The Berg River Catchment based in the Western Cape Province, South Africa services the greater Cape Town area with water, subsequent to supplying the vast agricultural activities that exist in the middle and the lower reaches. This study thus investigates the hydrogeochemical interactions between surface and groundwater in the Berg River Catchment with the aim of establishing trends and transfer of constituents between the surface and groundwater systems, investigates the role that geology plays in water chemistry as well as identifies the geochemical processes controlling surface and groundwater chemistry in the catchment. This study was carried out using three types of research designs namely i) experimental research design; ii) field research design and meta-analysis research design. Furthermore, the study made use of hydrochemical data ranging from 2003 to 2013 obtained from the National Water Monitoring Database owned and maintained by the Department of Water and Sanitation and data that were sampled in 2016 by authors and analyzed using the ICP-MS Technique Ground Water Chart, Arc-GIS and Geosoft (Oasis Montaj) were further employed to model the data. The results indicated that: i) in the Upper Berg there is not much interaction and transfer of constituents between surface and groundwater; ii) the Middle Berg, however, indicated a degree of interaction with the sharing of constituents between the two water systems and iii) the Lower Berg indicated only NaCl water type also noting that the area situated near the river mouth whereby there is the mixing of river and seawater.
{"title":"Hydrogeological Investigations of Groundwater and Surface Water Interactions in the Berg River Catchment, Western Cape, South Africa","authors":"Seiphi Prudence Mabokela, Ntokozo Malaza","doi":"10.30564/jees.v5i2.5918","DOIUrl":"https://doi.org/10.30564/jees.v5i2.5918","url":null,"abstract":"The Berg River Catchment based in the Western Cape Province, South Africa services the greater Cape Town area with water, subsequent to supplying the vast agricultural activities that exist in the middle and the lower reaches. This study thus investigates the hydrogeochemical interactions between surface and groundwater in the Berg River Catchment with the aim of establishing trends and transfer of constituents between the surface and groundwater systems, investigates the role that geology plays in water chemistry as well as identifies the geochemical processes controlling surface and groundwater chemistry in the catchment. This study was carried out using three types of research designs namely i) experimental research design; ii) field research design and meta-analysis research design. Furthermore, the study made use of hydrochemical data ranging from 2003 to 2013 obtained from the National Water Monitoring Database owned and maintained by the Department of Water and Sanitation and data that were sampled in 2016 by authors and analyzed using the ICP-MS Technique Ground Water Chart, Arc-GIS and Geosoft (Oasis Montaj) were further employed to model the data. The results indicated that: i) in the Upper Berg there is not much interaction and transfer of constituents between surface and groundwater; ii) the Middle Berg, however, indicated a degree of interaction with the sharing of constituents between the two water systems and iii) the Lower Berg indicated only NaCl water type also noting that the area situated near the river mouth whereby there is the mixing of river and seawater.","PeriodicalId":55272,"journal":{"name":"Carpathian Journal of Earth and Environmental Sciences","volume":"6 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134953862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Satellite image classification is crucial in various applications such as urban planning, environmental monitoring, and land use analysis. In this study, the authors present a comparative analysis of different supervised and unsupervised learning methods for satellite image classification, focusing on a case study in Casablanca using Landsat 8 imagery. This research aims to identify the most effective machine-learning approach for accurately classifying land cover in an urban environment. The methodology used consists of the pre-processing of Landsat imagery data from Casablanca city, the authors extract relevant features and partition them into training and test sets, and then use random forest (RF), SVM (support vector machine), classification, and regression tree (CART), gradient tree boost (GTB), decision tree (DT), and minimum distance (MD) algorithms. Through a series of experiments, the authors evaluate the performance of each machine learning method in terms of accuracy, and Kappa coefficient. This work shows that random forest is the best-performing algorithm, with an accuracy of 95.42% and 0.94 Kappa coefficient. The authors discuss the factors of their performance, including data characteristics, accurate selection, and model influencing.
{"title":"Comparison of Machine Learning Methods for Satellite Image Classification: A Case Study of Casablanca Using Landsat Imagery and Google Earth Engine","authors":"Hafsa Ouchra, Abdessamad Belangour, Allae Erraissi","doi":"10.30564/jees.v5i2.5928","DOIUrl":"https://doi.org/10.30564/jees.v5i2.5928","url":null,"abstract":"Satellite image classification is crucial in various applications such as urban planning, environmental monitoring, and land use analysis. In this study, the authors present a comparative analysis of different supervised and unsupervised learning methods for satellite image classification, focusing on a case study in Casablanca using Landsat 8 imagery. This research aims to identify the most effective machine-learning approach for accurately classifying land cover in an urban environment. The methodology used consists of the pre-processing of Landsat imagery data from Casablanca city, the authors extract relevant features and partition them into training and test sets, and then use random forest (RF), SVM (support vector machine), classification, and regression tree (CART), gradient tree boost (GTB), decision tree (DT), and minimum distance (MD) algorithms. Through a series of experiments, the authors evaluate the performance of each machine learning method in terms of accuracy, and Kappa coefficient. This work shows that random forest is the best-performing algorithm, with an accuracy of 95.42% and 0.94 Kappa coefficient. The authors discuss the factors of their performance, including data characteristics, accurate selection, and model influencing.","PeriodicalId":55272,"journal":{"name":"Carpathian Journal of Earth and Environmental Sciences","volume":"6 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134954025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objectives: When detecting changes in synthetic aperture radar (SAR) images, the quality of the difference map has an important impact on the detection results, and the speckle noise in the image interferes with the extraction of change information. In order to improve the detection accuracy of SAR image change detection and improve the quality of the difference map, this paper proposes a method that combines the popular deep neural network with the clustering algorithm. Methods: Firstly, the SAR image with speckle noise was constructed, and the FFDNet architecture was used to retrain the SAR image, and the network parameters with better effect on speckle noise suppression were obtained. Then the log ratio operator is generated by using the reconstructed image output from the network. Finally, K-means and FCM clustering algorithms are used to analyze the difference images, and the binary map of change detection results is generated. Results: The experimental results have high detection accuracy on Bern and Sulzberger's real data, which proves the effectiveness of the method.
{"title":"SAR Change Detection Algorithm Combined with FFDNet Spatial Denoising","authors":"Yuqing Wu, Qing Xu, Zheng Zhang, Jingzhen Ma, Tianming Zhao, Xinming Zhu","doi":"10.30564/jees.v5i2.5980","DOIUrl":"https://doi.org/10.30564/jees.v5i2.5980","url":null,"abstract":"Objectives: When detecting changes in synthetic aperture radar (SAR) images, the quality of the difference map has an important impact on the detection results, and the speckle noise in the image interferes with the extraction of change information. In order to improve the detection accuracy of SAR image change detection and improve the quality of the difference map, this paper proposes a method that combines the popular deep neural network with the clustering algorithm. Methods: Firstly, the SAR image with speckle noise was constructed, and the FFDNet architecture was used to retrain the SAR image, and the network parameters with better effect on speckle noise suppression were obtained. Then the log ratio operator is generated by using the reconstructed image output from the network. Finally, K-means and FCM clustering algorithms are used to analyze the difference images, and the binary map of change detection results is generated. Results: The experimental results have high detection accuracy on Bern and Sulzberger's real data, which proves the effectiveness of the method.","PeriodicalId":55272,"journal":{"name":"Carpathian Journal of Earth and Environmental Sciences","volume":"15 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136347573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Excessive accumulation of zinc (Zn) in urban soil can lead to environmental pollution and pose a potential threat to human health and the ecosystem. How to quickly and accurately monitor the urban soil zinc content on a large scale in real time and dynamically is crucial. Hyperspectral remote sensing technology provides a new method for rapid and nondestructive soil property detection. The main goal of this study is to find an optimal combination of spectral transformation and a hyperspectral estimation model to predict the Zn content in urban soil. A total of 88 soil samples were collected to obtain the Zn contents and related hyperspectral data, and perform 18 transformations on the original spectral data. Then, select important wavelengths by Pearson's correlation coefficient analysis (PCC) and CARS. Finally, establish a partial least squares regression model (PLSR) and random forest regression model (RFR) with soil Zn content and important wavelengths. The results indicated that the average Zn content of the collected soil samples is 60.88 mg/kg. Pearson's correlation coefficient analysis (PCC) and CARS for the original and transformed wavelengths can effectively improve the correlations between the spectral data and soil Zn content. The number of important wavelengths selected by CARS is less than the important wavelengths selected by PCC. Partial least squares regression model based on first-order differentiation of the reciprocal by CARS (CARS-RTFD-PLSR) is more stable and has the highest prediction ability (R2 = 0.937, RMSE = 8.914, MAE = 2.735, RPD = 3.985). The CARS-RTFD-PLSR method can be used as a means of prediction of Zn content in soil in oasis cities. The results of the study can provide technical support for the hyperspectral estimation of the soil Zn content.
{"title":"Hyperspectral Inversion and Analysis of Zinc Concentration in Urban Soil in the Urumqi City of China","authors":"Qing Zhong, Mamattursun Eziz, Mireguli Ainiwaer, Rukeya Sawut","doi":"10.30564/jees.v5i2.5947","DOIUrl":"https://doi.org/10.30564/jees.v5i2.5947","url":null,"abstract":"Excessive accumulation of zinc (Zn) in urban soil can lead to environmental pollution and pose a potential threat to human health and the ecosystem. How to quickly and accurately monitor the urban soil zinc content on a large scale in real time and dynamically is crucial. Hyperspectral remote sensing technology provides a new method for rapid and nondestructive soil property detection. The main goal of this study is to find an optimal combination of spectral transformation and a hyperspectral estimation model to predict the Zn content in urban soil. A total of 88 soil samples were collected to obtain the Zn contents and related hyperspectral data, and perform 18 transformations on the original spectral data. Then, select important wavelengths by Pearson's correlation coefficient analysis (PCC) and CARS. Finally, establish a partial least squares regression model (PLSR) and random forest regression model (RFR) with soil Zn content and important wavelengths. The results indicated that the average Zn content of the collected soil samples is 60.88 mg/kg. Pearson's correlation coefficient analysis (PCC) and CARS for the original and transformed wavelengths can effectively improve the correlations between the spectral data and soil Zn content. The number of important wavelengths selected by CARS is less than the important wavelengths selected by PCC. Partial least squares regression model based on first-order differentiation of the reciprocal by CARS (CARS-RTFD-PLSR) is more stable and has the highest prediction ability (R2 = 0.937, RMSE = 8.914, MAE = 2.735, RPD = 3.985). The CARS-RTFD-PLSR method can be used as a means of prediction of Zn content in soil in oasis cities. The results of the study can provide technical support for the hyperspectral estimation of the soil Zn content.","PeriodicalId":55272,"journal":{"name":"Carpathian Journal of Earth and Environmental Sciences","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135884997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ahmed Abubakar, Susilawati Kasim, Mohd Yusoff Ishak, Md Kamal Uddin
This paper examines the significance of innovative replanting strategies in maximizing oil palm yield while ensuring sustainable productivity. Through a comprehensive review of literature and analysis of current practices, the major findings of this research highlighted the importance of advanced breeding and clonal selection in developing high-yielding and disease-resistant oil palm varieties. Precision agriculture technologies, including IoT devices, drones, and sensors, were identified as critical tools for data-driven decision making, optimizing resource efficiency, and reducing environmental impact. Sustainable land use planning and agroforestry integration emerged as key strategies to balance productivity with environmental conservation. The broader impacts of this work extend to other agricultural sectors and land use planning, offering valuable insights for policymakers and stakeholders to promote responsible and resilient agricultural practices. By embracing innovative replanting strategies, the oil palm industry can contribute to a more sustainable and prosperous future, balancing economic growth with environmental stewardship. Continued research and collaboration are essential to achieve these goals and foster a harmonious coexistence between productivity and sustainability, integrating precision agriculture technologies for resource optimization and reduced environmental impact, promoting sustainable land use planning and agroforestry integration to enhance biodiversity and ecosystem services. Strengthening collaborations between governments, industry players, and research institutions for innovation and knowledge exchange is essential.
{"title":"Maximizing Oil Palm Yield: Innovative Replanting Strategies for Sustainable Productivity","authors":"Ahmed Abubakar, Susilawati Kasim, Mohd Yusoff Ishak, Md Kamal Uddin","doi":"10.30564/jees.v5i2.5904","DOIUrl":"https://doi.org/10.30564/jees.v5i2.5904","url":null,"abstract":"This paper examines the significance of innovative replanting strategies in maximizing oil palm yield while ensuring sustainable productivity. Through a comprehensive review of literature and analysis of current practices, the major findings of this research highlighted the importance of advanced breeding and clonal selection in developing high-yielding and disease-resistant oil palm varieties. Precision agriculture technologies, including IoT devices, drones, and sensors, were identified as critical tools for data-driven decision making, optimizing resource efficiency, and reducing environmental impact. Sustainable land use planning and agroforestry integration emerged as key strategies to balance productivity with environmental conservation. The broader impacts of this work extend to other agricultural sectors and land use planning, offering valuable insights for policymakers and stakeholders to promote responsible and resilient agricultural practices. By embracing innovative replanting strategies, the oil palm industry can contribute to a more sustainable and prosperous future, balancing economic growth with environmental stewardship. Continued research and collaboration are essential to achieve these goals and foster a harmonious coexistence between productivity and sustainability, integrating precision agriculture technologies for resource optimization and reduced environmental impact, promoting sustainable land use planning and agroforestry integration to enhance biodiversity and ecosystem services. Strengthening collaborations between governments, industry players, and research institutions for innovation and knowledge exchange is essential.","PeriodicalId":55272,"journal":{"name":"Carpathian Journal of Earth and Environmental Sciences","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135198622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Suraya Nabilah Zaini, Azlin Mohd Azmi, Annie Syazrin Ismail
The establishment of the National Low Carbon City Master Plan (NLCCM) by Malaysia's government presents a significant opportunity to minimize carbon emissions at the subnational or local scales, while simultaneously fostering remarkable economic potential. However, the lack of data management and understanding of emissions at the subnational level are hindering effective climate policies and planning to achieve the nationally determined contribution and carbon neutrality goal. There is an urgent need for a subnational emission inventory to understand and manage subnational emissions, particularly that of the energy sector which contribute the biggest to Malaysia's emission. This research aims to estimate carbon emissions for Selangor state in accordance with the Global Protocol for Community-Scale Greenhouse Gas Emission Inventories (GPC), for stationary energy activities. The study also evaluates the mitigation potential of Floating Solar Photovoltaic (FSPV) proposed for Selangor. It was found that the total stationary energy emission for Selangor for the year 2019 was 18,070.16 ktCO2e, contributed the most by the Manufacturing sub-sector (40%), followed by the Commercial and Institutional sub-sector; with 82% contribution coming from the Scope 2 emission. The highest sub-sector of Scope 1 emissions was contributed by Manufacturing while Scope 2 emissions from the Commercial and Institutional. Additionally, the highest fuel consumed was natural gas, which amounted to 1404.32 ktCO2e (44%) of total emissions. The FSPV assessment showed the potential generation of 2.213 TWh per year, by only utilizing 10% of the identified available ponds and dams in Selangor, equivalent to an emission reduction of 1726.02 ktCO2e, offsetting 11.6% Scope 2 electricity emission. The results from the study can be used to better evaluate existing policies at the sub-national level, discover mitigation opportunities, and guide the creation of future policies.
{"title":"Energy Emissions Profile and Floating Solar Mitigation Potential for a Malaysia's State","authors":"Suraya Nabilah Zaini, Azlin Mohd Azmi, Annie Syazrin Ismail","doi":"10.30564/jees.v5i2.5923","DOIUrl":"https://doi.org/10.30564/jees.v5i2.5923","url":null,"abstract":"The establishment of the National Low Carbon City Master Plan (NLCCM) by Malaysia's government presents a significant opportunity to minimize carbon emissions at the subnational or local scales, while simultaneously fostering remarkable economic potential. However, the lack of data management and understanding of emissions at the subnational level are hindering effective climate policies and planning to achieve the nationally determined contribution and carbon neutrality goal. There is an urgent need for a subnational emission inventory to understand and manage subnational emissions, particularly that of the energy sector which contribute the biggest to Malaysia's emission. This research aims to estimate carbon emissions for Selangor state in accordance with the Global Protocol for Community-Scale Greenhouse Gas Emission Inventories (GPC), for stationary energy activities. The study also evaluates the mitigation potential of Floating Solar Photovoltaic (FSPV) proposed for Selangor. It was found that the total stationary energy emission for Selangor for the year 2019 was 18,070.16 ktCO2e, contributed the most by the Manufacturing sub-sector (40%), followed by the Commercial and Institutional sub-sector; with 82% contribution coming from the Scope 2 emission. The highest sub-sector of Scope 1 emissions was contributed by Manufacturing while Scope 2 emissions from the Commercial and Institutional. Additionally, the highest fuel consumed was natural gas, which amounted to 1404.32 ktCO2e (44%) of total emissions. The FSPV assessment showed the potential generation of 2.213 TWh per year, by only utilizing 10% of the identified available ponds and dams in Selangor, equivalent to an emission reduction of 1726.02 ktCO2e, offsetting 11.6% Scope 2 electricity emission. The results from the study can be used to better evaluate existing policies at the sub-national level, discover mitigation opportunities, and guide the creation of future policies.","PeriodicalId":55272,"journal":{"name":"Carpathian Journal of Earth and Environmental Sciences","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135253992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mark Joseph J. Buncag, Jaybie S. Arzaga, Liezl F. Tangonan, Jeffrey H. de Castro, Mary Claire M. Villanueva, Lilia Margallo, Imelda R. Lactuan, Sheryl G. Docto, Angelo V. Garcia, Princes Eunice C. Denosta, Sweet Angelikate L. Villaruel
Community-based forest management agreement in the country is a needed instrument in attaining sustainability of mangrove management. Sadly, there is no assurance that the system implemented in the mangrove forest management is sustainable. So, evaluating the mangrove management sustainability of the local tribe is a viable avenue for the appropriate management. In this study, the sustainability of the mangrove management system of the Tagbanua tribe in Bgy. Manalo, Puerto Princesa City, Palawan was evaluated. The study utilized various criteria with relevant indicators of sustainable mangrove forest management in assessing the mangrove forest management system. Focused group discussions were conducted to identify the relevant sustainable mangrove forest management C & I and verifiers. Each indicator was rated using the formulated verifiers in the form of the rating scale. Through household interviews, FGD, KII, mangrove assessment, and secondary data analysis, this study also used a mathematical model on the Sustainability Index for Individual Criteria (SIIC) to evaluate the scores for individual criteria and the Overall Sustainability Index (OSI) of the community. As a result, there are a total of seven relevant criteria, and 35 relevant indicators for Mangrove Management in Barangay Manalo. Based on the individual rating of seven criteria, the overall rating of the sustainable mangrove management system is 1.80, which implies a fairly sustainable mangrove management system. Also, the computed overall sustainability index is 0.26, which is fairly or moderately sustainable. Each criterion has strengths and weaknesses and needs to be improved to have a highly sustainable mangrove management system.
{"title":"Sustainability Evaluation of Mangrove Forest Management System of Tagbanua Tribe in Bgy. Manalo, Puerto Princesa City, Palawan, Philippines","authors":"Mark Joseph J. Buncag, Jaybie S. Arzaga, Liezl F. Tangonan, Jeffrey H. de Castro, Mary Claire M. Villanueva, Lilia Margallo, Imelda R. Lactuan, Sheryl G. Docto, Angelo V. Garcia, Princes Eunice C. Denosta, Sweet Angelikate L. Villaruel","doi":"10.30564/jees.v5i2.5756","DOIUrl":"https://doi.org/10.30564/jees.v5i2.5756","url":null,"abstract":"Community-based forest management agreement in the country is a needed instrument in attaining sustainability of mangrove management. Sadly, there is no assurance that the system implemented in the mangrove forest management is sustainable. So, evaluating the mangrove management sustainability of the local tribe is a viable avenue for the appropriate management. In this study, the sustainability of the mangrove management system of the Tagbanua tribe in Bgy. Manalo, Puerto Princesa City, Palawan was evaluated. The study utilized various criteria with relevant indicators of sustainable mangrove forest management in assessing the mangrove forest management system. Focused group discussions were conducted to identify the relevant sustainable mangrove forest management C & I and verifiers. Each indicator was rated using the formulated verifiers in the form of the rating scale. Through household interviews, FGD, KII, mangrove assessment, and secondary data analysis, this study also used a mathematical model on the Sustainability Index for Individual Criteria (SIIC) to evaluate the scores for individual criteria and the Overall Sustainability Index (OSI) of the community. As a result, there are a total of seven relevant criteria, and 35 relevant indicators for Mangrove Management in Barangay Manalo. Based on the individual rating of seven criteria, the overall rating of the sustainable mangrove management system is 1.80, which implies a fairly sustainable mangrove management system. Also, the computed overall sustainability index is 0.26, which is fairly or moderately sustainable. Each criterion has strengths and weaknesses and needs to be improved to have a highly sustainable mangrove management system.","PeriodicalId":55272,"journal":{"name":"Carpathian Journal of Earth and Environmental Sciences","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135387329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Yangtze River Basin's water resource utilization efficiency (WUE) and scientific and technological innovation level (STI) are closely connected, and the comprehension of these relationships will help to improve WUE and promote local economic growth and conservation of water. This study uses 19 provinces and regions along the Yangtze River's mainstream from 2009 to 2019 as its research objects and uses a Vector Auto Regression (VAR) model to quantitatively evaluate the spatiotemporal evolution of the coupling coordination degree (CCD) between the two subsystems of WUE and STI. The findings show that: (1) Both the WUE and STI in the Yangtze River Basin showed an upward trend during the study period, but the STI effectively lagged behind the WUE; (2) The CCD of the two subsystems generally showed an upward trend, and the CCD of each province was improved to varying degrees, but the majority of regions did not develop a high-quality coordination stage; (3) The CCD of the two systems displayed apparent positive spatial autocorrelation in the spatial correlation pattern, and there were only two types: high-high (H-H) urbanization areas and low-low (L-L) urbanization areas; (4) The STI showed no obvious response to the impact of the WUE, while the WUE responded greatly to the STI, and both of them were highly dependent on themselves. Optimizing their interaction mechanisms should be the primary focus of high-quality development in the basin of the Yangtze River in the future. These results give the government an empirical basis to enhance the WUE and promote regional sustainable development.
{"title":"The Relationship between Water Resources Use Efficiency and Scientific and Technological Innovation Level: Case Study of Yangtze River Basin in China","authors":"Guangming Yang, Qingqing Gui, Junyue Liu, Fengtai Zhang, Siyi Cheng","doi":"10.30564/jees.v5i2.5745","DOIUrl":"https://doi.org/10.30564/jees.v5i2.5745","url":null,"abstract":"The Yangtze River Basin's water resource utilization efficiency (WUE) and scientific and technological innovation level (STI) are closely connected, and the comprehension of these relationships will help to improve WUE and promote local economic growth and conservation of water. This study uses 19 provinces and regions along the Yangtze River's mainstream from 2009 to 2019 as its research objects and uses a Vector Auto Regression (VAR) model to quantitatively evaluate the spatiotemporal evolution of the coupling coordination degree (CCD) between the two subsystems of WUE and STI. The findings show that: (1) Both the WUE and STI in the Yangtze River Basin showed an upward trend during the study period, but the STI effectively lagged behind the WUE; (2) The CCD of the two subsystems generally showed an upward trend, and the CCD of each province was improved to varying degrees, but the majority of regions did not develop a high-quality coordination stage; (3) The CCD of the two systems displayed apparent positive spatial autocorrelation in the spatial correlation pattern, and there were only two types: high-high (H-H) urbanization areas and low-low (L-L) urbanization areas; (4) The STI showed no obvious response to the impact of the WUE, while the WUE responded greatly to the STI, and both of them were highly dependent on themselves. Optimizing their interaction mechanisms should be the primary focus of high-quality development in the basin of the Yangtze River in the future. These results give the government an empirical basis to enhance the WUE and promote regional sustainable development.","PeriodicalId":55272,"journal":{"name":"Carpathian Journal of Earth and Environmental Sciences","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135436821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-31DOI: 10.26471/cjees/2023/018/273
Fran GJOKA, Liri MIHO, Avni SPAHOLLI, Elian KASA
This study comprehensively assesses weathering and soil development in the alluvial plains of Albania's Drin and Mat rivers. By analyzing soil properties, mineralogical compositions, and weathering indices, it provides crucial insights into the intricate link between geological processes and soil fertility in these key agricultural areas. The focus is on weathering indices such as the Chemical Index of Alteration (CIA), Chemical Index of Weathering (CIW), and Plagioclase Index of Alteration (PIA), which reveal distinct weathering patterns across soil profiles and alluvial plains. Drin River alluvial soils display moderate indices, signaling relatively lower weathering, while Mat River alluvial soils exhibit higher indices, indicating more pronounced weathering. The study emphasizes the role of mineral composition on weathering and soil development, with easily weathered minerals suggesting a more conducive environment for weathering in Mat River soils compared to Drin River soils. Elemental composition differences in these soils significantly impact fertility, potentially affecting agricultural productivity. Correlation analyses highlight the influence of mineralogy and chemical composition on weathering rates. This study's insights into weathering dynamics, mineralogical, and elemental composition in alluvial soils highlight soil fertility implications, crucial for optimizing agriculture and addressing environmental concerns in these vital Albanian regions.
{"title":"WEATHERING PATTERNS IN ALLUVIAL SOILS UNDER MEDITERRANEAN CLIMATIC CONDITIONS IN ALBANIA AND IMPLICATIONS FOR SOIL FERTILITY","authors":"Fran GJOKA, Liri MIHO, Avni SPAHOLLI, Elian KASA","doi":"10.26471/cjees/2023/018/273","DOIUrl":"https://doi.org/10.26471/cjees/2023/018/273","url":null,"abstract":"This study comprehensively assesses weathering and soil development in the alluvial plains of Albania's Drin and Mat rivers. By analyzing soil properties, mineralogical compositions, and weathering indices, it provides crucial insights into the intricate link between geological processes and soil fertility in these key agricultural areas. The focus is on weathering indices such as the Chemical Index of Alteration (CIA), Chemical Index of Weathering (CIW), and Plagioclase Index of Alteration (PIA), which reveal distinct weathering patterns across soil profiles and alluvial plains. Drin River alluvial soils display moderate indices, signaling relatively lower weathering, while Mat River alluvial soils exhibit higher indices, indicating more pronounced weathering. The study emphasizes the role of mineral composition on weathering and soil development, with easily weathered minerals suggesting a more conducive environment for weathering in Mat River soils compared to Drin River soils. Elemental composition differences in these soils significantly impact fertility, potentially affecting agricultural productivity. Correlation analyses highlight the influence of mineralogy and chemical composition on weathering rates. This study's insights into weathering dynamics, mineralogical, and elemental composition in alluvial soils highlight soil fertility implications, crucial for optimizing agriculture and addressing environmental concerns in these vital Albanian regions.","PeriodicalId":55272,"journal":{"name":"Carpathian Journal of Earth and Environmental Sciences","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135989951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-31DOI: 10.26471/cjees/2023/018/267
Duško VUJAČIĆ, Ivica MILEVSKI, Dragica MIJANOVIĆ, Filip VUJOVIĆ, Tin LUKIĆ
This work aims to determine the current state of sediment production and propose land use measures that will affect the reducing the intensity of soil erosion for the areas of the Polimlje drainage basin on the territories of Montenegro and Serbia, and the small Shirindareh sub-basin of Iran. The approach is based on field and laboratory methods, which are processed by Web-based Intensity of Erosion and Outflow (WIntErO)model used to calculate erosion intensity. By using the computer-graphical method of the "WIntErO" software, in the study of erosion intensity, surface values (watershed surface, surface between isohypsies, etc.) and length, i.e. deviations from the map (length of the main watercourse, length of the watershed line, etc.) is processed very precisely, which was not the case before when using mechanical instruments, planimeters and curvimeters. The new WIntErO model is an integrated computer-graphic program package of the third-generation method based on the earlier generations of the modelling tools "River basins", and IntErO and calculates the amount of sediment, the intensity of soil erosion, as well as the maximum runoff from the basin, according to the EPM model of Gavrilović.During the procedure, an accuracy assessment is conducted with measurements of reservoir sediment deposition. These measurements were performed in April 2017 using professional hydrographic recording equipment, following the same methodology as in 2012. The measurement of point locations was conducted using a GPS receiver and a Trimble R6 base station. The reservoir's depth was measured using a single-frequency portable echo sounder, specifically the Odom Hydro Track. The initial assessment shows fairly acceptable results of the implemented WIntErO modelling for both study areas. Z coefficient values ranging from 0.01 to 1.00 for the observed period indicate that the river basins delineate areas with varying levels of susceptibility to water erosion processes—ranging from very low to moderate and high risk—within the studied drainage basins. Based on the analysis, we found that the average erosion intensity in Polimlje is 331.78 m³ km⁻² year⁻¹ per square kilometer. For the Shirindareh sub-basins, the average actual soil losses per square kilometer are 201 m³ year⁻¹ km⁻². Given these findings, it is evident that these basins require prompt implementation of soil conservation measures.
{"title":"NITIAL RESULTS OF COMPARATIVE ASSESSMENT OF SOIL EROSION INTENSITY USING THE WIntErO MODEL: A CASE STUDY OF POLIMLJE AND SHIRINDAREH DRAINAGE BASINS","authors":"Duško VUJAČIĆ, Ivica MILEVSKI, Dragica MIJANOVIĆ, Filip VUJOVIĆ, Tin LUKIĆ","doi":"10.26471/cjees/2023/018/267","DOIUrl":"https://doi.org/10.26471/cjees/2023/018/267","url":null,"abstract":"This work aims to determine the current state of sediment production and propose land use measures that will affect the reducing the intensity of soil erosion for the areas of the Polimlje drainage basin on the territories of Montenegro and Serbia, and the small Shirindareh sub-basin of Iran. The approach is based on field and laboratory methods, which are processed by Web-based Intensity of Erosion and Outflow (WIntErO)model used to calculate erosion intensity. By using the computer-graphical method of the \"WIntErO\" software, in the study of erosion intensity, surface values (watershed surface, surface between isohypsies, etc.) and length, i.e. deviations from the map (length of the main watercourse, length of the watershed line, etc.) is processed very precisely, which was not the case before when using mechanical instruments, planimeters and curvimeters. The new WIntErO model is an integrated computer-graphic program package of the third-generation method based on the earlier generations of the modelling tools \"River basins\", and IntErO and calculates the amount of sediment, the intensity of soil erosion, as well as the maximum runoff from the basin, according to the EPM model of Gavrilović.During the procedure, an accuracy assessment is conducted with measurements of reservoir sediment deposition. These measurements were performed in April 2017 using professional hydrographic recording equipment, following the same methodology as in 2012. The measurement of point locations was conducted using a GPS receiver and a Trimble R6 base station. The reservoir's depth was measured using a single-frequency portable echo sounder, specifically the Odom Hydro Track. The initial assessment shows fairly acceptable results of the implemented WIntErO modelling for both study areas. Z coefficient values ranging from 0.01 to 1.00 for the observed period indicate that the river basins delineate areas with varying levels of susceptibility to water erosion processes—ranging from very low to moderate and high risk—within the studied drainage basins. Based on the analysis, we found that the average erosion intensity in Polimlje is 331.78 m³ km⁻² year⁻¹ per square kilometer. For the Shirindareh sub-basins, the average actual soil losses per square kilometer are 201 m³ year⁻¹ km⁻². Given these findings, it is evident that these basins require prompt implementation of soil conservation measures.","PeriodicalId":55272,"journal":{"name":"Carpathian Journal of Earth and Environmental Sciences","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135991263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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