Evaluating the potential of Sentinel-2 satellite images for water quality characterization
of artificial reservoirs: The Bin El Ouidane Reservoir case study (Morocco)
Karaoui Ismail, A. Boudhar, A. Abdelkrim, H. Mohammed, Sabri el Mouatassime, Ait Ouhamchich Kamal, Elhamdouni Driss, El Amrani Idrissi, Wafae Nouaim
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引用次数: 30
Abstract
Monitoring water quality in large dams is becoming a necessity for protecting stored water from various forms of pollution. This process requires analysis of several samples on a weekly or monthly basis. Our study aims to determine the relationship between water quality parameters (WQP) and digital data from the Sentinel-2 satellite to estimate and map the WQP in the Bin El Ouidane Reservoir. The in situ sampling was carried out in the Bin El Ouidane Reservoir (Azilal Province), followed by analysis of physicochemical parameters in the laboratory. These measurement results were compared with the reflectance in each sampling location to investigate the correlations between bands and laboratory chemical analysis results. The correlation results showed that all studied parameters have an R greater than 0.52, and they can be transformed to predictive models by stepwise regression. The accuracy of our proposed models was tested using the Oum Er-Rbia Hydraulic Basin Agency data, and the results showed that only three parameters yield admissible verification results (Chlorophyll A, dissolved Oxygen and Nitrate). Those models were then used in geographic information system software to produce a thematic map of each parameter over the entire surface of the reservoir. As a conclusion, the Sentinel-2 images could help indicate the eutrophication stage in the Bin El Ouidane Reservoir, which is a major risk in major Moroccan reservoirs.
评价Sentinel-2卫星图像对人工水库水质特征的潜力:Bin El Ouidane水库案例研究(摩洛哥)
监测大型水坝的水质正成为保护储水不受各种形式污染的必要条件。这个过程需要每周或每月分析几个样品。本研究旨在确定水质参数(WQP)与Sentinel-2卫星数字数据之间的关系,以估算和绘制Bin El Ouidane水库的WQP。在Bin El Ouidane水库(Azilal省)进行了现场采样,随后在实验室进行了理化参数分析。将这些测量结果与每个采样位置的反射率进行比较,以研究波段与实验室化学分析结果之间的相关性。相关结果表明,所有研究参数的R值均大于0.52,可以通过逐步回归转化为预测模型。利用欧姆Er-Rbia水力盆地管理局的数据对我们提出的模型的准确性进行了测试,结果表明只有三个参数(叶绿素A、溶解氧和硝酸盐)产生了可接受的验证结果。然后将这些模型用于地理信息系统软件,以在水库的整个表面上生成每个参数的专题地图。综上所述,Sentinel-2图像可以帮助指示Bin El Ouidane水库的富营养化阶段,这是摩洛哥主要水库的主要风险。