High-Frequency Sensor Data Reveal Across-Scale Nitrate Dynamics in Response to Hydrology and Biogeochemistry in Intensively Managed Agricultural Basins

Excess nitrate in rivers draining intensively managed agricultural watersheds has caused coastal hypoxic zones, harmful algal blooms, and degraded drinking water. Hydrology and biogeochemical transformations influence nitrate concentrations by changing nitrate supply, removal, and transport. For the Midwest Unites States, where much of the land is used for corn and soybean production, a better understanding of the response of nitrate to hydrology and biogeochemistry is vital in the face of high nitrate concentrations coupled with projected increases of precipitation frequency and magnitude. In this study, we capitalized on the availability of spatially and temporally extensive sensor data in the region to evaluate how nitrate concentration (NO3-) interacts with discharge (Q) and water temperature (T) within eight watersheds in Iowa, United States, by evaluating land use characteristics and multiscale temporal behavior from 5-year, high-frequency, time series records. We show that power spectral density of Q, NO3- , and T, all exhibit power law behavior with slopes greater than 2, implying temporal self-similarity for a range of scales. NO3- was strongly cross correlated with Q for all sites and correlation increased significantly with drainage area across sites. Peak NO3- increased significantly with crop coverage across watersheds. Temporal offsets in peak NO3- and peak Q, seen at all study sites, reduced the impact of extreme events. This study illustrates a relatively new approach to evaluating environmental sensor data and revealed characteristics of watersheds in which extreme discharge events have the greatest consequences. Plain Language Summary Nitrate export from the Midwest United States has caused water quality degradation extending from the Midwest, where concentrations exceed drinking water limits, to the northern Gulf of Mexico, where it contributes to the formation of the Dead Zone. Climate models predict that precipitation in the Midwest will increase; therefore, understanding the response of nitrate to streamflow (discharge) is vital. In this study, we analyzed the patterns within nitrate, discharge and temperature sensor data over time for eight agricultural watersheds to determine how nitrate concentration is related to discharge or water temperature. From this, we evaluated the relative importance of hydrology vs. nitrate removal or release in controlling nitrate export. We show that nitrate, discharge, and temperature all exhibit self-similar characteristics across a range of temporal scales and that the percent of land used for agriculture was predictive of peak nitrate concentration. We found that nitrate was strongly related to discharge and that the similarity between nitrate and discharge increased with watershed size. However, peak nitrate concentration generally lagged behind peak discharge resulting in maximum peak nitrate loads often occurring at intermediate-sized, not extreme, events.