Optimization of Riparian Zone Nitrogen and Phosphorus Management Through the Development of Riparian Model USDA-AFRI

(Collaborators: PI: P. Vidon, SUNY, ESF, Co-PIs: A. Gold and K. Addy)

Riparian zones are widely used as best management practices to mitigate the impact of agriculture on the quality of our waters. However, the buffering capacity of riparian zones regarding Nitrogen varies largely as a function of both upland land use/land cover and riparian hydrogeomorphic setting such as topography, soil type, and surficial geology of the riparian zone. So, the location is critical in determining the potential impact of a riparian zone on water. In spite of the acknowledged value of riparian zones in mitigating Nitrogen pollution, only a limited number of numerical models or landscape-based approaches have been developed in glaciated settings. However, the Riparian Ecosystem Management Model (REMM) has not been yet applied in the glaciated settings of the Northeast and Midwest regions, in spite of the fact that agricultural lands are linked to excessive nutrient pollution and that riparian zones are widely used in these regions to mitigate Nitrogen losses to streams. We used REMM to simulate the water quality functions of managed riparian ecosystems. In order to successfully predict riparian function(s), REMM requires daily subsurface and surface (if any) flow data from the field or upland area. In general, this information is missing from most field studies, which can hinder the ability of REMM to properly predict riparian functions.  To address this issue, the Annualized Agricultural Non-Point Source model (AnnAGNPS) is being used to predict the surface runoff loading and sediment loading to the riparian buffer simulated by REMM. The simulated surface runoff and sediment loading from AnnAGNPS is calibrated by means of comparing with observed data (USGS gauge). The calibrated daily runoff and the sediment loading are being used as input data in REMM. This study presents REMM model input development, model calibration, and validation to predict water table depth, groundwater nitrates, groundwater phosphate concentration from riparian sites in the US Midwest and US Northeast.