Filtration systems are essential for drip irrigation using sediment-laden water sources such as the Yellow River. This study focused on a sand filter (filtration accuracy: 150 μm), a disc filter (filtration accuracy: 125 μm), and their combined multi-stage filtration system (flow rate: 30–50 m3/h). In situ tests were conducted under Yellow River water conditions in the Hetao Irrigation District, Inner Mongolia, China, to evaluate the response of filtration performance to sediment characteristics, flow rate, and operating time. On this basis, Differential Evolution-optimized Random Forest Regression (DE/RFR) was further established to predict filtration performance. The results showed that: (1) Under sediment concentrations of 0.62–3.6 g/L and median particle sizes of 4.70–16.03 μm, the head loss of the sand filter (ΔHsi) remained stable over the operating time. Conversely, the head loss of the disc filter (ΔHdi) increased with the operating time; the magnitude of this increase grew with higher flow rates, sediment concentrations, and median particle sizes, reaching 0.07 MPa after 16–235 min of operation. The head loss of the multi-stage filtration system (ΔHi) was primarily generated by the disc filter. (2) The filtration efficiency of the filters and the filtration system was 2.5–6.4%. The outlet sediment concentration and particle size distribution were linearly correlated with the inlet values, and the outlet sediment particle size distribution remained below the clogging risk threshold for emitters. (3) Prediction models for ΔHsi, ΔHdi, and ΔHi were developed based on MLR, RFR, and DE/RFR. Among these, DE/RFR exhibited the highest accuracy in predicting these variables, with R2 values ranging from 0.71 to 0.93 and RMSE values from 0.0017 to 0.0104 MPa. (4) Results from Pearson correlation and feature importance analysis indicated that ΔHsi, ΔHdi, and ΔHi were primarily influenced by flow rate, sediment concentration and operating time, and flow rate and operating time, respectively. (5) Building upon the DE/RFR model, a Filtration Cycle Prediction Model (FCPM) was developed to determine the operational duration required for the head loss across both the filters and the filtration system to reach 0.07 MPa. The two models developed in this study provide technical support for the configuration and operation of drip irrigation filtration systems using sediment-laden water.
Niu et al. (Fri,) studied this question.
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