Search Results

You are looking at 1 - 2 of 2 items for :

  • Author or Editor: P. Das x
  • Journal of Hydrometeorology x
  • Refine by Access: All Content x
Clear All Modify Search
Julie A. Vano, Tapash Das, and Dennis P. Lettenmaier

Abstract

The Colorado River is the primary water source for much of the rapidly growing southwestern United States. Recent studies have projected reductions in Colorado River flows from less than 10% to almost 50% by midcentury because of climate change—a range that has clouded potential management responses. These differences in projections are attributable to variations in climate model projections but also to differing land surface model (LSM) sensitivities. This second contribution to uncertainty—specifically, variations in LSM runoff change with respect to precipitation (elasticities) and temperature (sensitivities)—are evaluated here through comparisons of multidecadal simulations from five commonly used LSMs (Catchment, Community Land Model, Noah, Sacramento Soil Moisture Accounting model, and Variable Infiltration Capacity model) all applied over the Colorado River basin at ⅛° latitude by longitude spatial resolution. The annual elasticity of modeled runoff (fractional change in annual runoff divided by fractional change in annual precipitation) at Lees Ferry ranges from two to six for the different LSMs. Elasticities generally are higher in lower precipitation and/or runoff regimes; hence, the highest values are for models biased low in runoff production, and the range of elasticities is reduced to two to three when adjusted to current runoff climatology. Annual temperature sensitivities (percent change in annual runoff per degree change in annual temperature) range from declines of 2% to as much as 9% per degree Celsius increase at Lees Ferry. For some LSMs, small areas, primarily at midelevation, have increasing runoff with increasing temperature; however, on a spatial basis, most sensitivities are negative.

Restricted access
T. Das, H. G. Hidalgo, D. W. Pierce, T. P. Barnett, M. D. Dettinger, D. R. Cayan, C. Bonfils, G. Bala, and A. Mirin

Abstract

This study examines the geographic structure of observed trends in key hydrologically relevant variables across the western United States at ⅛° spatial resolution during the period 1950–99. Geographical regions, latitude bands, and elevation classes where these trends are statistically significantly different from trends associated with natural climate variations are identified. Variables analyzed include late-winter and spring temperature, winter-total snowy days as a fraction of winter-total wet days, 1 April snow water equivalent (SWE) as a fraction of October–March (ONDJFM) precipitation total [precip(ONDJFM)], and seasonal [JFM] accumulated runoff as a fraction of water-year accumulated runoff. Observed changes were compared to natural internal climate variability simulated by an 850-yr control run of the finite volume version of the Community Climate System Model, version 3 (CCSM3-FV), statistically downscaled to a ⅛° grid using the method of constructed analogs. Both observed and downscaled model temperature and precipitation data were then used to drive the Variable Infiltration Capacity (VIC) hydrological model to obtain the hydrological variables analyzed in this study. Large trends (magnitudes found less than 5% of the time in the long control run) are common in the observations and occupy a substantial part (37%–42%) of the mountainous western United States. These trends are strongly related to the large-scale warming that appears over 89% of the domain. The strongest changes in the hydrologic variables, unlikely to be associated with natural variability alone, have occurred at medium elevations [750–2500 m for JFM runoff fractions and 500–3000 m for SWE/Precip(ONDJFM)] where warming has pushed temperatures from slightly below to slightly above freezing. Further analysis using the data on selected catchments indicates that hydroclimatic variables must have changed significantly (at 95% confidence level) over at least 45% of the total catchment area to achieve a detectable trend in measures accumulated to the catchment scale.

Full access