Using Hydrology to Target Salinity

Project Home | Impacts of plantation forestry on mean annual water yield | Impacts of plantation forestry on the flow regime | Groundwater flow systems | Impacts of land use changes in non-irrigated upland catchments on stream salinity and salt loads

Impacts of Plantation Forestry on Mean Annual Water Yield from Non-Irrigated Upland Catchments

Background

For many years it has been known that forested catchments transpire more and yield less water than non-forested catchments. The processes leading to higher transpiration have been well established, with a large number of paired catchment studies. However the relationship between the number of trees and water yield has not previously been used to predict mean annual water yield for a catchment.

The Holmes-Sinclair empirical relationship, based on data from 106 Victorian catchments, was a starting point. Previous research conducted in the Liverpool Plains suggested that this relationship was robust. External factors such as the Forestry 2020 vision and the Water Property Rights debate imply that there is a need to go beyond qualitative relationship to robust predictors that can be incorporated into regional planning tools.

Objectives

• Develop a robust and scientifically defendable mean annual predictor, relating mean annual rainfall and degree of forest cover to water yield
• Implement model in a spatial context that allows regional and industry planning
• Determine the sensitivity of the model to secondary factors such as rainfall seasonality, catchment water storage, and physical catchment properties
• Investigate the time lag between land-use change and impact on water yield.

Findings

• A robust model was developed and published in international peer-reviewed journals. Zhang Curves estimate the effects of land-use change on mean annual water yield, based on over 250 catchment experiments worldwide.
• GIS-based modelling of the Goulburn-Broken Catchment demonstrated the capability of the model for regional planning.
• The inclusion of second order effects, e.g. rainfall seasonality and mean catchment water storage, did slightly improve the predictor (although there is a diminishing return on the improvements when compared to increased model complexity).
• There are pronounced delays between planting trees and the full effect on catchment yield of between 10 and 20 years (determined using paired catchment experiments).

Our model, which predicts the impacts of land-use change on mean annual water yield, was based on over 250 catchment experiments worldwide

Publications

Potter NJ , Zhang L, Milly PCD, McMahon TA, Jakeman AJ (2005) The effects of rainfall seasonality and soil moisture capacity on mean annual water balance for Australian catchments. Water Resources Research, 41, W06007, doi:10. 1029/2004WR003697.

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.

Zhang L, Walker GR, Dawes WR. (2003) Catchment Scale Water Balance and its Implications for Deep Drainage Control, paper presented at the GRDC water balance workshop (invited), February 2003.

Zhang L, Hickel K, Dawes WR, Chiew F, Western A. (2004) A rational function approach for estimating mean annual evapotranspiration. Water Resources Research, 40, W02502, doi:10.1029/2003WR002710.

Permission to publish CRC-CH Technical Reports granted by David Perry for the CRC-CH