Uncovering the influence of hydrological and climate variables in chlorophyll-A concentration in tropical reservoirs with machine learning

Climate variability and change, associated with increasing water demands, can have significant implications for water availability. In the Brazilian semi-arid, eutrophication in reservoirs raises the risk of water scarcity. The reservoirs have also a high seasonal and annual variability of water level and volume, which can have important effects on chlorophyll-a concentration (Chla). Assessing the influence of climate and hydrological variability on phytoplankton growth can be important to find strategies to achieve water security in tropical regions with similar problems. This study explores the potential of machine learning models to predict Chla in reservoirs and to understand their relationship with hydrological and climate variables. The model is based mainly on satellite data, which makes the methodology useful for data-scarce regions. Tree-based ensemble methods had the best performances among six machine learning methods and one parametric model. This performance can be considered satisfactory as classical empirical relationships between Chla and phosphorus may not hold for tropical reservoirs. Water volume and the mix-layer depth are inversely related to Chla, while mean surface temperature, water level, and surface solar radiation have direct relationships with Chla. These findings provide insights on how seasonal climate prediction and reservoir operation might influence water quality in regions supplied by superficial reservoirs.

Application and validation of a biotic ligand model for calculating acute toxicity of lead to Moina dubia in lakes of Hanoi, Vietnam

It is increasingly being recognized that biotic ligand models (BLMs) can successfully predict the toxicity of divalent metals toward aquatic biota applied to temperate freshwater ecosystems. However, studies on the eutrophic lakes in tropical regions toward native tropical organisms, including Moina, are relatively limited. In this study, Moina dubia, the native organism of the Hanoi eutrophic urban lakes, were used in toxicological studies of lead (Pb); 24-h EC₅₀ value of Pb was 523.19 µg/L under optimal living conditions for M. dubia in the laboratory. The constant binding of Pb²⁺ on M. dubia surface sites (log K_PbBL = 2.38) was significantly low. Other stability constants were obtained under experiments as logK_CaBL = 2.48, logK_MgBL = 2.80, logK_NaBL = 2.35, logK_KBL = 2.49, and logK_HBL = 3.026. A BLM was developed to calculate the acute toxicity (EC₅₀-24 h) of lead on M. dubia based on the condition of the urban lakes of Hanoi. Validation with toxicity data in synthetic medium showed a coefficient determination of 79.16% and a mean absolute percentage error (MAPE) of 10.2%, while the validation with the toxicity data with natural water medium from 11 Hanoi lakes showed a coefficient determination of 73.7% and a MAPE of 13.66%. The BLM worked well with water at a pH of 7.0 to 8.0, but failed with water at a pH above 8.0. Eutrophic conditions proved to have a significant effect on the toxicity of lead on local zooplankton.