The effect of climate on water resources in Iraq using AI

Abstract

Climate change is increasingly affecting global water resources, considering their availability, quality, and distribution. The temperature rise, altered rainfall pattern, and extreme weather incidents further water challenges brought gains in vulnerable but dry areas. In this regard, the study adopted the utilization of AI, in particular, machine learning approaches for climate adaptation sciences concerning water resources. The models of decision tree, Naive Bayes, and linear regression evaluate relationships between temperature, humidity, wind speed, evaporation, and subsequent water balance using climatic data from 1991 to 2021 for three Iraqi governorates: Diwaniya, Najaf, and Karbala. The discovered trend indicates that rising temperature causes an increase in evapotranspiration brought about by water deficiency that persists. The application of AI in the research reflected that while the models can capture long-term phenomena at a gross scale, they are limited in making precise predictions, thereby making it imperative to develop solutions with ensemble learning and deep neural networks. Another thing gleaned from the study is the importance of AI as a complementary tool for water resource management based on data in the face of climate change. Another factor worthy of attention would be how to address the limits of the present when it comes to using data, model interpretability, and interdisciplinary integration so that we can define and implement sustainable climate adaptation options for tomorrow's water security. This study fills the gap in knowledge as it adopted a novel model using AI to predict the effect of climate change on water resources in Iraq. This study also opened a wide gate for future research in this domain.