The development of a hydrologic foundation, essential for advancing our understanding of flow-ecology relationships, was accomplished using the high-resolution physics-based distributed rainfall-runoff model Vflo. We compared the accuracy and bias associated with flow metrics that were generated using Vflo at both a daily and monthly time step in the Canadian River basin, USA. First, we calibrated and applied bias correction to the Vflo model to simulate streamflow at ungaged catchment locations. Next, flow metrics were calculated using both simulated and observed data from stream gage locations. We found discharge predictions using Vflo were more accurate than using drainage area ratios. General correspondence between predicted discharge and the gage data was apparent; however, flow metrics calculated using the Vflo output did not accurately represent flow variability. This work was part of a multidisciplinary project describing water quality, streamflow and runoff, and ecology of the Canadian River Basin from northeastern New Mexico to Lake Eufaula, Oklahoma. This study was done in cooperation with the South Central Climate Adaptation Science Center.

The development of a hydrologic foundation, essential for advancing our understanding of flow-ecology relationships, was accomplished using the high-resolution physics-based distributed rainfall-runoff model Vflo. We compared the accuracy and bias associated with flow metrics that were generated using Vflo at both a daily and monthly time step in the Canadian River basin, USA. First, we calibrated and applied bias correction to the Vflo model to simulate streamflow at ungaged catchment locations. Next, flow metrics were calculated using both simulated and observed data from stream gage locations. We found discharge predictions using Vflo were more accurate than using drainage area ratios. General correspondence between predicted discharge and the gage data was apparent; however, flow metrics calculated using the Vflo output did not accurately represent flow variability. This work was part of a multidisciplinary project describing water quality, streamflow and runoff, and ecology of the Canadian River Basin from northeastern New Mexico to Lake Eufaula, Oklahoma. This study was done in cooperation with the South Central Climate Adaptation Science Center.

The development of a hydrologic foundation, essential for advancing our understanding of flow-ecology relationships, was accomplished using the high-resolution physics-based distributed rainfall-runoff model Vflo. We compared the accuracy and bias associated with flow metrics that were generated using Vflo at both a daily and monthly time step in the Canadian River basin, USA. First, we calibrated and applied bias correction to the Vflo model to simulate streamflow at ungaged catchment locations. Next, flow metrics were calculated using both simulated and observed data from stream gage locations. We found discharge predictions using Vflo were more accurate than using drainage area ratios. General correspondence between predicted discharge and the gage data was apparent; however, flow metrics calculated using the Vflo output did not accurately represent flow variability. This work was part of a multidisciplinary project describing water quality, streamflow and runoff, and ecology of the Canadian River Basin from northeastern New Mexico to Lake Eufaula, Oklahoma. This study was done in cooperation with the South Central Climate Adaptation Science Center.

Geographic patterns and time trends of water-quality, modeled streamflow, and ecological data were compared along the Canadian River and selected tributaries in northeastern New Mexico to Lake Eufaula in Oklahoma to determine effects of climate change on water quality, streamflows, fish populations and ecological flows in this watershed from 1939 to 2013. Project participants included staff from the Oklahoma Cooperative Fish and Wildlife Research Unit, Vieux and Associates, USGS New Jersey Water Science Center and the USGS Oklahoma Water Science Center. Principal project funding was by the South Central Climate Science Center, with in-kind matching from the project participant organizations.

Geographic patterns and time trends of water-quality, modeled streamflow, and ecological data were compared along the Canadian River and selected tributaries in northeastern New Mexico to Lake Eufaula in Oklahoma to determine effects of climate change on water quality, streamflows, fish populations and ecological flows in this watershed from 1939 to 2013. Project participants included staff from the Oklahoma Cooperative Fish and Wildlife Research Unit, Vieux and Associates, USGS New Jersey Water Science Center and the USGS Oklahoma Water Science Center. Principal project funding was by the South Central Climate Science Center, with in-kind matching from the project participant organizations.

This directory contains file for each of the 26 site locations required for simulation of streamflow in HEC-ResSim. Each file contains the 100, 100-year streamflow time series in monthly streamflow volume format. Streamflow volume is presented in cubic meters. In column A, there is a row number, column B is the month of the stochastic streamflow volume, column C is the year in the stochastic timeseries, column D is named “simnum” and is the simulation number, and column E is named “monthly_tot” and is the total streamflow volume for the given month, year, and simulation number in cubic meters.

This directory contains file for each of the 26 site locations required for simulation of streamflow in HEC-ResSim. Each file contains the 100, 100-year streamflow time series in monthly streamflow volume format. Streamflow volume is presented in cubic meters. In column A, there is a row number, column B is the month of the stochastic streamflow volume, column C is the year in the stochastic timeseries, column D is named “simnum” and is the simulation number, and column E is named “monthly_tot” and is the total streamflow volume for the given month, year, and simulation number in cubic meters.

Our objective was to model the risk of becoming intermittent under drier climate conditions on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a conditional inference modeling approach to model the relation between intermittency status on gaged streams (115 gages) and selected mean and minimum flow metrics. We then projected intermittency status and if a stream reach would be "threatened by intermittency" under a drier climate to ungaged reaches in the Upper Colorado River Basin using predicted minimum flow coefficient of variation (CV) and specific mean annual flow for each stream reach in the basin. This data layer shows modeled values of stream intermittency based on minimum flow CV and specific mean annual flow for each stream reach in the basin.

Our objective was to model the risk of becoming intermittent under drier climate conditions on small, ungaged streams in the Upper Colorado River Basin. Modeling streamflows is an important tool for understanding landscape-scale drivers of flow and estimating flows where there are no gaged records. We focused our study in the Upper Colorado River Basin, a region that is not only critical for water resources but also projected to experience large future climate shifts toward a drier climate. We used a conditional inference modeling approach to model the relation between intermittency status on gaged streams (115 gages) and selected mean and minimum flow metrics. We then projected intermittency status and if a stream reach would be "threatened by intermittency" under a drier climate to ungaged reaches in the Upper Colorado River Basin using predicted minimum flow coefficient of variation (CV) and specific mean annual flow for each stream reach in the basin. This data layer shows modeled values of stream intermittency based on minimum flow CV and specific mean annual flow for each stream reach in the basin.