Wang Huan, Chen Wen-Bo, He Lei, Li Hai-Feng
College of Land Resource and Environment, Jiangxi Agricultural University, Nanchang 330045, China.
Nanchang Key Laboratory of Landscape and Environment, Nanchang 330045, China.
Ying Yong Sheng Tai Xue Bao. 2022 Jan;33(1):191-200. doi: 10.13287/j.1001-9332.202201.013.
The variation of water level is the main environmental factor controlling the growth of aquatic vegetation. It is of significance to understand its influences on aquatic vegetation coverage in sub-lakes under different hydrolo-gical control modes. Taking the free connected sub-lake Bang Lake and locally controlled sub-lake Dahuchi Lake of Poyang Lake as a case and based on remote sensing cloud computing platform of the Google Earth Engine (GEE), we used the pixel binary model to estimate aquatic vegetation coverage from 2000 to 2019, and analyzed the temporal and spatial differentiation characteristics, and the variation trend was simulated by combining the method of Sen+M-K. We analyzed the water level change characteristics during the study period and the relationship between the hydrological parameters and the aquatic vegetation coverage area of sub-lakes with different hydrological connectivity was explored by setting up the water level fluctuation parameters. The results showed that the aquatic vegetation coverage of Bang Lake was more susceptible to water level changes, while Dahuchi Lake was more stable. The aquatic vegetation was patchily and sporadically distributed in the years with low vegetation coverage. In the years with high vegetation coverage, it was distributed in a ring-like pattern, spreading from the center of the lake to the shore. The aquatic vegetation coverage of Bang Lake was more likely influenced by water level fluctuation rate, while the aquatic vegetation coverage of Dahuchi Lake was more likely influenced by the flooding duration of 17 m characteristic water level. The flooding duration of 19 m characteristic water level had a strong negative correlation with the aquatic vegetation coverage of Bang Lake and Dahuchi Lake. The trend of aquatic vegetation in Bang Lake was dominated by stabilization and slight improvement, while that in Dahuchi Lake was dominated by stabilization and significant degradation. Our results could help to further understand the dynamics of water hydrological ecosystem with different hydrological connectivity and provide a reference for lake management and conservation.
水位变化是控制水生植被生长的主要环境因素。了解其在不同水文控制模式下对子湖水生植被覆盖度的影响具有重要意义。以鄱阳湖自由连通子湖蚌湖和局部控制子湖大池湖为例，基于谷歌地球引擎（GEE）遥感云计算平台，利用像元二分模型估算2000—2019年水生植被覆盖度，分析其时空分异特征，并结合Sen+M-K法模拟变化趋势。分析研究期间的水位变化特征，通过设置水位波动参数，探讨不同水文连通性子湖的水文参数与水生植被覆盖面积的关系。结果表明，蚌湖的水生植被覆盖度对水位变化更敏感，而大池湖更稳定。在植被覆盖度较低的年份，水生植被呈斑块状、零星分布。在植被覆盖度较高的年份，呈环状分布，从湖心向岸边扩散。蚌湖的水生植被覆盖度更易受水位波动速率的影响，而大池湖的水生植被覆盖度更易受17 m特征水位淹没历时的影响。19 m特征水位的淹没历时与蚌湖和大池湖的水生植被覆盖度均呈显著负相关。蚌湖水生植被的变化趋势以稳定和略有改善为主，而大池湖水生植被的变化趋势以稳定和显著退化为主。研究结果有助于进一步了解不同水文连通性下水文生态系统的动态变化，为湖泊管理与保护提供参考。
