GAMEDE: A global activity model for evaluating the sustainability of dairy enterprises. Part II – Interactive simulation of various management strategies with diverse stakeholders

GAMEDE is a stock-flow dynamic simulation model designed with farmers to represent dairy farm functioning and the consequences of the farmer’s daily management decisions for whole-farm sustainability. Sustainability is evaluated according to its three pillars: technico-economic viability, respect for environment, and social liveability. The model provides original information for a better understanding of the processes regulating nitrogen dynamics within the farm, and the factors determining farmers’ decisions and practices. Model implementation experiments have revealed that GAMEDE is also a useful tool to support discussions and to generate knowledge exchange among various stakeholders who play an important role in the development of farm sustainability: farmers, extension agents and researchers.While a majority of researchers and advisers are specialised and a majority of farmers fix their attention on specific and narrow themes of farm management, such a comprehensive model can help stakeholders complement their knowledge to gain a holistic view of the farming system. This holistic and integrated view is crucial: (i) for researchers who wish to explain diversity in farming systems and understand decisional and biophysical processes and their interrelated effects operating in such complex agro-ecosystems, (ii) for advisers whose aim is to define alternative management strategies applicable in practice, i.e. taking into account farm specificities, and (iii) for farmers who must choose practices compatible with their resources, assets, constraints and objectives.Holism can also improve versatility and thus the generic character of models. Issues are narrowly specified and greatly vary both among categories of stakeholders (e.g. scientists versus farmers) and within each category (e.g. among farmers). A comprehensive model that: (i) details all farm management operations, and (ii) represents their effects on different spatio-temporal levels and on the three sustainability dimensions, is more likely to respond to the various issues facing different stakeholders. We argue that capacity of models to respond to stakeholders’ questions has to be considered in future evaluations of decision support systems.     

Modelling worker physical health and societal sustainability at farm level: An application to conventional and organic dairy farming

Farm-level modelling can be used to determine how farming systems and individual farm-management measures influence different sustainability indicators. Until now however, worker physical health and societal sustainability have been lacking in farm models. For this paper, we first selected attributes of physical health (working conditions) and societal sustainability (food safety, animal welfare and health, and landscape quality). Second, possible sustainability indicators for these attributes were identified, and those selected were included in an existing dairy farm LP-model that was subsequently used to analyse possible differences in societal sustainability within and between a conventional and organic dairy farming system. Results for physical health and societal sustainability were similar for conventional and organic dairy farming systems in the basis situation, as well as in the situation where additional management measures were applied to improve societal sustainability, but improved animal welfare did result in the organic system due to prescribed grazing, and due to assumed summer feeding in the conventional system. Results show that additional management measures considerably improved societal sustainability of the conventional as well as the organic system. LP-modelling appeared to be a suitable method for comparing farming systems and determining the effect of management measures on physical health and societal sustainability. The level of societal sustainability is determined mainly by applied management measures, and is related to the particular farming system in only a very limited way. This implies that societal sustainability is mainly dependent on the cost-effectiveness of management measures and on the attitude of the dairy farmer.     

Simulating management strategies: the rotational grazing example

This paper argues in favour of a simulation approach relying on an explicit and rigorous modelling of the management strategy that underlies the farmer’s decision-making behaviour. A strategy is defined as a roadmap of intended technical tasks over a management period. It is tied to an overall objective and specifies what to do depending on the situations encountered. An essential feature is its flexibility, enabling it to cope with stochastic fluctuations of the environment. In order to evaluate the worth of a strategy, the advocated approach relies on a simulation tool with which the effects of applying the strategy are evaluated under different hypothetical weather conditions. The example of a rotational grazing dairy production system is used to illustrate the modelling and simulation of a management strategy covering a production season. SEPATOU, the simulator built for this application domain, is designed to be used by extension services and farming system scientists. It provides a framework for virtual experimentation that can help to enhance decision-making capabilities of primary producers and find new or more profitable management strategies.     

Communicating complexity: Integrated assessment of trade-offs concerning soil fertility management within African farming systems to support innovation and development

African farming systems are highly heterogeneous: between agroecological and socioeconomic environments, in the wide variability in farmers’ resource endowments and in farm management. This means that single solutions (or ‘silver bullets’) for improving farm productivity do not exist. Yet to date few approaches to understand constraints and explore options for change have tackled the bewildering complexity of African farming systems. In this paper we describe the Nutrient Use in Animal and Cropping systems - Efficiencies and Scales (NUANCES) framework. NUANCES offers a structured approach to unravel and understand the complexity of African farming to identify what we term ‘best-fit’ technologies - technologies targeted to specific types of farmers and to specific niches within their farms. The NUANCES framework is not ‘just another computer model’! We combine the tools of systems analysis and experimentation, detailed field observations and surveys, incorporate expert knowledge (local knowledge and results of research), generate databases, and apply simulation models to analyse performance of farms, and the impacts of introducing new technologies. We have analysed and described complexity of farming systems, their external drivers and some of the mechanisms that result in (in)efficient use of scarce resources. Studying sites across sub-Saharan Africa has provided insights in the trajectories of change in farming systems in response to population growth, economic conditions and climate variability (cycles of drier and wetter years) and climate change. In regions where human population is dense and land scarce, farm typologies have proven useful to target technologies between farmers of different production objectives and resource endowment (notably in terms of land, labour and capacity for investment). In such regions we could categorise types of fields on the basis of their responsiveness to soil improving technologies along soil fertility gradients, relying on local indicators to differentiate those that may be managed through ‘maintenance fertilization’ from fields that are highly-responsive to fertilizers and fields that require rehabilitation before yields can improved. Where human population pressure on the land is less intense, farm and field types are harder to discern, without clear patterns. Nutrient cycling through livestock is in principle not efficient for increasing food production due to increased nutrient losses, but is attractive for farmers due to the multiple functions of livestock. We identified trade-offs between income generation, soil conservation and community agreements through optimising concurrent objectives at farm and village levels. These examples show that future analyses must focus at farm and farming system level and not at the level of individual fields to achieve appropriate targeting of technologies - both between locations and between farms at any given location. The approach for integrated assessment described here can be used ex ante to explore the potential of best-fit technologies and the ways they can be best combined at farm level. The dynamic and integrated nature of the framework allows the impact of changes in external drivers such as climate change or development policy to be analysed. Fundamental questions for integrated analysis relate to the site-specific knowledge and the simplification of processes required to integrate and move from one level to the next.     

Performance based irrigation planning under water shortage

A linear programming (LP) based optimization model and a simulation model are developed and applied in a typical diversion type irrigation system for land and water allocation during the dry season. Optimum cropping patterns for different management strategies are obtained by the LP model for different irrigation efficiencies and water availability scenarios. The simulation model yields the risk-related irrigation system performance measures (i.e. reliability, resiliency and vulnerability) for the management policies defined by the optimization model. The alternative strategies are evaluated in terms of all performance criteria (i.e. net economic benefit, equity and reliability) simultaneously through a trade-off analysis using a multi-criteria decision making method (compromise programming). For the case study of the Kankai irrigation system in Nepal, with equal preference to the objectives, a management strategy with equal share of water among the project subareas appears to be the most satisfactory alternative under water shortage conditions. The existing water allocation policy is not economically efficient. Deficit irrigation in Early paddy appears attractive under favorable hydrologic scenario, particularly if accompanied by measures to improve existing irrigation system efficiency.     

Dairy farm nutrient management model. 1. Model description and validation

Intensive dairy farming results in significant phosphorus (P) emission to the environment. Field data indicates that farm-gate P surplus is highly positive in Finland and strategies to mitigate the surplus are needed. The objectives of this study were to build a P cycle model for dairy farms (1) and to validate the model with independent field data (2). The dairy farm nutrient management model (“Lypsikki”) described in this paper includes three sub-models: (1) soil and crop, (2) dairy herd and (3) manure management. The model is based on empirical regression equations allowing estimations of crop and milk yields in response to increased fertilisation and nutrient supply, respectively. In addition, the model includes a dynamic simulation model of the dairy herd structure and calculation of the farm-gate nutrient surplus. The model was validated with independent annual (average for 1-4 years) farm-gate P surplus data from 21 dairy farms. Model simulations were conducted using two levels of soil productivity, mean (M) and low (L). The model validation indicated a strong relationships between model-predicted and observed farm-gate P surplus: (M: R² = 0.77 and L: R² = 0.80). The line bias between the model-predicted and observed data was negligible and insignificant (P > 0.6) suggesting a robustness of the model. The mean biases were relatively high and significant (M: 4.7 and L: 1.8 kg/ha, P < 0.001), but evidently related to overestimation of crop yields that has to be taken into account when using the model on a single farm. The prediction error of the model (observed minus predicted P surplus) was significantly correlated to the difference between simulated and observed P import in feeds (M: R² = 0.55 and L: R² = 0.51). This suggests either that all the dairy farms did not fully exploit the possibilities in the crop production or that all the model assumptions are not correct. The effects of purchased feed and fertiliser P and exported milk P (per cow or cropping area) on farm-gate P surplus were of the same magnitude in both observed and simulated data. This implies that the model developed can be used as a management decision tool to find strategies to mitigate P surplus on dairy farms.     

基于RFID与WSN的现代化奶牛养殖系统研究

为了提高奶牛养殖的现代化水平,将RFID和WSN技术相融合,充分发挥两者各自的优势,构建适用于大规模奶牛养殖的现代化管理系统。利用RFID技术实现牲畜个体识别与追踪,WSN技术实现奶牛健康状况、养殖场环境的实时监测,为奶牛养殖的现代化管理、疾病防治和食品安全等提出了综合的解决办法。试验表明,该系统具有稳定、方便、布置灵活、成本低等特点,具有良好的应用前景。     

An integrated sustainability assessment of mediterranean sheep farms with different degrees of intensification

In the European Mediterranean basin, pasture-based sheep farming systems are mostly located in marginal/High Nature Value areas. These production systems are multifunctional, and their economic, environmental and social roles are equally important and recognised by policy makers and by society. However, the number of animals and holdings is decreasing, and there is great uncertainty regarding the reproducibility of these farming systems, which depends on many internal and external farm factors and their interactions. The aim of this paper was to perform a comprehensive assessment of sustainability in different sheep farming systems in north eastern Spain using the MESMIS framework. We followed a case-study approach to perform an in-depth investigation of 4 sheep meat and dairy farms with different intensities of reproduction management. Critical points of sustainability, including weaknesses and opportunities, were obtained using a participatory process with stakeholders (farmers and technical advisers) that resulted in the selection of 37 sustainability indicators that were classified according to the systemic attributes defined by MESMIS (productivity, stability, self-reliance, adaptability, equity) and according to the classical sustainability pillars (social, economic and environmental). Some underlying patterns could be observed when analysing sustainability pillars, attributes and indicators. A positive relationship between productivity and intensification level in meat farms was observed; however, economic sustainability was determined not only by on-farm but also by off-farm activities. The economic efficiency of farming (without considering subsidies) was mainly explained by the capture of added value in the dairy systems and the combination of high animal productivity as well as high forage and feed self-sufficiency in the meat systems. Social issues were also central to explaining sustainability at the farm level, including the prospects of generational turnover and the manner in which farmers perceive and rate their activity. A clear trade-off between economic and environmental indicators was observed, i.e., the higher the economic sustainability, the lower the environmental sustainability. Each farm scored differently for diverse attributes, pillars and individual indicators. The scores differed according to size, structure, resource availability and managerial skills, which implies that it would be difficult to apply a holistic sustainability analysis to farming systems instead of individual farms. A number of methodological questions arose during the evaluation process relative to the stakeholders perception of these indicators, their relevance and meaning, the reference values for comparison, or their validity to assess sustainability across spatial and temporal scales. These questions are discussed in the paper.     

Irrigation management for optimizing crop production and nitrate leaching on grassland

Six supplementary irrigation management options for grazed grassland were defined and their effects on both agricultural production and nitrate leaching to the groundwater were studied. Data were available from the De Marke experimental farm for sustainable dairy farming. The calibrated and validated simulation models SWACROP and ANIMO were used to calculate the effects of the different irrigation management options on crop transpiration, and on water fluxes and nitrate concentrations for three fields of the farm. Comparisons with the common practice at the farm were made. A change in application volume from 25 to 15 mm per irrigation resulted in higher irrigation efficiencies and lower annual water use for supplementary irrigation with only small changes in the ratio of actual and potential transpiration (T_a/T_p). The advisory system ‘irrigation planner’ generally also resulted in high irrigation efficiencies combined with a reduction of water use and a small effect on the transpiration ratio. The different irrigation strategies had no significant effect on nitrate concentrations in the leachate from two dry fields studied. For the relatively wet field in this study an increase of irrigation water use would improve agricultural production conditions and reduce nitrate concentrations at 1 m depth. For the evaluation of environmental effects of irrigation management options it is advised to assess the actual nitrate concentrations and not only the water fluxes, which potentially cause solute leaching.     

Livestock water productivity in mixed crop–livestock farming systems of the Blue Nile basin: Assessing variability and prospects for improvement

Water scarcity is a major factor limiting food production. Improving Livestock Water Productivity (LWP) is one of the approaches to address those problems. LWP is defined as the ratio of livestock’s beneficial outputs and services to water depleted in their production. Increasing LWP can help achieve more production per unit of water depleted. In this study we assess the spatial variability of LWP in three farming systems (rice-based, millet-based and barley-based) of the Gumera watershed in the highlands of the Blue Nile basin, Ethiopia. We collected data on land use, livestock management and climatic variables using focused group discussions, field observation and secondary data. We estimated the water depleted by evapotranspiration (ET) and beneficial animal products and services and then calculated LWP. Our results suggest that LWP is comparable with crop water productivity at watershed scales. Variability of LWP across farming systems of the Gumera watershed was apparent and this can be explained by farmers’ livelihood strategies and prevailing biophysical conditions. In view of the results there are opportunities to improve LWP: improved feed sourcing, enhancing livestock productivity and multiple livestock use strategies can help make animal production more water productive. Attempts to improve agricultural water productivity, at system scale, must recognize differences among systems and optimize resources use by system components.     

Perceived environmental uncertainty in Dutch dairy farming: The effect of external farm context on strategic choice

This paper explores the way in which dairy farmers perceive their environment (PE), i.e., the external context of their farm, and the uncertainty (PEU) this poses to them. The environment is defined using the STEP concept (society, technology, economy and politics) and Porter’s five forces model. The relationship between the perception of the external farm environment and the strategy farmers choose for their farm is quantified to gain insight into the effect of the external farm environment on decision-making. Data from a survey of 103 Dutch dairy farmers was analyzed using regression analysis. The results indicate that environmental uncertainty is not related to complexity or dynamism, but to the illiberality (i.e., intolerance, hostility) of the external farm environment. The institutional environment is considered especially illiberal, thus causing high uncertainty. Farmers with high PEU are more likely to choose a diversification strategy, while low perceived uncertainty results in a process-control strategy for the farm. A growth strategy is not affected by perceived environmental uncertainty. The PE and PEU approach is new in agricultural research and shows that the farmer’s view on the external environment is a key issue for decision-making on farms The significant relationship between the perceived uncertainty caused by the external farm environment and farm strategies shows that to get a good understanding of the farm, farming system boundaries should be expanded to incorporate the effect of the external farm environment on decision making. Reduction of uncertainty will enhance decision-making because instead of farming within an uncertain context, risk management practices can be used.     

An LP-model to analyse economic and ecological sustainability on Dutch dairy farms: model presentation and application for experimental farm “de Marke”

Farm level modelling can be used to determine how farm management adjustments and environmental policy affect different sustainability indicators. In this paper indicators were included in a dairy farm LP (linear programming)-model to analyse the effects of environmental policy and management measures on economic and ecological sustainability on Dutch dairy farms. For analysing ecological sustainability, seven indicators were included in the model: eutrophication potential, nitrate concentration in groundwater, water use, acidification potential, global warming potential, terrestrial ecotoxicity, and aquatic ecotoxicity. Net farm income was included for measuring economic sustainability. The farm structure of “De Marke” formed the basis for three optimisations: (1) basis situation without environmental policy, (2) situation with Dutch environmental policy for 2004, and (3) situation with farm management measures applied at “De Marke”. The Dutch environmental policy was included to comply with the EC nitrate directive. It resulted in lower fertiliser use and consequently in a decrease in sales of maize. This led to a decrease in net farm income of ca. €2500. Including this policy improved most used ecological indicators (except for ecotoxicity) and showed to be an effective tool to reduce the environmental impact of dairy farming. Adapting the model with farm management measures applied at experimental farm “De Marke” resulted in even better ecological performance compared to the situation with environmental policy. Nonetheless this increase in ecological performance led to a considerably lower net farm income (€14,500).     

Nutrient flows and balances at the field and farm scale: Exploring effects of land-use strategies and access to resources

Nutrient flux and balance studies are valuable tools to assess the sustainability of agro-ecosystems and potential consequences for agricultural productivity. This paper presents results from a study at the field/farm scale representing mixed farming systems typical for the East African Highlands. We selected catchments in the Dega (cool highlands and Woina Dega (warm-to-cool mid-highlands) of the Central Highlands of Ethiopia, to get more insight on how individual land use strategies and access to resources affect the magnitude of nutrient flows and resulting balances and to explore some of reasons of the variability within and between farming systems at different altitudes. Our results show that environmental condition, farming system (e.g. choice of crop), access to resources (e.g. land, livestock and fertilizer) and smallholders’ source of off farm income influence the magnitude of nutrient fluxes and the degree to which nutrient fluxes may be imbalanced.     

奶牛智能饲喂关键技术研究

随着现代规模化养殖新格局的初步形成,奶牛智能养殖装置的不断涌现,奶牛饲喂技术发展呈现出信息化、精细化、智能化的趋势。通过分析奶牛全混合日粮饲喂技术与奶牛自动饲喂装备系统的特点和应用情况,对国内外奶牛养殖技术装备进行总结,国内中小型养殖场仍存在自动化水平较低、饲喂技术与装备结合不完善、饲喂效率较低等问题;大规模养殖场面临核心技术需进口、养殖成本与装备研制成本较高的问题;国外的智能养殖装备技术相对成熟,相关装备系统已经大范围使用。此外结合国内外研究现状提出我国饲喂技术装备的改进方向,针对实际养殖情况对装备技术进行研发,促进我国自主装备及核心技术的推广应用,推进奶牛养殖装备技术向精细化、智能化发展,切实提升我国奶牛养殖水平。     

GAMEDE: A global activity model for evaluating the sustainability of dairy enterprises Part I – Whole-farm dynamic model

 Crop-livestock farms are complex systems. The interactions operating in such systems involve decisional, biophysical, structural, and environmental factors. Moreover, as farmers face a large range of management options, tools are needed to support their decision-making to enable them to reach production levels meeting their objectives and compatible with their human and physical resources, while controlling their effects on the environment. Gamede, a whole-dairy-farm model, has been developed to explore this complexity and to represent dynamically the effect of management decisions on biomass and nitrogen flows and on numerous sustainability indicators, such as milk and forage crop productivity, labour requirements, nitrogen balance, and nitrogen efficiency.This article describes the integration of six modules accounting for biophysical processes in a dairy farm (forage production; forage conditioning; herd demography; milk, excreta and animal biomass productions; grazing, quality of fertilisers; and nitrogen gaseous emissions) together with a decision system accounting for the farmer’s strategy and technical operations. Most of the six biophysical modules incorporate mathematical models from the literature, but the decision system stems from our own original work.Six commercial farms with different structures, agro-climatic conditions and management strategies were used for validation. The model can explain the differences found in their sustainability indicators at the year scale. The intra-year variability of the main biomass stocks and flows is also well explained. This quantitative validation was completed by a qualitative validation from researcher, adviser and farmer points of view, including simulations of prospective scenarios.     

Life cycle assessment of Swiss farming systems: I. Integrated and organic farming

Organic farming (OF) is considered a promising solution for reducing environmental burdens related to intensive agricultural management practices. The question arises whether OF really reduces the environmental impacts once lower yields and all the changes in farming methods are taken into consideration. This question is addressed in a comprehensive study of Swiss arable cropping and forage production systems comparing OF to integrated production (IP) systems by means of the life cycle assessment (LCA) method.The LCA study investigated the environmental impacts of two long-term farming system experiments: the DOC experiment comparing bio-dynamic, bio-organic and conventional/integrated farming and the “Burgrain” experiment encompassing integrated intensive, integrated extensive and organic production. All treatments received similar amounts of farmyard manure. The system boundary encompasses the plant production system; storage and application of farmyard manure is included in the system boundary, the animal husbandry is not included. The Swiss Agricultural Life Cycle Assessment method (SALCA) was used to analyse the environmental impacts.In the overall assessment OF was revealed to be either superior or similar to IP in environmental terms. OF has its main strengths in better resource conservation, since the farming system relies mainly on farm-internal resources and limits the input of external auxiliary materials. This results in less fossil and mineral resources being consumed. Moreover the greatly restricted use of pesticides makes it possible to markedly reduce ecotoxicity potentials on the one hand, and to achieve a higher biodiversity potential on the other. This overall positive assessment is not valid for all organic products: some products such as potatoes had higher environmental burdens than their counterparts from IP.The main drawbacks identified for Swiss OF systems are lower yields. As a consequence some production factors are used less efficiently, thus partly negating the advantages of OF. Furthermore, the different manure management strategy leads to relatively high nutrient losses in relation to yield. These two points were shown to be the main priorities for the environmental optimisation of OF systems. The differences between the bio-organic and the bio-dynamic farming systems consisted in a slightly higher input of organic matter, a few applications of mineral fertilisers and copper applications in the former.The eco-efficiency analysis led to the conclusion that the optimisation of OF is mainly output-driven, i.e. that higher yields of good quality should be achieved with the available (limited) resources. On the contrary, optimisation of IP was found to be input-driven; the inputs should be used in a quantity and manner which minimise the environmental burdens per unit produced. The study showed that despite the efforts of recent years, there is still considerable room for the environmental optimisation of Swiss farming systems.     

Systematic design and evaluation of crop rotations enhancing soil conservation, soil fertility and farm income: a case study for vegetable farms in South Uruguay

Rapid changes in the social and economic environment in which agriculture is developing, together with the deterioration of the natural resource base threatens sustainability of farm systems in many areas of the world. For vegetable farms in South Uruguay, survival in the long term depends upon the development of production systems able to reduce soil erosion, maintain or improve physical and biological soil fertility, and increase farmer’s income to socially acceptable levels. We propose a model-based explorative land use study to support the re-orientation of vegetable production systems in South Uruguay. In this paper we present a new method to quantitatively integrate agricultural, environmental and socio-economic aspects of agricultural land use based on explicit design objectives. We describe the method followed to design and evaluate a wide variety of land use activities for Canelón Grande (South Uruguay) and we illustrate the usefulness of this approach in an ex-ante evaluation of new farming systems using data from 25 farms in this region. Land use activities resulted from systematic combination of crops and inter-crop activities into crop rotations, different crop management techniques (i.e., mechanisation, irrigation and crop protection) and animal production. We identified and quantified all possible rotations and estimated inputs and outputs at crop rotation scale, explicitly considering interactions among crops. Relevant inputs and outputs (i.e., soil erosion, balance of soil organic matter and nutrients, environmental impact of pesticides, labour and machinery requirements, and economic performance) of each land use activity were quantified using different quantitative methods and following the target-oriented approach. By applying the methodology presented in this paper we were able to design and evaluate 336,128 land use activities suitable for the different soil types in Canelón Grande and for farms with different availability of resources, i.e., land, labour, soil quality, capital and water for irrigation. After theoretical evaluation, a large subset of these land use activities showed promise for reducing soil erosion, maintaining soil organic matter content of the soil and increasing farmer’s income, allowing improvement of current farming systems in the region and providing a widely diverse set of strategic options for farmers in the region to choose from. This method can be used as a stand-alone tool to explore options at the field and farm scale or to generate input for optimisation models to explore options at the farm or regional scale.     

Evaluation of the water use efficiency of alternative farm practices at a range of spatial and temporal scales: A conceptual framework and a modelling approach

Water is the principal limiting resource in Australian broadacre farming, and the efficiency with which farmers use water to produce various products is a major determinant both of farm profit and of a range of natural resource management (NRM) outcomes. We propose a conceptual framework based on multiple water use efficiencies (WUEs) that can be used to gain insight into high-level comparisons of the productivity and sustainability of alternative farming practices across temporal and spatial scales. The framework is intended as a data aggregation and presentation device. It treats flows of water, biomass and money in a mixed farming system; economic inefficiencies in these flows are tracked as they are associated with a range of NRM indicators.We illustrate the use of the framework, and its place in a larger research programme, by employing it to synthesise the results from a set of modelling analyses of the effect of land use choices on long-term productivity and a range of NRM indicators (frequency of low ground cover, deep drainage, N leaching rates and rate of change in surface soil organic carbon). The analyses span scales from single paddocks and years to whole farms and have been carried out with the APSIM and GRAZPLAN biophysical simulation models and the MIDAS whole-farm economic model.In single wheat crops in one study, different land uses in preceding years affect grain yield primarily by affecting the harvest index. When the scale changes to cropping rotations, the critical factor affecting overall water use efficiency is found to be the proportion of stored soil water that is transpired by crops. When ordinated in terms of their water use efficiencies, a set of 45 modelled rotation sequences at another location are differentiated mainly by the proportion of pasture in the rotation; when rotations are ordinated using key NRM indicators, the proportion of lucerne pasture is the main distinguishing factor. Finally, we show that for whole crop-livestock farms at three different locations across southern Australia, the pattern of water use efficiencies in the most profitable farming systems changes in similar ways as cropping proportion is altered. At this scale, land use choices affect multiple water use efficiency indices simultaneously and commodity prices determine the balance of the resulting economic tradeoffs.Limitations to the use of the WUE framework arising from its relative simplicity are discussed, as are other areas of farming systems research and development to which it can be applied.     

BANAD: A farm model for ex ante assessment of agro-ecological innovations and its application to banana farms in Guadeloupe

The ex ante assessment of innovative agro-ecological innovations is a key step in the development of more sustainable crop management systems. To this end, models are useful tools because they make it possible to rapidly assess numerous innovations in different contexts. Whereas many farm optimisation models focusing on the farmer’s strategic decision to adopt new crop management systems have been published, little attention has been given to the ex ante modelling of the dynamic operational impacts of innovation adoption at the farm level. BANAD, a mechanistic model for such applications, is proposed. It allows the ex ante assessment of innovative management systems including new agro-ecological techniques, while taking into account different farming contexts and policy and market conditions. It includes three components: (i) a crop management system model, (ii) a crop model (SIMBA) and (iii) a farming system model. Our results applied to the ex ante assessment of six innovative banana management systems for three contrasted farm types in Guadeloupe showed that the impacts of agro-ecological innovations, which include rotations, improved fallow, intercropping, pest-resistant cultivar, and an integrated organic system, can vary considerably according to (i) the farm type in which the innovation is integrated, (ii) the nature of the agro-ecological innovations, and (iii) the criteria considered and the temporal horizon of the assessment. Innovative intercropping systems that were effective at the field level in terms of the yield improvement and decreased pesticide use could be problematic at the farm level because they increased the workload and decreased income. The adoption of rotations or improved fallow seemed to be relevant for smallholders but could induce a critical period of 1.5-2.5 years during which income decreased drastically. Under certain conditions of markets and subsidies, very environmentally friendly innovations that are less productive can however be economically effective.     

Performance measure for improving irrigation management

A measure to evaluate performance in irrigation systems is analyzed using the mean square prediction error concept. In the context of irrigation system management, the term error means the deviation of actual performance from a reference performance. The measure assesses performance in terms of the management objectives of adequacy and dependability of water delivery and an equitable distribution among various water users. It provides an understanding of the management capacity to schedule and distribute water in an irrigation system. Application of the performance measure is demonstrated by evaluating performance of an irrigation system in the Northwest Frontier Province of Pakistan.