Floodplain inundation in the Murray–Darling Basin under current and future climate conditions

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  • Serra-Llobet, A. et al. Restoring Rivers and Floodplains for Habitat and Flood Risk Reduction: Experiences in Multi-Benefit Floodplain Management From California and Germany. Front Environ Sci 9, (2022).

  • Pratt, O. P., Beesley, L. S., Pusey, B. J., Setterfield, S. A. & Douglas, M. M. The implications of brief floodplain inundation for local and landscape-scale ecosystem function in an intermittent Australian river. Mar Freshw Res 75, (2024).

  • Opperman, J. J., Luster, R., McKenney, B. A., Roberts, M. & Meadows, A. W. Ecologically Functional Floodplains: Connectivity, Flow Regime, and Scale1. JAWRA Journal of the American Water Resources Association 46, 211–226 (2010).

    Article 
    ADS 

    Google Scholar 

  • Blöschl, G. et al. Changing climate shifts timing of European floods. Science 1979(357), 588–590 (2017).

    Article 
    ADS 
    MATH 

    Google Scholar 

  • Alifu, H., Hirabayashi, Y., Imada, Y. & Shiogama, H. Enhancement of river flooding due to global warming. Sci Rep 12, (2022).

  • Blöschl, G. et al. Changing climate both increases and decreases European river floods. Nature 573, 108–111 (2019).

    Article 
    ADS 
    PubMed 

    Google Scholar 

  • Gu, X. H. et al. The changing nature and projection of floods across Australia. J Hydrol (Amst) 584, (2020).

  • Schmocker-Fackel, P. & Naef, F. More frequent flooding? Changes in flood frequency in Switzerland since 1850. J Hydrol (Amst) 381, 1–8 (2010).

    Article 
    MATH 

    Google Scholar 

  • Smith, A., Freer, J., Bates, P. & Sampson, C. Comparing ensemble projections of flooding against flood estimation by continuous simulation. J Hydrol (Amst) 511, 205–219 (2014).

    Article 

    Google Scholar 

  • Chen, J. et al. Impacts of climate warming on global floods and their implication to current flood defense standards. J Hydrol (Amst) 618, 129236 (2023).

  • Di Baldassarre, G. Floods in a Changing Climate: Inundation Modelling. Floods in a Changing Climate: Inundation Modelling https://doi.org/10.1017/CBO9781139088411 (2010).

    Article 
    MATH 

    Google Scholar 

  • Douglas, E. M., Vogel, R. M. & Kroll, C. N. Trends in floods and low flows in the United States: impact of spatial correlation. J Hydrol (Amst) 240, 90–105 (2000).

    Article 
    MATH 

    Google Scholar 

  • Lawrence, J. et al. Australasia. in Climate Change 2022 – Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds. Pörtner, H.-O. et al.) 1581–1688 (Cambridge University Press, 2022). https://doi.org/10.1017/9781009325844.013.

  • DAWE. Murray Darling Basin Plan. Preprint at https://www.agriculture.gov.au/water/mdb (2012).

  • Wasko, C. & Sharma, A. Steeper temporal distribution of rain intensity at higher temperatures within Australian storms. Nat Geosci 8, 527–529 (2015).

    Article 
    ADS 
    CAS 
    MATH 

    Google Scholar 

  • Guerreiro, S. B. et al. Detection of continental-scale intensification of hourly rainfall extremes. Nat Clim Chang 8(9), 803–807 (2018).

    Article 
    ADS 
    MATH 

    Google Scholar 

  • Dowdy, A. J. et al. Review of Australian east coast low pressure systems and associated extremes. Clim Dyn 53, 4887–4910 (2019).

    Article 
    MATH 

    Google Scholar 

  • Sharma, A., Wasko, C. & Lettenmaier, D. P. If Precipitation Extremes Are Increasing, Why Aren’t Floods?. Water Resour Res 54, 8545–8551 (2018).

    Article 
    ADS 

    Google Scholar 

  • Bennett, B., Leonard, M., Deng, Y. & Westra, S. An empirical investigation into the effect of antecedent precipitation on flood volume. J Hydrol (Amst) 567, 435–445 (2018).

    Article 
    MATH 

    Google Scholar 

  • Wasko, C., Guo, D., Ho, M., Nathan, R. & Vogel, E. Diverging projections for flood and rainfall frequency curves. J Hydrol (Amst) 620, 129403 (2023).

  • Ho, M. et al. Changes in flood-associated rainfall losses under climate change. J Hydrol (Amst) 625, 129950 (2023).

  • Hettiarachchi, S., Wasko, C. & Sharma, A. Can antecedent moisture conditions modulate the increase in flood risk due to climate change in urban catchments?. J Hydrol (Amst) 571, 11–20 (2019).

    Article 

    Google Scholar 

  • Wasko, C. & Nathan, R. Influence of changes in rainfall and soil moisture on trends in flooding. J Hydrol (Amst) 575, 432–441 (2019).

    Article 
    MATH 

    Google Scholar 

  • Wasko, C., Sharma, A. & Westra, S. Reduced spatial extent of extreme storms at higher temperatures. Geophys Res Lett 43, 4026–4032 (2016).

    Article 
    ADS 
    MATH 

    Google Scholar 

  • Di Luca, A., Evans, J. P. & Ji, F. Australian snowpack in the NARCliM ensemble: evaluation, bias correction and future projections. Clim. Dyn. 51, 639–666 (2018).

    Article 
    MATH 

    Google Scholar 

  • Vermote, E., Justice, C., Claverie, M. & Franch, B. Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. Remote Sens Environ 185, 46–56 (2016).

    Article 
    ADS 

    Google Scholar 

  • Lewis, A. et al. The Australian Geoscience Data Cube — Foundations and lessons learned. Remote Sens Environ 202, 276–292 (2017).

    Article 
    ADS 
    MATH 

    Google Scholar 

  • Chiew, F. H. S., Zheng, H., Post, D. A., Robertson, D. E. & Rojas, R. Hydroclimate Trends and Future Projections in the Murray-Darling Basin. https://www.mdba.gov.au/sites/default/files/publications/mdb-outlook-hydroclimate-literature-review2.pdf (2022).

  • Barry Hart, Neil Byron, Nick Bond, Carmel Pollino & Michael Stewardson. Murray-Darling Basin, Australia: Its Future Management. (Elsevier, 2020).

  • MDBA. The 2020 Basin Plan Evaluation. https://www.mdba.gov.au/sites/default/files/pubs/bp-eval-2020-full-report.pdf (2020).

  • MDBA. Assessment of Environmental Water Requirements for the Proposed Basin Plan: Riverland–Chowilla Floodplain. (2012).

  • Roberts, J. & Marston, F. Water Regime for Wetland and Floodplain Plants: A Source Book for the Murray-Darling Basin. (Australian Government: National Water Commission, 2011).

  • Ticehurst, C., Penton, D., Teng, J. & Sengupta, A. Maximum two-monthly surface water extent for MDB from MIM and WOFS – Version 2. CSIRO. Data Collection (2023) https://doi.org/10.25919/s7c2-hc39.

  • Gallant, A. J. E., Kiem, A. S., Verdon-Kidd, D. C., Stone, R. C. & Karoly, D. J. Understanding hydroclimate processes in the Murray-Darling Basin for natural resources management. Hydrol Earth Syst Sci 16, 2049–2068 (2012).

    Article 
    ADS 

    Google Scholar 

  • Chiew, F. H. S. & McMahon, T. A. Climate Variability, Climate Change and Water Resources in Australia. Proceedings of the Second International Conference on Climate and Water, Vols 1–3 (1998).

  • Peel, M. C., McMahon, T. A. & Finlayson, B. L. Continental differences in the variability of annual runoff-update and reassessment. J. Hydrol. (Amst.) 295, 185–197 (2004).

    Article 
    ADS 
    MATH 

    Google Scholar 

  • Chiew, F. H. S. & McMahon, T. A. Global ENSO-streamflow teleconnection, streamflow forecasting and interannual variability. Hydrol. Sci. J. 47, 505–522 (2002).

    Article 
    MATH 

    Google Scholar 

  • Hart, B., Byron, N., Bond, N., Pollino, C. & Stewardson, M. Murray-Darling Basin, Australia: Its Future Management (Elsevier, 2020).

    Google Scholar 

  • Our Story—Coleambally Irrigation. https://www.colyirr.com.au/our-story.

  • Murray-Darling Basin water markets: trends and drivers 2002–03 to 2018–19. https://daff.ent.sirsidynix.net.au/client/en_AU/ABARES/search/detailnonmodal/ent:$002f$002fSD_ASSET$002f0$002fSD_ASSET:1029942/one.

  • Academy of Science, A. Investigation of the Causes of Mass Fish Kills in the Menindee Region NSW over the Summer of 2018–2019. www.science.org.au/fish-kills-report (2019).

  • Vertessy, R. et al. Final Report of the Independent Assessment of the 2018-19 Fish Deaths in the Lower Darling. https://s3-ap-southeast-2.amazonaws.com/figshare-production-eu-latrobe-storage9079-ap-southeast-2/31186917/1185369_VertessyR_2019.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIARRFKZQ25KW2DIYRU/20250110/ap-southeast-2/s3/aws4_request&X-Amz-Date=20250110T060546Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=0303ca3c2d4f5f2d4e1e875b257e7083da480bd76ddebf8627b2fb927df249fa (2019).

  • Jackson, S. & Head, L. Australia’s mass fish kills as a crisis of modern water: Understanding hydrosocial change in the Murray-Darling Basin. Geoforum 109, 44–56 (2020).

    Article 
    MATH 

    Google Scholar 

  • Murray–Darling Basin Authority. The Murray–Darling Basin Authority Annual Report 2012–13 (2013).

  • Sen, P. K. Estimates of the regression coefficient based on Kendall’s Tau. J. Am. Stat. Assoc. 63, 1379–1389 (1968).

    Article 
    MathSciNet 
    MATH 

    Google Scholar 

  • Fu, G. et al. Statistical analysis of attributions of climatic characteristics to nonstationary rainfall-streamflow relationship. J. Hydrol. (Amst.) 603, 127017 (2021).

    Article 
    MATH 

    Google Scholar 

  • Prosser, I. P., Chiew, F. H. S. & Smith, M. S. Adapting water management to climate change in the Murray–Darling Basin, Australia. Water (Switzerland) 13, 1–19 (2021).

    Google Scholar 

  • Speer, M. S., Leslie, L. M., MacNamara, S. & Hartigan, J. From the 1990s climate change has decreased cool season catchment precipitation reducing river heights in Australia’s southern Murray-Darling Basin. Sci. Rep. 11(1), 1–16 (2021).

    Article 
    ADS 

    Google Scholar 

  • Golding, B. & Campbell, C. Learning to be drier in the southern Murray-Darling Basin: Setting the scene for this research volume. Aust. J. Adult Learn. 49, 423–450 (2009).

    MATH 

    Google Scholar 

  • Potter, N. J. & Chiew, F. H. S. An investigation into changes in climate characteristics causing the recent very low runoff in the southern Murray-Darling Basin using rainfall-runoff models. Water Resour. Res. 47 (2011).

  • Whetton, P. & Chiew, F. Climate change in the Murray-Darling Basin. In Murray-Darling Basin, Australia—Its Future Management (eds Hart, B. T. et al.) 253–274 (Elsevier, 2020). https://doi.org/10.1016/C2018-0-01363-8.

    Chapter 

    Google Scholar 

  • Post, D. A. et al. Decrease in southeastern Australian water availability linked to ongoing Hadley cell expansion. Earths Future 2, 231–238 (2014).

    Article 
    ADS 
    MATH 

    Google Scholar 

  • CSIRO. Water Availability in the Murray-Darling Basin A Report from CSIRO to the Australian Government. https://publications.csiro.au/rpr/download?pid=legacy:530&dsid=DS1 (2008).

  • Hart, B. T. The Australian Murray-Darling Basin Plan: Challenges in its implementation (part 1). Int. J. Water Resour. Dev. 32, 819–834 (2016).

    Article 
    MATH 

    Google Scholar 

  • Pittock, J., Williams, J. & Grafton, Q. The Murray-Darling Basin Plan fails to deal adequately with climate change. Water (Basel) 26–30 (2015).

  • Grafton, R. Q. & Wheeler, S. A. Economics of water recovery in the Murray-Darling Basin, Australia. 46, 55 (2024)

  • Sheldon, F. et al. Are environmental water requirements being met in the Murray–Darling Basin, Australia? Mar. Freshw. Res. 75 (2024).

  • Connell, D. & Grafton, R. Q. Water reform in the Murray-Darling Basin. Water Resour. Res. 47 (2011).

  • Pahl-Wostl, C. Transitions towards adaptive management of water facing climate and global change. Water Resour. Manag. 21, 49–62 (2007).

    Article 
    MATH 

    Google Scholar 

  • Kingsford, R. T., Biggs, H. C. & Pollard, S. R. Strategic adaptive management in freshwater protected areas and their rivers. Biol. Conserv. 144, 1194–1203 (2011).

    Article 
    MATH 

    Google Scholar 

  • Pittock, J. & Finlayson, C. M. Australia’s MurrayDarling Basin: Freshwater ecosystem conservation options in an era of climate change. Mar. Freshw. Res. 62, 232–243 (2011).

    Article 
    CAS 
    MATH 

    Google Scholar 

  • Commonwealth Environmental Water Holder. Water Management Plan 2023–24. https://www.dcceew.gov.au/sites/default/files/documents/cewh-water-mgt-plan-2023-24-full.pdf (2023).

  • Tulbure, M. G., Broich, M., Stehman, S. V. & Kommareddy, A. Surface water extent dynamics from three decades of seasonally continuous Landsat time series at subcontinental scale in a semi-arid region. Remote Sens. Environ. 178, 142–157 (2016).

    Article 
    ADS 

    Google Scholar 

  • Heimhuber, V., Tulbure, M. G. & Broich, M. Modeling 25 years of spatio-temporal surface water and inundation dynamics on large river basin scale using time series of Earth observation data. Hydrol. Earth Syst. Sci. 20, 2227–2250 (2016).

    Article 
    ADS 

    Google Scholar 

  • Heimhuber, V., Tulbure, M. G. & Broich, M. Modeling multidecadal surface water inundation dynamics and key drivers on large river basin scale using multiple time series of Earth-observation and river flow data. Water Resour. Res. 53, 1251–1269 (2017).

    Article 
    ADS 

    Google Scholar 

  • Pekel, J. F., Cottam, A., Gorelick, N. & Belward, A. S. High-resolution mapping of global surface water and its long-term changes. Nature 540(7633), 418–422 (2016).

    Article 
    ADS 
    CAS 
    PubMed 
    MATH 

    Google Scholar 

  • Senanayake, I. P., Yeo, I.-Y. & Kuczera, G. A. Three decades of inundation dynamics in an Australian dryland wetland: An eco-hydrological perspective. Remote Sens. 16, 3310 (2024).

    Article 
    MATH 

    Google Scholar 

  • Ceola, S., Laio, F. & Montanari, A. Human-impacted waters: New perspectives from global high-resolution monitoring. Water Resour. Res. 51, 7064–7079 (2015).

    Article 
    ADS 
    MATH 

    Google Scholar 

  • Teng, J. et al. Two-monthly maximum flood water depth spatial timeseries for the MDB. CSIRO. Data Collection (2023). https://doi.org/10.25919/c5ab-h019.

  • Penton, D. J. et al. The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps. Sci. Data 10, 652 (2023).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Ticehurst, C., Teng, J. & Sengupta, A. Development of a multi-index method based on Landsat reflectance data to map open water in a complex environment. Remote Sens. (Basel) 14 (2022).

  • Cohen, S. et al. The Floodwater Depth Estimation Tool (FwDET v2.0) for improved remote sensing analysis of coastal flooding. Nat. Hazards Earth Syst. Sci. 19, 2053–2065 (2019).

  • Teng, J. et al. A comprehensive assessment of floodwater depth estimation models in semiarid regions. Water Resour. Res. 58 (2022).

  • Marvanek, S. et al. LIDAR enhanced SRTM Digital Elevation Model (DEM) for Murray Darling Basin. CSIRO. Data Collection (2022)

  • Jeffrey, S. J., Carter, J. O., Moodie, K. B. & Beswick, A. R. Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environ. Model. Softw. 16, 309–330 (2001).

    Article 

    Google Scholar 

  • Chiew, F. H. S. & McMahon, T. A. The applicability of morton and penman evapotranspiration estimates in rainfall-runoff modeling. Water Resour. Bull. 27, 611–620 (1991).

    Article 
    MATH 

    Google Scholar 

  • Morton, F. I. Operational estimates of areal evapo-transpiration and their significance to the science and practice of hydrology. J. Hydrol. (Amst.) 66, 1–76 (1983).

    Article 
    ADS 
    MATH 

    Google Scholar 

  • Chiew, F. H. S. et al. Estimating climate change impact on runoff across southeast Australia: Method, results, and implications of the modeling method. Water Resour. Res. 45 (2009).

  • Zheng, H. et al. Projections of future streamflow for Australia informed by CMIP6 and previous generations of global climate models. J. Hydrol. (Amst.) 636, 131286 (2024).

    Article 

    Google Scholar 

  • Perrin, C., Michel, C. & Andreassian, V. Improvement of a parsimonious model for streamflow simulation. J. Hydrol. (Amst.) 279, 275–289 (2003).

    Article 
    ADS 
    MATH 

    Google Scholar 

  • Chiew, F. H. S. et al. Future runoff projections for Australia and science challenges in producing next generation projections. 1745–1751 Preprint at http://www.mssanz.org.au/modsim2017/L16/chiew.pdf (2017).

  • Zheng, H., Chiew, F. H. S., Potter, N. J. & Kirono, D. G. C. Projections of water futures for Australia: an update. 1000–1006 Preprint at https://mssanz.org.au/modsim2019/K7/zhengH.pdf (2019).

  • Viney, N. R. et al. The usefulness of bias constraints in model calibration for regionalisation to ungauged catchments. In 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation 3421–3427 Preprint at http://www.mssanz.org.au/modsim09/I7/viney_I7a.pdf (2009).

  • Blöschl, G. et al. Twenty-three unsolved problems in hydrology (UPH)—A community perspective. Hydrol. Sci. J. 64, 1141–1158 (2019).

    Article 
    MATH 

    Google Scholar 

  • Fowler, K. J. A., Peel, M. C., Western, A. W., Zhang, L. & Peterson, T. J. Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall-runoff models. Water Resour. Res. 52, 1820–1846 (2016).

    Article 
    ADS 

    Google Scholar 

  • Saft, M., Peel, M. C., Western, A. W., Perraud, J. M. & Zhang, L. Bias in streamflow projections due to climate-induced shifts in catchment response. Geophys. Res. Lett. 43, 1574–1581 (2016).

    Article 
    ADS 

    Google Scholar 




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