Pub Date : 2023-03-26DOI: 10.25073/2588-1094/vnuees.4927
P. V. Anh, Nguyen Quang Truong, Tran Van Thuy, Le Duc Minh, Nguyen Tuan Anh, Nguyen Kieu Bang Tam, Pham Thi Thu Ha, Dang Thi Hai Linh, Doan Thi Nhat Minh
From the field survey research between 2012 and 2021, we herein provide a list of 39 threatened species of amphibians and reptiles from Son La Province. Of these, the following species have high conservation values: two species are listed in the Governmental Decree No. 64/2019/ND-CP, 12 species are listed in the Governmental Decree No. 84/2021/ND-CP, 12 species are listed in the CITES Appendices, 22 species are listed in the Vietnam Red Data Book (2007), and 24 species are listed in the IUCN Red List (2022). In addition, 21 species are being exploited for food and wildlife trade by local people. Major threats to the habitat and populations of amphibians and reptiles in the study areas include deforestation, slash-and-burn cultivation, hunting activities, exploitation of forest products, quarrying, hydropower and road construction, as well as overharvesting for food and trade. The research results provide a scientific base for conservation and management of amphibians, reptiles and biodiversity of Son La Province.
{"title":"Threatened Species of Amphibians and Reptiles from Son La Province and Their Conservation Values","authors":"P. V. Anh, Nguyen Quang Truong, Tran Van Thuy, Le Duc Minh, Nguyen Tuan Anh, Nguyen Kieu Bang Tam, Pham Thi Thu Ha, Dang Thi Hai Linh, Doan Thi Nhat Minh","doi":"10.25073/2588-1094/vnuees.4927","DOIUrl":"https://doi.org/10.25073/2588-1094/vnuees.4927","url":null,"abstract":"From the field survey research between 2012 and 2021, we herein provide a list of 39 threatened species of amphibians and reptiles from Son La Province. Of these, the following species have high conservation values: two species are listed in the Governmental Decree No. 64/2019/ND-CP, 12 species are listed in the Governmental Decree No. 84/2021/ND-CP, 12 species are listed in the CITES Appendices, 22 species are listed in the Vietnam Red Data Book (2007), and 24 species are listed in the IUCN Red List (2022). In addition, 21 species are being exploited for food and wildlife trade by local people. Major threats to the habitat and populations of amphibians and reptiles in the study areas include deforestation, slash-and-burn cultivation, hunting activities, exploitation of forest products, quarrying, hydropower and road construction, as well as overharvesting for food and trade. The research results provide a scientific base for conservation and management of amphibians, reptiles and biodiversity of Son La Province. \u0000 \u0000 ","PeriodicalId":247618,"journal":{"name":"VNU Journal of Science: Earth and Environmental Sciences","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124148929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract: This study was conducted to determine the criteria for evaluating sustainable universities for Vietnam. The Delphi method is used to collect opinions of experts from the field of environment and sustainable development on some proposed criteria. The results of the first round of Delphi were synthesized and analyzed according to KAMET principles. A set of proposed criteria have been identified and selected. The Kendall coefficient, calculated from the Delphi round 2 questionnaire, is 0.52, showing a strong consensus and high level of confidence of experts on the four groups of sustainable university evaluation criteria for Vietnam, including: Research training and participation in extracurricular activities; Operation; Governance and policy; Community involvement and social responsibility. The research results provide the foundation for a set of criteria to evaluate sustainable universities for Vietnam.
{"title":"Application of Delphi method to identify sustainable university assessment criteria for Vietnam","authors":"Tran Thi Minh Hang, Tran Thi My Huong, Pham Hung Son, Nguyễn Mạnh Khải","doi":"10.25073/2588-1094/vnuees.4790","DOIUrl":"https://doi.org/10.25073/2588-1094/vnuees.4790","url":null,"abstract":"Abstract: This study was conducted to determine the criteria for evaluating sustainable universities for Vietnam. The Delphi method is used to collect opinions of experts from the field of environment and sustainable development on some proposed criteria. The results of the first round of Delphi were synthesized and analyzed according to KAMET principles. A set of proposed criteria have been identified and selected. The Kendall coefficient, calculated from the Delphi round 2 questionnaire, is 0.52, showing a strong consensus and high level of confidence of experts on the four groups of sustainable university evaluation criteria for Vietnam, including: Research training and participation in extracurricular activities; Operation; Governance and policy; Community involvement and social responsibility. The research results provide the foundation for a set of criteria to evaluate sustainable universities for Vietnam. \u0000 ","PeriodicalId":247618,"journal":{"name":"VNU Journal of Science: Earth and Environmental Sciences","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116459748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.25073/2588-1094/vnuees.4877
Bui Thi Nuong, Bui Khanh Linh, Vu Quynh Trang, Phung Thi Huyen, Bui Thi Phuong Thao, Nguyễn Ngọc, B. Duong
Vietnam is gifted with a dense network of rivers and abundant water resources. However, the gift along with the limited irrigation system of the country seems putting more pressure on the sustainable management of water resources in river basins. In order to develop a framework for assessing environmental sustainability for water resources in the Srepok River basin in Vietnam (VSRB), this study applied the Fuzzy Analytical Hierarchy Process (Fuzzy AHP) since this approach has been powerful and appropriate for sustainability assessment studies. The ten core environmental sustainability indicators were developed based on the current issues existing in the VSRB.
{"title":"Applying Fuzzy Analytical Hierarchy Process to Establish Environmental Sustainability Indicators for Water Resources Srepok River Basin, Vietnam","authors":"Bui Thi Nuong, Bui Khanh Linh, Vu Quynh Trang, Phung Thi Huyen, Bui Thi Phuong Thao, Nguyễn Ngọc, B. Duong","doi":"10.25073/2588-1094/vnuees.4877","DOIUrl":"https://doi.org/10.25073/2588-1094/vnuees.4877","url":null,"abstract":"Vietnam is gifted with a dense network of rivers and abundant water resources. However, the gift along with the limited irrigation system of the country seems putting more pressure on the sustainable management of water resources in river basins. In order to develop a framework for assessing environmental sustainability for water resources in the Srepok River basin in Vietnam (VSRB), this study applied the Fuzzy Analytical Hierarchy Process (Fuzzy AHP) since this approach has been powerful and appropriate for sustainability assessment studies. The ten core environmental sustainability indicators were developed based on the current issues existing in the VSRB. ","PeriodicalId":247618,"journal":{"name":"VNU Journal of Science: Earth and Environmental Sciences","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121245954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.25073/2588-1094/vnuees.4738
Doan Quang Cuong, Tran Van Tuan, Trinh Thi Kieu Trang
The land valuation process is an integrated assessment of land price determinants that help managers formulate land-use policies, taxes, and the real estate market. In this study, ten factors affecting land value are selected and divided into 03 groups of factors, including i) Accessibility; ii) Environment; and iii) Socio-culture. The study then determined the weights of the elements by AHP and performed the spatial analysis by GIS, Fuzzy, to determine land value. The results reflect the distribution of land value zones in the Dong Anh district and show a strong correlation with the actual land prices traded in the market. This land value information is assigned to the land parcels to support automated valuation models and urban planning. This study can be implemented in other areas or on a larger scale.
{"title":"Apply GIS, Fuzzy Theory and AHP to Determine Land Value for Land Valuation: A Case Study of Dong Anh District, Hanoi","authors":"Doan Quang Cuong, Tran Van Tuan, Trinh Thi Kieu Trang","doi":"10.25073/2588-1094/vnuees.4738","DOIUrl":"https://doi.org/10.25073/2588-1094/vnuees.4738","url":null,"abstract":"The land valuation process is an integrated assessment of land price determinants that help managers formulate land-use policies, taxes, and the real estate market. In this study, ten factors affecting land value are selected and divided into 03 groups of factors, including i) Accessibility; ii) Environment; and iii) Socio-culture. The study then determined the weights of the elements by AHP and performed the spatial analysis by GIS, Fuzzy, to determine land value. The results reflect the distribution of land value zones in the Dong Anh district and show a strong correlation with the actual land prices traded in the market. This land value information is assigned to the land parcels to support automated valuation models and urban planning. This study can be implemented in other areas or on a larger scale. \u0000 \u0000 ","PeriodicalId":247618,"journal":{"name":"VNU Journal of Science: Earth and Environmental Sciences","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115865254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.25073/2588-1094/vnuees.4890
Nguyen Thanh Tuan, N. Phu, N. Quy, H. Nhung
Abstract: The assessment of carbon stocks is one of the key measurements to support climate change mitigation policies. The research applied Landsat 8 satellite imagery combined with field-measurements using four machine learning methods (random forest - RF, artificial neural networks - NNET, support vector machines – SVM, and linear regression - LM) to estimate aboveground carbon in evergreen broadleaf forest in Binh Phuoc province. The field sample plots were randomly divided into training (96 plots) and testing (24 plots) data. The results showed that RF yielded the greatest precision with an R2 value above 0,9 and RMSE below 6 ton/ha on the training data, with an R2 value of 0,41 and RMSE of 11,04 ton/ha on the testing data. The estimate of forest carbon stock increased distinctly from the mean value of 59,80 ton/ha in the very poor forest to 87,78 ton/ha in the rich forest. The results found in the present study demonstrated that Landsat 8 imagery in conjunction with RF has the appropriate to estimate aboveground carbon stock in evergreen broadleaf forest-leaved in Binh Phuoc province. Keywords: Random forest, aboveground carbon, REDD+, forest carbon estimation.
摘要:碳储量评估是支持气候变化减缓政策的关键措施之一。本研究将Landsat 8卫星图像与野外测量相结合，采用随机森林(RF)、人工神经网络(NNET)、支持向量机(SVM)和线性回归(LM)四种机器学习方法对平福省常绿阔叶林的地上碳进行了估算。田间样地随机分为训练样地(96块)和检验样地(24块)。结果表明，在训练数据上，RF精度最高，R2值在0.9以上，RMSE在6 t /ha以下;在测试数据上，RF精度最高，R2值为0.41,RMSE为11.04 t /ha。森林碳储量估计值从极贫林的平均值59,80 t /ha明显增加到富林的平均值87,78 t /ha。本研究的结果表明，Landsat 8影像与RF相结合可以较好地估算平福省常绿阔叶林的地上碳储量。关键词:随机森林，地上碳，REDD+，森林碳估算
{"title":"Applied Machine Learning Algorithms and Landsat 8 for Estimating Aboveground Carbon Stock in Evergreen Broadleaf Forest in Binh Phuoc Province","authors":"Nguyen Thanh Tuan, N. Phu, N. Quy, H. Nhung","doi":"10.25073/2588-1094/vnuees.4890","DOIUrl":"https://doi.org/10.25073/2588-1094/vnuees.4890","url":null,"abstract":"Abstract: The assessment of carbon stocks is one of the key measurements to support climate change mitigation policies. The research applied Landsat 8 satellite imagery combined with field-measurements using four machine learning methods (random forest - RF, artificial neural networks - NNET, support vector machines – SVM, and linear regression - LM) to estimate aboveground carbon in evergreen broadleaf forest in Binh Phuoc province. The field sample plots were randomly divided into training (96 plots) and testing (24 plots) data. The results showed that RF yielded the greatest precision with an R2 value above 0,9 and RMSE below 6 ton/ha on the training data, with an R2 value of 0,41 and RMSE of 11,04 ton/ha on the testing data. The estimate of forest carbon stock increased distinctly from the mean value of 59,80 ton/ha in the very poor forest to 87,78 ton/ha in the rich forest. The results found in the present study demonstrated that Landsat 8 imagery in conjunction with RF has the appropriate to estimate aboveground carbon stock in evergreen broadleaf forest-leaved in Binh Phuoc province. \u0000Keywords: Random forest, aboveground carbon, REDD+, forest carbon estimation. \u0000 \u0000 ","PeriodicalId":247618,"journal":{"name":"VNU Journal of Science: Earth and Environmental Sciences","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127486037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.25073/2588-1094/vnuees.4853
N. Truc, Nguyen Van Hoan, Tran Ngoc Tu, Nguyen Trong Van
Abstract: Fly ash (FA) and coal bottom ash (CBA) of thermal power plants is industrial wastes but can be used for many different purposes. This paper focuses on the authors’ research on using CBA to successfully produce artificial sand to replace natural sand; using FA and CBA as aggregates for producing of non-fired brick, and applying of the important properties of CBA to prevent salinization of structures based on capillary test results combined with a specialized design method. The research and application of coal ash not only contribute to solving environmental problems and natural resources but also significantly contribute to promoting sustainable development and proactively responding to climate change.
{"title":"The Application of Coal Ash of Thermal Power Plant in Building Materials and Anti-salinity Foundation","authors":"N. Truc, Nguyen Van Hoan, Tran Ngoc Tu, Nguyen Trong Van","doi":"10.25073/2588-1094/vnuees.4853","DOIUrl":"https://doi.org/10.25073/2588-1094/vnuees.4853","url":null,"abstract":"Abstract: Fly ash (FA) and coal bottom ash (CBA) of thermal power plants is industrial wastes but can be used for many different purposes. This paper focuses on the authors’ research on using CBA to successfully produce artificial sand to replace natural sand; using FA and CBA as aggregates for producing of non-fired brick, and applying of the important properties of CBA to prevent salinization of structures based on capillary test results combined with a specialized design method. The research and application of coal ash not only contribute to solving environmental problems and natural resources but also significantly contribute to promoting sustainable development and proactively responding to climate change. \u0000 \u0000 \u0000 ","PeriodicalId":247618,"journal":{"name":"VNU Journal of Science: Earth and Environmental Sciences","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123840483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.25073/2588-1094/vnuees.4896
Mai Van Tien, Tran To Uyen
Total tannins were separated and recovered from paper mills wastewater by distributed extraction and used as a raw material to synthesize quaternary ammonium tannate through the Mannich reaction. Quaternary ammonium tannins are used as coagulants and flocculants in wastewater treatment. The structural and properties of the quaternary ammonium tannate materials were determined by FTIR infrared spectroscopy, SEM scanning electron microscopy, DSC-TGA thermal analysis and determine the point of zero charge-pHpzc. The experiment to evaluate the coagulation and flocculation ability of the quaternary ammonium tannate in wastewater treatment was performed using the Jartest device model and evaluated through the removal efficiency of Pb2+ and Cd2+ metal ions, turbidity and DO index. The DO index and turbidity of the wastewater sample are best treated with quaternary ammonium tannin content in the range of 0.5-1%, the time for coagulation and flocculation is 30 minutes. The removal efficiency of metal ions Pb2+ and Cd2+ reached 92% and 75% respectively in the pH range from 5-7 with the input ion concentration of 50 ppm.
{"title":"Synthesis of Quaternary Ammonium Tannin from Paper Mill Wastewater for Application in Water Treatment","authors":"Mai Van Tien, Tran To Uyen","doi":"10.25073/2588-1094/vnuees.4896","DOIUrl":"https://doi.org/10.25073/2588-1094/vnuees.4896","url":null,"abstract":"Total tannins were separated and recovered from paper mills wastewater by distributed extraction and used as a raw material to synthesize quaternary ammonium tannate through the Mannich reaction. Quaternary ammonium tannins are used as coagulants and flocculants in wastewater treatment. The structural and properties of the quaternary ammonium tannate materials were determined by FTIR infrared spectroscopy, SEM scanning electron microscopy, DSC-TGA thermal analysis and determine the point of zero charge-pHpzc. The experiment to evaluate the coagulation and flocculation ability of the quaternary ammonium tannate in wastewater treatment was performed using the Jartest device model and evaluated through the removal efficiency of Pb2+ and Cd2+ metal ions, turbidity and DO index. The DO index and turbidity of the wastewater sample are best treated with quaternary ammonium tannin content in the range of 0.5-1%, the time for coagulation and flocculation is 30 minutes. The removal efficiency of metal ions Pb2+ and Cd2+ reached 92% and 75% respectively in the pH range from 5-7 with the input ion concentration of 50 ppm. \u0000 \u0000 \u0000 \u0000 ","PeriodicalId":247618,"journal":{"name":"VNU Journal of Science: Earth and Environmental Sciences","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116852213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.25073/2588-1094/vnuees.4872
D. M. Hien, Nguyen Van Hoang, M. Le Dung, Luong Huu Dung, Ngo Thi Thuy, Van Thi Hang
The main purpose of this article is to establish a susceptibility zonation map of the landslides and debris flows in Phin Ngan commune, Bat Xat district, Lao Cai province on a large scale using statistical methods and machine learning combined with the FlowR model. First, the five Landslide Susceptibility Index (LSI) maps were established from two statistical models (Logistic Regression - LR, Discriminant Analysis – DA) and three machine learning models (Bayesian Network – BN, Artificial Neural Network – ANN, Support Vector Machine – SVM) were generated based on seven maps of landslide conditioning factors (slope, curvature, stream power index-SPI, topographic wetness index-TWI, sediment transportation index-STI, land use/land cover and weathering crust). Next, the five LSI maps will be evaluated for performance with the value of Area Under the Curve (AUC) according to the Receiver Operating Characteristic (ROC) curve. After that, a susceptibility map of debris flow established with FlowR software was combined with the five LSI maps created from five statistical and machine learning methods to generate a susceptibility zonation map of landslides and debris flows in the study area. The area percentage of the locations with landslides and debris flows located in the zones of susceptibility (very low, low, medium, high, very high), which were created from five combined methods: BN-FlowR, LR-FlowR, DA-FlowR, ANN-FlowR, and SVM-FlowR, were compared and evaluated. The results indicate that the integrated models have given outputs with good forecasting ability. They are also very useful in land-use planning as well as the prevention and mitigation of risks due to landslides and debris flows in the research area and other similar mountainous areas.
{"title":"Large-scale Mapping of Landslide and Debris Flow using Flowr Model with Statistical and Machine Learning Methods","authors":"D. M. Hien, Nguyen Van Hoang, M. Le Dung, Luong Huu Dung, Ngo Thi Thuy, Van Thi Hang","doi":"10.25073/2588-1094/vnuees.4872","DOIUrl":"https://doi.org/10.25073/2588-1094/vnuees.4872","url":null,"abstract":"The main purpose of this article is to establish a susceptibility zonation map of the landslides and debris flows in Phin Ngan commune, Bat Xat district, Lao Cai province on a large scale using statistical methods and machine learning combined with the FlowR model. First, the five Landslide Susceptibility Index (LSI) maps were established from two statistical models (Logistic Regression - LR, Discriminant Analysis – DA) and three machine learning models (Bayesian Network – BN, Artificial Neural Network – ANN, Support Vector Machine – SVM) were generated based on seven maps of landslide conditioning factors (slope, curvature, stream power index-SPI, topographic wetness index-TWI, sediment transportation index-STI, land use/land cover and weathering crust). Next, the five LSI maps will be evaluated for performance with the value of Area Under the Curve (AUC) according to the Receiver Operating Characteristic (ROC) curve. After that, a susceptibility map of debris flow established with FlowR software was combined with the five LSI maps created from five statistical and machine learning methods to generate a susceptibility zonation map of landslides and debris flows in the study area. The area percentage of the locations with landslides and debris flows located in the zones of susceptibility (very low, low, medium, high, very high), which were created from five combined methods: BN-FlowR, LR-FlowR, DA-FlowR, ANN-FlowR, and SVM-FlowR, were compared and evaluated. The results indicate that the integrated models have given outputs with good forecasting ability. They are also very useful in land-use planning as well as the prevention and mitigation of risks due to landslides and debris flows in the research area and other similar mountainous areas. \u0000 ","PeriodicalId":247618,"journal":{"name":"VNU Journal of Science: Earth and Environmental Sciences","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128139983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.25073/2588-1094/vnuees.4878
Vu Phuong Lan, Ha Minh Cuong, Nguyen Phuong Bac, Dinh Thi Bao Hoa, Pham Van Manh, Doan Quang Cuong, Nguyen Huu Duy
Extreme hydrological events become increasingly unpredictable due to climate change and sea-level rise, highlighting the importance of coastal sea level monitoring. This study aims to develop a Global Navigation Satellite System (GNSS) reflectometry technology that uses low-cost multi-frequency antennas to measure water levels. A multi-frequency GNSS antenna was installed in the Tam Giang lagoon area, Thua Thien Hue province, to collect data of GPS/GLONASS/Galileo/Beidou satellites at 1Hz from April 10 to April 29, 2022. Water level elevation is calculated from GNSS reflectometry data using Interference Pattern Technical (IPT) based on Signal-to-Noise Ratio (SNR). After filtering, the water level results are validated by data from the water level sensor located in the same location. The Root Mean Square Error between the water level from the GNSS - Reflectometry (GNSS– R) and the in situ measurement is 0,049 m and the correlation coefficient reaches 0,93 when combining different frequencies. The study results demonstrate that the multi-frequency GNSS-R station can be used as an additional method to measure water levels with an accuracy comparable to that of a standard tidal gauge. In addition, the study results also show the sensitivity of the GNSS reflected signal to weather conditions and the state of the sea surface, which is the basis for forecasting and early warning of storm surge extremes from GNSS reflectometry data.
{"title":"Application of GNSS Reflectometry in Water Level Monitoring using Low-cost GNSS Antenna: A Case Study in Tam Giang Lagoon, Thua Thien Hue Province","authors":"Vu Phuong Lan, Ha Minh Cuong, Nguyen Phuong Bac, Dinh Thi Bao Hoa, Pham Van Manh, Doan Quang Cuong, Nguyen Huu Duy","doi":"10.25073/2588-1094/vnuees.4878","DOIUrl":"https://doi.org/10.25073/2588-1094/vnuees.4878","url":null,"abstract":"Extreme hydrological events become increasingly unpredictable due to climate change and sea-level rise, highlighting the importance of coastal sea level monitoring. This study aims to develop a Global Navigation Satellite System (GNSS) reflectometry technology that uses low-cost multi-frequency antennas to measure water levels. A multi-frequency GNSS antenna was installed in the Tam Giang lagoon area, Thua Thien Hue province, to collect data of GPS/GLONASS/Galileo/Beidou satellites at 1Hz from April 10 to April 29, 2022. Water level elevation is calculated from GNSS reflectometry data using Interference Pattern Technical (IPT) based on Signal-to-Noise Ratio (SNR). After filtering, the water level results are validated by data from the water level sensor located in the same location. The Root Mean Square Error between the water level from the GNSS - Reflectometry (GNSS– R) and the in situ measurement is 0,049 m and the correlation coefficient reaches 0,93 when combining different frequencies. The study results demonstrate that the multi-frequency GNSS-R station can be used as an additional method to measure water levels with an accuracy comparable to that of a standard tidal gauge. In addition, the study results also show the sensitivity of the GNSS reflected signal to weather conditions and the state of the sea surface, which is the basis for forecasting and early warning of storm surge extremes from GNSS reflectometry data. \u0000 ","PeriodicalId":247618,"journal":{"name":"VNU Journal of Science: Earth and Environmental Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130888349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-27DOI: 10.25073/2588-1094/vnuees.4664
Pham Anh Hung, Nguyen Quoc Viet, Nguyen Ngoc Huyen, Tran Thien Cuong, Le Sy Chung, Le Xuan Thai, Le Sy Chinh
This research uses the GHI (Global Horizontal Irradiation Index) raster data source of solar radiation potential map developed by The World Bank Group and the land use map data, infrastructure in 2019 of Thanh Hoa province to calculate the solar radiation technical potential in Thanh Hoa province. In addition, GIS techniques are also applied to overlay thematic maps to determine the available solar energy development area according to the method of the Institute of Energy. The results show that the available solar energy development area is 54,621.15 ha, accounting for 5% of the province's natural area, the technical potential is 21,848.46 MWp. The well-developed regions are concentrated in the lowland and midland districts due to favorable conditions of land scale and infrastructure, less affected by natural disasters such as storms, floods and landslides. Regarding the method of determining technical potential, it is required to be more specific to identify available and exclusion areas with some types of land such as water surface, forest and paddy rice land.
{"title":"Research Method for Assessing the Potential of Solar Energy Source: Case Study in Thanh Hoa Province","authors":"Pham Anh Hung, Nguyen Quoc Viet, Nguyen Ngoc Huyen, Tran Thien Cuong, Le Sy Chung, Le Xuan Thai, Le Sy Chinh","doi":"10.25073/2588-1094/vnuees.4664","DOIUrl":"https://doi.org/10.25073/2588-1094/vnuees.4664","url":null,"abstract":" \u0000This research uses the GHI (Global Horizontal Irradiation Index) raster data source of solar radiation potential map developed by The World Bank Group and the land use map data, infrastructure in 2019 of Thanh Hoa province to calculate the solar radiation technical potential in Thanh Hoa province. In addition, GIS techniques are also applied to overlay thematic maps to determine the available solar energy development area according to the method of the Institute of Energy. The results show that the available solar energy development area is 54,621.15 ha, accounting for 5% of the province's natural area, the technical potential is 21,848.46 MWp. The well-developed regions are concentrated in the lowland and midland districts due to favorable conditions of land scale and infrastructure, less affected by natural disasters such as storms, floods and landslides. Regarding the method of determining technical potential, it is required to be more specific to identify available and exclusion areas with some types of land such as water surface, forest and paddy rice land. \u0000 ","PeriodicalId":247618,"journal":{"name":"VNU Journal of Science: Earth and Environmental Sciences","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126657166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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