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Modelling climate-change impacts on groundwater recharge in the Murray-Darling Basin, Australia

Modelisation d’impacts de changements climatiques sur la recharge de nappe dans le Murray-Darling Basin, Australie

Modelado de impactos del cambio climático en la recarga del agua subterránea en la Cuenca Murray-Darling, Australia

模拟澳大利亚墨累-达令盆地地下水补给对气候变化的响应

Modelação dos impactes das alterações climáticas na recarga de água subterrânea na Bacia Murray-Darling, Austrália

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Abstract

A methodology is presented for assessing the average changes in groundwater recharge under a future climate. The method is applied to the 1,060,000 km2 Murray-Darling Basin (MDB) in Australia. Climate sequences were developed based upon three scenarios for a 2030 climate relative to a 1990 climate from the outputs of 15 global climate models. Dryland diffuse groundwater recharge was modelled in WAVES using these 45 climate scenarios and fitted to a Pearson Type III probability distribution to condense the 45 scenarios down to three: a wet future, a median future and a dry future. The use of a probability distribution allowed the significance of any change in recharge to be assessed. This study found that for the median future, climate recharge is projected to increase on average by 5% across the MDB but this is not spatially uniform. In the wet and dry future scenarios the recharge is projected to increase by 32% and decrease by 12% on average across the MDB, respectively. The differences between the climate sequences generated by the 15 different global climate models makes it difficult to project the direction of the change in recharge for a 2030 climate, let alone the magnitude.

Résumé

Une méthode est présentée pour évaluer les variations moyennes de la recharge de nappes souterraines sous un climat futur. La méthode est appliquée au Murray-Darling Basin (MDB), Australie, d’une superficie de 1,060,000 km2. Des séquences climatiques ont été dévelopées sur la base de trois scénarios pour 2030 rapportés au climat de 1990, à partir de 15 modèles climatiques globaux. La recharge diffuse en milieu aride a été modélisée avec WAVES en utilisant 45 scénarios climatiques ajustés à une distribution de Pearson de Type III pour réduire le nombre de scénarios à trois: climat futur humide, climat futur intermédiaire, climat futur sec. L’utilisation d’une distribution probabiliste a permis d’évaluer l’importance de n’importe quelle variation de la recharge. Cette étude a mis en évidence que, pour un futur climatique intermédiaire, la recharge augmente en moyenne de 5% dans le MDB, mais de façon non uniforme sur l’ensemble du bassin. Pour les scénarios humide et sec, la recharge augmenterait en moyenne de 32% et baisserait de 12% respectivement dans le MDB. Les différences entre les séquences climatiques générées par les 15 modèles climatiques globaux rendent difficile la projection de la tendance d’évolution de la recharge à l’horizon 2030, sans parler de son amplitude.

Resumen

Se presenta una metodología para evaluar los cambios promedios en la recarga del agua subterránea bajo un clima futuro. El método se aplica a los 1,060,000 km2 de la Cuenca Murray-Darling (MDB) en Australia. Se desarrollaron secuencias climáticas basadas sobre tres escenarios para el clima de 2030 relativo al clima de 1990 a partir de las salidas de 15 modelos climáticos globales. La recarga difusa de agua subterránea en tierras desérticas fue modelada con WAVES usando estos 45 escenarios climáticos y ajustados a una distribución de probabilidad Pearson Tipo III para condensar estos 45 escenarios a 3: un futuro húmedo, un futuro mediano y un futuro seco. El uso de la distribución de probabilidad permitió evaluar la importancia de cualquier cambio climático en la futura recarga. Este estudio encontró que para un futuro clima medio la recarga se proyecta incrementándose en promedio un 5% a través de la MDB pero esto no es espacialmente uniforme. En los escenarios futuros húmedos y secos la recarga se ve proyectada a incrementarse en un 32% y decrecer 12% en promedio a través de la MDB, respectivamente. Las diferencias entre las secuencias climáticas por 15 modelos climáticos globales diferentes hace difícil proyectar la dirección del cambio en la recarga para el clima del 2030, y mucho menos aún la magnitud.

摘要

本文提出了一种方法用于评估未来气候条件下地下水补给的平均变化。将该方法应用于面积约1,060,000 km2的澳大利亚墨累-达令 (Murray-Darling) 盆地。基于15个全球气候模型和三个基于1990年气候的2030年气候情景, 预测了气候序列。利用WAVES模拟45个不同气候情景下干旱大陆的地下水补给。之后使用皮尔逊III型概率分布曲线将这45个情景分为三个类型: 潮湿、正常和干旱的未来。应用概率分布评估任意补给变化的意义。研究发现正常气候会导致MD盆地平均补给增加5%, 但是这个补给存在空间差异。在干旱和湿润情景下, MD盆地平均补给分别降低12%和增加32%。由15个不同的全球气候模型生成的气候序列的差异导致2030年气候条件下地下水补给变化趋势评估变的困难, 更不用说其定量化。

Resumo

Apresenta-se uma metodologia para avaliar as alterações médias da recarga de água subterrânea sob um cenário futuro de alterações climáticas. O método foi aplicado à Bacia Murray-Darling (BMD), com 1,060,000 km2, na Austrália. Foram desenvolvidas sequências climáticas baseadas em três cenários para o clima em 2030 relativamente ao clima em 1990, a partir dos resultados de 15 modelos climáticos globais. A recarga difusa da água subterrânea de Dryland foi modelada com programa WAVES, usando estes 45 cenários de clima, e foi ajustada a uma distribuição de probabilidades do Tipo Pearson III, de modo a condensar os 45 cenários a três: um futuro húmido, um futuro mediano e um futuro seco. A utilização de uma distribuição de probabilidades permitiu avaliar a significância de qualquer alteração da recarga a atingir. Neste estudo prevê-se que a recarga correspondente ao futuro cenário climático mediano aumente em média 5% ao longo da BMD, mas este aumento não é espacialmente uniforme. Nos futuros cenários húmido e seco prevê-se que a recarga aumente 32% e diminua 12% em média ao longo da BMD, respectivamente. As diferenças entre as sequências climáticas geradas pelos 15 modelos de clima global dificultam a previsão do sentido de alteração da recarga para o clima em 2030, se excluirmos a magnitude.

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References

  • Abbs K, Littleboy M (1998) Recharge estimation for the Liverpool plains. Aust J Soil Res 36(2):335–357

    Article  Google Scholar 

  • ABS (2003) Year Book Australia 2003. Australian Bureau of Statistics, Canberra, Australia

    Google Scholar 

  • Beverly C, Bari M, Christy B, Hocking M, Smettem K (2005) Predicted salinity impacts from land use change: comparison between rapid assessment approaches and a detailed modelling framework. Aust J Exp Agric 45(11):1453–1469

    Article  Google Scholar 

  • Broadbridge P, White I (1998) Constant rate rainfall infiltration: a versatile non-linear model: I. analytical solution. Water Resour Res 24:145–154

    Article  Google Scholar 

  • Brouyère S, Carabin G, Dassargues A (2004) Climate change impacts on groundwater resources: modelled deficits in a chalky aquifer, Geer basin, Belgium. Hydrogeol J 12(2):123–134

    Article  Google Scholar 

  • BRS (2008) Integrated Vegetation Cover 2008. Bureau of Rural Sciences, Canberra, Australia

    Google Scholar 

  • Brunner P, Bauer P, Eugster M, Kinzelbach W (2004) Using remote sensing to regionalize local precipitation recharge rates obtained from the chloride method. J Hydrol 294(4):241–250

    Article  Google Scholar 

  • Charles SP, Bates BC, Smith IN, Hughes JP (2004) Statistical downscaling of daily precipitation from observed and modelled atmospheric fields. Hydrol Process 18(8):1373–1394

    Article  Google Scholar 

  • Chiew FHS, Teng J, Kirono D, Frost AJ, Bathols JM, Vaze J, Viney NR, Young WJ, Hennessy KJ, Cai WJ (2008a) Climate data for hydrologic scenario modelling across the Murray-Darling Basin. A report to the Australian government from the CSIRO Murray-Darling Sustainable Yields Project, CSIRO, Canberra, Australia

    Google Scholar 

  • Chiew FHS, Vaze J, Viney NR, Jordan PW, Perraud J-M, Zhang L, Young WJ, Penaarancibia J, Morden RA, Freebairn A, Austin J, Hill PI, Weisenfeld CR, Murphy R (2008b) Rainfall-runoff modelling across the Murray-darling basin. A report to the Australian government from the CSIRO Murray-Darling Sustainable Yields Project, CSIRO, Canberra, Australia

    Google Scholar 

  • Chiew FHS, Teng J, Vaze J, Post DA, Perraud JM, Kirono DGC Viney NR (2009) Estimating climate change impact on runoff across southeast Australia: method, results, and implications of the modeling method. Water Resour Res 45, W10414, 17 pp

    Google Scholar 

  • Christensen JH, Hewitson B, Busuloc A, Chen A, Gao X, Held I, Jones R, Kolli RK, Kwon WT, Laprise R, Magana Rueda V, Mearns L, Menendez CG, Ralsanen J, Rinke A, Sarr A, Whetton P (2007) Regional climate projections. In: Solomon S et al (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Cook PG, Walker GR, Jolly ID (1989) Spatial variability of groundwater recharge in a semiarid region. J Hydrol 111:195–212

    Article  Google Scholar 

  • Crosbie RS, Wilson B, Hughes JD, McCulloch C, King WM (2008) A comparison of the water use of tree belts and pasture in recharge and discharge zones in a saline catchment in the Central West of NSW, Australia. Agric Water Manage 95(3):211–223

    Article  Google Scholar 

  • CSIRO and BOM (2007) Climate change in Australia, CSIRO and BOM, Canberra, Australia

  • D’Agnese FA, Faunt CC, Hill MC, Turner AK (1999) Death Valley regional ground-water flow model calibration using optimal parameter estimation methods and geoscientific information systems. Adv Water Resour 22(8):777–790

    Article  Google Scholar 

  • Dawes WR, Gilfedder M, Stauffacher M, Coram J, Hajkowicz S, Walker GR, Young M (2002) Assessing the viability of recharge reduction for dryland salinity control: WANILLA, Eyre Peninsula. Aust J Soil Res 40(8):1407–1424

    Article  Google Scholar 

  • Dawes W, Zhang L, Dyce P (2004) WAVES v3.5 User Manual, CSIRO Land and Water, Canberra, Australia

  • Delin GN, Healy RW, Lorenza DL, Nimmoc JR (2007) Comparison of local- to regional-scale estimates of ground-water recharge in Minnesota, USA. J Hydrol 334(1–2):231–249

    Article  Google Scholar 

  • DFA (1974) Agreement between the Government of Australia and the Government of Japan for the protection of migratory birds in danger of extinction and their environment. Australian Treaty Series 1981 No. 6, Department of Foreign Affairs, Canberra, Australia

  • DFAT (1986) Agreement between the Government of Australia and the Government of the People’s Republic of China for the protection of migratory birds and their environment. Australian Treaty Series 1988 No. 22, Department of Foreign Affairs and Trade, Canberra, Australia

  • IPCC (2001) Climate change 2001: the scientific basis. Contribution of working group 1 to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge

    Google Scholar 

  • IPCC (2007) Climate change 2007: the physical science basis. Contribution of working group 1 to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, 996 pp

    Google Scholar 

  • Isbell RF (2002) Australian soils classification. CSIRO, Collingwood, Victoria, Australia, 144 pp

    Google Scholar 

  • Jeffrey SJ, Carter JO, Moodie KB, Beswick AR (2001) Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environ Model Softw 16(4):309–330

    Article  Google Scholar 

  • Johnston RM, Barry SJ, Bleys E, Bui EN, Moran CJ, Simon DAP, Carlile P, McKenzie NJ, Henderson BL, Chapman G, Imhoff M, Maschmedt D, Howe D, Grose C, Schoknecht N, Powell B, Grundy M (2003) ASRIS: the database. Aust J Soil Res 41(6):1021–1036

    Article  Google Scholar 

  • Jyrkama MI, Sykes JF (2007) The impact of climate change on spatially varying groundwater recharge in the Grand River watershed (Ontario). J Hydrol 338(3–4):237–250

    Article  Google Scholar 

  • Lim WH, Roderick ML (2008) Global water cycle atlas based on the IPCC AR4 Climate Models. The Australian National University, Canberra

    Google Scholar 

  • Littleboy M, Herron N, Barnett P (2003) Applying unsaturated zone modelling to develop recharge maps for the Murray-Darling Basin in New South Wales, Australia. In: Post DA (ed) Proceedings of International Congress on Modelling and Simulation, MODSIM 2003, Modelling & Simulation Society of Australia & New Zealand Inc., Perth, Australia

    Google Scholar 

  • Loáiciga HA, Maidment DR, Valdes JB (2000) Climate-change impacts in a regional karst aquifer, Texas, USA. J Hydrol 227(1–4):173–194

    Article  Google Scholar 

  • McCallum JL, Crosbie RS, Walker GR, Dawes WR (2010) Impacts of climate change on groundwater in Australia: a sensitivity analysis of recharge. Hydrogeol J. doi:10.1007/s10040-010-0624-y

  • Meehl GA, Covey C, Delworth T, Latif M, McAvaney B, Mitchell JFB, Stouffer RJ, Taylor KE (2007) The WCRP CMIP3 multimodel dataset: a new era in climate change research. Bull Am Meteorol Soc 88(9):1383–1394

    Article  Google Scholar 

  • Nunez M, McGregor JL (2007) Modelling future water environments of Tasmania, Australia. Clim Res 34(1):25–37

    Article  Google Scholar 

  • Petheram C, Walker G, Grayson R, Thierfelder T, Zhang L (2002) Towards a framework for predicting impacts of land-use on recharge: 1. a review of recharge studies in Australia. Aust J Soil Res 40(3):397–417

    Article  Google Scholar 

  • Pilgrim DH (1987) Australian rainfall and runoff: a guide to flood estimation, 1. The Institution of Engineers, Barton, ACT, Australia

    Google Scholar 

  • Post DA, Chiew FHS, Teng J, Vaze J, Yang A, Mpelasoka F, Smith IN, Katzfey J, Marston F, Marvanek SP, Kirono D, Nguyen K, Kent D, Donohue RJ, McVicar TR (2009) Climate scenarios for Tasmania. Tasmania Sustainable Yields Project, A report to the Australian Government from the CSIRO Tasmania Sustainable Yields Project, CSIRO, Canberra, Australia

    Google Scholar 

  • Ramsar Convention Bureau (1971) Convention on wetlands of international importance especially as waterfowl habitat. Ramsar, Iran, 2 February 1971. UN Treaty Series No. 14583. As amended by the Paris Protocol, 3 December 1982, and Regina Amendments, 28 May 1987

  • Rosenberg NJ, Epstein DJ, Wang D, Vail L, Srinivasan R, Arnold JG (1999) Possible impacts of global warming on the hydrology of the Ogallala Aquifer region. Clim Change 42(4):677–692

    Article  Google Scholar 

  • Salama R, Hatton T, Dawes W (1999) Predicting land use impacts on regional scale groundwater recharge and discharge. J Environ Qual 28(2):446–460

    Article  Google Scholar 

  • Scanlon BR, Healy RW, Cook PG (2002) Choosing appropriate techniques for quantifying groundwater recharge. Hydrogeol J 10:18–39

    Article  Google Scholar 

  • Serrat-Capdevila A, Valdés JB, Pérez JG, Baird K, Mata LJ, Maddock T (2007) Modeling climate change impacts - and uncertainty - on the hydrology of a riparian system: the San Pedro Basin (Arizona/Sonora). J Hydrol 347(1–2):48–66

    Article  Google Scholar 

  • Slavich PG, Walker GR, Jolly ID, Hatton TJ, Dawes WR (1999) Dynamics of Eucalyptus largiflorens growth and water use in response to modified watertable and flooding regimes on a saline floodplain. Agric Water Manage 39(2–3):245–264

    Article  Google Scholar 

  • Sophocleous M (1992) Groundwater recharge estimation and regionalization: the Great Bend Prairie of central Kansas and its recharge statistics. J Hydrol 137:113–140

    Article  Google Scholar 

  • Szilagyi J, Harvey FE, Ayers JF (2005) Regional estimation of total recharge to ground water in Nebraska. Ground Water 43(1):63–69

    Article  Google Scholar 

  • Tuteja NK, Vaze J, Teng J (2005) The CLASS modelling framework: a platform for distributed eco-hydrological modelling, MODSIM, 2005, Melbourne, Australia, December 2005

  • UNFCCC (1992) United Nations framework convention on climate change. UN, New York

    Google Scholar 

  • USGS (1982) Guidelines for determining flood flow frequency. Bulletin #17B of the Hydrology Subcommittee, US Geological Survey, Reston, VA

  • Wang HX, Zhang L, Dawes WR, Liu CM (2001) Improving water use efficiency of irrigated crops in the North China Plain: measurements and modelling. Agric Water Manage 48(2):151–167

    Article  Google Scholar 

  • Wu H, Rykiel EJ, Hatton T, Walker J (1994) An integrated rate methodology (IRM) for multi-factor growth rate modelling. Ecol Model 73(1–2):97–116

    Article  Google Scholar 

  • Xu C, Martin M, Silberstein R, Smetten K (2008) Identifying sources of uncertainty in groundwater recharge estimates using the biophysical model WAVES. Water Down Under, Adelaide, Australia

    Google Scholar 

  • Yang YH, Watanabe M, Wang ZP, Sakura Y, Tang CY (2003) Prediction of changes in soil moisture associated with climatic changes and their implications for vegetation changes: WAVES model simulation on Taihang Mountain, China. Clim Change 57(1–2):163–183

    Article  Google Scholar 

  • Zhang L, Dawes W (1998) WAVES: an integrated energy and water balance model. Technical Report No. 31/98, CSIRO Land and Water, Canberra, Australia

  • Zhang L, Dawes WR, Hatton TJ (1996) Modelling hydrologic processes using a biophysically based model–application of WAVES to FIFE and HAPEX-MOBILHY. J Hydrol 185(1–4):147–169

    Article  Google Scholar 

  • Zhang L, Dawes WR, Hatton TJ, Hume IH, O’Connell MG, Mitchell DC, Milthorp PL, Yee M (1999) Estimating episodic recharge under different crop/pasture rotations in the Mallee region. Part 2. Recharge control by agronomic practices. Agric Water Manage 42(2):237–249

    Article  Google Scholar 

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Acknowledgements

This paper is based upon work conducted as a small portion of the Murray-Darling Basin (MDB) Sustainable Yield (MDBSY) Project (http://www.csiro.au/partnerships/MDBSY.html) funded by the National Water Commission.

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Correspondence to Russell S. Crosbie.

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Crosbie, R.S., McCallum, J.L., Walker, G.R. et al. Modelling climate-change impacts on groundwater recharge in the Murray-Darling Basin, Australia. Hydrogeol J 18, 1639–1656 (2010). https://doi.org/10.1007/s10040-010-0625-x

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