| Autor: |
Gunawardana, Menik Hitihami M. A. S. V., Sanjaya, Kelum, Atapaththu, Keerthi S. S., Yapa Mudiyanselage, Ajith L. W. Y., Masakorala, Kanaji, Widana Gamage, Shirani M. K. |
| Předmět: |
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| Zdroj: |
Journal of Water & Health; Sep2022, Vol. 20 Issue 9, p1364-1379, 16p |
| Abstrakt: |
This study aimed to develop an empirical model to predict the spatial distribution of Aphanizomenon using the Ridiyagama reservoir in Sri Lanka with a dual-model strategy. In December 2020, a bloom was detected with a high density of Aphanizomenon and chlorophyll-a concentration. We generated a set of algorithms using in situ chlorophyll-a data with surface reflectance of Sentinel-2 bands on the same day using linear regression analysis. The in situ chlorophyll-a concentration was better regressed to the reflectance ratio of (1 + R665)/(1–R705) derived from B4 and B5 bands of Sentinel-2 with high reliability (R² = 0.81, p < 0.001). The second regression model was developed to predict Aphanizomenon cell density using chlorophyll-a as the proxy and the relationship was strong and significant (R² = 0.75, p<0.001). Coupling the former regression models, an empirical model was derived to predict Aphanizomenon cell density in the same reservoir with high reliability (R² = 0.71, p<0.001). Furthermore, the predicted and observed spatial distribution of Aphanizomenon was fairly agreed. Our results highlight that the present empirical model has a high capability for an accurate prediction of Aphanizomenon cell density and their spatial distribution in freshwaters, which helps in the management of toxic algal blooms and associated health impacts. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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