Spatiotemporal distribution and prediction of chlorophyll-a in Ulansuhai lake from an arid area of China

Abstract

Lake Ulansuhai, a typical shallow lake in an arid area that is economically and ecologically important along the Yellow River, is currently eutrophic. Long-term (2010–2020) data on chlorophyll-a, nutrient, and environmental factors were obtained from three Lake Ulansuhai monitoring stations. The temporal and spatial distribution characteristics of Chl-a were analyzed. Additionally, a hybrid evolutionary algorithm was established to simulate and predict Chl-a, and sensitivity analysis revealed the interaction between environmental factors and eutrophication. The results indicated that (1) the seasonal variation of eutrophication showed an obvious trend of spring > summer > autumn > winter, and the concentration of Chl-a in the inlet was significantly higher than that in the outlet; (2) The inlet, center, and outlet of Ulansuhai Lake are satisfactorily affected by HEA in the best suited method. The fitting coefficients (R2) of the optimal models were 0.58, 0.59, and 0.62 for the three monitoring stations, and the root mean square errors (RMSE) were 3.89, 3.21, and 3.56, respectively; (3) under certain range and threshold conditions, Chl-a increased with the increase of permanganate index, water temperature, dissolved oxygen concentration, and ammonia nitrogen concentration, but decreased with the increase of water depth, Secchi disk depth, pH, and fluoride concentration. The results indicate that the HEA can simulate and predict the dynamics of Chl-a, and identify and quantify the relationships between eutrophication and the threshold data. The research results provide theoretical basis and technical support for the prediction and have great significance for the improvement of water quality and environmental protection in arid and semi-arid inland lakes.