Prediction of Phytoplankton Biomass in Small Rivers of Central Spain by Data Mining Method of Partial Least-Squares Regression

Juan Carlos García-Prieto,Manuel G Roig,Francisco Javier Burguillo Muñoz,José Bernardo Proal-Najera

doi:10.3390/ecws-4-06427

Juan Carlos García-Prieto, Manuel G Roig + Show 2 more

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https://doi.org/10.3390/ecws-4-06427

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Abstract

The Water Framework Directive (WFD, EC, 2000) states that the “good” ecological status of natural water bodies must be based on their chemical, hydromorphological and biological features, especially under drastic conditions of floods or droughts. Phytoplankton is considered a good environmental bioindicator (WFD) and climate change has a strong impact on phytoplankton communities and water quality. The development of robust techniques to predict and control phytoplankton growth is still in progress. The aim of this study is to analyze the impact of the different stressors associated with the change in phytoplanktonic communities in small rivers in the center of the Iberian Peninsula (Southwestern Europe). A statistical study on the identification of the essential limiting variables in the phytoplankton growth and its seasonal variation by climate change was carried out. In this study, a new method based on the partial least-squares (PLS) regression technique has been used to predict the concentration of phytoplankton and cyanophytes from 22 variables usually monitored in rivers. The predictive models have shown a good agreement between training and test data sets in rivers and seasons (dry and wet). The phytoplankton in dry periods showed greatest similarities, these dry periods being the most important factor in the phytoplankton proliferation

Highlights

The Water Framework Directive (WFD, EC, 2000) states that the “good” ecological status of natural water bodies must be based on their chemical, hydromorphological and biological characteristics, compared to the reference conditions [1]
To comply with the protection of surface waters established in the Water Framework Directive, it is necessary to monitor the ecological and chemical status of water quality, especially under drastic conditions of floods or droughts due to the greater epidemiological risk that occur during these periods
A new methodology, based on the multivariate regression technique partial least-squares (PLS), has been proposed in this work, which allows, based on 22 variables usually monitored in rivers, the concentration of phytoplankton and cyanophytes to be predicted

Summary

Introduction

The Water Framework Directive (WFD, EC, 2000) states that the “good” ecological status of natural water bodies must be based on their chemical, hydromorphological and biological characteristics, compared to the reference conditions [1]. With regard to environmental and climatic conditions, phytoplankton depends on light intensity and temperature since they affect the speed of photosynthetic processes [9,10] on the level of the water surface since a low flow rate and a decrease in the level of water in rivers produces an increase of phytoplankton [11]. Other studies have shown that increasing organic carbon and nutrient inputs from landfills can lead to changes in the competitive dynamics between bacteria and phytoplankton, reducing phytoplankton biomass and increasing bacterial abundance [5]. In this sense, climate change affects ecosystems on a planetary scale [12] and is especially important in some regions around the world. The effects of drought on the hydrology of the Mediterranean basins has been studied [15,16,17,18,19] since it is expected that the effects—in terms of frequency and intensity—of the hydrological drought will be more severe due to climate change

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