Total phosphorus removal in multi-soil-layering nature-based technology: assessment of influencing factors and prediction by data driven methods

Excess phosphorus (P) in wastewater can produce eutrophication, posing a serious risk to the safety of water resources and ecosystems. Therefore, effective pollutant removal including P from wastewater is the key strategy to save the environment and public health. Multi-soil-layering (MSL) is a promising nature-based technology that mainly relies on a soil mixture containing iron to remove P-pollution from wastewater. Fifteen water quality parameters were monitored in the MSL influent to determine which ones have the strongest relationship with total phosphorus (TP) removal. The influence of hydraulic loading rate (HLR) and climatic variables on the removal of TP was investigated. Three data-driven methods including multiple linear regression (MLR), k-nearest neighbors (KNN), and random forest (RF) were conducted to predict TP removal at the MSL system outlet. In contrast to climatic variables, the results reveal that the HLR has a significant impact (p <0.05) on TP removal (47%-90%) in the MSL system. Furthermore, using a feature selection technique, the HLR, pH, orthophosphate, and TP were suggested as the relevant input variables affecting TP removal in the MSL system, while an examination of accuracy shows that the RF model achieves good prediction accuracy (R² = 0.94).