COMPARISON AND EVALUATION OF LARGE SAMPLE HYDROMETEOROLOGICAL DATASETS IN THE UNITED STATES

Comparative hydrology essentially characterizes hydrological processes based on interactions between the climate, landscape, and human controls. Large sample hydrology (LSH) relies on large sets of catchments to develop statistically significant relationships within and between regions. MOdel Parameter Estimation EXperiment (MOPEX) and Catchment Attributes and MEteorology for Large-sample Studies (CAMELS) are the only two LSH datasets for the contiguous united states (CONUS) and contain daily streamflow records, daily precipitation, daily temperature, and landscape attributes. This study compares these LSH datasets and statistical analyses indicate compatibility on monthly and annual temporal scales and the extension of both using DAYMET gridded data. The most variability between the two was evident in arid climate regions but still exhibited strong seasonal correlation. Streamflow simulations using HEC-HMS indicated similar trends and results using both MOPEX and CAMELS.