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

Abstract

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.