ORCID Profile
0000-0002-6557-0237
Current Organisation
University of Sydney
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Surfacewater Hydrology | Natural Hazards | Statistics | Global Change Biology | Crop and Pasture Production | Physical Geography and Environmental Geoscience | Plant Biology | Knowledge Representation and Machine Learning | Surfacewater Hydrology | Applied Statistics | Ecosystem Function | Tree Nutrition and Physiology | Plant Physiology | Agro-ecosystem Function and Prediction | Agronomy | Natural Resource Management |
Ecosystem Adaptation to Climate Change | Environmental Management Systems | Field crops | Native forests | Climate variability | Land and water management | Precious (Noble) Metal Ore Exploration | Mining Land and Water Management | Forest and Woodlands Water Management | Global climate change adaptation measures
Publisher: Elsevier BV
Date: 06-2022
Publisher: Elsevier BV
Date: 06-2014
Publisher: Elsevier BV
Date: 09-2021
Publisher: Copernicus GmbH
Date: 06-12-2022
DOI: 10.5194/HESS-26-6073-2022
Abstract: Abstract. 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.
Publisher: American Geophysical Union (AGU)
Date: 12-2014
DOI: 10.1002/2013WR015208
Abstract: Soil sodicity, where the soil cation exchange complex is occupied for a significant fraction by Na + , may lead to vulnerability to soil structure deterioration. With a root zone flow and salt transport model, we modeled the feedback effects of salt concentration ( C ) and exchangeable sodium percentage ( ESP ) on saturated hydraulic conductivity K s ( C , ESP ) for different groundwater depths and climates, using the functional approach of McNeal (1968). We assume that a decrease of K s is practically irreversible at a time scale of decades. Representing climate with a Poisson rainfall process, the feedback hardly affects salt and sodium accumulation compared with the case that feedback is ignored. However, if salinity decreases, the much more buffered ESP stays at elevated values, while K s decreases. This situation may develop if rainfall has a seasonal pattern where drought periods with accumulation of salts in the root zone alternate with wet rainfall periods in which salts are leached. Feedback that affects both drainage/leaching and capillary upward flow from groundwater, or only drainage, leads to opposing effects. If both fluxes are affected by sodicity‐induced degradation, this leads to reduced salinity ( C ) and sodicity ( ESP ), which suggests that the system dynamics and feedback oppose further degradation. Experiences in the field point in the same direction.
Publisher: Elsevier BV
Date: 05-2012
Publisher: Elsevier BV
Date: 12-2010
Publisher: CSIRO Publishing
Date: 2006
DOI: 10.1071/SR05037
Abstract: Palæochannels, or prior streams, are strings of sandier sediments that occur frequently in the irrigated alluvial plains of Northern New South Wales, Australia. These landscape features have been recognised as locations of substantial deep drainage losses, and are therefore target areas for water use efficiency. Electromagnetic induction (EM) measurements were used to identify the width and the depth of the palæochannel sediments in a 2-dimensional transect. Three different inversion techniques, Tikhonov regularisation, the McNeill layered earth model, and an optimal linear combination of EM measurements, were applied to a combination of EM-38 and EM-34 data. Using various kriging techniques, the resulting conductivity profiles were interpolated to soil property data and transformed to saturated hydraulic conductivities using pedotransfer functions. There were distinct differences in the resulting stratigraphies depending on the inversion and interpolation method employed. Trend kriging of the s led soil property data using the Cook and Walker and Tikhonov inversion data as a trend surface gave the most consistent hydraulic conductivity values compared to the s led soil property data. However, differences between inversion and interpolation methods were negated by uncertainties in the pedotransfer functions.
Publisher: Elsevier BV
Date: 09-2016
Publisher: American Geophysical Union (AGU)
Date: 05-2010
DOI: 10.1029/2010WR009373
Publisher: Wiley
Date: 09-09-2020
DOI: 10.1002/HYP.13880
Publisher: American Chemical Society (ACS)
Date: 30-07-2020
Publisher: CSIRO Publishing
Date: 2006
DOI: 10.1071/SR05152
Abstract: Using a range of earlier published results and a recently published dataset, pedotransfer functions (PTFs) were developed to predict some hydraulic properties of Vertosols. A fitting approach using neural networks was employed with good results to predict the soil water characteristic curve. The developed functions are complex due to the large numbers of parameters, but moisture contents are predicted to within 5%. Other PTFs to predict the moisture content at the drained upper limit (DUL) and lower limit (LL), and bulk density in the normal shrinkage curve, were developed using multiple linear regression. The PTFs to predict the soil water characteristic curve, DUL and LL, and the bulk density in the normal shrinkage zone were mainly based on total clay, sand, and silt contents and bulk density, with minor contributions of ECEC and total carbon content. PTFs for unsaturated hydraulic conductivities were also developed using multi-linear regression and were mainly dependent on silt contents and ESP values. The mean error in these predictions was 2.76 mm/h, which is reasonable for predictions at the field and farm scale where inherent soil variability can cause larger variation. The developed PTFs can be used to predict parameters needed in crop modelling tools such as OZCOT to simulate cotton development on Vertosols. Some further ex les of the use of the PTFs for management of irrigation are given.
Publisher: Elsevier BV
Date: 12-2018
DOI: 10.1016/J.WATRES.2018.09.008
Abstract: Biodegradation of glyphosate (GLP) and its metabolite aminomethylphosphonic acid (AMPA) was numerically assessed for a vineyard and a wheat field in the Po Valley, Italy. Calculation of the Hazard Quotient suggested that GLP and AMPA can pose a risk of aquifer contamination in the top 1.5 m depth within 50 years of GLP use. Numerical results relative to soil GLP and AMPA concentrations, and GLP age, half life, and turnover time show that GLP was equivalently removed through hydrolysis and oxidation, but the latter produced AMPA. Biodegradation processes in the root zone removed more than 90% of applied GLP and more than 23% of the produced AMPA between two consecutive applications. Doubling organic carbon availability enhanced GLP and AMPA biodegradation, especially GLP hydrolysis to sarcosine. This work highlights that GLP and AMPA removal is controlled by soil water dynamics that depend on ecohydrological boundary conditions, and by carbon sources availability to biodegraders.
Publisher: Copernicus GmbH
Date: 04-04-2018
Publisher: Copernicus GmbH
Date: 20-04-2022
Abstract: Abstract. The Millennium Drought lasted more than a decade, and is notable for causing persistent shifts in the relationship between rainfall and runoff in many south-east 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 a range of possible process explanations of flow response, and then evaluates these hypotheses against available evidence. The hypotheses consider climatic forcing, vegetation, soil moisture dynamics, groundwater, and anthropogenic influence. The hypotheses are assessed against evidence both temporally (eg. why was the Millennium Drought different to previous droughts?) and spatially (eg. why did rainfall-runoff relationships shift in some catchments but not in 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, reduced recharge associated with vadose zone expansion, and reduced connection between subsurface and surface water processes. Other causes include increased evaporative demand and interception 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 understanding of hydrological shifts, particularly given their relevance to water planning under climate variability and change.
Publisher: Elsevier BV
Date: 02-2011
Publisher: Springer Science and Business Media LLC
Date: 10-10-2016
Publisher: MDPI AG
Date: 15-04-2019
DOI: 10.3390/W11040780
Abstract: Uncertainty about global change requires alternatives to quantify the availability of water resources and their dynamics. A methodology based on different satellite imagery and surface elevation models to estimate surface water volumes would be useful to monitor flood events and reservoir storages. In this study, reservoirs with associated digital terrain models (DTM) and continuously monitored volumes were selected. The inundated extent was based on a supervised classification using surface reflectance in Landsat 5 images. To estimate associated water volumes, the DTMs were s led at the perimeter of inundated areas and an inverse distance weighting interpolation was used to populate the water elevation inside the flooded polygons. The developed methodology (IDW) was compared against different published methodologies to estimate water volumes from digital elevation models, which assume either a flat water surface using the maximum elevation of inundated areas (Max), and a flat water surface using the median elevation of the perimeter of inundated areas (Median), or a tilted surface, where water elevations are based on an iterative focal maximum statistic with increasing window sizes (FwDET), and finally a tilted water surface obtained by replacing the focal maximum statistic from the FwDET methodology with a focal mean statistic (FwDET_mean). Volume estimates depend strongly on both water detection and the terrain model. The Max and the FwDET methodologies are highly affected by the water detection step, and the FwDET_mean methodology leads to lower volume estimates due to the iterative smoothing of elevations, which also tends to be computationally expensive for big areas. The Median and IDW methodologies outperform the rest of the methods, and IDW can be used for both reservoir and flood volume monitoring. Different sources of error can be observed, being systematic errors associated with the DTM acquisition time and the reported volumes, which for ex le fail to consider dynamic sedimentation processes taking place in reservoirs. Resolution effects account for a fraction of errors, being mainly caused by terrain curvature.
Publisher: Elsevier BV
Date: 03-2003
Publisher: Springer Science and Business Media LLC
Date: 27-10-2020
Publisher: Elsevier BV
Date: 05-2020
Publisher: Springer Science and Business Media LLC
Date: 06-2019
Publisher: Scientific Research Publishing, Inc.
Date: 2016
Publisher: Elsevier BV
Date: 06-2012
Publisher: Springer Science and Business Media LLC
Date: 02-05-2015
Publisher: CSIRO Publishing
Date: 2009
DOI: 10.1071/SR08116
Abstract: Understanding the process by which nutrients and solids enter waterways from pastures in the Great Lakes district, New South Wales, Australia, may assist in maintaining water quality to ensure ongoing environmental and economic sustainability of the region. Rainfall simulations, using a 100-year return storm event, were conducted to determine nutrient and suspended solid concentrations in the runoff of 8 pasture sites in 3 of the catchments in the district. On 5 of the 8 sites, considerable concentrations of N or P were mobilised during the simulated rainfall event, but average nutrient concentrations and total loads across all sites were relatively low and similar to other studies of nutrient runoff from pastures. In addition, low runoff coefficients indicated that runoff is probably not the major pathway for nutrient losses from pasture in this area. Overall, rainfall runoff responses at the sites were similar in the 3 catchments. In contrast, the results suggest that, despite generating more runoff, the sites in the Wang Wauk catchment generated less nutrients in runoff than the sites in the Wallamba and Myall catchments. There was no difference in total suspended solids loads for the sites analysed by catchment. Relationships between soil physical and chemical characteristics and total nutrients loads or cumulative runoff were not strong.
Publisher: Elsevier BV
Date: 04-1999
Publisher: Elsevier BV
Date: 09-2002
Publisher: Frontiers Media SA
Date: 03-2022
DOI: 10.3389/FENVS.2022.788248
Abstract: Drought is the most expensive natural hazard and one of the deadliest. While drought propagation through standardised indices has been extensively studied at the regional scale, global scale drought propagation, and particularly quantifying the space and time variability, is still a challenging task. Quantifying the space time variability is crucial to understand how droughts have changed globally in order to cope with their impacts. In particular, better understanding of the propagation of drought through the climate, vegetation and hydrological subsystems can improve decision making and preparedness. This study maps spatial temporal drought propagation through different subsystems at the global scale over the last decades. The standardised precipitation index (SPI) based on the gamma distribution, the standardised precipitation evapotranspiration index (SPEI) based on the log-logistic distribution, the standardised vegetation index (SVI) based on z-scores, and the standardised runoff index (SRI) based on empirical runoff probabilities were quantified. Additionally, drought characteristics, including duration, severity and intensity were estimated. Propagation combined the delay in response in the subsystems using drought characteristics, and trends in time were analysed. All these were calculated at 0.05 to 0.25 arc degree pixels. In general, drought propagates rapidly to the response in runoff and streamflow, and a with longer delay in the vegetation. However, this response varies spatially across the globe and depending on the observation scale, and lifies progressively in duration and severity across large regions from the meteorological to the agricultural/ecological and hydrologic subsystems, while attenuating in intensity. Significant differences exist between major Köppen climate groups in drought characteristics and propagation. Patterns show intensification of drought severity and propagation affecting vegetation and hydrology in regions of southern South America, Australia, and South West Africa.
Publisher: MDPI AG
Date: 12-07-2019
DOI: 10.3390/W11071433
Abstract: Land use change is an important driver of trends in streamflow. However, the effects are often difficult to disentangle from climate effects. The aim of this paper is to demonstrate that trends in streamflow can be identified by analysing residuals of rainfall-runoff simulations using a Generalized Additive Mixed Model. This assumes that the rainfall-runoff model removes the average climate forcing from streamflow. The case study involves the Santa Lucía river (Uruguay), the GR4J rainfall-runoff model, three nested catchments ranging from 690 to 4900 km 2 and 35 years of observations (1981–2016). Two exogenous variables were considered to influence the streamflow. Using satellite data, growth in forest cover was identified, while the growth in water licenses was obtained from the water authority. Depending on the catchment, effects of land use change differ, with the largest catchment most impacted by afforestation, while the middle size catchment was more influenced by the growth in water licenses.
Publisher: Copernicus GmbH
Date: 02-02-2012
Abstract: Abstract. Fire can considerably change hydrological processes, increasing the risk of extreme flooding and erosion events. Although hydrological processes are largely affected by scale, catchment-scale studies on the hydrological impact of fire in Europe are scarce, and nested approaches are rarely used. We performed a catchment-scale experimental fire to improve insight into the drivers of fire impact on hydrology. In north-central Portugal, rainfall, canopy interception, streamflow and soil moisture were monitored in small shrub-covered paired catchments pre- and post-fire. The shrub cover was medium dense to dense (44 to 84%) and pre-fire canopy interception was on average 48.7% of total rainfall. Fire increased streamflow volumes 1.6 times more than predicted, resulting in increased runoff coefficients and changed rainfall-streamflow relationships – although the increase in streamflow per unit rainfall was only significant at the subcatchment-scale. Fire also fastened the response of topsoil moisture to rainfall from 2.7 to 2.1 h (p = 0.058), and caused more rapid drying of topsoils after rain events. Since soil physical changes due to fire were not apparent, we suggest that changes resulting from vegetation removal played an important role in increasing streamflow after fire. Results stress that fire impact on hydrology is largely affected by scale, highlight the hydrological impact of fire on small scales, and emphasize the risk of overestimating fire impact when upscaling plot-scale studies to the catchment-scale. Finally, they increase understanding of the processes contributing to post-fire flooding and erosion events.
Publisher: Elsevier BV
Date: 10-2016
Publisher: American Geophysical Union (AGU)
Date: 04-1999
DOI: 10.1029/98WR02289
Publisher: Informa UK Limited
Date: 04-08-2017
Publisher: Copernicus GmbH
Date: 07-11-2011
DOI: 10.5194/HESS-15-3343-2011
Abstract: Abstract. Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the probability of flow occurring in any of the systems. We then use the same regression framework in combination with a right-skewed distribution, the Box-Cox t distribution, to model the intensity (depth) of the non-zero streamflows. Time, seasonality and climate indices, describing the Pacific and Indian Ocean sea surface temperatures, are tested as covariates in the GAMLSS model to make probabilistic 6 and 12-month forecasts of the occurrence and intensity of streamflow. The output reveals that in the study region the occurrence and variability of flow is driven by sea surface temperatures and therefore forecasts can be made with some skill.
Publisher: CSIRO Publishing
Date: 2016
DOI: 10.1071/CP15053
Abstract: Rainfall is a major driver for dryland wheat yields across Australia. Many authors have covered issues such as rainfall trends in Australia, and much of this information has been reviewed and updated in recent years in relation to the Millennium drought and associated concerns about climate change. However, despite a long history of work relating rainfall to grain yields, there has been no overall historical review of attempts at predictive methods and their reliability. Although many of these attempts have now been abandoned or revised, and science has moved in different directions, a review is useful to identify historical patterns and to recognise recurring themes. This might lead to new science questions and a re-appreciation of older findings. The aim of this study is therefore to review the overall literature on this topic, provide a historical timeline, and summarise the achievements and any remaining research questions. The early use of climatic data in Australia was to categorise existing and likely areas for production, with production, not surprisingly, being the emphasis. The search for a crop or climatic index was possibly initiated in an attempt to understand or simplify the complex relationships between crops and the environment. No single index has proved universally applicable, but some acceptance of early growing-season rains as an indicator seems common. The development of complex climatic models, and the availability of quality data for agricultural systems models, has allowed further quantification of the relationship between crops and climate, especially on a seasonal basis. There is little doubt that the relationship between the climatic southern oscillation phenomenon and seasonal rainfall patterns in Australia is important, but its absolute definition remains elusive. From a producer’s perspective, relationships between rainfall at specific (indicator) periods and seasonal or annual rainfall, as appropriate to specific crops, would be useful simple indicators because many farmers already maintain their own rainfall records.
Publisher: American Geophysical Union (AGU)
Date: 10-2009
DOI: 10.1029/2008WR007245
Publisher: IWA Publishing
Date: 10-2003
Abstract: The water balance allows the calculation of deep drainage from other components of the hydrological cycle. Deep drainage has been linked to outbreaks of dryland and irrigated salinity. Until recently, deep drainage was not considered to be an issue on the alluvial plains of the Northern Murray-Darling Basin. Recent simulation studies and calculations using the water balance suggest that substantial deep drainage occurs under irrigated agriculture. However, these estimates have large uncertainties due to possible errors in measurement, calculation and due to spatial variability. On a catchment scale the relative area under a certain land use as well as the connection to local groundwater and the influence of anomalies such as prior streams needs to be considered. This paper discusses the current state of knowledge on the water balance in the Northern Murray-Darling Basin and highlights the need for a concentrated effort to measure all the components of the water balance in this area, as well as the effect on shallow groundwater quality and levels.
Publisher: Elsevier BV
Date: 12-2013
Publisher: PeerJ
Date: 26-08-2019
DOI: 10.7717/PEERJ.7523
Abstract: Analysis of observational data to pinpoint impact of land cover change on local rainfall is difficult due to multiple environmental factors that cannot be strictly controlled. In this study we use a statistical approach to identify the relationship between removal of tree cover and rainfall with data from best available sources for two large areas in Australia. Gridded rainfall data between 1979 and 2015 was used for the areas, while large scale (exogenous) effects were represented by mean rainfall across a much larger area and climatic indicators, such as Southern Oscillation Index and Indian Ocean Dipole. Both generalised additive modelling and step trend tests were used for the analysis. For a region in south central Queensland, the reported change in tree clearing between 2002–2005 did not result in strong statistically significant precipitation changes. On the other hand, results from a bushfire affected region on the border of New South Wales and Victoria suggest significant changes in the rainfall due to changes in tree cover. This indicates the method works better when an abrupt change in the data can be clearly identified. The results from the step trend test also mainly identified a positive relationship between the tree cover and the rainfall at p 0.1 at the NSW/Victoria region. High rainfall variability and possible regrowth could have impacted the results in the Queensland region.
Publisher: American Geophysical Union (AGU)
Date: 09-2011
DOI: 10.1029/2010WR009790
Publisher: Wiley
Date: 02-11-2015
DOI: 10.1002/WAT2.1121
Abstract: Forecasts can be an important component of water cycle management and farm decision making, particularly where rainfall is uncertain. In Kenya, the use of informal or indigenous forecasting ( IF ) is known to be widespread, but farmers also use more formal seasonal forecasting ( SF ) to make decisions in relation to the water cycle. A review of literature indicates that local knowledge is adaptable and often mixes indigenous knowledge and external information. In most cases, IF focusses on more local features and relates more to practical farm activities. Based on extensive interviews and focus groups of farmers in two study areas in Kenya, a majority of farmers from each area used IF , even though SF was also used. There were few farmer characteristics that explained the difference in the use of IF and SF . However, there were differences between the two study areas in how farmers interpreted SF and whether they used a combination of SF and IF . Furthermore there were differences in the local IF indicators used by farmers to identify the onset of the rainy season. To improve the acceptance of SF and increase its use, the information provided in SF needs to be easily incorporated into farmers’ current working knowledge, which might also include IF . This means that SF tools should be developed using participatory approaches to ensure the engagement of local farmers. WIREs Water 2016, 3:127–140. doi: 10.1002/wat2.1121 This article is categorized under: Human Water Water as Imagined and Represented
Publisher: Wiley
Date: 04-2021
DOI: 10.1002/HYP.14156
Publisher: Springer Science and Business Media LLC
Date: 23-02-2007
Publisher: American Geophysical Union (AGU)
Date: 27-11-2021
DOI: 10.1029/2021WR029799
Abstract: Storage and subsequent release of water is a key function of catchments that moderates the impact of meteorological and climate extremes. Despite the fact that many key hydrological processes depend upon storage, there are relatively few studies that focus on storage itself. Storage is difficult to quantify due to catchment heterogeneity and the paucity of data on key catchment characteristics that largely determine storage, such as soil, hydrogeology, and topography. We adopt a multi‐method approach to estimate the dynamic and extended dynamic storages using hydrometric data in 69 catchments in the Murray‐Darling Basin in south‐eastern Australia. We test relationships between the derived catchment storages and hydrological and physical characteristics that potentially control storage. The study catchments tended to have small dynamic storages relative to the extended dynamic storage proportionally the dynamic storages were all less than 10% of the extended dynamic storage. While storage estimates produced by the different methods and study catchments varied, the order in which they ranked was consistent. Correlations between catchment characteristics and estimates of storage were inconsistent however, the results indicated that greater storage is strongly associated with steeper catchments and smoother hydrographs. This study highlights limitations in the current methodology to derive storage and the quality of widely applied hydrometric data. We reinforce the need to collect data that can validate storage estimates and call for new approaches that can broadly estimate storage at the catchment scale.
Publisher: Elsevier BV
Date: 07-2021
Publisher: Elsevier BV
Date: 03-2019
DOI: 10.1016/J.SCITOTENV.2018.12.179
Abstract: Glyphosate (GLP) is one of the most widely-used herbicides globally and its toxicity to humans and the environment is controversial. GLP is biodegradable, but little is known about the importance of site exposure history and other environmental variables on the rate and pathway of biodegradation. Here, GLP was added to microcosms of soils and sediments with different exposure histories and these were incubated with amendments of glucose, ammonium, and phosphate. GLP concentrations were measured with a newly-developed HPLC method capable of tolerating high concentrations of ammonium and amino acids. GLP biodegradation occurred after a lag-time proportional to the level of GLP pre-exposure in anthropogenically-impacted s les (soils and sediments), while no degradation occurred in s les from a pristine sediment after 180 days of incubation. Exposure history did not influence the rate of GLP degradation, after the lag-time was elapsed. Addition of C, N, and P triggered GLP degradation in pristine sediment and shortened the lag-time before degradation in other s les. In all microcosms, GLP was metabolised into aminomethylphosphonic acid (AMPA), which was highly persistent, and thus appears to be a more problematic pollutant than GLP. Bacterial communities changed along the gradients of anthropogenic impacts, but in some cases, taxonomically very-similar communities showed dramatically different activities with GLP. Our findings reveal important interactions between agriculturally-relevant nutrients and herbicides.
Publisher: Elsevier BV
Date: 06-2023
Publisher: Copernicus GmbH
Date: 04-12-2020
Publisher: Elsevier BV
Date: 08-2020
Publisher: CSIRO Publishing
Date: 2013
DOI: 10.1071/CP13168
Abstract: Regional climactic variability coupled with an increasing demand on water has placed an even greater pressure on managers to understand the complex relationships between surface water and groundwater in the Murray–Darling Basin. Based on limited soil s ling combined with geophysical observations, past research has suggested that relic subsurface drainage features (also known as palæochannels) have a higher risk of deep drainage and lateral flow, particularly where water is impounded or applied as irrigation. The aim of this study was to investigate the hydrological behaviour of an irrigated 25-ha site in North-western New South Wales in more detail to predict deep drainage risk in the presence of palæochannel systems. Several years of direct and indirect observations, including soil s ling and groundwater measures, were collected. Coupling the field data with one- and two-dimensional water balance models revealed a more complex behaviour where a palæochannel functions like a large underground drain. In contrast to other studies, this study suggests that the actual palæochannel does not pose a higher drainage risk, but the combination of the palæochannels with the surroundings soils does have a higher deep drainage risk.
Publisher: Elsevier BV
Date: 02-2018
DOI: 10.1016/J.SCITOTENV.2017.09.315
Abstract: Empirical evidence from Australia shows that fuel reduction burning significantly reduces the incidence and extent of unplanned fires. However, the integration of environmental values into fire management operations is not yet well-defined and requires further research and development. WAVES, a plant growth model that incorporates Soil-Vegetation-Atmosphere Transfer, was used to simulate the hydrological and ecological effects of three fuel management scenarios on a forest ecosystem. WAVES was applied using inputs from a set of forest plots for one year after three potential scenarios: (1) all litter removed, (2) all litter and 50% of the understorey removed, (3) all litter and understorey removed. Modelled outputs were compared with sites modelled with no-fuel reduction treatment (Unburnt). The key change between unburnt and fuel reduced forests was a significant increase in soil moisture after fire. Predictions of the recovery of aboveground carbon as plant biomass were driven by model structure and thus variability in available light and soil moisture at a local scale. Similarly, effects of fuel reduction burning on water processes were mainly due to changes in vegetation interception capacity (i.e. regrowth) and soil evaporation. Predicted effects of fuel reduction burning on total evapotranspiration (ET) - the major component of water balance - were marginal and not significant, even though a considerable proportion of ET had effectively been transferred from understorey to overstorey. In common with many plant growth models, outputs from WAVES are dictated by the assumption that overstorey trees continue to grow irrespective of their age or stage of maturity. Large areas of eucalypt forests and woodlands in SE Australia are well beyond their aggrading phase and are instead over-mature. The ability of these forests to rapidly respond to greater availability of water remains uncertain.
Publisher: Wiley
Date: 20-04-2011
DOI: 10.1002/HYP.8102
Publisher: Elsevier BV
Date: 12-2016
Publisher: Wiley
Date: 19-04-2021
Publisher: American Geophysical Union (AGU)
Date: 08-2008
DOI: 10.1029/2008WR006889
Publisher: Springer International Publishing
Date: 28-12-2015
Publisher: Elsevier BV
Date: 2020
Publisher: MDPI AG
Date: 25-02-2022
DOI: 10.3390/SU14052732
Abstract: To increase water productivity and assess water footprints in irrigated systems, there is a need to develop cheap and readily available estimates of components of water balance at fine spatial scales. Recent developments in satellite remote sensing platforms and modelling capacities have opened opportunities to address this need, such as those being developed in the WaterSENSE project. This paper showed how evapotranspiration, soil moisture, and farm-dam water volumes can be quantified based on the Copernicus data from the Sentinel satellite constellation. This highlights distinct differences between energy balance and crop factor approaches and estimates that can be derived from the point scale to the landscape scale. Differences in the results are related to assumptions in deriving evapotranspiration from remote sensing data. Advances in different parts of the water cycle and opportunities for crop detection and yield forecasting mean that crop water productivity can be quantified at field to landscape scales, but uncertainties are highly dependent on input data availability and reference validation data.
Publisher: Wiley
Date: 15-11-2021
Publisher: CSIRO Publishing
Date: 2003
DOI: 10.1071/SR02154
Abstract: This paper describes the hydraulic, structural and fundamental soil properties for 23 Vertosol horizons from 18 s ling sites in New South Wales and southern Queensland. At each site a combination of infiltration measurements and soil s ling was conducted. S les were collected for determination of the soil water characteristic, shrink–swell relationships, and fundamental soil properties such as particle size distributions, pH, electrical conductivity (EC), exchangeable cations (Ca2+, Mg2+, K+, Na+), extractable P contents, extractable sulfate and Fe contents, and CaCO3 and total C contents. Large cores were s led, impregnated with resin, and sectioned for image analysis. The program SOLICON v2.1 was used to calculate structural form parameters from the images. Measured hydraulic conductivities of the surface soils were large compared with earlier reported research for Vertosols. However, a sharp decrease in hydraulic conductivity occurred with depth in the profiles, which is assumed to be due to increased bulk densities and exchangeable sodium percentages (ESP). The data also indicated a general north–south trend in the structural development of these Vertosols. Surface soils from the northern areas, such as the Gwydir and Namoi valleys, exhibited more porous structural forms, and as a result, greater average hydraulic conductivities. This appears to be due to differences in ESP, clay content and the mineralogical suite of the clay surface s les with smaller ESPs and larger proportions of smectitic clay tended to have the greatest values of hydraulic conductivity. Other fundamental soil properties such as extractable Fe and P contents, and CaCO3 content, were found to have little or no correlation to the hydraulic or structural properties of these Vertosols, while differences in measured shrink-swell and water retention properties were largely a function of soil depth. The database developed has given an overview of the hydraulic properties of Vertosols used for cotton production in south-eastern Australia.
Publisher: MDPI AG
Date: 19-11-2019
DOI: 10.3390/W11112424
Abstract: Many lumped rainfall-runoff models are available but no single model can account for the uniqueness and variability of all catchments. While there has been progress in developing frameworks for optimal model selection, the process currently selects a range of model structures a priori rather than starting from the hydrological data and processes. In addition, studies on differential split s le tests (DSSTs) have focused on objective function definitions and calibration approaches. In this study, seven hydrological signatures and 12 catchment characteristics from 108 catchments around Australia were extracted for two 7-year time periods: (1) wet and (2) dry. The data was modelled using the GR4J, HBV and SIMHYD models using three objective functions to explore the relationship between model performance, catchment features and identified parameters. The hypothesis is that the hydrological signatures and catchment characteristics reflect catchment behaviour, and that certain signatures and characteristics are associated with better calibration performance. The results show that a greater percentage of catchments achieved a better calibration performance in the wet period compared to the dry period and that better calibration performance is associated with catchments that have greater cumulative flow and a steeper flow duration curve. The findings are consistent across the three models and three objective functions, suggesting that there is a bias in the studied models to wetter catchments. This study echoes the need to develop a conceptual model that can accommodate a wide variety of catchments and climates and provides a foundation to optimise and improve model selection in catchments based on their unique characteristics.
Publisher: Wiley
Date: 21-09-2015
DOI: 10.1002/WAT2.1118
Abstract: Farmer perceptions clearly influence the adoption of technology and adaptation to climate change, but may not be consistent with or captured by scientific measurements. There has been a significant research on how perceptions influence water resource management and adaptation to climate, but conclusions are unclear or contradictory. This research aimed to clarify what shapes perceptions and how this understanding can refine meteorological data collection and to make more relevant and useful tools for farmers to adapt to changes in the water cycle. A survey of 244 small‐scale maize farmers was conducted using a questionnaire and semi‐structured interviews in two districts in southern and western Kenya which differed in climate type and farming systems. Farmer perceptions of and adaptation to climate uncertainty were investigated and compared with meteorological data. Most farmers perceived changes in the patterns of rainfall and dry spells, including later onset of rains than in the past. They have already adjusted their management based on these perceptions, including later planting times. Despite this, analysis of meteorological data indicated no major trends in rainfall or dry spell patterns in the two regions. This research confirms that the perception that the water cycle is changing is based on a combination of climatic, economic, or social observations, and farmers are already changing their management to adapt to the perceived changes in climate. The article explores the reasons why these perceptions were inconsistent with the available meteorological data and suggests that research may improve the usefulness of meteorological data to farmers. WIREs Water 2016, 3:105–125. doi: 10.1002/wat2.1118 This article is categorized under: Human Water Water as Imagined and Represented
Publisher: Wiley
Date: 15-12-2020
DOI: 10.1002/HYP.13999
Publisher: Informa UK Limited
Date: 26-04-2021
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 02-2020
Publisher: Wiley
Date: 22-06-2012
DOI: 10.1002/ECO.1288
Publisher: Elsevier BV
Date: 11-2014
Publisher: Wiley
Date: 06-2017
DOI: 10.1002/HYP.11219
Publisher: Elsevier BV
Date: 06-2019
Publisher: Wiley
Date: 07-2021
DOI: 10.1002/HYP.14291
Abstract: Black Box ( Eucalyptus largiflorens F. Muell.), is a keystone tree species of lowland semi‐arid floodplain ecosystems in south‐eastern Australia. E. largiflorens woodlands are of high conservation value and threatened by climate change‐induced drought and irrigation water ersions due to their location on upper floodplain areas where flood frequency has declined. Water requirements of E. largiflorens have not been well quantified using empirical data. Accordingly, knowledge gaps exist in relation to volumes of environmental water required to maintain and improve ecological condition for disconnected floodplain woodlands. To further assist conservation and water resource management, we tested the use of drip irrigation to provide a variety of water regimes to experimental plots in order to monitor tree responses. Water was provided via irrigation delivery across four regimes representing known volumes of water, referred to as an environmental water provision, applied over a 22‐week period for two Austral summers. Benefits to trees were identified by measuring transpiration and plant water status using sap flow sensors and a Scholander pressure chamber, respectively. Results indicate that volumes of 0.3, 0.4, 0.7 and 0.8 ML increased transpiration and improved plant water status in comparison to a control, with delivery recommended to commence early autumn. Greater volumes (1.4 ML), substantially increased transpiration and improved water status, especially when delivered at a rate of ~25 mm week −1 compared to a monthly 'burst' which broadly represented natural, sporadic summer rainfall in the region. For an environmental watering provision of 25 mm week −1 , ~178 ha of E. largiflorens woodland can be watered with a 1 GL environmental water allocation. The study methods presented are relevant worldwide and our results further the collective understanding of the benefits environmental water provides to E. largiflorens .
Publisher: Elsevier BV
Date: 04-2023
Publisher: Wageningen University and Research
Date: 15-12-2020
DOI: 10.18174/SESMO.2020A17892
Abstract: The inherent complexity of numerical models and the ersity of stakeholders in integrated water resources management (IWRM) create challenges in achieving credibility, salience and legitimacy to develop trust in model-based scenarios. In Uruguay, there has been significant debate on increasing agricultural production while managing agriculture’s environmental impacts (e.g., on water quality and environmental flows). This paper reports on the evolution of a stakeholder process in a case study with a multi-institutional participatory modelling group, supported by researchers. This specific participatory modelling (PM) project is unique in that the active stakeholders are the actual hydrological modellers, and the role of “experts” is mainly in facilitation and capacity building. The results highlight the different bottlenecks and the factors that enabled effective collaboration in this PM project. The main bottlenecks were related to: different views on representation of the watershed, the quality and usability of different input data, the public information for the technical implementation of the model, and the priority of output scenarios. The factors that enhanced collaboration were: a focus on a single basin problem, strong support from upper management, and support from experts in coordination and capacity building. The detailed documentation provided with this project can inspire similar approaches in the future.
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 12-2018
DOI: 10.1016/J.SCITOTENV.2018.07.052
Abstract: An improved understanding of the drivers controlling infiltration patterns in semiarid regions is of key importance, as they have important implications for ecosystem productivity, retention of resources and the restoration of degraded areas. The infiltration depth variability (ΔInf) in vegetation patches at the hillslope scale can be driven by different factors along the hillslope. Here we investigate the effects of vegetation and terrain attributes under hypothesis that these attributes exert a major control in ΔInf within the patches. We characterise the ΔInf within vegetation patches at a semiarid hillslope located at the Jornada Experimental Range at dry antecedent conditions preceding two winter frontal rainfall events. We measured these events that are typical during winter conditions, and are characterised by low intensity (0.67 and 4.48 mm h
Publisher: Copernicus GmbH
Date: 22-09-2022
DOI: 10.5194/IAHS2022-2
Abstract: & & Building Rating Curves is complex since it depends on the availability of direct instantaneous stage-velocity/area measurements (gaugings) and variable hydraulic conditions. This work proposes a methodology to estimate synthetic (non-gauged) daily rating curves. A regional rainfall-runoff model (GR4J) is coupled with an instantaneous/stage - daily/discharge relationship based on third-order Chebyshev polynomials. Bayesian inference with Delayed Rejection Adaptive Metropolis algorithm is used to optimize the parameters and to quantify the uncertainty in the joint daily rating curve and the regional rainfall-runoff model. The likelihood function based on the model residuals is assumed to be gaussian, homoscedastic, and independent. As a study area, a region with 4 gauging sites located in New South Wales, Australia was chosen, and periods with no changes in the stage-discharge relationship were selected. Then, the method is implemented 4 times across the gauging sites, where 3 sites are supposed to be gauged and 1 site is supposed to be partially gauged (with only instantaneous water level). The proposed approach can increase the spatial representation of hydrological data when used in combination with satellite river altimetry. Another extension would be to identify the error if fewer gaugings are available.& Future works could address how to incorporate heteroscedastic, autocorrelation, and zero-inflation of model residuals as well as how to account for the variation in the range of model residuals across the gauging sites.& & & & & & & & & & img src=& quot data:image ng base64, 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Fa6jidzcXND/fz5w+fjUqUtZmzVpjzK6bmNFVLW9oKBAoV0SiURhPW2OXUXnAVD1N/Dy8ZQ/lyUSidJzVJMYy9alzjqq/qYYexVVKVldvHgRUVFR+PPPPxUuP+Tl5WHOnDnYvn07oqOjMX78eBw/flxYnpOTg//973/48ccfsXXrVkyePBnr1q1DZmYmPvnkE/z3339wdHSEmZkZ/v33X2E7qVQKV1dX/Pjjj0hMTMS2bdvg7OyM3NxcAEBAQAD69+8PMzMzREREYPPmzTh27Bjmz5+PuXPnKrThxo0bWLt2LRITE3Hu3DmMHDkS8fHxWvXHhQsX4ODgAAsLC4SGhmLdunVwcHDAwYMH1apLWZvVbc+NGzewcOFCFBYWYv369Vi4cCHCw8N13kZt2h4YGIgBAwagTp06+Oeff4S2Dh06FCYmJjh69KhGbQUqPw8uXryIZcuWAQCWLl2KhQsXCv8AYM2aNVi4cCHu3LlTYZsqimfBggWYM2cOiouLsWXLFnh4eGDFihUYN26ckKjVibGsEydOYPbs2XB3d8eePXtw7NgxhXUq+5tS5t69e3BwcMD169dVrseY3lPnxtb69esJAK1bt47++OMP+v777+njjz+mGTNm0L1795RuM27cOFqyZInw+sWLF2RjY0MJCQlERDR37lyaPn26sHzFihU0bNgwYV0iIqlUSmKxWO6GsbOzM61atUqurj179tDQoUOF10VFRSQSiWjp0qXCjfWcnBwSiUR08+ZNuW0dHBxo8eLFwuuNGzdSnz59FNpjamqq1o3rlJQUAkAbNmwQ4nVzc1O7LmVt1qQ9FhYWdPnyZZ21Ud12V9b2goICAkB///233Da2trbCOpq0VZ3zICMjgwBQVFSU3HoAKCQkRK02qYrH2dmZ8vPzhXUtLS3J29tboxiJiHbs2EEffPABFRUVCWXe3t4KAywq+5siUjxe165dIysrK/L09FSrvYzpK42+WU2ZMgWzZ8/GqlWrMGHCBPj5+SE5OVlhvf/++w8nTpzAmDFjhDIrKyv06NEDJ06cAABcuXIFb731lrC8ffv2uHLlCohIGBRgYGAAIyMjYZ2YmBjs2LEDEydOlKvv888/h4+PDy5evAgAMDQ0hFgsRosWLYQb6+bm5mjYsCGio6Plth03bhzatWsnvO7evTuCgoJQXFysSdcISr9htm7dGgCwdetWTJs2Te26yrdZ0/Yoo+s2VkRV201MTJQOGCj/jVydtqp7HuiCqnhsbGxgamoqrNu6dWvExsZqFGNmZia+++47zJ07F4aG/3cL+YMPPpDbTp2/KWV69+6N9PR0jBo1SsseYEw/aDXAQiQS4bPPPkNgYCCmTJmCe/fuwdLSUlheegkrJCQE9+7dE8rt7Oxgbm4OAHjnnXfkEt3Tp0/RuXNnlfcXgoKCIJPJ0KRJE7lyCwsLWFtb49q1axgyZIhQ3qxZM7n1xGKxwhv0N998g4SEBGzbtg0ZGRnIzMwEEaGwsFDuzUNTrVq1Uiiral3qtEcZXbVx3759ePLkiVzZ4sWLFZKrsrYDmt07UtVWTc8DXVAWjy5iDAkJQW5uLjp27Ci3Xvm+UudvqiI86IK9Cqo0GvDtt99GcnIyrl69ihEjRgjlpW9eEyZMkBuRVvopGwAWLVoEJycnHDt2DObm5vD29sa+fftU1ieRSABA7r5AWQUFBXKvSz8Jq7JmzRqcOXMGBw8ehL29PYKDg7Fx48ZKt6tM2U/cuqpLnfYoo6s2Pn/+HE+fPpUrU3YslLW9IhUdS1Vt1fQ80AVl8egixtJBF5UdW3X+phh7lVVpgEXp5bqyn/QAwMHBAUDJEzDKS0hIAABcvnwZERERePvtt9G0aVNcvHgRnTp1Ullf6X5L91EqIyMD6enpwnJ1RUZGYvXq1di3bx/s7e0ByI/G8vLy0mh/+lJXddX73XffYevWrXL/jI2N1d6+/Lc4IkJ6erra25fS9XlQHdSNsVu3bsLTRsoqP9JPnb8pxl5laiWr0k9/5YfetmjRAgCEEVXp6em4cuUK2rdvj1mzZmHXrl1y6/v7+wvrFhcXY/369SVBGBjg4cOHSocoy2QyYVhw586dMX36dLi5ucmt4+bmhl69emH06NFy25X/g5dKpXJlpfcXyv5wNjo6GiKRCMXFxXIj5pTtT5nSNpTvK03rKj8UWp32lJaVrbuqbVS33aV1A4ptL9WiRQukpKQIrwMDA2FkZITs7OxK6yzbVnXPg9J4yu6r9P/qDCNXN56qxNiwYUMsXLgQBw4ckFuv9J5Wad+o8zelLNZbt26hU6dO8Pf3V7u9jOkjsaurq2tFC0NDQ7Fp0yZ4enpCIpEgOjoaYWFhcHR0BFByHT8hIQF///03PvvsM3h4eGDgwIGwsLDAkCFDEB4ejsOHD4OIEBAQgBcvXmDChAkASu5rTJkyBX/99Rf27t2LX375Bb///jtevHiBQYMGITg4GKtXr0Z0dDTi4+NhY2ODNm3a4KOPPsLVq1fh7e2N/Px8HDlyBHFxcXBzc4OZmRmCgoLg4uKCuLg4JCYmoqioCGKxGK6urggPD0dsbCyysrLQp08ftGjRAvHx8fjrr79Qr149hIWFoWPHjpBKpThz5gy6deuGvLw8uLi4ICYmBvfv34dMJkOXLl2U9pePjw/Wrl2LpKQkREVFITo6Gh9++CEAqF1X+TY/e/ZMrfYYGxvDxcUFUVFRiI2Nxe3btzFo0CC0atVKqzYWFhaq3e7K2l6qWbNm2LdvHxo2bIjw8HAUFxfjxo0bCAoKQkFBAUQikdrHrrLzoGw8CQkJMDY2Fvry/v37iI6Oxu3btzF48OAK21TZufTw4UNkZWWhYcOGcHFxwbVr1xATE4OUlBR8+OGHlcZY6sMPP8Tt27fh6ekJsViMK1euIC8vD15eXrh79y5MTEzQpUsXlX9TwcHBSo9XUlIS3NzcMGzYMLkBTYy9dHQxpDAsLIwOHjxIsbGxCsuKioooOjqaJBKJUJaUlER9+vShpKQkoUwqlVJMTAz17NmT/vzzz0rrlEgkFBUVJTd0WFsSiYTi4uJIJpMJZQUFBVXeb23XpQ/1lldcXEyxsbGUl5dHREQxMTGUnJxMhYWFWu1Pl+dBdVE3RolEQjExMSSVSkkqlVJkZCSlpKTIDWknUv43xdirTkRUwR3garR3715ERkZi06ZNCsu2b9+OxMREbNiwoabDYowxpqdqZT6r4cOH4+bNmwgLC5MrT0xMxIkTJ3iEE2OMMTm18s2KMcYY0wTPFMwYY0zvcbJijDGm9zhZMcYY03ucrBhjjOk9TlaMMcb0Hicrxhhjeo+TFWOMMb3HyYoxxpje42TFGGNM73GyekUdOHCgwon/GFPF3d1d7WlhGKspVZop+FVVXFyMU6dO4fz58zA1NYW5uTmMjIzg7OyMhg0b4vvvv8fatWuF9Z8+fYrdu3crJAdDQ0M0bdoUffv2RcuWLVXWGRoainfffVflOh4eHkhISICRkRFEIhEkEgnef/999OvXT269H374AT169Kh0OvOLFy/C0dFR6xmI2aupa9eu+Pbbb5U+aJqxWlObj3zXR0FBQdSpUydavHgxpaenC+VZWVk0Y8YMGjt2LM2YMUNuG5lMRs+fP6fRo0eTtbU1JSUlUVpaGt25c4c8PT3J3t6evvzyS7npOcr666+/6L333qs0try8PEpNTaWJEyeSiYkJ3b17V2GaiCtXrtDSpUvVauvPP/+s1nrs9bNjxw46fPhwbYfBmICTVRlHjx4lKysr8vDwULr8/v37ZGBgQAcPHlS6vGPHjjR27FiF8nPnzhEAOnXqlMKyjIwM6tChg1rJqlTfvn1p0KBBCuVSqZR69OhBaWlpau1n/fr1atfJXi+FhYXUrVs3ysnJqe1QGCMiIr7+8//5+/tjypQp2LhxIz7//HOl67Ro0QJNmzZVuOwGAM+ePcPdu3fRv39/hWWll9mSkpIUlu3cuRMjRoxQO878/HwEBwcrrScoKAgdOnTAG2+8Uel+YmJi0KZNG7XrZa8XY2NjDB8+HEePHq3tUBgDUIUBFkQEiUQi9 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 Are/PNN+nQoUNERBQeHk4AKDg4WG6dYcOG0c8//0xE/5esyieMO3fuKJSPHj1a7qZwVFQUnT59moiILly4QI0aNaKTJ08Ko5wiIyMpIyND7XjVjZmIaPDgwTRr1izhdXx8PO3fv19ZNykobXNISIhcua+vr1B3dHQ0GRgY0L179+TWyc7OJkNDQ/r777+FsvLJikh1X5VVWZ9oEkdF+3J1dZUr69q1K/32228KsZRvx6+//kr79u0TXvv7+5NIJJJ7wy+/nTrngTKPHj2i+vXrK5Rr0v7S41q+nzMyMsjc3Jw8PDwU9lE2WWny96LsWKrr/PnzZGtrS//880+F63To0EEhDmWJnLGq0OgyoL29PQoKCvDixQuV68XHxyv9fUbZywsAIBaLUVxcDADCJZ2QkBAcOHBA+GdnZydcPy9V/kZz27ZtAQDXrl0TyubOnYujR48KsXp6emLkyJEAgMGDB2PIkCEYO3Ys6tevj/fffx8PHz5EvXr11I5Xk5jnzJmDI0eOICcnBwBw/PhxjB8/XrHjNNC1a1cAJZdEg4KCIJPJ0KRJE7l1LCwsYG1tLdcvyqjqq/JU9YmmcSjbV2V9XpFvvvkG/fr1w7Zt27B27VqcO3cORKTyPo2650F5mZmZMDMzUyjX5jiUv1weEhKC3NxchUFK5c95Tf5elF2SV9fQoUPRtWtXjB8/HhkZGUrXqVu3rsKyV2EgD9MvhpqsPHXqVFy8eBFXrlxROcjizJkzcHZ2Vig3MKg4NxoZGQEAJkyYAGtra6F82rRplcZV+odR9rq5o6MjGjduDDc3N8yePRsmJiYwNCxprkwmw759+7Bs2TL4+/vj/PnzGDZsGK5evYrevXurFa8mMY8cORKWlpY4cuQInJycUFxcrPTNThOlsRUXF0MikQBAhU9RqGxQhqq+qqheZTSNQ9m+KuvziqxZswZnzpzBwYMHYW9vj+DgYGzcuFHlNuqeB+XVr19f+OBRljbHwdTUVO51aXLV1bmnrA5Vdu3ahe7du6Nbt25CWceOHXHp0iUEBgZixIgRCttkZ2fX6KhI9nrS6J1h4sSJGDJkCLZs2VLhOkSE7Oxsjf5AgJIbtQBw+/ZthWUJCQkKdZQVFxcHAHJvMCKRCHPmzMHOnTtx9OhRueR68OBB3L59G23atMHMmTNx+vRpLFu2DF5eXtUSs6GhIWbOnIldu3bh7NmzGD16tEb1AIptLq2zd+/eQhzl+ykjIwPp6enC8oqo6itNVDUObUVGRmL16tXYt28f7O3tAciPoqvouGp7Htja2iInJ0dhNKQu2t+tWzeIxWLcv39frrz8SD9N/l7UFRsbizlz5sDFxUWuvDQxl02KZWVkZMDOzk6rOhlTl8YfY/fs2YPU1FSsWLFC6SfIzZs3Y8KECQrlMplM4Q9OKpUKZe3bt8esWbOwa9cuuXX8/f0VRsxFRETIvd67dy/Gjh2r8GnYyckJDx8+RFBQEBo3biyUE5FCPW3atJG7BFVZvJrGPHPmTERERMDLywudOnWCpsLDw+Veb9iwQWhz586dMX36dLi5ucmt4+bmhl69esklR2XtAiruq7Iq65OqxlG+fysqK92+9Jt0bGwsAMDKykpYHh0dDZFIhOLiYrlRgWXrVec8UEYsFqNly5YKj23SpP2lia78Zcr/x96dx8d0/f8Df2UliyUhEkWCxr5VfQjJJ4KStqqtLvpVGhVVWkVRFLFEFxJtVYuKUsT+KZWKWIJIIrKJJEiILJqNkEgy2SYzySzv3x8euT9jZpI7k5nM0PN8PDwe7rnn3vOemzPznnvvuWecnJywePFiBAcHK5SHh4cDeHwWA/Dre+raUMfFxQWDBg3Cxo0buTIiwtWrV9G/f38MHz5caRuBQACZTIYXXniBK7t58yYGDhyI6OhoXu0yDB9m/urGpKrRrl07fPLJJzh16hTWrl0LKysr1NXVIS4uDrt378bkyZO5b7fA4+v4a9euRU5ODvLy8iCRSGBmZgZ/f3+kpqYiOzsbVVVV8PDwwKuvvorU1FQcOnQIRISYmBgIBAIu+dXV1eH27dvw8PBAREQEBAIBgoKCIJPJsG3bNu7SSAMrKyvk5ORg+vTpCtftb968ibS0NDx69Ai1tbWIjY1Famoqli1bhsTERN7xAmgy5iePW2pqKt566y2F49OUuro6BAQEYPjw4UhPT0dlZSUCAgLQqVMnhdf82muv4fLlyzh9+jREIhEOHz6MnJwc7Nu3D9bW1tzrysrKQm5uLuRyOV566aUmj5Wmf8Om4mhqX4WFhaiqqoKTkxPWrl2L2NhYZGVlobi4GOPGjUNiYiLWrVuHzMxM3L17Fx07dsSECRNw9+5dhIaGol27dkhJScGAAQMgk8kQEhKCl19+GbW1tUqv38TERG0/MDMza/Tvkp6eDlNTU+7eYYOmXj8AXLhwAd999x0KCgpw584dZGZmYty4cdw+xo0bh7S0NJw8eRJmZmaIiIhAbW0twsLCcOvWLbRq1QovvfRSo32vqTZUMTMzw6BBg3D06FHI5XLIZDIEBgYiPz8fx44dQ6dOnZS2iYmJgVQqxdtvv82VFRQUYN++fZg4cSJcXV0bbZNheGvO6IySkhIKCQmhgwcPUnp6OjcMubkkEgllZmZSfX292jo1NTWUkZHRaB0iom+//VZpZJJQKCS5XE5isZjS09OpvLy8xWLW1JOjAfm85vr6erpz547C8G++VB0rbTUnjua0mZOTo/AaxGKx2vrN6QcxMTE0adKkRmNp7uuvr6+nrKwskslkJJPJ6Pbt21RcXKw0wpFP39OEWCymiIgI2r9/PyUmJpJUKlVbd968eRrN0cgw2jIher5+2+DGjRsoLCzEpEmTUFhYiDNnzmDu3LmGDktrlZWVaN++Pa5du4Zhw4bpdN/P27FqaV5eXjh48CC6detm6FAMoqqqChMmTEBsbKzaATkMoyvP3e9ZHT9+HFu3bgUAHDlyBLNmzTJwRNqTy+UoKCgA8PjSSlNTPmnqeTpWhvDrr79izZo1hg7DYDZu3IgNGzawRMW0iOfuzKq0tBRhYWGorKzEW2+9pXbC3WdBREQEIiIiYGFhAalUikGDBmHq1Kk62//zdKwMJTg4GDKZ7F+X6M+ePYv09HQsW7bM0KEw/xLPXbJimJYWHh4Ob2/vf9WDsBcuXMCECRMMHQbzL8KSFcMwDGP0nrt7VgzDMMzzhyUrhmEYxuixZMUwDMMYPZasGIZhGKPHkhXDMAxj9FiyYhiGYYweS1YMwzCM0WPJimEYhjF6LFkxDMMwRo8lK4ZhGMbosWTFMM+QXbt2cb+QzDC68iz0KzY3IMM8I/z8/BAZGQlnZ2ccPnwYpqbsuybTfM9KvzLOqBiGUbB161Z07doVcXFx+Oijj7BixQpDh8Q8B56lfsXOrBjGyAmFQmRkZOA///kPV5abmwszMzM4OzsbMDLmWfas9atn4swqODgYus6pBw4cgFwu1+k+GeOij36jD03FaWNjo/CBAgA9evTg9YHSWD9n7wHtsH5lmH6lVbKSyWRYsWIFZsyYgZ9//lnXMSn49ttv4eTkpPMfths6dCiWLl2q030yxkNf/UbXVMUZExODzz//HB988AEKCgqatf/G+jl7D2iO9avHDNGvtEpWZmZmWLVqFVJTU1FfX6/rmDiXLl1CbW0tXn31VZ3ve+DAgejVqxcOHz6s830zhqXPfqNL6uJ0d3fH2LFjERoaik6dOjWrjcb6OXsPaIb1q//PIP2KtFRXV0dWVlYUHx+v7S4aJZPJaMSIEVRaWqqX/RM9fg0vv/wy1dTU6K0NY5Cfn0/nz583dBgtoiX6jS40FeemTZvI09NTJ2011s+b8x5g/cr4PA/9Sh2t71klJCTA1NRU6ZqnrsTFxaF///7o0KGDXvYPAJaWlnjjjTdw9OhRvbVhDHJzc3H16lVDh9EiWqLf6EJTcUZGRsLLy0snbTXWz5vzHmD9yvg8D/1KHa2TVWRkJDw8PGBubq62jkgkanI/dXV1KstDQkKaPN0mIoXLkKTFTc+xY8fi0KFDGm+nC3K5XOFBvPr6eshkMoPEoo4+YhSLxY2u59Nv 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 lXv5HL5dSrVy+Fb6alpaU0duxYpTNYVf1GIBCQlZUV5efnE9Hjm/rjx48nLy8vIiL69ttvjSJOIiJvb2/y8/NTKBswYADt27eP6urqaP369Trv59q+B7Q5s9K0/xM9/sx5+jK/Mfy9+PSrpmINDAw0mn5FpPlnqD76lTpm/v7+ 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quot alt=& quot & quot & & & & ul& & li& & em& u& /em& : gauged site& /li& & li& & em& v:& /em& partially gauged site& /li& & li& & em& q& /em& : streamflow (mm/day)& /li& & li& & em& h& /em& : water level (m)& /li& & li& & em& h^& /em& : Transformed & em& h& /em& & /li& & li& & #216 : climatological forcing (mm/day, P & PET)& /li& & li& & #949 : model residuals& /li& & li& x& sub& & /sub& ...x& sub& & /sub& : GR4J parameters& /li& & li& x& sub& & /sub& ...x& sub& & /sub& :Chebyshev parameters& /li& & li& & #963 : variance of residuals& /li& & /ul& & & & & & & & Gauging sites (Figure 1) are located in Lachlan River at Reids Flat & (3742 km& sup& & /sup& ), Lachlan River at Narrawa & (2256 km& sup& & /sup& ), Abercrombie River at Abercrombie (2636 km& sup& & /sup& ), and Abercrombie River at Hadley & (1635 km& sup& & /sup& ).& & & & & img src=& quot data:image ng base64, 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 1q1bOxsniAQoGISoqKiIpluBwBMySQqGTe3evVtBQeHBgwfm5uZQ1IEW4VBfvHgRWR8IDw+HWgiUiyBrU1PTk6dOQawwcuRIERERdI2fdKFgyHn27NmwYcNAwWBwqHLBiQ1Ch4oX0ioNvzJy 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 Sy9HiW2XaBbZ/ 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 qbt68ec2aNQcPHvzjDCBDmR4q2N3adAwOp6x9veZP53xmpB/Pwmkz1m6MSh8qz8JjCm5DQECAsrJyaip53agb1DU1b/tSeD6yvLNHMYziK08Hlky0yvqaj68j9PfeERAnqqiosLGx6evrU/HR7X8CfJdDhw4JCQndvn3bwcHh8+fPdnZ2nz590tLSAim/f/8eouDeFL1DgR4qODXcn2fB1AnzV3mGdTUjHPBa/xLNMJzqmVuVnc/bNsjAFExOZmamvLy8rq5uj3WTX0tYYZvzJecPlff9fiVsH3LWfMzd4F6w/XtxeFH/tRucG6 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 0yeIgpOSkn71GTYxMWFiYuLj4zt37tzoWHhQBUNhq ycHB4e3tjWT9f9DZ2Xn8+HFpaWl9PO2/PqEPquCRB1XwH9LR0XHz5k2oZYuJicnIyEA4DDfoRHzJY25ubmtrO5wWXsL4wK1btw6/+Rse/uLiYjMzMzY2Niix7t27N5xG5z9nUAVDrVxVVXUTnr83o834BC47XH9SUlIjIyOowCG5wwZV8MiDKnhEAMVA/AhVvJMnT3JxcUGQ9fjx49TU1IlS1YXgffv27efPnyfMlvBT3rx5IysrO/xZYBITEyH4Wr58uaur628EX7/NoArOz8+fPn06Bg/UXZDc/xugBBISEvL/rfndUQWPPKiCR5ywsDAHBwdxcfFVq1ZZWFj8RqwxanR3d4NM3d3dra2t4YAlJSVLB1udbCB5eXlKSko/HcTRC5hXXV199C/FoAqGu33//v3gX3Jy8hHpqjWxgCJQTU0tMDAQSf8KqIJHHlTBf4mSkpJDhw6BdyBARrLGH7m5uRCciomJOTk5WVlZ2dnZDbMJBaJmc3NzR0dHJP1D 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gODNUdHR/MDB35jPB6UCuD0EXk/FhcXBwoOCAh4/PgxPJn9XrJDmGxoaDj8xTVGnJ8qGK481Dzg4JH0/weBgYFQNRnOMJx+oAoeeVAFj0PgR4HoDCr47u7u9+7dA4PA0zJwRG98fLy2tvZvNCY8f/5cXV09PT0dSf8BEN5COSEmJgZFhbCwcGxsLLIBDzyxGzZsGJNpKgn8VMGEd5KwG5L+PwCqLBYWFtbW1r/RXRJV8MiDKnjcAhHxjx+S8vJyBQWFY8eOIelhExMTA1H2b/RFG0g3ftLOsrIyCN7Btk+fPkU24IHocunSpV++fEHSo85PFQwFm4mJyblz5351vouJC9xXioqKz549Q9K/AqrgkQdV8IQmJCRk7dq17969+yWD3PPxkZOTG1kzOjo6QmBFPGtEfX39zp079+/fP4Z2+6mCgaCgIA0NjT 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& quot alt=& quot & quot & & & & & & & & & & The best fit of the prediction is obtained in the central limb of the rating curves (Figure 2).& & & & & & & & & & img src=& quot data:image ng base64, 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 cRqSk5PxpmpsDaAncsg0VHFp+mZhX+XOmKAeb1tkr0xyDQwNbW1sGIhS09IOHTzImEzTp6GLNJQJVWU6FhAQQPfg8Ji2Y6ZQGTyOSEOd4eawjSIoOgljFMviby2gbHQSOg8FUKM0MOihAmqgxtB/6L10WhGkhuhOCLp4fANP9Oabbx4+fJjeRXOnIkNCQvbu3SsSC/BBOB3dSyhaMMJsKMRUF87SmDFjyJY+9scff+CVECCsrrq6ElA0ps+YViF/gF+jm2n9skBveWi19D0sJP4aOaCO1BUaxKwc3VTDOlDFpEcXxo4dK2Lo///5z3+QeJaZJbz77rscDsM/dU2NIBO0V+0NJEzJMeMVfzRDshEF3KgIoiZMXBB0Cok 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 2SkpbOCkGE9RrOYpNsGlTwxVvNnDUJkzJOP+WXmae0apqYyMjMTEREoiVgsovIODQyM+HFsfgi7vQ5dIJNWDglhbW4sb5hBiIyMjdNzW1pb4qn9aZBPkm201bsRYbIWSkkM5NS+lqMgoJUWJKn09hsBDMR6qWPY0NMlITk7PycnTvEPRTzF5RLGtRM2hWNm+3zg6Vlw9Bz070kTqjW/WSEGXSCTVg/bhKH18fFxdXZ2cnPjr6emJva3JjSIWFhYeHh5+fn4tNLi5uVX6a6ShYfGNGSYoRZuV7N9zMpPS0pia2ytGNophnFIUrxQVl77qvBIiswyxvRpBp+TsruIDugwwjfujaH0gBV0ikVSPxs4a4Mfx146OjnZ2dljvitdM9EIaUiKgbMLfKrYqMTIq8vFRQtxFMFLJ/1HJ/ErJTNX8Curm6mro7JCkFCDorympu5XcUjOuF3+bYisrdixCzAwoMyUXww9/WeYQGvEX0XpCCrpEIqkRpYpuYIAiI+v8reh5q4ANkVEQmaixFTEwyG3ftmDqOKWnd7ij8r359d+U7EtKvmJqypwAv51bWJimKAVKUYGduWGpfImsyumYYcmIfoXengZFRUYZGaaRkWaxsTaGhkws3N3dmR/wl2UmHDd1CM0C+aNoc0L+KNoU+Hv+KFrHaL5KYZSSYlBQUGxuXmxtrRQVmYZHGCclK/n5BWlp18LClm3ZuiIl6dL1LBMrKwsLC5oNpU1PT3dwcPDz8ZnRrv2d1/N98vKx34q9rZKeqSSnsa1iZqp4uWfdN6vQ3c04Ns7s1Bmj6GjGg4IWvnnt2ua1CirWPDRf1aDSUNxKLVT2o6gU9OaEFPSmgBT0W8SguJg+bBofb3rilGFWVpGzc4Gvt0F+gdUfqw1PnlPy8i452Cx3dVywZXOC5j1x1tbWdnZ2CZovQtjY2LRo0WLy5Mn3zZjhlpNTkplZYGZW6OVlnJhodvK0YWpqkaNjbpfOxQ4OlgcOWq5ep/y5V0nUVJOfTfH4welz7iVxabAJIAVdRQq6FPRGRAr6LYKIW+w/aPneZ0pUipJfrNiaKA5WiqmxcilZySq6rOT/ZHn9/0wKMnJyOMMuLi7Y87i4OHG2O3fujJrfe++9KFqp0xb6ZWTEglJYWPorqKEhQZadX3xV2RiqxKnf0S2lk1vB1LFpD87TXltvXOpD0OU1dIlE0qCYnTptuXKNcjZJSS2IzM6Ji81SzqQqZ5KUrMITSs53SsYv19OT0tNRcA8PDyQvXbPMhoOtbeclpt+/ZafdV18nhB2NiIi4fO1aXFJSfkFBMdpualoi3uVSUmIcF6dExylxN4648ekmFy+ry7cpUtAlEkmDYhwTq5y8oOQXrlWyPlLSUfBzSg7Bo0ru90rWauX6BaXAVFE8rayU/HzxXJKNogxXLO7LspgUXeJ1Mtp29RaHNetKLkcyU8/IyEhNTWXaquYuwIMXEnPj5Qf8e0kld8XcLkhBl0gkDUt+fub1vI3K9W+VzBVK9jIl+ycla3+pmmeuU7JPKfnIt1PpdRMlJzMTsXYxNetqaTNHsZmgmHspRkpageHZFK8dB6xiY0s0lx9RfARde/W4xNCw2M5OcXNWHG+8IuFkXejnqy7fpkhBl0gkdQnCWlxcXFhYWKABqSWortM8iJ9mbLzfwgBvvlvJi1WKIpX835XsL5SMX5XscKXQVlGcFeN2imlOdu71/Hx7RQkwNL7f1HaaYmWv/O+z40YX0k3TMww0r3FnL2T7v58DDQyKbG0LOndQ2ngrpa/zQuUMS8W9tX9ut65N5AJ6PSEFXSKR1DG5ubnJycnRGrDY4gq4gFVrr2e9Vph9QMlJVYpMSz/Sb+KoGK5VspKU0ssmAYrpfYrNO4pjS8XIUlE6K+aP51rPyrc0riBWpT+Elom4uMNdLAsyp9xx/R9zlQm9lRBXpW+L4gcmZ829t1TQb2vkXS7NCXmXS1NA3uVSNWlpaRkZGeQsrmuzI2trawcHBwsLi8zMzF9++WXzhg3nzp5NTk+3UpQWpe9jUZDyBI2aD2rRckqhwbToYiR+o3L9rFIQoJiMUCxtHMyU1Bs+UVscaHv6oZmJnTsZmZhwOJ6enuxIV9Mx74aZmUZJSYaZWSXUl6NDob19iRX7bCrUx10u1Qg60pmQkHDlypW4uDgqgxoiCxsbG06fr6+vs7OzeWN82FMKuhT0RkQKemUgJhAbGysuaquximJmZoamo7a///77+vXrIyMjM5OTKYNrdj7qk6EUxylFtorSW7GY1q3j8Jwi39Oln7bIUYpSlGJrxdDOylTxcyz9kfNahpJVqBgZKoG2MSP6x/Trk+flia7Z2dmRGyZd7K65cCu1cHOCTmNlxnT16tVr165FRUWh5oy62dnZVBIlICMnJycPDw8vLy/xth0kXu/ZpKxsGB8fn5eXZ2RkZGtryyYUpdzkiONhd0lJSezX3t7e3d2dXZRLo4sUdCnojYgU9MpATGic6Ea57sm5IubChQuLFy+Ojo5GDSzMzGyMjW0zsuLyCxKVIhfFKFgxmafYjOoe7JZTqJxKVLcUeJgrQ7oVubsZRV1T0jIUC/O8QL/o4UNz3FwNzc0ZLTgc5KIKxWiaNJCg00wTExMPHDiwZcuW8+fPFxYWBgUF+fj4ILXsnrVotPjQOJl27tx51KhRHTp0QOIJqlloEKPCwYMHDx8+zCZs6+/vT2Jvb29tOcTez507R5qTJ0/SGjD+I0aMCAgIKJebLlLQm7WUSEFvdOpP0MkTyc5OSzPKzzcoKFQMDXONDONTUw8eOrRixYpUzVflLCwsbCwsbA0MriQnZ+TkOClG7RSTJxW7CYqlkbe1UlCkxOs8DaQYKB1dcv8x5/qIYcVGRgYFBSVGRiWUv+nVAocPFEkEtZf1KxtpGkjQz5w58/bbb+PK+/XrN3jwYMSajSmc8ODaQmPYSblx48bdu3cPHDhw9uzZrVu3FjkIKOXx48d/+OGHe+65x8/P78qVK4g78ffffz9TJJFGZLVw4UJEatCgQYwKixYtYvzo0qULmi7SVEQKuhT0RkQKemUIcYiJji4+c9buxEnrq9GF1lYHXJxWXzi/afduXB1nzM3Njb2TNDY6Oic/30pRBiuW8xXbkYplqXaXx0Dxt1a6tcvr3+f64IFFDg4lxpobXQwMmqago0sIIyfWyMiIw7S2ttbKekVupRYqE3SjV199VV0sg3Nkbm4+adIkBB1VFS+Z1ChJKSyAyM7Z2RkR79u3L5XUsmVLGxsbNQsNSUlJERERHOGwYcNcXV3Jk6nWkSNHyLa0RjWwr8jIyLNnz7q7u/fq1Yt4qic2NpZdkKFIUxEmDbWoRcrMWUYNOYNqVHOj9LMChoa0G45CjWpu3B61QC9t7rXAIdD7qAUOhAVgQZi2WwHxctq4yW31n+7bD1pfirYNv3rs/On9kREX0tPJ39PTU+hARkYGymdnZXVXseV9JdYDFfPSm1hczZRs/OWNFjO7SElMND5x2uLwYcXJsdDVhdIT3dRqAVHKzMxE9BB0DhDwnRQPKaPBq4luRLcW1KgaQ556c9bj0ClKcnIyEox8E+R8EUMFsGORQAvjDyJOPIeB7pf7gTQ9PT0mJoZJFnabVQkJCYcPH96xY8dzzz2n/ewTZ4HIo0ePMnKMGDGCfV28eHHTpk0tWrRgRBFpONr4+HjmcSLoUNvPdTMscUTskcNRo5ob1B9wwjkKNaq5cXvUguiHzVfQ6Y8cBT2Lfk0/RXo4HGLoVnRk/BquUk16UxQVGaak2Lz+trLpgJKg1u9FJf832/zl1kapxsbIT25+fk5ubl5amr2D47iRI6b5B3Q1MnYsKCyV6e17lFNXy93N8j+sjZVZI3LuGJ/fswehplYLuGw0Ck3XVVRcr5eXFyqp93xqa6EW9pQN2VxItC7V3OWSmpZ2OSLizJkzTJcqnrjOnTsPHDhQDVSA9PRb8mcgwqefP3/+1KlTxE+dOlXr5TmYnTt3RkVFBQUF9e/fn+qJi4tbsmSJt7f33XffLdJwpg4ePLhr1y4RZE7Qrl27Ki7IVAYHj31o1v2Q8gtXwlGoUc0NWQtNAWqBQ8jNzcWK4bqElyQGAXLRIJSCSMjLz6e2OOrSuXmFOf4NFBaanD5t9K9XlJ2X1BgNB5yLv3U231lYkJmennX9elF2toupWW8bu8dmzvC5Y6KZuzsmxczKyubjz5S1W5XLlV9N7e+v3HNX7qwZpXXQxGqBofHcuXPlnBYlDAwMdHJyorRqlA6iFugItesLNXXouuzbt+/7779fu3YtQzf7LlesWbNmVbxio4s43cxBzp49GxYWxvCFmvv4+GibBUPTli1bMO/BwcF9+vQhMS2MPSLoZC7ScKbw7CtXrhTBrl27DhgwICQkRARrjih/02kBtUB7/quutaaMrIWmgKiFlJSUa9euMR1XYzWHhqZjmMRsmzpiIkUy+imbWFlZiW+BisR6KCw03r1XefUdJTRSjSml5JyL4W92Rp8lxWekpbGxhWLUXjF5SXHo5+EQPX9Wcp/epvb2rnZ27gcPGy74Tjl8ufQyi146uChzphfOf0QIuohrIrWA5T158mTFwmBAK/tQ3630BTYR44EaLqMaQf/mm2++/PLLHj16zJw509PTs9z4jNF2dHRUA 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 zI8RevGqrOTkZHpiRR9Df0T61UAF2BBL/s477xw8eJAMGQ/Q8datWzNOJCYmihhbRRmvWD6l2E1TrOyEIOQVKUfDzZeutl66GnetyUmXCqLhbKp0aH19QN9CDw/F0tLEzKyc0BAU6iGpb6oRdIYOBhAcOkZAxFA3OIKWLVvSJrQ/zkgkktqBfItepoY1EIMWA5oLSDnLOHTdZJg7jLmdnZ3eO80FePPdu3fv2bMnNjaWbb28vHBmjBYZGRlMCFjwcnMb1LXrPCuHcYqll+79iIn5ytkU5XSSGtTFy6wgxK042F6xNlLMjBQ/G2VUz+tDBokHiAw0z6+CVtNZsNI8rSqCknqlGkGnGqiMM2fOMJKLxkT7o22dOnWKIfdm30kvkUjKgSVXl3Sgr6G2gCXnL1Je0Twh6Kh51fcs0lvZkJQorKOjo7g5LSYmhpk3Cy1atBjYr99dI0aOtrOzqexBofIYFLjbx/XveW1E/9SBbdMHB18fMyDjrqm5PbqVlCk4+7K3t6dgGmEvvb8F6vYWF0llVHMNnWE8Kipq//79AQEB27Zto1aYrx0/fvzbb79ltO/fv3+rVq3UpA0IzbTi3LNaGIEwC/IaeuNye9RCHV69JR9x1UUN1xg2xG+ZmJhohwTtBXct6Km5uXlERAQFdnd3Z2A4efIkEs+Gvr6+Y8aMue/++5l/O508aZSRpeTeMEuoBIOsdp7XBvaL6ds7rnfPuH69c/v3NfTzM9S5g4V9iQtB7AVZB+YQRKqr6wh5Db02P4oy0iLiO3fu/O233y5duoS4b9y4cc2aNTSOe++9t2+/fhbm5mrSBkQKuhT0RqRupYSzIbp0LU4IAp2p+VwRdhsqCjqFpKh04WvXrkVGRiYkJNBxkFd/f//Zs2ePHTvW28fHys6uyMbKPP6aQZrO94YqxSDX3ymlbes8J/WxfgrPJJ5qFUFd2DVQqooFu3WkoNdG0GklDg4Obdu2ZRjHpLdr165z587Dhw+/4447WGBVfVRVtUhBl4LeiNStlNCD6GVYWs4MII7iocqanB9RBlKKn1W1V2bIkL/knJWVdfr0adzYxYsX09LSCNJnvb292UXXrl3p1Ii7qYWF4uJc3DrIoJ2fka2inI3R5F0Zhin92qUFtyqwVa+Jsxc8OCUXQS3Ea1Gj6hQp6HoFXc+TorocPHhw//79QUFBtAO2B0Z7lnHuFfNqMGi+NE01UGPoKpSfkYB2r0Y1N+STok2B+nhGUfRqahb5Yzk7OzspKUkrVXR7cdKq6K2asb70w9BoNN2Tv7hy+u+mTZtCQ0PT09PJgZNP/yUTGDZs2NChQ0NCQpydndncoKjIMD3d/ORpi3UbDM5eLEnPKikuNigqMUjJUdLKbpS0MMoLcrxwz7TU4KDCsmss5Ml8nWxFsMGQT4pyzqlTNVxGNQ59z549DO+0jIyMDNFW7OzsEHSW62ngrQnSoTdrV3Ib1EKde0N6E32K/gkscIrIXwg0Z4x+J+4SKbW7mn7HWs12/4MY1I2uwYnlb0xMzObNm9esWYOa480x0bhy8mHzK1euoO9ki5QHBgaKnBk0Siws8t3dMoP800yN0t2d0/18Mlp4FjhblziZljiZF7lbZwd7xPfpltCtSyHyrSkJpRVXZSmwphQNh3TonPyKp70ah37mzBkxwrNAa8Cq9+7du1evXp6enrQDmghTRTVpAyIderN2JbdBLdS3N6RXQq7mqVFt16XZQ+m9L7m5WHg1qUbl1aUyp5+amoqa79y5MzIyEtXgnGPCyIFeExsbSwydt2PHjpj0kSNH0peFLog9ipe6kI/IkBxN0zMsExPZTY6jo7h0Tnp2ymBDzi4uLo1i76RD1+vQqxF0TlY2e8vOjouLCwsLO378+KlTpxISEmgNAwYM6Nevn3wfekMiBb0p0DCCrv0LQi4JAu47MzMTAy5Wga6Y0jUuXLjwxx9/hIeHo8voPoLbsmVLZBpXzjknAeI+dOjQwYMHEy/uRXF1dUWjUXPSYOdv8LyUofTaS2lM6Y2JRkZoENZeuHKWxWAgBb0W1IegV3PJhdqyMDenyp2cnLy8vFq3bs0cjcijGsixT58+atIGRF5yadbTzNugFup7so8+6oX9il0ju2vWrImIiCCSvim2wn3v3bt3/fr1ly5dIgFi5+3t7eHhER8fj7gj5Zx5X1/fcePG4cZ8fHyYYZOGo0AXkH4xANC5RG4qKLWhIW5cwYYbGrIJu7O1tWVqLtRcFExN3IDISy7UGn/VcBnVOHQQ+7t69SrTtytXrjDy01wwCIzzkydPnjNnjpquAUHNKz5nUS00QY6/doNBE4HyixbQfBuxrIVbBKU+ffr02rVrd+zYQZdGmidMmEB5zp07t3///hMnTtBPMdp0T7CwsKCnIPQoNUKMJe/duzcmTDxhJDJEjkmJPSel3iMiATYfKWeZPWLq+dsoIq7L7dEXOATKX4u+wIZiTFXDZVQj6DSFixcv8vf8+fPXrl1LTExknLe3txf3L/LX399fTdqAMMDUYkyjFYrTV96DNB8oP9CIQY1qbtwetYCc0XEaoBZEUxeaxX4TEhJOnTq1adOmP//8MzMzE1EbNmzYXXfdlZqaSuSRI0fopEzkgdmznZ2deP0WThDJDg4ORs1B/RW0DI6FGPp1ZX2K/TIvJweWG13HtTRkLdQTt9gXhDdSA2VUI+gYgS+++AJLTpto27Ztt27d+vbty18xtqiJGhwan7yGrkY1N26PWqjbq7f0QV1hElLFAhWdkZFBU6fB0+dx0Fu3bsWYHzp0iLV2imLv7Ny5S5fA9u337d9/5swZzDvSjPK2aNECk840OikpiROOp+7UqRNGHl3m5Gt28j/YFwnELtSoCvj4+Nja2jZil6+IvIZemx9F16xZs3LlShS8Z8+erq6uVDyTONScRiDaXKMgBV0KeiNS51JCheZqXpjFAieHjspZIl7zYq5UdJwGHxUVtWLFigsXLojfLVkdZGk91tMrzdJ8a871uMREziflYdLcp08f9Pf7779nPp2dne3t7T1gwIARI0bQf1GBct2WIC6PHk0B2LsaWwFfX18EvRG7fEWkoNdG0Bnko6Oj2ZIFGpy/v3+bNm3i4+M9PDzIq7EqWAp6s27Et0Et1KGU4IvpWQg3HZvOSJ9CXjHa9vb2dD3a+dWrV48cObJ37140HYEGX8V4gGLuoRhfdDS5YFgSk5eXlplJ+v79+w8ZMqRDhw7ktnr16tDQUFSYSAyZu7s7wi06LEZb3JDOMn8JUhcUozIpIDH9HRForP6uFynoegW9mrtc2IwGtHbt2m3bttGkaGqenp4///zziRMnyI7mUjHHBoDGV4ta5Fho06hhZdcKmz7yLpemQBX3VxApxio8h/jdXlymqEIKkWxMN3/RJoFQdnNzc1xUWFjYnj179u3bJ7y5rbFxR2OzvoWm1orhFaXwWE7WletZRiYm7m5uI0eOvOOOO3r37o12Y7fRdzs7O3GZFDmmGKIMKAjxLi4uJBCCQoFJX07NSQzUFGru6OhIZ2dZXdc0kHe5oL0VK6UaQb9y5crmzZtXrVplbW19/Phx2kGXLl22bNmyfft28nJ2dmYepyZtQKSgS0FvRFA6xI9GSFdkWY3V3A9Gs0R2xf1/qCRp6LEcr0Ye9Ws6bprEeit0x44dmzZtQtPDw8PJx83Nrb2FZYhi5JRbckDJO6DkxCnFjopRgLPTsN697nnooY6dOyPTQiAQa19f35YtWyLfanYaNacj022dnJyYBODPKGFmZmbF3sRwgoiTCaYN2LCy8jcWUtD1Cno1v3Ig4sh3x44dP/roI/G1uRYtWjz11FP83b17N3M6kUwi+TuAfAAimIMJ17wJCzURkawlPi0tLSkpCbuNQ0emkzWg7HRakaYidGY2VANlkJ6B4Y8//jh69Gh0dDQ2GVXFbk/y9DaztPhFydqt5KZpfhcNUIzvcnV/efqM1gEB4s5C4cHp6uLnLpGhAI1GykmmVWcW0JSKYk0O+Hqm4w6N/Z4PyU1RjaAnJCRgN6ZOnUoFi0plVPH29p45cyat8OrVqyKZRPJ3APnGzzJtjYiIiIyMpP3HxMRo7S09AhVGi0UQEHHSo8hxcXFIvBpbgYpajxzjtfv06ePo6Iinxj/NmDEDQV+Wm70kPTlBKR0AUPNpis2r9q4PenobtGtrUHbxk21x32yFEIsYAfHouxB9LSJxOb2mj5Os3OaSZkE1gk5NU6/lhnRimuA1NYmkXkF2cdM4brw5Io5849DFFXDiWat37kw8iXFFKSkpbFJRu+lNoAbKwDUj6JMmTRo4cOCIESOGDh0aGxu7Y8eOC3Fx+H9SBysm/1IcH3Rw6ty5TfHoESV2diVl9xTSQ+mbYiTQ5kwMnoyYctpNPJGurq7iCgwwFSCo/dVU0ryoRtBpFlQwLYm5pLhWReukbW3dupVh3N3dXSSTSG570GsUHDXXvWiLRmeXPS4vlFTEl4MEOHT6TkVBt9I8BKSrnqgwekr/atWq1ZAhQwICAuhxx44dY1qQmJRk5+LSOiRkwp139J863GHKiPTRw64GByWkpqalp+vmTw4ODg7icjm92MXFhWBFmSbI7ujjJCMxkBhxJ1IKenOkmh9FacFYkv3797O8Z88e2jRjeGhoKILeoUOHAQMG+Pr6ipQNCd2DtqsGagw9hP5Gb6zFTxBNBPmjaCNC48/V3C2uhsvATWNy6RfUCy1TuHV1nQ4cNcLN4ZcTSiGdbAgihpTkxl9M/ZUrV8LCwsQ9i6zy8PDw8vJq1779uKlTTdq3T+vcMcPbK8fYWEwahDqLDIF9oeDsFCihiea5RLELVml/jiOl2COJgQW9V9WbGvJH0dr8KNquXbsxY8ZQu2+//falS5cOHDjw3HPPffzxx4znEyZM6NGjh5pOIrndoRdoBVEXEYms0Luwt+bm5hW7GVTcHDEC4pFROzs77VqkOTU1FSnftm3bwoULN2zYEBcXRxpEmf6IYacr5xkY5NvalJiYkC+ZIArMABgAMjMzCYp8gDzRdyEcTV+jJbdONQ8WsRaTnpiYePLkycjISEwETVZ8jo7ZGYN5o7QS2m6WfLCoedJ8a4G+QMOLiYkpd9c28i1EE8G1t7endmicGHndJoqe2tjYiDePa7sMmXAemAFnZ2fj0bROk14WHR29fv36w4cPo+zp6elsS3fr16/fxYsXr127xr569eo1bdo0W1tbsYmAnOme7u7u5UaOilALlJmdNuu+IB8soiup4TL0XHIh94iIiNL7rTTQnjhlNERMhIuLC96chst5pMnSBFlWN2tAaPG1qEVOAUdBmWsxwWkiyEsujQhyCZRfuF0gkroQ1VF6xUTzmyfdDKNDTyMZ3URsQjeh+4g7TIgRW0FCQgKemlNBSs1OSl+miI6vW7fu2LFj4g5IDw+PwMDA4ODgCxcuXL16VfRHOmnHjh3JlpMpNhQII1+toIujYKfNui9wCJzDZt0Xal0L1DttrFztgx6Hfu7cuY8++kgNVMmQIUOmT5+uBhoQ6dCbtStpvrWgEeFSW00VYGgQX0RcXadRaiTb19eXAxR1hJdnggtC1olH63HfUVFR5IPjxm5rq5JNiEfNjx49eunSJbwUmzAVxkWxgO4j6Bh2JgF48B49eowaNQp3hcUTmwtw6OK5UDVcCdKhNwXqw6HrqXhOUGLNqIWqSiTNF3QZrbTWfO8FI4woqys0EES7kRhUnl6KQNNd8VAE6SmY8cjIyNDQ0D/++GPRokVLly49f/486dmQTdDrs2fPbt26dfPmzSdOnKCHI82tWrXy8/NjR/Hx8QcOHEDNEXd/f/+BAwdOmDDB2dm5nJqL4vFXDUv+fuhx6MTQwtRAlYgGpAYaEOnQm7UraUa1IHqHbh+hwQtviKG5evUqdaGu0IB8t2zZkqNDoGmi9CMQHYrjJf3y5cvRccSdZIjysGHDLCwsMPIXL15E6E+dOoXrx3zZ2Ni4ubmNGTMGcT9z5gxGnsyJbN269WANpBF71IVIcfehGq4c6dCbAg3k0IFWWxOkF5Dc9iAZiCweGQVHprUKTlc0u/HBenoE3QwdT9Z8ZxljzrbEI+hRUVHo9UcffSQkm0jWskBuiPvGjRu//vprVomO7e7u3rNnz1GjRv3111/Hjh3DmBNpb2+Pjs+aNat///4Vu7GANNh5NSD5W1LNXS5NE+nQpUNvAOgaeOekpCT+Ch1HxM3NzT09PTFHNMKUlBS0m2MRnQh9t7Ozy87OZpWQcjEY7N279/jx4xEREWg3qxw0Hw8aNGhQ27Ztsd6hoaHnzp1jtEhPT0eOO3To4OXlhWsjvXh9LoOEh4cH6bt168Yq3ce2tRAjHg7C7zOuqLGVIx16U6DhHLpE8jcHpcjTPNmP10bQ6XWAHGPSARER4q6rnog+KYFtkXiUHdO9evVqjPaJEyeuXLlCGn9//379+o0cObJVq1bnz5/fvHnz4cOH8e8YdsaJAQMGDBw40NHRETVnLQMGI0SbNm1w69jzli1botdoN5TryexODCGSvzlS0CWS/4EyostiCoiUo93lhJK14nIKy6wiKOw5EMkqYpB+nDtqvm3bNiT7woULWDDsM4rcs2fPoUOHent7nz59etWqVUeOHImLi8Nqubu7h4SEjB8/vnPnzgTFBJRIvDwSP2TIEDc3N4YQIo2MjBhIKj4Cwi7ET7JqWPK3pKpLLqyiadJAResp14AaEdHf1ECNkZdcmgJNvBY4t1hsRFYYbTX2RrDJPj4+yCsOmpRqbBkIbnR09N69ezHmSDkxpLexsQkMDJw4cSICfe3atR07duzatSshIYG1rPL19UW1x40bxzyaXkaCnTt3rlu3rkePHkRi6nVvN7a1tcW26x1snJ2d7e3t2Z0arhx5yaUpUB+XXKoSdAb8rVu3hoWFzZs3z8XFRbdVNS5S0KWg1xM0LfEsaBVWl77EIQi7A2psGbifn376Cb2+evWqaKXiO5/9+vVDu4lHrKOiosR1G/S3f//+ffv2bdOmDWeGxAg6Tj81NTUiIiIgIADtps/reilHR0e2YgYgBV0KekVBr+qSCztjT5GRkUwPm+9Zk0i00P8Ra9RQe9eKuHgiYC29q2o1B9Kg+1BRzVFe9HRgu3YdvL2NsrJ8TM0edvWYH9x6iL8/nnrJkiWbNm2iQ1EAkgUFBd19991jxoxBza01L7YVwk2/Q7UZBvhLjxWRWigwsHm5ePwWYwnbqmHJ35Kq3rZoaGiIxaDpnzlzhuZCC87OzqZdppdBu6+JHahzaNC1GGAY0zgKcYlTjWpuyEf/bwWaK204LS0NHWcB4RZloEgaLTVgSsoqGrlIXw4S0CPEjFbvvJYEzJ8sSkoCwo7ZnD5rHZM5qshimomlm6FyKTVlw/lzhw4fjouLYxeenp5t27YdMmQIzt3Dw6NiJxJ3QJKhGtaBs2eu+T4c5xAoSel+TUxsbW2ZAVS2VTlIxi7EAKZGNTfko/9UOn/VcBnV3LZ4/Pjx5cuXYyvwCy1atGACSCHUdYrSqVOnAQMGqIEGhN4oL7moUc2NRqwFdoqaJyUlaSUA7aM87u7ueFs6AmYF70zrEmu1aM4683sj0uiVe7GW3OhONnHxAV9+m3XoQnxmXoBinKwU/6XkrDLP3WmiMJKwO2dn59atW/ft27dXr1705yr0V5Nf+e5JDk5OTsg3XYCxQTxrSq+0t7dH6Cv2cL2QCWVGR+Qll0bkVmqBGr 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 z2TJ5G0wP79+zMBveOOO1BzPAeZME/dv3//zz//nHHjC3iFYUfZcUxMEfjLsrpOImlYqm95tE6MuTAseCIsD8GOHTuiv8xM1UQ3z9mzZzds2MCUmTGqW7du5Lx69epff/2VPhwUFCQFXVKFWAsqm1xixiMiIpYuXYoxx57TxpBpvAwtrZzUIuWnTp1avHjxrl27cN/YF+Sb5ocrHzFiRJs2bRgVUHnxUQucO+mvXLnC1EGUjdxot3glFoSmC4R5l0ganmoEXTgOXDNTTmdnZ9q3eP8ccwRav7AzNQHJ7tChg+48lOkGGYrO0K59e9Yyk2XYCAkJwbMzZqjpJH8zkGmh1BWnk9WCzjLt27t379q1a7dt24YKY8xpaUjzwIEDcSHiPkLyxzdcvXo1NDR0/fr1SLZ4f4uXlxdpxowZg5oHBATgXXbu3Llx48YTJ06QLdrt6+s7YMAAR8334UDclk45pYJLmgjVXEPfsWMHc8yoqKinnnoK80Lw9OnTM2fOROKPHj06ePDgZ555Rk3agMhr6M36uqHeWtDIeOmFFESZBY4RhU1LS6vsqosWYYpJhv4i38ePH9+3bx++m1X4A5yBj48PfqJ///72mre4kBILj0Cj5mFhYefPn2en4isTbdu2JVnnzp1JQJs/cOAAYwNaT1aurq6o+aBBg+677z4yoYSIOHaEw2FtsxN0il3rq7dNBHkNvab3oYtzhJuG9IyMPbt3f/jhh6NGjbrjjjuOHDny3//+l25Df2NaOn369CFDhqibNSBS0Jt1I9ZbC7Q6Zn7x8fHEc4BoNBaYGJbVFPpASUnGJBI1x2ivXr06PDycYYBVqLmLi0uPHj2GDx/esmVLYmjq7IVxIjIycsmSJSh1cnKy6BgeHh7jx4/v2rUr7pudovIrVqw4d+4c01CRoHv37qg5kBV75BD+tlLSRJCCXlNBZyq6atWqDh06tG7dmvbN/lJTU9mYCSYySodhBkpvwcjgfbDt6mYNiBT020/QMcVxcXFCzUUMYl2xcZYDZ02XQH8XLFhw6dKlTM096cTTPnv37o3++vn5iT0SSW5XrlzZvXv3tm3bMjIy2BfFQMrx72PGjPH09KQx09RJsGnTpqSkJKQfT4PHR+t79epFSroDgk5fIkMp6I2LFPSaCvrhw4fnz5/P/NTJyYmZZosWLWjE/GXKST9h98LXODg44IzUbRoWKejNuhFXrAUaIeoZFRVVtR+n9ZNAt8UKP3Hy+PFPP/gwKj4uKzvbw8Y2wMO964ABQZ06+fj6sjsxMLC7Q4cOHTt27OzZs9HR0TQhGjANG+uNNaF5MyfArISGhh49epQ5KGMD8i0umpPAzc2NrGj/3t7eJqamf2cpaSJIQdcr6Hpen0vXiomJYYGpa0JCAqZGvKycnnDx4kVi6FRkxMST0tANxFYNSaF8fW6zfbBIby1wRHma12+p4UpgQzqwGtBA0CAt3eDcucLd+67lXm9XZDzM1OIOG7shQUF2ISEm1taoOd4fgd67dy/Wm2bMBJRG6+XlFRIS0rdvX4w8ak5LJhlSvnXr1gsXLtC6/P39O3XqNHToUPEKXEYO+g9unYW/+Ytbmwjy9bmIMH/VcBmVXkNHxy9fvhwZGYltYRkdZxhBxF1cXNzd3ekPAQEBHTp0qMUj+LeOdOjN2pVUrAUaIRVKM6vYGnURrV8NlGEbHuG4ZVvWb7s+VzL6KOZDFAtfI7OCYPtj/3wk3dMj4 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 KSEmyvnOsABhpeI67A5pAy1Cy0tjigeZCX2D2gnWTWlqLNDtpffv36zp07v/zyyx9++OHy5ctlZWUMIEHFw8NjypQpBMJ6Bk0TYiig8vXr13/99dcodFEV0XTy5MkvvfTSsGHDsIK2u9QA8aN3797R0dEUp+z8+fOfeuqpvn371vMBryR0fYAkdH1ASxB6C+6hw9Qsw5nqrNyhRcTg6dOnYaLXX3/dxsZG5IGXDxw4EB4eDjn6+PhABAkJCXCllwoiD7o+Pj7+zJkz4hQtD2XUsyGjjWuq59CLi4sZOyWpGowI0QWaZiXBsDIaMBG0CJUDqFxNTFzSLC5IXDlpYXBrVPnJkyf3799P2IN/c3JyGDpaOHToUFY2xEg3NzfCzB0pGPx640Z+Xt7WrVsPHjwYFxeXkZFx/fp1qqKS0aNHjxw5cuDAgbiaLr2jYZTds2cPBrKzswsKCurfvz8jo1yuDcILDZvQVcAZtN3JUCCtoA9oihWYnkxSbQHXsoQOB0GmmoT+/fffsybQJPSQkBA43cnJae7cuYjfsLCw2NhYJOfs2bNFHgpCPYh3cQrRox/d3d3FqS5gvAoKCqBsGoNaV3sAI0IggQchdJYIFRUVXGKkiCtCgOsoeFsURUVFiHFCI4Nw6NAhmJ0YaWVlhR5nKMaPH+/n5weN6si/1JaUlBQZGQmhX7hwgTFBiaOyfX19Z86cOXz4cOKlkls3MGI0iXpMTU0dHByU1LqBB9PU27PQYOch7QcMZsvNnZaGtII+oClWoMjdVugISRbjCMAHH3wQpi4sKjodHb1r166//OUv6EGRB6qNiIg4evQoAnPOnDkEq9TU1K+//hp+X758uciDBiQSkEecQl6urq7QmTjVEfS/RAXYkChCrwnvgs0Bw0oe7n57aG/d6qwfP5pDI4lAR44cYdDEZhSJIvwwCFOnTp03b17Pnj11jDpEMmiXkdyuAmESbyDQwuDijaH6HxVtLnALIaykNmxFCCvg8HiFkmRokFZAd95VQs/OzkZXQsTPPPMMghdm5xT1/fgTT1hWv+NOT86ePRsaGurs7CwIPS0tTRD60qVLRR5tNOixRTXEljds3oiHhFoFDM6JEydWrlwZFRWlJBkZIaWh8vnz5zcopOH0LEG++OKL4ODguLg4kUhYDQwMXLZs2ahRo0TKXYDBWUEb8rFFfYB8bLFrbY8tNuwptwYBLclaHh5JT0+nxfxHsw8ePNhY9UQzYhmKh7Ogcnicq+L02LFj9JOCopJ7GYRfT09PliMODg4scQYMGPDyyy+/++67UHCDPkIoKChAkj/77LPiy7lIYYT9/PxeeumlF198cciQISKbhISEoaMFFTo1I9LDwsKKi4vhJlibBT6re/Fi0ZEjR1DriE24KTIyMjk5uby8nGxlZWUeHh7u7u71bObeIwpdmGbv3r2schgWdDThEGHOUktHVUJP0eP79u1D41+4cKG0tJTAzoCPGTNm7Nix1IZI1w7yLQqDs4I2pELXB0iFXqtCb8HHFtupXq5BpxcWFsLmHCA2XVxc2queD8nNzYXokeempqZmqldv0OxQGITl7e1dz8ssACHfCCsyBCKuGMruLaMEiIKMhpub2+jRo+FfExMTRoleKJnqAI6OGCdq7tmzJyQk5MyZM0RBQikmmDBhwuzZs0eMGFH/g4mEkKKiIvFdLkpSc8DgrKAN+diiPkA+tgi7as/fFlToLYd7RKFrA1Vyxy/nwj9Y62RmZoaGhv7yyy8sfQio9L1Hjx4+Pj5TVDCv7QeG1MAl4HGkfUpKCgpi1qxZrAnwPOVy0yAVuj5AKnR9QEsodEnohgRdCF28jvvpp59GRUVB5aTQcZZHDz/88Jw5c3T5KJXKg4OD165dm5CQMGDAgJUrV4on05XLTYMkdH2AJHR9QEsQegt+KCpx93Hu3LnPP//8tddeE7/rT4qDg8OkSZM+/vjjBQsW3PGjVELFxYsXP/roow8//DAxMZEaMjIyvv76awS7kkNCQkKPIQm9FZCVlRUaGrp7927ERbOskCDi4uLibdu2rVu3bufOncnJybm5ucRwf3//+fPn//73vx86dGjPnj3rV9mw9pEjR6hh7969q 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& quot alt=& quot & quot & & & & & & & & & & As a result, the misfit residuals show a pattern of under and over estimations for high/low& br& flows (Figure 3).& & & & & & & & & & img src=& quot data:image ng base64, 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 HHdzy7YofrRrIesRsSGVgRR4Tvk7pJyiVSq0HchbXu2KRWIbWq2Dy2mh9j7G//9m//9E//9Oc//3nDSZJeeumlW2+99ac//SlEv+F0StLf33/33Xd/9atfhbI3nHYzODh411133XLLLaZpNpyOE2otpRY6eKVNWGnTm+kh64RwSqiwDg6QGZBJfE+Y8zQq5yIOD2i6Ddvc4orKFYVTmRAkMireyQPHIY7TsOiPHFjlq1atqtfrExMTu3bt2mOwe54HaxeEm0cKigrE0Ng4MPBzjOO8EBwnCVN933i ouvfTSt771rbquN5yOF5xIjEocS8Nh2jItRply5lPLVvLjEt3d+2UyuAOMUbPmtXWwRAK5tOF+UKJRprjw6TvKlDOCazdNKiyG/aQozplo1osnJEXZe+9hjDKFkfuLX/xi+/btfX19c+fOffvb3/7qV78a7k888cSjjz4Kg/e8884bGhpKJBLnn38+VDKVSmEv3FEYrFmzBsly1qxZV1111bx585A7UCo89dRTOCesI8u8973vhdX/3HPPwabGnTzrrLOuvvpq3MmwzSebzY6NjSFOnOHatWsREBkNJ4wjXnLJJZqmjYyMIOy2bdsQJJ/PYxdiQOSIE+nh8ssvP+ecc/Bo7r// UrVy5btgzeEAPO5A1vfGMqmUSQF198EWXVBz7wAWQixIYTfv7553HO3d3dCL548eKj+6TJsw/lX3qxFMvyd94824hN64+iyF/4whcaq6cVSCsAeRtGwWHoGoGgixej9boQ8WC1sUdoug/LCwYXS2ckVds3E+4XVVVF3j0Zn52DDCFz4gSg6ce9gfIwCS8f2bWxfQLBtQPchMN79IcGUUFfkJYa25PAHYYMYUWrVRP58cT4WKxYwBIv5mMTE/FCPlY3Y5VKrFJ+5VKJl8vxcsmoVmLlUqxUFKFKRbVW8wyDyzLkOJPJhIfYF1zUzp07//u///uaa66ZPXt2rVaDSl5xxRU4T8g9hHvTpk24/yhyII4w5yGCCxYswN144IEHnnzyyWKxCIlEkYDEmUwmofjw9l//9V8QfcQMg2DOnDm33XYbRBxmAYJDZBcuXIgrhYLfcccdiBmPdcaMGRDcu+66C7FhFwqAQqEAQ7ujowPrt99+++OPP44iwTRNKDLKHpxhqVTCQVGEwA8ucP369U8//TSeFE4MjjgH5Ku2tjZUQVasWIGDvva1r8XFPhKAyHHOuGocC3empaUlvBVHRP/O+uiQrcakpedmFWVaV7tP44tHKscv0jQy5MGBHxl6nUpRGVVlYbJTFAmciV/cAlSeYVK1tZNYHHrZCHMocHTx5zCOPkXg2vErH/YJH3cad+CEg+MCcfnH7+aL9HRQEhPjbZs2znr+uXCZ+cLzM19a071lU/eGl/a/bFqPZdaaF2e9sLIR5MWVnRvWqtahG5Shg7CXN2/evGTJkmuvvRbSHBrCkGnshQJCat/xjnf867/+67vf/W6UOrDrsQvS+dBDD6GY/5u/+Zsvf/nLCAtVffjhh8M4obzpdPr1r389goSCe/HFF3/+85//yEc+AkWG5qKQwMr4+Pjy5cv/4i/+Aqb6Cy+8AJn+9Kc//aUvfQkSDJW/9957w3IUCg6J//CHP3zLLbd0dnbCckft7bOf/ewHP/jBHTt2YBN+cBUIfuGFF/7t3/7txz/+cRj13/rWt1AkTC6JR0dHH3vsMcSGc/63f/s31Dwg9zjn41JaT2dOV1lHVoQhgF/YWbBHDgmMlmSuSZ+/UO/sNmLxmOvGPT/muTBejNaO2Kx58baOZDrd8H0YwFRB0EQ83tg+gSCfoy4MaTtZJwBwAjh6Y+PEguOKcho273G6dtzPQyq7mHmCedRzX158TyzeIZc9QeDfP5xmXwgorPJZs2a1t7dDnZubmyF/cIE9i72wZM855xzIJU4bog/TG8Y71Hz16tVIk0uXLkVAXM7111+PkgBlQyiRkN2LLrroggsugO0PJT377LPPOussSC3s9M985jNYR1jY6TjiW97yllwuB6GHLX 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 VHd365aVW15MnQTZ7Xa2FfST0jtFsyylPDQTCjdhUlAgbeMaLPL40OysqY1jr2OvFGFXEy1m7tpp3+ZepDZCJFzqxaTSFz2vOMlrGp1uSXYD20I2QeEiEm9jcovOLG9TTURTodKEg9wLYzWzKjQeY1xN01pxz0XjCqZUqFW44wESvkJhCWHDua6QfdBrD+s/ZD9CrMNmsuL7IcnQQhVukTvkkeAiSrzUaClm8fSeImSn0hMX/LPT+gwKhA/kgIheOBNvrD6Z68b6d77znTNnzvzO7/zO7bff3m63kcdX2s1hOqyh+h7WX3Y4BPZBoUyFMjwxImvJlhQRsN7T2YLOrMhOO5ly9lYV9slwgp76GoI7yVhczuybwEcf6S+06m8mZr+Vq5U25CNMOBE6Rt01zj642zmtzYXLcE+rbyyOp5wtGtUz0MgNvIjaDX0bxOOD1ZcfNM824i/gjjqJEI9v10nK+5cn7xb8XK0vNvKZDWOz235KiufadZu7Q4jZpSqDQN105lDQipwcJNpFNJsFDVqXgjR3DaY30l6RP4NALZWZ0udBozVQ6V1cNVS/opk1aGtN42TcUpVOdI1aqmUD+d4hH49tLxOa3xsVhg8qMCu9FR4XhTpP1hJXWgsqFwulPqXr89xteXfR+XPWIWWXpOxJcXk6w+syHLKH9avYa8H6zOXGblDHg+5ydws3aPvOTERGJAVokwzesjh9R+HHz5ovf3/rbzcnT6K+jnUnkhl2I2nR5FFz0I/Srhvrm5ubFy9ezPMcwhzZMF97062h+h7WXxbrM0O5BD3rwKdBxFJZlysuExUnnJnAUYhXROixMreTbeoppp755gMpClDOWG/nJFZ2izt6C7LprakUeYehDgrP75um+yv9beVp2Aj2FOF4Vv11Wi6wcKRIUAeAZT9Q1K9YBgop+Wj7fB8KoIkBLfqsVTzQrruCX5ymI2pTiDCOB5P0yUg+l5Z3cZokr+lauXQsSWsUDwFRTw4gmxZAEzYt428TLJ1WgcDNsdgtS+q12PZi29d2Kan3Z9Xh1HQUTTzioeBiL1suTj1qKUiz0rK05gueGkUGlyZoblaJ1rhiDnqdaaYD6lBmMwd5nyoRJ0Aho74XwfNAA+U7RHZ6J50ifT2G69jD+lXstWAdJljIuD8RIsMEyL6fU/tsblAycSHSnFet1uTe5fptPd3bZE+e2H302NaXNyfPoCB30jXI9qaM/YjturGOdB+NRn/4h3949OjRb33rW4888shXr7CyLG+99db5rjfSGqrvYf0VsI7yFdHoC6AHFNED54beuOAXpdyvwmHFV0QtfF75cp+MTrGYBlETa8DPgrFyrt8BXqhXHoYQ44wfKGOwdTakPSI3hSy1atnoe8rIWnmWnA048jcQ2UfSepBWuE3JRyN1tV8S1I29gLRmCedAQmIRVzeDNP5CWUvXi+xaSqhNvT5jlEONUuqC9HX8bAzB7Pvcd2bHNKegLh0cTtp/fkZcPlUVjZ90AZ2OYGlGbOqgh0RTMkTK9VOzFtkl6VPuW5Hrx24pNmuJWUo8zY2UWZ1YZLmQ3Fe8bXgXtYZkNngdaKgRwkT4AQ0W4SHxhYlY0XJofURo10DWx+RZBKevQ1CCA/EdQfOi0JVfj+1h/er2GrGOcpPyMAlyI8iaiSOsjhk5mKZNwLZEiS+FzLXx8XQpKe/OJodbdsWFcrs+dnr47bODb4+KMyi2sW6jNm+C/NHYdWP9zJkzX/nKV77whS+gYE0mk52dnY0rbHV19a1vfet81xtpDdX3sP4KWCcKcJZw4kgmleYayz0elpVfZNMlUadhyP0kErKtWreoCFsv4HJAJ98wnco5eDXrnKGHjOcEdWmDVH2rOpb8zYtArq/Au54h176Rlc/jIFQA2rHYPteqnosNFx57tsi5LqGtCXYm0meLtDz7AMHNCop580W0lr6TmIPt6lbtcNOPnJwWyuXaFskFq84KPkGdoezapeAoABLpTW97E+AsGMJ64wieel2wsWkyk9PdhuyJdn3le4IcoHmsIU/xtpmcj/lCbzPyRiAk8MzSUqwB6/TGaVCOBtSTaxyKM9oANB6SWc9rTe55A2juhUm8o/dS6QLzwAB0SHssrzQ9lrPrvUajDN3D+svba8U6Mp4mcwlDpi4EFfNwiNsXevqwQMNxp7zaFK5QyXrL3tOpb0+KVZFHJq92pxs7xYmd4vlxec7YXMoYcIeiao6+qXbdWP/c5z73iU98ApL8Z3/2Z++9914sHLnC7r777kOHDs13vZHWUH0P66+AdRh2bjrZ6eXIFR3v1/GajjuAsc8TmjOoyphZ1B0tW2tadKnHxJ71NZG9ISHBPRgm82YeUYDfBnUAAKAVSURBVMhw+3ySF8ov+6jjVNSQ2kjyleg4azl11yS7pVbnRRhJGiIJuA/b5aMJjg1JANlVgky7jLLZ3yb9CInzRTpx84f+Ulc71S0Q1Iut6TszFwk+MhJwt5UMu+mOiZ+TfEP7BeVTFmg6Doo3HUr9Ozi2+Ukrmo/AJTYna7ZQjw2WFIE+KEh1iWqLPO4jBWh8CyBmeGc3OZvrSSVxjVnFWxU7aFnPhZYJmUcTh5oizXwdVCFIJBbqMep5Us5kFLolF7/BS/Ia7FhYI5qHIoQjWqNiaa7vWg0772H9KvYasT6zNgpzYOeDOh2iO0XVohm/5pvIguPFlhDb4qBiWSRNK53eupA/uOTekdiFyXSwOTh2cff5YXne+KlnVgh58+F+3ViHTn/iiSf+1b/6V7/xG7/x3ve+98EftJvDdFhD9T2svzLWrzQgUosoVq1ELXTitW6ynkULiUxaXGqpKsa6zK6GqbKjEzOlTt3rZeaHH2LbPyVGfV6fpLEx+VYSTrZdL6heGUWMl01/Nv47Dnkqbp8mb51klrNjaU1kh8XmaKf4m6S+r4j2lRGkPYXdNABoYfbB/8aQmjgrVs36UppNZFjGvRGX9/byezNnJ+mzlaKnlNPIDFpn6uQr/eKgtms8AKUUG4SNoEiQNzL6stEGCm4W8Oy8s80zaa+l6dZqEERNa6jvvl+IYiPbupDa7Sjb1rn2Szwskk8vltKH6hI62yzMEvTHWclrDK9bEPTMZt7GvpYhD35NySVFLtJwsv2axufMLu0aDTvvYf0q9rpgHfmRNm/fPx4SZNMhYdpNpT03KJ48J+/4Sx2xzuTaWLTL4CQfLGcX37I2/Mh6/b7I9s+Pv/f45l9dzJ+IlOpnByN1U+daum6sP/bYY0ePHv3Qhz60vr6O4jVfe9Otofoe1q8P61caB1jQpAzWusL6aVeqFMgI1ri8duM1VnWYuy3svjNcfJfYPay4klAcqs3FWXJqNZlothN7q3yv1tqJXLlCenLzK10pQuLEvkqvl9HjSJuIpDq58Y3t57u51W6l0l0LAUQ4w/YXU+3y7yZl8esy+GgZQPTtpL5jYfxgyk6WalhLctWY63qn820pTkSuJeoDFHhzEL6o+mhk+0y8z9bi3iSm08rLEaEN+EEpEzJ6c4teXEpis6TcSmLXY7vOQ6eUohaZYYn0kQooA3FzLAfGcZwU9L6iD6LpcxHSijp105YdRQ6JsyrlqlIZPWmlaucgAE2nnEfqWmwP61e31wXrMEVd6qFm4ns+OcJNj7vkBbJDSkyYMazTpYnxcBvFVvQLuTJSKyORVsKmyfCWxZ2fOrD7kdbO7bsXd85tfb/mw25nTUoUquvI7ldt14313d3ds2fPfve7303TdDKZDAaDrSsMmd2+KXMANlTfw/qrxDpCmFlgwfg8rzdjlcacJ9ymYdx2m+tstOY2DrDhCi/TUEPge67HQe8G2Q31/jDOBbuo+BNxcNq1jTCCFDbCxUIhHcru7I2kxcCfATdloN527BPZJ9L6XFLj3u3XKvbA4AvF/DJ8Z/xFuuLQ5hcZ9cYQAQme0rdjuy+rD2QmZmKn0nmNGkXXRXShjo4xuYlNJLkuvUZLh13+04RJhmWS8bMbjXg+29yQHZUHzYlHWygQxDOVrosPuYkMKXM9FlrgvkB9xUVoBkRSrKHZUSrogmk2VYlk0Ix1fNQKvZgvS2I6Llly3pVin1J7nTBX2hsH68gT5FvC/HMhggDocr/G0f5sNuF/UdCkmGip9vqcHC6juHvAnSeGZ0Z2KtX1URZnoq/NohytyK11dmG9OCvsQIaK8lyQO1E6yw2y68b6k08++dnPfvaRRx7Z2Nj4/ve//53vfOdbVxgK7X333Tff9UZaQ/U9rL96tT4zBOWDq93Uh1pxobnXYSrNZssP2343CxXjshCtSGaS8XEQW4BzqFLmF5XoKbWlxLHIlcrtaLurXa5sxf1E27FytfBAvBHhoJXciW3fAJx62+3ZtP5CbLrNFKmdpnf+hRvmkmHVLFlfSN1LMG44CJTqyBxODUR0W3vj5HalfKFtEW2b6ISXuzG9TIT7MaX7Zxb45RO8KMeaAOfLzb44QoRIUJ8qKIOGBjkLkz5B4yTyPeEzGTpN/wzufR/QyJl19lCHOnmUoe4cHKeYUlwqTqMbU96JedI4DYBU15wvSbXQ+Ku/fOJrMey+h/Wr2OuFdRjiEXN67/RUiFosrHOTzQQ78gBMryqGFFheJm+OTR5SoYGQiR1vGd6uBD5ZpVIRR+0odOuRH20M7CC2O1G5xattVo+CK5tWI26813TRL2HXjfXHH38c+F5aWirL8kVSHXbw4MF3v/vd811vpDVU38P6a8c6xIaSQpduiIXAnHHTyg4qM2TBGqamomXVYipYxF0V3NjZUWAJF4sqQpNygYszgp9NyqNp/b20+mZSSeUG2l6MjYWKZWyqXBz4rWVy/zSBjjk7e2UJcM+qb7cqD7J7kToRIyeblznnAJ6BGN8QwNDsMw7jP64cG2Z/GxNuKSvv6ZS3ar5l5YimSFV+Ehe7rWcitqFcBF0vfMpnD6xwbJNX85PM/jS/m7+Xf+OkzXNXiPQQC5dAktPaIFXIFJje+IAUuOsZgI7dIpqWg0ZPzr6FwO2tyOEAj4SKQkQuw4SUHMoPks8EBs0+642Zn++aDZe8h/Wr2OuIdcr+5vHp8RDXjPe438/JTT6yDLd9qGueT3mvH7T+YSqTftceyl30SrGQh+7Q6K3cb+TF2OwKu5lOz4hyI9QDZqbBl8zXuPHoOHoQ1JS112jNo4EfQ7ONoXzvOeZ97TkIwV7ZYVHvjOuNSXlhWm9sTU9UTF4QK7tyaYU6VaCa7bYtj1r5XbZ0G6tV1OU8zr06yloXXUw+3FEoERMr2DRhVn1k3DpUxFNNibNo5G2TrGvU97uT/3hkg2UF9VLAEPAk+38eW3/vdq9jFN1GVCLnKJ/ZHL5Y06yCNrrUGzM3rMc/z8tx939/eu2/b7YHqFFmmw6Purds/EZ/938JfhE/6Zgm5NnRcxcw9Ht2hpld+ksvbFnqUmHCi4EXtecAMkqa8ARvhCGEj2O7NNPp9JNCQt3khKaB/kbxsstE29FgGcF8Gopbit3M9CJxKFJrSskrruIaDRe+55j3KvaqHfNexf7Gts8G9VZR 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& quot alt=& quot & quot & & &
Publisher: Springer Science and Business Media LLC
Date: 13-09-2022
Start Date: 2009
End Date: 2012
Funder: Australian Research Council
View Funded ActivityStart Date: 2010
End Date: 2012
Funder: Australian Research Council
View Funded ActivityStart Date: 2013
End Date: 2016
Funder: Australian Research Council
View Funded ActivityStart Date: 2019
End Date: 2023
Funder: Australian Research Council
View Funded ActivityStart Date: 06-2010
End Date: 10-2014
Amount: $228,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 07-2009
End Date: 04-2015
Amount: $785,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 03-2014
End Date: 12-2019
Amount: $541,581.00
Funder: Australian Research Council
View Funded ActivityStart Date: 08-2020
End Date: 08-2025
Amount: $3,973,202.00
Funder: Australian Research Council
View Funded Activity