Intensification of the eutrophication process in surface water leads to an increase in the intensity and frequency of cyanobacterial blooms, compromising the availability of drinking water. Therefore, the aim of this study was to investigate the spatio-temporal dynamics of cyanobacteria and identify the most important nutrients for such dynamics in a semiarid artificial lake, the Orós reservoir, in north-eastern Brazil. Seventy-seven water samples were collected in 11 campaigns (six during the dry season and five during the rainy season) from seven points. The attributes under investigation were the Secchi transparency, turbidity, pH, apparent colour, electrical conductivity, total solids, total phosphorus, soluble orthophosphate content, total Kjeldahl nitrogen, ammonia content, nitrate content, and cyanobacteria dynamics, resulting in a total of 924 samples (number of campaigns × number of points × number of attributes). Principal component analysis and cluster analysis were used to investigate the significance and determinant attributes of the spatio-temporal dynamics of cyanobacteria. Of the 17 species of cyanobacteria identified, 10 accounted for 72.47% of the total accumulated variance. During the rainy season, four homogeneous groups of cyanobacteria formed, whereas during the dry season, only three groups formed. The greatest concentrations occurred during the dry season, notably for Aphanocapsa spp., Cylindrospermopsis sp., and Geitlerinema sp., which are potentially toxic and show a greater affinity to the physical attributes of water. Climate seasonality was decisive in the spatio-temporal dynamics of cyanobacteria, and high transparency values limited excessive proliferation of the dominant species.

Phosphorus input into surface water is a global concern due to its role in eutrophication, which is especially critical in semi-arid regions with their challenging climatic conditions. This study evaluated the best model for estimating the phosphorus decay coefficient (k) in semi-arid lakes, using flows from the Soil Moisture Accounting Procedure (SMAP), model of Génie Rural à 4 paramètres Journalier (GR4J), and reverse water balance hydrological models. Conducted at the Orós reservoir with 37 sampling campaigns from 2008 to 2017, it compared decay rates for temperate, tropical, and semi-arid climates. Some analyses also used phosphorus concentrations measured at the reservoir inlet. Model efficiency was assessed with bias, mean relative error, mean squared error, root mean squared error, and standard deviation. from the best models, water quality classes were classified based on phosphorus concentrations with the use of a confusion matrix to calculate accuracy, precision, recall, and F1 score. The findings demonstrated that the decay rate tailored for semi-arid regions, when combined with GR4J flow data, offered the highest accuracy in estimating phosphorus concentrations (bias = 0.0012, RMSE = 0.0326, EMR = 60.6134, STD = 0.0312). In contrast, the decay rate calibrated for tropical conditions with SMAP-derived flows proved superior for classifying water quality categories (classes defined by CONAMA Resolution 357/05). Therefore, the GR4J model for semi-arid conditions stands out for concentration estimation, while the tropical decay rate with SMAP flows is preferable for effective classification of water quality status.