Water bodies eutrophication is a worldwide environmental problem characterized by excessive phytoplankton growth which often includes occurrence of harmful algal blooms events. Chlorophyll-a concentration is widely used as an indicator of biomass and can be quantified by optic sensors. In this work, we use a satellite derived Chlorophyll-a concentration time series for the period 2001–2014 obtained from MODIS/TERRA data to detect and characterize algal bloom events in an eutrophic reservoir. Our results demonstrate that fixed threshold methods identify too many bloom dates but a dynamic method based on frequencies analysis and statistical approach, performed better because it represents the normal phytoplankton mass and a bloom is identified like a deviation from it. This approach was tested in San Roque reservoir which supplies fresh water to Córdoba city, one of the most populated of Argentina. According to Carlson index values, this is an eutrophic to hypereutrophic water body. Validation of log₁₀ (Chlorophyll-a concentration) derived from satellite model concentration with ground-based measurements data of Chlorophyll-a concentration demonstrates an acceptable error (RMSE = 0.59) considering data distribution. The implementation of the proposed method to identify blooms over a control data set and validated with LANDSAT 8 - OLI images, demonstrates that the approach described is robust and stable over time.

水体富营养化是一个全球性的环境问题，其特征是浮游植物过度生长，通常包括有害藻华的发生。叶绿素a的浓度被广泛用作生物量的指标，可以通过光学传感器进行定量。在这项工作中，我们使用从MODIS / TERRA数据获得的卫星衍生的2001-2014年叶绿素a浓度时间序列，来检测和表征富营养化水库中的藻华事件。我们的结果表明，固定阈值方法可以识别出过多的开花日期，但是基于频率分析和统计方法的动态方法表现更好，因为它代表正常的浮游植物质量，并且可以识别出与其相反的开花。这种方法在圣罗克水库进行了测试，该水库为阿根廷人口最多的科尔多瓦市提供淡水。根据卡尔森指数值，这是富营养化至富营养化的水体。验证日志从卫星模型浓度和基于叶绿素a浓度的地面测量数据得出的₁₀（叶绿素a浓度）在考虑数据分布的情况下显示出可接受的误差（RMSE = 0.59）。所提出的方法来识别控制数据集上的水华并用LANDSAT 8-OLI图像进行验证，该方法的实施证明了所描述的方法在时间上是稳健而稳定的。