{"id":"doi:10.1016/j.jhydrol.2021.127297","kind":"article","title":"Improving streamflow prediction in the WRF-Hydro model with LSTM networks","authors":["Kyeungwoo Cho","Yeonjoo Kim"],"author_count":2,"year":2021,"published":"2021-12-13","venue":"Journal of Hydrology","cited_by":332,"doi":"10.1016/j.jhydrol.2021.127297","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.jhydrol.2021.127297","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.jhydrol.2021.127297","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W4200366988","pdf_url":"https://www.sciencedirect.com/science/article/pii/S0022169421013470/pdf","abstract":null,"abstract_license":null,"license":"cc-by-nc-nd","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Hydrological Forecasting Using AI"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0).","topics":[{"slug":"ai-weather-climate","name":"AI Weather & Climate Modeling","domain_slug":"energy"}],"cited_in_dossiers":[]}