Managing nitrate-nitrogen in the intensively drained upper Mississippi River Basin, USA under uncertainty: a perennial path forward

Shubham Aggarwal, Joe Magner, Rallapalli Srinivas, Gouri Sajith

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The upper Mississippi River basin has been identified as the most significant contributor of excessive nutrients to the hypoxic zone in the Gulf of Mexico. The land-use changes from an internally drained prairie-wetland complex to an intensively managed corn-soybean production system drained by subsurface tile drainage system in the north-central Iowa and south-central Minnesota are the primary cause of nutrient loads into the Mississippi River and many other environmental stresses. The present study summarizes the water-quality degradation from land-use change and offers a fuzzy logic-based decision support for assessing degree of suitability of the four recommended perennial plant options for managing water and nitrate-nitrogen export. These options are designed based on landscape position that currently fails to produce high yielding row crops and scale: (1) marginal upland depressions for water storage by planting deep-rooted perennial grasses and fast-growing woody poplar, willow, and alder in poorly drained swales; (2) saturated buffers and/or subtle changes in landscape slope for draining high nitrate-nitrogen subsurface (through multi-species phytoremediation treatment buffers or strips of perennial vegetation); (3) two-stage ditches with linear floodplains planted with perennial grasses; and (4) riparian and in-channel ecologically engineered trees, shrubs, and grasses to better connect meander belt width to frequent peak stream flows at larger scales. When applied throughout a typical (Des Moines Lobe Till) DMLT watershed, each option can have positive cumulative environmental effects. Fuzzy logic enhanced the precision in watershed decision-making by incorporating the uncertainty associated with factors like cost effectiveness, nitrate reduction potential, water quality improvement, and level of acceptance.

Original languageEnglish (US)
Article number704
JournalEnvironmental Monitoring and Assessment
Volume194
Issue number10
DOIs
StatePublished - Oct 2022

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

Keywords

  • Corn belt
  • Fuzzy logic
  • Nitrogen phytoremediation
  • Riparian functions
  • Tile drainage
  • Water management
  • Water quality

PubMed: MeSH publication types

  • Journal Article

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