Numerical study on the influences of complicated hydrological processes on water, heat and salt in the tidal river wetland
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摘要: 长江下游感潮河段水文条件复杂,针对其对滨岸湿地水热盐的影响及季节性差异的认识较为匮乏。以长江南京段绿水湾湿地为研究对象,监测湿地水文变化及信号特征,构建湿地水热运移与氮迁移转化模型,揭示潮汐过程对湿地水热储量和除氮的影响及其季节性差异。研究结果表明:湿地水位水温变化包含径流和潮汐两个信号特征,春夏季径流较强,而秋冬季潮汐波动幅度较大。春夏季河流水位水温升高,水土界面溶解氧降低,径流驱动下的湿地除氮量约为秋冬季的3~5倍。但秋冬季潮汐波动幅度约为春夏季的2倍,显著增强了湿地的除氮量,在径流驱动基础上提升脱氮效率约为63%和31%,为春夏季的2.5~5.0倍。研究结果可为长江下游滨岸带生态环境保护提供理论依据。Abstract: Although the hydrological state of the lower Yangtze River’s tidal portion is quite complex, its effects on the dynamics of the wetland water, heat, and salt are not well understood. This study used the Lvshuiwan wetland in the Nanjing section of the Yangtze River as its research subject. We tracked the wetland’s hydrological changes and their signal characteristics, built a model of the wetland’s hydrothermal transport and nitrogen migration and transformation, and discussed how tidal processes affected the wetland’s hydrothermal storage and nitrogen removal as well as its seasonal variations. The findings indicated that runoff and tide, with significant runoff in spring and summer and increased tidal fluctuation in autumn and winter, are two signal characteristics that contribute to changes in water level and temperature in the wetland. The amount of nitrogen removed from the wetland due to runoff is three to five times more during spring and summer due to the rise in river water level, temperature, and dissolved oxygen at the water-soil interface. Nevertheless, the amplitudes of tidal fluctuations in autumn and winter are roughly twice as large as those in spring and summer, which significantly improves the nitrogen removal of the wetland and increases the nitrogen removal efficiency by about 63% and 31% on the basis of that driven by runoff, making it about 2.5–5 times as large as in spring and summer. The findings of the study offer a theoretical framework for the ecological protection of the tidal river wetland in the lower Yangtze River.
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Key words:
- tidal river /
- wetland /
- hydrologic process /
- denitrification /
- numerical simulation
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表 1 湿地水动力-水质模型参数率定结果
Table 1. Calibration results of hydrodynamic-water quality model parameters
模型 参数 率定值 单位 来源 水动力模型 渗透系数(K) 0.5 m·d−1 Carsel等 [15] 有效孔隙率(ne) 0.25 - Carsel等 [15] 单位储水量(S0) 0.001 m−1 Carsel等 [15] 剩余饱和度(θr) 0.146 - Carsel等 [15] 最大饱和度(θs) 0.98 - Carsel等 [15] 滞留曲线拟合参数($ \xi $) 7.5 m−1 Carsel等[15] 孔径分布指数(N) 1.89 - Carsel等 [15] 纵向弥散度(DL) 5 m Triska等[16] 纵向/横向弥散度(DL / DT) 1 - Triska等[16] 水质模型 上覆水O2质量体积分数 - mg·L−1 实测时段序列 上覆水NH4+质量体积分数 - mg·L−1 实测时段平均 上覆水NO3−质量体积分数 - mg·L−1 实测时段平均 上覆水DOC质量体积分数 - mg·L−1 实测时段平均 地下水O2、NH4+、NO3−、DOC质量体积分数 - mg·L−1 实测时段平均 单位最大有氧呼吸速率(UAR) 2 mg·L−1·d−1 Shuai等[17]、Gu等[18] 单位最大硝化速率(UNI) 1.05k1 mg·L−1·d−1 Shuai等[17]、Gu等[18] 单位最大反硝化速率(UDN) 2k2 mg·L−1·d−1 Shuai等[17]、Gu等[18] O2半饱和常数($K_{{\rm{O}}_2} $) 1 mg·L−1 Shuai等[17]、Gu等[18] NH4+半饱和常数($K_{{\rm{NH}}_4} $) 0.5 mg·L−1 Shuai等[17]、Gu等[18] NO3−半饱和常数($K_{{\rm{NO}}_3} $) 1 mg·L−1 Shuai等[17]、Gu等[18] DOC半饱和常数(KDOC) 5 mg·L−1 Shuai等[17]、Gu等[18] O2抑制常数(KI) 1 mg·L−1 Zarnetske等 [19] O2分配系数($y_{{\rm{O}}_2} $) 0.64 - Zarnetske等 [19] 注:k1、k2分别是硝化、反硝化功能微生物介导系数的修正系数,与水土界面溶解氧质量体积分数(CDO)、温度(T)存在无量纲定量关系[17-19]:k1 = [CDO]·T/180,k2 = 9[T]/(20[CDO])。 表 2 湿地不同季节水文特征对比
Table 2. Comparison of hydrological characteristics of the tidal river wetland in different seasons
季节 时段 地表水-地下水
初始水力梯度地表水-地下水初始
温度差/ ℃地表水位径流信号
波动幅度/m地表水位潮汐信号
平均波动幅度/m地表水溶解氧/
(mg·L−1)冬季 2021-12-31—2022-01-15 −0.190 −9.0 0.25 0.96 10.54~14.86 春季 2022-04-27—2022-05-12 0.006 3.0 0.48 0.55 7.39~8.20 夏季 2022-06-20—2022-07-05 0.022 9.0 0.73 0.30 5.33~6.31 秋季 2022-10-19—2022-11-03 −0.030 1.5 0.26 1.12 7.07~9.04 表 3 不同季节除氮情况对比
Table 3. Comparison of nitrogen removal of the tidal river wetland in different seasons
季节 时段 径流信号日均
脱氮量/(g·m−1)实际水位日均
脱氮量/(g·m−1)潮汐信号日均
脱氮量/(g·m−1)潮汐信号脱氮
效率提升/%冬季 2021-12-31—2022-01-15 0.76 1.10 0.34 31 春季 2022-04-27—2022-05-12 1.40 1.61 0.21 13 夏季 2022-06-20—2022-07-05 2.58 2.93 0.35 12 秋季 2022-10-19—2022-11-03 0.49 1.32 0.83 63 -
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