What will the future of AI and ML modeling of water resource development look like?

What is next in AI & ML Modeling of Water Resource Development?

AI & ML modeling application is now widespread in water resource development studies. But due to the uncertainty in water parameters, much more innovation is required for their practical applications

In recent years like all the other fields of studies, the application of Artificial Intelligence and Machine Learning (AI&ML) on water resource development projects has increased manifold.

For example :

Sukanya, S., and Sabu Joseph. "Climate change impacts on water resources: An overview." Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence (2023): 55-76.

Kommadi, Bhagvan. "AI and ML Applications: 5G and 6G." (2023).

Joseph, Kiran, Ashok K. Sharma, Rudi van Staden, P. L. P. Wasantha, Jason Cotton, and Sharna Small. "Application of Software and Hardware-Based Technologies in Leaks and Burst Detection in Water Pipe Networks: A Literature Review." Water 15, no. 11 (2023): 2046.

Yurtsever, Mustafa, and E. M. E. Ç. Murat. "Potable Water Quality Prediction Using Artificial Intelligence and Machine Learning Algorithms for Better Sustainability." Ege Academic Review 23, no. 2 (2023): 265-278.

However, the uncertainty involved in Hydrologic/Hydraulic or Water Quality Parameters is very hard to simulate, and even with the advent of such cognitive algorithms accuracy and reliability of the models nevertheless lack substance. In this field of study, there is still much to be done. Some interesting objectives can be :

Click here to see the five interesting objectives in HydroGeek Newsletter.

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