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DATASET OVERVIEW

Dataset Title: Dayflow

Investigators: Ganesh Ghimire, ghimiregr@ornl.gov, ORCID:0000-0002-4284-3941; Carly Hansen, ORCID:0000-0001-9328-0838; Sudershan Gangrade, ORCID:0000-0002-0730-0810
               Shih-Chieh Kao, ORCID:0000-0002-3207-5328; Peter E. Thornton, ORCID:0000-0002-4759-5158; Debjani Singh, ORCID:0000-0002-7783-8608

Point of Contact: Shih-Chieh Kao, kaos@ornl.gov, Oak Ridge National Laboratory

Summary: Dayflow V1 is a historical streamflow reanalysis dataset reconstructed for a 36-year period (1980-2015).
         Dayflow provides both daily and monthly scale streamflow data at about 2.7 million NHDPlusV2 stream reaches in the 
         conterminous US (CONUS) along with a comprehensiove summary of associated performance metrics.  

Keywords: Dayflow, VIC, RAPID, Streamflow Reanalysis

Acknowledgments: The dataset was produced with funding from the US Department of Energy, Water Power Technologies Office.

Related Publication: Manuscript in preparation

Related Datasets: N/A
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DATASET CHARACTERISTICS

Spatial Resolution: NHDPlusV2 stream reaches

Projection Information: N/A

Temporal Resolution: daily and monthly

Temporal Coverage: 1980-2015

File Format: .nc, .csv

File Naming Convention: Each data file is in the format of VIC4_RAPID_Obs2015C_HUC8Type_1980_2015.nc where:
						HUC8 8-digit hydrologic unit code
						Type Simulation type (N for natural and C for assimilated)

File Descriptions: See FieldDescriptors.csv
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APPLICATION & DERIVATION 
These data supplement limited streamflow gauge observations at the Conterminous US scale and provide support to long-term water resources planning, 
ecological system conservation, flood resilience and mitigation, food-energy-water nexus studies, among others.

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QUALITY ASSESSMENT 
Estimate of Uncertainty: The Dayflow dataset uses multiple inputs such as meteorological forcings, land and soil information, and river network information
that are not free of uncertainties which could propagate to the streamflow outputs. Observational uncertainties associated with the streamflow measurements 
also affect not just the assimilated streamflow outputs but also overall performance evaluation. At this point, RAPID algorithm used to produce Dayflow also
does not account for the lakes/reservoir releases. We address it to a degree with hierarchial streamflow assimilation framework implemented in producing Dayflow.
The dataset is quality controlled without any flags that the authors are aware of. 
  
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DATA ACQUISITION, MATERIALS & METHODS
The calibrated Variable Infiltration Capacity (VIC) model parameters used in this dataset generation is from Oubeidillah et al. (2014) and Naz et al. (2016).

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CHANGE LOG
This section will be updated with the release of newer versions.

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REFERENCES
- Naz, B. S., Kao, S. C., Ashfaq, M., Rastogi, D., Mei, R., & Bowling, L. C. (2016). Regional hydrologic response to climate change in the conterminous United States 
  using high-resolution hydroclimate simulations. Global and Planetary Change, 143, 100–117. https://doi.org/10.1016/j.gloplacha.2016.06.003
- Oubeidillah, A. A., Kao, S.-C., Ashfaq, M., Naz, B. S., & Tootle, G. (2014). A large-scale, high-resolution hydrological model parameter data set for climate change 
  impact assessment for the conterminous US. Hydrology and Earth System Sciences, 18(1), 67–84.

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SUPPLEMENTAL FILES
- FieldDescriptors.csv
- README.txt

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