Elevated nutrient concentrations present significant challenges to surface water quality management globally, and dissolved organic matter mediates several key biogeochemical processes. Storm events often dominate riverine loads of nitrate, phosphorus, and dissolved organic matter, and are expected to increase in frequency and intensity in many regions due to climate change. This dissertation focuses on improving the application of in situ optical water quality sensors and interpreting the high-frequency data they produce to better understand biogeochemical and watershed processes that are critical for resource management.

We deployed in situ sensors to monitor water quality in three watersheds with contrasting land use / land cover, including agricultural, urban, and forested landscapes. The sensors measured absorbance of ultraviolet-visible light through the water column at 2.5 nanometer wavelength increments at 15-minute intervals for three years. These deployments provided a testbed to evaluate the sensors and improve models to predict concentrations of nitrate, three phosphorus fractions, and dissolved organic carbon using absorbance spectra and laboratory analyses through multivariate statistical techniques. In addition, an improved hysteresis calculation method was used to determine short-timescale storm dynamics for several parameters during 220 storm events.

Goals of each dissertation chapter were to: (1) examine the influences of seasonality, storm size, and dominant land use / land cover on storm dissolved organic carbon and nitrate hysteresis and loads; (2) evaluate the utility of the sensors to determine total, dissolved, and soluble reactive phosphorus concentrations in streams draining different land use / land covers, and perform the first statistically robust validation technique applied to optical water quality sensor calibration models; and (3) analyze storm event dissolved organic matter quantity and character dynamics by calculating hysteresis indices for DOC concentration and spectral slope ratio, and develop a novel analytical framework that leverages these high frequency measurements to infer biogeochemical and watershed processes. Each chapter includes key lessons and future recommendations for using in situ optical sensors to monitor water quality.