Streamflow in the Columbia River Basin: Quantifying Changes Over the Period 1951‐2008 and Determining the Drivers of Those Changes

Abstract

Trend, detection, and attribution analyses were performed using naturalized streamflow observations and routed land surface model runoff for 10 subbasins in the Columbia River Basin during water years 1951–2008. The Energy Exascale Earth System land‐surface model (ELM) version 1.0 and the Routing Application for Parallel computatIon of Discharge (RAPID) routing model were used to conduct semi‐factorial simulations driven by multiple sets of bias‐corrected forcing data sets. Four main potential drivers, including climate change (CLMT), CO2 concentration (CO2), nitrogen deposition (NDEP), and land use and land cover change (LULCC), were analyzed during the assessment. All subbasins showed significant (α = 0.10) declines in the observed amount of annual total streamflow, except for the Middle and Upper Snake and Upper Columbia Subbasins. These declines were led by significant decreases in June–October streamflow, which also directly led to significant decreases in peak and summer streamflow. Except for the Snake River Subbasins, LULCC had the same pattern of declines in monthly streamflow, but the period was shifted to May–September. NDEP also had significant trends in June–October; however, rather than decreases, the trends showed significant increases in streamflow. While there were significant trends in CO2, NDEP, and LULCC, their signals of change were weak in comparison to the signal in CLMT and the natural internal variability found in streamflow. Overall, the detection and attribution analysis showed that the historical changes found in annual total, center of timing of, and summer mean streamflow could be attributed to changing climate and variability.

Climate Change and Changes in Compound Coastal‐Riverine Flooding Hazard Along the U.S. Coasts

“…(2017) and Forbes et al. (2019). Observed flow data are compared with simulated flow data using different statistical indices (Figure S2‐1–S2‐26).…”

“…Naz et al (2016) provide a detailed description of the VIC model setup and evaluation. The use of RAPID routing model along with NHDPlus river network can be further referred to Tavakoly et al (2017) and Forbes et al (2019). Observed flow data are compared with simulated flow data using different statistical indices (Figure S2-1-S2-26).…”

Simulation of Hurricane Harvey flood event through coupled hydrologic‐hydraulic models: Challenges and next steps

“…The hourly ST4 rainfall data were spatially interpolated to each VIC grid cell for hourly simulation. The simulated hourly VIC total runoff was then routed through 1929 NHD+ river segments in the San Jacinto River Basin by RAPID to simulate streamflow (similar to the procedures used in Forbes et al, 2019). The detailed model evaluation results are presented and discussed in Section 3.1.…”

Hysteresis Patterns of Watershed Nitrogen Retention and Loss Over the Past 50 years in United States Hydrological Basins

“…We calculated trends for the concentration time‐series Cn(t), export time‐series Ex(t) , area normalized export time series (yields) Ys(t) and discharge time‐series Qs(t) . We calculated trends for each nitrogen (N) and carbon (C) parameter using two techniques: (1) linear models to extract the slope (β) representing the trend and (2) Mann‐Kendall tests to extract the slope (β MK ) representing the trend (Forbes et al., 2019; Helsel & Hirsch, 2002). We analyzed a suite of statistics using the R statistical software for each time series (R Core Team, 2020).…”