Research on Hydrogeology and Water Resources Evaluation Based on Big Data Technology

Abstract

With the development of science and technology, the amount of hydrological information data has undergone tremendous growth. How to fully utilize these large-scale data to support decision-making and water resource evaluation is currently a problem faced by scientists and society. In the traditional process of water resource allocation, the calculation of reservoir water balance results in a huge amount of abandoned water, resulting in the waste of a large amount of available water resources. By training Big data, the model self-learning can quickly analyze the characteristics of the river water level discharge relationship, fit the water level discharge relationship curve, and obtain the water balance, which reduces the number of flow measurements required to fit the water level discharge relationship curve by traditional methods, thus reducing errors, improving accuracy, and reducing time and economic costs.