Predicting Floodplain Hypoxia in the Atchafalaya River, Louisiana, USA, a Large, Regulated Southern Floodplain River System

Abstract

The Atchafalaya River Basin Floodway (ARBF), a regulated river/floodplain distributary of the Mississippi River, experiences an annual flood pulse that strongly influences floodplain physicochemistry. We developed several metrics to investigate the relationship between the timing and magnitude of the flood pulse and floodplain hypoxia, which in most years is a spatially extensive and temporally prolonged problem in the lower ARBF. Principal components analysis of flood metrics from 2001 to 2009 revealed contrasting flood types (early cool and late warm), but component‐based general linear models were unable to predict the magnitude of hypoxia in ARBF water management areas (WMAs). Further analyses based on temperature and geographic information system‐determined WMA inundation with generalized additive models (GAMs) revealed WMA‐specific patterns of hypoxia, but the likelihood of hypoxia consistently increased when temperatures approached 20°C and inundation rose above 20–30%. Validation with held‐out data based on logistic regression indicated that the models constructed with the 2001–2009 temperature and inundation data were able to accurately predict the probabilities of hypoxia in two WMAs based on data collected from 2010 to 2013. The GAMs were an effective tool for visualizing and predicting the probability of hypoxia based on two easily generated parameters. Our analyses indicate that modification of the Atchafalaya River flood pulse could reduce the magnitude of hypoxia within the lower ARBF, subject to engineering (control structure operation) and economic (commercial fisheries production) constraints, by minimizing floodplain inundation after water temperatures reach 20°C. Copyright © 2015 John Wiley & Sons, Ltd.

Aquatic vegetation mediates the relationship between hydrologic connectivity and water quality in a managed floodplain

“…However, the locations that we sampled are typically inundated nearly every year. Additionally, in this study, the relationship between dD in 2011 with DO for 2004-2011 was significant, and a hypoxia model conditioned on 2000-2009 floods predicted spatial variability of the 2011 flood well (Pasco et al, 2015). In combination, these analyses suggest that, although the 2011 flood was exceptional, physical and chemical conditions on the floodplain were similar and connectivity pathways were likely not substantially different for our sample year compared to others.…”

“…Therefore, connectivity between the river and backswamps was likely greater during this flood than in typical or dry years. Buffalo Cove WMU was inundated up to 95 % of its area in 2011 and averaged 76 % inundation during the 2000-2009 floods, and Henderson WMU was 68 % inundated in 2011 compared to mean 32 % during the 2000-2009 floods (Pasco et al, 2015). However, the locations that we sampled are typically inundated nearly every year.…”

The impact of flooding on aquatic ecosystem services

“…Flood impact on fish populations is further complicated by flood timing. Floods that inundate large areas and occur when temperatures are warm are likely to result in hypoxia, affecting fish physiology, behavior, and survival (Pasco et al 2016 ). Additionally, small floods that occur when temperatures are too low for native fish spawning may cause proliferation of invasive fish populations (Rayner et al 2015 ).…”

Wetland-tree growth responses to hydrologic variability derived from development and optimization of a non-linear radial growth model

“…One potential explanation is that water level was related to precipitation which also affected vapor pressure deficits, but water level was unrelated to monthly precipitation in both Verret (R 2 = 0.08) and Atch (R 2 = 0.01). Atchafalaya River stage and water quality are mostly 481 controlled by the Mississippi River (Pasco et al, 2015). Given that high discharge is often 482 coupled with other beneficial inputs, like nutrients (Junk et al, 1989;Tockner et al, 1999), a 483 second potential explanation is that water quality differences associated with high water levels 484 stimulated tree growth.…”