Applications of Artificial Intelligence in Water Resources Forecasting
Golmar Golmohammadi, Seyed Mostafa Biazar, Rohith Reddy Nedhunuri, and Nikolaos Tziolas
The advent of artificial intelligence (AI) and machine learning has permeated every aspect of our lives. Water resource management is becoming increasingly important due to the impacts of climate change and human activities. This publication provides examples of how AI can potentially improve the forecasting of water resource variables at both the field and regional levels. The main goal is to introduce new AI techniques for forecasting key environmental factors (climate, soil, water) related to water resources in Florida. The results demonstrate how deep learning models performed consistently well and established their superiority in capturing the temporal dynamics of river discharge and groundwater in the region. The results also show a dramatic groundwater level drawdown in certain areas, which could jeopardize the ability to meet water demands for agricultural purposes. The increase in river discharge and high groundwater levels might be related to flooding in those areas.
