Overabundant nitrate in Iowa’s surface water threatens stream health, drinking water safety, and significantly contributes to hypoxic zones in the Gulf of Mexico. Researchers have quantified surface water nitrate loads historically with grab samples and, more recently, in-situ sensors. In-situ sensor networks capture changes in nitrate concentration over small time scales, providing high temporal resolution data to accurately calculate nitrate loading. However, because advanced sensors are expensive, spatial resolution is often compromised when sensors are deployed on large rivers. To collect high spatial resolution nitrate samples that complement the high temporal resolution data from in-situ sensors, we first used traditional grab samples on small, non-navigable streams in the Clear Creek and the English River watersheds. Dense grab samples across watersheds provide higher resolution data, but not at the spatial resolution achievable on navigable streams with newly developed, boat-deployed sensor technology.
We constructed a boat-deployed sensor system that automatically measured nitrate concentrations, temperature, dissolved oxygen, conductivity, and pH as we navigated a boat on a given waterbody. We used the system on the Iowa and Cedar Rivers to capture spatial and temporal changes never previously observed in Iowa. Our data suggest nitrate concentrations and yields were highest in low-relief landforms dominated by row crop agriculture. Nitrate concentrations were lower in higher-relief landforms with less row crop production.
We also measured water in Storm Lake, IA with the boat-deployed system. We measured little heterogeneity of nitrate concentrations in the lake, but observed significant nitrate reduction in a large wetland just upstream. The system captured fine scale spatial dynamics of nitrate reduction in the wetland and low nitrate concentrations throughout Storm Lake.
Our newly developed sensor platform captured high resolution water quality data, complementing the high temporal resolution data collected with in-situ sensors. High spatial resolution data in this and similar studies provide powerful insights for decision makers to target problematic areas, reduce nitrate, and improve water quality.