Recent years have witnessed an upsurge of worldwide interest in potential impacts of climate change on water resources. Climate change is often entwined with alteration of water quantity as well as quality, aggravating the fast-growing water crisis. Over the past few decades, the negative effects of climate extremities are reflected in hydrological cycle, viz., pronounced shifts in global precipitation patterns and increased atmospheric water vapor content, glacier melting, floods, soil erosion, and drought etc. This situation substantially hinders the progress toward the attainment of Sustainable Development Goals (SDGs), thus jeopardizing the needs of future generations. It is therefore necessary to scientifically address the water security issues triggered by the escalating atmospheric and ocean temperatures. Water resource management has an obvious impact on a wide range of policy sectors, including energy, health, food security, and environment. As a result, practitioners need to design appropriate adaptation and mitigation strategies across diverse water-dependent sectors. However, there is a call for scrutinizing the current knowledge gaps in climate change vis-à-vis its implications on water resources. Owing to the complexities of climate system, anticipating these impacts is extremely challenging. Hence climate models related to the hydrological cycle provides a framework to conceptualize future scenario which is important for effective decision making. This chapter briefly discusses climate change impacts on water resources and process based modeling approaches combined with artificial intelligence /machine learning for tackling those issues.
Elsevier, Visualization Techniques for Climate Change with Machine Learnng and Artificial Intelligence, Sukanya S, Sabu Joseph, 2023, Pages 55-76