A computer simulation model to analyse risks of soil erosion to long-term crop production is described. The model, called PERFECT, simulates interactions between soil type, climate, fallow management strategy and crop sequence. It contains six main modules; data input, water balance, crop growth, crop residue, erosion and model output. Modules are arranged in a framework that allows alternative modules to be used as required for the potential range of applications. The model contains dynamic crop growth models for wheat, sorghum and sunflower. Validation of PERFECT against small catchment and contour bay data collected throughout Queensland showed that PERFECT explained up to 84% of the variation in total available soil water, 89% of the variation in daily runoff, and up to 75% of the variation in grain yield. Average annual soil erosion was accurately predicted but daily erosion totals were less accurate due to the exclusion of rainfall intensity in erosion prediction. Variability in climate dominates agricultural production in the subtropical region of Australia. The validated model can be coupled with long-term climate and soils databases to simulate probabilities of production and erosion risks due to climatic variability. It provides a method to determine the impact of soil erosion on long-term productivity.

Dryland salinity is recognised as a major environmental concern on the Liverpool Plains in north-eastern New South Wales. Previous hydrogeological and dryland salinity studies have highlighted the importance of adopting appropriate farming systems to reduce recharge into shallow aquifers. In this study, we applied the cropping systems model PERFECT to investigate the effects of climate, soil, and land use on recharge. Model inputs were derived from a range of sources including historical weather data, soil survey data, and information from landholder surveys. We investigated 47 different soils identified in a published soil survey covering approximately 280 000 ha of the Liverpool Plains. This study demonstrated a significant variation in soil physical properties and estimated recharge within soil types and illustrates the dangers of generalising soils into broad groupings. For example, under a wheat-sorghum rotation, predicted average annual recharge for soils classified as black earths ranged from 28 to 80 mm. Similar variability of predicted drainage is evident within other Great Soil Groups. The results reveal that response cropping alone will not significantly reduce recharge for all soils. Considering one black earth soil, average annual recharge is predicted to be 48 mm for a wheat-sorghum rotation, 22 mm for a response cropping rotation, and 8 mm for a lucerne{response cropping rotation. Therefore, including lucerne within a response cropping system is of benfit in reducing recharge. For all soil types, least recharge is predicted for permanent pasture but this land use is not an attractive option to farmers given the diversity of farming systems in the region. However, for some soils, continuous pasture is appropriate because excessive recharge is estimated for all cropping systems. This study has extended previous modelling work in the region as it considered a much wider range of soil types and cropping systems than previously investigated. Such a modelling approach permits the quantification of the effects of climate, soil type, and land use on recharge below the root-zone.

Techniques to simulate effects of surface cover and tillage on runoff and erosion are described. Data for 15 soil management treatments on an Alfisol in the semi-arid tropics, India, were used to modify existing procedures of runoff prediction using USDA runoff curve numbers. A relationship between surface cover and curve number was developed to account for the effects of surface cover on runoff. Impact of shallow or deep tillage was predicted using functions that relate curve number to cumulative rainfall since tillage. The derived relationships were applied to adjust curve number due to the effects of cover and tillage on a daily basis and were incorporated into the cropping systems model called PERFECT-IND. Results of model validation showed that PERFECT-IND explained between 71 and 91% of the variation in daily runoff volumes. The model also provided accurate predictions of average annual runoff ranging from 33 to 217 mm for the 15 soil management treatments. Runoff was reduced to a much greater extent by surface cover compared with surface roughness. Surface cover reduced runoff curve number by a maximum of 35 units. The maximum reduction in curve number due to surface roughness was 5 units for shallow tillage and 10 units for deep tillage. Erosion predictions were acceptable but the lack of erosion data for all years in the experimental data limits the confidence in model output. Model calibration and validation have provided a set of parameters that can be coupled with historical climate records to provide a long-term perspective of the effects of soil management on runoff and erosion.

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This paper provides experimental data on the effect of tree clearing, introduction of perennial Stylosanthes based pastures, and the use of native grasses on the water balance of a red earth soil in the Upper Burdekin Catchment near Charters Towers. The water balance simulation models SWIM and PERFECT are used to extend the results and estimate deep drainage for this and other soils in this tropical environment. The analysis illustrates that the soil/climate interaction in the wet/dry tropics has a similarity with the winter-dominant rainfall zone where vegetation change can substantially increase deep drainage beyond the root-zone. Salt distribution in the soil/landscapes of the Upper Burdekin suggests that there is a salinity hazard, should a significant shift in the water balance occur as a result of tree clearing. Therefore, in the Upper Burdekin Catchment of North Queensland, indiscriminate tree clearing is a hazardous form of land management and should only proceed after the risks of dryland salinity have been evaluated and shown to be negligible.