Effects of groundwater on land-atmosphere interactions during droughts and heatwaves in Australia

Droughts and heatwaves impact human and natural systems in Australia, and groundwater helps ecosystems survive these extremes. However, how groundwater affects land-atmosphere interactions during droughts and heatwaves has rarely been examined. This thesis explores the influence of groundwater on the impact and the intensity of heatwaves and droughts, focusing on southeast Australia, by using the Community Atmosphere-Biosphere Land Exchange (CABLE) land surface model (LSM). First, this thesis evaluates multiple ways to represent key processes in CABLE using a comprehensive set of observations in an Australian water-limited site. CABLE simulates the land hydrology during droughts and heatwaves well, if high-resolution observations of evaporation and root zone processes are available to configure the model and to select appropriate parameterizations. The results highlight both the opportunity and the challenge in improving LSMs for simulating droughts and heatwaves well. Second, using the most realistic model configuration from the model evaluation step, this thesis examines how groundwater influences ecosystems during co-occurring heatwaves and droughts. Results demonstrate the importance of groundwater in sustaining transpiration for the first 1–2 years of multi-year droughts. Results also demonstrate how the lack of deep roots or stomatal closure under high vapour pressure deficit or high temperature can reduce the role of groundwater. Given these are not always represented in LSMs, these results indicate the potential for overestimating the impact of droughts and heatwaves in climate model simulations. Third, coupled experiments using Weather Research and Forecasting (WRF) and CABLE examined the influence of groundwater on heatwave intensity in southeast Australia. Results show that groundwater moistens and cools both the land surface and atmospheric boundary layer during heatwaves. Groundwater reduces maximum air temperatures near the surface by up to 3 °C, and by up to 1 °C through the atmospheric boundary layer, but only where the water table depth was shallow, and overlain by forests. Overall, this work quantifies the impact of groundwater on heatwave intensity and identifies the impacted regions over southeast Australia. The thesis concludes with areas for future model development, with the goal of further improving the simulations of heatwaves and droughts which are projected to increase in many regions of the world due to climate change

Predicting resilience through the lens of competing adjustments to vegetation function

There is a pressing need to better understand ecosystem resilience to droughts and heatwaves. Eco-evolutionary optimization approaches have been proposed as means to build this understanding in land surface models and improve their predictive capability, but competing approaches are yet to be tested together. Here, we coupled approaches that optimize canopy gas exchange and leaf nitrogen investment, respectively, extending both approaches to account for hydraulic impairment. We assessed model predictions using observations from a native Eucalyptus woodland that experienced repeated droughts and heatwaves between 2013 and 2020, whilst exposed to an elevated [CO2] treatment. Our combined approaches improved predictions of transpiration and enhanced the simulated magnitude of the CO2 fertilization effect on gross primary productivity. The competing approaches also worked consistently along axes of change in soil moisture, leaf area, and [CO2]. Despite predictions of a significant percentage loss of hydraulic conductivity due to embolism (PLC) in 2013, 2014, 2016, and 2017 (99th percentile PLC > 45%), simulated hydraulic legacy effects were small and short-lived (2 months). Our analysis suggests that leaf shedding and/or suppressed foliage growth formed a strategy to mitigate drought risk. Accounting for foliage responses to water availability has the potential to improve model predictions of ecosystem resilience

Identifying areas at risk of drought-induced tree mortality across South-Eastern Australia

South-East Australia has recently been subjected to two of the worst droughts in the historical record (Millennium Drought, 2000–2009 and Big Dry, 2017–2019). Unfortunately, a lack of forest monitoring has made it difficult to determine whether widespread tree mortality has resulted from these droughts. Anecdotal observations suggest the Big Dry may have led to more significant tree mortality than the Millennium drought. Critically, to be able to robustly project future expected climate change effects on Australian vegetation, we need to be able to assess the vulnerability to drought of Australian trees. Here, we implemented a model of plant hydraulics into the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. We parameterised the drought response behaviour of five broad vegetation types, based on a common garden dry-down experiment with species originating across a rainfall gradient (188–1125 mm yr1 ) across South-East Australia. The new hydraulics model significantly improved (~35–45 % reduction in root mean square error) CABLE’s previous predictions of latent heat fluxes during periods of water stress at two eddy covariance sites in Australia. Landscape-scale predictions of the greatest percentage loss of hydraulic conductivity (PLC), 40–60 %, were broadly consistent with satellite estimates of regions of the greatest change in both droughts. In neither drought did CABLE predict that trees would have reached critical PLC in widespread areas (i.e. it projected a low mortality risk), although the model highlighted critical levels near the desert regions of South-East Australia where few trees live. Overall, our experimentally constrained model results imply significant resilience to drought conferred by hydraulic function, but also highlight critical data and scientific gaps. Our approach presents a promising avenue to integrate experimental data and make regional-scale predictions of potential drought-induced hydraulic failure

Temporal Convolutional Network-Based Axle Load Estimation from Pavement Vibration Data

Measuring the axle loads of vehicles with more accuracy is a crucial step in weight enforcement and pavement condition assessment. This paper proposed a vibration-based method, which has an extended sensing range, high temporal sampling rate, and dense spatial sampling rate, to estimate axle loads in concrete pavement using distributed optical vibration sensing (DOVS) technology. Temporal convolutional networks (TCN), which consist of non-causal convolutional layers and a concatenate layer, were proposed and trained by over 6000 samples of vibration data and ground truth of axle loads. Moreover, the TCN could learn the complex inverse mapping between pavement structure inputs and outputs. The performance of the proposed method was calibrated in two field tests with various conditions. The results demonstrate that the proposed method obtained estimated axle loads within 11.5% error, under diverse circumstances that consisted of different pavement types and loads moving at speeds ranging from 0~35 m/s. The proposed method demonstrates significant promise in the field of axle load reconstruction and estimation. Its error, closely approaching the 10% threshold specified by LTPP, underscores its efficacy. Additionally, the method aligns with the standards set by Cost-323, with an error level-up to category C. This indicates its capability to provide valuable support in the assessment and decision-making processes related to pavement structure conditions.ISSN:2076-341

Porous Hexagonal Boron Nitride as Solid-Phase Microextraction Coating Material for Extraction and Preconcentration of Polycyclic Aromatic Hydrocarbons from Soil Sample

Sample pretreatment plays important role in the analysis and detection of trace pollutants in complex matrices, such as environmental and biological samples. The adsorption materials of sample pretreatment receive considerable attention, which has a significant effect on the sensitivity and selectivity of the analytical method. In this work, the porous hexagonal boron nitride (h-BN) was utilized as a coating material of solid-phase microextraction (SPME) to extract and preconcentrate polycyclic aromatic hydrocarbons (PAHs) prior to separation and detection with GC-FID. Attributed to the multiple interactions including hydrophobicity, hydrogen bonding and strong π–π interaction, the h-BN coating showed excellent extraction performance for PAHs. Under the optimal conditions, the method showed the linear relationship in the range of 0.1–50 ng mL−1 for acenaphthene, 0.05–50 ng mL−1 for pyrene, and 0.02–50 ng mL−1 for fluorene, phenanthrene and anthracene with a correlation coefficient (R2) not lower than 0.9910. The enrichment factors were achieved between 1526 and 4398 for PAHs with h-BN as SPME fiber coating. The detection limits were obtained in the range of 0.004–0.033 ng mL−1, which corresponds to 0.08–0.66 ng g−1 for soil. The method was successfully applied to analysis of real soil samples. The recoveries were determined between 78.0 and 120.0% for two soil samples. The results showed that h-BN material provided a promising alternative in sample pretreatment and analysis

Evaluating a land surface model at a water-limited site: implications for land surface contributions to droughts and heatwaves

Land surface models underpin coupled climate model projections of droughts and heatwaves. However, the lack of simultaneous observations of individual components of evapotranspiration, concurrent with root-zone soil moisture, has limited previous model evaluations. Here, we use a comprehensive set of observations from a water-limited site in southeastern Australia including both evapotranspiration and soil moisture to a depth of 4.5 m to evaluate the Community Atmosphere-Biosphere Land Exchange (CABLE) land surface model. We demonstrate that alternative process representations within CABLE had the capacity to improve simulated evapotranspiration, but not necessarily soil moisture dynamics-highlighting problems of model evaluations against water fluxes alone. Our best simulation was achieved by resolving a soil evaporation bias, using a more realistic initialisation of the groundwater aquifer state and higher vertical soil resolution informed by observed soil properties, and further calibrating soil hydraulic conductivity. Despite these improvements, the role of the empirical soil moisture stress function in influencing the simulated water fluxes remained important: using a site-calibrated function reduced the soil water stress on plants by 36 % during drought and 23 % at other times. These changes in CABLE not only improve the seasonal cycle of evapotranspiration but also affect the latent and sensible heat fluxes during droughts and heatwaves. The range of parameterisations tested led to differences of similar to 150 W m(-2) in the simulated latent heat flux during a heatwave, implying a strong impact of parameterisations on the capacity for evaporative cooling and feedbacks to the boundary layer (when coupled). Overall, our results highlight the opportunity to advance the capability of land surface models to capture water cycle processes, particularly during meteorological extremes, when sufficient observations of both evapotranspiration fluxes and soil moisture profiles are available.ISSN:1027-5606ISSN:1607-793

Predicting resilience through the lens of competing adjustments to vegetation function

There is a pressing need to better understand ecosystem resilience to droughts and heatwaves. Eco-evolutionary optimization approaches have been proposed as means to build this understanding in land surface models and improve their predictive capability, but competing approaches are yet to be tested together. Here, we coupled approaches that optimize canopy gas exchange and leaf nitrogen investment, respectively, extending both approaches to account for hydraulic impairment. We assessed model predictions using observations from a native Eucalyptus woodland that experienced repeated droughts and heatwaves between 2013 and 2020, whilst exposed to an elevated [CO2] treatment. Our combined approaches improved predictions of transpiration and enhanced the simulated magnitude of the CO2 fertilization effect on gross primary productivity. The competing approaches also worked consistently along axes of change in soil moisture, leaf area, and [CO2]. Despite predictions of a significant percentage loss of hydraulic conductivity due to embolism (PLC) in 2013, 2014, 2016, and 2017 (99th percentile PLC > 45%), simulated hydraulic legacy effects were small and short-lived (2 months). Our analysis suggests that leaf shedding and/or suppressed foliage growth formed a strategy to mitigate drought risk. Accounting for foliage responses to water availability has the potential to improve model predictions of ecosystem resilience