Search

In drought-prone Australia, multi-year droughts have detrimental impacts on both the natural environment and human societies. For responsible water management, we need a thorough understanding of the full range of variability in multi-year droughts and how this might change in a warming world. But research into the long-term frequency, persistence, and severity of Australian droughts is limited. This is partly due to the length of the observational record, which is short relative to the time scales of hydroclimatic variability, and hence may not capture the range of possible variability. Using simulations of Australian precipitation over the last millennium (850–2000 CE), we characterise the nature of multi-year meteorological droughts across Australia, and including a particular focus on the Murray-Darling Basin (MDB); the largest agricultural region in Australia. We find that simulated Australian droughts in the twentieth century (1900–2000) are within the bounds of pre-industrial natural variability in terms of drought intensity, severity, and frequency. A tendency to longer droughts in southwestern and eastern Australia (including the MDB) in the 20th century compared with the pre-industrial period suggests an emerging anthropogenic influence, consistent with projected rainfall changes in these regions. Large volcanic eruptions tend to promote drought-free intervals in the MDB. Model simulations suggest future droughts across Australia could be much longer than what has been experienced in the twentieth century, even without any human influence. With the addition of anthropogenic climate change—which favours drought conditions across much of southern Australia, due to reduced cool season rainfall—it is likely that future droughts in Australia will exceed historical experience.

Global environmental change is expected to alter the spatial and temporal distribution of water resources but quantifying its effects on the terrestrial water balance remains a challenge. Evapotranspiration (ET) is a key ecosystem variable linking water, energy and carbon cycles, but although global aggregate ET is expected to increase in a warming climate, regional changes in ET have remained particularly poorly constrained due in part to difficulty in measuring ET. The effects of vegetation and increasing atmospheric CO₂ represent a further complication. Experiments have shown that elevated atmospheric CO₂ affects vegetation productivity and water use, but it remains uncertain whether these processes have led to detectable changes in ET or runoff at ecosystem scales. This thesis aims to quantify large-scale variations in ET, and, in particular, to better constrain the effects of elevated CO₂ on catchment-scale hydrology. The approach relies on observations to the greatest extent possible, and the water-balance method (the difference of precipitation and streamflow at the river catchment scale) is used to quantify ET throughout, as it remains the most firmly observationally based measure of ET. The first data chapter of the thesis attributes causes of water-balance ET trends globally by considering all key drivers, including climate, land use and vegetation effects. The study statistically accounts for ET trends in energy-limited "wet" and water-limited "dry" river catchments and finds ET is primarily controlled by precipitation in both environments (with precipitation explaining 45-55% and 80-95% of interannual variability and trends in ET in wet and dry catchments, respectively). There is some evidence for vegetation effects based on model simulations, but the detection and attribution of ET trends is hindered by uncertainties in the data available for global analysis and the lack of direct observations of vegetation properties covering the study period 1960-1999. Making use of high quality streamflow observations for Australia, the second chapter quantifies recent CO₂ effects on runoff, ET and vegetation cover across Australian river catchments in varying climates. The CO₂ effect was quantified by cncurrently analysing vegetation cover (Normalised Difference Vegetation Index) and water-balance ET, relying solely on observations. Contrary to common expectation, the analysis shows that vegetation is not only greening, but also consuming more water in sub-humid and semi-arid climates, leading to significant (24-28%) reductions in runoff over the period 1982-2010. The analysis pointed to increased runoff in the wet and arid climates but the results were not statistically significant and it was thus not possible to detect a CO₂ effect in the wettest or driest climates based on the measurements. Finally, future water resources in Australia are projected using bias-corrected state-of-the-art climate model projections to drive the Land Surface Processes and eXchanges dynamic global vegetation model (LPX). LPX explicitly simulates vegetation CO₂ responses and is shown to capture observed CO₂ effects on ET. LPX results are contrasted with projections from the empirical Budyko framework, which accounts for only the climatic effects on ET. Future precipitation patterns remain highly uncertain across much of Australia, but predicted vegetation effects are robust. Vegetation is shown to buffer the effects of climate change, alleviating water stress in highly poplated regions with robust declines in precipitation due to CO₂-induced water savings. In northern Australia, CO₂ fertilisation reduces runoff but is accompanied by increased vegetation productivity. The findings of this thesis highlight the importance of considering vegetation in studies of water resources. Recent increases in atmospheric CO₂ are shown to have left a detectable imprint on Australian ecosystems, and the impacts are projected to continue to the end of the 21st century and beyond.

Climate change is projected to increase the imbalance between the supply (precipitation) and atmospheric demand for water (i.e. increased potential evapotranspiration), stressing plants in water-limited environments. Plants may be able to offset increasing aridity because rising CO2 increases water-use-efficiency. CO2 fertilization has also been cited as one of the drivers of the widespread ‘greening’ phenomenon. However, attributing the size of this CO2 fertilization effect is complicated, due in part to a lack of long-term vegetation monitoring and interannual to decadal-scale climate variability. In this study we asked the question, how much has CO2 contributed towards greening? We focused our analysis on a broad aridity gradient spanning eastern Australia’s woody ecosystems. Next we analysed 38-years of satellite remote sensing estimates of vegetation greenness (normalized difference vegetation index, NDVI) to examine the role of CO2 in ameliorating climate change impacts. Multiple statistical techniques were applied to separate the CO2-attributable effects on greening from the changes in water supply and atmospheric aridity. Widespread vegetation greening occurred despite a warming climate, increases in vapor pressure deficit, and repeated record-breaking droughts and heatwaves. Between 1982–2019 we found that NDVI increased (median 11.3 %) across 90.5 % of the woody regions. After masking disturbance effects (e.g. fire), we statistically estimated an 11.7 % increase in NDVI attributable to CO2, broadly consistent with a hypothesized theoretical expectation of an 8.6 % increase in water-use-efficiency due to rising CO2. In contrast to reports of a weakening CO2 fertilization effect, we found no consistent temporal change in the CO2 effect. We conclude rising CO2 has mitigated the effects of increasing aridity, repeated record-breaking droughts, and record-breaking heat waves in eastern Australia. However, we were unable to determine whether trees or grasses were the primary beneficiary of the CO2 induced change in water-use-efficiency, which has implications for projecting future ecosystem resilience. A more complete understanding of how CO2 induced changes in water-use-efficiency affect trees and non-tree vegetation is needed.

Knowledge of how water stress impacts the carbon and water cycles is a key uncertainty in terrestrial biosphere models.\ud - We tested a new profit maximisation model, where photosynthetic uptake of CO2 is optimally traded against plant hydraulic function, as an alternative to the empirical functions commonly used in models to regulate gas exchange during periods of water stress. We conducted a multi-site evaluation of this model at the ecosystem scale, before and during major droughts in Europe. Additionally, we asked whether the maximum hydraulic conductance in the soil-plant\ud continuum (

The Community Atmosphere Biosphere Land Exchange (CABLE) land surface model overestimates evapotranspiration (E) at numerous flux tower sites during boreal spring. The overestimation of E is not eliminated when the nonlinear dependence of soil evaporation on soil moisture or a simple litter layer is introduced into the model. New resistance terms, previously developed from a pore‐scale model of soil evaporation, are incorporated into the treatment of under canopy water vapor transfer in CABLE. The new resistance terms reduce the large positive bias in spring time E at multiple flux tower sites and also improve the simulation of daily sensible heat flux. The reduction in the spring E bias allows the soil to retain water into the summer, improving the seasonality of E. The simulation of daily E is largely insensitive to the details of the implementation of the pore model resistance scheme. The more physically based treatment of soil evaporation presented here eliminates the need for empirical functions that reduce evaporation as a function of soil moisture that are included in many land surface models., Journal of Advances in Modeling Earth Systems, 9 (1), ISSN:1942-2466

Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future., Biogeosciences, 15 (11), ISSN:1726-4170

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model‐data intercomparison project, where we tested the ability of ten terrestrial biosphere models to reproduce observed sensitivity of ecosystem productivity to rainfall changes at ten sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed.