Citation:

Isik, S., H. Haas, L. Kalin, Mohamed M. Hantush, AND C. Nietch. Nutrient Removal Potential of Headwater Wetlands in Coastal Plains of Alabama, USA. WATER. MDPI, Basel, Switzerland, 15(15):2687, (2023). https://doi.org/10.3390/w15152687

Impact/Purpose:

This is one of the a few attempts (if any) to estimate nutrient (nitrate and phosphate) function of natural wetlands at the watershed-scale using a distributed modeling framework applied to a sparsely-gauged watershed. In addition to improved understanding of headwater wetland nutrient function, the probabilistic-based modeling analysis produced statistical regression relationships that are of broader utility than the wetlands and watershed in the study-area. They can be used as tools to extrapolate nutrient load reduction and removal efficiency to similar natural wetlands and to scale-up removal rates to larger basins. The study-site is the Upper Fish River Watershed in Coastal Alabama. Key findings from the modeling study and the integrated watershed-wetland model framework can be applied by researchers in similar watersheds. The statistical regression models and key findings can be used as planning tools for watershed-scale wetland restoration projects and effective nutrient management.  

Description:

Headwater streams drain over 70% of the land in the United States with headwater wetlands covering 6.59 million hectares. These ecosystems are important landscape features in the southeast United States, with underlying effects on ecosystem health, water yield, nutrient cycling, biodiversity, and water quality. However, little is known about the relationship between headwater wetlands’ nutrient function (i.e., nutrient load removal (RL) and removal efficiency (ER)) and their physical characteristics. Here, we investigate this relationship for 44 headwater wetlands located within the Upper Fish River watershed (UFRW) in coastal Alabama. To accomplish this objective, we apply the process-based watershed model SWAT (Soil and Water Assessment Tool) to generate flow and nutrient loadings to each study wetland and subsequently quantify the wetland-level nutrient removal efficiencies using the process-based wetland model WetQual. Results show that the calculated removal efficiencies of the headwater wetlands in the UFRW are 75–84% and 27–35% for nitrate (NO−3NO3−) and phosphate (PO+4)(PO4+), respectively. The calculated nutrient load removals are highly correlated with the input loads, and the estimated PO+4PO4+ ERshows a significant decreasing trend with increased input loadings. The relationship between NO−3NO3− ER and wetland physical characteristics such as area, volume, and residence time is statistically insignificant (p > 0.05), while for PO+4PO4+, the correlation is positive and statistically significant (p < 0.05). On the other hand, flashiness (flow pulsing) and baseflow index (fraction of inflow that is coming from baseflow) have a strong effect on NO−3NO3− removal but not on PO+4PO4+ removal. Modeling results and statistical analysis point toward denitrification and plant uptake as major NO−3NO3− removal mechanisms, whereas plant uptake, diffusion, and settling of sediment-bound P were the main mechanisms for PO+4PO4+ removal. Additionally, the computed nutrient ER is higher during the driest year of the simulated period compared to during the wettest year. Our findings are in line with global-level studies and offer new insights into wetland physical characteristics affecting nutrient removal efficiency and the importance of headwater wetlands in mitigating water quality deterioration in coastal areas. The regression relationships for NO−3NO3− and PO+4PO4+ load removals in the selected 44 wetlands are then used to extrapolate nutrient load removals to 348 unmodeled non-riverine and non-riparian wetlands in the UFRW (41% of UFRW drains to them). Results show that these wetlands remove 51–61% of the NO−3NO3− and 5–10% of the PO+4PO4+ loading they receive from their respective drainage areas. Due to geographical proximity and physiographic similarity, these results can be scaled up to the coastal plains of Alabama and Northwest Florida.

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