 0 FA Mahmoud Hooshyar Payam Noor university hooshyar@pnu.ac.ir Y Land use is one of the most important aspects of studying natural resources management and reviewing environmental changes, and studying it is also very important in understanding the microclimate of urban areas. Therefore, according to the importance of the topic in this research, the spatial pattern of land use changes and surface temperature in Bukan city in the statistical period of 1990-2020 using Landsat satellite images and sensors (OLI-TIRS, ETM+, TM) and the separate window algorithm. was evaluated. The results showed that the land use of the area has changed a lot during the period under review, so that the residential use has increased and the agricultural use has decreased. The results of the survey of the earth's surface temperature also showed that in 1990, the highest temperature was related to pasture areas and barren lands with a temperature between 32 and 40 degrees Celsius and the lowest temperature was related to areas with dense vegetation with a temperature between 15 and 20 degrees. It is Celsius. The temperature in residential and urban areas varies between 28 and 31 degrees Celsius. In 2020, the average temperature of pasture use was 35 degrees Celsius, residential use was 30 degrees Celsius, and garden and agricultural land was 14 and 24 degrees Celsius, which, apart from pasture use, which did not change significantly, other studied uses increased. They show a temperature of 2 to 4 degrees Celsius compared to 1990. The examination of the temperature in relation to the land use changes showed that there is a high correlation between the land cover and the surface temperature of the land, so that in some of the sampled places, it showed that the change in the use of gardens Residential use or pasture has caused an increase of 15 to 20 degrees Celsius in the temperature of the earth's surface in these areas. Based on the results of land use and overall vegetation, it has an indirect and strong relationship with the surface temperature of the earth, and with the increase in the area of residential and barren lands and the decrease of vegetation and agricultural lands, the surface temperature of the earth will increase. Earth surface temperature, land use, remote sensing, Bukan city. http://jsaeh.khu.ac.ir/article-1-3371-en.html http://jsaeh.khu.ac.ir/article-1-3371-en.docx

دانشگاه خوارزمی Journal of Spatial Analysis Environmental hazarts 2423-7892 2588-5146 12 4 2025 12 1 Assessing Seismic Resilience of Urban Water Distribution Networks: A Case Study of Sanandaj, Iran 0 0 FA Shaida sharifi UniveUniversity of Kurdistan shaidashrifi1987@gmail.com N Abdullah Nosrati unversity of Kurdistan ab.nosraty@gmail.com N Hadi Nayyeri University of Kurdistan h.nayeri@uok.ac.ir Y                     This study employs the Analytic Hierarchy Process (AHP) to assess the vulnerability and resilience of the urban water distribution network in the Feyzabad and Baharan districts of Sanandaj against the parameter of Peak Ground Velocity (PGV). The main objective is to identify the key factors influencing network vulnerability and to propose strategies for enhancing the resilience of this critical infrastructure. PGV values were derived based on data from 40 faults longer than 10 km within a 70 km radius of the city, using empirical attenuation relationships. Geological, geomorphological, soil type, and pipe diameter and material data were collected from reliable local sources.In the AHP model, the main criteria including PGV, geology, soil, pipe material, and pipe diameter were integrated with weights of 0.460, 0.112, 0.243, and 0.182, respectively, and vulnerability maps of the network were generated. Results showed that PGV values across the city range between 35 and 39 cm/s. In Feyzabad, lower PGV values combined with thick steel pipes and Quaternary alluvial soils resulted in 81% of the network falling into the low-vulnerability class and only 2.1% into the high-vulnerability class. Conversely, in Baharan, higher PGV values (39 cm/s), combined with small-diameter asbestos pipes and shale bedrock, placed 34% of the network in the very high-vulnerability class.                                 seismic resilience, peak ground velocity ((PGV)), water distribution network, analytical hierarchy process geographi information systems http://jsaeh.khu.ac.ir/article-1-3495-en.html http://jsaeh.khu.ac.ir/article-1-3495-en.docx

دانشگاه خوارزمی Journal of Spatial Analysis Environmental hazarts 2423-7892 2588-5146 12 4 2025 12 1 Ecological Catastrophe in the Sultanieh Grassland: An Integrated Assessment of Anthropogenic and Climatic Drivers Using Remote Sensing and Catastrophe Theory 0 0 FA jafarihas@yahoo.com Y peyam Afshar University of Zanjan payam.afshr@gmail.com N Eisa Piri University of Zanjan isapiri@znu.ac.ir N Objective: “This study aims to investigate the drivers of ecological rupture in the Sultanieh Grassland, one of Iran’s most valuable natural ecosystems, which has experienced severe degradation over the past two decades. The research seeks to identify and prioritize the relative contributions of climatic, hydrological, and anthropogenic factors in triggering systemic instability and to assess whether the ecosystem has crossed a critical threshold toward irreversible collapse. Methods: An integrated analytical framework was employed, combining multi-source datasets from 2000 to 2021. Remote sensing indicators—including the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and Soil Moisture (SM)—were derived from MODIS and Landsat imagery. Hydroclimatic time series (temperature, precipitation, potential evapotranspiration [PET], and groundwater levels) were analyzed alongside demographic statistics and land use/land cover (LULC) changes. A multi-criteria weighting approach, grounded in catastrophe theory, was applied to objectively quantify the relative influence of key drivers while minimizing subjective bias in decision-making. Results: The analysis reveals a 15% decline in effective precipitation, a 1°C increase in mean annual temperature, and a groundwater table drop exceeding 30 meters over the study period. These environmental stresses were compounded by a fourfold population growth and a doubling of per capita water consumption. Consequently, vegetation cover declined persistently, with NDVI decreasing from 0.2817 in 2004 to 0.1701 in 2021, while barren lands expanded significantly. Within the catastrophe theory framework, three primary drivers—groundwater depletion, vegetation loss, and population–water pressure—were identified as collectively responsible for 50% of the system’s destabilization. The evidence confirms a transition from a stable ecological state to a dissipative, degraded phase. Conclusions: The Sultanieh Grassland has likely crossed a critical ecological threshold due to the synergistic intensification of anthropogenic and climatic pressures within a geomorphologically and hydrologically vulnerable setting. Without immediate intervention—including sustainable groundwater management, strict control of urban expansion, and active restoration of hydrological equilibrium—the ecosystem faces irreversible transformation into an active source of dust emissions and desertification. This study underscores the urgency of science-based policy actions to prevent the total collapse of this irreplaceable natural and cultural heritage site. Anthropocene, catastrophe theory, ecological rupture, land use change, Sultanieh Grassland http://jsaeh.khu.ac.ir/article-1-3523-en.html http://jsaeh.khu.ac.ir/article-1-3523-en.docx