Brief communication: Seasonal prediction of salinity intrusion in the Mekong Delta

Abstract

Abstract. The Mekong Delta is the most important food production area in Vietnam. Salinity intrusion during the dry season poses a serious threat to agricultural production and local livelihoods. A seasonal forecast of salinity intrusion is required in order to mitigate the negative effects. This communication present a simple statistical seasonal forecast model able to predict the salinity intrusion up to 9 months ahead with high skill. The model can thus be used as a basis for timely adaptation and mitigation planning, which is urgently needed for the imminent severe salinity intrusion expected in spring 2020.

Reconstructing Daily Discharge in a Megadelta Using Machine Learning Techniques

“…We acknowledge that reconstructing salinity and sediment data is even more challenging than reconstructing river flows; thus, the latter is vital for the former and will be the focus of our future research. Such predictions have been made using statistical models (Apel et al., 2020). However, most predictions are medium‐term estimates (up to 9 months), and appropriate and proactive water resource planning and management tasks require long‐term predictions, especially considering variations in upstream inflows because of changes in dam management and climate change, downstream rising sea level and saline water instruction, and the increasing water demand within the delta (e.g., Binh, Kantoush, Saber, et al., 2020; Park et al., 2021, 2022).…”

Apply Machine Learning to Predict Saltwater Intrusion in the Ham Luong River, Ben Tre Province

“…XNM là một trong những vấn đề chính của quản lý nguồn nước vùng cửa sông ven biển [6,7]. XNM làm giảm khả năng lọc và gia tăng các loại độc tố trong đất, dẫn đến năng suất cây trồng thấp [8].…”

“…Ở ĐBSCL, XNM là một vấn đề sinh tháixã hội cần được nghiên cứu và giải quyết, vấn đề này trở nên rất nghiêm trọng trong điều kiện biến đổi khí hậu hiện nay [4]. Chín trên tổng số mười ba tỉnh vùng ĐBSCL đang chịu ảnh hưởng từ XNM [4,7]. Từ đây, hàng nghìn hecta hoa màu, cây ăn trái, lúa gạo, nuôi trồng thủy sản bị tác động [7].…”

Performance evaluation of Auto-Regressive Integrated Moving Average models for forecasting saltwater intrusion into Mekong river estuaries of Vietnam

“…The two most severe events of drought and SWI in recorded history in 2016 and 2020 caused widespread shortages of freshwater supply for domestic and agricultural demands and 18,201 billion VND in national damage (Vietnamese Disaster Management Authority, 2019, 2020). An important factor leading to these large losses was the lack of timely forecasting and warning of SWI to prepare and respond proactively (Apel et al, 2020).…”

“…The patterns of annual salinity variations in agricultural land and their relationship to drought in Ben Tre province were examined using multi-temporal Landsat images and spatial regression (Tran et al, 2019). A logistic regression model using either the ENSO34 index or streamflow as a predictor could reliably forecast SWI up to nine months ahead in MKD (Apel et al, 2020). An ARIMA model was built to forecast the Ham Luong river (Tran et al, 2020).…”