Evapotranspiration (ET) is the process by which liquid water becomes water vapor and energetically this accounts for much of incoming solar radiation. If this ET did not occur temperatures would be higher, so understanding ET trends is crucial to predict future temperatures. Recent studies have reported prolonged declines in ET in recent decades, although these declines may relate to climate variability. Here, we used a well-validated diagnostic model to estimate daily ET during 1981–2012 and its three components: transpiration from vegetation (E_t), direct evaporation from the soil (E_s) and vaporization of intercepted rainfall from vegetation (E_i). During this period, ET over land has increased significantly (p < 0.01), caused by increases in E_t and E_i, which are partially counteracted by E_s decreasing. These contrasting trends are primarily driven by increases in vegetation leaf area index, dominated by greening. The overall increase in E_t over land is about twofold of the decrease in E_s. These opposing trends are not simulated by most Coupled Model Intercomparison Project phase 5 (CMIP5) models and highlight the importance of realistically representing vegetation changes in earth system models for predicting future changes in the energy and water cycle.

Quantifying the responses of the coupled carbon and water cycles to current global warming and rising atmospheric CO₂ concentration is crucial for predicting and adapting to climate changes. Here we show that terrestrial carbon uptake (i.e. gross primary production) increased significantly from 1982 to 2011 using a combination of ground-based and remotely sensed land and atmospheric observations. Importantly, we find that the terrestrial carbon uptake increase is not accompanied by a proportional increase in water use (i.e. evapotranspiration) but is largely (about 90%) driven by increased carbon uptake per unit of water use, i.e. water use efficiency. The increased water use efficiency is positively related to rising CO₂ concentration and increased canopy leaf area index, and negatively influenced by increased vapour pressure deficits. Our findings suggest that rising atmospheric CO₂ concentration has caused a shift in terrestrial water economics of carbon uptake.

This paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–runoff models informed by 1 GCM (a less than 7% difference between the minimum and maximum results). The difference between the rainfall–runoff modeling results is larger in the drier regions for scenarios of big declines in future rainfall and in the low-flow characteristics. The rainfall–runoff modeling here considers only the runoff sensitivity to changes in the input climate data (primarily daily rainfall), and the difference between the hydrological modeling results is likely to be greater if potential changes in the climate–runoff relationship in a warmer and higher CO2 environment are modeled.