Recent studies have highlighted the important role of vegetated coastal ecosystems in atmospheric carbon sequestration. Saltmarshes constitute 30 % of these ecosystems globally and are the primary intertidal coastal wetland habitat outside the tropics. Eddy covariance (EC) is the main method for measuring biosphere–atmosphere fluxes, but its use in coastal environments is rare. At an Australian temperate saltmarsh site on French Island, Victoria, we measured CO2 and water gas concentration gradients, temperature, wind speed, and radiation. The marsh was dominated by a dense cover of Sarcocornia quinqueflora. Fluxes were seasonal, with minima in winter when vegetation is dormant. Net ecosystem productivity (NEP) during the growing season averaged 10.54 g CO2 m−2 d−1, decreasing to 1.64 g CO2 m−2 d−1 in the dormant period, yet the marsh remained a CO2 sink due to some sempervirent species. Ecosystem respiration rates were lower during the dormant period compared with the growing season (1.00 vs. 1.77 µmolCO2m-2s-1), with a slight positive relationship with temperature. During the growing season, fluxes were significantly influenced by light levels, ambient temperatures, and humidity, with cool temperatures and cloud cover limiting NEP. The ecosystem water use efficiency of 0.86 g C kg−1 H2O was similar to other C3 intertidal marshes, and evapotranspiration averaged 2.48 mm d−1 during the growing season.

The vegetation dynamics in highly heterogeneous landscapes (e.g., riparian vegetation surrounding waterholes and oases) are difficult to detect from large (e.g., MODIS) and moderate (e.g., Landsat) spatial resolution remote sensing products. Within a “classify-to-monitor” approach, a method to monitor spatially heterogeneous riparian vegetation dynamics is developed by integrating high spatial resolution discrete return airborne LiDAR data (1 m pixels) with moderate resolution Landsat fraction of Photosynthetically Active Radiation absorbed by vegetation (fPAR) data (30 m). LiDAR was used to identify and classify vegetation surrounding permanent waterholes within the Cooper Creek floodplain, in dryland Australia. These waterholes are important areas for ecological conservation given their highly spatially heterogeneous vegetation structure. Landsat fPAR was temporally decomposed into persistent and recurrent components and then integrated with the LiDAR-derived vegetation classes. The LiDAR data were used as a mask to separate the fPAR signal of each vegetation class, capturing their specific dynamics and which fPAR component they are associated with. The newly developed method provides the means to improve the interpretation of Landsat fPAR by monitoring distinct vegetation functional groups within each Landsat pixel. Results showed that LiDAR data provided good estimates of vegetation cover compared to field measurements (R2=0.952). LiDAR data identified different vegetation structural classes within the riparian zone. The integration of LiDAR and Landsat data permitted the distinction of temporal patterns of each vegetation structural class, uncovering the specific temporal and spatial variability of fPAR that would otherwise be undetected. Landsat fPAR provided information on which vegetation component contributed to the fPAR variability in each class, thus providing the means for enhanced ecological interpretation of the temporally decomposed fPAR components. The method can be applied to other similar highly spatially heterogeneous ecosystems to monitor structurally specific vegetation dynamics more accurately than if only using moderate spatial resolution time-series optical satellite imagery.

Land surface phenology (LSP) is useful to understand patterns of terrestrial ecosystems. Detecting LSP in drylands is more challenging when compared to agricultural and mesic environments due to vegetation heterogeneity, the presence of evergreen and seasonal species, and the dominant role of water (which is often received episodically with variable timing) in determining vegetation growth. In this study, LiDAR-derived vegetation classes are defined to guide and improve the interpretation of LSP metrics extracted using temporally decomposed Landsat fPAR time series. This method was applied to waterholes within the Cooper Creek floodplain, in dryland Australia, which are important for ecological conservation. Results showed that phenology is mostly associated with the recurrent vegetation (approximately 80% of all identified phenological events) in all waterholes. However, during high streamflow periods, the number of phenological events associated with the persistent vegetation greatly increased (up to 40% of the identified events). Non-annual phenology was also identified, with more than one phenological event occurring across a water year during high streamflow periods. The duration of the phenological events of the persistent vegetation exceeded one water year during periods of high streamflow. Phenological differences of the LiDAR-derived vegetation classes occupying the riparian zone of the waterholes were also identified. Streamflow movement across the floodplain exerts an important influence on the vegetation phenology, as suggested by a lag in the phenology when comparing southern and northern waterholes. The method developed herein can be applied to other highly spatially heterogeneous ecosystems where vegetation species simultaneously present permanent and seasonal patterns. Knowing the vegetation life cycle is useful to understand terrestrial ecosystems. However, understanding these cycles in drylands is more complex when compared to agricultural and mesic environments due to heterogeneity and presence of evergreen and seasonal vegetation. In this study, vegetation structure is characterized to guide and improve the interpretation of the vegetation cycles identified using the temporally decomposed time series of a vegetation index. This method was applied at the Cooper Creek floodplain, in dryland Australia. Results showed vegetation cycles are mostly associated with the seasonal vegetation (approximately 80% of all identified cycles). However, during high streamflow periods, the number of cycles associated with the evergreen vegetation greatly increased (up to 40% of the identified events). Multiple cycles were also identified within one water year during high streamflow periods. The duration of the cycles of the evergreen vegetation exceeded one water year during periods of high streamflow. Differences on the life cycle of the different vegetation types were also identified. Streamflow exerts an important influence on the vegetation life cycles by creating a north-to-south gradient. The method developed herein can be applied to other highly spatially heterogeneous ecosystems where vegetation species simultaneously present permanent and seasonal patterns. Vegetation phenology in riparian zones of waterholes in central Australia is studied by integrating LiDAR data and Landsat time series LiDAR-derived vegetation classes assisted in interpreting temporally decomposed Landsat fPAR time series providing ecohydrological insights Reflective satellite mixed pixel problem commonly found in drylands was addressed by extracting the phenology of each vegetation component

Non-perennial rivers are valuable water resources that support millions of humans globally, as well as unique riparian ecosystems. In Australia, the Earth’s driest inhabited continent, over 70% of rivers are non-perennial due to a combination of ancient landscape, dry climates, highly variable rainfall regimes, and human interventions that have altered riverine environments. Here, we review Australian non-perennial river research incorporating geomorphology, hydrology, biogeochemistry, ecology, and Indigenous knowledges. The dominant research themes in Australia were drought, floods, salinity, dryland ecology, and water management. Future research will likely follow these themes but must address emerging threats to river systems due to climate change and other anthropogenic impacts. Four high level opportunities for future research are identified, namely: (1) integrating Indigenous and western scientific knowledge; (2) quantifying climate change impacts on hydrological and biological function; (3) clarifying the meaning and measurement of “restoration” of non-perennial systems; and (4) understanding the role of groundwater. These challenges will require inter- and multi-disciplinary efforts supported by technological advances. The evolving body of knowledge about Australian rivers provides a foundation for comparison with other dryland areas globally where recognition of the importance of non-perennial rivers is expanding.

Understanding hydrological connectivity is essential to investigate ecological processes in river catchments and floodplains. Assessing flooding behavior, including flooded areas and connection times, is required to analyze hydrological connectivity in river floodplains. Deep learning, especially Convolutional Neural Networks (CNNs), is an attractive alternative to hydrodynamic modeling, which is more computationally expensive. This paper aims to develop a methodology to analyze the functional connectivity in remote and field measurement data-scarce areas using remote sensing data, CNN models, and connectivity metrics. The northern Lakes of the Narran River catchment, located in the Condamine-Balonne River floodplain in New South Wales, Australia, is the showcase for this method. One-dimensional CNN and two-dimensional U-Net configurations were applied and yielded comparable flood extents to the satellite images with Hit Rate values of 0.853 and 0.873, respectively. Two algorithms for determining hydrological connectivity were investigated, including the geostatistical Connectivity Function (CF) and the newly proposed Potential Connection Length (PCL). It was found that the connection along the main Narran River stream was more substantial than between the river and the floodplain lakes. The analysis using the PCL shows that the connectivity patterns in different stages of a flood event can vary depending on the initial condition of the floodplain. The overall conclusion from this work is that hydrological connectivity can be assessed computationally efficiently using only remote sensing, discharge data, and CNN models.

Previous studies on saltwater up-coning are mostly based on the assumption of a homogeneous aquifer and neglect the effect of heterogeneity. A numerical study was carried out to explore the impact of a low-permeability ( k ) layer on the pumping efficiency under threats of saltwater up-coning. It is found that the presence of the low- k layer could impede up-coning of saltwater, thereby improving significantly pumping efficiency, as expected. For the cases adopted, when the permeability of the 2 m thick low- k layer is three orders of magnitude less than that of the corresponding homogeneous aquifer, the pumping duration (i.e., the time before the salinity of pumped water reaches 2%) can be up to about 10 times longer than that of the homogeneous aquifer case. Additionally, a sound linear relationship could be developed between the normalized pumping duration of the layered case ( E ) (defined as the difference of the pumping duration between layered and homogeneous cases relative to the pumping duration in the homogeneous case) and the permeability of the homogeneous aquifer relative to that of the low- k layer ( β ). However, a short low- k layer may lead to the failure of this linear relationship. Moreover, a thicker low- k layer leads to a larger E when all other conditions are unchanged. When varying the location of the low- k layer, the large E occurs for the low- k layer located below and near the well bottom. The results obtained in the current study offer significant implications for preventing saltwater up-coning and improving the pumping efficiency through natural and artificial barriers.

Land use affects evapotranspiration rates and is a primary driver of the catchment water balance. The water balance of two catchments in southeastern Australia dominated by either grazed pasture or blue gum ( Eucalyptus globulus ) plantation was studied, focusing on the patterns of evapotranspiration (ET) throughout the year. Rainfall, streamflow, and groundwater levels measured between 2015-2019 were combined to estimate annual ET using a water balance equation. In the pasture, eddy covariance was used to measure ET from the catchment. Sap flow measurements were used to estimate tree transpiration in May 2017 – May 2018 and Feb 2019 – Feb 2021 in two different plots within the plantation. The tree transpiration rates were added to direct evaporation, estimated as a percentage of annual rainfall, to calculate ET from the plantation catchment. ET in the pasture showed strong seasonal cycles with very low ET rates in summer and ET rates in spring that were larger than the transpiration rates in the plantation, where trees transpired consistently throughout the year. The estimated annual ET from the water balance equation were comparable to ET estimated from other measurements. In the pasture, ET on average accounted for 88% of annual rainfall, while ET in the plantation was on average 93% of rainfall, exceeding it in the years with annual rainfall lower than 500 mm. The difference between the ET rates in the plantation and the pasture were approximately 30 to 50 mm y­ . The larger ET rates in the plantation are reflected in a gradual decrease in the groundwater storage. The differences in ET rates were thus enough to cause a decrease in groundwater storage in the plantation, while the groundwater levels in the pasture remained stable.

Determining the sources and mean transit times (MTTs) of water that generates streamflows is important for understanding and managing headwater catchments. The sources and especially the MTTs of water that contributes to streamflow in seasonally intermittent streams are far less studied than for perennial streams. Here we use major ions, dissolved organic carbon, stable isotopes, radon and tritium to quantify the sources and MTTs of intermittent streamflows in three headwater catchments (Banool, McGill and Plantation) from a semi-arid area in southeast Australia. At the start of streamflows, the MTTs of stream water varied from 25 to 42 years in the 1.51 km(2) Banool catchment, 3 to 4 years in the 3.38 km(2) McGill catchment and 9 to 14 years in the 3.41 km(2) Plantation catchment. Winter rainfall increased the relative contribution of younger waters in all three catchments. During higher winter streamflows, the MTTs of stream water reduced to <= 5 years in the Banool catchment and <1 year in the McGill and Plantation catchments. The sources of streamflow also differed between the catchments. Regional groundwater, which close to the stream has a residence time of several hundred years, dominated in the Banool catchment, whereas younger water (residence times of up to 9 years) stored in the riparian zone was the main source in the McGill and Plantation catchments. The differences in MTTs between the catchments may reflect land-use differences, especially the presence of plantation forests in the McGill and Plantation catchments. Overall, due to being less well-connected to the regional groundwater, the MTTs of these intermittent streams are far shorter than those reported for perennial headwater streams in southeast Australia. The short MTTs indicate that these intermittent streams are vulnerable to short-term variations in rainfall.

The Millennium Drought lasted more than a decade and is notable for causing persistent shifts in the relationship between rainfall and runoff in many southeastern Australian catchments. Research to date has successfully characterised where and when shifts occurred and explored relationships with potential drivers, but a convincing physical explanation for observed changes in catchment behaviour is still lacking. Originating from a large multi-disciplinary workshop, this paper presents and evaluates a range of hypothesised process explanations of flow response to the Millennium Drought. The hypotheses consider climatic forcing, vegetation, soil moisture dynamics, groundwater, and anthropogenic influence. The hypotheses are assessed against evidence both temporally (e.g. why was the Millennium Drought different to previous droughts?) and spatially (e.g. why did rainfall–runoff relationships shift in some catchments but not in others?). Thus, the strength of this work is a large-scale assessment of hydrologic changes and potential drivers. Of 24 hypotheses, 3 are considered plausible, 10 are considered inconsistent with evidence, and 11 are in a category in between, whereby they are plausible yet with reservations (e.g. applicable in some catchments but not others). The results point to the unprecedented length of the drought as the primary climatic driver, paired with interrelated groundwater processes, including declines in groundwater storage, altered recharge associated with vadose zone expansion, and reduced connection between subsurface and surface water processes. Other causes include increased evaporative demand and harvesting of runoff by small private dams. Finally, we discuss the need for long-term field monitoring, particularly targeting internal catchment processes and subsurface dynamics. We recommend continued investment in the understanding of hydrological shifts, particularly given their relevance to water planning under climate variability and change.

Modelling the water transport along the soil-plant-atmosphere continuum is fundamental to estimating and predicting transpiration fluxes. A tree-hydrodynamic model (SPAC-3Hpy :::::::: FETCH3) for the water fluxes across the soil-plant-atmosphere continuum is presented here. The model combines the water transport pathways to one vertical dimension, and assumes that the water flow through the soil, roots, and above-ground xylem can be approximated as a flow in porous media. This results in a system of three partial differential equations resembling the Richardson-Richards equation describing the transport of 5 water through the plant system and with additional terms representing sinks and sources for the transfer of water from to the soil to the roots and from the leaves to the atmosphere. The numerical scheme, developed in Python 3, was tested against exact analytical solutions for steady state and transient conditions using simplified but realistic model parametrizations. The model was also used to simulate a previously published case study where observed transpiration rates were available in order to evaluate model performance. With the same model setup as the published case study, SPAC-3Hpy ::::::: FETCH3 : results were in 10 agreement with observations. Through a rigorous coupling of soil, roots , and hydroactive xylem, SPAC-3Hpy ::::: xylem, :::: and :::: stem :::::: xylem, ::::::: FETCH3 : can account for variable ::::: water capacitance while conserving mass and the continuity of the water potential between these three layers. SPAC-3Hpy ::::::: FETCH3 : provides a ready-to-use open access numerical model for the simulation of water fluxes across the soil-plant-atmosphere continuum.

Anabranching rivers are characterized by multiple active channels. Vegetation, flow regime and sediment retention are critical components for the formation, evolution and stability of these rivers; however, the connections relating river dynamics with riparian vegetation development and distribution are still not well known. This review discusses the relationship between anabranching rivers and riparian vegetation, showing examples of how vegetation affects anabranching rivers and how it is also affected by river dynamics. Consequences of poor management and human activities that can disrupt river–vegetation systems are also explored, presenting some examples of modifications to the stability and longevity of anabranching rivers. Challenges to design and implement appropriate policy and management practices in anabranching rivers are most frequently driven by poor experimental evidence due to difficulties in collecting data in these often remote and large river systems. Remote sensing technologies that account for key interactions between riparian vegetation, river flow and morphology changes can provide means to overcome these challenges.

Abstract. Modelling the water transport along the soil–plant–atmosphere continuum is fundamental to estimating and predicting transpiration fluxes. A Finite-difference Ecosystem-scale Tree Crown Hydrodynamics model (FETCH3) for the water fluxes across the soil–plant–atmosphere continuum is presented here. The model combines the water transport pathways into one vertical dimension, and assumes that the water flow through the soil, roots, and above-ground xylem can be approximated as flow in porous media. This results in a system of three partial differential equations, resembling the Richardson–Richards equation, describing the transport of water through the plant system and with additional terms representing sinks and sources for the transfer of water from the soil to the roots and from the leaves to the atmosphere. The numerical scheme, developed in Python 3, was tested against exact analytical solutions for steady state and transient conditions using simplified but realistic model parameterizations. The model was also used to simulate a previously published case study, where observed transpiration rates were available, to evaluate model performance. With the same model setup as the published case study, FETCH3 results were in agreement with observations. Through a rigorous coupling of soil, root xylem, and stem xylem, FETCH3 can account for variable water capacitance, while conserving mass and the continuity of the water potential between these three layers. FETCH3 provides a ready-to-use open access numerical model for the simulation of water fluxes across the soil–plant–atmosphere continuum.

The establishment and expansion of commercial plantations for timber production and carbon sequestration raises concerns because of their large water use. Eucalyptus globulus (blue gum) is one of the most planted species globally, as it grows rapidly and is adaptable to a range of climatic conditions. The dearth of experimental observations on water use and growth in blue gum plantations in their early years after establishment makes it difficult to develop management practices. This study quantified the trade-offs between water use and carbon assimilation in a blue gum plantation in the first 4 years after establishment. The study site is located in southwest Victoria, Australia, where energy, water and CO2 fluxes were continuously measured above the tree canopy for 4 years after the trees were planted. During the first year after establishment, understory vegetation and ecosystem respiration had a major impact on the net ecosystem exchange (NEE), with the plantation being a net carbon source. Subsequently, the trees started dominating the contributions to NEE, and after approximately 2 years the plantation became a consistent carbon sink. These shifts in NEE were accompanied by smaller increases in annual evapotranspiration rates, which was 70% of the annual precipitation in the first year and 74% in the 3rd year of measurements. As a result, yearly averages of water use efficiency increased from 2.86 gC kg(-1)H(2)O in 2018 to 4.3 gC kg(-1)H(2)O in 2020, following tree development. This shows a remarkable increase in productivity at the expense of a small amount of water.

Remotely sensed evapotranspiration (ET) rates can provide an additional constraint on the calibration of groundwater models beyond typically-used water table (WT) level observations. The value of this constraint, measured in terms of reductions in model error, however, is expected to vary with the method by which it is imposed and by how closely the ET flux is dependant to groundwater levels. To investigate this variability, four silvicultural sites with different access to groundwater were modeled under three different model-data configurations. A benchmark model that used only WT levels for calibration was compared to two alternatives: one in which satellite remotely sensed ET rates from MODIS-CMRSET were also included in model calibration, and one in which the satellite ET data were assimilated, through the Ensemble Kalman Filter, into the model. Large error reductions in ET flux outputs were achieved when CMRSET data were used to calibrate the model. Assimilation of CMRSET data further improved the model performance statistics where the WT was < 6.5 m deep. It is advantageous to use spatially distributed actual ET data to calibrate groundwater models where it is available. In situations where vegetation has direct access to groundwater, assimilation of ET observations is likely to improve model performance.

Modelling the water transport along the soil-plant-atmosphere continuum is fundamental to estimating and predicting transpiration fluxes. A tree-hydrodynamic model (SPAC-3Hpy) for the water fluxes across the soil-plant-atmosphere continuum is presented here. The model combines the water transport pathways to one vertical dimension, and assumes that the water flow through the soil, roots, and above-ground xylem can be approximated as a flow in porous media. This results in a system of three partial differential equations resembling the Richardson-Richards equation describing the transport of water through the plant 5 system and with additional terms representing sinks and sources for the transfer of water from to the soil to the roots and from the leaves to the atmosphere. The numerical scheme, developed in Python 3, was tested against exact analytical solutions for steady state and transient conditions using simplified but realistic model parametrizations. The model was also used to simulate a previously published case study where observed transpiration rates were available in order to evaluate model performance. With the same model setup as the published case study, SPAC-3Hpy results were in agreement with observations. Through a 10 rigorous coupling of soil, roots, and hydroactive xylem, SPAC-3Hpy can account for variable capacitance while conserving mass and the continuity of the water potential between these three layers. SPAC-3Hpy provides a ready-to-use open access numerical model for the simulation of water fluxes across the soil-plant-atmosphere continuum. 1 https://doi.org/10.5194/gmd-2021-270 Preprint. Discussion started: 2 September 2021 c © Author(s) 2021. CC BY 4.0 License.

Water smart cities are increasing their use of irrigation and misting to cope with extreme heat and drought. This is being enabled by widespread use of rainwater tanks, stormwater capture and storage systems, and recycled sewage wastewater to irrigate street trees as well as private and public green spaces. These alternative water resources provide new options for cities to better withstand and function under extreme summer heatwave conditions with little or no impact on drinking water supplies. Small‐scale approaches to evaporatively cool urban animals, vegetation habitat, and people are showing initial success. However, ongoing testing and modeling are needed to understand the impacts of scaling up these interventions and to evaluate their cost‐effectiveness. We describe current innovations in irrigation of Australian cities to help policy development in other countries and cities experiencing similar climates with episodic summer heatwaves.

Biofiltration systems can help mitigate the impact of urban runoff as they can treat, retain and attenuate stormwater. It is important to select the optimal design characteristics of biofilters (e.g., vegetation, filter media depth) to ensure high treatment performance. Operational conditions (e.g., infiltration rate) can also lead to significant changes in biofilter treatment performance over time. The impact of specific operational conditions on water quality treatment performance of stormwater biofilters is still not well understood. Furthermore, despite the importance of design characteristics and operational conditions on biofilter treatment performance, there is a lack of models that can be used to determine the optimal design and operation. In this paper, we developed a series of statistical models to predict the Total Phosphorus (TP) and Total Nitrogen (TN) removal performance of stormwater biofilters using various numbers of design characteristics and operational conditions. These statistical models were tested using data collected from four extensive laboratory-scale biofilter column studies. It was found that all models performed relatively well with a Nash-Sutcliffe Efficiency (NSE) of 0.42 - 0.61 for TP and 0.37 - 0.63 for TN. The most important design characteristics were filter media type and depth for TP treatment, and vegetation type and submerged zone depth for TN treatment. In addition, infiltration rate and inflow concentrations were the operational conditions that greatly influence outflow TP and TN concentrations from stormwater biofilters. As such, these variables need to be carefully considered when designing and operating stormwater biofilters. Sensitivity analysis results indicate that the model was quite sensitive to all regression coefficients and intercepts. Additional modelling exercises show that the model could be further simplified by reducing the number of cross-correlated parameters. These models can be used by practitioners for not just optimising the design, but also operating biofilters using real-time monitoring and control to achieve optimum performance.

Understanding the applicability and uncertainties of methods for documenting recharge rates in semi-arid areas is important for assessing the successive effects of land-use changes and understanding groundwater systems. This study focuses on estimating groundwater recharge rates and understanding the impacts of land-use changes on recharge rates in a semi-arid area in southeast Australia. Two adjacent catchments were cleared ∼180 years ago following European settlement, and a eucalypt plantation forest was subsequently established ∼15 years ago in one of the catchments. Chloride mass balance analysis yields recharge rates of 0.2 to 61.6 mm yr−1 (typically up to 11.2 mm yr−1). The lower of these values probably represents recharge rates prior to land clearing, whereas the higher likely reflects recharge rates following the initial land clearing. The low pre-land-clearing recharge rates are consistent with the presence of old groundwater (residence times up to 24 700 years) and the moderate-to-low hydraulic conductivities (0.31 to 0.002 m d−1) of the aquifers. Recharge rates estimated from tritium activities and water table fluctuations reflect those following the initial land clearing. Recharge rates estimated using water table fluctuations (15 to 500 mm yr−1) are significantly higher than those estimated using tritium renewal rates (0.01 to 89 mm yr−1; typically <14.0 mm yr−1) and approach the long-term average annual rainfall (∼640 mm yr−1). These recharge rates are unrealistic given the estimated evapotranspiration rates of 500 to 600 mm yr−1 and the preservation of old groundwater in the catchments. It is likely that uncertainties in the specific yield results in the water table fluctuation method significantly overestimating recharge rates, and despite the land-use changes, the present-day recharge rates are relatively modest. These results are ultimately important for assessing the impacts of land-use changes and management of groundwater resources in semi-arid regions in Australia and elsewhere.

Abstract. The biophysical processes occurring in the unsaturated zone have a direct impact on the water table dynamics. Representing these processes through the application of unsaturated zone models of different complexity has an impact on the estimates of the volumes of water flowing between the unsaturated zone and the aquifer. These fluxes, known as net recharge, are often used as the shared variable that couples unsaturated to groundwater models. However, as recharge estimates are always affected by a degree of uncertainty, model–data fusion methods, such as data assimilation, can be used to inform these coupled models and reduce uncertainty. This study assesses the effect of unsaturated zone models complexity (conceptual versus physically based) to update groundwater model outputs, through the assimilation of actual evapotranspiration rates, for a water-limited site in South Australia. Actual evapotranspiration rates are assimilated because they have been shown to be related to the water table dynamics and thus form the link between remote sensing data and the deeper parts of the soil profile. Results have been quantified using standard metrics, such as the root mean square error and Pearson correlation coefficient, and reinforced by calculating the continuous ranked probability score, which is specifically designed to determine a more representative error in stochastic models. It has been found that, once properly calibrated to reproduce the actual evapotranspiration–water table dynamics, a simple conceptual model may be sufficient for this purpose; thus using one configuration over the other should be motivated by the specific purpose of the simulation and the information available.

Surface water connectivity between rivers and floodplain lakes is essential to maintain biodiversity and ecological functioning in floodplain wetlands. This study proposes a method to analyze the spatial and temporal connectivity using hydraulic modeling and freely available remote sensing data. A novel dynamic connectivity metric introduced here accounts for the entire flow path, which can be a substitute for flow connectivity indicators and statistical connectivity indicators. The metric allows comparing the hydrological connectivity between different phases of a flood event, between different flood events, and potentially between different catchments. The method was applied to the Northern Lakes of the Narran River catchment in New South Wales, Australia. The results indicate that there is no clear transition in the connectivity between different stages of a flood event in the flat Narran River wetland compared with other wetlands connecting to deeper river channels. Thus, the proposed metric brings a more comprehensive observation on hydrological connectivity in floodplain wetlands than previously developed metrics, which is expected to further support ecological and water management studies in river catchments.