Predict saline intrusion process at Vu Gia - Thu Bon river basin by Artificial Intelligence model
1. Background & Purpose
Vu Gia - Thu Bon River basin is the most extensive river system of Quang Nam province and Danang City, with an area of 10,350 km2 (1). The river contributes to the development of the country's economy, society, and water security with 2.5% of the total water supply; this river basin contributes 1.5% to the national GDP. However, this river basin is changing for the worse because the flow of the Vu Gia - Thu Bon river basin is also declining, which leads to empty downstream of the river basin and saltwater intrusion (2). The intrusion of saltwater caused by withdrawals of freshwater from the groundwater system means there is insufficient water to supply for daily life and production of the people (agriculture, aquaculture,…) around the area. Solving saltwater intrusion and water scarcity in Da Nang City, Quang Nam Province, is urgent.

Fig 1. Location of Vu Gia - Thu Bon River basin in Quang Nam - Da Nang and Vietnam
There are many solutions used to predict salt intrusion, such MIKE 11 method can, predict many scenarios of salt intrusion via the effects of climate change and sea level rise in the future. Le Hung (2016) estimated salt intrusion in the Vu Gia – Thu Bon River basin up to 2100 due to climate change (3), however, some limitations are found, such as the significant variance of accuracy, prediction time being too long, and accuracy being affected by many factors.

Fig 2. Thousands of hectares of crops have been damaged by saltwater in the Mekong Delta Vietnam
This research project proposes an intelligent technique for predicting the early salt intrusion process to address the problems above. The proposed model will obtain higher accuracy and earlier prediction than previous methods. Also, it can be developed and embedded into the LoRa-based Internet of Things to monitor water quality in real time in the future. The findings prove a new approach to Artificial Intelligence (AI) and Machine Learning (ML).
The consequences of saltwater intrusion in the Vu Gia River basin are severe for communities’ health, agriculture, environment, and economy. Therefore, to gain an overview of the theoretical to practical basis for solving this problem, team members include artificial intelligence experts, medical doctors, public health experts, and environmental experts.
Our purpose to develop a practical AI model with control chart technique to predict salinity intrusion at Vu Gia - Thu Bon River basin

Fig 3. The process of proposed method for project purpose
2. Program Goals and Main Activities
2.1. Program goals
The proposed idea is to develop a practical AI model with control chart technique to predict the water quality at Vu Gia River, especially when water is salty. To achieve that goal, the specific objective of the project is:
To develop a practical model, combining the Transformer and Support Vector Data Description with control chart, to accurately predict the water pollution and salt intrusion process, thereby providing a valuable tool for water quality management.
The findings will assist to enhance early warning systems at Cau Do water plant, the government in making long- and short-term policies to reduce water pollution and minimize the saltwater intrusion process effectively. The new approach is also considered one of the most cost-effectiveness solution for local water plant, governments, agriculture and people.
*Method:
+ Transformer: Transformer is a new kind of neural architecture which encodes the input data as powerful features via the attention mechanism. Some studies about water quality prediction have shown high performance of transformer model or transformer combining models (14, 15). Project team members have also studied using transformer in some areas (6, 10, 12)