COMPARISON OF TWO LARGE HYDRO METEOROLOGICAL DATASETS FOR THE CONTINENTAL UNITED STATES

Hydroclimatic variables and catchment characteristics drive hydrological processes, which in turn, control water resource availability. Datasets typically contain detailed information for limited experimental catchments or by contrast, consist of large network of observations but frequently lack all necessary variables. Large sample hydrology (LSH) is essentially comparative hydrology, which relies on hundreds to thousands of catchments and derives relationships, develops new models, and facilitates the transfer of knowledge between regions. Large sample studies for the continental United States (CONUS), or additional continents , consist of a large number of catchments, and are characterized by varying spatial and temporal scales. A wide range of data sources with varying analysis and derivation methods can introduce uncertainty, especially when metadata is excluded. Are derived results due to the observed relationship or an artifact of error? This study aims to analyze two of the largest hydrometeorological datasets for the CONUS, the Model Parameter Estimation Experiment (MOPEX) and the Catchments Attributes and Meteorology for Large-sample Studies dataset (CAMELS) and determine their comparability and accuracy. Additional data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and eddy covariance flux towers are also used for comparison. The data for two catchments were used as input to the Hydrologic Modeling System (HEC-HMS) to compare streamflow simulation.