Sensitivity of the projected hydroclimatic environment of the Delaware River basin to formulation of potential evapotranspiration
Tanja N. Williamson (),
Elizabeth A. Nystrom and
Paul C. D. Milly
Additional contact information
Tanja N. Williamson: Indiana-Kentucky Water Science Center
Elizabeth A. Nystrom: New York Water Science Center
Paul C. D. Milly: National Research Program
Climatic Change, 2016, vol. 139, issue 2, No 7, 215-228
Abstract:
Abstract The Delaware River Basin (DRB) encompasses approximately 0.4 % of the area of the United States (U.S.), but supplies water to 5 % of the population. We studied three forested tributaries to quantify the potential climate-driven change in hydrologic budget for two 25-year time periods centered on 2030 and 2060, focusing on sensitivity to the method of estimating potential evapotranspiration (PET) change. Hydrology was simulated using the Water Availability Tool for Environmental Resources (Williamson et al. 2015). Climate-change scenarios for four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCMs) and two Representative Concentration Pathways (RCPs) were used to derive monthly change factors for temperature (T), precipitation (PPT), and PET according to the energy-based method of Priestley and Taylor (1972). Hydrologic simulations indicate a general increase in annual (especially winter) streamflow (Q) as early as 2030 across the DRB, with a larger increase by 2060. This increase in Q is the result of (1) higher winter PPT, which outweighs an annual actual evapotranspiration (AET) increase and (2) (for winter) a major shift away from storage of PPT as snow pack. However, when PET change is evaluated instead using the simpler T-based method of Hamon (1963), the increases in Q are small or even negative. In fact, the change of Q depends as much on PET method as on time period or RCP. This large sensitivity and associated uncertainty underscore the importance of exercising caution in the selection of a PET method for use in climate-change analyses.
Date: 2016
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DOI: 10.1007/s10584-016-1782-2
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