Quantifying watershed sensitivity to spatially variable N loading and the relative importance of watershed N retention mechanisms

The link between watershed nitrogen (N) loading and watershed nitrate (NO 3-) export is poorly understood yet critical to addressing the growing global problem of watershed N enrichment. We introduce the Big Sky nutrient export model (BiSN) which incorporates spatial stream water chemistry, data from instream tracer additions and geologic weathering experiments, and terrain and land use analysis to quantify the spatial variability of watershed sensitivity to N loading and the relative importance of upland, riparian, and instream N retention (storage, removal, or transformation) across land use/land cover (LULC) and landscape positions. Bayesian Markov chain Monte Carlo (MCMC) methods were used for model specification and were helpful in assessing model and parameter uncertainty and advancing understanding of the primary processes governing watershed NO 3- export. Modeling results revealed that small amounts of wastewater loading occurring in watershed areas with short travel times to the stream had disproportionately large impacts on watershed nitrate (NO 3-) export compared to spatially distributed N loading or localized N loading in watershed areas with longer travel times. In contrast, spatially distributed N inputs of greater magnitude (terrestrial storage release and septic systems) had little influence on NO 3- export. During summer base flow conditions, 98%-99% of watershed N retention occurred in the uplands, most likely from biological assimilation or lack of hydrologic transport. The relative role of instream N retention increased with N loading downstream through the stream network. This work demonstrates the importance of characterizing the spatial variability of watershed N loading, export and retention mechanisms, and considering landscape position of N sources to effectively manage watershed N. Copyright 2011 by the American Geophysical Union.

Duke Scholars

Author Brian McGlynn Earth and Climate Sciences