Journal Articles - Environment and Environmental Protection - 2023
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Publication"Assessment of groundwater potential modeling using support vector machine optimization based on Bayesian multi-objective hyperparameter algorithm"( 2023)Duong Tran Anh, Manish Pandey, Varun Narayan Mishra, Kiran Kumari Singh, Kourosh Ahmadi, Saeid Janizadeh, Thanh Thai Tran, Nguyen Thi Thuy Linh, Nguyen Mai Dang."Today, water supply in order to achieve sustainable development goals is one of the most important concerns and challenges in most countries. For this reason, accurate identification of areas with groundwater potential is one of the important tools in the protection, management and exploitation of water resources. Accordingly, the present study was conducted with the aim of modeling and predicting groundwater potential in Markazi province, Iran using Multivariate adaptive regression spline (MARS) and Support vector machine (SVM) machine learning models and using two random search (RS) and Bayesian optimization hyperparameter algorithms to optimize the parameters of the SVM model. For this purpose, 18 variables affecting the groundwater potential and 3482 spring locations were used to model the groundwater potential. Data for modeling were divided into two categories of training (70%) and validation (30%). The receiver operating characteristics (ROC) were used to evaluate the performance of the models. The results of evaluation models showed that using hyperparameters random search and Bayesian optimization were improved SVM accuracy in training and validation stages. Bayesian optimization methods are very efficient because they are consciously choosing the parameters of the model that this strategy improves the performance of the model. Evaluating accuracy in the validation stage showed that the AUC value is for MARS, SVM, RS-SVM and B-SVM models 87.40%, 88.25%, 90.73% and 91.73%, respectively. The results of assessment variables importance showed elevation, precipitation in the coldest month, soil and slope variables have the most importance in modeling groundwater potential, while aspect, profile curvature and TWI variables, have the least importance in predicting groundwater potential in Markazi province."
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Publication"Assessment of Long-Term Surface Water Quality in Mekong River Estuaries Using A Comprehensive Water Pollution Index"( 2023)Thai Thanh Tran, Nguyen Duy Liem, Ha Hoang Hieu, Huynh Thanh Tam, Nguyen Van Mong, Nguyen Thi My Yen, Tran Thi Hoang Yen, Ngo Xuan Quang, Pham Thanh LuuSurface water quality (SWQ) has been degraded in the Mekong River Basin under increasing pressures of population growth, economic development, and global climate change. This study employed the comprehensive water pollution index (CWPI) to assess the spatio-temporal variation of SWQ in the downstream Mekong River estuaries. Eight water quality parameters were measured between 2005 and 2021 at 21 sampling sites downstream of the Mekong River. These parameters included total suspended solids (TSS), biological oxygen demand (BOD5), chemical oxygen demand (COD), ammonia (N-NH4 + ), nitrate (N-NO3 - ), phosphate (P-PO4 3- ), iron (Fe), and total coliform. Most of the monitoring locations in the estuaries of Ham Luong, Cua Dai, Ba Lai, and Co Chien exhibited slightly to moderately polluted conditions, as indicated by the CWPI values ranging from 0.67-2.91, 0.41-2.20, 0.27- 3.02, and 0.37-2.95, respectively. TSS and Fe concentrations consistently exceeded the allowable limits, while the majority of values for N-NH4 + , N-NO3 - , P-PO4 3- , and coliform remained within acceptable thresholds. Additionally, parameters indicative of organic pollution, namely BOD5 and COD, displayed a noticeable upward trend between 2005 and 2021. SWQ exhibited significant spatial and temporal variations with TSS, organic matter, nutrients, and iron being the main areas of concern. These findings can provide guidance to policymakers involved in the assessment and enhancement of water quality in the presence of pollutant compounds that lead to a decline in water quality.
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Publication"Long-term water level dynamics in the Red River basin in response to anthropogenic activities and climate change "( 2023)Nguyen Hao Quang, Tran Quoc Viet, Ha Nam Thang , Nguyen Trinh Duc Hieu."Understanding the regular variations in water levels and identifying the potential drivers under the combined pressures of anthropogenic activities and climate change can offer valuable insights into riverine management. In this study, we analyzed long-term daily observational data, including water levels and water discharge, spanning from the ~1950s to 2021 at seven gauging stations within the Red River basin. We investigated the spatio temporal variation in mean water levels using standard analytical tools, including the Mann-Kendall (MK) test, rating curves, and Empirical Orthogonal Function (EOF). Specifically, we observed a notable and substantial decline in water levels downstream of the major tributaries, including Da, Red, and Lo Rivers, as well as at their confluence, starting at the end of 2008. Notably, a strong correlation between water levels and discharge is found, highlighting the pivotal role of discharge in influencing water levels. Surprisingly, relationships between water levels and climatic factors such as rainfall and air temperature proved less influential. This suggests that water levels are predominantly shaped by discharge and anthropogenic activities, rather than climate change. The study emphasized the substantial impact of human-induced activities, particularly dam operation and sand mining, on downstream water levels in the Red River basin. An intriguing finding revealed that upstream dy namics, particularly at the Hoa Binh dam, led to significant water level increases with the same discharge, "
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Publication"Nexus of Globalization and Environmental Quality: Investigating Heterogeneous Effects through Quantile Regression Analysis "( 2023)Tran Thai Ha Nguyen, Thi Anh Le, Thang Le Dinh, Thi Ha An Pham, Gia Quyen Phan, Tu My Vuu. Ha Manh Bui."This study examines the effects of globalization on environmental quality, explicitly focusing on the scale, technique, and composition aspects proposed by KOF Swiss Economic Institute. A large sample of 115 developed and developing countries is analyzed to understand how different dimensions of globalization impact environmental degradation at various levels, using the quantile regression method. The results indicate that globalization has a positive effect on emissions at lower and middle quantiles, but at the upper quantiles, the effect becomes negative, based on the distribution of CO2 per capita (CO2PC). Additionally, each dimension of globalization has its influence on emissions: (i) Renewable energy consumption significantly negatively impacts environmental quality across most percentiles, except for the 90th percentile. (ii) Foreign direct investment inflows positively affect environmental quality at lower quantiles but negatively at higher quantiles. (iii) Urbanization initially correlates negatively with environmental degradation at the 50th percentile, but this relationship turns positive at the 75th percentile. Overall, globalization benefits countries facing environmental degradation seriously, while countries maintaining a high quality environment have not benefited much from globalization. These findings offer valuable insights for policymakers in developing effective environmental policies considering diverse economic and environmental conditions across countries"
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PublicationRanking Sub-Watersheds for Flood Hazard Mapping:A Multi-Criteria Decision-Making Approach( 2023)Nguyet Minh Nguyen, Reza Bahramloo, Jalal Sadeghian, Mehdi Sepehri, Hadi Nazaripouya, Vuong Nguyen Dinh, Afshin Ghahramani, Ali Talebi, Ismail Elkhrachy, Chaitanya B. Pande, Sarita Gajbhiye Meshram."The aim of this paper is to assess the extent to which the Sad-Kalan watershed in Iran participates in floods and rank the Sad-Kalan sub-watersheds in terms of flooding potential by utilizing multi-criteria decision-making approaches. We employed the entropy of a drainage network, stream power index (SPI), slope, topographic control index (TCI), and compactness coefficient (Cc) in this investigation. After forming a decision matrix with 25 possibilities (sub-watersheds) and 5 evaluation indices, we used four MCDM approaches, including the analytic hierarchy process (AHP), best–worst method (BWM), interval rough numbers AHP (IRNAHP), picture fuzzy with AHP (PF-AHP), and picture fuzzy with linear assignment model (PF-LAM, hereafter PICALAM) algorithms, to rank the sub-watersheds. The study results demonstrated that PICALAM exhibited superior performance compared to the other methods due to its consideration of both local and global weights for each criterion. Additionally, among the methods used (AHP, BWM, and IRNAHP) that showed similar performances in ranking the sub-watersheds, the BWM method proved to be more time-efficient in the ranking process."
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PublicationWhat role renewable energy consumption, renewable electricity, energy use and import play in environmental quality?( 2023)