Search

Your search keyword '"Duc, Thang Tang"' showing total 4 results
Start Over Author "Duc, Thang Tang"
4 results on '"Duc, Thang Tang"'

1. Application of Artificial Intelligence to Forecast Drought Index for the Mekong Delta.

Author

Ha, Duong Hai, Duc, Phong Nguyen, Luong, Thuan Ha, Duc, Thang Tang, Ngoc, Thang Trinh, Minh, Tien Nguyen, and Minh, Tu Nguyen

Subjects
MACHINE learning, WATER management, SOUTHERN oscillation, METEOROLOGICAL stations, DEEP learning, DROUGHT forecasting
Abstract

Droughts have a substantial impact on water supplies, agriculture, and ecosystems worldwide. Agricultural sustainability and production in the Mekong Delta of Vietnam are being jeopardized by droughts caused by climate change. Conventional forecasting methods frequently struggle to comprehend the intricate dynamics of meteorological occurrences connected to drought, necessitating the use of sophisticated prediction techniques. This study assesses the effectiveness of various statistical models (ARIMA), machine learning, and deep learning models (Gradient Boosting, XGBoost, RNN, and LSTM) in forecasting the SPEI over different time periods (1, 3, 6, and 12 months) across six prediction intervals. The models were developed and evaluated using data from 11 meteorological stations spanning from 1985 to 2022. These models incorporated various climatic variables, including precipitation, temperature, humidity, potential evapotranspiration (PET), Southern Oscillation Index (SOI) Anomaly, and sea surface temperature in the NINO4 region (SST_NINO4). The results demonstrate that XGBoost and LSTM models exhibit outstanding performance, showcasing lower error metrics and higher R² values compared to Gradient Boosting and RNN. The performance of the model fluctuated depending on the forecast step, with error metrics often increasing with longer prediction horizons. The use of climatic indices improved the accuracy of the model. These findings are consistent with earlier research on drought episodes in the Mekong Delta and support studies from other areas that show the effectiveness of advanced modeling tools for predicting droughts. The work emphasizes the capacity of machine learning and deep learning models to enhance the precision of drought forecasting, which is vital for efficient water resource management and agricultural planning in places prone to drought. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

2. Research on the spread of pathogens-carrying water in the coastal aquaculture system

Author

Duc Thang Tang and Dinh Vuong Nguyen

Subjects
Fishery, Aquaculture, business.industry, Environmental science, business
Abstract

This paper presents the application of water source components theory in combination with the MIKE11 modeling tool (1D) to simulate the transport of pathogens-carrying water components in the coastal aquaculture system of Kien Giang province. The simulation results show that pathogens-carrying water spreads at a relatively fast pace and extensively in the system. Drainage schemes have also been proposed to control and minimise the spread of diseases. The application of water source components theory provides the scientific basis to ensure the rational and sustainable design of irrigation system for coastal shrimp-farming areas.

Published
2021

4. Using salt intrusion measurements to determine the freshwater discharge distribution over the branches of a multi-channel estuary: The Mekong Delta case

Author

Duc Thang Tang, Hubert H. G. Savenije, Anh Duc Nguyen, and Duc Nghia Pham

Subjects
Hydrology, geography, geography.geographical_feature_category, Discharge, Flow (psychology), Tidal irrigation, Estuary, Aquatic Science, Oceanography, Salinity, Water resources, Environmental science, Alluvium, Drainage
Abstract

The fresh water discharge is an important parameter for modelling salt intrusion in an estuary. In alluvial converging estuaries during periods of low flow, when salinity is highest, the river discharge is generally small compared to the tidal flow. This makes the determination of the fresh water discharge a challenging task. Even if discharge observations are available during a full tidal cycle, the fresh water discharge is seldom much larger than the measurement error in the tidal discharge. Observations further upstream, outside the tidal region, do not always reflect the actual flow in the saline area due to withdrawals or additional drainage. Discharge computation is even more difficult in a complex system such as the Mekong Delta, which is a multi-channel estuary consisting of many branches, over which the freshwater discharge distribution cannot be measured directly. This paper presents a new approach to determine the freshwater discharge distribution over the branches of the Mekong Delta by means of an analytical salt intrusion model, based on measurements made during the dry season of 2005 and 2006. It appears that the analytical model agrees well with observations and with a hydraulic model. This paper demonstrates that with relatively simple and appropriate salinity measurements and making use of the analytical salt intrusion model, it is possible to obtain an accurate discharge distribution over the branches of a complex estuary system. This makes the analytical model a powerful tool to analyze the water resources in tidal regions.

Published
2008

Catalog

Books, media, physical & digital resources
See catalog results