| Popis: |
Terrestrial evapotranspiration (ET) is a significant component of the energy and water balances at the land surface. However, direct, continuous measurements of ET are spatially limited and only available since the 1990s. Due to this lack of observations, detecting and attributing long-term regional trends in ET remains difficult. This dissertation aims to alleviate the data limitation and detect long-term trends by developing a method to infer ET from data collected at common weather stations, which are spatially and temporally abundant. The methodology used to infer ET from historical meteorological data is based on an emergent relation between the land surface and atmospheric boundary layer. We refer to this methodology as the Evapotranspiration from Relative Humidity at Equilibrium method, or the “ETRHEQ method”. In the first section of this dissertation, we develop the ETRHEQ method for use at common weather stations and demonstrate the utility of the method at twenty eddy covariance sites spanning a wide range of climate and plant functional types. Next, we apply the ETRHEQ method at historical weather stations across the continental U.S. and show that ET estimates obtained via the ETRHEQ method compare well with watershed scale ET, as well as ET estimates from land surface models. From 1961 to 1997, we find negligible or increasing trends in summertime ET over the central U.S. and the west coast and negative trends in the eastern and western U.S. From 1998 to 2014, we find a sharp decline in summertime ET across the entire U.S. We show that this decline is consistent with decreasing transpiration associated with declines in humidity. Lastly, we assess the sensitivity of ET to perturbations in soil moisture and humidity anticipated with climate change. We demonstrate that the response of ET to changing humidity and soil moisture is strongly dependent on the biological and hydrological state of the surface, particularly the degree of water stress and vegetation fraction. In total, this dissertation demonstrates the utility of the ETRHEQ method as a means to estimate ET from weather station data and highlights the critical role of vegetation in modulating ET variability. |
