Register      Login
Animal Production Science Animal Production Science Society
Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

Predicted salinity impacts from land use change: comparison between rapid assessment approaches and a detailed modelling framework

C. Beverly A E , M. Bari B , B. Christy A , M. Hocking C and K. Smettem D
+ Author Affiliations
- Author Affiliations

A CRC for Plant-Based Management of Dryland Salinity, Rutherglen Research Institute, Department of Primary Industries, Chiltern Valley Road, Rutherglen, Vic. 3685, Australia.

B Water and Rivers Commission, Hyatt Centre, 3 Plain Street, East Perth, WA 6004, Australia.

C Hocking et al. Pty Ltd, PO Box 1085, Bendigo, Vic. 3552, Australia.

D Centre for Water Research, The University of Western Australia, Nedlands, WA 6009, Australia.

E Corresponding author. Email: Craig.Beverly@dpi.vic.gov.au

Australian Journal of Experimental Agriculture 45(11) 1453-1469 https://doi.org/10.1071/EA04192
Submitted: 8 September 2004  Accepted: 28 October 2005   Published: 16 December 2005

Abstract

This paper illustrates the hydrological limitations and underlying assumptions of 4 catchment modelling approaches representing different generic classes of predictive models. These models are commonly used to estimate the impacts of land use and management change on stream flow and salinity regimes within a target region. Three approaches are based on a simple conceptual framework that assumes a single layer groundwater aquifer and requires minimal information and calibration (Zhang-BC2C, CAT1D-BC2C and LUCICAT), whereas the fourth approach (CAT3D) adopts a fully distributed highly parameterised catchment model capable of simulating complex multi-layered groundwater aquifer systems. All models were applied to the Gardiner subcatchment within the Goulburn–Broken region of Victoria, identified as a National Action Plan for Salinity priority subcatchment. Current condition simulation results were compared with observed stream flow and groundwater hydrograph data. Results show that the simple frameworks predicted whole-of-catchment mean annual salt and water yield with minimum parameterisation. The fully distributed framework produced similar catchment-scale responses to the simple approaches, but required more intensive input data and solution times. However, the fully distributed framework provides finer temporal and spatial scale information within the catchment. The more detailed models (such as CAT3D) also have the predictive capacity to assess the within-catchment dynamics at a range of scales and account for landscape position and complex surface/groundwater interactions.

This paper concludes that the simple frameworks are useful for judging the whole-of-catchment impacts of broad-scale land use change on catchment water yields and salinity and therefore provide valuable tools for community engagement. However, the within-catchment dynamics are not well represented and particular care must be taken when applying such models in those catchments where the interaction between groundwater and surface features result in saturated areas that are disconnected from streams. Adoption of a distributed groundwater modelling environment similar to that of CAT3D provides higher spatial resolution relative to the lumped broad scale groundwater glow system (GFS) based parameterisation adopted by the BC2C rapid assessment approaches. The developers of the BC2C model acknowledge that such models are currently limited to upland local and intermediate groundwater flow systems. Given that the majority of land salinisation is located in regions dominated by intermediate and regional groundwater systems, this tool is not well suited to adequately model regional processes. In contrast, the CAT3D distributed groundwater models are likely to be applicable across a range of scales and provide the capacity to assess the trade offs between salinity recharge and discharge intervention strategies. We conclude that more complex models (e.g. CAT3D) are needed to identify at the land management scale (paddock/farm) cost effective land use and land management changes within the catchment to improve catchment health.

Additional keywords: catchment modelling, groundwater, land management, salinity, water balance.


Acknowledgments

We thank the CRC for Plant-Based Management of Dryland Salinity for providing funding and the Department of Sustainability and Environment for support through the National Action Plan for Salinity and Water Quality initiative. We also thank Glenn Walker and Mat Gilfedder for assistance in the application of the BC2C models, Terry McLean for technical support, Charlie Showers for GIS support and Neil McKenzie for providing underlying soil characterisation parameters. Thanks also to Naomi Watson from DPI Benalla and Xiang Cheng from DPI Bendigo for the development and provision of all the BC2C spatial data layers.


References


Bari MA, Smettem KR (2004) Modelling monthly runoff generation processes following land use changes: groundwater–surface water interactions. Hydrology and Earth Systems Sciences 8, 903–922. [verified 16 November 2005]

Boughton WC (1968) A mathematical catchment model for estimating runoff. Journal of Hydrology, New Zealand 7, 75–100. [verified 16 November 2005]

Day KA, McKeon GM, Carter JO (1997) Evaluating the risks of pasture and land degradation in native pastures in Queensland. Final Project Report, RIRDC Project DAQ124A.

Dawes WR, Gilfedder M, Walker GR, Evans WR (2004) Biophysical modelling of catchment-scale surface and groundwater response to land use change. Journal of Mathematics and Computers in Simulation 64, 3–12.
Crossref | GoogleScholarGoogle Scholar | open url image1

Diersch HG (1998) ‘FEFLOW: finite element subsurface FLOW system.’ (WAST Institute for Water Resources Planning and Systems Research Ltd: Berlin)

Dowling T, Dawes WR, Evans WR, Dyson P, Walker G (2004) Prioritising upland catchments in the Murray-Darling Basin with respect to salinity benefits from afforestation. CSIRO Land and Water Technical Report 15/04, CSIRO Land and Water, Canberra.

DPIE (1997) ‘Plantations for Australia: the 2020 vision.’ (Department of Primary Industries and Energy: Canberra)

Evans R, Gilfedder M, Austin J (2004) Application of the biophysical capacity to change (BC2C) model to the Little River (NSW). CSIRO Land and Water Technical Report No 16/04, March 2004.

Fetter CW (1994) ‘Applied hydrogeology.’ 4th edn. (Prentice Hall: New Jersey)

Freer M, Moore AD, Donnelly JR (1997) GRAZPLAN: decision support systems for Australian grazing enterprises. II. The animal biology model for feed intake, production and reproduction and the GrazFeed DSS. Agricultural Systems 54, 77–126.
Crossref | GoogleScholarGoogle Scholar | open url image1

Gallant JC, Dowling TI (2003) A multi-resolution index of valley bottom flatness for mapping depositional areas. Water Resources Research 39, 1347.
Crossref | GoogleScholarGoogle Scholar | open url image1

Hammer GL, Goyne PJ, Woodruff DR (1982) Phenology of sunflower cultivars. III Models for prediction in field environments. Australian Journal of Agricultural Research 33, 263–274.
Crossref | GoogleScholarGoogle Scholar | open url image1

Johnson IR, Lodge GM, White RE (2003) The sustainable grazing systems pasture model: description, philosophy and application to the SGS national experiment. Australian Journal of Experimental Agriculture 43, 711–728. open url image1

Jones CA, Kiniry JR (1986) ‘CERES-MAIZE: a simulation model of maize growth and development.’ (A and M University Press: Texas)

Jones R, Dowling P, Michalk D (2002) ‘The economics of sustainability and perennial pasture grazing systems.’ (NSW Agriculture: Orange)

Holmes JW, Sinclair JA (1986) Streamflow from some afforested catchments in Victoria. In ‘Proceedings of hydrology and water resources symposium’. pp. 214–218. (The Institution of Engineers, Australia, Griffith University: Brisbane)

Landsberg JJ, Waring RH (1997) A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecology and Management 95, 209–228.
Crossref | GoogleScholarGoogle Scholar | open url image1

Littleboy M, Silburn DM, Freebairn DM, Woodruff DR, Hammer GL, Leslie JK (1992) Impact of soil erosion on production in cropping systems. I Development and validation of a simulation model. Australian Journal of Soil Research 30, 757–774.
Crossref | GoogleScholarGoogle Scholar | open url image1

McDonald MC, Harbaugh AW (1988) ‘MODFLOW, a modular three-dimensional finite difference ground-water flow model.’ (US Geological Survey: Washington DC)

McCown RL, Hammer GL, Hargreaves JNG, Holzworth DP, Freebairn DM (1996) APSIM: a novel software system for model development, model testing and simulation in agricultural systems research. Agricultural Systems 50, 255–271.
Crossref | GoogleScholarGoogle Scholar | open url image1

McKenzie N (2001) LandMark Task 3b: integrating farm system modelling with catchment scale analysis, CSIRO Land and Water, LandMark, Task 3b Summary, Canberra.

McKenzie NJ, Jacquier DW, Ashton LJ, Cresswell HP (2000) Estimation of soil properties using the atlas of Australian soil. CSIRO Land and Water Technical Report 11/00.

Moore AD, Donnelly JR, Freer M (1997) GRAZPLAN: decision support systems for Australian grazing enterprises. III. Pasture growth and soil moisture submodels, and the GrassGro DSS Agricultural Systems 55, 535–582.
Crossref | GoogleScholarGoogle Scholar | open url image1

Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2001) ‘Soil water assessment tool theoretical documentation, Version 2000.’ (Grassland, Soil and Water Research Laboratory: Temple)

Paydar Z, Gallant JC (2003) Applying a spatial modeling framework to assess land use effects on catchment hydrology. In ‘Proceeding of the international congress on modeling and simulation. Vol. 2. Townsville, Qld, Australia. 14–17 July 2003’. (Ed. DA Post) pp. 491–495. (Modelling and Simulation Society of Australia and New Zealand Inc.: Perth)

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. Australian Journal of Soil Research 40, 397–417. open url image1

PIRVIC (2005) ‘Technical manual catchment analysis tool. Version 14.’ (Department of Primary Industries: Rutherglen, Vic.)

Rassam D, Littleboy M (2003) Identifying the lateral component of drainage flux in hill slopes. In ‘Proceedings of the international congress on modelling and simulation, Townsville, Australia, July 2003. Vol. 1’. (Ed. DA Post) pp. 183–188. (Modelling and Simulation Society of Australia and New Zealand Inc.: Perth)

Ritchie JT, Otter S (1985) Description and performance of CERES-Wheat: a user-oriented wheat yield model. In ‘ARS wheat yield project. ARS-38’. (Ed. WO Willis) pp. 159–175. (USDA–ARS)

Sadras V, Baldock J, Roget D, Rodriguez D (2003) Measuring and modelling yield and water budget components of wheat crops in coarse-textured soils with chemical constraints Field Crops Research 84, 241–260.
Crossref | GoogleScholarGoogle Scholar | open url image1

Simunek J, Sejna M, van Genuchten MTh (1999) ‘HYDRUS-2D/MESHGEN-2D, simulating water flow and solute transport in two-dimensional variably saturated media, IGWMC 53c.’ (Colorado School of Mines: Golden, CO)

Thornley JHM (1972) A balanced quantitative model for root:shoot ratios in vegetative plants. Annals of Botany 36, 431–441. open url image1

Tuteja NK, Beale GTH, Dawes W, Vaze J, Murphy B , et al. (2003) Predicting the effects of land use change on water and salt balance — a case study for a catchment affected by dryland salinity in NSW, Australia. Journal of Hydrology 283, 67–90.
Crossref | GoogleScholarGoogle Scholar | open url image1

van Dijk AIJM, Cheng X, Austin J, Gilfedder M, Hairsine P (2004) Predicting stream flow and salinity changes after reafforestation in the south-west Goulburn. A regional BC2C model application to develop commercial environmental forestry. CSIRO Land and Water Client Report, Commercial Environmental Forestry report CLW/03.

Vertessy RA, Bessard Y (1999) Anticipation of the negative hydrological effects of plantation expansion: results from GIS-based analysis on the Murrumbidgee Basin. In ‘Forest management for the protection of water quality and quantity. Proceedings of the 2nd erosion in forests meeting, Warburton, 4–6 May 1999. Report 99/6’. (Eds J Croke, P Lane ) pp. 69–74. (CRC for Catchment Hydrology: Canberra)

Williams JR, Dyke PT, Jones CA (1983) EPIC: a model for assessing the effects of erosion on soil productivity. In ‘Analysis of ecological systems: state-of-the-art in ecological modelling’. (Eds WK Laurenroth, GV Skogerboe, M Flug) pp. 553–572. (Elsevier: Amsterdam)

Zhang L, Dowling T, Hocking M, Morris J, Adams G, Hickel K, Best A, Vertessy R (2003) Predicting the effects of large-scale afforestation on annual flow regime and water allocation: an example for the Goulburn–Broken catchments. CRC for Catchment Hydrology Technical Report No. 03/5. CRC for Catchment Hydrology, Canberra.

Zhang L, Dowling T, Hocking M, Morris J, Adams G, Hickel K, Best A, Vertessy R (2002) Predicting the effects of blue gum plantations on water yield in the Goulburn–Broken catchments. CRC for Catchment Hydrology Report No. 02/12, Monash University, Bundoora.

Zhang L, Dawes WR, Walker GR (2001) The response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resources Research 37, 701–708.
Crossref | GoogleScholarGoogle Scholar | open url image1

Zhang L, Dawes WR, Walker GR (1999) Predicting the effect of vegetation changes on catchment average water balance. CRC for Catchment Hydrology Report No. 99/12, Monash University, Bundoora.