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We present a community data set of daily forcing and hydrologic response datafor 671 small- to medium-sized basins across the contiguous United States(median basin size of 336 km<sup>2</sup>) that spans a very wide range ofhydroclimatic conditions. Area-averaged forcing data for the period1980–2010 was generated for three basin spatial configurations – basinmean, hydrologic response units (HRUs) and elevation bands – by mappingdaily, gridded meteorological data sets to the subbasin (Daymet) and basinpolygons (Daymet, Maurer and NLDAS). Daily streamflow data was compiled fromthe United States Geological Survey National Water Information System. Thefocus of this paper is to (1) present the data set for community use  and (2)provide a model performance benchmark using the coupled Snow-17 snow modeland the Sacramento Soil Moisture Accounting Model,calibrated using the shuffled complex evolution global optimization routine.After optimization minimizing daily root mean squared error, 90% of thebasins have Nash–Sutcliffe efficiency scores ≥0.55 for the calibrationperiod and 34% ≥ 0.8. This benchmark provides a reference level ofhydrologic model performance for a commonly used model and calibrationsystem, and highlights some regional variations in model performance. Forexample, basins with a more pronounced seasonal cycle generally have anegative low flow bias, while basins with a smaller seasonal cycle have apositive low flow bias. Finally, we find that data points with extreme error(defined as individual days with a high fraction of total error) are morecommon in arid basins with limited snow  and, for a given aridity, fewerextreme error days are present as the basin snow water equivalent increases

hydrology and earth system sciences

Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance