A dynamic watershed model for determining the effects of transient storage on nitrogen export to rivers

Abstract

Legacy anthropogenic nitrogen (N) has been suggested as a major cause for increasing riverine N exports despite significant declines in anthropogenic N inputs in many regions. However, little quantitative knowledge exists concerning the contribution of the legacy N pool to riverine N export. This study developed a dynamic watershed N delivery model to address the role of transient storage of anthropogenic N inputs on riverine N flux. Employing simple mass balance and equivalent substitution rules, the model expresses the transient storage of legacy N mass with a term that combines the previous one year's riverine total N (TN) flux, relevant explanatory variables, and unknown parameters, enabling us to inversely calibrate the model parameters from measurable variables using Bayesian statistics. The model efficacy was demonstrated through application to the Yong'an River watershed in eastern China based on a 31 year record of riverine TN fluxes. The model can quantify annual transient storage of legacy N and its resulting contribution to annual riverine N flux. The model also allows partitioning of the complete longterm mass balance for the fate (e.g., transient storage, riverine export, and loss/retention by denitrification, biomass uptake and wood product export) of annual anthropogenic N inputs. To further improve the model, various N input-output processes can be specified and long-term measurements of N fates are required to further verify the model results. This study demonstrates the need to consider transient storage effects as an improvement to current watershed models and for developing and assessing N pollution control measures.

Legacy Nutrient Dynamics at the Watershed Scale: Principles, Modeling, and Implications

“…Studies also demonstrated a growing N saturation responds to excessive N inputs in many highly managed watersheds Tessier and Raynal, 2003). Therefore, many N balance studies conducted in many countries and regions (Chen et al, 2014a;Drury et al, 2011;Van Meter et al, 2016;Worrall et al, 2015) suggested a very large and ongoing storage of N in terrestrial ecosystem. In terms of P, studies conducted for many watersheds across China, United States, and Europe (Chen et al, 2015b;Goyette et al, 2016;Han et al, 2012;Hong et al, 2012;Russell et al, 2008) indicated that synthetic fertilizer application and food and feed import are major sources for total anthropogenic P inputs over the past several years to decades.…”

“…The variable hydrologic and biogeochemical residence times in different landscapes along the terrestrial-aquatic continuum give rise to distinct spatial and temporal patterns of legacy nutrient pools (Chen et al, 2014a;Sharpley et al, 2013). Legacy N hot spots always occur in large watersheds with longer time for groundwater updates and areas with longer time for N biogeochemical cycling (Worrall et al, 2015).…”

“…However, a major challenge remains in determining the appropriate length of the multiyear period that should be used to consider nutrient source inputs into models to satisfy the steady-state assumption (Chen et al, 2014b). For example, the lag times between watershed anthropogenic N inputs and riverine export associated with biological and hydrological processes can be 10 and 24.5 years as indicated in the Yongan watershed in eastern China and the Southern Ontario watershed in the United States, respectively (Chen et al, 2014a;, which is significantly longer than 5 years used in some lumped and statistical models.…”

“…Another recent attempt is applying Hydrus 1D model with meteorological and soil physical data, and boundary conditions to evaluate catchment lag time for nutrient or solute transport through unsaturated zone in a grassland catchment and an arable catchment ($10 km 2 ) in Ireland (Vero et al, 2017). By adopting simple mass balance and equivalent substitution rules, Chen et al (2014aChen et al ( , 2015a developed two new dynamic models to express the watershed legacy N mass and the indefinite number of lag terms from previous years' NANI by functions of the previous 1 year's riverine N flux. The two models were well calibrated by 31 years recodes in the Yongan watershed eastern China and yield close results concerning the legacy N source contributed riverine N fluxes (i.e., 72%-85% vs 64%-81%) and N leaching lag time lengths (i.e., 12 years vs 11 years).…”

“…The two models were well calibrated by 31 years recodes in the Yongan watershed eastern China and yield close results concerning the legacy N source contributed riverine N fluxes (i.e., 72%-85% vs 64%-81%) and N leaching lag time lengths (i.e., 12 years vs 11 years). These two models also allow partitioning of the complete long-term mass balance for the fate (e.g., transient storage, riverine export, and loss/retention by denitrification, biomass uptake, and wood product export) of annual NANI (Chen et al, 2014a) and to estimate dynamic export of annual NANI by river over years (Chen et al, 2015a). Based on these efforts, Van Meter and Basu (2015) coupled the MODFLOW/MODPATH approach and a simple SON decomposition function to address hydrologic (nitrate in groundwater) and biogeochemical (sorbed organic N within the root zone) N legacies.…”