Abstract
To estimate the optimal grid size for radar reflectivity, an artificial neural network (ANN) model was employed to estimate the precipitation in the Soyanggangdam basin in Korea. The model was simulated using constant altitude plan position indicator (CAPPI) data from the weather radar observatory in Gwangduksan. To configure the ANN model, only the reflectivity of cells of the ground observatory was selected to estimate the precipitation. An optimal grid size for the CAPPI, which exhibited minimal influence on runoff, was suggested. The simulated precipitation was applied in a soil and water assessment tool (SWAT) model, which is a continuous physical model utilized to determine variation in runoff and peak flood. An optimal grid size of radar reflectivity in the range of 4–8km was obtained for the Soyanggangdam basin by analyzing the variation in runoff.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
