Response of Colorado River runoff to dust radiative forcing in snow

Abstract

The waters of the Colorado River serve 27 million people in seven states and two countries but are overallocated by more than 10% of the river's historical mean. Climate models project runoff losses of 7-20% from the basin in this century due to human-induced climate change. Recent work has shown however that by the late 1800s, decades prior to allocation of the river's runoff in the 1920s, a fivefold increase in dust loading from anthropogenically disturbed soils in the southwest United States was already decreasing snow albedo and shortening the duration of snow cover by several weeks. The degree to which this increase in radiative forcing by dust in snow has affected timing and magnitude of runoff from the Upper Colorado River Basin (UCRB) is unknown. Here we use the Variable Infiltration Capacity model with postdisturbance and predisturbance impacts of dust on albedo to estimate the impact on runoff from the UCRB across 1916-2003. We find that peak runoff at Lees Ferry, Arizona has occurred on average 3 wk earlier under heavier dust loading and that increases in evapotranspiration from earlier exposure of vegetation and soils decreases annual runoff by more than 1.0 billion cubic meters or ∼5% of the annual average. The potential to reduce dust loading through surface stabilization in the deserts and restore more persistent snow cover, slow runoff, and increase water resources in the UCRB may represent an important mitigation opportunity to reduce system management tensions and regional impacts of climate change.

Fig. 1.

Overview of Upper Colorado River Basin, and the Colorado Plateau and Great Basin physiographic provinces, overlain with change in date of ΔSD_90% for elevations above 1,800 m. Star indicates Lees Ferry, AZ and flag indicates SBBSA.

Fig. 2.

Differences in runoff timing and volume between ADL and BDL dust scenarios. (A) Mean discharge at Lees Ferry, AZ on the Colorado River for ADL and BDL scenarios across the period 1916–2003. (B) Time series of BDL versus ADL Δ runoff in billion cubic meters across 1916–2003. (C) Time series of BDL versus ADL Δ runoff in percent of ADL runoff.

Fig. 3.

Simulated spatial changes in runoff and ET in the UCRB. (A) Spatial change in monthly average runoff (BDL–ADL) for March–August. (B) Spatial change in monthly average ET (BDL–ADL) for March–August. Note the difference in scales. Representation of runoff and ET in terms of depth (mm) is traditional for these studies and can be thought of as the depth of water across the entire grid cell. Each cell’s volume of runoff or ET comes from multiplying this depth by the area of the cell.

Fig. 4.

Relative timing of snow cover disappearance and rapid increase in ET. (A) Mean time series (1916–2003) of total ET and SCA for the VIC cell containing the SBBSA. (B) Time series of SBBSA total cell ET and SCA for ADL and BDL scenarios for an individual year (1970), showing the acute sensitivity of ET to changes in snow-covered area.