Environmental Earth Sciences

, Volume 74, Issue 7, pp 6047–6063 | Cite as

Assessing the impact of drought and forestry on streamflows in south-eastern Australia using a physically based hydrological model

  • Stuart C. BrownEmail author
  • Vincent L. Versace
  • Rebecca E. Lester
  • M. Todd Walter
Original Article


An increase in plantation forestry has been linked to a reduction in streamflows in some catchments. Quantifying the relative contribution of this land-use change on streamflows can be complex when those changes occur during weather extremes such as drought. In this study, the Soil and Water Assessment Tool (SWAT) model was applied to two sub-catchments in south-eastern Australia which have seen the introduction and establishment of plantation land use in the past 15 years, coinciding with severe drought (1997–2009). The models were both manually and auto-calibrated and produced very good fits to observed streamflow data during both calibration (1980–1991) and validation (1992–2009) periods. Sensitivity analyses indicated that the models were most sensitive to soil and groundwater parameterisation. Analysis of drought conditions on streamflows showed significant declines from long-term average streamflows, while assessment of baseflow contributions by the models indicated a mix of over- and underestimation depending on catchment and season. The modelled introduction of plantation forestry did not significantly change streamflows for a scenario which did not include the land-use change, suggesting that the modelled land-use change in the catchments was not sufficiently extensive to have an impact on streamflows despite simulating actual rates of change. The SWAT models developed by this study will be invaluable as a basis for future use in regional climate-change studies and for the assessment of land management and land-use change impact on streamflows.


Hydrological modelling Streamflow Australia Land-use change Eucalyptus 



The authors acknowledge the Cornell University Soil and Water Laboratory for hosting the lead author in 2012 and, in particular, Dr. Daniel Fuka for extensive advice on model calibration. The authors also wish to thank the Glenelg-Hopkins Catchment Management Authority for providing funding to support this project, Dr. Daniel Ierodiaconou for supplying land-cover maps used herein and the two anonymous reviewers for their contributions to the manuscript.


  1. Abbaspour KC (2011) SWAT-CUP 4: SWAT calibration and uncertainty programs: a user manual. Swiss Federal Institute of Aquatic Science and Technology, Eawag, DuebendorfGoogle Scholar
  2. Abbaspour KC, Yang J, Maximov I, Siber R, Bogner K, Mieleitner J, Zobrist J, Srinivasan R (2007) Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. J Hydrol 333:413–430CrossRefGoogle Scholar
  3. Arnold JG, Allen PM (1999) Automated methods for estimating baseflow and ground water recharge from streamflow records. J Am Water Resour Assoc 35:411–424CrossRefGoogle Scholar
  4. Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment part I: model development. J Am Water Resour Assoc 34:73–89CrossRefGoogle Scholar
  5. Arthington AH, Pusey BJ (2003) Flow restoration and protection in Australian rivers. River Res Appl 19:377–395CrossRefGoogle Scholar
  6. Australian Greenhouse Office (2000) Land clearing: a social history, technical report 4. National Carbon Accounting System. Australian Greenhouse Office, CanberraGoogle Scholar
  7. Benyon RG, Doody TM, Theiveyanathan S, Vijay K (2008) Plantation forest water use in southwest Victoria, technical report no. 164. CSIRO, Mount GambierGoogle Scholar
  8. Brath A, Montanari A, Moretti G (2006) Assessing the effect on flood frequency of land use change via hydrological simulation (with uncertainty). J Hydrol 324:141–153CrossRefGoogle Scholar
  9. Breuer L, Eckhardt K, Frede HG (2003) Plant parameter values for models in temperate climates. Ecol Model 169:237–293CrossRefGoogle Scholar
  10. Brown SC, Versace VL, Laurenson L, Ierodiaconou D, Fawcett J, Salzman S (2012) Assessment of spatiotemporal varying relationships between rainfall, land cover and surface water area using geographically weighted regression. Environ Model Assess 17:241–254CrossRefGoogle Scholar
  11. Brown SC, Lester RE, Versace VL, Fawcett J, Laurenson L (2014) Hydrologic landscape regionalisation using deductive classification and random forests. PLoS ONE 9:e112856CrossRefGoogle Scholar
  12. Bureau of Meteorology (2012) Bureau of Meteorology gridded climate data. Accessed Mar 2012
  13. Chase TN, Pielke RA, Kittel TGF, Nemani RR, Running SW (2000) Simulated impacts of historical land cover changes on global climate in northern winter. Clim Dyn 16:93–105CrossRefGoogle Scholar
  14. Costa MH, Botta A, Cardille JA (2003) Effects of large-scale changes in land cover on the discharge of the Tocantins River, Southeastern Amazonia. J Hydrol 283:206–217CrossRefGoogle Scholar
  15. CSIRO (2012) Climate and water availability in south-eastern Australia: a synthesis of findings from phase 2 of the South eastern Australian climate initiative (SEACI). CSIRO, AdelaideGoogle Scholar
  16. Department of Sustainability and Environment (2008) Climate change in the Glenelg Hopkins region. Department of Sustainability and Environment, MelbourneGoogle Scholar
  17. Fan J, Tian F, Yang Y, Han S, Qiu G (2010) Quantifying the magnitude of the impact of climate change and human activity on runoff decline in Mian River Basin, China. Water Sci Technol 62:783–791CrossRefGoogle Scholar
  18. FAO (2007) Digital soil map of the world, version 3.6. FAO, RomeGoogle Scholar
  19. Fohrer N, Haverkamp S, Eckhardt K, Frede HG (2001) Hydrologic response to land use changes on the catchment scale. Phys Chem Earth B 26:577–582CrossRefGoogle Scholar
  20. Gassman PW, Reyes MR, Green CH, Arnold JG (2007) The soil and water assessment tool: historical development, applications, and future research directions. Trans ASABE 50:1211–1250CrossRefGoogle Scholar
  21. Geoscience Australia (2011) 3 second SRTM derived hydrological digital elevation model (DEM-S) version 1.0, ANZLIC unique identifier: ANZCW0703014217. Geoscience Australia, CanberraGoogle Scholar
  22. Geza M, McCray JE (2008) Effects of soil data resolution on SWAT model stream flow and water quality predictions. J Environ Manag 88:393–406CrossRefGoogle Scholar
  23. Girvetz EH, Maurer EP, Duffy P, Ruesch A, Thrasher B, Zganjar C (2013) Making climate data relevant to decision making: the important details of spatial and temporal downscaling. The World BankGoogle Scholar
  24. Graetz R, Wilson M, Campbell S (1995) Landcover disturbance over the Australian continent: a contemporary assessment. Biodiversity Series Paper, vol 7. Department of the Environment, Sport and Territories, CanberraGoogle Scholar
  25. Ierodiaconou D, Laurenson L, Leblanc M, Stagnitti F, Duff G, Salzmann S, Versace VL (2005) The consequences of land use change on nutrient exports: a regional scale assessment in south-west Victoria, Australia. J Environ Manag 74:305–316CrossRefGoogle Scholar
  26. Ladson A (2011) Hydrology: an Australian introduction. Oxford University Press, South MelbourneGoogle Scholar
  27. Lahmer W, Pfützner B, Becker A (2001) Assessment of land use and climate change impacts on the mesoscale. Phys Chem Earth B 26:565–575CrossRefGoogle Scholar
  28. Lambin EF, Turner BL, Geist HJ, Agbola SB, Angelsen A, Bruce JW, Coomes OT, Dirzo R, Fischer G, Folke C, George PS, Homewood K, Imbernon J, Leemans R, Li X, Moran EF, Mortimore M, Ramakrishnan PS, Richards JF, Skånes H, Steffen W, Stone GD, Svedin U, Veldkamp TA, Vogel C, Xu J (2001) The causes of land-use and land-cover change: moving beyond the myths. Glob Environ Change 11:261–269CrossRefGoogle Scholar
  29. Li Z, Liu WZ, Zhang XC, Zheng FL (2009) Impacts of land use change and climate variability on hydrology in an agricultural catchment on the Loess Plateau of China. J Hydrol 377:35–42CrossRefGoogle Scholar
  30. McMahon TA, Finlayson BL (2003) Droughts and anti-droughts: the low flow hydrology of Australian rivers. Freshwat Biol 48:1147–1160CrossRefGoogle Scholar
  31. Moriasi D, Starks P (2010) Effects of the resolution of soil dataset and precipitation dataset on SWAT2005 streamflow calibration parameters and simulation accuracy. J Soil Water Conserv 65:63–78CrossRefGoogle Scholar
  32. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50:885–900CrossRefGoogle Scholar
  33. Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2011) Soil and Water Assessment Tool: theoretical documentation 2009 vol TR-406. Technical report no. 406 edn. Texas Water Resources Institute—Texas A&M University, College StationGoogle Scholar
  34. OECD (1996) Guidelines for aid agencies for improved conservation and sustainable use of tropical and sub-tropical wetlands. Organisation for Economic Cooperation and Development, ParisGoogle Scholar
  35. Peel MC, McMahon TA, Finlayson BL (2010) Vegetation impact on mean annual evapotranspiration at a global catchment scale. Water Resour Res 46:1–16Google Scholar
  36. R Core Team (2014) R: a language and environment for statistical computing, version 3.1.2. R Foundation for Statistical Computing, Vienna. Accessed Aug 2014
  37. Ramankutty N, Graumlich L, Achard F, Alves D, Chhabra A, DeFries RS, Foley JA, Geist H, Houghton RA, Goldewijk KK, Lambin EF, Millington A, Rasmussen K, Reid RS, Turner BLT II (2006) Global land-cover change: recent progress, remaining challenges. In: Lambin EF, Geist HJ (eds) Land-use and land-cover change: local processes and global impacts. Springer, New YorkGoogle Scholar
  38. Rodriguez Suarez JA, Diaz-Fierros F, Perez R, Soto B (2014) Assessing the influence of afforestation with Eucalyptus globulus on hydrological response from a small catchment in northwestern Spain using the HBV hydrological model. Hydrol Process 28:5561–5572CrossRefGoogle Scholar
  39. Romanowicz AA, Vanclooster M, Rounsevell M, La Junesse I (2005) Sensitivity of the SWAT model to the soil and land use data parametrisation: a case study in the Thyle catchment, Belgium. Ecol Model 187:27–39CrossRefGoogle Scholar
  40. Saha PP, Zeleke K, Hafeez M (2014) Streamflow modeling in a fluctuant climate using SWAT: Yass River catchment in south eastern Australia. Environ Earth Sci 71:5241–5254CrossRefGoogle Scholar
  41. Scott DF, Lesch W (1997) Streamflow responses to afforestation with Eucalyptus grandis and Pinus patula and to felling in the Mokobulaan experimental catchments, South Africa. J Hydrol 199:360–377CrossRefGoogle Scholar
  42. Sinclair-Knight-Merz (2008) Water and land use change study: stage 3. Water and land use change in the catchment of the Crawford River. Report to Glenelg Hopkins Catchment Management Authority and Water and Land Use Change Steering Committee. Sinclair-Knight-Merz, Project VW03647Google Scholar
  43. Smedema LK, Rycroft DW (1983) Land drainage: planning and design of agricultural drainage systems. Cornell University Press, IthacaGoogle Scholar
  44. Teng J, Chiew FHS, Vaze J, Marvanek S, Kirono DGC (2012) Estimation of climate change impact on mean annual runoff across continental Australia using Budyko and Fu equations and hydrological models. J Hydrometeorol 13:1094–1106CrossRefGoogle Scholar
  45. Tollan A (2002) Land-use change and floods: what do we need most, research or management? Water Sci Technol 45:183–190Google Scholar
  46. Versace VL, Ierodiaconou D, Stagnitti F, Hamilton AJ (2008a) Appraisal of random and systematic land cover transitions for regional water balance and revegetation strategies. Agric Ecosyst Environ 123:328–336CrossRefGoogle Scholar
  47. Versace VL, Ierodiaconou D, Stagnitti F, Hamilton AJ, Walter MT, Mitchell B, Boland AM (2008b) Regional-scale models for relating land cover to basin surface-water quality using remotely sensed data in a GIS. Environ Monit Assess 142:171–184CrossRefGoogle Scholar
  48. Watson BM (2006) A hydrologic model for the Woady Yaloak River catchment. PhD thesis, Deakin UniversityGoogle Scholar
  49. Xu CY, Singh VP (2004) Review on regional water resources assessment models under stationary and changing climate. Water Resour Manag 18:591–612CrossRefGoogle Scholar
  50. Yihdego Y, Webb JA (2011) Modeling of bore hydrographs to determine the impact of climate and land-use change in a temperate subhumid region of southeastern Australia. Hydrogeol J 19:877–887CrossRefGoogle Scholar
  51. Yihdego Y, Webb J (2013) An empirical water budget model as a tool to identify the impact of land-use change in stream flow in southeastern Australia. Water Resour Manag 27:4941–4958CrossRefGoogle Scholar
  52. Zambrano-Bigiarini M (2014a) hydroGOF: goodness-of-fit functions for comparison of simulated and observed hydrological time series. R package version 0.3-8. Accessed Aug 2014
  53. Zambrano-Bigiarini M (2014b) hydroTSM: time series management, analysis and interpolation for hydrological modelling. R package version 0.4-2-1. Accessed Aug 2014
  54. Zedler JB, Kercher S (2005) Wetland resources: status, trends, ecosystem services, and restorability. Annu Rev Environ Resour 30:39–74CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Stuart C. Brown
    • 1
    Email author
  • Vincent L. Versace
    • 2
    • 3
  • Rebecca E. Lester
    • 1
  • M. Todd Walter
    • 4
  1. 1.School of Life and Environmental SciencesDeakin UniversityWarrnamboolAustralia
  2. 2.Centre for Environmental Management, Faculty of Science and TechnologyFederation UniversityBallaratAustralia
  3. 3.Greater Green Triangle University Department of Rural HealthFlinders University and Deakin UniversityWarrnamboolAustralia
  4. 4.Department of Biological and Environmental EngineeringCornell UniversityIthacaUSA

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