Results in Earth Sciences最新文献

{"title":"Retrieval of the land surface temperature using thermal remote sensing and its relationship with hydrometeorological variables, Sabarmati Basin, Gujarat, India","authors":"Pooja Kumari ,&nbsp;Rina Kumari ,&nbsp;Deepak Kumar","doi":"10.1016/j.rines.2025.100091","DOIUrl":"10.1016/j.rines.2025.100091","url":null,"abstract":"<div><div>Climatic variation and land-atmosphere interaction affect the natural resources, particularly in the arid/ semi-arid regions. The present research work has been carried out in the Sabarmati basin to quantify Land surface temperature (LST), factors and their impact on hydrometeorology and biophysical parameters. LST and indices were estimated using Landsat 5, 7 and 8 images on a decadal basis using thermal and spectral bands. The monthly TRMM (Tropical Rainfall Measuring Mission) data was used to analyse the rainfall pattern in the study area. Different indices such as normalised difference vegetation index (NDVI), normalised difference moisture index (NDMI), and normalised difference water index (MNDWI) were calculated. Results suggests that from 1990 to 2020, the maximum LST increased by 4.36°C and the minimum LST increased by 5.90°C. In 2020, high LST zones (areas above the mean LST) increased by 8085.51 sq. km compared to 1990. The study finds a negative correlation coefficient of LST with Vegetation Index (NDVI) (r = −0.41), MNDWI (r = −0.54), and Moisture Index (NDMI) (r = −0.69), whereas a moderate positive correlation exists with elevation (r = 0.33). The surface water body area increased significantly in 2020 compared to 1990 due to the formation of new reservoirs and water channels, as well as increased rainfall during the 2019 monsoon season in the river basin. This study provides valuable insights into climate change impacts, aiding urban planning. It also emphasizes the importance of preserving green spaces and water bodies and expanding vegetation in barren lands to combat LST intensification.</div></div>","PeriodicalId":101084,"journal":{"name":"Results in Earth Sciences","volume":"3 ","pages":"Article 100091"},"PeriodicalIF":0.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143882126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A geospatial assessment of land use changes and their influence on land surface temperature in Koch Bihar district, West Bengal","authors":"Pritam Saha ,&nbsp;Shasanka Kumar Gayen","doi":"10.1016/j.rines.2025.100089","DOIUrl":"10.1016/j.rines.2025.100089","url":null,"abstract":"<div><div>Land use and land cover (LULC) changes significantly impact regional climate, particularly their influence on land surface temperature (LST). This study employs remote sensing (RS) and geographic information system (GIS) techniques to assess LULC transitions and their thermal effects in the Koch Bihar district of West Bengal over the past three decades (1991–2021). Previous studies have predominantly concentrated on assessing land-use transformations, with limited attention given to the LST dimension and the systematic identification of major conversion patterns and temporal trends. Multi-temporal Landsat imagery was used to classify vegetation, agricultural land, built-up areas, fallow land and water bodies, revealing significant transformations. Results showed that agricultural land expanded by 6.31 %, while built-up areas increased by 5.18 %, primarily at the expense of vegetation cover (10.81 %), contributing to significant LST modifications. Seasonal temperature trends indicate a rise in summer LST from 37.52°C (1991) to 39.76°C (2021) and an increase in autumn temperatures, highlighting the urban heat island (UHI) effect. In the study area, Normalized Difference Vegetation Index (NDVI) values declined over time, confirming a loss of vegetative cover and reflecting intensified urbanisation. The spatial trend analysis indicates that urbanisation, agricultural intensification and deforestation have led to higher thermal loads across the region. The outcomes of this study may serve as a valuable resource for policymakers and enhance public awareness by offering a scientific foundation for sustainable land use planning and effective management strategies.</div></div>","PeriodicalId":101084,"journal":{"name":"Results in Earth Sciences","volume":"3 ","pages":"Article 100089"},"PeriodicalIF":0.0,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143851973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aquifer integrity test using the Dar Zarouk parameters in Emure Ekiti Southwestern Nigeria","authors":"M.A. Bello ,&nbsp;M.I. Oladapo ,&nbsp;M.R. Abraham-A ,&nbsp;O.M. Orji","doi":"10.1016/j.rines.2025.100087","DOIUrl":"10.1016/j.rines.2025.100087","url":null,"abstract":"<div><div>The call for borehole drilling to exploit underground water in Emure Ekiti due to the failure/unavailability of pipe bone water engenders the application of the Dar Zarouk parameter for potential aquifer delineation, which is uncommon for the region. H and HA curve types are the most dominant sounding curves, revealing (3) to six (6) subsurface layers whose topsoil resistivity and thickness range from 42 Ω-m to 4965 Ω-m and 0.4 m and 2.1 m, respectively. The laterite layer resistivity and thickness range from 42 Ω-m to infinity (∞) and 2.9 m to 63.4 m, respectively. The fracture basement layer resistivity and thicknesses range between 112 Ω-m and ∞ , 8.1 m and 95.1 m, respectively. The weathered layer gave a resistivity value between 145 and 16100 Ω-m and a layer thickness of 61.5 m and ∞ . The fresh bedrock resistivity and depths range from 1537 Ω-m and 0.4 m to 132.4 m, respectively. The basement relief map reveals fairly deep basement depressions on the northeastern flank and basement ridges on the southwestern flank. Geoelectric parameters and maps classify the study area into poor/low, medium, and high groundwater potential zones. 80 % of Emure Ekiti is underlain by marginally thick overburden, thus constituting shallow aquifer units with poor to marginal groundwater potential. The weathered fractured basements constitute the aquifer unit. Partially weathered/fractured basements in isolated regions tend to have low to marginal groundwater yield around the northeastern flank. The results reasonably provide essential information that is expected to assist the town’s future development of groundwater resources.</div></div>","PeriodicalId":101084,"journal":{"name":"Results in Earth Sciences","volume":"3 ","pages":"Article 100087"},"PeriodicalIF":0.0,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scaling mine pit highwall sulfide reactivity based on humidity cell tests and a 13-year field oxidation test","authors":"Maggy Lengke,&nbsp;Andy Davis","doi":"10.1016/j.rines.2025.100086","DOIUrl":"10.1016/j.rines.2025.100086","url":null,"abstract":"<div><div>The reliability of kinetic humidity cell tests (HCTs) to predict sulfide oxidation and leachate chemistry in mine highwalls was assessed using long-term field oxidation data from the Gold Quarry mine in Nevada, USA. HCTs use finely crushed material (&lt;6.35 mm), which may overestimate weathering rates compared to field conditions where rock is coarser and exposed to natural conditions. Four material types, ranging from highly acid-generating to highly acid-neutralizing, were crushed to &lt; 2, 2–4, 4–16, and 16–64 mm fractions and subjected to both laboratory HCTs (for up to 22 weeks) and a 30-week field weathering test in 1996–1997, with a 1000 cm³ block also deployed in the field. In 2011, these materials were retrieved and run in HCTs to assess long-term effects. The leachate pH and sulfate in the 2011 HCTs closely matched the terminal 1997 HCT data, confirming that the 1997 HCTs had reached equilibrium. HCT sulfide oxidation rates were 2.1–4.7 times higher than the corresponding field tests for 2–64 mm fractions and up to ∼1600 times higher than those of the blocks, highlighting the need for empirical scaling. Mineralogical analysis identified dissolution and precipitation reactions, confirmed by geochemical modeling. The sulfate release and scaling factors correlated with pH and particle size, providing a robust, field-calibrated framework to scale laboratory sulfide reactivity data to more accurately predict pit lake and waste rock draindown chemistry, necessary for Environmental Impact Statements and mine closure planning.</div></div>","PeriodicalId":101084,"journal":{"name":"Results in Earth Sciences","volume":"3 ","pages":"Article 100086"},"PeriodicalIF":0.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Significance of Digitalized Logs and Seismics through Structural Modelling and Petrophysical Analyses: Case study: Neogene-Paleogene reservoirs of the Rio Del Rey Basin, Gulf of Guinea. Cameroon","authors":"Mbouemboue Nsangou Moussa Ahmed ,&nbsp;Olugbengha Ajayi Ehinola ,&nbsp;Wakwenmendam Nguet Pauline ,&nbsp;Marie Joseph Ntamak Nida ,&nbsp;Anatole Eugene Djieto Lordon","doi":"10.1016/j.rines.2025.100085","DOIUrl":"10.1016/j.rines.2025.100085","url":null,"abstract":"<div><div>The advent of geophysics into the world of hydrocarbon exploration has been proven to date very far back in time demonstrated by information from well logs and seismics. This study tries to characterize the reservoir using well logs and seismics originally digitized from analogue from the Rio Del Rey basin of Cameroon. Well logs and seismic maps were transformed from analogue to digital format using the Neuralog software 2018 package. Five well logs: Log L1, L2, L4, and L5, and five digital seismic maps were available for this study generated from LongiviNeuralog and Neuramap respectively. One very important reservoir was mapped for the five well scenarios. Plots were produced randomly in Interactive petrophysics software; Porosity plots, shale volume, and petroleum play maps. Reservoirs were delineated randomly in all the well scenarios with different thicknesses. Lithological plots of these formations indicated that reservoirs consist of sand, limestone, and dolomite and a Ypression mega sequence of deposition containing 4 – 6 sand units (S1.0, S1A2, S1A3, S1A4, SB). The presence of hydrocarbon in a complex paralic sand environment was inferred from the highly faulted area (7 listric faults). Finding saw reservoir compartmentalization from the structural, petrophysical, and stratigraphic anisotropy observed; 0.37–0.45 well L2, 0.08–029 well L4, 0.1624–0.30 well L1, and 0.10–0.35 well L5 for porosity, 4.099–133.4 mD, 2068.9 – above 10000 mD, 1.4228–227.3726 mD, 12.5237–454.8518 mD, For L1, L2, L4, L5 respectively. So, drilling for wells at the center of the study area is discouraged for those at the western and eastern edge of the study area. This study extends the understanding of the reservoir characterization of the Neogene-Paleogene formation proving efficient digitization using Neuralog, Petrel 2017, and an efficient reservoir study using Interactive petrophysics, Techlog, and Petrel.</div></div>","PeriodicalId":101084,"journal":{"name":"Results in Earth Sciences","volume":"3 ","pages":"Article 100085"},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning and neural networks in predicting grain-size of sandy formations","authors":"Fori Yao Paul Assalé ,&nbsp;Assiès François Aristide Kouao ,&nbsp;Marcel Touvalé Kessé","doi":"10.1016/j.rines.2025.100084","DOIUrl":"10.1016/j.rines.2025.100084","url":null,"abstract":"<div><div>A total of 2520 sand samples, obtained from grain size analysis, were used in this study. The primary aim is to predict sand grain sizes using machine learning and deep learning algorithms. The input data consists of the five grain size fractions of sands based on the Udden-Wentworth scale, while the output data represents the five sand types (very coarse, coarse, medium, fine, and very fine) according to the average grain size. The machine learning algorithms employed are Random Forest and XGBoost, while the deep learning algorithms include MLP (Multilayer Perceptron) and LSTM (Long Short-Term Memory). All algorithms were implemented using Python. The evaluation metrics used for model assessment include K-fold validation, confusion matrix, and accuracy. The dataset was split into training (70 %, 1764 samples) and validation (30 %, 756 samples) sets. The study reveals that LSTM and MLP neural networks are better suited for predicting sand sizes, with MLP achieving the highest accuracy at 99.6 %. While machine learning algorithms performed well, they slightly lagged behind neural networks, with Random Forest achieving 99.07 % accuracy and XGBoost 98.81 %. In terms of sand type classification, all algorithms predicted very fine and very coarse sands with 100 % accuracy. However, fine, medium, and coarse sands showed some susceptibility to misclassification. Coarse sands were the most prone to misclassification, particularly being misidentified as medium or very coarse sands.</div></div>","PeriodicalId":101084,"journal":{"name":"Results in Earth Sciences","volume":"3 ","pages":"Article 100084"},"PeriodicalIF":0.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimisation of stope support system using kinematic analysis and numerical modelling – A sustainable mining approach","authors":"Wayne Mudamburi ,&nbsp;Tawanda Zvarivadza ,&nbsp;Takunda Bvumai Muwirimi ,&nbsp;Moshood Onifade ,&nbsp;Manoj Khandelwal","doi":"10.1016/j.rines.2025.100083","DOIUrl":"10.1016/j.rines.2025.100083","url":null,"abstract":"<div><div>Optimising stope support design is crucial in mining engineering to ensure underground safety and stability. Traditionally, rock mass classification methods have guided support strategies, but they come with inherent limitations. This study takes a novel approach by adopting support resistance design criteria, providing a more effective alternative. Using advanced numerical modelling techniques, the research evaluates stope support systems by considering key factors such as geomechanical properties, stope geometry, and support configurations. The study specifically examines three primary failure modes wedge failure, block failure, and spalling through simulations that replicate real-world mining conditions. By integrating empirical data with sophisticated analytical tools, the research accurately determines support resistance requirements, ensuring structural reliability and minimising failure risks. The optimised design, tailored to local geological conditions, significantly enhances worker safety and operational resilience by reducing the likelihood of support failures. A comprehensive economic analysis indicates that while the initial implementation costs are slightly higher, the long-term advantages such as reduced downtime, fewer ground falls, and improved safety protocols far outweigh the investment. This approach strikes a balance between economic feasibility and operational sustainability by prioritising durable and effective support systems. By moving away from traditional methodologies, this study highlights the need for innovative strategies in stope support design, ultimately contributing to safer, more efficient, and sustainable mining practices. The findings also promote resource optimisation, reducing unnecessary support material usage and mitigating the need for ground fall reclamation.</div></div>","PeriodicalId":101084,"journal":{"name":"Results in Earth Sciences","volume":"3 ","pages":"Article 100083"},"PeriodicalIF":0.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heat map from aeromagnetic data processing to uncover potential gold prospects in Bidzar and surrounding area, North Cameroon","authors":"David Ikome Lyonga ,&nbsp;Christopher M. Agyingi ,&nbsp;Ligbwah Victor Wotanie ,&nbsp;Mary Ewokolo Mbua Etutu ,&nbsp;Jean Paul Sep Nlomngan ,&nbsp;Quentin Marc Anaba Fotze ,&nbsp;Ngalla Ndi ,&nbsp;Ganwa Alembert Alexandre","doi":"10.1016/j.rines.2025.100082","DOIUrl":"10.1016/j.rines.2025.100082","url":null,"abstract":"<div><div>The mining and petroleum sectors serve as the cornerstone of a resilient economy in the CEMAC (Economic Community of Central African State) subregions and Cameroon in particular. These deposits are structurally controlled, and with the global demand for these commodities, novel techniques are required to identify additional potential prospects. In this study, aeromagnetic datasets were processed using the Centre for Exploration Targeting grid analysis technique to map out structurally complex zones in and around the locality of Bidzar, North Cameroon. The Centre for Exploration Targeting (CET) lineament trend predominantly follows ENE-WSW, NE-SW, and E-W orientations, while lesser trends include NNE-SSW, NW-SE, and WNW-ESE directions. These structures are attributed to deformation phases, foliations, shear zones, and faults, which indicate the major structural event in Cameroon. The Contact Occurrence Density (COD) and Orientation Entropy (OE) heat maps generated from the vectorized structures delineate potential gold prospects related to hydrothermal activity on the sheared lithologies of the Neoproterozoic Pan-African greenstone belt and metasediment in the vicinity of Bidzar, north Cameroon. This study demonstrates that structural interpretation based on aeromagnetic data is an effective tool in mineral discovery.</div></div>","PeriodicalId":101084,"journal":{"name":"Results in Earth Sciences","volume":"3 ","pages":"Article 100082"},"PeriodicalIF":0.0,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of brittleness and comparison of hydrofracturing potential of water and non-aqueous alternative- CO2 in coal","authors":"Sarada Prasad Pradhan ,&nbsp;Pranay Bhapkar ,&nbsp;Mohd Sharique Siddiqui ,&nbsp;Piyush Ranjan Das ,&nbsp;Vikram Vishal","doi":"10.1016/j.rines.2025.100081","DOIUrl":"10.1016/j.rines.2025.100081","url":null,"abstract":"<div><div>Hydraulic Fracturing (HF) is a significant method used for enhancing the oil and gas recovery from low permeability reservoirs. The selection of specific injecting fluid impacts the reservoir permeability enhancement, long-term production efficiency and fracture propagation potential of the reservoir. This study compares the fracture propagation potential of water and non-aqueous alternative- supercritical CO₂, using Perkins-Kern-Nordgren (PKN) and the Khristianovic-Geertsma-de-Klerk (KGD) fracture models in low permeability coal and shale reservoir. Reservoir compatibility for performing HF operations is identified by studying the brittleness of the reservoir based on the elastic parameters (i.e., poisson’s ratio <span><math><mrow><mo>(</mo><mi>v</mi><mo>)</mo></mrow></math></span>, young’s modulus (E)). Brittleness is highly influenced by tensile strength, modulus of elasticity, poisson’s ratio, and coal composition. Based on the analysis of elastic parameters, coal samples are found to be high to moderately brittle in nature, indicating the suitability of Jharia coalfield for carrying out HF operations. Comparing two injecting fluids, CO₂ shows 116 % greater fracture propagation length than water using the PKN model, whereas the difference is ∼90 % when tested using the KGD model. The results indicate that the fracture propagation ability of the reservoir primarily depends on Poisson’s ratio <span><math><mrow><mo>(</mo><mi>v</mi><mo>)</mo></mrow></math></span>, shear modulus (G), Young’s modulus (E), temperature of the reservoir and viscosity of injecting fluid (<span><math><mrow><mi>μ</mi><mo>)</mo></mrow></math></span>.</div></div>","PeriodicalId":101084,"journal":{"name":"Results in Earth Sciences","volume":"3 ","pages":"Article 100081"},"PeriodicalIF":0.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flood susceptibility mapping in Kali River Basin, Southern India: A GIS-based analytical hierarchy process modelling","authors":"Ananda Krishnan ,&nbsp;S.G. Dhanil Dev ,&nbsp;S. Arjun ,&nbsp;V. Deepchand ,&nbsp;Yogendra Singh ,&nbsp;E. Shaji ,&nbsp;P.K. Krishnaprasad","doi":"10.1016/j.rines.2025.100079","DOIUrl":"10.1016/j.rines.2025.100079","url":null,"abstract":"<div><div>Across the globe, floods are always a matter of concern for everyone due to the uncertainty of their occurrence and place. Though their prediction is still in the progress stage, there are enough methods available to identify the areas that have the potential to experience any specific kind of hazard. The present study is focused on an area located in the Uttara Kannada district of Karnataka and the South Goa district in Goa, which experienced a natural hazard for the first time in the form of the Kali River flood in 2019. The study aims to develop flood susceptibility maps for selected subbasins of the Kali River using integrated remote sensing techniques with the analytical hierarchy process system. Detailed analyses of numerous causative factors, i.e., elevation, slope, distance from the river, precipitation, flow accumulation, stream density, soil types, water ratio index, land use land cover, topographic wetness index, and stream power index, were carried out. The result shows that the area can be categorized into five zones ranging from very low to very high susceptibility to flooding. The prevalence of flooding in the study area can be attributed to increased sediment deposition, anthropogenic disturbances, land use and land cover patterns, gentle slopes, elevated soil moisture levels, reduced stream capacity, and limited soil infiltration capacity. The accuracy of the result was assessed using the receiver operating characteristic (ROC) method and confirmed the predictive capability of the generated map. Approximately 30 % of the study area falls within the highly susceptible zone. The outcome of the study provides valuable insights for urban planners and policymakers, assisting them in formulating strategies to mitigate the impact of future flood hazards and minimize the damages, particularly in southwest coast India.</div></div>","PeriodicalId":101084,"journal":{"name":"Results in Earth Sciences","volume":"3 ","pages":"Article 100079"},"PeriodicalIF":0.0,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}