Water quality and spatial parameters from the main channel of a 6th order stream collected with an uncrewed surface vehicle

Nitrate concentrations in streams and rivers in the midwestern United
States are often elevated, reflecting the predominance of agriculture in
the surrounding landscape. Recent advances in technology, including
surface-water drones and more precise sensors, provide an opportunity to
investigate nitrate dynamics with high spatial and temporal resolution. We
deployed an aquatic drone, the AquaBOT, in a 6th-order, agriculturally
influenced river to examine longitudinal patterns in water quality. Our
goal was to measure the spatial and temporal heterogeneity in nitrate and
nitrate-removal processes and determine the influence of tributary inputs
on mainstem chemistry. We navigated the drone along a 12-km reach of the
Des Moines River (Iowa, USA) nine times between June 2021 and August 2022.
Across the deployments, mean nitrate concentration was positively related
to discharge and was nearly two orders of magnitude higher in spring than
summer. We observed contrasting patterns in mainstem nitrate, which
decreased downstream during some runs (e.g., 3.1 to 2.7 mg N/L in June
2021), demonstrating nitrate uptake along the reach, and remained constant
on other dates. Similarly, tributaries to the Des Moines had varied
influence on riverine nitrate, either increasing or decreasing nitrate
concentrations depending on the tributary and date. Nitrate removal rates
were spatially and temporally variable but showed some consistency at the
sub-reach (2 km) scale, with two sub-reaches in particular often showing
elevated rates of nitrate removal across dates. Our study reveals nuanced
heterogeneity in nitrate dynamics of the Des Moines River despite the
homogeneity of agricultural land cover in the watershed.