
TY  - JOUR
A1  - Pracilio, G. 
A1  - Asseng, S. 
A1  - Cook, S. E. 
A1  - Hodgson, G. 
A1  - Wong, M. T. F. 
A1  - Adams, M. L. 
A1  - Hatton, T. J. 
T1  - Estimating spatially variable deep drainage across a central-eastern wheatbelt catchment, Western Australia
JF  - Australian Journal of Agricultural Research
JO  - Aust. J.  Agric. Res.
Y1  - 2003
VL  - 54
IS  - 8
SP  - 789
EP  - 802
KW  - APSIM, dryland salinity, Expector, mapping, leakage, recharge.
UR  - https://doi.org/10.1071/AR02084 
N2  - The management of excess water (recharge or deep drainage) is one of many important issues required to address dryland salinity. To provide information on site-specific risk of deep drainage at a landholder scale, spatially variable deep drainage beneath an annual crop was estimated for a catchment of approximately 25 000 ha. The method coupled the results from one-dimensional crop simulation modelling (Agricultural Production Systems Simulator) with probabilistic soil mapping (Expector). Annual deep drainage over the catchment averaged 18 mm, representing 5% of rainfall. The annual deep drainage for the most probable soil types averaged 25 mm for acid loamy sand, 19 mm for yellow duplex, 14 mm for loamy sand, and 12 mm for red duplex. Groundwater modelling (Flowtube) highlighted that the groundwater table below the flat valley is not likely to be lowered with the introduction of perennial vegetation upslope. However, scenario spatial modelling indicated that replacing vegetation in areas of the most drainage-prone soil types, acid loamy sand (22% of catchment) and acid loamy sand plus yellow duplex (together at 48% of catchment area), was predicted to reduce annual average deep drainage by 38 and 60%, respectively. Mapping deep drainage by this method is of value to land managers who want to reduce deep drainage by locating priority areas for the establishment of perennial vegetation. 
ER  -

