EGU25-18959, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-18959
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Enhancing Hydrological Forecasting in the Sabarmati Basin through Hybrid Approaches Integrating Physically-Based and Machine Learning Models
- 1Gujarat Technological University, Civil Engineering Department, Ahmedabad, India (samnankadri786@gmail.com)
- 2Civil engineering dept, L. D. College of Engineering, Gujarat, India
How to cite: Kadri, S. and Shaikh, M. M.: Enhancing Hydrological Forecasting in the Sabarmati Basin through Hybrid Approaches Integrating Physically-Based and Machine Learning Models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18959, https://doi.org/10.5194/egusphere-egu25-18959, 2025.