Physics and Chemistry of the Earth最新文献

{"title":"Influence of land use pattern on urban stormwater runoff characteristics: a spatio-temporal case study of Delhi, India","authors":"Shivani Yadav ,&nbsp;Saurav Ambastha ,&nbsp;Harsh Pipil ,&nbsp;A.K. Haritash","doi":"10.1016/j.pce.2025.103989","DOIUrl":"10.1016/j.pce.2025.103989","url":null,"abstract":"<div><div>The current study underlines physico-chemical characterisation of the rainwater and stormwater runoff in capital city of Delhi, India, and to suggest the suitable treatment method for its reusability. The analysis of rainwater reveals that acidic ionic species (SO₄²⁻ and NO₃⁻) are being neutralized by alkaline ionic species (Ca²⁺, NH₄⁺, HCO₃⁻, etc.) present in suspended form in the atmosphere that resulted in no event of acid rain (pH &lt; 5.6) over Delhi. Similarly, stormwater runoff was neutralized when it came in contact with earth's surface which is majorly covered with alluvial nature of soil that is chiefly of crustal origin. Non-sea salt fraction revealed no contribution of marine bodies that may influence rainwater characterisation. Neutralization factor suggested the dominance of alkaline ionic species (NH₄⁺, HCO₃⁻, K⁺, Ca²⁺, and Mg²⁺) in rainwater over acidic ionic species (SO₄²⁻ and NO₃⁻) resulting in alkaline pH of rainwater. Presence of nutrients (PO₄³⁻ and NO₃⁻) in significant concentration which has the potential to cause eutrophication in freshwater bodies of Delhi. The study also compared the stormwater runoff quality with Indian drinking water standards suggesting the potential to reuse following the water treatment process and can help to bridge water supply and demand gap. Also, the use of constructed wetlands is suggested as a sustainable and eco-friendly treatment method to treat stormwater runoff and store it for further non-potable use in Delhi. The study targets and connects with the United Nations's Sustainable Development Goals (SDG) 6 and 11.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 103989"},"PeriodicalIF":3.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271245","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":"Hydrogeochemical characterization of groundwater quality in the Weining Plain, northwest China","authors":"Jiajia Kong ,&nbsp;Peiyue Li ,&nbsp;Mengyu Gong","doi":"10.1016/j.pce.2025.103994","DOIUrl":"10.1016/j.pce.2025.103994","url":null,"abstract":"<div><div>The Weining Plain relies heavily on groundwater to support human livelihoods and economic development. This research investigated the hydrochemical characteristics of groundwater in the Weining Plain, analyzed the processes controlling the changes in groundwater quality using multivariate statistics and graphical methods, and quantified the extent of the influence of water-rock interactions on the hydrochemical evolution by means of hydrogeochemical modeling. The results point to that the concentration sequence in which the dominant groundwater constituents in the Weining Plain unfold as follows: Na⁺&gt;Ca²⁺&gt;Mg²⁺&gt;K⁺ among cations, while HCO₃⁻&gt;SO₄²⁻&gt;Cl⁻&gt;CO₃²⁻ among anions, with hydrochemical types primarily categorized as SO₄·Cl–Ca·Mg, SO₄·Cl–Na, and HCO₃–Ca·Mg. Also, it revealed severe nitrate pollution in the region, with most groundwater not meeting drinking water standards. Principal component analysis identified that a combination of natural factors and human activities makes a difference in determining the quality of groundwater in the region. The water-rock processes are the primary natural controlling factor, coupled with strong shallow groundwater evaporation, which significantly regulate groundwater chemical changes, while human activities exacerbate groundwater chemistry degradation. Hydrogeochemical modeling of PHREEQC highlights that the dissolution of anorthite dominates the left bank path of the Yellow River with 5.32 mmol/L, whereas the cation exchange is significant in the right bank path, with 4.32 mmol/L of Na⁺. The dissolution of halite, gypsum, anorthite, coupled with cation exchange from Ca²⁺ to Na⁺, are key hydrogeochemical reactions driving changes in groundwater quality within the study region. This study provides a solid scientific basis for the management of groundwater resources in the region.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 103994"},"PeriodicalIF":3.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144290951","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 inversion modeling of surface gold abundance based on remote sensing imagery and geochemical Data: An example from Tasiast-Tijirit gold district, Mauritania","authors":"Gong Cheng ,&nbsp;Asad Atta ,&nbsp;Xiaoqing Deng ,&nbsp;Aqil Tariq ,&nbsp;Syed Hussain ,&nbsp;Lingyi Liao ,&nbsp;Mohamed Faisal ,&nbsp;Changliang Gao","doi":"10.1016/j.pce.2025.103991","DOIUrl":"10.1016/j.pce.2025.103991","url":null,"abstract":"<div><div>The Tasiast-Tijirit Terrane in northwestern Mauritania is an important gold mining district that mainly consists of igneous and metamorphic units that are thought to represent the remnants of older greenstone belts. Surface outcrops typically contain a high concentration of economically valuable elements. This study focuses on the quantitative inversion of auriferous soil and rock samples based on remote sensing data, highlighting the significance of using surface geochemical samples to delineate anomaly areas of gold mineralization in desert regions for effective mineral exploration programs. The backpropagation neural network inversion model was used in this work to quantitatively invert the soil and rock samples with spectral band reflectance of Landsat-7 ETM+ and GF-2 satellite imagery at 1:50000 and 1:5000 scale, respectively. Landsat-7 ETM+ was chosen because its spectral bands are almost identical to the GF-2 remote sensing data, allowing for a reasonable correlation between the datasets. Results indicate that the established model achieved R² values of modeling and test sets are 0.65 and 0.63, 0.52 and 0.49 with RMSE values of 0.009 and 0.014, 0.034 and 0.055 for soil and rock samples, respectively, using Landsat-7 ETM+. Similarly, GF-2 imagery R² values of modeling and test sets are 0.73 and 0.69, 0.60 and 0.57, with RMSE values of 0.005 and 0.004, 0.015 and 0.023 for soil and rock samples, respectively. The inversion modeling and predicted anomaly areas are well aligned with the geochemical exploration map and actual mining area. The findings suggest that although Landsat-7 imagery provides an overall distribution of surface gold elements, it is restricted in its ability to delineate high gold-rich zones in desert regions due to relatively coarse resolution besides the geological and environmental conditions such as wind erosion and weathering effects. Conversely, GF-2 imagery enabled precise delineation of the anomaly locations with rock samples, proving to be more effective owing to its higher resolution scale of 1:5000. Overall, the adopted innovative methodology that implements high-resolution satellite data with the bakpropagation neural network model promise to be very effective in enhacing minerals prediction accuracy and lowering the exploration costs.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 103991"},"PeriodicalIF":3.0,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289147","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":"Advancements in human health risk, detection and bioremediation of bacterial contaminants in water: A review","authors":"Venkatesh Anand Iyer ,&nbsp;Praveen Dahiya ,&nbsp;Dharmender Kumar","doi":"10.1016/j.pce.2025.103990","DOIUrl":"10.1016/j.pce.2025.103990","url":null,"abstract":"<div><div>Worldwide, the bacterial pollution in drinking water constitutes a major concern to human health. Bacterial infections by <em>Escherichia coli, Salmonella</em> spp.<em>, Campylobacter</em> spp., and <em>Legionella pneumophila</em>, can cause serious diseases, and their propensity to multiply swiftly in aquatic environments amplifies the risk. The vulnerable populations, including children and the elderly, are particularly prone to waterborne illnesses. Bacteria having pathogenic potential reproduce rapidly and this will increase risk of human health. In addition to this, many bacterial pathogens produce that have negative health effects resulting in severe illness, organ damage, and even lead to the death of a human being. The advances in detection and disinfection technologies, including quantitative microbial risk assessment (QMRA), metagenomics, and molecular diagnostic approaches, have boosted pathogen surveillance. Control techniques, such as membrane filtration, advanced oxidation processes, and bioremediation, offer viable options. This review addresses the entry and survival processes of bacterial pathogens in water, related health risks, and new technological breakthroughs in microbial abatement. Through microbial bioremediation technology, this study delives a comprehensive understanding of bacterial contamination in water and offers useful insights for policymakers, water management authorities, and public health specialists. Therefore, the development of a rapid detection and control strategy for water contaminants might lead to the necessity of coordinated measures to protect water quality for public health concerns.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 103990"},"PeriodicalIF":3.0,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271244","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":"Adsorptive removal of arsenic from water/wastewater using nano-sized metal oxides: A review","authors":"Hemant Kumar Joshi ,&nbsp;Naveen Chandra Joshi","doi":"10.1016/j.pce.2025.103992","DOIUrl":"10.1016/j.pce.2025.103992","url":null,"abstract":"<div><div>The discharge of arsenic metal contamination onto ecological settlements is a significant factor contributing to contemporary environmental concerns. The requirement to prioritize water security has emerged as a relatively recent societal concern. Nano sized oxides of metals like Fe, Al, Ti, Zn, etc. have garnered significant attention and research as promising adsorbents for efficient arsenic removal from wastewater because to their effective surface active sites, abundant availability, porous architectures, wide surface area, cost-effectiveness, environmental friendliness, and chemical stability. This article examines the recent advancements made in the field of eliminating arsenic from wastewater by the utilization of Nano sized metal oxides and their derivatives, with a critical perspective. The comparative study shows that mesoporous aluminium magnesium oxide was found to be the best adsorbent for arsenite As(III) and arsenate As(V) with adsorption capacity of 813 mg/g at pH 7 and 912 mg/g at pH 3, respectively, that has been synthesized and used for arsenic removal to date. This article also provides descriptions of adsorption mechanism, behaviour and regeneration. The enhancement of adsorption efficacy is emphasized by focusing on future prospects and technological challenges. The assessment encompassed the commercial feasibility of real-time applications, as well as their potential utilization on a large-scale industrial level, in addition to the projected outlook for these applications.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 103992"},"PeriodicalIF":3.0,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243024","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":"Water reservoirs quality management using meta-heuristic Algorithms: Analysis and optimization of water quality considering uncertainties","authors":"Seyedeh Zahra Hassani ,&nbsp;Parisa-Sadat Ashofteh ,&nbsp;Seyed Rohollah Hoseini Vaez","doi":"10.1016/j.pce.2025.103987","DOIUrl":"10.1016/j.pce.2025.103987","url":null,"abstract":"<div><div>Managing reservoir water quality under uncertainty remains a critical challenge in contemporary water resource management. This study introduces a robust simulation–optimization meta-model framework to enhance reservoir outflow quality, focusing on minimizing Total Dissolved Solids (TDS) concentrations. To circumvent the computational limitations of high-fidelity simulators, a Supervised Learning (SL) surrogate model was developed as a substitute for the CE-QUAL-W2 simulator. Achieving a prediction accuracy of 85 %, the SL model effectively captures complex, nonlinear interactions within water quality dynamics. Two hybrid metaheuristic frameworks—Particle Swarm Optimization integrated with SL (PSO-SL) and Enhanced Vibrating Particle System integrated with SL (EVPS-SL)—were implemented to optimize reservoir outflows under uncertainty. Both approaches successfully balanced the competing objectives of meeting downstream water demand and minimizing TDS concentrations, while significantly reducing computational costs and improving convergence behavior. The rigorously calibrated CE-QUAL-W2 model demonstrated high validation scores (<em>NSE</em> = 0.99 for storage volume and 1.00 for water level; PBIAS = −0.05 % and −0.0004 %, respectively), confirming its reliability for surrogate training. Additionally, the study examined uncertainty propagation using two widely adopted sampling techniques: Monte Carlo Simulation and Latin Hypercube Sampling (LHS). Optimization outcomes were assessed using performance metrics—reliability, vulnerability, and resilience. The PSO-SL model, coupled with Monte Carlo sampling, exhibited the most balanced performance, achieving 41 % reliability and 26 % vulnerability. In contrast, EVPS-SL with LHS demonstrated faster convergence (30 % reduction in computational time) but yielded lower reliability (16 %) and higher vulnerability (87 %). This research not only advances reservoir water quality management under uncertainty but also contributes methodologically to the integration of data-driven surrogates and optimization within environmental systems modeling.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 103987"},"PeriodicalIF":3.0,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144262073","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":"Integrated geophysical evaluation of potential gold mineralisation within Nigerian Yashi Sheet 56 (1:100, 000)","authors":"Fahad Abubakar ,&nbsp;Babangida Mohammed Ahmed ,&nbsp;Ibrahim Adeiza Rabiu ,&nbsp;Joseph Omeiza Alao ,&nbsp;Ismail Ahmad Abir ,&nbsp;Aliyu Ohiani Umaru ,&nbsp;Fatihu Kabir Sadiq ,&nbsp;Ahmed Ibrahim Isiaka ,&nbsp;Lukman Adesina Olayinka ,&nbsp;Jose Adoze Usman ,&nbsp;Gomina David Ochu ,&nbsp;Danga Onimisi Abdulmalik","doi":"10.1016/j.pce.2025.103986","DOIUrl":"10.1016/j.pce.2025.103986","url":null,"abstract":"<div><div>This research aims to identify prospective gold mineralisation zones in northern Nigeria, specifically within the Nigerian Yashi Sheet 56 (1:100,000), where artisanal mining activities are increasingly prevalent. The study integrates hydrothermal alteration analysis and structural mapping using high-resolution airborne gamma-ray spectrometry and magnetic datasets. Advanced enhancement techniques, including K/eTh ratio mapping, ternary imaging, and radioelemental distribution, were employed to assess hydrothermal alterations and improve interpretative accuracy. Structural delineation of mineralized zones was achieved through analytic signal processing and Center for Exploration Targeting (CET) Grid analysis. Results indicate that high K/eTh ratio values (0.097–0.118 %/ppm) correlate strongly with hydrothermal alteration zones and known mining sites. The highest amplitude peaks (0.058–0.140 nT/m) and high lineament density zones are identified as potential mineralisation targets. The predominant structural trends are E-W, ENE-WSW, and NE-SW, with mineralisation zones aligning more closely with the NE-SW trend. However, two of the six documented mining sites were not captured by the analytic signal and CET Grid analysis, likely due to intense potassic hydrothermal alteration, as suggested by the K/eTh ratio. A strong correlation among the datasets confirms the effectiveness of this integrated approach in delineating potential gold mineralisation zones, particularly in the southeastern part of the study area, where mining activities are concentrated. Areas characterized by high K/eTh ratios, elevated magnetic amplitudes, and dense lineament distributions are considered prime exploration targets. However, more priority is given to high K/eTh ratio due to the nature of mineralisation in the area. The findings boost the gold exploration strategy.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 103986"},"PeriodicalIF":3.0,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144231005","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":"Physicochemical characterisations and basic geotechnical properties of untreated and treated marine stabilised soil with Anadara granosa powder and nano-SiO2 powder","authors":"Ahmad Azizi Harun ,&nbsp;Masyitah Md Nujid ,&nbsp;Muhammad Mukhlisin","doi":"10.1016/j.pce.2025.103973","DOIUrl":"10.1016/j.pce.2025.103973","url":null,"abstract":"<div><div>Marine soil in the Penang State of Malaysia was characterised with respect to its engineering properties as a subgrade pavement layer in road constructions and coastal construction projects. The marine soil samples were collected from the Simpang Ampat region of Penang and underwent comprehensive physicochemical, mineralogical, and basic geotechnical analyses, potentially using them as subgrade pavement in road construction. The study explored the impact of incorporating <em>Anadara granosa</em> or better known as cockle shell powder and nano-SiO₂ or nano-silica powder into marine soil, focusing on its physicochemical and geotechnical properties. It involved a series of laboratory experiments to examine the grain size distribution, pH, and ignition loss of marine soil and determine its physical, chemical, and microstructure characteristics. The findings from ANOVA analysis demonstrated that incorporating cockle shell powder and nano-silica powder significantly affected the basic properties of marine soils, such as clay content, dry density, void ratio, and porosity. This study improved the understanding of the physicochemical properties of both untreated and treated marine soils, laying the groundwork for future research aimed at developing engineering solutions and mitigation strategies for coastal construction. Understanding the unique characteristics of marine soils is essential for building sustainable coastal areas and adapting infrastructure to changing environmental conditions.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 103973"},"PeriodicalIF":3.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195696","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":"Intercomparison of machine learning models for estimating leaf area index of rice using UAV-based multispectral imagery","authors":"Sumit Kumar Vishwakarma,&nbsp;Benu Bhattarai,&nbsp;Kritika Kothari,&nbsp;Ashish Pandey","doi":"10.1016/j.pce.2025.103977","DOIUrl":"10.1016/j.pce.2025.103977","url":null,"abstract":"<div><div>Leaf Area Index (LAI) serves as a crucial biophysical indicator, providing valuable insights into canopy vigor and water use. Accurate LAI estimation is essential for crop monitoring, and crop yield prediction. The present study assessed the efficacy of different machine learning (ML) algorithms in estimating LAI obtained from field experiment conducted in Roorkee, India, where rice was grown under two irrigation techniques, and three nitrogen levels. LAI was measured using a ceptometer and images were captured from an Unmanned Aerial Vehicle (UAV)-borne multispectral sensor. Nine ML models were built using 20 vegetation indices, which included Multiple Linear Regression (MLR), Ridge Regression, Lasso Regression, Elastic Net Regression, Extreme Gradient Boosting Regression (XGBoosting), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Artificial Neural Network (ANN) and Random Forest (RF). Among the vegetation indices used in the study, ENDVI and EG showed the highest positive correlation (r = 0.68) with LAI values. Other vegetation indices such as NDVI, ARVI, OSAVI, and NDI also had a positive correlation (r ≥ 0.60) with LAI values. During model testing, lower R² values were recorded for MLR (0.74), Ridge (0.75), Lasso (0.78), ElasticNet (0.74), and XGBoosting (0.77) models, while KNN (0.82), SVM (0.84), ANN (0.83), and RF (0.80) models performed better. Overall, the SVM outperformed other ML algorithms in predicting the LAI of rice under different treatments. Our study demonstrated that UAV-based multispectral images coupled with ML algorithms are capable of producing LAI of rice with reasonable accuracy.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 103977"},"PeriodicalIF":3.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204834","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":"Multicriteria evaluation of cropland suitability using multisource datasets of satellite remote sensing and ground observation","authors":"Danish Raza ,&nbsp;Hong Shu ,&nbsp;Sahar Mirza ,&nbsp;Hasnat Aslam ,&nbsp;Aqil Tariq ,&nbsp;Rana Waqar Aslam ,&nbsp;Hafsa Aeman ,&nbsp;Muhsan Ehsan ,&nbsp;Maryam Muhammad Ali","doi":"10.1016/j.pce.2025.103978","DOIUrl":"10.1016/j.pce.2025.103978","url":null,"abstract":"<div><div>The potential of agriculture land monitoring serves as the lifeblood of communities, nourishing populations and fostering economic growth on a global scale. Towards the advancement of the computational approach, this study employed an analytical hierarchal process modeling for agriculture land suitability assessment by integrating a comprehensive array of 4 major criteria with a decision matrix, including 19 influencing parameters. This research incorporates the field data, including soil chemical and physical properties, irrigation water accessibility and irrigation water quality parameters, which are analyzed with cutting-edge remote sensing data layers and climatic variables using an integrated modelling approach. Thorough field observations and integrated methodology improved the conventional practices by considering the close interactions between soil, irrigation water, cropland and topography. The most innovative aspect of this research is based upon the seamless fusion of data layers of different datasets, which improves agriculture's suitability. Pairwise comparisons are systematically conducted to assign weights to each parameter, ensuring a robust decision-support framework with weighted overlay. The finding showed that the 72209.03 acres (9.13 %) cropland is highly suitable, whereas the 717738.48 acres (90.77 %) area is suitable, and the 788.49 acres (0.1 %) area is less suitable for crop cultivation. The study emphasizes the significance of each parameter in influencing suitability, contributing valuable insights into sustainable land management practices. The findings provide meaningful information for policymakers, land use planners and agriculture stakeholders interested in optimizing land management strategies to ensure sustainable agriculture development.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"140 ","pages":"Article 103978"},"PeriodicalIF":3.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144212665","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}