Code and data for probabilistic algal biomass forecasting in Lake Dianchi using Bayesian additive regression trees

This dataset supports a study of 1- to 5-day-ahead chlorophyll-a forecasting in Lake Dianchi using BART. It includes processed daily water-quality observations from Huiwanzhong Station obtained from the China National Environmental Monitoring Center, together with R code and model outputs. The results show that BART provides competitive point accuracy while enabling uncertainty quantification and model explanation.