High Expectations and Open Questions: Using High-Frequency Proxy Data to Calibrate a Catchment-Scale Phosphorus Model

High-frequency (HF) in situ sensor data capture temporal water quality variability. Using HF data to calibrate catchment-scale water quality models remains uncommon, despite previous studies demonstrating the value of HF data in reducing uncertainty in model output. This study aims to provide new insights regarding the use of HF proxy data [turbidity as a proxy for total phosphorus (TP) and total suspended solids (TSS)] compared to low-frequency (LF) data for model calibration. Four calibration data sets were used to calibrate a catchment-scale water quality model: monthly grab samples of TSS and TP (LF) and HF in situ sensor turbidity proxies for TSS and TP, alone and in combinations. These calibration data sets resulted in significant differences in model output, with HF data sets projecting more variable results and affecting modeled TP/TSS concentrations, loads, and performance statistics. Multiobjective calibration using HF proxy data highlighted important knowledge gaps concerning the theoretical and practical implications of using HF turbidity for model calibration, which is why it should be used with caution in future studies. Further research areas include investigating the nature of proxy relationships, such as linearity/nonlinearity, exploring the concentration range coverage, and an improved understanding of turbidity and TSS- and TP-generating processes.