Abstract
This paper presents a processed phytoplankton dataset from Lake Zerendi and other Kokshetau Upland lakes, Kazakhstan. The study aimed to develop an automated method for controlling the distribution of phytoplankton in fresh open water using a gradient descent approach with the search for a starting point for research. The paper also presents the reconstructed biomass indicators for changes in water temperature, with model calibration based on results from 5 years of surface sampling. A special feature of the proposed computer data processing is the cubic spline interpolation, which allows a higher calculation accuracy. This method reduces the sample size required, providing a comprehensive picture of the condition of the infrastructure and allowing for a more efficient response to emerging ecosystem issues.