Tracking the nitrogen leaching from different sources in bioretention systems with a process-based model

Bioretention systems are a typical stormwater management technology intended to reduce runoff and non-point source pollution. Multiple sources can contribute to nitrogen (N) leaching from bioretention systems, including the current rainfall-runoff (i.e., immediate leaching), recent rainfall-runoffs (i.e., fast leaching) and long-ago legacy N (i.e., slow leaching), however, there is a lack of methods to quantify these contributions. Here, a process-based Bioretention System (BRS) model for N leaching simulations was verified with artificially-labeled 15N data besides N data to reduce predictive uncertainties. The BRS model was then coupled with an Nitrogen Source Apportionment (NSA) module for N leaching tracking to quantify the contributions from different sources. Results from a bioretention system showed that additional 15N data reduced the predictive uncertainty of total N (TN) concentrations by 23 %. Immediate leaching, fast leaching and slow leaching increased, decreased and remained steady during the leaching process and accounted for 79.54 ± 5.08 %, 2.80 ± 1.74 % and 17.66 ± 4.11 % of N leaching, respectively. The dominant immediate leaching can be significantly weakened by a submerged zone, a shorter antecedent dry periods (ADP), a lower rainfall intensity or influent concentration. This study provides a framework to quantify N leaching from multiple sources with implications for long-term N leaching management.