Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, Hohai University, Nanjing, 210098, China; College of Environment, Hohai University, Nanjing, 210098, China.
School of Atmospheric Science and Remote Sensing, Wuxi University, Wuxi, 214105, China; School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
J Environ Manage. 2023 Oct 15;344:118406. doi: 10.1016/j.jenvman.2023.118406. Epub 2023 Jun 22.
Climate warming impact on excessive nitrogen (N) load in sediment favours cyanobacterial blooms in eutrophic waters. The nitrate (NO-N) and ammonium (NH-N) are two forms of N loads that contribute to algae blooms. However, little attention is paid to the impact of environmental factors on N loads variations at different time scales. This paper used a well-calibrated and validated EFDC model to investigate the temporal patterns and trends of ammonium and nitrate from June 2016 to June 2017. This paper presented the relationship and effects between these variations and environmental factors using data from satellite and reanalysis-based observations obtained for six meteorological parameters. The relationship and effects between these variations and environmental factors were also examined at different timescales (i.e., daily, monthly and seasonal scales). Model calibration results indicated that measured values reasonably matched simulated values. The validation results revealed that relative error (RE) values were within an acceptable range. The REs of ammonium at East Taihu (S12) and Xu Lake (S23) sampling sites were 55.83% and 57.61%, while that of nitrate was 24.37% (S12) and 41.08%, respectively. The daily analysis of NH-N and NO-N variations was 7.318 ± 3.876 (g/m/day) and 0.0275 ± 0.222 (g/m/day), respectively. The monthly analysis showed NH-N and NON range from 2.04 to 12.04 (g/m/day) and 0.0008 to 0.064 (g/m/day), respectively. The magnitude NH-N and NO-N varied and showed distinct inter-monthly variations. , The relationship between sediment fluxes and meteorological parameters showed the magnitude of correlation coefficient (r) and strength of correlation varied significantly. At daily scales, the relationship of NH-N and NO-N had a significant positive correlation with all meteorological parameters. At monthly, the correlation coefficient (r) of NH-N and NON were heterogenous. At daily and monthly scales, air temperature and wind speed are the main drivers affecting sediment N loads' dynamics; however, the influence of relative humidity, precipitation, and evaporation on N loads are smaller. The study demonstrates the contribution of meteorological conditions to the magnitude and timing of N loadings variability in water bodies. The findings provide more insight into lake ecosystem protection and environmental remediation.
气候变暖导致沉积物中过量氮（N）负荷有利于富营养水体中的蓝藻水华。硝酸盐（NO3-N）和氨氮（NH4-N）是导致藻类大量繁殖的两种 N 负荷形式。然而，人们很少关注环境因素对不同时间尺度 N 负荷变化的影响。本文使用经过良好校准和验证的 EFDC 模型，研究了 2016 年 6 月至 2017 年 6 月期间铵和硝酸盐的时间模式和趋势。本文利用卫星和基于再分析的观测数据，展示了这些变化与六种气象参数之间的关系和影响。还在不同时间尺度（即每日、每月和季节性尺度）上研究了这些变化与环境因素之间的关系和影响。模型校准结果表明，实测值与模拟值相当吻合。验证结果表明，相对误差（RE）值在可接受范围内。太湖东部（S12）和胥湖（S23）采样点的铵的相对误差（RE）分别为 55.83%和 57.61%，而硝酸盐的相对误差（RE）分别为 24.37%（S12）和 41.08%。NH-N 和 NO-N 变化的日分析结果分别为 7.318 ± 3.876（g/m/d）和 0.0275 ± 0.222（g/m/d）。每月分析显示，NH-N 和 NON 的范围分别为 2.04 至 12.04（g/m/d）和 0.0008 至 0.064（g/m/d）。NH-N 和 NO-N 的变化幅度较大，且具有明显的月际变化。沉积通量与气象参数之间的关系表明，相关系数（r）的大小和相关性的强弱变化显著。在日尺度上，NH-N 和 NO-N 与所有气象参数呈显著正相关。在月尺度上，NH-N 和 NON 的相关系数（r）不均匀。在日尺度和月尺度上，气温和风速是影响沉积物 N 负荷动态的主要驱动因素，而相对湿度、降水和蒸发对 N 负荷的影响较小。本研究表明了气象条件对水体 N 负荷变化幅度和时间的贡献。研究结果为湖泊生态系统保护和环境修复提供了更深入的了解。
