TY - JOUR
T1 - Managing nitrate-nitrogen in the intensively drained upper Mississippi River Basin, USA under uncertainty
T2 - a perennial path forward
AU - Aggarwal, Shubham
AU - Magner, Joe
AU - Srinivas, Rallapalli
AU - Sajith, Gouri
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
PY - 2022/10
Y1 - 2022/10
N2 - 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.
AB - 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.
KW - Corn belt
KW - Fuzzy logic
KW - Nitrogen phytoremediation
KW - Riparian functions
KW - Tile drainage
KW - Water management
KW - Water quality
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U2 - 10.1007/s10661-022-10401-4
DO - 10.1007/s10661-022-10401-4
M3 - Article
C2 - 35999476
AN - SCOPUS:85136404825
SN - 0167-6369
VL - 194
JO - Environmental Monitoring and Assessment
JF - Environmental Monitoring and Assessment
IS - 10
M1 - 704
ER -