Physics and Chemistry of the Earth最新文献

{"title":"Soil erosion-induced watershed prioritization in the beas river sub-basin of the western himalayas: A multi-criteria decision-making and XAI-Based approach","authors":"Intejar Ansari ,&nbsp;Mohd Rihan ,&nbsp;Md Rejaul Islam ,&nbsp;Mohd Waseem Naikoo ,&nbsp;Swapan Talukdar ,&nbsp;Shahfahad ,&nbsp;Md Rejaur Rahman ,&nbsp;Atiqur Rahman","doi":"10.1016/j.pce.2025.104011","DOIUrl":"10.1016/j.pce.2025.104011","url":null,"abstract":"<div><div>Beas River Sub-Basin is experiencing severe soil erosion due to extreme hydro-climatic events and anthropogenic activities. Therefore, prioritizing erosion-prone watersheds is essential for effective soil resource management. This study proposes an integrated approach combining morphometric analysis using weighted compound factor (WCF) and soil erosion susceptibility modelling (SESM) through fuzzy analytical hierarchy process (FAHP). The results from both analyses were integrated using fuzzy overlay to derive watershed priority rankings, from highest (rank 1) to lowest (rank 20). Watersheds A01BEA09, A01BEA14 and A01BEA19, located in the middle sub-basin, showed the highest susceptibility and were ranked 1st, 2nd and 3rd, respectively. In contrast, watersheds A01BEA01 and A01BEA02 in the eastern region showed the lowest susceptibility and were ranked 20th and 19th. The results also show that 7141 km² (57.7 %) of the northern and northwestern sub-basin is highly susceptible to soil erosion, while 4238 km² (33.6 %) and 1219.55 km² (9.6 %) show moderate and slight susceptibility, respectively. The SHapley Additive exPlanations (SHAP) analysis identified land use land cover (LULC), slope, rainfall and sediment transport index (STI) as the most influential parameters. Sensitivity analysis confirmed LULC as the dominant factor, followed by rainfall, slope and STI. Excluding LULC reduced the model's accuracy from 0.843 to 0.628. The findings highlight the critical role of LULC management in mitigating soil erosion, which threatens agricultural productivity, accelerates reservoir sedimentation, and endangers food and water security. This study provides valuable insights for stakeholders and policymakers to develop targeted strategies and implement watershed management frameworks in high-risk areas.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 104011"},"PeriodicalIF":3.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of radiological hazards due to natural radioactivity in groundwater from Al Masaraat aquifer, Oman","authors":"F. Al Hatmi ,&nbsp;Z. Embong ,&nbsp;A. Gismelseed","doi":"10.1016/j.pce.2025.104012","DOIUrl":"10.1016/j.pce.2025.104012","url":null,"abstract":"<div><div>Evaluating radiological health risks of drinking water by analyzing radionuclides is essential for public health studies, as it provides insights into population exposure levels. This research presents the first comprehensive evaluation of the quality of groundwater in Al Dhahirah Governorate, Oman, which is the major source of drinking water source. This investigation evaluates the risks of contamination from naturally occurring radionuclides (²³⁸U, ²³²Th, ⁴⁰K) using a Hyper Pure Germanium detector (HPGe). Additionally, determine both internal and external radiation hazard indices (H_ex and H_in) to determine whether the groundwater meets safety standards, providing essential data to guide public health protection and environmental sustainability. The findings indicated that the water is slightly alkaline, with moderate levels of dissolved salts, as evidenced by electrical conductivity (EC) and total dissolved solids (TDS) readings. Radionuclide concentrations (²³⁸U, ²³²Th, and ⁴⁰K) in all samples were below the World Health Organization (WHO) permissible limits for drinking water. The calculated annual effective doses (AEDs) for two age groups were also well below the WHO-recommended threshold of 0.10 mSv/year, indicating that the residents living in these areas are not at risk from radiological exposure due to groundwater consumption. Furthermore, hazard indices (H_ex and H_in) were below reference levels, indicating no significant health risks from radiation. In conclusion, groundwater is chemically and radiologically suitable for domestic and irrigation purposes. Based on the findings, the groundwater from the study area can be used for drinking and agricultural purposes with practically insignificant radiological health risks towards the local population. Conversely, routine monitoring of radionuclide concentrations and indicators of water quality parameters is crucial to ensure sustainability of the water safety, especially where there may be impending geological or anthropogenic changes that might influence groundwater composition.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 104012"},"PeriodicalIF":3.0,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deciphering the teleconnections of extreme temperature indices with local scale meteorology using wavelet coherence","authors":"Adarsh Sankaran ,&nbsp;Ali Najah Ahmed ,&nbsp;Ahmed El-Shafie ,&nbsp;Mohsen Sherif ,&nbsp;Anna Maria Antony ,&nbsp;Krishna Anilkumar ,&nbsp;Libina Nasarudeen Raheena ,&nbsp;Jumna Thalakkottu Purath","doi":"10.1016/j.pce.2025.104009","DOIUrl":"10.1016/j.pce.2025.104009","url":null,"abstract":"<div><div>This study investigates the teleconnections of Extreme Temperature Indices (ETIs) with local meteorological parameters in a multi-scale perspective. Firstly, wavelet analysis was conducted on nine extreme temperature indices (ETIs) and three local meteorological variables over six major cities in India during the period 1981–2021, with the associations was studied using Bivariate Wavelet Coherence (BWTC) and Multivariate Wavelet Coherence (MWTC) approaches. The variability of extreme temperature indices is examined with local meteorological variables like Relative Humidity (RH), Surface Pressure (PS) and Wind speed at 2 m (WS2M) of Delhi, Mumbai, Chennai, Kolkata, Kochi and Guwahati which were distinctly different in climatic conditions, population and geographical features. The study revealed that significant coherence (AWC &gt;0.5) exists between selected extreme temperature indices and each local meteorological variable. Relative humidity is the most dominating local meteorological variable in cities Delhi and Guwahati, surface pressure in Chennai and Kochi, and wind speed in Mumbai and Kolkata. It was observed that relative humidity, surface pressure and wind speed are significant contributors to temperature indices at a scale of 8–16 months except percentile-based indices TX10p and TN90p in BWTC analysis. Multiple wavelet coherences suggest that the extremes can be better explained by combining two or more parameters and each city each city has a unique combination of local meteorological variables that together best described variances in the extreme climate indices.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 104009"},"PeriodicalIF":3.0,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The 2017 Lesvos (Midilli) earthquake (Mw 6.3): Earthquake hazard implications from source modeling, numerical waveform simulation with regional 1D velocity structure and static stress field","authors":"Özlem Karagöz ,&nbsp;Onur Tan","doi":"10.1016/j.pce.2025.104007","DOIUrl":"10.1016/j.pce.2025.104007","url":null,"abstract":"<div><div>We investigate the earthquake hazard of Lesvos Island and the Turkish coast, considering the source mechanism and rupture propagation of the June 12, 2017 Lesvos (Midilli) mainshock (Mw 6.3), its numerical waveform simulations with regional new 1D deep velocity structures, relocated seismicity, and crustal stress loading due to the destructive earthquakes. The teleseismic body waveform inversion indicates that the strike, dip, and rake of the fault are 127°, 47°, and −97°, respectively. The depth is 9 km, and the seismic moment is 3.4 × 10²⁵ dyne cm. The mainshock ruptures a 12 × 15 km² area with a maximum 1.9 m slip and 3.4 MPa average stress drop. The previous rupture models are evaluated with simulated broadband (0.05–10 Hz) ground motions based on the discrete wavenumber method, considering shallow soil amplifications. The S-wave velocity models used in the simulations between the mainshock and stations are defined with the multiple-filter method. Our bilateral rupture propagation model gives better fits for the waveform arrivals and Fourier spectrum. The waveforms’ frequency with the highest horizontal amplitude is ∼3 Hz, which agrees with the soil fundamental frequency in Vrissa village. It is concluded that the damage in Vrissa is caused by the soil structure, not rupture propagation. The earthquake clusters in the north and south of Lesvos agree with a right-lateral synthetic shear if the Psara-Lesvos and Agia-Paraskevi faults are considered the principal displacement zone of a SW-NE right-lateral strike-slip shear zone. The results infer the possibility of continuing the earthquake hazard for Lesvos Island and the western coast of Türkiye.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 104007"},"PeriodicalIF":3.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative source apportionment and health risk assessment of potentially toxic elements from the surface water and groundwater in a typical coal-mining area","authors":"Shiming Yang ,&nbsp;Zhan Xie ,&nbsp;Denghui Wei ,&nbsp;Lanchu Tao ,&nbsp;Qingsong Chen ,&nbsp;Md Galal Uddin ,&nbsp;Yangshuang Wang ,&nbsp;Ying Wang ,&nbsp;Yunhui Zhang","doi":"10.1016/j.pce.2025.104008","DOIUrl":"10.1016/j.pce.2025.104008","url":null,"abstract":"<div><div>Globally, water affected by potentially toxic elements (PTEs) from coal mining activities has threatened human health. The source apportionment and health risk assessment of these PTEs have yet to be further analyzed. Thus, the objectives of this study are to understand the main exceeding PTEs, quantify their source contributions, and estimate associated human health risks. 26 groundwater (GW) and 22 surface water (SW) samples were collected from the coal mining area of southwestern China. Fe (ER, GW: 46.15 %, SW: 77.27 %), Mn (GW: 26.92 %, SW: 77.27 %), and sulfate (SO₄²⁻) (GW: 15.38 %, SW: 18.18 %) exhibited higher rates of exceeding the limit in groundwater and surface water, respectively. The source apportionment showed that natural factors, agricultural processes, coal mining activities, and wastewater discharge commonly controlled the concentrations of the chemical components in the groundwater and surface water. The iron (Fe) and manganese (Mn) were attributed to coal mining activities, nitrate (NO₃⁻) was from agricultural processes, and fluoride (F) and arsenic (As) were derived from trace element minerals, with As also linked to coal mining activities. Health risk assessment indicated that the groundwater and surface water posed significant non-carcinogenic health risks for children (ER, GW: 23.08 %, SW: 36.36 %), females (GW: 23.08 %, SW: 36.36 %), and males (GW: 23.08 %, SW: 31.82 %). Among these PTEs, arsenic (As) had the most significant impact on the human health of various populations. This research provided a valuable understanding of protecting the water environment in coal-mining areas worldwide.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 104008"},"PeriodicalIF":3.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Agricultural drought assessment using deep learning and multi-sensor remote sensing data integration","authors":"Prashant Kumar,&nbsp;Sonvane Chetan Chandrakant,&nbsp;Sudhanshu Ranjan,&nbsp;Akshar Tripathi","doi":"10.1016/j.pce.2025.104006","DOIUrl":"10.1016/j.pce.2025.104006","url":null,"abstract":"<div><div>This study proposes a Deep Learning Multi-Layer Perceptron Neural Network (DLMLPNN) model-based Drought Index (DI), capable of handling large amounts of remotely sensed data from different sensors, for the Gaya district of South Bihar. Apart from Synthetic Aperture RADAR (SAR) data from Sentinel-1, the multispectral data from Sentinel-2 was to generate vegetation (NDVI) and moisture indices (NDMI) for the Gaya district in South Bihar. Further, rainfall data from the Tropical Rainfall Measuring Mission (TRMM) along with surface soil moisture data from the Soil Moisture Active Passive (SMAP) satellite, thermal data from Landsat-8 Operational Land Imager (OLI) and CH₄ and O₃ concentration data from Sentinel-5P are used. These remote sensing datasets were used as input for training the DLMLPNN to predict the Normalized Differential Moisture Index (NDMI) as an indicator of soil moisture. It was observed that the model estimated the NDMI with R² statistics of 0.87 and 0.852 in the training and testing phases respectively. The NDMI gave a high correlation of more than 60 % with the ground collected Volumetric Soil Moisture (VSM). Feature Importance (FI) score was also computed to find out the contribution of each parameter used in the estimation of soil moisture. Based upon the weightage of each parameter used in the estimation of NDMI, a novel DI of the Gaya region was prepared for 2023. This index is the first of its kind for multi-sensor and multi-parameter drought analysis for the region and can be used to indicate drought conditions in other drought-prone areas.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 104006"},"PeriodicalIF":3.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144470262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation on plastic-aggregates in coastal and marine pollution: Distribution, possible formation process, and disintegration prospects","authors":"Sudeshna Chell ,&nbsp;Mijanur Mondal ,&nbsp;Uday Kumar Ghorui ,&nbsp;Uttiya Dey ,&nbsp;Sabyasachi Chakrabortty ,&nbsp;Kousik Das ,&nbsp;Harish Puppala","doi":"10.1016/j.pce.2025.104000","DOIUrl":"10.1016/j.pce.2025.104000","url":null,"abstract":"<div><div>Plastic-aggregates are made up from unused or waste plastic and natural aggregates which have recently been emerged as a significant addition to the existing emerging contaminants list mainly in the coastal environment. The transformation from plastics/microplastics to Plastic-aggregates signifies a crucial shift in our understanding and use of plastics and prompting us to reconsider their fundamental characteristics along with possible environmental threats. When plastic waste is incinerated for the purpose of disposal, it combines with organic and inorganic substances present in the surrounding environment, leading to a new type of material. Besides, some natural factors (physical, chemical, biological or in combination) also act upon discarded plastics to combine with rocks and other earthen materials to form plastic-aggregates. Our research aims to build fundamental knowledge and critically review the possible formation process, classification, and possible degradation of all such polymer-rock compounds along with their impact on the ecosystem. The knowledge gap related to the degradation and release of secondary pollutants from these agglomerates is to be addressed urgently in future research. Development and standardization of proper sampling and reporting procedures for plastic-aggregates can enhance our understanding related to their impacts on human health as well as to the entire environment as these aggregates contain different toxic chemicals.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 104000"},"PeriodicalIF":3.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144587873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal variability and source attribution of PM2.5/PM10 ratios: Aerosol type classification and AQI evaluation across seventy monitoring stations in Delhi and Haryana, India","authors":"Ram Pravesh Kumar ,&nbsp;Ravent Rana ,&nbsp;Arti Choudhary ,&nbsp;Ranjit Singh","doi":"10.1016/j.pce.2025.104005","DOIUrl":"10.1016/j.pce.2025.104005","url":null,"abstract":"<div><div>The present study examines PM2.5 and PM10 levels at 70 CAAQMS stations across Delhi and Haryana from 2020 to 2023. The aerosol-type classifications were employed based on PM2.5/PM10 ratios, revealing a significant source of particulate matter. PM2.5 levels increased from 84.31 μg/m³ in 2020 to 154.64 μg/m³ in 2023, while PM10 rose from 171.12 μg/m³ to 268.46 μg/m³, both exceeding NAAQS limits and posing risks to human health and the environment. The lower concentration in 2020 was linked to reduced activities during the COVID-19 lockdowns. Chandni Chowk had the highest PM2.5 levels in 2020, but by 2023, New Moti Bagh had become the most polluted. For PM10, Chandni Chowk recorded the highest concentration in 2020 and 2021, while Anand Vihar surpassed it in 2022 and 2023. Seasonal variation showed higher PM2.5/PM10 ratios in winter and post-monsoon, and lower ratios in the monsoon and pre-monsoon seasons due to climatic factors. Delhi has higher PM2.5/PM10 ratios than Haryana, likely due to greater vehicular density and industrial activity. PM2.5/PM10 ratio analysis reveals that mixed-anthropogenic type (IIb1) and mixed dust type (IIb2) dominate the aerosols in Delhi and Haryana. The AQI results reveal that PM2.5 is the dominant pollutant in Delhi and Haryana across all seasons (2020–2023), with the highest values during winter, 220 and 179 days and in post-monsoon, 280 and 302 days, respectively. The study emphasises the need for stricter emission controls, particularly in Delhi, and aligns with SDG 11, supporting urgent policies to combat air pollution and protect community health and the environment.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 104005"},"PeriodicalIF":3.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144312800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Managing climate change risks in urban areas: determinants of climate change responses by informal settlement dwellers","authors":"Sani Abubakar Mashi ,&nbsp;Amina Ibrahim Inkani ,&nbsp;Elizabeth Dorsuu Jenkwe ,&nbsp;Martins Momoh","doi":"10.1016/j.pce.2025.104004","DOIUrl":"10.1016/j.pce.2025.104004","url":null,"abstract":"<div><div>Urban areas are central to climate change (CC) risk management but are among the most affected by its impacts, particularly informal settlements, where vulnerability is highest. However, little information exists on how informal sector dwellers respond to CC effects. This study examines the determinants of CC response strategies among informal sector households in Abuja Federal Capital City, Nigeria. A structured questionnaire survey was conducted with 388 purposefully selected households across five informal settlements, and logistic regression analysis was used to identify key factors influencing their CC responses. Findings show that while 55 %–83 % of respondents across the study locations were aware of CC response strategies, actual adoption was low. Only 27 % used fans or air conditioners for cooling, and 10 % adjusted seasonal activities in response to changing climate conditions. The remaining 16 response strategies, including solar energy use, flood prevention, tree planting, migration, and infrastructural adjustments, were each used by less than 7 % of households. Overall, CC responses in these informal settlements were uncoordinated, reactive, and lacked institutional support. Barriers to CC response adoption included lack of knowledge (24 %), inadequate infrastructure (23 %), financial constraints (21 %), and time limitations (19 %). Logistic regression analysis identified education, income, and occupation as significant positive determinants of CC response adoption, while marital status had a negative influence. These factors explained 80 % of the variation in CC responses, with a model accuracy of 94.6 %. To enhance CC resilience among informal sector households, effective strategies are needed, including intensive disaster risk education, economic support through grants and microfinance, and infrastructural upgrades such as drainage systems and green spaces. Institutional interventions are essential to support coordinated and sustainable climate adaptation in urban informal settlements. Upgrading programs are needed to provide some physical infrastructure to make the area more CC resilient.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 104004"},"PeriodicalIF":3.0,"publicationDate":"2025-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial assessment of snow cover patterns in the Sutlej River Basin using machine learning approaches and remote sensing data","authors":"Abhilash Gogineni ,&nbsp;Ravindra Vitthal Kale ,&nbsp;Srija Roy ,&nbsp;Prakhar Modi ,&nbsp;Pramod Kumar","doi":"10.1016/j.pce.2025.103996","DOIUrl":"10.1016/j.pce.2025.103996","url":null,"abstract":"<div><div>Snow cover information plays a significant role in the hydrology and climate of Himalayan river basins, making it an essential parameter for understanding seasonal flow variations in these regions. This study investigates the spatial variation of snow cover concerning elevation, slope, and aspect ratio across the Sutlej River Basin (SRB) over three seasons, monsoon, winter, and summer, from 2013 to 2021. The study was conducted on the Google Earth Engine (GEE) platform, using two machine–learning algorithms, Random Forest (RF) and Support Vector Machine (SVM), to classify the Landsat satellite data. The study results reveal that the Random Forest classification consistently demonstrated better performance across all three seasons, showing higher overall accuracy and Kappa coefficient values. A decadal increasing trend in Snow Cover Area (SCA) was observed throughout the Sutlej River Basin (SRB). Furthermore, topographic parameters such as elevation, slope, and aspect significantly influenced the spatial distribution of snow cover, showing patterns that contrast with broader climate trends. Specifically, higher elevations particularly those above 4500 m consistently retained substantial snow cover across all seasons. Slopes between 30° and 45°, classified as intermediate gradients, provided an optimal balance between steepness and flatness, promoting maximum snow retention. Regarding aspect, northern and northeastern-facing slopes showed the highest snow accumulation due to reduced solar radiation, which aids in preserving snow during warmer periods. Further, the results highlight the influence of climate variability, with a declining trend in summer snow cover and an increasing trend in monsoon snow cover observed over the past three years (2019–2021).</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 103996"},"PeriodicalIF":3.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}