Risk Estimation of Surface Water Pollution in Vam Co Tay River Based on Remote Sensing Data and Multi-criteria Decision Analysis Methods

Abstract Satellite remote sensing (SRS) is a technique that can provide effective method on surface water quality assessment at large spatial scales studies. The analysis research involves: (1) analysis of changes in surface water quality in the Vam Co Tay River, Long An province, Vietnam in the period 2015–2020, (2) select a model to estimate water quality assessment index from remote sensing data based on Bayesian Model Averaging - BMA; and (3) quantitative assessment of surface water pollution risks in the study area. The results show that the predictive coefficients of determination (R2) for water quality (BOD5, COD, and TSS) are higher than 0.70 for all three parameters. In particular, the upstream of ​​Vam Co Tay river with "very high risk level" in 2015 tended to decrease to "high risk level" in 2020. Besides, the results also show the increasing of the risk in downstream from "low risk" in 2015 to "moderate risk" in 2020. The study demonstrated the potential of SRS for providing an overall assessment of the spatial distribution of risks associated with surface water pollution and forecasting the concentration change trends in the future, and supporting to overcome data shortages in water monitoring