Journal
WATER RESEARCH
Volume 229, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.watres.2022.119468
Keywords
Nitrate export; Water quality; Agricultural management; Hydrological mixing; Nutrient loss reduction; Modeling
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This study analyzed observations from 83 intensively managed agricultural watersheds in the central U.S. Midwest and found that excessive nitrate export from agriculture degrades water quality. A coupled model was developed to explain the relationship between nitrate concentration and discharge, and quantify the main drivers. Agricultural practices and tile drainage were found to explain a significant portion of the spatial variability in nitrate concentration.
Excessive agricultural nitrate export to aquatic systems degrades water quality and causes downstream ecological crises. Limited understanding of their underlying mechanisms and controls hinders mitigation measures. Here we analyzed observations of nitrate concentration (C) and discharge (Q) in 83 intensively managed agricultural watersheds across the central U.S. Midwest (37.0-44.5 N, 97.5-80.0 W), which reveals a regionally consistent pattern in C similar to Q relationships: C similar to Q relationship is chemodynamic at low flows and chemostatic at high flows, i. e., C increases with Q until a threshold beyond which C levels off. Motivated by this universal pattern, we developed a coupled model at the event scale that involves mixing of quick flow with high nitrate levels coming from shallow soils and the slow flow with low nitrate levels coming from deeper soils. Its implementation in combination with seasonal patterns of hydrology and agricultural practices explains observed patterns in the C similar to Q relationship across broad spatial and temporal scales and quantifies their main driving factors. Agricultural practices (i.e., corn fraction, nitrogen fertilizer use) explain 49% of spatial variability of C in quick flow during peak season, whereas tile drainage explains another 25%. Scenario analysis of changing area fraction of tile and corn using model projections sheds light on plausible pathways to assess and implement nutrient loss reduction goals.
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