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Water Resources Management
Published in: Water Resources Management 15/2020

04-11-2020

A New Predictive Model for Evaluating Chlorophyll-a Concentration in Tanes Reservoir by Using a Gaussian Process Regression

Authors: Paulino José García-Nieto, Esperanza García-Gonzalo, José Ramón Alonso Fernández, Cristina Díaz Muñiz

Published in: Water Resources Management | Issue 15/2020

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Abstract

Chlorophyll-a (hereafter referred to as Chl-a) is a recognized indicator for phytoplankton abundance and biomass –hence, an effective estimation of the trophic condition– of water bodies as lakes, reservoirs and oceans. Indeed, Chl-a is the primary molecule responsible for photosynthesis. A strong and robust Bayesian nonparametric technique, termed Gaussian process regression (GPR) approach, for foretelling the dependent variable Chl-a concentration in Tanes reservoir from a dataset concerning to 268 samples is shown in this paper. Ten years (2006–2015) of monitoring water quality variables (biological and physico-chemical independent variables) in the Tanes reservoir were used to build this mathematical GPR-relied model. As an optimizer, the method known as Limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGSB) iterative algorithm was used; this allows the selection of kernel optimal parameters during the GPR training phase, which greatly determines the regression precision. The results of the current investigation can be summarized in two. Firstly, the relevance of each input variable on Chl-a concentration in Tanes reservoir is determined. Secondly, the Chl-a can be successfully predicted using this hybrid LBFGSB/GPR–relied model (R2 and r values were 0.8597 and 0.9306, respectively). The concordance between observed data and the model clearly proves the high efficiency of this innovative approach.
previous article Comparison of Several Aggregation Techniques for Deriving Analytic Network Process Weights
next article Trends in Demand of Urban Surface Water Extractions and in Situ Use Functions

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Metadata
Title
A New Predictive Model for Evaluating Chlorophyll-a Concentration in Tanes Reservoir by Using a Gaussian Process Regression
Authors
Paulino José García-Nieto
Esperanza García-Gonzalo
José Ramón Alonso Fernández
Cristina Díaz Muñiz
Publication date
04-11-2020
Publisher
Springer Netherlands
Published in
Water Resources Management / Issue 15/2020
Print ISSN: 0920-4741
Electronic ISSN: 1573-1650
DOI
https://doi.org/10.1007/s11269-020-02699-x

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