Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models

Water
By: , and 

Links

Abstract

Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) stream gages across the conterminous United States to examine the range/distribution of base flow inputs and the utility of this method to build a hydrologic model calibration dataset. OHS models with acceptable goodness-of-fit criteria were insensitive to drainage area, stream density, watershed slope, elevation, agricultural or perennial snow/ice land cover, average annual precipitation, runoff, or evapotranspiration, implying that OHS results are a viable calibration dataset applicable in diverse watersheds. OHS-estimated base flow contribution was compared to base flow-like model components from the USGS National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS). The NHM-PRMS variable gwres_flow is most conceptually like a base flow component of streamflow but the gwres_flow contribution to total streamflow is generally smaller than the OHS-estimated base flow contribution. The NHM-PRMS variable slow_flow, added to gwres_flow, produced similar or greater estimates of base flow contributions to total streamflow than the OHS-estimated base flow contribution but was dependent on the total flow magnitude.

Study Area

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models
Series title Water
DOI 10.3390/w11081629
Volume 11
Issue 8
Year Published 2019
Language English
Publisher MDPI
Contributing office(s) WMA - Integrated Modeling and Prediction Division, Maryland Water Science Center, Colorado Water Science Center
Description 1629, 25 p.
Country United States
Other Geospatial conterminous United States