Enhancing Rainfall-Runoff Simulation via Meteorological Variables and a Deep-Conceptual Learning-Based Framework

• Published in: Atmosphere
• Main Authors: Mohammed Achite, Babak Mohammadi, Muhammad Jehanzaib, Nehal Elshaboury, Quoc Bao Pham, Zheng Duan
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2022
• Subjects: conceptual hydrological model; deep learning model; runoff simulation; data-driven model; Meteorology. Climatology; QC851-999; Kalixälven; Northern Sweden
• Online Access: https://doi.org/10.3390/atmos13101688; https://doaj.org/article/4fad12333eb5487eab5071338f168203

Accurate streamflow simulation is crucial for many applications, such as optimal reservoir operation and irrigation. Conceptual techniques employ physical ideas and are suitable for representing the physics of the hydrologic model, but they might fail in competition with their more advanced counterp...