High-resolution Annual Dynamic dataset of Curve Number from 2008 to 2021 over Conterminous United States.

ABSTRACT: The spatial distribution and data quality of curve number (CN) values determine the performance of hydrological estimations. However, existing CN datasets are constrained by universal-applicability hypothesis, medium resolution, and imbalance between specificity CN tables to generalized land use/land cover (LULC) maps, which hinder their applicability and predictive accuracy. A new annual CN dataset named CUSCN30, featuring an enhanced resolution of 30 meters and accounting for temporal variations in climate and LULC in the continental United States (CONUS) between 2008 and 2021, was developed in this study. CUSCN30 demonstrated good performance in surface runoff estimation using CN method when compared to observed surface runoff for the selected watersheds. Compared with existing CN datas

SUBMITTER: Wu Q 

PROVIDER: S-EPMC10869687 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature