Hydrologic Variability Controls Nutrient and Hormone Export from a Midwestern Agroecosystem

The long-term, repeated applications of animal wastes can lead to the build-up of legacy sources of nutrients within agroecosystems. However, the land-application of these wastes also introduces other contaminants of interest into agroecosystems, including hormones. These emerging contaminants have been detected in surface water bodies around the world and are known to cause endocrine disruption in sensitive aquatic species even at trace concentrations. In this research, we explore the potential for long-term, high-frequency applications of animal waste (effluent irrigation) to cause legacy build-up of hormones. We sampled tile drains and a receiving ditch on a working farm in north-central Indiana for hormones (estradiol, E2; estrone, E1; and estriol, E3) and nutrients (nitrate, N; orthophosphate, P) at a high temporal resolution for a one-year period. Repeated animal waste applications led to high frequency of detection of hormones (> 50% in the tile drain; > 90% in the ditch) and nutrients (> 70% for P and 100% for N). We used several techniques in order to assess the roles that hydrologic and biogeochemical factors played in controlling their fate and transport, including: concentration-discharge (C-Q) relationships, load-discharge (L-Q) relationships, comparison of concentration variability to hydrologic variability (CVC/CVQ), and a quantification of the importance of high-flow events to total annual loads. Hydrologic variability was found to be the dominant factor controlling export of N, P, and E1 to the tile drain and ditch, lending strong evidence that high-frequency applications of animal waste can cause hydrologic controls to overwhelm biogeochemical controls in the export of not only nutrients, but hormones as well. The vast majority of export of nutrients and hormones occurred when flowrates exceeded the 80th percentile, demonstrating the importance of high-flow events to their fate and transport. These findings have important implications for best management practices (BMPs), and suggest that BMPs must be effective during large flow events to significantly reduce transport to downstream locations.