Bayesian networks application to forecast the national economies development taking into account the water factor

Abstract

The influence of this factor on the development of national economies is studied. This study uses the Bayesian network, which illustrates the interaction of indicators of water supply and water use and includes nodes that are formally represented as vectors. The most valuable result of the modelling is not the general forecast obtained with the help of the model, but the structure of the network itself, which allows to identify connections within the model and explain the reason for the emerging interdependencies. modelling using Bayesian networks confirmed the fact that there is a direct relationship between GDP and water consumption and drainage. The obtained results confirm the possibility of achieving an increase in the overall GDP of the country with an increase in the amount of water resources used for production needs. However, this should be implemented in combination with a simultaneous reduction in the volume of return (wastewater) discharged into surface water bodies.