Physics and Chemistry of the Earth最新文献_第5页

Assessing the impact of land surface temperature on off-seasonal precipitation in Surat city at the regional level

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2024-12-25 DOI: 10.1016/j.pce.2024.103844

Rachana Patil, Meenal Surawar

In the context of advancing urbanization, cities grapple with escalating challenges such as heightened and unpredictable occurrences of heatwaves and increased precipitation, resulting in recurrent issues like urban heat islands, waterlogging, water pollution, and floods. Particularly in densely populated countries like India, this has become a pressing concern due to a surge in mortality and morbidity rates linked to the amplified frequency of heat and off-season precipitation events. Given that the impacts of rising temperatures and precipitation exhibit a regional character, a comprehensive analysis at the urban scale is impractical. Consequently, this research focuses on a 75 km buffer surrounding Surat city. The study delves into the spatial patterns and influences of land surface temperature, wind speed, surface pressure, and the Normalized Difference Vegetative Index on off season precipitation across the decades from 1991 to 2021, considering both summer and winter seasons to capture the unpredictable nature of the events. Additionally, the research examines correlations among these parameters and delineation of vulnerable areas to heightened off-season precipitation events. In winter, the effect of LST on precipitation is localized, resulting in a positive correlation. In contrast, during summer, the influence of LST on precipitation is not localized, leading to a negative correlation. These findings provide valuable insights for planners, enabling the formulation of regionally tailored policies that address vulnerabilities beyond urban boundaries.

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引用次数: 0

Modelling of snow cover area in relation with climatic variability over the Sind basin of Kashmir Himalayas (2002–2022)

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2024-12-22 DOI: 10.1016/j.pce.2024.103843

Suhail Ahmad Dar , Md. Omar Sarif

The Snow Cover Area (SCA) of the Kashmir Himalayas is vital for environmental, hydrological, and socio-economic stability, influencing water management, agriculture, hydroelectric power, biodiversity, and tourism. This study evaluates the monthly, seasonal, and annual SCA of the Sind basin (2002–2022) using MODIS Terra (MOD10A2) data and NASA POWER PROJECT climate data, employing Mann-Kendall Trend Analysis to examine climatic sensitivities. The average annual SCA is 57.94% (895.75 km²), with a statistically insignificant increase of 0.16% per year. Seasonal SCA averages are 86.12% in winter, 70.72% in spring, 24.15% in summer, and 49.13% in autumn. Significant trends include a winter increase of 0.37% per year and a spring decline of −0.28% per year. Mann-Kendall Trend Analysis results indicated that Annual precipitation shows a statistically significant rise (Sen's slope: +25.61 mm/year). While temperature negatively correlates with annual SCA (≤ −0.77 in all years during 2002-2022), highlighting rising temperatures' detrimental effects on snow retention. A positive correlation of SCA with precipitation indicates (≥0.69 in all years during 2002-2022) that increased precipitation could partially offset snow cover loss. These findings underscore snow cover's sensitivity to climate variability and the critical need for adaptive management strategies. With snow resources essential for water security and ecosystem stability, the study provides valuable insights for regional climate adaptation and policy development, emphasizing the urgency of addressing climate change impacts on the fragile Himalayan environment.

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引用次数: 0

Near-surface seismic refraction anomalies due to underground target models and the application in civil and environmental engineering

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2024-12-21 DOI: 10.1016/j.pce.2024.103845

Joseph Omeiza Alao , Kolawole Muideen Lawal , Bala Bello Muhammad Dewu , Jimoh Raimi

Identifying the precise depth and location of shallow underground utilities in civil and environmental engineering through geophysical means is quite challenging due to near-surface and cultural noise. This study investigates the influence of buried targets on seismic refraction tomography (SRT) measurements at a geophysical experimental site, aiming to evaluate the accuracy and reliability of SRT data. A pre-burial study was performed, resulting in seismic velocity distributions between 200 m/s and 800 m/s for the unsaturated upper layer at depth of 0.0 m–3.0 m, 800 m/s to 1300 m/s for the middle layer at depth of 0.5 m–2.5 m, and 1300 m/s to 2400 m/s for the lower layer at depth of 1.1 m–6.0 m, unveiling a complex stratigraphy that holds valuable insights for engineering endeavours. Parallel seismic layers observed in the pre-study were attributed to a short distance profile (40 m). The pre-burial and post-burial surveys showed consistent layer velocities and thicknesses. The position of larger modelled targets such as drums and clustered plastic buckets indicates significant distortion with depressed/projected displacements, suggesting SRT anomalies, which spatially coincide with the positions of the target buried. However, some of the buried targets have not yet been detected by the SRT technique, which may be due to several factors. The suspected seismic refraction anomalies due to the non-metallic and metallic buried targets tend to generate downward and upward curve nature anomalies, respectively. In addition, the highest displacement resulting from the refraction of seismic waves at various depths appears to be a combination of shear wave and body wave overlapped. Based on the sizes of the buried modelled targets, the study recommends a 0.50 m geophone spacing for investigating very shallow underground utilities in civil and environmental engineering using 2D SRT.

{"title":"Near-surface seismic refraction anomalies due to underground target models and the application in civil and environmental engineering","authors":"Joseph Omeiza Alao , Kolawole Muideen Lawal , Bala Bello Muhammad Dewu , Jimoh Raimi","doi":"10.1016/j.pce.2024.103845","DOIUrl":"10.1016/j.pce.2024.103845","url":null,"abstract":"<div><div>Identifying the precise depth and location of shallow underground utilities in civil and environmental engineering through geophysical means is quite challenging due to near-surface and cultural noise. This study investigates the influence of buried targets on seismic refraction tomography (SRT) measurements at a geophysical experimental site, aiming to evaluate the accuracy and reliability of SRT data. A pre-burial study was performed, resulting in seismic velocity distributions between 200 m/s and 800 m/s for the unsaturated upper layer at depth of 0.0 m–3.0 m, 800 m/s to 1300 m/s for the middle layer at depth of 0.5 m–2.5 m, and 1300 m/s to 2400 m/s for the lower layer at depth of 1.1 m–6.0 m, unveiling a complex stratigraphy that holds valuable insights for engineering endeavours. Parallel seismic layers observed in the pre-study were attributed to a short distance profile (40 m). The pre-burial and post-burial surveys showed consistent layer velocities and thicknesses. The position of larger modelled targets such as drums and clustered plastic buckets indicates significant distortion with depressed/projected displacements, suggesting SRT anomalies, which spatially coincide with the positions of the target buried. However, some of the buried targets have not yet been detected by the SRT technique, which may be due to several factors. The suspected seismic refraction anomalies due to the non-metallic and metallic buried targets tend to generate downward and upward curve nature anomalies, respectively. In addition, the highest displacement resulting from the refraction of seismic waves at various depths appears to be a combination of shear wave and body wave overlapped. Based on the sizes of the buried modelled targets, the study recommends a 0.50 m geophone spacing for investigating very shallow underground utilities in civil and environmental engineering using 2D SRT.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103845"},"PeriodicalIF":3.0,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167853","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}

引用次数: 0

Utilizing machine learning to estimate monthly streamflow in ungauged basins of Thailand's southern basin

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2024-12-20 DOI: 10.1016/j.pce.2024.103840

Nureehan Salaeh , Pakorn Ditthakit , Sirimon Pinthong , Warit Wipulanusat , Uruya Weesakul , Ismail Elkhrachy , Krishna Kumar Yadav , Ghadah Shukri Albakri , Maha Awjan Alreshidi , Nand Lal Kushwaha , Mohamed Elsahabi

Predicting streamflow in ungauged basins is a challenging hydrological issue that requires accurate estimation for effective water resource management. This article aims to evaluate the effectiveness of five different Machine Learning (ML) models (i.e., M5 model tree (M5), Random Forest (RF), Support Vector Regression-polynomial kernel (SVR-poly), Support Vector Regression-radial basis function kernel (SVR-rbf), and Multilayer Perceptron (MLP)) for predicting monthly streamflow in ungauged basins. The proposed models were compared with the method of GR2M's regionalized model parameters. Data was collected from 37 streamflow stations in the southern basin of Thailand. The data utilized included hydrological information like monthly rainfall, potential evapotranspiration, and streamflow, as well as physical watershed characteristics such as basin size, river length, distance from the hydrometric station to the area's centroid, and slope. The study evaluated these methods for two distinct scenarios, namely (a) estimating average monthly streamflow and (b) estimating monthly streamflow. The study was conducted in four phases: selection of input data, hyperparameter tuning, performance comparison of different models, and assessment of the chosen model's suitability for predicting monthly streamflow in ungauged basins. Five-fold cross-validation with four statistical indicators, namely, the Nash-Sutcliffe Efficiency (NSE), Overall Index (OI), Coefficient of Determination (r²), and Combined Index (CI), were utilized for the model's performance comparison. The results showed that the RF model produced the best performance compared to other ML models and outperformed the GR2M's regionalized model parameters in both scenarios, achieving performance indicators with NSE >0.6, OI > 0.6, r² > 0.6, and CI > 2.0.

{"title":"Utilizing machine learning to estimate monthly streamflow in ungauged basins of Thailand's southern basin","authors":"Nureehan Salaeh , Pakorn Ditthakit , Sirimon Pinthong , Warit Wipulanusat , Uruya Weesakul , Ismail Elkhrachy , Krishna Kumar Yadav , Ghadah Shukri Albakri , Maha Awjan Alreshidi , Nand Lal Kushwaha , Mohamed Elsahabi","doi":"10.1016/j.pce.2024.103840","DOIUrl":"10.1016/j.pce.2024.103840","url":null,"abstract":"<div><div>Predicting streamflow in ungauged basins is a challenging hydrological issue that requires accurate estimation for effective water resource management. This article aims to evaluate the effectiveness of five different Machine Learning (ML) models (i.e., M5 model tree (M5), Random Forest (RF), Support Vector Regression-polynomial kernel (SVR-poly), Support Vector Regression-radial basis function kernel (SVR-rbf), and Multilayer Perceptron (MLP)) for predicting monthly streamflow in ungauged basins. The proposed models were compared with the method of GR2M's regionalized model parameters. Data was collected from 37 streamflow stations in the southern basin of Thailand. The data utilized included hydrological information like monthly rainfall, potential evapotranspiration, and streamflow, as well as physical watershed characteristics such as basin size, river length, distance from the hydrometric station to the area's centroid, and slope. The study evaluated these methods for two distinct scenarios, namely (a) estimating average monthly streamflow and (b) estimating monthly streamflow. The study was conducted in four phases: selection of input data, hyperparameter tuning, performance comparison of different models, and assessment of the chosen model's suitability for predicting monthly streamflow in ungauged basins. Five-fold cross-validation with four statistical indicators, namely, the Nash-Sutcliffe Efficiency (NSE), Overall Index (OI), Coefficient of Determination (r<sup>2</sup>), and Combined Index (CI), were utilized for the model's performance comparison. The results showed that the RF model produced the best performance compared to other ML models and outperformed the GR2M's regionalized model parameters in both scenarios, achieving performance indicators with NSE >0.6, OI > 0.6, r<sup>2</sup> > 0.6, and CI > 2.0.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103840"},"PeriodicalIF":3.0,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167321","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}

引用次数: 0

Rainwater infiltration in a vegetated slope subjected to high intensity rainfall

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2024-12-20 DOI: 10.1016/j.pce.2024.103841

Somjai Yubonchit , Avirut Chinkulkijniwat , Taworn Tirametatiparat , Suksun Horpibulsuk

Vegetation is widely accepted as an effective and environmentally friendly approach to mitigating slope failure. However, due to global warming, very high rainfall intensity might become more common. Rainwater infiltration in a sloping ground was studied, using a vegetated slope model subjected to very high rainfall intensity. The model slope was planted with the grass species Axonopus compressus to create two soil layers of uniform thickness, one with plant roots and one without. It was found that, for every simulated rainfall intensity used in this study, water infiltrated vertically in both soil layers. Furthermore, even under simulated rainfall of very high intensity, there existed a final infiltrated water content (

θ_{f}

) whose magnitude could be approximated from the k-function of the soil and the final infiltration capacity. Results from this study would enhance the knowledge of rainwater infiltration in a vegetated slope subjected to high rainfall intensity, and hence the stability assessment of vegetated slopes.

{"title":"Rainwater infiltration in a vegetated slope subjected to high intensity rainfall","authors":"Somjai Yubonchit , Avirut Chinkulkijniwat , Taworn Tirametatiparat , Suksun Horpibulsuk","doi":"10.1016/j.pce.2024.103841","DOIUrl":"10.1016/j.pce.2024.103841","url":null,"abstract":"<div><div>Vegetation is widely accepted as an effective and environmentally friendly approach to mitigating slope failure. However, due to global warming, very high rainfall intensity might become more common. Rainwater infiltration in a sloping ground was studied, using a vegetated slope model subjected to very high rainfall intensity. The model slope was planted with the grass species <em>Axonopus compressus</em> to create two soil layers of uniform thickness, one with plant roots and one without. It was found that, for every simulated rainfall intensity used in this study, water infiltrated vertically in both soil layers. Furthermore, even under simulated rainfall of very high intensity, there existed a final infiltrated water content (<span><math><mrow><msub><mi>θ</mi><mi>f</mi></msub></mrow></math></span>) whose magnitude could be approximated from the k-function of the soil and the final infiltration capacity. Results from this study would enhance the knowledge of rainwater infiltration in a vegetated slope subjected to high rainfall intensity, and hence the stability assessment of vegetated slopes.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103841"},"PeriodicalIF":3.0,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167852","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}

引用次数: 0

Integrated reservoir characterization and simulation approach to enhance production of tight sandstone gas reservoir, Sulige gas field, Ordos Basin, China

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2024-12-20 DOI: 10.1016/j.pce.2024.103846

Sayed Muhammad Iqbal , Dawei Hu , Javid Hussain , Nafees Ali , Wakeel Hussain , Altaf Hussain , Edwin E. Nyakilla

The tight gas reservoir is a significant unconventional hydrocarbon resource of energy worldwide. However, the complex nature and heterogeneity make it challenging during exploration and production. Moreover, constructing and updating 3D reservoir model is vital for reservoir monitoring and surveillance. Such reservoirs require precise simulation strategies to accurately assess the hydrocarbon potential and formulate effective field development plans. Hence, this study delivers an efficient workflow integrating 3D reservoir modeling, history matching, and feasible development scenarios to enhance the gas recovery of the tight gas reservoir, block Su-6 of the Sulige gas field, China. Initially, history matching was verified so that the model aligned with the actual production data, reflecting a more accurate depiction of fluid flow dynamics within the reservoir. Manual matching was utilized by adjusting parameters, e.g., the relative permeability, pore volume, and transmissibility multiplier, by limited simulation runs to attain a good history match. Next, the most reliable matching model can serve as the base case to predict reservoir performance via the field development strategy. The optimal scenario, identified in the 3D gas reservoir model, was to add five infill horizontal wells, which generate 8.2 % extra gas recovery related to the reference case. This finding reveals that the accurate field development strategy is to enhance the effectiveness of the production via infill a horizontal well in the unswept area of the reservoir. The primary contribution of this research indicates the worth of the field development strategy of complex tight reservoirs. Moreover, it assists operators in understanding the fluid flow dynamics and production enhancement utilizing the production history portrait and field development scenarios of the tight sandstone gas reservoir of China or elsewhere.

{"title":"Integrated reservoir characterization and simulation approach to enhance production of tight sandstone gas reservoir, Sulige gas field, Ordos Basin, China","authors":"Sayed Muhammad Iqbal , Dawei Hu , Javid Hussain , Nafees Ali , Wakeel Hussain , Altaf Hussain , Edwin E. Nyakilla","doi":"10.1016/j.pce.2024.103846","DOIUrl":"10.1016/j.pce.2024.103846","url":null,"abstract":"<div><div>The tight gas reservoir is a significant unconventional hydrocarbon resource of energy worldwide. However, the complex nature and heterogeneity make it challenging during exploration and production. Moreover, constructing and updating 3D reservoir model is vital for reservoir monitoring and surveillance. Such reservoirs require precise simulation strategies to accurately assess the hydrocarbon potential and formulate effective field development plans. Hence, this study delivers an efficient workflow integrating 3D reservoir modeling, history matching, and feasible development scenarios to enhance the gas recovery of the tight gas reservoir, block Su-6 of the Sulige gas field, China. Initially, history matching was verified so that the model aligned with the actual production data, reflecting a more accurate depiction of fluid flow dynamics within the reservoir. Manual matching was utilized by adjusting parameters, e.g., the relative permeability, pore volume, and transmissibility multiplier, by limited simulation runs to attain a good history match. Next, the most reliable matching model can serve as the base case to predict reservoir performance via the field development strategy. The optimal scenario, identified in the 3D gas reservoir model, was to add five infill horizontal wells, which generate 8.2 % extra gas recovery related to the reference case. This finding reveals that the accurate field development strategy is to enhance the effectiveness of the production via infill a horizontal well in the unswept area of the reservoir. The primary contribution of this research indicates the worth of the field development strategy of complex tight reservoirs. Moreover, it assists operators in understanding the fluid flow dynamics and production enhancement utilizing the production history portrait and field development scenarios of the tight sandstone gas reservoir of China or elsewhere.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103846"},"PeriodicalIF":3.0,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167851","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}

引用次数: 0

Spatio-temporal Variations and Forecast of PM2.5 concentration around selected Satellite Cities of Delhi, India using ARIMA model

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2024-12-19 DOI: 10.1016/j.pce.2024.103849

Vipasha Sharma , Swagata Ghosh , Varun Narayan Mishra , Pradeep Kumar

Air pollution presents serious threats to society around the world, especially in India. Among various ambient air pollutants, particulate matter (PM_2.5 & PM₁₀) have drawn significant attention from researchers owing to its adverse health impacts. Therefore, the accurate prediction of particulate matter 2.5 (PM_2.5) is essential for effective air pollution management and the prevention of respiratory diseases. The present study aims to systematically monitor and forecast the concentration of PM_2.5 in selected satellite cities of Delhi, an area that has been relatively underexplored despite its high pollution levels. In such data scarce zone, the estimation and prediction of PM_2.5 have been done using an autoregressive integrated moving average (ARIMA) model. The model's predictive accuracy and stability were validated with correlation coefficient (R), root mean square error (RMSE), mean absolute error (MAE), and relative prediction error (RPE). The results indicate that ARIMA model predicted PM_2.5 with sufficient accuracy for the current research area, demonstrating superior values of R (0.90), R² (0.82) and lower RPE (16.84), RMSE (18.28), MAE (16.89). The findings of the study indicate that the ARIMA model is a reliable method to predict PM2.5 concentrations, with acceptable accuracy. However, the ARIMA model depends on historical time series data to find trend and predict future conditions, assuming that the series remains static. Subsequently, it cannot consider the external factors that might cause alterations in the series. Such assumption limits its ability to effectively model cause-and-effect relationships. This approach is helpful for policy formulation and governance.

{"title":"Spatio-temporal Variations and Forecast of PM2.5 concentration around selected Satellite Cities of Delhi, India using ARIMA model","authors":"Vipasha Sharma , Swagata Ghosh , Varun Narayan Mishra , Pradeep Kumar","doi":"10.1016/j.pce.2024.103849","DOIUrl":"10.1016/j.pce.2024.103849","url":null,"abstract":"<div><div>Air pollution presents serious threats to society around the world, especially in India. Among various ambient air pollutants, particulate matter (PM<sub>2.5</sub> & PM<sub>10</sub>) have drawn significant attention from researchers owing to its adverse health impacts. Therefore, the accurate prediction of particulate matter 2.5 (PM<sub>2.5</sub>) is essential for effective air pollution management and the prevention of respiratory diseases. The present study aims to systematically monitor and forecast the concentration of PM<sub>2.5</sub> in selected satellite cities of Delhi, an area that has been relatively underexplored despite its high pollution levels. In such data scarce zone, the estimation and prediction of PM<sub>2.5</sub> have been done using an autoregressive integrated moving average (ARIMA) model. The model's predictive accuracy and stability were validated with correlation coefficient (R), root mean square error (RMSE), mean absolute error (MAE), and relative prediction error (RPE). The results indicate that ARIMA model predicted PM<sub>2.5</sub> with sufficient accuracy for the current research area, demonstrating superior values of R (0.90), R<sup>2</sup> (0.82) and lower RPE (16.84), RMSE (18.28), MAE (16.89). The findings of the study indicate that the ARIMA model is a reliable method to predict PM2.5 concentrations, with acceptable accuracy. However, the ARIMA model depends on historical time series data to find trend and predict future conditions, assuming that the series remains static. Subsequently, it cannot consider the external factors that might cause alterations in the series. Such assumption limits its ability to effectively model cause-and-effect relationships. This approach is helpful for policy formulation and governance.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103849"},"PeriodicalIF":3.0,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167847","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}

引用次数: 0

Seasonal precipitation changes in response to long-term aerosol anomalies: A case from West Africa

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2024-12-19 DOI: 10.1016/j.pce.2024.103847

Anselem Onyejuruwa , Zhenghua Hu , Abu Reza Md Towfiqul Islam , Matthews Nyasulu , Kyaw Than Oo

In southern West Africa (SWA), highly absorbing aerosol types can significantly alter precipitation trends. Therefore, it is essential to investigate the changes in precipitation anomalies from the dry season to the monsoon season. This study examines the impact of aerosol anomalies on precipitation trends and anomalies during the pre-monsoon season in the SWA region. The study analyzed monthly datasets of aerosol optical depth (AOD_550nm), precipitation, and atmospheric parameters from 1981 to 2020. The results base on anomaly and MK trend tests shows a decline in precipitation trends and anomalies across most of SWA during the last two decades (2001–2020). High positive spatial AOD anomalies corresponded with negative precipitation anomaly patterns. The regression analysis indicates a strong negative spatial correlation and slope between AOD and precipitation, especially along the coasts, with statistical significance for both periods. However, precipitation did not show a statistically significant relationship with zonal wind speed, geopotential height, or relative humidity at 850 hPa, even though these parameters exhibited stronger negative correlations and slope patterns over major cities in coastal SWA during the last two decades. The decrease in pre-monsoon precipitation anomalies suggests the dominance of aerosol-saturated atmosphere, which could diminish the influence of atmospheric parameters on cloud microphysics and precipitation, likely exacerbated by proximity to the ocean. The findings highlight the possible impact on the region's hydrological system due to amplification in aerosol concentrations; therefore, policies on emission control and mitigation are encouraged.

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引用次数: 0

Reservoir potential of middle Jurassic carbonates in the Nizampur Basin, Pakistan: Insights from paleoenvironmental and diagenetic analyses

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2024-12-19 DOI: 10.1016/j.pce.2024.103842

Waseem Khan , Salman Ahmed Khattak , Licheng Wang , Yisi Zhong , Nasar Khan , Quan Wan , Ihtisham Islam , Anwar Qadir

Depositional and diagenetic processes are the primary controls that impact the quality of carbonate reservoirs. The findings of a multiproxy study on carbonates of the Middle Jurassic Samana Suk Formation from the Nizampur Basin of Pakistan display a wide range of rock fabrics and diagenetic features, all affecting reservoir potential and flow properties in a complex manner. Based on petrographic and facies analyses, the model of a homoclinal ramp geometry with four characteristic microfacies types is proposed, including bioclastic mudstone, bioclastic wackestone, peloidal packstone, and bioclastic peloidal grainstone deposited in shoals, lagoons (restricted and relatively open conditions), and open marine environments. The Samana Suk Formation reservoir properties are shaped by diagenetic processes reflecting marine, meteoric, and burial diagenetic settings, such as the porosity being enhanced by fracturing, dolomitization, and dissolution, while cementation, chemical compaction, micritization, and neomorphism have reduced it. The 3-D microporosity in the form of vugs, intergranular, intercrystalline, and intraparticle pore spaces was unveiled through scanning electron microscopy (SEM). The net porosity of the formation could be enhanced by dissolution and fracturing, which makes it a better reservoir for petroleum exploration. The data shown here has been correlated with its nearby stratigraphic equivalents dealing with the Jumara Dome sediments of the Kachchh Basin and the Jaisalmer Formation (Fort Member) of the Jaisalmer Basin on India's western margin, which is important to understand and predict reservoir properties in other carbonate fields with similar properties.

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引用次数: 0

Seasonally adjusted periodic time series for Mann-Kendall trend test

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2024-12-19 DOI: 10.1016/j.pce.2024.103848

Yavuz Selim Güçlü , Ramazan Acar , Kemal Saplıoğlu

In this study, temperature data trend analysis is conducted, which is thought to be influenced by global warming, climate change, and local factor impacts. The main objective of this paper is to obtain an acceptable autoregressive correlation value for the MK test. For this purpose, seasonality (periodicity) especially in monthly time series is adjusted. Autoregressive correlation and homogeneity test values decrease after seasonal adjusting, but reasonable results are not achieved. Then, prewhitening procedure is also applied to the seasonally adjusted data. This process resulted in the data becoming both homogeneous and free autoregressive correlation. The final version of the time series is suitable for the MK test. Furthermore, the time series are divided into different time intervals, and the efficacy of the method is investigated. The results demonstrated that the method is suitable for time series with less than 30 years of data. The study demonstrated that the proposed method enhances the reliability of the data. Also, multiplication by 12 (months) allows the MK test with Z score in place of the Student's t-test in short-term data sets. This suggested methodology can be used to identify MK trend conditions in monthly time series. The application is based on monthly and annual average temperature data between 1957 and 2022 from three stations within the Kızılırmak basin (Çankırı, Kırşehir, Sivas stations) and one station within Seyhan Basin (Adana station) in Türkiye. The test results exhibited a significant increasing trend.

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引用次数: 0