Rain use efficiency gradients across Australian ecosystems.

Rain use efficiency (RUE) quantifies the ecosystem's capacity to use precipitation water to assimilate atmospheric CO2. The spatial distribution of RUE and its drivers across the Australian continent is largely unknown. This knowledge gap limits our understanding of the possible contribution of Australian ecosystems to global carbon assimilation. This study investigates the spatial distribution of RUE across diverse terrestrial ecosystems in Australia. The results show that RUE ranges from 0.43 (1st percentile) to 3.10 (99th percentile) g C m-2 mm-1 with a continental mean of 1.19 g C m-2 mm-1. About 68 % of the spatiotemporal variability of RUE can be explained by a multiple linear regression model primarily contributed by climatic predictors. Benchmarked by the model estimation, drainage-diverging/converging landscapes tend to have reduced/increased RUE. The model also revealed the impact of increasing atmospheric CO2 concentration on RUE. The continental mean RUE would increase by between 29.3 and 64.8 % by the end of this century under the SSP5-8.5 scenario in which the CO2 concentration is projected to double from the present level. This increase in projected RUE is attributed to the assumed greening effect of increasing CO2 concentration, which does not consider the saturation of CO2 fertilisation effect and the warming effect on increasing wildfire occurrence. Under the SSP1-2.6 scenario, RUE would decrease by about 7 %. This study provides baseline RUEs of various ecosystems in Australia for investigating the impacts of human interferences and climate change on the capacity of Australian vegetation to assimilate atmospheric CO2 under given precipitation.

Streamflow Prediction in Highly Regulated, Transboundary Watersheds Using Multi-Basin Modeling and Remote Sensing Imagery.

Despite the potential of remote sensing for monitoring reservoir operation, few studies have investigated the extent to which reservoir releases can be inferred across different spatial and temporal scales. Through evaluating 21 reservoirs in the highly regulated Greater Mekong region, remote sensing imagery was found to be useful in estimating daily storage volumes for within-year and over-year reservoirs (correlation coefficients [CC] ≥ 0.9, normalized root mean squared error [NRMSE] ≤ 31%), but not for run-of-river reservoirs (CC < 0.4, 40% ≤ NRMSE ≤ 270%). Given a large gap in the number of reservoirs between global and local databases, the proposed framework can improve representation of existing reservoirs in the global reservoir database and thus human impacts in hydrological models. Adopting an Integrated Reservoir Operation Scheme within a multi-basin model was found to overcome the limitations of remote sensing and improve streamflow prediction at ungauged cascade reservoir systems where previous modeling approaches were unsuccessful. As a result, daily regulated streamflow was predicted competently across all types of reservoirs (median values of CC = 0.65, NRMSE = 8%, and Kling-Gupta efficiency [KGE] = 0.55) and downstream hydrological stations (median values of CC = 0.94, NRMSE = 8%, and KGE = 0.81). The findings are valuable for helping to understand the impacts of reservoirs and dams on streamflow and for developing more useful adaptation measures to extreme events in data sparse river basins.

Prediction of effluent arsenic concentration of wastewater treatment plants using machine learning and kriging-based models.

This study evaluates the potential of kriging-based (kriging and kriging-logistic) and machine learning models (MARS, GBRT, and ANN) in predicting the effluent arsenic concentration of a wastewater treatment plant. Two distinct input combination scenarios were established, using seven quantitative and qualitative independent influent variables. In the first scenario, all of the seven independent variables were taken into account for constructing the data-driven models. For the second input scenario, the forward selection k-fold cross-validation method was employed to select effective explanatory influent parameters. The results obtained from both input scenarios show that the kriging-logistic and machine learning models are effective and robust. However, using the feature selection procedure in the second scenario not only made the architecture of the model simpler and more effective, but also enhanced the performance of the developed models (e.g., around 7.8% performance enhancement of the RMSE). Although the standard kriging method provided the least good predictive results (RMSE = 0.18 ug/l and NSE=0.75), it was revealed that the kriging-logistic method gave the best performance among the applied models (RMSE = 0.11 ug/l and NSE=0.90).

Transport and retention of graphene oxide nanoparticles in sandy and carbonaceous aquifer sediments: Effect of physicochemical factors and natural biofilm.

There is a paucity of information regarding the interaction between GONPs and natural aquifer sediments. Therefore, batch and column experiments were carried out to determine the transport, retention and attachment behavior of GONPs with the surfaces of native aquifer sediments. The experiments were performed with sediments comprising contrasting mineralogical features (sand grains, quartz and limestone sediments), at different temperatures, ionic strength and compositions. Uniquely, this research also investigated the effect of natural biofilm on the retention behavior of nanoparticles in porous media. The retention rate of GONPs at 22 °C was higher than at 4 °C. Moreover, there was greater retention of GONPs onto the surfaces of collectors at higher ionic strengths and cation valence. The retention profiles (RPs) of GONPs in pristine porous media at low ionic strength were linear, which contrasted with hyper-exponential shape of RPs at high ionic strength. The size-distribution analysis of retained GONPs showed decreasing particle diameter with increasing distance from the column inlet at high ionic strength and equal diameter at low ionic strengths. The GONP retention rate was higher for natural porous media than for sand, due to the presence of metal oxides heterogeneities. The presence of biofilm on porous media increased the retention rate of GONPs when compared to the porous media in the absence of biofilm.

Role of biofilm on virus inactivation in limestone aquifers: implications for managed aquifer recharge.

BACKGROUND: Virus, as nano-sized microorganisms are prevalent in aquifers, which threaten groundwater quality and human health wellbeing. Virus inactivation by attachment onto the limestone surfaces is a determining factor in the transport and retention behavior of virus in carbonaceous aquifers. METHODS: In the present study, the inactivation of MS2 -as a model virus- by attachment onto the surfaces of limestone grains was investigated in a series of batch experiments under different conditions such as limestone particle size distribution (0.25-0.50, 0.5-1 and 1-2 mm), treated wastewater and RO water, temperature (4 and 22 °C), initial MS2 concentrations (103-107 PFU/mL) and static and dynamic conditions. The experimental data of MS2 inactivation was also fitted to a non-linear kinetic model with shoulder and tailing. The characteristics of biofilm on the surfaces of limestone aquifer materials were assessed using scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM). RESULTS: The inactivation rate of virus decreased with increasing the adsorbent diameter. Furthermore, virus inactivation was greater at room temperature (22 °C) than 4 °C, in both static and dynamic conditions. The inactivation of virus via attachment onto the limestone aquifer materials in dynamic conditions was higher than under static conditions. In addition, fitting the experimental data with a kinetic model showed that virus inactivation was high at higher temperature, smaller limestone grains and dynamic conditions. Moreover, the experiments with treated wastewater showed that in authentic aqueous media, the virus inactivation was considerably higher than in RO water, due to the presence of either monovalent or divalent cations and surface roughness created by biofilms. CONCLUSION: Finally, in terms of managed aquifer recharge systems, the presence of biofilm increases bacteria and virus retention onto the aquifer surfaces. Graphical abstract.

Effect of bacteria and virus on transport and retention of graphene oxide nanoparticles in natural limestone sediments.

This research was conducted to evaluate the effect of co-transport of different-sized microorganisms on graphene oxide nanoparticles (GONPs) transport and retention in saturated pristine and biofilm-conditioned limestone columns. The transport and retention behavior of GONPs was studied in columns in the presence of MS2 -as a nano-sized- and Escherichia coli (E.coli) -as a micro-sized- microorganisms at low and high ionic strength conditions. Results showed no changes in GONPs transport and retention at high ionic strength in the presence of MS2 or E. coli, which was attributed to the effect of high concentration of divalent cation on aggregation of nanoparticles and microorganisms. Furthermore, simultaneous enhanced transport and decreased retention of GONPs in column was observed in the co-presence of microorganisms at low ionic strength. Results revealed that the main mechanism governing increasing GONPs transport in porous media was occupation of reactive surface sites of collectors by microorganisms, which prevented attachment of nanoparticles. The pre-saturation of columns with MS2 and E. coli caused increasing transport of GONPs in the columns, due to the occupation of surface reactive sites. Moreover, conditioning limestone collectors with natural biofilm resulted in the same rates of nanoparticle elution and retention (i.e., in the presence or absence of microorganisms) by straining of GONPs in the inlet end of columns which shows that the biofilm acts as a bio-filter against discharging nanoparticles into the effluents. Finally, from the obtained results, it can be postulated that the presence of microorganisms in a MAR site causes risk of groundwater pollution by toxic nanoparticles.

Hyporheic Exchange Controls Fate of Trace Organic Compounds in an Urban Stream.

First-order half-lives for 26 trace organic compounds (TrOCs) were determined in the hyporheic zone (HZ) and along a 3 km reach of a first-order stream in South Australia during both dry and wet seasons. Two salt tracer experiments were conducted and evaluated using a transient storage model to characterize seasonal differences in stream residence time and transient storage. Lagrangian and time-integrated surface water sampling were conducted to calculate half-lives in the surface water. Half-lives in the HZ were calculated using porewater samples obtained from a modified mini-point sampler and hyporheic residence times measured via active heat-pulse sensing. Half of the investigated TrOCs (e.g., oxazepam, olmesartan, candesartan) were not significantly removed along both the investigated river stretch and the sampled hyporheic flow paths. The remaining TrOCs (e.g., metformin, guanylurea, valsartan) were found to be significantly removed in the HZ and along the river stretch with relative removals in the HZ correlating to reach-scale relative removals. Using the modeled transport parameters, it was estimated that wet season reach-scale removal of TrOCs was predominately caused by removal in the HZ when the intensity of hyporheic exchange was also higher. Factors that increase HZ exchange are thus likely to promote in-stream reactivity of TrOCs.

Model-based classification of CPT data and automated lithostratigraphic mapping for high-resolution characterization of a heterogeneous sedimentary aquifer.

Cone penetration testing (CPT) is one of the most efficient and versatile methods currently available for geotechnical, lithostratigraphic and hydrogeological site characterization. Currently available methods for soil behaviour type classification (SBT) of CPT data however have severe limitations, often restricting their application to a local scale. For parameterization of regional groundwater flow or geotechnical models, and delineation of regional hydro- or lithostratigraphy, regional SBT classification would be very useful. This paper investigates the use of model-based clustering for SBT classification, and the influence of different clustering approaches on the properties and spatial distribution of the obtained soil classes. We additionally propose a methodology for automated lithostratigraphic mapping of regionally occurring sedimentary units using SBT classification. The methodology is applied to a large CPT dataset, covering a groundwater basin of ~60 km2 with predominantly unconsolidated sandy sediments in northern Belgium. Results show that the model-based approach is superior in detecting the true lithological classes when compared to more frequently applied unsupervised classification approaches or literature classification diagrams. We demonstrate that automated mapping of lithostratigraphic units using advanced SBT classification techniques can provide a large gain in efficiency, compared to more time-consuming manual approaches and yields at least equally accurate results.

Contrasting responses of water use efficiency to drought across global terrestrial ecosystems.

Drought is an intermittent disturbance of the water cycle that profoundly affects the terrestrial carbon cycle. However, the response of the coupled water and carbon cycles to drought and the underlying mechanisms remain unclear. Here we provide the first global synthesis of the drought effect on ecosystem water use efficiency (WUE = gross primary production (GPP)/evapotranspiration (ET)). Using two observational WUE datasets (i.e., eddy-covariance measurements at 95 sites (526 site-years) and global gridded diagnostic modelling based on existing observation and a data-adaptive machine learning approach), we find a contrasting response of WUE to drought between arid (WUE increases with drought) and semi-arid/sub-humid ecosystems (WUE decreases with drought), which is attributed to different sensitivities of ecosystem processes to changes in hydro-climatic conditions. WUE variability in arid ecosystems is primarily controlled by physical processes (i.e., evaporation), whereas WUE variability in semi-arid/sub-humid regions is mostly regulated by biological processes (i.e., assimilation). We also find that shifts in hydro-climatic conditions over years would intensify the drought effect on WUE. Our findings suggest that future drought events, when coupled with an increase in climate variability, will bring further threats to semi-arid/sub-humid ecosystems and potentially result in biome reorganization, starting with low-productivity and high water-sensitivity grassland.

Impact of shale gas development on water resources: a case study in northern poland.

Shale gas is currently being explored in Europe as an alternative energy source to conventional oil and gas. There is, however, increasing concern about the potential environmental impacts of shale gas extraction by hydraulic fracturing (fracking). In this study, we focussed on the potential impacts on regional water resources within the Baltic Basin in Poland, both in terms of quantity and quality. The future development of the shale play was modeled for the time period 2015-2030 using the LUISA modeling framework. We formulated two scenarios which took into account the large range in technology and resource requirements, as well as two additional scenarios based on the current legislation and the potential restrictions which could be put in place. According to these scenarios, between 0.03 and 0.86% of the total water withdrawals for all sectors could be attributed to shale gas exploitation within the study area. A screening-level assessment of the potential impact of the chemicals commonly used in fracking was carried out and showed that due to their wide range of physicochemical properties, these chemicals may pose additional pressure on freshwater ecosystems. The legislation put in place also influenced the resulting environmental impacts of shale gas extraction. Especially important are the protection of vulnerable ground and surface water resources and the promotion of more water-efficient technologies.

Dissolved phosphorus transport from soil to surface water in catchments with different land use.

Diffuse phosphorus (P) export from agricultural land to surface waters is a significant environmental problem. It is critical to determine the natural background P losses from diffuse sources, but their identification and quantification is difficult. In this study, three headwater catchments with differing land use (arable, pasture and forest) were monitored for 3 years to quantify exports of dissolved (<0.45 µm) reactive P and total dissolved P. Mean total P exports from the arable catchment ranged between 0.08 and 0.28 kg ha(-1) year(-1). Compared with the reference condition (forest), arable land and pasture exported up to 11-fold more dissolved P. The contribution of dissolved (<0.45 µm) unreactive P was low to negligible in every catchment. Agricultural practices can exert large pressures on surface waters that are controlled by hydrological factors. Adapting policy to cope with these factors is needed for lowering these pressures in the future.

Historical land use change has lowered terrestrial silica mobilization.

Continental export of Si to the coastal zone is closely linked to the ocean carbon sink and to the dynamics of phytoplankton blooms in coastal ecosystems. Presently, however, the impact of human cultivation of the landscape on terrestrial Si fluxes remains unquantified and is not incorporated in models for terrestrial Si mobilization. In this paper, we show that land use is the most important controlling factor of Si mobilization in temperate European watersheds, with sustained cultivation (>250 years) of formerly forested areas leading to a twofold to threefold decrease in baseflow delivery of Si. This is a breakthrough in our understanding of the biogeochemical Si cycle: it shows that human cultivation of the landscape should be recognized as an important controlling factor of terrestrial Si fluxes.

Improving Distributed Runoff Prediction in Urbanized Catchments with Remote Sensing based Estimates of Impervious Surface Cover.

The amount and intensity of runoff on catchment scale are strongly determinedby the presence of impervious land-cover types, which are the predominant cover types inurbanized areas. This paper examines the impact of different methods for estimatingimpervious surface cover on the prediction of peak discharges, as determined by a fullydistributed rainfall-runoff model (WetSpa), for the upper part of the Woluwe Rivercatchment in the southeastern part of Brussels. The study shows that detailed informationon the spatial distribution of impervious surfaces, as obtained from remotely sensed data,produces substantially different estimates of peak discharges than traditional approachesbased on expert judgment of average imperviousness for different types of urban land use.The study also demonstrates that sub-pixel estimation of imperviousness may be a usefulalternative for more expensive high-resolution mapping for rainfall-runoff modelling atcatchment scale.

Remote Sensing and Wetland Ecology: a South African Case Study.

Remote sensing offers a cost efficient means for identifying and monitoring wetlands over a large area and at different moments in time. In this study, we aim at providing ecologically relevant information on characteristics of temporary and permanent isolated open water wetlands, obtained by standard techniques and relatively cheap imagery. The number, surface area, nearest distance, and dynamics of isolated temporary and permanent wetlands were determined for the Western Cape, South Africa. Open water bodies (wetlands) were mapped from seven Landsat images (acquired during 1987 - 2002) using supervised maximum likelihood classification. The number of wetlands fluctuated over time. Most wetlands were detected in the winter of 2000 and 2002, probably related to road constructions. Imagery acquired in summer contained fewer wetlands than in winter. Most wetlands identified from Landsat images were smaller than one hectare. The average distance to the nearest wetland was larger in summer. In comparison to temporary wetlands, fewer, but larger permanent wetlands were detected. In addition, classification of non-vegetated wetlands on an Envisat ASAR radar image (acquired in June 2005) was evaluated. The number of detected small wetlands was lower for radar imagery than optical imagery (acquired in June 2002), probably because of deterioration of the spatial information content due the extensive pre-processing requirements of the radar image. Both optical and radar classifications allow to assess wetland characteristics that potentially influence plant and animal metacommunity structure. Envisat imagery, however, was less suitable than Landsat imagery for the extraction of detailed ecological information, as only large wetlands can be detected. This study has indicated that ecologically relevant data can be generated for the larger wetlands through relatively cheap imagery and standard techniques, despite the relatively low resolution of Landsat and Envisat imagery. For the characterisation of very small wetlands, high spatial resolution optical or radar images are needed. This study exemplifies the benefits of integrating remote sensing and ecology and hence stimulates interdisciplinary research of isolated wetlands.