Agricultural nitrate export patterns shaped by crop rotation and tile drainage. (1st February 2023)

• Record Type: Journal Article
• Authors: Ma, Zewei; Guan, Kaiyu; Peng, Bin; Sivapalan, Murugesu; Li, Li; Pan, Ming; Zhou, Wang; Warner, Richard; Zhang, Jingwen
• Is Part Of: Water research. Volume 229(2023)
• Publication Date: 2023-02-01
• Subjects: Nitrate export -- Water quality -- Agricultural management -- Hydrological mixing -- Nutrient loss reduction, Modeling; Water -- Pollution -- Research -- Periodicals; 363.7394
• DOI: 10.1016/j.watres.2022.119468
• Languages: English
• ISSNs: 0043-1354

Abstract

Highlights: Nitrate concentration(C)∼discharge(Q) relationship was assessed in the U.S. Midwest. A transition from chemodynamic to chemostatic in C∼Q relationship was observed. Hydrological vertical mixing explains the transition in the C∼Q relationship. Hydrology and crop seasonality drive the seasonal patterns of the C∼Q relationship. Corn and tile dominate the spatial variations of nitrate export in peak river flow season. Abstract: 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∼Q relationships: C∼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∼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. Graphical abstract: Image, graphical abstract