Characterizing the impacts of macrophyte-dominated ponds on nitrogen sources and sinks by coupling multiscale models.
Sci Total Environ
; 811: 152208, 2022 Mar 10.
Article
em En
| MEDLINE
| ID: mdl-34896488
Macrophyte-dominated ponds, widely distributed in lowland areas, play an important role in nitrogen (N) retention for nonpoint source pollution. However, their impacts on N sources and sinks are scarcely quantified at a watershed scale. This study aimed to investigate N dynamics (sources, sinks, transport, etc.) of macrophyte-dominated ponds and their driving factors in a typical lowland artificial watershed (the Zhong River Watershed) in East China. For this purpose, an hourly-scale pond model (nitrogen dynamic model for macrophyte-dominated ponds, NDP-Pond) was developed, and coupled with a daily scale watershed model (Nitrogen Dynamic Polder model, NDP) to simulate N dynamics, and estimate N retention in macrophyte-dominated ponds. A comparison with the measured water level and total nitrogen (TN) revealed an acceptable model performance (coefficient of determination (R2) > 0.53) for these two models. Based on the N source/sink simulations, we found that 1) macrophyte-dominated ponds showed a large TN removal capacity with a rate of 55%, and a TN loading removal rate of 67 kg·ha-1·yr-1. 2) Denitrification was the main pathway for N removal with a contribution of 57.7%, followed by the uptake of macrophytes (35.8%) and sedimentation (6.5%). 3) The optimal coverage of macrophytes (Alternanthera philoxeroides) to enhance N removal is 2-4 kg·m-2. 4) During the macrophyte-growth period, the TN removal capacity of the pond was higher with a retention time of 1-10 days. Increasing the pond retention time would decrease the N removal efficiency. This study revealed the high value of coupling multiscale models to gain in-depth insights into N retention in macrophyte-dominated pond ecosystems.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Poluentes Químicos da Água
/
Poluição Difusa
Tipo de estudo:
Prognostic_studies
País/Região como assunto:
Asia
Idioma:
En
Revista:
Sci Total Environ
Ano de publicação:
2022
Tipo de documento:
Article