Thiagarajah Ramilan

Analysis of environmental and economic efficiency using a farm population micro-simulation model

New Zealands success in raising agricultural productivity has been accompanied by higher input use, leading to adverse effects on the environment. Until recently, analysis of farm performance has tended to ignore such negative externalities. The current emphasis on environmental issues has led dairy farmers to target improvements in both environmental performance and productivity. Therefore, measuring the environmental performance of farms and integrating this information into farm productivity calculations should assist in making informed policy decisions which promote sustainable development. However, this is a challenging process since conventional environmental efficiency measures are usually based on simple input and output flows but nitrogen discharge is a complex process affected by climate, pasture composition, cow physiology and geophysical variability. Furthermore, the outdoor pastoral nature of New Zealand farming means that it is difficult to control input and output flows, particularly of nitrogen. We present a novel approach to measure the environmental and economic efficiency of farms, using the Overseer nutrient budget model and spatially micro-simulated virtual population data. The empirical analysis is based on dairy farms in the Karapiro catchment, where nitrogen discharge from dairy farming is a major source of nonpoint pollution.

Framework for evaluating management interventions for water-quality improvement across multiple agents

It is difficult to accurately predict the impacts of policies for control of nonpoint-source pollution because analytical frameworks incorporating agent heterogeneity are rare. This paper overcomes this limitation through describing a new framework in which the behaviour of individual firms is explicitly represented by large, complex models calibrated to baseline information. Disaggregation allows the simulation of policies that require uniform reductions in pollutant load or those that allow different rates of abatement between firms to achieve a given nutrient target at least cost, as with the trading of pollution entitlements. The reduction of nitrate leaching from intensive dairy production in a catchment of the Waikato River in New Zealand is used as an illustrative application. It is highlighted that satisfaction of water-quality standards will incur substantial costs within this region. Overall, the framework is notable for its integration of multiple modelling techniques from diverse disciplines and its focus on the behaviour of individual agents. Moreover, it can easily be applied elsewhere where sufficient information is available.

Evaluating the accuracy of the Agricultural Production Systems Simulator (APSIM) simulating growth, development, and herbage nutritive characteristics of forage crops grown in the south-eastern dairy regions of Australia

Abstract. Pasture-based dairy farms are a complex system involving interactions between soils, pastures, forage crops, and livestock as well as the economic and social aspects of the business. Consequently, biophysical and farm systems models are becoming important tools to study pasture-based dairy systems. However, there is currently a paucity of modelling tools available for the simulation of one key component of the system—forage crops. This study evaluated the accuracy of the Agricultural Production Systems Simulator (APSIM) in simulating dry matter (DM) yield, phenology, and herbage nutritive characteristics of forage crops grown in the dairy regions of south-eastern Australia. Simulation results were compared with data for forage wheat (Triticum aestivum L.), oats (Avena sativa L.), forage rape (Brassica napus L.), forage sorghum (Sorghum bicolor (L.) Moench), and maize (Zea mays L.) collated from previous field research and demonstration activities undertaken across the dairy regions of south-eastern Australia. This study showed that APSIM adequately predicted the DM yield of forage crops, as evidenced by the range of values for the coefficient of determination (0.58–0.95), correlation coefficient (0.76–0.94), and bias correction factor (0.97–1.00). Crop phenology for maize, forage wheat, and oats was predicted with similar accuracy to forage crop DM yield, whereas the phenology of forage rape and forage sorghum was poorly predicted (R2 values 0.38 and 0.80, correlation coefficient 0.62 and –0.90, and bias correction factors 0.67 and 0.28, respectively). Herbage nutritive characteristics for all crop species were poorly predicted. While the selection of a model to explore an aspect of agricultural production will depend on the specific problem being addressed, the performance of APSIM in simulating forage crop DM yield and, in many cases, crop phenology, coupled with its ease of use, open access, and science-based mechanistic methods of simulating agricultural and crop processes, makes it an ideal model for exploring the influence of management and environment on forage crops grown on dairy farms in south-eastern Australia. Potential future model developments and improvements are discussed in the context of the results of this validation analysis.

Simulation of alternative dairy farm pollution abatement policies

New Zealand dairy farmers face a tradeoff between profit maximisation and environmental performance. The integrated simulation model presented here enables assessment of the economic and environmental impact of dairy farming with a focus on nitrogen pollution at the catchment level. Our approach extends the value of the DairyNZ Whole Farm Model (Beukes et al., 2005) as an environmental policy tool by building and integrating nitrogen discharge functions for specific soil types and topography using a metamodelling technique. A hybrid model is created by merging the merits of differential evolution and non-linear optimisation to expedite policy simulations, in which farm profits and nitrogen discharges obtained from the differential evolution optimisation process are assembled to form a profit-pollution frontier. This frontier is then subject to constrained optimisation based on non-linear optimisation in order to predict producer responses to alternative pollution control policies. We apply this framework to derive marginal abatement costs for heterogeneous farm types and find that abatement costs for intensive farms are lower than for moderate and extensive farming systems. We further conclude that abatement can be achieved more cheaply using a compulsory standard or threshold tax than using a standard emissions tax.

Modelling the resilience of forage crop production to future climate change in the dairy regions of Southeastern Australia using APSIM

A warmer and potentially drier future climate is likely to influence the production of forage crops on dairy farms in the southeast dairy regions of Australia. Biophysical modelling was undertaken to explore the resilience of forage production of individual forage crops to scalar increases in temperature, atmospheric carbon dioxide (CO 2 ) concentration and changes in daily rainfall. The model APSIM was adapted to reflect species specific responses to growth under elevated atmospheric CO 2 concentrations. It was then used to simulate 40 years of production of forage wheat, oats, annual ryegrass, maize grown for silage, forage sorghum, forage rape and alfalfa grown at three locations in southeast Australia with increased temperature scenarios (1, 2, 3 and 4 °C of warming) and atmospheric CO 2 concentration (435, 535, 640 and 750 ppm) and decreasing rainfall scenarios (10, 20 or 30% less rainfall). At all locations positive increases in DM yield compared with the baseline climate scenario were predicted for lucerne (2·6–93·2% increase), wheat (8·9–37·4% increase), oats (6·1–35·9% increase) and annual ryegrass (9·7–66·7% increase) under all future climate scenarios. The response of forage rape and forage sorghum varied between location and climate change scenario. At all locations, maize was predicted to have a minimal change in yield under all future climates (between a 2·6% increase and a 6·8% decrease). The future climate scenarios altered the seasonal pattern of forage supply for wheat, oats and lucerne with an increase in forage produced during winter. The resilience of forage crops to climate change indicates that they will continue to be an important component of dairy forage production in southeastern Australia.

An Economic Framework for Sharing Water Within a River Catchment

A framework for sharing a limited quantity, but also a variable quantity, of water between irrigation and the environment to maximize social wellbeing is developed and illustrated. The optimal water allocation equates the marginal social value of water across different uses. A simplified illustration allocates water from the Goulburn River in northern Victoria, Australia, between environmental water to increase numbers of Golden Perch (GP) fish stocks and irrigation demand for water for dairy farmers. The value of water for GP is developed using a combination of fish numbers as an ecological response function of water and Choice Model estimates of willingness to pay by Victorian households for improved fish stocks. Irrigation demand for water by dairy farmers is developed using a Linear Programming study. The complex ecological response functions require a numerical search model to evaluate the socially efficient allocation of water between the different uses. The shadow price of water as optimally allocated between the environmental and agricultural uses is developed as seasonal water availability varies. Further development of the framework could include identifying dependencies within the ecological responses and incorporating multiple ecological and agricultural responses in an expanded model. The policy implications include information on the socially efficient allocation of limited water between irrigation and the environment and the value of water when shared optimally between uses.

Sensitivity of Livestock Production to Climatic Variability Under Indian Drylands and Future Perspective

The livestock production system is considered equally sensitive to climate change as that of core agriculture system and at the same time livestock itself is also contributing to the phenomenon. The present paper attempts to analyze the sensitivity of livestock productivity in rainfed regions to climatic variability, significance of climate change with respect to Indian livestock and mitigation options and leverage points in such a scenario. The sensitively of livestock productivity was examined by using district level data of milk productivity of cow as well as buffalo for the year 1992 and 1997 for 100 districts which was regressed on important weather variables. The analysis shows that weather variables like rainfall and temperature do significantly influence the milk productivity of animals in rainfed regions. Increased climatic variability due to changing climate is likely to negatively influence the livestock productivity. Based on analysis and stakeholders consultation the paper suggests appropriate adaptation strategies particularly focusing on mitigating feed scarcity situations arising due to climatic variability.

Using Microsimulation to Maximise Scarce Survey Data: Applications for Catchment Scale Modelling and Policy Analysis

Microsimulation can be used to extend the use of scarce survey resources by creating simulated populations whose characteristics are close to those of the real population. The technique involves merging detailed survey observations with variables from more extensive data sets in order to create a simulated population. We illustrate how microsimulated data enable analysis of the economic and environmental impact of different policies on a catchment for which detailed farm level data was unavailable. Use of microsimulation for agri-environmental policy analysis is applicable to diverse problems from simulation of nitrogen trading to modelling of agent response to policy shocks. Scale flexibility is easily implemented since data can be aggregated or disaggregated to the preferred scale. Simulated catchment data allows better understanding of the effects of policies on different types of farm and should be extremely valuable to organisations that want to minimise the economic impact of environmental policies.