نوع مقاله : ویژه نامه دریاچه ارومیه
نویسندگان
1 عضو هیات علمی، دانشگاه تربیت مدرس
2 مهندسی آب، دانشگاه تربیت مدرس
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Water quality management in inland lakes requires continuous monitoring of chlorophyll-a (Chl-a) concentration and trophic state. As a critical variable of eutrophication, concentration of Chl-a in the north of Lake Urmia was modeled using Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) models developed based on Landsat-8 and Sentinel-2 satellite images. Both models based on Landsat-8 images (ANNLandsat-8, MLRLandsat-8) accurately estimated Chl-a concentration in the north of Lake Urmia, while models based on Sentinel-2 images (MLRSentinel-2 and ANNSentinel-2) showed poor performances. Moreover, the ANN models based on both Landsat-8 and Sentinel-2 images performed slightly better than MLR models. Then, the optimum ANNlandsat-8 model (with a hidden layer) was used to analyze the spatiotemporal variation of Chl-a concentration and the trophic state index (TSI) of northern Lake Urmia. Analysis of the spatial pattern of Chl-a concentration showed an increase towards the central deeper parts of the lake and a decrease towards the causeway. Furthermore, the average Chl-a concentration and TSI in the north of the lake increased significantly from February to July followed by a drop from July to September and then a rise between September and October. Based on the optimum ANNLandsat-8 model, northern Lake Urmia experienced acute mesotrophic conditions in February and September of 2016, and mild eutrophic conditions in July, August, and October.
کلیدواژهها [English]
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