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A study of nitrogen fate and transport in agricultural landscapes at the field, wetland, and watershed scales

Reducing agricultural nutrient loading in Iowa is critical to achieving Gulf of Mexico hypoxia water quality goals. Iowa comprises 4.4% of the Mississippi-Atchafalaya River Basin but contributes an average of 29% of the annual nitrate (NO3-N) load to the Gulf of Mexico (Jones et al., 2018). The main goal of this research was to study nitrogen fate and transport in agricultural areas of Iowa at different spatial scales using a unique combination of water monitoring and numerical modeling. High-frequency, continuous water quality monitoring provided valuable insights into stream and wetland NO3-N dynamics. A biogeochemical model was written and coupled to a spatially distributed, surface-subsurface hydrologic model to perform continuous (multi-year) nitrogen fate and transport simulations at the field, wetland, and watershed scales.
Field scale simulations of a tile-drained, corn-soybean rotation under conventional agricultural management over a 5-yr period illustrated strengths and weaknesses of the soil nitrogen model. Using a simplified approach to describe soil organic matter dynamics, the simulated annual nitrogen balance and NO3-N loss in tile drainage were comparable to observations and literature estimates. However, the model was not able to predict the correct response of NO3-N loss in tile drainage to fertilizer rate, which was attributed in part to limitations with the current plant uptake function which did not capture the nonlinear relationship expected between fertilizer rate and crop nitrogen uptake.
NO3-N removal was quantified at one of Iowa’s largest constructed wetlands using high-frequency (15-min), continuous water quality monitoring and hydrologic modeling. The wetland reduced incoming NO3-N concentrations 49% and loads by an estimated 61 kg day-1 from May-Nov over a 3-yr period. Wetland removal was influenced by both hydrologic and biological conditions; mass removal was greatest in Jun when discharge and NO3-N loading were highest, while percent removal was greatest in Aug when discharge was low, water residence times in the wetland were high, and warm water temperatures enhanced processing. The high-frequency monitoring captured NO3-N dynamics not possible with traditional lower frequency grab sampling, including concentration dynamics connected to storm events telling of sources and pathways of NO3-N delivery, diurnal variations in concentration indicative of biological processes, and the marked variability in wetland removal performance during low and high flow conditions. Over 5600 wetlands of similar removal performance treating over 60% of Iowa’s area and costing $1.5 billion would be required to reduce the state’s baseline NO3-N load by 45%.
The high-frequency monitoring guided and informed numerical simulations of nitrogen fate and transport at the wetland and watershed scales. Wetland simulations using imposed discharge and water quality conditions upstream of the wetland (inlet) and first order, temperature dependent kinetics produced satisfactory daily and monthly predictions of NO3-N concentration and water temperature downstream of the wetland (outlet) from May-Nov in 3/4 and 4/4 study years, respectively. NO3-N predictions were most sensitive to the denitrification first order rate constant and temperature during low discharge periods and least sensitive to both during storm events. Temperature dependent kinetics were necessary to accurately predict wetland NO3-N removal in late summer.
The continuous watershed simulations produced satisfactory monthly predictions of inlet and outlet NO3-N concentration and outlet water temperature. Consistent with findings from other modeling studies, annual nitrogen components and NO3-N dynamics were simulated reasonably well under average hydrologic conditions, while simulated NO3-N dynamics weakened under extreme (wet) hydrologic conditions. Temperature was important for predicting the seasonality of wetland NO3-N removal during the growing season, while other factors such as organic carbon and dissolved oxygen may be more influential outside the growing season when removal can still occur despite cold conditions.
A preliminary evaluation of six recently constructed wetlands that detain and process agricultural runoff from 12% of a 45 km2 watershed in north central Iowa estimated sizable flood and NO3-N reductions locally which diminished moving downstream. Continuous watershed simulations over a 13 month period following wetland implementation estimated peak flow reductions of 3-43% at the wetlands that dissipated with drainage area; similarly, the wetlands reduced NO3-N loads by an estimated 7-25% locally and 2% at the watershed outlet. Further refinements to the biogeochemical-hydrologic model are needed to improve simulated NO3-N dynamics in order to more reliably assess downstream flow and NO3-N reduction benefits.
This work identified limitations with the current modeling approach, areas of future work, and offers recommendations to guide future conservation design. Sensible hydrologic predictions are imperative to the success and dependability of the water quality simulations, which may seem obvious but can be difficult to ascertain in ungauged catchments. Future work aspires to couple a complete agricultural systems model with a physically-based hydrologic model to simulate the nitrogen cycle in a more comprehensive manner to assess which field scale nitrogen processes are most important to accurately predict stream nutrient loading at the watershed scale. Constructed wetlands could provide greater flood and nutrient reduction benefits if the normal pool hydraulics were designed with smaller hydraulic structures that more effectively throttle down incoming flows and provide the opportunity for active rather than passive pool management. As the ultimate goal of this research and other like work is to quantify progress of water quality goals set forth by the Gulf Hypoxia Task Force and help guide future conservation practice implementation, continued investment in science-based water research, water monitoring, and water modeling is necessary.

Identiferoai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-8065
Date01 December 2018
CreatorsDrake, Chad Walter
ContributorsWeber, Larry Joseph, Arenas Amado, Antonio
PublisherUniversity of Iowa
Source SetsUniversity of Iowa
LanguageEnglish
Detected LanguageEnglish
Typedissertation
Formatapplication/pdf
SourceTheses and Dissertations
RightsCopyright © 2018 Chad Walter Drake

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