Detecting the impact of land cover change on observed rainfall

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

Determining water requirements for Black Box (Eucalyptus largiflorens) floodplain woodlands of high conservation value using drip-irrigation

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 diversions 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 similar to 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), similar to 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.The authors gratefully acknowledge funding from the BiodiversityFund of the South Australian Murray-Darling Basin Natural ResourceManagement Board. We thank Riverland West Landcare and RebeccaTurner for their support and assistance; Treasury Wine Estates PtyLtd for provision of environmental water and for establishing andmaintaining the drip irrigation, led by Brendan Turner; Kelly Marsland(MDBA) and Kate Holland (CSIRO Land and Water, Adelaide) foradvice on experimental design; Kate Frahn (SARDI) and JodiePritchard (CSIRO) for field assistance; Martin Nolan and Sultan Umoru(CSIRO Land and Water, Adelaide) for GIS assistanc

Bayesian inference of synthetic daily rating curves by coupling Chebyshev Polynomials and the GR4J model

&lt;jats:p&gt;Abstract. In fluvial dynamics studies, there are instances where it becomes necessary to estimate the daily discharge of a river in locations where only one instantaneous level record is available per day. In such cases, there may be no rating curve, or one that is unreliable, making it difficult to make accurate discharge estimates. A daily rating curve would be an estimate of the daily discharge of a river, from a single instantaneous stage level. This work proposes to estimate synthetic (non-gauged) daily rating curves from nearby gauged locations using a rainfall-runoff model. A rainfall-runoff model (GR4J) is coupled with an instantaneous/stage–daily/discharge relationship based on third order Chebyshev polynomials. The parameters in the joint daily rating curve and rainfall-runoff model are optimized and uncertainty is quantified with Bayesian inference and the Delayed Rejection Adaptive Metropolis algorithm assuming model residuals to be normally distributed N(0,σ). A case study with four gauging sites in New South Wales, Australia, and periods with no changes in the stage-discharge relationship were selected. The method is implemented four times across the gauging sites, where three sites are assumed gauged and one site is assumed to have only instantaneous water level records. The results of this methodology can help provide a more comprehensive understanding of the hydrological functioning of systems, where only one instantaneous stage level per day is available. This is particularly useful in situations where historical observations or satellite altimetry data in rivers is used to estimate daily flows. &lt;/jats:p&gt

Comparison of Surface Water Volume Estimation Methodologies That Couple Surface Reflectance Data and Digital Terrain Models

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 sampled 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 example fail to consider dynamic sedimentation processes taking place in reservoirs. Resolution effects account for a fraction of errors, being mainly caused by terrain curvature

Remotely sensed evapotranspiration to calibrate a lumped conceptual model: Pitfalls and opportunities

Physically representative hydrological models are essential for water resource management. New satellite evapotranspiration (ETobs) data might offer opportunities to improve model structure and parameter identifiability, if used as an independent calibration set. This study used a modelling experiment on 4 catchments in New South Wales, Australia, to investigate whether MODIS (16A3) ETobs can be used to improve parameter calibration for low parameter conceptual models. The catchment moisture deficit and exponential routing form of the model IHACRES was used to test calibration against streamflow, MODIS ETobs or a combination setoff the two. Results were compared against a regionalized parameter model and a model using MODIS ETobs directly as input. Firstly, the results indicated that the observed water balance of the catchments has, currently unexplained, large positive differences which impact the calibrated parameters. More generally, using MODIS ETobs as a calibration set, results in a reduction of the model performance as all residuals of the local water balance and timing differences between the water balance and the outflow need to be resolved by the routing component of the model. This is further complicated by variations in land cover affecting the MODIS ETobs. Finally this study confirms that the calibration of models using multiple environmental timeseries (such as MODIS ETobs and Q) can be used to identify structural model issues

From ad-hoc modelling to strategic infrastructure : A manifesto for model management

Models are playing an increasingly prominent role in watershed management, and environmental management more generally. To successfully utilize model-based tools for governing water resources, modelling timelines must match decision making timelines, and modelling costs must fall within budget constraints. Clarity on management options for modelling processes, and effective strategies, are likey to improve outcomes. This paper provides a first conceptualisation of model management and lays out its scope. We define management of numerical models (MNM) as governance, operational support, and administration of modelling, and argue that it is a universal activity that is crucial but often overlooked in organizations that rely on modelling. The paper lays out the leverage points available to a model manager, based on a review of model management practices in several fields, highlights lessons learned, and opportunities for further improvement as model management becomes a mainstream concern in both research and practice.Peer reviewe

Constraining water age dynamics in a south-eastern Australian catchment using an age-ranked storage and stable isotope approach

Improving our knowledge of the travel times of water through catchments is critical for the management and protection of water resources and to improve our understanding of fundamental catchment behaviour. In this study we use the age-ranked storage framework StorAge Selection (SAS) to investigate travel times in the Corin catchment, a headwater catchment in the south-east of Australia covered by native Eucalyptus species. Few studies have applied the SAS framework globally and in energy-intensive areas where catchment losses are heavily in favour of evapotranspiration relative to streamflow. A combination of observed and modelled values of oxygen-18 (δ18O), the stable isotope in water, are used to constrain storage selection preferences of streamflow and evapotranspiration and the size of the catchment active storage. The highest performing parameter combinations that could reproduce δ18O in streamflow were dependent on a strong preference for young water in evapotranspiration, and a mixture of weak young and old water preference in streamflow. The mean travel time of streamflow over the study period 2007–2019, weighted by the flow rate, is limited to within a probable range of 2.81–9.77 years. The size of the active storage, a key parameter in the SAS framework, was poorly identified, and in combination with the isotopic inputs into the model, contributed to the uncertainty of the results. We discuss the implications of the results with respect to the study area, as well as within the context of SAS research globally and identify ways to improve the modelling process

Constraining the response of continental-scale groundwater flow to climate change

Numerical models of groundwater flow play a critical role for water management scenarios under climate extremes. Large-scale models play a key role in determining long range flow pathways from continental interiors to the oceans, yet struggle to simulate the local flow patterns offered by small-scale models. We have developed a highly scalable numerical framework to model continental groundwater flow which capture the intricate flow pathways between deep aquifers and the near-surface. The coupled thermal-hydraulic basin structure is inferred from hydraulic head measurements, recharge estimates from geochemical proxies, and borehole temperature data using a Bayesian framework. We use it to model the deep groundwater flow beneath the Sydney–Gunnedah–Bowen Basin, part of Australia’s largest aquifer system. Coastal aquifers have flow rates of up to 0.3 m/day, and a corresponding groundwater residence time of just 2,000 years. In contrast, our model predicts slow flow rates of 0.005 m/day for inland aquifers, resulting in a groundwater residence time of ∼ 400,000 years. Perturbing the model to account for a drop in borehole water levels since 2000, we find that lengthened inland flow pathways depart significantly from pre-2000 streamlines as groundwater is drawn further from recharge zones in a drying climate. Our results illustrate that progressively increasing water extraction from inland aquifers may permanently alter long-range flow pathways. Our open-source modelling approach can be extended to any basin and may help inform policies on the sustainable management of groundwater.</p