Chlorophyll-A Time Series Study on a Saline Mediterranean Lagoon: The Mar Menor Case
The Mar Menor, Europe’s largest saline lagoon, has experienced significant eutrophication. The concentration of chlorophyll-a (Chl-a) in the water is used as a critical indicator of this eutrophication process and can alert us to possible ecosystemic changes such as a massive fish die-off. The main...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-09-01
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| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/68/1/65 |
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| Summary: | The Mar Menor, Europe’s largest saline lagoon, has experienced significant eutrophication. The concentration of chlorophyll-a (Chl-a) in the water is used as a critical indicator of this eutrophication process and can alert us to possible ecosystemic changes such as a massive fish die-off. The main objective of this paper is to predict chlorophyll-a concentration using various time series models. Among them, multivariate models such as short-term memory networks (LSTM) and, in particular, the autoregressive integrated moving average model with eXogenous variables (ARIMAX) demonstrated superior performance. These models incorporate multiple predictors, such as humidity, water temperature, conductivity and turbidity, thus capturing the complex interactions that affect Chl-a levels. Despite their effectiveness, these multivariate models introduce cascading errors due to the uncertainty inherent in the exogenous inputs. Consequently, the application of univariate models—such as Prophet, Triple Exponential Smoothing and ARIMA—are also studied for their relative robustness to error propagation. |
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| ISSN: | 2673-4591 |