Physics and Chemistry of the Earth最新文献

{"title":"Forecasting the bottom hole closed pressure using time series analysis paradigms. A case study of the Mishrif reservoir at West Qurna oilfield, southern Iraq","authors":"Mustafa A. Abdulhasan,&nbsp;Amna M. Handhal,&nbsp;Alaa M. Al-Abadi","doi":"10.1016/j.pce.2026.104283","DOIUrl":"10.1016/j.pce.2026.104283","url":null,"abstract":"<div><div>This study seeks to establish a reliable forecasting framework for Bottom-Hole Close Pressure (BHCP) in the Mishrif Formation of the West Qurna-1 oilfield, southern Iraq, through a comparative analysis of six time-series and machine learning models evaluated under realistic operational conditions. Monthly BHCP, production, and injection data spanning a 12-year period were analyzed using a combination of classical time-series models-including Autoregressive Integrated Moving Average (ARIMA), Seasonal ARIMA (SARIMA), and Seasonal ARIMA with Exogenous Variables (SARIMAX)–alongside advanced machine learning techniques, specifically Long Short-Term Memory (LSTM) neural networks and Extreme Gradient Boosting (XGBoost). Model performance was assessed using root mean square error (RMSE) and mean absolute error (MAE). The LSTM achieved the best predictive performance, followed closely by Holt–Winters and SARIMA. Although SARIMAX produced slightly higher errors, it offered superior interpretability by explicitly modeling BHCP as a function of injection and production rates. In contrast, XGBoost overfitted severely, producing excellent training accuracy but poor generalization. Using the best-performing models (LSTM and SARIMAX), BHCP forecasts were generated under three different operational conditions. Scenario forecasting from 2022 to 2030 showed that increasing production by 40–80 % leads to a progressive pressure decline, whereas increasing injection by 40–80 % results in measurable pressure recovery. Under constant operational conditions, SARIMAX predicts a stable BHCP trajectory fluctuating around 2700–2800 psi. These findings demonstrate that reservoir pressure in the Mishrif Formation is highly sensitive to the production–injection balance and underscore the effectiveness of SARIMAX as a robust forecasting tool for reservoir-management decision-making.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104283"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977765","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":"A comparative study of developed rainfall intensity-duration-frequency curves for Ganjam District, Odisha, India","authors":"Padminee Samal ,&nbsp;Sandeep Samantaray ,&nbsp;Prakash C. Swain ,&nbsp;Hashem Shafik Shakir ,&nbsp;Zaher Mundher Yaseen","doi":"10.1016/j.pce.2026.104284","DOIUrl":"10.1016/j.pce.2026.104284","url":null,"abstract":"<div><div>Inadequate availability of hydrological data, such as rainfall and runoff patterns over regions like Ganjam district in Odisha state, India, makes it challenging for hydrologists to effectively plan, organize, and design water resources projects. Hence, there is need for the development of rainfall Intensity-Duration-Frequency (IDF) curves using specific empirical methods. To develop an empirical relationship for Ganjam, in the state of Odisha, daily rainfall data were collected from 22 raingauge stations for the period from 1995 to 2018. The intensity of rainfall values was designed for shorter durations for various return periods, including 2 years, 5 years, 10 years, 20 years, 50 years, 100 years, and 200 years. The representative IDF curves developed using the least squares method were compared with the IDF curves developed using Kothyari and Garde's method. The findings showed that, the IDF generated on a regional constant basis by Kothyari and Garde's equation underestimates the rainfall intensities for 2-year and 5-year return periods. An application of the findings was made to predict the runoff for a given set of rainfall derived from the IDF curves using SCS-Curve Number method. The graphs were developed using the IDF curves applicable for a region under consideration and using SCS-CN method and known as the Runoff Depth-Rainfall Frequency-Rainfall Duration curves. Hence, in areas, where data availability is limited, the created IDF relationship can be utilized to forecast rainfall and runoff depths for the purpose of planning, design and operation of various water resources projects.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104284"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977762","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":"Assessing the impact of microplastic polymer wastes on environmental fate and human health risks","authors":"Maria Joseph Angelaa Lincy ,&nbsp;Senthil Kumar Babu ,&nbsp;Saghya Infant Shofia ,&nbsp;Senthilkumar Nangan ,&nbsp;Balamurugan Paneerselvam","doi":"10.1016/j.pce.2025.104246","DOIUrl":"10.1016/j.pce.2025.104246","url":null,"abstract":"<div><div>As plastics keep getting manufactured and wasted in enormous amounts, microplastic pollution is becoming a serious environmental and human health issue. This review consolidates new developments concerning the sources, distribution, detection, and physiological effects of microplastics. Microplastics are derived from the breakdown of large plastic litter and from direct industrial sources like cosmetics, textiles, and tire tread particles, infiltrating aquatic, atmospheric, and terrestrial environments. Recent research illustrates that microplastics have the ability to pass through biological barriers, accumulate in various human organs, and induce oxidative stress, release of inflammatory cytokines, mitochondrial impairment, and changes in lipid metabolism offering novel evidence for physiological causation of toxicity. Parameters controlling environmental transport are particle size, form, density, and ecological factors like wind patterns, ocean currents, and precipitation. Human exposure is mainly via ingestion, inhalation, and dermal uptake, with recent biomonitoring verifying microplastics in blood, placenta, breast milk, and lung tissues. Analytical advancements such as Fourier Transform Infrared (FTIR), Raman, and pyrolysis–GC/MS methods have enhanced detection sensitivity but continue to pose challenges with respect to contamination control, nanoplastic quantification, and standardization of methods. Recent studies also investigate synergistic toxicity between microplastics and co-contaminants (e.g., heavy metals, persistent organic pollutants) and examine potential transgenerational and microbiome-mediated effects. By synthesizing these novel findings, this review presents an updated understanding of microplastic contamination and its mechanistic connections to human physiology, with the goal of informing future research direction and evidence-based environmental policy.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104246"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840039","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":"Soil-structure interaction and uplift bearing capacity: A study on low-header CEP single pile foundations","authors":"Muhammad Rizwan ,&nbsp;Sobia Naseem ,&nbsp;Muhammad Akhtar Tarar","doi":"10.1016/j.pce.2025.104255","DOIUrl":"10.1016/j.pce.2025.104255","url":null,"abstract":"<div><div>Low-header Concrete Expanded-Plate (CEP) single pile foundations play a critical role in supporting renewable energy structures, transmission line supports, and seismic-resilient infrastructure. Their unique geometry and interaction with surrounding soil make uplift resistance a key design consideration. Despite growing application, research on their uplift behavior remains fragmented, with studies often focusing on isolated mechanisms, simplified analytical models, or site-specific experiments. This critical and state-of-the-art review synthesizes current knowledge on soil–structure interaction (SSI) and uplift bearing capacity of low-header CEP piles, integrating experimental findings, numerical simulations, and analytical models across diverse soil conditions. The review evaluates key mechanisms governing uplift resistance, including plate–soil interlocking, shaft shear transfer, and nonlinear soil behavior, while highlighting inconsistencies, methodological limitations, and gaps in existing research. Furthermore, it examines field validation studies, centrifuge testing, and modern numerical approaches, identifying opportunities for reliability-based design, machine-learning-assisted prediction, and adaptive monitoring of pile performance. By consolidating dispersed evidence and providing a structured evaluation of SSI effects, this review offers guidance for improved design strategies and outlines directions for future research to enhance the reliability and efficiency of CEP pile foundations under uplift-dominated loading.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104255"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840033","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":"BAMPP: A novel Bayesian network enhanced by average marginal posterior probabilities to identify critical ground truth meteorological stations for drought monitoring","authors":"Rizwan Niaz ,&nbsp;Saman Munir ,&nbsp;Muhammad Ahmad Raza ,&nbsp;Rifat Tur ,&nbsp;Sadegh Partani ,&nbsp;Ali Danandeh Mehr","doi":"10.1016/j.pce.2025.104215","DOIUrl":"10.1016/j.pce.2025.104215","url":null,"abstract":"<div><div>This study introduces a new approach for identifying critical meteorological stations essential for analyzing spatiotemporal dynamics of drought events at regional scale. We propose a Bayesian network enhanced by Average Marginal Posterior Probabilities (AMPP) to evaluate stations based on frequency, severity, and persistence of Standardized Precipitation Index (SPI) at multiple timescales (SPI-3, SPI-6, and SPI-12). The method is demonstrated across the province of Ankara, Türkiye, effectively capturing the probabilistic relationships and interdependencies governing drought propagation among stations. Our analysis revealed distinct spatiotemporal patterns across the region at all time scales. For short-term droughts (SPI-3), critical station identity varied seasonally, indicating localized dynamics; for instance, Esenboga was key station in February, March, July, October and December, while Beypazari was influential in the other months. In contrast, for medium- and long-term droughts (SPI-6, SPI-12), Beypazari was the most critical station across all months, establishing it as the representative station for long-term drought monitoring in the region. This method provides a robust, probabilistic tool for optimizing drought monitoring networks and enhancing regional water resource management.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104215"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840099","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":"Integrating Conventional and machine learning approaches with seismic inversion for optimized porosity estimation in heterogeneous siliciclastic rocks","authors":"Muyyassar Hussain ,&nbsp;Urooj Shakir ,&nbsp;Zohaib Naseer ,&nbsp;Muhammad Raiees Amjad ,&nbsp;Farooq Arshad ,&nbsp;Muhammad Kamal ,&nbsp;Ahmed E. Radwan","doi":"10.1016/j.pce.2025.104248","DOIUrl":"10.1016/j.pce.2025.104248","url":null,"abstract":"<div><div>Heterogeneous siliciclastic rocks pose significant challenges in reservoir characterization, where such heterogeneity is often not sufficiently captured by conventional petrophysical techniques alone. In this work, an innovative integrative framework for optimizing porosity estimation in complex depositional conditions is presented, combining sophisticated machine learning (ML) methods with traditional seismic inversion, considering the extreme heterogeneity of the Lower Goru Formation (LGF), Tajjal gas field, Gambat area, Lower Indus Basin (LIB), Pakistan. Specifically, a probabilistic neural network (PNN) is employed as a sophisticated deep-learning technique and coupled with well logs and 3D seismic datasets to develop an optimized predictive model for porosity estimation within the C-Interval of the LGF. A three-dimensional variation of porosity, calculated using a seismic inverted PNN map, ranges from -10 % to 13%. The petrophysical analysis began with a conventional approach based on empirical formulas, and the computed properties were then calibrated and cross-matched with log analysis performed using machine learning algorithms. Along with a limited 3D seismic dataset, three wells were used for petrophysical evaluation with the conventional technique, whereas in the supervised ML approach, two wells were used for training while one was kept as a test well. Among the models applied, the Extra Trees Regressor (ETR) provided low Vshl values and high effective porosity (PHIE), achieving over 99% R² with the lowest Mean Squared Error (MSE) score. When compared to conventional interpretation at the test well, the Random Forest Regressor (RFR) provided water saturation (Sw) estimates with approximately 100% accuracy, demonstrating a relatively lower deviation than traditional petrophysical methods. Thus, the porosity values obtained from the integrated approach show strong agreement, reinforcing confidence in their reliability for future exploration endeavors in heterogeneous siliciclastic formations. Consequently, the results of this research can be applied to similar geological settings, particularly those characterized by alternating shale–sandstone layers enriched with hydrocarbons and exhibiting thickness variations with lateral extents.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104248"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840102","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 source apportionment, risk assessment, and probabilistic modeling of potentially toxic elements in soils from an undeveloped metallogenic region, northwest China","authors":"Qiong Han ,&nbsp;Wenfeng Wang ,&nbsp;Tongyang Zhao ,&nbsp;Liuyuan Jin ,&nbsp;Yangshuang Wang ,&nbsp;Shiming Yang ,&nbsp;Yunhui Zhang","doi":"10.1016/j.pce.2026.104288","DOIUrl":"10.1016/j.pce.2026.104288","url":null,"abstract":"<div><div>While risk zones of potentially toxic elements (PTEs) are generally associated with intensive anthropogenic disturbances, undeveloped metallogenic regions (UMRs) feature naturally high PTE concentrations that have received limited scientific attention. To fill this gap, this study investigated the sources and quantified the contributions of PTEs in the soils of a UMR in Northwest China, while assessing their associated ecological-health risks. A total of 480 soil samples were collected for analysis. A multi-method framework combining geochemical baseline values (GBVs), Positive Matrix Factorization (PMF), integrated pollution indices, and probabilistic health risk modeling was established. The results revealed that Mercury (Hg) exhibited the highest exceedance rate (13.33 %) compared with other PTEs. PTEs were predominantly derived from natural sources: soil parent material (61.91 %), Pb enrichment (22.98 %), Cu mineralization (10.50 %), and hydrothermal processes (4.61 %), suggesting a primarily geogenic origin. Ecological risk assessment identified Hg as the main contributor to ecological risk. Overall, soil quality in the study area ranged from unpolluted to slightly polluted, with localized high-risk zones mainly distributed in the eastern region. Health risk assessment showed that chromium (Cr) and cobalt (Co) were the major contributors to non-carcinogenic risk, while Cr dominated the carcinogenic risk. Notably, 49.32 % of the samples posed unacceptable non-carcinogenic risks to children, 10.01 % and 0.90 % posed unacceptable carcinogenic risks to children and adults, respectively. These results highlighted that natural metallogenic processes alone could generate unacceptable risks to ecological systems and vulnerable populations. Based on these findings, long-term monitoring of Cr, Co, and Hg in soils near PTE-enriched areas is recommended to mitigate potential ecological and health threats. The study results can provide a scientific basis for the management of soil PTEs in high-background metallogenic regions worldwide.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104288"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977767","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":"Reconstructing seismic landslide spatial records in data-scarce Indian Himalayas: a polygon-based inventory and susceptibility assessment for the 1999 Chamoli earthquake","authors":"Shivani Joshi ,&nbsp;Akshat Vashistha ,&nbsp;Srikrishnan Siva Subramanian ,&nbsp;Ali P. Yunus","doi":"10.1016/j.pce.2025.104243","DOIUrl":"10.1016/j.pce.2025.104243","url":null,"abstract":"<div><div>The seismically active Himalayas are highly prone to secondary hazards such as earthquake-induced landslides (EIL), which pose serious risks to local populations and reshape mountainous terrains. However, spatial data on historic EIL events in India remain limited. This study presents the first polygon-based landslide inventory for the 1999 M_w 6.6 Chamoli earthquake in Uttarakhand, improving significantly upon earlier point-based datasets. A total of 73 landslides were identified and mapped across the Chamoli and Rudraprayag districts, with validations through field surveys and archival reports. The study employed the frequency ratio method for landslide susceptibility mapping and evaluated the influence of topographic, geological, land-use, and tectonic factors. Despite the 25-year gap since the event, the landslide inventory aligns well with global trends in landslide size and frequency, confirming its completeness. These findings highlight the significance of historical remote sensing for reconstructing past events, supporting seismic hazard assessment, landscape evolution studies, and disaster risk reduction.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104243"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840038","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":"Experiments and simulations of gas slippage effect on gas permeability and gas production in methane-hydrate-bearing montmorillonite sediments","authors":"Qingkai Gu ,&nbsp;Zhaoran Wu ,&nbsp;Guijing Li ,&nbsp;Jianhua Geng","doi":"10.1016/j.pce.2026.104309","DOIUrl":"10.1016/j.pce.2026.104309","url":null,"abstract":"<div><div>Gas flow in deep-sea natural gas hydrate reservoirs is significantly influenced by gas slippage, particularly in montmorillonite-rich clay sediments characterized by high porosity (&gt;0.4), low permeability (&lt;2.3 mD), and micro-nano scale pore spaces. Under these conditions, clay expansion markedly enhances the gas slippage effect. Therefore, this study selects montmorillonite sediments as the representative research medium. Understanding the gas slippage effect on permeability and production rate is crucial for gas hydrate exploitation. By fitting experimental data and eliminating the gas slippage effect on permeability, a relationship was derived between gas permeability and decomposed water content, effective stress, gas slippage effect, and porosity. A gas production model for methane-hydrate-bearing montmorillonite sediments was developed accounting for gas slippage effect. Numerical simulation results indicate that the change in gas permeability is not a linear decline during the depressurization decomposition of methane hydrates. Instead, there are periods where gas permeability increases or the rate of decline slows. The contributions of gas slippage compensation, effective stress, decomposed water, and the reduction in hydrate saturation to the changes in gas permeability were analyzed in details. The average gas production rates for each stage shows that gas slippage compensation enhances permeability and increases gas production.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104309"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023085","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 discrepancy of stable isotopes in river water and groundwater, eastern Qaidam Basin: Controlling factors and implications for hydrological cycle","authors":"Nuan Yang ,&nbsp;Xinming Song ,&nbsp;Liang Guo ,&nbsp;Shouchuan Zhang ,&nbsp;Guangcai Wang","doi":"10.1016/j.pce.2025.104251","DOIUrl":"10.1016/j.pce.2025.104251","url":null,"abstract":"<div><div>Stable isotope-based hydrological cycle is the most commonly employed approach for water resource management. Qaidam Basin is situated near the summer monsoon boundary and exhibits particular hydrological sensitivity to climate change. Investigating the spatial variations and controlling factors of hydrogen and oxygen isotopes in water bodies in the eastern margin of the Qaidam Basin is conducive to elucidate hydrological processes and response to climate change. Focusing on the Xiangride and Delingha areas, the study combined the stable isotopic analysis (δD, δ¹⁸O, d-excess) in river water and groundwater and water vapor transport trajectories modeling (HYSPLIT model) to identify water sources, river water-groundwater interaction, and moisture sources and transport trajectories. The Xiangride and Delingha areas exist both commonalities and distinctions in the hydrological cycle processes. The relationships among δD, δ¹⁸O, and d-excess suggest that river water and groundwater in two areas derive from atmospheric precipitation generated in the surrounding mountainous areas and experience semblable evaporation intensities. River water-groundwater interaction follow a consistent pattern: river water infiltrates and recharges groundwater in the piedmont zone, followed by groundwater discharges into river water in the fine-soil plain. The combination of d-excess analysis and HYSPLIT modeling reveals that the moisture sources generated precipitation in two regions are controlled by the Westerlies, while the Delingha area is further influenced by local recycled moisture from the plain area. The study results provide a critical scientific basis for managing regional river water and groundwater resources or even entire Qaidam Basin.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"142 ","pages":"Article 104251"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884576","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}