A protocol to build soil descriptions for APSIM simulations.

Soil processes have a major impact on agroecosystems, controlling water and nutrient cycling, regulating plant growth and losses to the wider environment. Process-based agroecosystem simulation models generally encompass detailed descriptions of the soil, including a wide number of parameters that can be daunting to users with a limited soil science background. In this work we review and present an abridged description of the models used to simulate soil processes in the APSIM (Agricultural Production Systems sIMulator) framework. Such a resource is needed because this information is currently spread over multiple publications and some elements have become outdated. We list and briefly describe the parameters, and establish a protocol with guidelines, for building a soil description for APSIM. This protocol will promote consistency, enhancing the quality of the science done employing APSIM, and provide an easier pathway for new users. This compilation should also be of relevance to users of other models that require detailed soil information.•This paper presents a brief description of the models for simulating soil processes in the APSIM model.•The method stablishes guidelines to define the parameters for building a soil description for APSIM.

Estimating economic and environmental trade-offs of managing nitrogen in Australian sugarcane systems taking agronomic risk into account.

Use of chemical agricultural inputs such as nitrogen fertilisers (N) in agricultural production can cause diffuse source pollution thereby degrading the health of coastal and marine ecosystems in coastal river catchments. Previous reviewed economic assessments of N management in agricultural production seldom consider broader environmental impacts and uncertain climatic and economic conditions. This paper presents an economic risk framework for assessing economic and environmental trade-offs of N management strategies taking into account variable climatic and economic conditions. The framework is underpinned by a modelling platform that integrates Agricultural Production System sIMulation modelling (APSIM), probability theory, Monte Carlo simulation, and financial risk analysis techniques. We applied the framework to a case study in Tully, a coastal catchment in north-eastern Australia with a well-documented N pollution problem. Our results show that switching from managing N to maximise private net returns to maximising social net returns could reduce expected private net returns by $99 ha-1, but yield additional environmental benefits equal to $191 ha-1. Further, switching from managing N to maximise private returns in years with the highest profit potential (hereafter, good years) to maximising mean social net returns could reduce expected private profits in good years by $277 ha-1, but yield additional environmental benefits equal to $287 ha-1. We contend that it is essential to incorporate farmer risk behaviour and environmental impacts in analyses that inform policies aimed at enhancing adoption of management activities for mitigating deterioration of the health of coastal and marine ecosystems due to diffuse source pollution from agricultural production.

Prioritizing Crop Management to Increase Nitrogen Use Efficiency in Australian Sugarcane Crops.

Sugarcane production relies on the application of large amounts of nitrogen (N) fertilizer. However, application of N in excess of crop needs can lead to loss of N to the environment, which can negatively impact ecosystems. This is of particular concern in Australia where the majority of sugarcane is grown within catchments that drain directly into the World Heritage listed Great Barrier Reef Marine Park. Multiple factors that impact crop yield and N inputs of sugarcane production systems can affect N use efficiency (NUE), yet the efficacy many of these factors have not been examined in detail. We undertook an extensive simulation analysis of NUE in Australian sugarcane production systems to investigate (1) the impacts of climate on factors determining NUE, (2) the range and drivers of NUE, and (3) regional variation in sugarcane N requirements. We found that the interactions between climate, soils, and management produced a wide range of simulated NUE, ranging from ∼0.3 Mg cane (kg N)-1, where yields were low (i.e., <50 Mg ha-1) and N inputs were high, to >5 Mg cane (kg N)-1 in plant crops where yields were high and N inputs low. Of the management practices simulated (N fertilizer rate, timing, and splitting; fallow management; tillage intensity; and in-field traffic management), the only practice that significantly influenced NUE in ratoon crops was N fertilizer application rate. N rate also influenced NUE in plant crops together with the management of the preceding fallow. In addition, there is regional variation in N fertilizer requirement that could make N fertilizer recommendations more specific. While our results show that complex interrelationships exist between climate, crop growth, N fertilizer rates and N losses to the environment, they highlight the priority that should be placed on optimizing N application rate and fallow management to improve NUE in Australian sugarcane production systems. New initiatives in seasonal climate forecasting, decisions support systems and enhanced efficiency fertilizers have potential for making N fertilizer management more site specific, an action that should facilitate increased NUE.

High-frequency nutrient monitoring to infer seasonal patterns in catchment source availability, mobilisation and delivery.

To explore the value of high-frequency monitoring to characterise and explain riverine nutrient concentration dynamics, total phosphorus (TP), reactive phosphorus (RP), ammonium (NH4-N) and nitrate (NO3-N) concentrations were measured hourly over a 2-year period in the Duck River, in north-western Tasmania, Australia, draining a 369-km(2) mixed land use catchment area. River discharge was observed at the same location and frequency, spanning a wide range of hydrological conditions. Nutrient concentrations changed rapidly and were higher than previously observed. Maximum nutrient concentrations were 2,577 µg L(-1) TP, 1,572 µg L(-1) RP, 972 µg L(-1) NH4-N and 1,983 µg L(-1) NO3-N, respectively. Different nutrient response patterns were evident at seasonal, individual event and diurnal time scales-patterns that had gone largely undetected in previous less frequent water quality sampling. Interpretation of these patterns in terms of nutrient source availability, mobilisation and delivery to the stream allowed the development of a conceptual model of catchment nutrient dynamics. Functional stages of nutrient release were identified for the Duck River catchment and were supported by a cluster analysis which confirmed the similarities and differences in nutrient responses caused by the sequence of hydrologic events: (1) a build-up of nutrients during periods with low hydrologic activity, (2) flushing of readily available nutrient sources at the onset of the high flow period, followed by (3) a switch from transport to supply limitation, (4) the accessibility of new nutrient sources with increasing catchment wetness and hydrologic connectivity and (5) high nutrient spikes occurring when new sources become available that are easily mobilised with quickly re-established hydrologic connectivity. Diurnal variations that could be influenced by riverine processes and/or localised point sources were also identified as part of stage (1) and during late recession of some of the winter high flow events. Illustrated by examples from the Duck River study, we demonstrate that the use of high-frequency monitoring to identify and characterise functional stages of catchment nutrient release is a constructive approach for informing and supporting catchment management and future nutrient monitoring strategies.