Standard monitoring of lake water usually depends on monthly measurements that are affected by financing capabilities and weather conditions, often leading to various data being left out. Aiming to solve this issue, we enrolled on the task of developing a set of fitted equations allowing the researchers to predict the values of various water quality parameters even in situations when not all of the data are available. By implementing a serious of tests we were able to establish equations with reasonable adjusted correlation coefficient values suggesting feasible projections of the considered output parameters.
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