@article{ART003063553},
author={Park Hyeseung and Hyun-Ho Yang and Hojun Lee and Jongwook Yoon},
title={A Comparative Study on Reservoir Level Prediction Performance Using a Deep Neural Network with ASOS, AWS, and Thiessen Network Data},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={3},
pages={67-74},
doi={10.9708/jksci.2024.29.03.067}
TY - JOUR
AU - Park Hyeseung
AU - Hyun-Ho Yang
AU - Hojun Lee
AU - Jongwook Yoon
TI - A Comparative Study on Reservoir Level Prediction Performance Using a Deep Neural Network with ASOS, AWS, and Thiessen Network Data
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 3
PB - The Korean Society Of Computer And Information
SP - 67
EP - 74
SN - 1598-849X
AB - In this paper, we present a study aimed at analyzing how different rainfall measurement methods affect the performance of reservoir water level predictions. This work is particularly timely given the increasing emphasis on climate change and the sustainable management of water resources. To this end, we have employed rainfall data from ASOS, AWS, and Thiessen Network-based measures provided by the KMA Weather Data Service to train our neural network models for reservoir yield predictions. Our analysis, which encompasses 34 reservoirs in Jeollabuk-do Province, examines how each method contributes to enhancing prediction accuracy. The results reveal that models using rainfall data based on the Thiessen Network's area rainfall ratio yield the highest accuracy. This can be attributed to the method’s accounting for precise distances between observation stations, offering a more accurate reflection of the actual rainfall across different regions. These findings underscore the importance of precise regional rainfall data in predicting reservoir yields. Additionally, the paper underscores the significance of meticulous rainfall measurement and data analysis, and discusses the prediction model's potential applications in agriculture, urban planning, and flood management.
KW - ASOS;AWS;Thiessen Network;Reservoir Level Prediction;Deep Learning
DO - 10.9708/jksci.2024.29.03.067
ER -
Park Hyeseung, Hyun-Ho Yang, Hojun Lee and Jongwook Yoon. (2024). A Comparative Study on Reservoir Level Prediction Performance Using a Deep Neural Network with ASOS, AWS, and Thiessen Network Data. Journal of The Korea Society of Computer and Information, 29(3), 67-74.
Park Hyeseung, Hyun-Ho Yang, Hojun Lee and Jongwook Yoon. 2024, "A Comparative Study on Reservoir Level Prediction Performance Using a Deep Neural Network with ASOS, AWS, and Thiessen Network Data", Journal of The Korea Society of Computer and Information, vol.29, no.3 pp.67-74. Available from: doi:10.9708/jksci.2024.29.03.067
Park Hyeseung, Hyun-Ho Yang, Hojun Lee, Jongwook Yoon "A Comparative Study on Reservoir Level Prediction Performance Using a Deep Neural Network with ASOS, AWS, and Thiessen Network Data" Journal of The Korea Society of Computer and Information 29.3 pp.67-74 (2024) : 67.
Park Hyeseung, Hyun-Ho Yang, Hojun Lee, Jongwook Yoon. A Comparative Study on Reservoir Level Prediction Performance Using a Deep Neural Network with ASOS, AWS, and Thiessen Network Data. 2024; 29(3), 67-74. Available from: doi:10.9708/jksci.2024.29.03.067
Park Hyeseung, Hyun-Ho Yang, Hojun Lee and Jongwook Yoon. "A Comparative Study on Reservoir Level Prediction Performance Using a Deep Neural Network with ASOS, AWS, and Thiessen Network Data" Journal of The Korea Society of Computer and Information 29, no.3 (2024) : 67-74.doi: 10.9708/jksci.2024.29.03.067
Park Hyeseung; Hyun-Ho Yang; Hojun Lee; Jongwook Yoon. A Comparative Study on Reservoir Level Prediction Performance Using a Deep Neural Network with ASOS, AWS, and Thiessen Network Data. Journal of The Korea Society of Computer and Information, 29(3), 67-74. doi: 10.9708/jksci.2024.29.03.067
Park Hyeseung; Hyun-Ho Yang; Hojun Lee; Jongwook Yoon. A Comparative Study on Reservoir Level Prediction Performance Using a Deep Neural Network with ASOS, AWS, and Thiessen Network Data. Journal of The Korea Society of Computer and Information. 2024; 29(3) 67-74. doi: 10.9708/jksci.2024.29.03.067
Park Hyeseung, Hyun-Ho Yang, Hojun Lee, Jongwook Yoon. A Comparative Study on Reservoir Level Prediction Performance Using a Deep Neural Network with ASOS, AWS, and Thiessen Network Data. 2024; 29(3), 67-74. Available from: doi:10.9708/jksci.2024.29.03.067
Park Hyeseung, Hyun-Ho Yang, Hojun Lee and Jongwook Yoon. "A Comparative Study on Reservoir Level Prediction Performance Using a Deep Neural Network with ASOS, AWS, and Thiessen Network Data" Journal of The Korea Society of Computer and Information 29, no.3 (2024) : 67-74.doi: 10.9708/jksci.2024.29.03.067
