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Article

Simulation of Chlorophyll a Concentration in Donghu Lake Assisted by Environmental Factors Based on Optimized SVM and Data Assimilation

by 1 and 2,*
1
School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
2
School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
*
Author to whom correspondence should be addressed.
Academic Editor: Thomas Meixner
Water 2022, 14(15), 2353; https://doi.org/10.3390/w14152353
Received: 20 June 2022 / Revised: 22 July 2022 / Accepted: 26 July 2022 / Published: 29 July 2022
(This article belongs to the Section Water Quality and Contamination)
Lake eutrophication is a global water environmental problem and has become a research focus nowadays. Chlorophyll a concentration is an important index in terms of evaluating lake eutrophication. The aim of this study was to build an effective and universal empirical model for simulation of chlorophyll a concentration in Donghu Lake. On the basis of the relationship between chlorophyll a concentration and dissolved oxygen (DO), water temperature (T), total nitrogen (TN), and total phosphorus (TP), models for simulating chlorophyll a concentration were built by using simulated annealing (SA), genetic algorithm (GA), artificial bee colony (ABC), and particle swarm optimization (PSO) to optimize parameters of support vector machine (SVM). Moreover, a collaborative mode (Col-SVM model) was built by introducing data assimilation, and meanwhile, accuracy and universality of the model were studied. Modeling results showed that the application of optimization algorithms and data assimilation improved the performance of modeling based on SVM. Model simulation results demonstrated that the Col-SVM model has high accuracy, decent stability, and good simulation effect; the root mean square error (RMSE), mean absolute percentage error (MAPE), Nash–Sutcliffe efficiency coefficient (NSE), bias, and mean relative error (MRE) between simulated values and observed values were 10.07 μg/L, 0.31, 0.96, −0.050, and 0.15, respectively. In addition, model universality analysis results revealed that the Col-SVM model has good universality and can be used to simulate the chlorophyll a concentration of Donghu Lake at different times. Overall, we have built an effective and universal simulation model of chlorophyll a concentration that provides a new idea and method for chlorophyll a concentration modeling. View Full-Text
Keywords: chlorophyll a concentration; support vector machine; optimization algorithm; data assimilation; Donghu Lake chlorophyll a concentration; support vector machine; optimization algorithm; data assimilation; Donghu Lake
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MDPI and ACS Style

Tang, X.; Huang, M. Simulation of Chlorophyll a Concentration in Donghu Lake Assisted by Environmental Factors Based on Optimized SVM and Data Assimilation. Water 2022, 14, 2353. https://doi.org/10.3390/w14152353

AMA Style

Tang X, Huang M. Simulation of Chlorophyll a Concentration in Donghu Lake Assisted by Environmental Factors Based on Optimized SVM and Data Assimilation. Water. 2022; 14(15):2353. https://doi.org/10.3390/w14152353

Chicago/Turabian Style

Tang, Xiaodong, and Mutao Huang. 2022. "Simulation of Chlorophyll a Concentration in Donghu Lake Assisted by Environmental Factors Based on Optimized SVM and Data Assimilation" Water 14, no. 15: 2353. https://doi.org/10.3390/w14152353

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