Evapotranspiration sensitivity to air temperature across a snow-influenced watershed: Space-for-time substitution versus integrated watershed modeling

Changes in long-term, montane actual evapotranspiration (ET) in response to climate change could impact future water supplies and forest species composition. For scenarios of atmospheric warming, predicted changes in long-term ET tend to differ between studies using space-for-time substitution (STS) models and integrated watershed models, and the influence of spatially varying factors on these differences is unclear. To examine this, we compared warming-induced (+2 to +6 °C) changes in ET simulated by an STS model and an integrated watershed model across zones of elevation, substrate available water capacity, and slope in the snow-influenced upper San Joaquin River watershed, Sierra Nevada, USA. We used the Soil Water and Assessment Tool (SWAT) for the watershed modeling and a Budyko-type relationship for the STS modeling. Spatially averaged increases in ET from the STS model increasingly surpassed those from the SWAT model in the higher elevation zones of the watershed, resulting in 2.3-2.6 times greater values from the STS model at the watershed scale. In sparse, deep colluvium or glacial soils on gentle slopes, the SWAT model produced ET increases exceeding those from the STS model. However, watershed areas associated with these conditions were too localized for SWAT to produce spatially averaged ET-gains comparable to the STS model. The SWAT model results nevertheless demonstrate that such soils on high-elevation, gentle slopes will form ET “hot spots” exhibiting disproportionately large increases in ET, and concomitant reductions in runoff yield, in response to warming. Predicted ET responses to warming from STS models and integrated watershed models may, in general, substantially differ (e.g., factor of 2-3) for snow-influenced watersheds exhibiting an elevational gradient in substrate water holding capacity and slope. Long-term water supplies in these settings may therefore be more resilient to warming than STS model predictions would suggest.