Physics and Chemistry of the Earth最新文献_第2页

Revisiting the Urban heat and pollution Islands over the Kolkata metropolitan area, India 重访印度加尔各答大都市区的城市热岛和污染岛

IF 4.1 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2026-01-31 DOI: 10.1016/j.pce.2026.104330

Pragya Pandey , Bhishma Tyagi , Pradeep Kumar , Saroj Kumar Sahu , Kuldeep Sharma

Urban environments alter local climate and air quality through concentrated emissions of heat and pollutants, giving rise to effects such as Urban Heat Island (UHI) and Urban Pollution Island (UPI). These microclimatic phenomena have seen growth due to industrialisation and urbanisation. Their coupled interaction in the context of Indian cities, however, remains poorly understood. In this study, we have investigated the evolution of UHI and UPI over a megacity of India, Kolkata, with a focus on Kolkata Metropolitan Area (KMA) by analysing Remote Sensing (MODIS) and in situ measurements (CPCB) of Land Surface Temperature (LST), UHI, Aerosol Optical Depth (AOD), Direct and Diffuse Solar Radiation, and Particulate Matter (PM_2.5 and PM₁₀) for a collective period of 2001–2024. UHI and UPI were observed over KMA, with both Nighttime LST (NLST) and Daytime LST (DLST) as well as AOD having significantly higher values over the urban region by +1.79 °C, +2.92 °C, and 0.18, respectively, than in rural areas. The results also suggested that the magnitudes of UHI and UPI are increasing over the years for KMA. As a result of increasing UPI, the study observed a simultaneous reduction of direct solar radiation by 22.64 W/m² and an increase of diffuse radiation by 18.82 W/m² over urban areas for the study period. The study suggests that the UPI and UHI may influence each other through direct and diffuse radiative forcing, and that the modulation of urban surface energy balance may occur due to these changes, which may be a link to unprecedented weather events over the region. The results provide a scientific basis for developing policies on regional climate adaptation and air quality management in Indian cities.

城市环境通过集中排放热量和污染物改变当地气候和空气质量，产生城市热岛（UHI）和城市污染岛（UPI）等效应。由于工业化和城市化，这些小气候现象有所增加。然而，它们在印度城市背景下的耦合相互作用仍然知之甚少。在这项研究中，我们通过分析遥感（MODIS）和现场测量（CPCB）的陆地表面温度（LST）、城市热岛、气溶胶光学深度（AOD）、太阳直接辐射和漫射辐射以及颗粒物（PM2.5和PM10），研究了印度大城市加尔各答的城市热岛和UPI的演变，重点研究了加尔各答大都市区（KMA） 2001-2024年的变化。在KMA观测到UHI和UPI，夜间LST （NLST）和日间LST （DLST）以及AOD在城市地区的值分别显著高于农村地区+1.79°C, +2.92°C和0.18°C。结果还表明，KMA的UHI和UPI的大小逐年增加。由于UPI的增加，研究发现在研究期间，城市地区的太阳直接辐射减少了22.64 W/m2，散射辐射增加了18.82 W/m2。研究表明，UPI和UHI可能通过直接辐射强迫和扩散辐射强迫相互影响，这些变化可能导致城市地表能量平衡的调节，这可能与该地区前所未有的天气事件有关。研究结果为制定印度城市区域气候适应和空气质量管理政策提供了科学依据。

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引用次数: 0

Impact of lime treatment on the microstructure and geotechnical properties of micaceous soil 石灰处理对云母土微观结构及岩土力学性质的影响

IF 4.1 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2026-01-30 DOI: 10.1016/j.pce.2026.104324

Amaranatha Ginkapalli Anjaneyappa , Seelam Srikanth , Subhashish Dey

Micaceous soils present significant challenges in geotechnical engineering due to their platy mineral structure, high compressibility and poor load-bearing capacity. The untreated soil examined in this study contained a high fraction of flaky mica and exhibited inherently weak engineering behavior, with an unconfined compressive strength (UCS) of approximately 45 kPa and low bearing resistance, rendering it unsuitable for direct use in pavement and embankment applications. Although the lime stabilization is widely adopted for improving fine-grained soils, its effectiveness and underlying mechanisms in mica-rich soils remain inadequately understood, particularly the relationship between micro-structural evolution and engineering performance. To address this gap, the present study systematically evaluates the influence of lime treatment on the mechanical and micro-structural behavior of micaceous soil. Soil samples were treated with 2%, 4%, 6% and 8% quicklime and cured for periods of up to 56 days, followed by evaluation of strength, compaction characteristics, consistency limits and micro-structural characteristics. The UCS increased substantially, reaching a peak value of 244.8 kPa at 4% lime after 56 days, representing an improvement of approximately 5.4 times compared to the untreated soil. The California Bearing Ratio (CBR) also peaked at the same lime dosage, with unsoaked CBR increasing from 3.65% to 9.34% and soaked CBR from 2.12% to 7.15%. Micro-structural analyses using SEM, EDS, XRD and FTIR revealed the formation of cementitious products, particularly calcium silicate hydrate (C–S–H) and calcium aluminates hydrate (C-A-H) phases, providing mechanistic insight into the observed strength improvements. The added value of this study lies in explicitly linking micro-structural transformations to macroscopic strength and bearing enhancement in lime stabilized micaceous soils, demonstrating that lime treatment can effectively upgrade problematic mica-rich soils to meet the engineering requirements for pavement sub-grades and embankment fills.

云母土由于其板状矿物结构、高压缩性和较差的承载能力，在岩土工程中面临着巨大的挑战。本研究中检测的未经处理的土壤含有大量片状云母，其固有的工程性能较弱，无侧限抗压强度（UCS）约为45千帕，承载阻力低，因此不适合直接用于路面和路堤。石灰稳定被广泛用于改善细粒土，但其在富云母土中的有效性和潜在机制尚不清楚，特别是微观结构演变与工程性能之间的关系。为了解决这一空白，本研究系统地评估了石灰处理对云母土力学和微观结构行为的影响。土壤样品分别用2%、4%、6%和8%的生石灰处理，并固化长达56天，然后评估强度、压实特性、一致性极限和微观结构特征。UCS大幅增加，56天后，当石灰含量为4%时，UCS达到244.8 kPa的峰值，比未经处理的土壤提高了约5.4倍。石灰投加量相同时，加州承载比（CBR）也达到峰值，未浸泡CBR由3.65%增至9.34%，浸泡CBR由2.12%增至7.15%。利用SEM、EDS、XRD和FTIR进行的微观结构分析揭示了胶凝产物的形成，特别是水合硅酸钙（C-S-H）和水合铝酸钙（C-A-H）相，为观察到的强度提高提供了机制。本研究的附加价值在于明确地将石灰稳定云母土的微观结构转变与宏观强度和承载增强联系起来，表明石灰处理可以有效地升级问题云母土，以满足路面分层和路堤填筑的工程要求。

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引用次数: 0

Mineralogical characterization and rock physics parameter estimation in sandstone reservoir: A template-based approach and cross-plots analysis 砂岩储层矿物学表征和岩石物理参数估计：基于模板的方法和交叉图分析

IF 4.1 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2026-01-30 DOI: 10.1016/j.pce.2026.104329

Muhsan Ehsan , Muhammad Nofal Munir , Rujun Chen , Muhammad Ali , Kamal Abdelrahman , Ali Y. Kahal

Tight gas reservoirs require unconventional recovery techniques to obtain maximum production and need a detailed understanding of reservoir rock elastic parameters. Pab Formation has intervals of low permeability with promising hydrocarbon saturation. The study aims to provide a thorough analysis of the effect of porosity and mineralogical composition on the rock physics properties and brittleness index of the Pab Formation. In the present study, an investigation into clay minerals and types was conducted using cross-plot analysis from well log data, and validation was performed using SEM and XRD results from core samples. The research incorporates the calculation of the elastic parameters from the specialized user-defined equation and rock physics template (RPT). The findings of this research through petrography and XRD analysis of core samples reveal sandstone as the dominant lithology of the Pab Formation and are rich in quartz and kaolinite; cross-plot analysis also showed the presence of these clay minerals. Combining elastic moduli, porosity, and current petrophysical data for RPT analysis will serve as a robust framework and can be beneficial for similar studies in other basins.

致密气藏需要非常规采油技术来获得最大产量，并且需要详细了解储层岩石弹性参数。Pab组具有低渗透层段，含油饱和度较好。研究旨在全面分析孔隙度和矿物组成对Pab组岩石物理性质和脆性指标的影响。在本研究中，利用测井数据的交叉图分析对粘土矿物和类型进行了调查，并利用岩心样品的SEM和XRD结果进行了验证。该研究结合了专用自定义方程和岩石物理模板（RPT）计算弹性参数。岩心岩石学和XRD分析结果表明，Pab组岩性以砂岩为主，富含石英和高岭石；交叉图分析也显示了这些粘土矿物的存在。将弹性模量、孔隙度和当前岩石物性数据结合起来进行RPT分析，将成为一个强大的框架，并有助于其他盆地的类似研究。

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引用次数: 0

Calcium ferrate-ozone for enhanced removal of methylene blue: An innovative hybrid system 高铁酸钙-臭氧增强去除亚甲基蓝：一种创新的混合系统

IF 4.1 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2026-01-30 DOI: 10.1016/j.pce.2026.104314

Gcobisa Ndzungu, Caliphs Zvinowanda, Catherine Jane Ngila

Textile and paper industries produce hazardous dyes, especially methylene blue (MB), which harms the environment. Industrial coloured dyes are difficult to degrade with conventional wastewater treatment processes. Alternative wastewater treatment technologies that breakdown these coloured dyes are needed. This study examined how calcium ferrate (CaFeO₄), ozone (O₃), and their hybrid system degrade methylene blue (MB). Batch tests examined MB degradation under different pH and reaction time conditions at a given temperature and oxidant concentration. The degrading efficiency and performance of CaFeO₄ were measured by measuring MB absorbance at 665 nm using UV–Vis spectroscopy. After 2 and 60 min at pH 2, the average removal efficiencies were 98.52% and 99.91%. Under the same reaction conditions, degradation efficiency was very poor above pH 4. O₃ treatment was highly effective at pH 2 and 12, with 99.03% and 99.99% elimination efficiency, respectively. Calcium ferrate and ozone synergistically degraded 99.7% in 30 s, promising fast and effective wastewater treatment. Thus, the hybrid system outperformed single treatments in removal percentage and reaction time, giving it an alternate remediation method.

纺织和造纸工业生产有害染料，特别是亚甲基蓝（MB），对环境有害。传统的废水处理工艺难以降解工业有色染料。需要替代废水处理技术来分解这些有色染料。本研究考察了高铁酸钙（CaFeO4）、臭氧（O3）及其杂化体系如何降解亚甲基蓝（MB）。批量试验考察了在给定温度和氧化剂浓度下，不同pH值和反应时间条件下MB的降解情况。通过紫外-可见光谱法测定665 nm处的MB吸光度，考察了CaFeO4的降解效率和性能。在pH 2条件下处理2 min和60 min，平均去除率分别为98.52%和99.91%。在相同的反应条件下，pH大于4时，降解效率很差。O3处理在pH为2和12时效果最好，去除率分别为99.03%和99.99%。高铁酸钙与臭氧在30 s内协同降解99.7%，具有快速有效的废水处理前景。因此，混合系统在去除率和反应时间方面优于单一处理，为其提供了一种替代修复方法。

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引用次数: 0

DOC-governed metal solubility and mobility in river sediments: Integrating machine learning, causal pathways, and geochemical simulations doc控制的河流沉积物中的金属溶解度和流动性：整合机器学习，因果途径和地球化学模拟

IF 4.1 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2026-01-29 DOI: 10.1016/j.pce.2026.104322

Fahmida Sultana , Zia Ahmed , Fei Zhang , Tasrina R. Choudhury , M. Safiur Rahman

This study explores the complex interactions between sediment texture, dissolved organic carbon (DOC) levels, and water chemistry in influencing the solubility and mobility of toxic metals (Cd, Ni, Zn, Cu, Cr, Pb) in river sediments. A multi-tiered approach integrating machine learning, Structural Equation Modeling (SEM), and geochemical simulations was employed to understand metal behavior in the Meghna River, Bangladesh. Redundancy Analysis (RDA) revealed that sediment texture and DOC fractions are the primary drivers of metal mobility, with clay content contributing the most to variation in metal concentrations (Variance Inflation Factor (VIF) values for clay = 3.50). The study employed Random Forest (RF) and XGBoost models to predict metal concentrations, achieving exceptional predictive accuracy with Area Under the Curve (AUC) values of 1.000 for Ni, Zn, Cr, and Pb, and 0.964 for Cd. Regression models demonstrated strong performance with R² values of 0.963 for Pb, 0.938 for Ni, and 0.928 for Zn, highlighting the robustness of DOC and sediment texture in explaining metal variability. SEM analysis indicated that pH mediates the DOC–metal relationship, with standardized path coefficients for DOC retention and metal mobility being −0.475 and 0.96 for Zn, respectively. The GIS-based Metal Mobility Index (MMI) and Soil Mobility Index (SMI) predicted high-risk zones for metal mobility, with an AUC of 0.91, effectively distinguishing between high and low mobility regions. These findings provide critical insights into metal transport dynamics and offer valuable tools for river sediment management and metal contamination risk assessment.

本研究探讨了沉积物结构、溶解有机碳（DOC）水平和水化学之间的复杂相互作用对河流沉积物中有毒金属（Cd、Ni、Zn、Cu、Cr、Pb）溶解度和迁移率的影响。采用结合机器学习、结构方程建模（SEM）和地球化学模拟的多层方法来了解孟加拉国梅克纳河中的金属行为。冗余分析（RDA）表明，沉积物结构和DOC组分是金属迁移的主要驱动因素，粘土含量对金属浓度变化的贡献最大（粘土的方差膨胀因子（VIF）值= 3.50）。研究采用随机森林（Random Forest， RF）和XGBoost模型预测金属浓度，Ni、Zn、Cr和Pb的曲线下面积（Area Under The Curve， AUC）值为1.000，Cd的AUC值为0.964，预测精度极高。回归模型显示，Pb的R2值为0.963，Ni的R2值为0.938，Zn的R2值为0.928，这突出了DOC和沉积物质地在解释金属变异方面的鲁棒性。SEM分析表明pH调节了DOC与金属的关系，Zn的DOC保留率和金属迁移率的标准化通径系数分别为- 0.475和0.96。基于gis的金属流动性指数（MMI）和土壤流动性指数（SMI）预测了土壤金属流动性的高风险区，AUC为0.91，有效区分了土壤金属流动性的高、低风险区。这些发现为金属运移动力学提供了重要的见解，并为河流沉积物管理和金属污染风险评估提供了有价值的工具。

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引用次数: 0

Experimental study and analysis on optimized mix ratio of mullite powder mortar and mechanical properties of foam concrete 莫来石粉砂浆优化配合比及泡沫混凝土力学性能的试验研究与分析

IF 4.1 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2026-01-29 DOI: 10.1016/j.pce.2026.104328

Jingshuang Zhang , Ziyang Chen , Yanqing Wu , Xuhui Xu

To address the strength problem of lightweight wall materials, mullite powder foam concrete was prepared. The optimal ratio of mullite mortar was obtained through three-factor three-level orthogonal tests of fly ash, mullite powder and glass fiber, using range and variance analysis based on strength, water absorption rate and softening coefficient. Tests were performed to evaluate the compressive strength, tensile strength, water absorption rate, and softening coefficient of mullite foam concrete under varying foaming agent dosages and distinct foaming conditions, guided by this ratio. The optimized mullite mortar demonstrated a compressive strength of 29.73 MPa, along with 6 % water absorption and a 0.92 softening coefficient. Constrained foaming exhibited better performance compared to free foaming methods. At a 20 % foaming agent content, the mullite-based foam concrete exhibited optimal comprehensive performance, achieving compressive strength of 18.09 MPa, split tensile strength of 3.65 MPa, water absorption of 12.09 %, and a softening coefficient of 0.82. Microscopic examination reveals that within mullite powder foam concrete, hydration products including C–S–H and AFt interact with mullite particles and aggregates to create a compact network configuration, which effectively improves the material's mechanical characteristics while ensuring compliance with engineering strength specifications.

为解决轻质墙体材料的强度问题，研制了莫来石粉泡沫混凝土。通过粉煤灰、莫来石粉和玻璃纤维三因素三水平正交试验，基于强度、吸水率和软化系数进行极差和方差分析，得出莫来石砂浆的最佳配比。以该配比为指导，对不同发泡剂用量和不同发泡条件下莫来石泡沫混凝土的抗压强度、抗拉强度、吸水率和软化系数进行了试验研究。优化后的莫来石砂浆抗压强度为29.73 MPa，吸水率为6%，软化系数为0.92。约束发泡比自由发泡表现出更好的性能。当发泡剂含量为20%时，莫来石基泡沫混凝土的综合性能最佳，抗压强度为18.09 MPa，劈裂抗拉强度为3.65 MPa，吸水率为12.09%，软化系数为0.82。微观检查表明，在莫来石泡沫混凝土中，水化产物包括C-S-H和AFt与莫来石颗粒和骨料相互作用，形成紧凑的网络结构，有效改善了材料的力学特性，同时确保符合工程强度规范。

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引用次数: 0

Microplastics in the environment: Sources, impacts, degradation strategies and energy recovery options-A rigorous review 环境中的微塑料：来源，影响，降解策略和能源回收方案-严格审查

IF 4.1 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2026-01-28 DOI: 10.1016/j.pce.2026.104323

J. Aravind Kumar , A. Annam Renita , S. Sathish , D. Prabu , Ashwin Jacob , Ahmad Hosseini-Bandegharaei , M. Kavisri , Meivelu Moovendhan

Microplastics, pervasive in the environment, have emanated as a pressing environmental implication due to their widespread dispersal and potential adverse effects on ecosystems and human health. This comprehensive review succumbs an in-depth scrutiny of microplastics, encompassing their sources, distributions, and environmental impacts. Sources of microplastics encompass a wide array of industrial and household activities, ranging from daily care products to the food industry and common household items. In addition, algae play a key part in the degrading processes that microplastics undergo, with macro- and microalgae being major players in remediation initiatives. To understand the flowing ecological effects, the complex relationships that microplastics have with marine organisms, especially those that are part of the marine food web are examined. Furthermore, cutting-edge process technologies like anaerobic digestion, hydrothermal liquefaction (HTL), and thermal hydrolysis process (THP) present viable paths for managing microplastics, with a focus on energy recovery via co-digestion procedures. The review additionally presents potential directives for forthcoming research, highlighting the necessity of continuing efforts to maximize cleanup tactics, lessen environmental effects, and protect ecosystems around the world from the increasingly dangerous threat of microplastic pollution. Biodegradation strategies for disintegrating such microplastic were also highlighted and explored at the outset.

微塑料在环境中无处不在，由于其广泛扩散和对生态系统和人类健康的潜在不利影响，已成为一个紧迫的环境问题。这一全面的审查屈服于微塑料的深入审查，包括它们的来源，分布和环境影响。微塑料的来源包括一系列广泛的工业和家庭活动，从日常护理产品到食品工业和普通家庭用品。此外，藻类在微塑料的降解过程中起着关键作用，宏藻和微藻是修复行动的主要参与者。为了理解流动的生态效应，研究了微塑料与海洋生物的复杂关系，特别是那些作为海洋食物网一部分的关系。此外，厌氧消化、水热液化（HTL）和热水解过程（THP）等尖端工艺技术为管理微塑料提供了可行的途径，重点是通过共消化过程回收能量。这篇综述还为未来的研究提出了潜在的指示，强调了继续努力最大限度地提高清理策略、减轻环境影响、保护世界各地的生态系统免受微塑料污染日益危险的威胁的必要性。一开始就强调并探讨了分解这种微塑料的生物降解策略。

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引用次数: 0

Remote sensing applications for assessing climate change impacts on deciduous forests—A systematic review 气候变化对阔叶林影响的遥感评估——系统综述

IF 4.1 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2026-01-28 DOI: 10.1016/j.pce.2026.104321

Sude Gül Yel , Hasan Burak Özmen , Siğnem Öney Birol , Esra Tunç Görmüş , Gordana Kaplan

Deciduous forests play a vital role in global carbon sequestration, hydrological regulation, and biodiversity conservation, yet they are increasingly vulnerable to the adverse effects of climate change. This review synthesizes recent advances in remote sensing applications for assessing climate-induced changes in phenology, productivity, and resilience of deciduous forests. A systematic literature analysis was conducted using Web of Science, incorporating 70 peer-reviewed studies that employed satellite-based datasets such as MODIS, Landsat, and Sentinel-2. The review identifies key remote sensing metrics, including NDVI, EVI, LAI, and SIF, which are used to monitor phenological shifts, drought impacts, and changes in forest productivity. Analytical approaches such as time series analysis, regression models, and machine learning (e.g., RF, LMEM) were evaluated for their effectiveness in modeling forest-climate interactions. Results highlight distinct regional patterns in phenological responses, sensor preferences across climate zones, and a growing reliance on multi-sensor data fusion to enhance monitoring precision. Despite advancements in remote sensing technologies, critical research gaps persist, especially regarding the biological interpretation of spectral indices and the assessment of forest resilience mechanisms at finer spatial scales. This review underscores the need for interdisciplinary approaches and advanced remote sensing frameworks to support future forest conservation and climate adaptation strategies.

落叶森林在全球固碳、水文调节和生物多样性保护方面发挥着至关重要的作用，但它们越来越容易受到气候变化的不利影响。本文综述了近年来遥感应用在评估气候引起的落叶森林物候、生产力和恢复力变化方面的最新进展。利用Web of Science进行了系统的文献分析，纳入了70项同行评议的研究，这些研究采用了基于卫星的数据集，如MODIS、Landsat和Sentinel-2。该综述确定了用于监测物候变化、干旱影响和森林生产力变化的关键遥感指标，包括NDVI、EVI、LAI和SIF。对时间序列分析、回归模型和机器学习（如RF、LMEM）等分析方法在模拟森林-气候相互作用方面的有效性进行了评估。结果突出了物候响应的不同区域模式，不同气候带的传感器偏好，以及越来越多地依赖多传感器数据融合来提高监测精度。尽管遥感技术取得了进步，但关键的研究差距仍然存在，特别是在光谱指数的生物学解释和在更精细的空间尺度上评估森林恢复力机制方面。这一综述强调需要跨学科方法和先进的遥感框架来支持未来的森林保护和气候适应战略。

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引用次数: 0

Machine learning for water quality prediction and uncertainty assessment 用于水质预测和不确定性评估的机器学习

IF 4.1 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2026-01-27 DOI: 10.1016/j.pce.2026.104319

Tarekegn Dejen Mengistu , Il-Moon Chung , Sun Woo Chang

Effective water quality monitoring requires predictive models that combine high accuracy, interpretability, and credible uncertainty quantification. Machine learning (ML) techniques have emerged as powerful tools for predicting water quality and quantifying associated uncertainties. Similarly, Bayesian deep learning (BDL) frameworks enable probabilistic predictions that quantify uncertainties. These approaches can capture nonlinear interactions and provide robust predictions in diverse environmental conditions. This study integrated ensemble ML and BDL to assess the complex relationships between physicochemical parameters and the Water Quality Index (WQI). Six supervised ensemble ML algorithms, namely Decision Tree (DT), Random Forest (RF), Extra Trees (ERT), XGBoost, CatBoost, and LightGBM were evaluated using Bayesian optimisation to identify the optimal hyperparameter configurations. DT achieved the highest predictive accuracy with MAE = 0.657 and 0.428, RMSE = 1.181 and 0.747, MAPE = 10.561 and 7.155, R² = 0.960 and 0.987, and nRMSE = 0.065 and 0.042 for the training and test sets, respectively. The DT outperformed more complex ensemble models, and SHapley Additive exPlanations (SHAP)-based eXplainable Artificial Intelligence (XAI) identified the most influential predictors, aligning model predictions with underlying hydrochemical processes. To capture predictive uncertainty, a probabilistic BDL was developed yielding probabilistic outputs and explicit epistemic uncertainty estimates. ROC analysis confirmed strong performance across WQI classes, with AUC scores of up to 0.90 for WQI classes. The probabilistic approach provides actionable insights for adaptive water quality management, enabling targeted monitoring in areas of high uncertainty and supporting transparent, evidence-based decision-making. These results underscore the value of integrating ML, and Bayesian optimisation to advance robust and adaptive water quality assessment. The proposed workflow provides a scalable framework to enhance monitoring, optimize resources, and advance sustainable water management aligned with the SDGs.

有效的水质监测需要结合高精度、可解释性和可信的不确定性量化的预测模型。机器学习（ML）技术已经成为预测水质和量化相关不确定性的强大工具。类似地，贝叶斯深度学习（BDL）框架实现了量化不确定性的概率预测。这些方法可以捕捉非线性相互作用，并在不同的环境条件下提供可靠的预测。本研究结合集合ML和BDL来评估理化参数与水质指数（WQI）之间的复杂关系。使用贝叶斯优化评估六种监督集成ML算法，即决策树（DT），随机森林（RF），额外树（ERT）， XGBoost， CatBoost和LightGBM，以确定最佳超参数配置。DT预测准确率最高，训练集和测试集的MAE分别为0.657和0.428，RMSE分别为1.181和0.747，MAPE分别为10.561和7.155，R2分别为0.960和0.987，nRMSE分别为0.065和0.042。DT优于更复杂的集成模型，基于SHapley加性解释（SHAP）的可解释人工智能（XAI）确定了最具影响力的预测因子，将模型预测与潜在的水化学过程结合起来。为了捕获预测不确定性，开发了一个概率BDL，产生概率输出和明确的认知不确定性估计。ROC分析证实了WQI类别的良好表现，WQI类别的AUC得分高达0.90。概率方法为适应性水质管理提供了可行的见解，可以在高度不确定的领域进行有针对性的监测，并支持透明的、基于证据的决策。这些结果强调了整合ML和贝叶斯优化来推进鲁棒性和适应性水质评估的价值。拟议的工作流程提供了一个可扩展的框架，以加强监测，优化资源，并推进与可持续发展目标一致的可持续水资源管理。

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引用次数: 0

A novel hydrogeophysical framework for developing conceptual site models and simulating groundwater flow conditions in heterogeneous aquifer systems 一个新的水文地球物理框架，用于开发概念场地模型和模拟非均质含水层系统中的地下水流动条件

IF 4.1 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2026-01-27 DOI: 10.1016/j.pce.2026.104326

Musaab A.A. Mohammed , Norbert P. Szabó , Péter Szűcs

Numerical simulation of groundwater flow is crucial for understanding and managing aquifer systems, especially in heterogeneous environments. One of the key challenges in groundwater flow simulation is the limited availability of detailed geological and hydrogeological data, which is essential for accurately characterizing aquifer properties and flow dynamics. This study presents a novel approach to simulate the flow conditions in data-scare regions in which the primary inputs are obtained from the interpretation of the geophysical well-logging data. The conceptual model is established through the novel application of the Most Frequent Value-assisted Cluster Analysis (MFV-CA) and Csókás method, complemented by available water level data. MFV-CA is a robust clustering technique that uses Stiener Distance (Weighted Euclidean Distance) for rock differentiation mitigating the drawbacks of the standard k-means cluster analysis (CA) being sensitive to outliers in the dataset. On the other hand, the Csókás method is introduced as a modified version of the Kozeny-Carman equation to provide a continuous estimation of hydraulic conductivity. Accordingly, a 3D geological model is constructed, discretized, and characterized. The conceptual model is translated into a numerical model using the MODFLOW-USG framework employing a control volume finite difference unstructured grid that allows the representation of the system heterogeneity. The results showed an acceptable agreement between the observed and the calibrated hydraulic head. The study demonstrated the effectiveness of using geophysical data as an input for groundwater flow models that enhance data coverage and resolution. The proposed approach provides a practical decision-support tool for improving groundwater management and planning in data-scarce and geologically complex settings.

地下水流动的数值模拟对于理解和管理含水层系统至关重要，特别是在非均质环境中。地下水流动模拟的关键挑战之一是详细的地质和水文地质数据的可用性有限，而这些数据对于准确表征含水层性质和流动动力学至关重要。该研究提出了一种新的方法来模拟数据稀缺地区的流动条件，其中主要输入来自地球物理测井数据的解释。概念模型是通过最频繁值辅助聚类分析（MFV-CA）和Csókás方法的新应用建立的，并辅以可用的水位数据。MFV-CA是一种鲁棒的聚类技术，它使用斯蒂纳距离（加权欧氏距离）来区分岩石，减轻了标准k-均值聚类分析（CA）对数据集中的异常值敏感的缺点。另一方面，Csókás方法作为Kozeny-Carman方程的修改版本被引入，以提供水力导电性的连续估计。据此，构建三维地质模型，对其进行离散化和表征。使用MODFLOW-USG框架将概念模型转换为数值模型，该框架采用控制体积有限差分非结构化网格，允许表示系统异质性。结果表明，在观测和校准水头之间的一致性是可以接受的。该研究表明，将地球物理数据作为地下水流动模型的输入是有效的，可以提高数据的覆盖范围和分辨率。提出的方法为改善数据稀缺和地质复杂环境下的地下水管理和规划提供了一种实用的决策支持工具。

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引用次数: 0