Hydrology Newsletter

To ensure a sustainable future, graduates should be knowledgeable in all branches, including Civil and Military Engineering, which will always have problems that graduates will be required to solve. Knowledge of these branches is essential for their careers, as they will be required to solve problems like optimization of power generation, minimization of losses in different electrical/mechanical/civil systems. Data science and Artificial Intelligence can help achieve this, and implementing Machine Learning Codes with the Internet of Things (IoT) can make the system smart. The best choice for graduates is to take any one branch at the time of graduation, followed by a post-graduation course that teaches AI/ML/DS/IoT. Additionally, pursuing a Ph.D. in a field that applies modern techniques to solve basic engineering problems will ensure a job and a sustainable future. Read the entire article in my newsletter: HydroGeek .

Find below the free e-course on Arithmetic Mean Method, Thiessen Polygon Method, and Isohyetal Method Mean Precipitation over an Area by Iso Hyetal Method Estimation of Mean Precipitation by Thiessen Polygon Method Mean Precipitation Prediction by Arithmetic Mean Method More free tutorials on hydrology coming soon. Subscribe to stay tuned. You may also like : Very Short-Term Courses: Optimization Techniques and their Application in Hydro-informatics Be Sustainable: How to Use WCI and ECI to save water and electricity use? Confused about which method to use? iDecide will help . Create your own Video and manage it . Become an Affiliate of other related books, courses, and products Guest Posting to this newsletter New but peer-reviewed journals Learn about data science with simple examples Evaluate the suitability of a journal with respect to your article Host your own App Read the book:  Lecture Notes on MCDM Preorder: GIS in One Page Preorder: 50 Project Ideas on MCDM and GIS For websit

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

“Multi-attribute utility theory (MAUT) combines a class of psychological measurement models and scaling procedures which can be applied to the evaluation of alternatives which have multiple values relevant attributes.” Von Winterfeldt and Fischer (1975) . Some example applications of MAUT in Water Resource Management? Feeny, David, William Furlong, George W. Torrance, Charles H. Goldsmith, Zenglong Zhu, Sonja DePauw, Margaret Denton, and Michael Boyle. "Multiattribute and single-attribute utility functions for the health utilities index mark 3 system." Medical care 40, no. 2 (2002): 113-128. Zheng, Yong, and David Xuejun Wang. "Hybrid Multi-Criteria Preference Ranking by Subsorting." arXiv preprint arXiv:2306.11233 (2023). @data_hydrology , @Merchandise or @ @products_sustainability Add to Listy /