Tuesday, 14 January 2020
Hall B (Boston Convention and Exhibition Center)
Nitrogen supports global demand for food and energy production, but it may threaten water resources across the globe with eutrophication. This study presents an integrated modeling system to simulate nitrogen in soil at regional scale watersheds and in surface water at large scale river networks. It enables us to mechanistically model nitrogen that are influenced by climate and human activities as well as to quantitatively assess their impacts on the nitrogen cycle and water quality. For this purpose, the Noah-MP land surface model with terrestrial Carbon and Nitrogen dynamics (Noah-MP-CN) model and the Net Anthropogenic Nitrogen Inputs (NANI) dataset were incorporated to simulate nitrate flux leaving soil. The nitrogen fluxes leaving soil are routed and transported along river networks. The river routing model is the Routing Application for Parallel ComputatIon of Discharge (RAPID). We investigated the efficacy of this regional ecosystem modeling approach using data from two Texas Basins, which flow into the Gulf of Mexico. The San Antonio and Guadalupe Basins are ideal study sites, because the drainage basins are covered by various types of nitrogen sources. The integrated modeling system was run over 9 years (2008-2016) at a daily time step. The simulations are compared with various observational data sets, including the U.S. Geological Survey (USGS) streamflow and nitrate concentration data, the Moderate Resolution Imaging Spectroradiometer (MODIS)-observed evapotranspiration (ET) and leaf area index (LAI) data, the Soil Climate Analysis Network (SCAN)-observed soil moisture data, the AmeriFlux tower micrometeorological ET and net ecosystem exchange (NEE) measurements. Results are expected that this model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and riverine nitrogen transport). The addition of nitrogen dynamics is expected to improve carbon modeling (e.g. leaf area index, net ecosystem exchange). Furthermore, compared with the observations and to the baseline Noah MP simulations, Noah-MP-CN is expected to show improvement in hydrological modeling (e.g. ET, soil moisture, and streamflow).
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