Satellite remote sensing technology presents advantages of macroscopicity, timeliness and cost effectiveness and has been increasingly used in lake water quality monitoring. In this paper, an empirical model for the remote sensing inversion of the chlorophyll a (Chl-a) concentration in Erhai Lake was established using ground monitoring Chl-a concentration data and multispectral remote sensing data from environmental satellites from 2010 to 2017. The average absolute error and relative error were 1.92 mg/m³ and 22%, respectively. A 10-year remote sensing inversion of Erhai blooms identified the temporal and spatial distribution characteristics of blooms and showed that the occurrence frequency of blooms was 37%, and they were mainly in the form of light algal blooms at a local scale. Moderate and severe blooms occurred at a frequency of 42%, mainly from Oct. to Jan. Moderate algal blooms were distributed along the southern and northern coasts and in coastal areas, while severe algal blooms were distributed in the northern section and across the entire lake. During the bloom period, the growth rate of the bloom area reached 102 km²/d, which was faster than the reduction rate (90 km²/d). Bloom events generally lasted for 6–37 days. The inflow of pollution sources led to a higher frequency of blooms in the coastal zone than in the lake center, and the frequency in the northern section was nearly twice as high as that in the southern section. Most blooms in Erhai Lake occurred from late summer to winter (i.e., Jul. to Jan. of the following year) because of the higher average air temperature (AT) and lower wind speed (WS) in winter and spring and the amount of precipitation in summer and autumn. The remote sensing method captured the high-risk areas and the spatial-temporal evolution trend of algal blooms, and the model provided support for the prevention and control of lake algal blooms; however, this work should be complemented by ground monitoring data for cloudy days.

卫星遥感技术具有宏观，及时性和成本效益的优势，已越来越多地用于湖泊水质监测中。本文利用地面监测Chl-a浓度数据和环境卫星2010年至2017年的多光谱遥感数据，建立了hai海湖泊叶绿素a（Chl-a）浓度遥感反演的经验模型。绝对误差和相对误差为1.92 mg / m ³和22％。对of海大花进行了10年的遥感反演，确定了大花的时空分布特征，发现大花的发生频率为37％，且主要以局部轻藻花的形式出现。中度和重度水华的发生频率为42％，主要是从10月到1月。中度水华的水华分布在南部和北部沿海以及沿海地区，而重度水华的水华分布在北部和整个湖泊中。 。在开花期，开花面积的增长率达到102 km ² / d，快于减少率（90 km ² / d）。/ d）。绽放事件通常持续6-37天。污染源的流入导致沿海地区的水华发生频率高于湖中心，而北部地区的水华发生频率几乎是南部地区的两倍。hai海的大部分水华发生在夏末至冬季（即次年的7月至次年的1月），这是因为冬季和春季的平均气温较高（AT），风速较低（WS）以及降水量较大在夏季和秋季。遥感方法捕捉到了高风险区和藻华的时空演化趋势，该模型为湖藻华的防治提供了支持。但是，这项工作应该在多云的日子得到地面监测数据的补充。