基于MODIS数据的太湖浮游植物物候变化及其对水表温度的响应
洪恬林(1995— ),女,江苏无锡人,硕士生,主要从事水环境遥感研究。E-mail: hestia945@foxmail.com |
收稿日期: 2020-04-28
要求修回日期: 2020-08-12
网络出版日期: 2020-12-25
基金资助
国家重点研发计划项目(2017YFB0503902)
版权
Patterns of Phytoplankton Phenology and Its Response to Temperature of Water Surface in Lake Taihu based on MODIS Data
Received date: 2020-04-28
Request revised date: 2020-08-12
Online published: 2020-12-25
Supported by
National Key Research and Development Program of China(2017YFB0503902)
Copyright
浮游植物物候能够反映浮游植物的生长变化与湖泊生态系统的变化,水温、营养盐浓度等因素对物候有重要影响。太湖富营养化程度较高,水温的影响作用日趋显著,物候与水温关系的研究对理解、控制和改善太湖生态系统具有重要意义。本研究利用2003—2018年MODIS遥感数据计算浮游植物物候指标和湖泊水表温度(Temperature of Water Surface,LSWT),通过分析太湖浮游植物物候时空变化特点探究了不同区域的物候特征,并结合LSWT揭示了浮游植物物候对LSWT变化的响应关系。结果表明:① 不同浮游植物物候指标具有不同空间分布特点,水华发生次数、峰值叶绿素a(Chla)浓度和水华总持续时间呈现由西部沿岸向湖心区递减的趋势;浮游植物生长开始时间和峰值Chla发生时间分布复杂但在沿岸区域相对较早;② 太湖可被划分为4种具有不同物候特征的区域,Ⅰ类区域主要位于贡湖湾、东部沿岸以及太湖中部开阔水域,该区Chla浓度范围为50~60 μg/L,且波动平缓,水华发生次数最少、开始最晚、持续时间最短;Ⅱ类区域主要分布于太湖西部沿岸,Chla浓度范围为50~90 μg/L且变化剧烈,该区水华发生次数最多、开始最早、持续时间最长;Ⅲ和Ⅳ类属于过渡区域,前者主要分布于梅梁湾、竺山湾及入湾口,后者主要位于南部沿岸以及太湖中部;③ 浮游植物物候对LSWT变化的响应受营养水平影响,当营养水平较高时,浮游植物的生长受LSWT的促进作用显著,LSWT年际变化的升高趋势对浮游植生长物候提前、生物量增加的影响明显,反之,则LSWT变化对浮游植物生长的影响减弱。
洪恬林 , 李云梅 , 吕恒 , 孟斌 , 毕顺 , 周玲 . 基于MODIS数据的太湖浮游植物物候变化及其对水表温度的响应[J]. 地球信息科学学报, 2020 , 22(10) : 1935 -1945 . DOI: 10.12082/dqxxkx.2020.200206
Due to the influence of water temperature and nutrient concentration, phytoplankton phenology can reflect the growth of phytoplankton and the changes of lake ecosystem. Because of the serious eutrophication in Lake Taihu, the effect of water temperature on phytoplankton growth is more and more significant. Thus, it is of great significance to study the relationship between phenology and water temperature for understanding, controlling and improving the ecosystem of Lake Taihu. This study firstly calculated the phytoplankton phenology metrics and the Temperature of Water Surface (LSWT) by MODIS data from 2003 to 2018, and then explored the phenological characteristics of different regions by analyzing the temporal-spatial distribution variation of phytoplankton phenology. At last, the response of phytoplankton phenology to LSWT change was revealed by combining the LSTW and the phenological characteristics. The results showed that: ① Different phytoplankton phenological indexes had different spatial distribution characteristics. The number of blooms, the peak value of Chlorophyll a (Chla) concentration and the total duration of algal blooms showed a decreasing trend from the western coast to the center of lake; the dates when the phytoplankton began to grow and the Chla peak appeared were complex in the lake. However, the date was relatively early in the coastal area; ② Lake Taihu could be divided into four types of areas with different phenological characteristics. The Type I area was mainly located in Gonghu Bay, eastern coast and the central part of Lake Taihu, where the fluctuation of Chla concentration (50~60 μg/L) was gentle, the number of blooms was the lowest, the start date was the latest, and the duration was the shortest. Type II area was mainly distributed along the western coast, with the violently fluctuating Chla concentration (50~90 μg/L), the most frequent blooms, the earliest onset, and the longest duration. Types III and IV were the transition areas. The former was mainly distributed in Meiliang Bay, Zhushan Bay and their exits, while the latter was mainly located in the southern coast and central lake. ③ The response of phytoplankton phenology to LSWT changes was affected by the level of nutrients. When the nutrient level was high, the promotion effect of LSWT on phytoplankton growth was more significant. The increasing trend of inter-annual LSWT had obvious influence on the advance of phytoplankton phenology and the increase of biomass. On the contrary, the effect of LSWT on the growth of phytoplankton was weakened.
图3 2003—2018年太湖水华发生次数空间分布Fig. 3 Spatial distribution of the number of blooms in Lake Taihu from 2003 to 2018 |
图4 2003—2018年太湖浮游植物生长开始时间空间分布Fig. 4 Spatial distribution of phytoplankton growth start date in Lake Taihu from 2003 to 2018 |
图5 2003—2018年太湖水华开始时间空间分布Fig. 5 Spatial distribution of bloom start date in Lake Taihu from 2003 to 2018 |
图6 2003—2018年太湖峰值Chla浓度空间分布Fig. 6 Spatial distribution of chla concentration peak in Lake Taihu from 2003 to 2018 |
图7 2003—2018年太湖水华平均持续时间空间分布Fig. 7 Spatial distribution of average bloom duration in Lake Taihu from 2003 to 2018 |
图10 太湖各区域不同浮游植物物候指标箱型图(水华事件)Fig. 10 Box plots of different phytoplankton phenology metrics in various regions of Lake Taihu (blooming events) |
图13 2003—2018年LSWT下的水华开始时间和峰值Chla发生时间(水华事件)Fig. 13 Bloom start date and peak Chla occurrence time under LSWT from 2003 to 2018 (blooming events) |
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