Enli Wang

An overview of APSIM, a model designed for farming systems simulation

The Agricultural Production Systems Simulator (APSIM) is a modular modelling framework that has been developed by the Agricultural Production Systems Research Unit in Australia. APSIM was developed to simulate biophysical process in farming systems, in particular where there is interest in the economic and ecological outcomes of management practice in the face of climatic risk. The paper outlines APSIMs structure and provides details of the concepts behind the different plant, soil and management modules. These modules include a diverse range of crops, pastures and trees, soil processes including water balance, N and P transformations, soil pH, erosion and a full range of management controls. Reports of APSIM testing in a diverse range of systems and environments are summarised. An example of model performance in a long-term cropping systems trial is provided. APSIM has been used in a broad range of applications, including support for on-farm decision making, farming systems design for production or resource management objectives, assessment of the value of seasonal climate forecasting, analysis of supply chain issues in agribusiness activities, development of waste management guidelines, risk assessment for government policy making and as a guide to research and education activity. An extensive citation list for these model testing and application studies is provided.

Development of a generic crop model template in the cropping system model APSIM

The Agricultural Production Systems slMulator, APSIM, is a cropping system modelling environment that simulates the dynamics of soil-plant-management interactions within a single crop or a cropping system. Adaptation of previously developed crop models has resulted in multiple crop modules in APSIM, which have low scientific transparency and code efficiency. A generic crop model template (GCROP) has been developed to capture unifying physiological principles across crops (plant types) and to provide modular and efficient code for crop modelling. It comprises a standard crop interface to the APSIM engine, a generic crop model structure, a crop process library, and well-structured crop parameter files. The process library contains the major science underpinning the crop models and incorporates generic routines based on physiological principles for growth and development processes that are common across crops. It allows APSIM to simulate different crops using the same set of computer code. The generic model structure and parameter files provide an easy way to test, modify, exchange and compare modelling approaches at process level without necessitating changes in the code. The standard interface generalises the model inputs and outputs, and utilises a standard protocol to communicate with other APSIM modules through the APSIM engine. The crop template serves as a convenient means to test new insights and compare approaches to component modelling, while maintaining a focus on predictive capability. This paper describes and discusses the scientific basis, the design, implementation and future development of the crop template in APSIM. On this basis, we argue that the combination of good software engineering with sound crop science can enhance the rate of advance in crop modelling. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

Increased yield potential of wheat-maize cropping system in the North China Plain by climate change adaptation

In the North China Plain, the grain yield of irrigated wheat-maize cropping system has been steadily increasing in the past decades under a significant warming climate. This paper combined regional and field data with modeling to analyze the changes in the climate in the last 40 years, and to investigate the influence of changes in crop varieties and management options to crop yield. In particular, we examined the impact of a planned adaptation strategy to climate change -“Double-Delay” technology, i.e., delay both the sowing time of wheat and the harvesting time of maize, on both wheat and maize yield. The results show that improved crop varieties and management options not only compensated some negative impact of reduced crop growth period on crop yield due to the increase in temperature, they have contributed significantly to crop yield increase. The increase in temperature before over-wintering stage enabled late sowing of winter wheat and late harvesting of maize, leading to overall 4–6% increase in total grain yield of the wheat-maize system. Increased use of farming machines and minimum tillage technology also shortened the time for field preparation from harvest time of summer maize to sowing time of winter wheat, which facilitated the later harvest of summer maize.

Modelling the growth and water uptake function of plant root systems: a review

Crop models have been intensively used as a tool to analyse the performance of cropping systems under variable climate in terms of productivity, profitability, and off-site impact. The importance of modelling the function of plant roots in water and nutrient uptake from the soil is becoming increasing clear with the expanding application areas of crop models. This paper reviews the approaches and assumptions used in growth and uptake modelling of plant roots, and how the responses of plant root system to internal and external factors are captured in the widely used crop models. Most modelling approaches are based on one of the following assumptions: (i) that plant roots are uniformly distributed in homogenous soil layers and all roots have the same ability for uptake, or (ii) that plant root length is always sufficient for resource uptake in rooted soil layers. In structured soils, an overestimation of water uptake is likely to be expected. Further studies on root growth, distribution, and function in structured soils will require quantification of soil structures and root distribution patterns; and for non-uniformly distributed plant populations, spatial distribution of plant roots and non-uniform uptake need to be modelled. Root architecture modelling may help to address such issues. However, in order for the model to be useful at the field production level, simplified approaches that require easily measurable inputs need to be developed. Some examples are given. The oversimplification of root response to soil drying and hardness is likely to lead to overestimation of root growth and water uptake in dense soils. A soil strength factor needs to be incorporated so that the improved model can help evaluate the effect of subsoil compaction on production and resource use. Responses of root growth and uptake to soil salinity, boron toxicity, and extreme pH need to be further investigated if models are to be used for evaluation of crop performance in such environments. Effect of waterlogging also needs to be added for use of the model on heavy clay soils under irrigation or concentrated rainfall. There is an urgent need for joint efforts of crop physiologists, agronomists, breeders, and soil scientists to integrate interdisciplinary knowledge and to collect data that better describe the crop root system and its growth and uptake ability, to quantify plant process level responses, and for better soil quantification. Such knowledge and data are essential for improvement of model performance and successful applications.

Biofuels agriculture: landscape-scale trade-offs between fuel, economics, carbon, energy, food, and fiber

First‐generation biofuels are an existing, scalable form of renewable energy of the type urgently required to mitigate climate change. In this study, we assessed the potential benefits, costs, and trade‐offs associated with biofuels agriculture to inform bioenergy policy. We assessed different climate change and carbon subsidy scenarios in an 11.9 million ha (5.48 million ha arable) region in southern Australia. We modeled the spatial distribution of agricultural production, full life‐cycle net greenhouse gas (GHG) emissions and net energy, and economic profitability for both food agriculture (wheat, legumes, sheep rotation) and biofuels agriculture (wheat, canola rotation for ethanol/biodiesel production). The costs, benefits, and trade‐offs associated with biofuels agriculture varied geographically, with climate change, and with the level of carbon subsidy. Below we describe the results in general and provide (in parentheses) illustrative results under historical mean climate and a carbon subsidy of A

Impact of agricultural management practices on soil organic carbon: simulation of Australian wheat systems

20 t−1 CO2−e. Biofuels agriculture was more profitable over an extensive area (2.85 million ha) of the most productive arable land and produced large quantities of biofuels (1.7 GL yr−1). Biofuels agriculture substantially increased economic profit (145.8 million

Modeling biomass growth, N-uptake and phenological development of potato crop

A yr−1 or 30%), but had only a modest net GHG abatement (−2.57 million t CO2−e yr−1), and a negligible effect on net energy production (−0.11 PJ yr−1). However, food production was considerably reduced in terms of grain (−3.04 million t yr−1) and sheep meat (−1.89 million head yr−1). Wool fiber production was also substantially reduced (−23.19 kt yr−1). While biofuels agriculture can produce short‐term benefits, it also has costs, and the vulnerability of biofuels to climatic warming and drying renders it a myopic strategy. Nonetheless, in some areas the profitability of biofuels agriculture is robust to variation in climate and level of carbon subsidy and these areas may form part of a long‐term diversified mix of land‐use solutions to climate change if trade‐offs can be managed.

Decadal Trends in Evaporation from Global Energy and Water Balances

Quantifying soil organic carbon (SOC) dynamics at a high spatial and temporal resolution in response to different agricultural management practices and environmental conditions can help identify practices that both sequester carbon in the soil and sustain agricultural productivity. Using an agricultural systems model (the Agricultural Production Systems sIMulator), we conducted a high spatial resolution and long-term (122 years) simulation study to identify the key management practices and environmental variables influencing SOC dynamics in a continuous wheat cropping system in Australias 96 million ha cereal-growing regions. Agricultural practices included five nitrogen application rates (0-200 kg N ha(-1) in 50 kg N ha(-1) increments), five residue removal rates (0-100% in 25% increments), and five residue incorporation rates (0-100% in 25% increments). We found that the change in SOC during the 122-year simulation was influenced by the management practices of residue removal (linearly negative) and fertilization (nonlinearly positive) - and the environmental variables of initial SOC content (linearly negative) and temperature (nonlinearly negative). The effects of fertilization were strongest at rates up to 50 kg N ha(-1) , and the effects of temperature were strongest where mean annual temperatures exceeded 19 °C. Reducing residue removal and increasing fertilization increased SOC in most areas except Queensland where high rates of SOC decomposition caused by high temperature and soil moisture negated these benefits. Management practices were particularly effective in increasing SOC in south-west Western Australia - an area with low initial SOC. The results can help target agricultural management practices for increasing SOC in the context of local environmental conditions, enabling farmers to contribute to climate change mitigation and sustaining agricultural production.

Estimations of vapour pressure deficit and crop water demand in APSIM and their implications for prediction of crop yield, water use, and deep drainage

Abstract Using the modeling tool Expert-N, daily fluxes of water, carbon and nitrogen in potato fields were simulated in this study. The crop growth model Soil–Plant–Atmosphere System Simulation (SPASS) was integrated in Expert-N and adapted for the simulation of potato growth. The aim of the study was to investigate the extent to which the SPASS model, tested thus far only for winter wheat, is suitable for the simulation of potato crops. In addition to re-parameterization of the model, minor modifications, such as description of phenological development, assimilate partitioning, nitrogen uptake and leaf senescence were carried out without changing the overall structure of the model. The SPASS model was calibrated using data from a potato field experiment carried out in 1996 at the Research Station Scheyern, which examined the effects of various fertilization applications on the growth and yield of two potato varieties, “Christa” and “Agria”, representing early and late maturity classes, respectively. Distinctions between “Christa” and “Agria” were realized by variable parameter values concerning phenological development, assimilate partitioning and nitrogen concentration in tubers. The models ability to predict potato yields and nitrogen uptake was compared with actual values obtained in different years at other fields of the Research Station (only “Agria”). Simulation results show that the SPASS model was able to describe the effect of different N fertilizer applications on potato growth and nitrogen uptake. Differences between the two potato varieties could be adequately predicted, and tuber yields and nitrogen uptake well predicted. However, estimated modeling efficiencies suggest that further improvements are due. Crucial components of the model are the control of root nitrogen uptake and the regulation of the distribution of assimilates to different plant organs. To obtain a broader basis for the verification of the corresponding simulation modules, further experiments addressing optimal nitrogen concentrations in plant organs are necessary. Efforts to refine the SPASS model should be concentrated on a dynamical description of the partitioning pattern of assimilates, including a direct response of the partitioning pattern to changing environmental conditions.

Meta‐modeling soil organic carbon sequestration potential and its application at regional scale

AbstractSatellite and gridded meteorological data can be used to estimate evaporation (E) from land surfaces using simple diagnostic models. Two satellite datasets indicate a positive trend (first time derivative) in global available energy from 1983 to 2006, suggesting that positive trends in evaporation may occur in “wet” regions where energy supply limits evaporation. However, decadal trends in evaporation estimated from water balances of 110 wet catchments do not match trends in evaporation estimated using three alternative methods: 1) , a model-tree ensemble approach that uses statistical relationships between E measured across the global network of flux stations, meteorological drivers, and remotely sensed fraction of absorbed photosynthetically active radiation; 2) , a Budyko-style hydrometeorological model; and 3) , the Penman–Monteith energy-balance equation coupled with a simple biophysical model for surface conductance. Key model inputs for the estimation of and are remotely sensed radiation an...