Environmental decision support system development for seasonal wetland salt management in a river basin subjected to water quality regulation

Seasonally managed wetlands in the Grasslands Basin on the west-side of California’s San Joaquin Valley provide food and shelter for migratory wildfowl during winter months and sport for waterfowl hunters during the annual duck season. Surface water supply to these wetlands contain salt which, when drained to the San Joaquin River (SJR) during the annual drawdown period, can negatively impact water quality and cause concern to downstream agricultural riparian water diverters. Recent environmental regulation, limiting discharges salinity to the SJR and primarily targeting agricultural non-point sources, now also targets return flows from seasonally managed wetlands. Real-time water quality management has been advocated as a means of continuously matching salt loads discharged from agricultural, wetland and municipal operations to the assimilative capacity of the SJR. Past attempts to build environmental monitoring and decision support systems (EDSS’s) to implement this concept have enjoyed limited success for reasons that are discussed in this paper. These reasons are discussed in the context of more general challenges facing the successful implementation of a comprehensive environmental monitoring, modelling and decision support system for the SJR Basin.     

模型库系统在农业信息决策支持系统中的应用

介绍了模型库系统中模型操纵的几种方法、农业信息决策支持系统常见模型的种类及存储方式；阐述了农业信息决策支持系统中模型库系统结构设计方法，以及经济效益分析的构模过程。     

How does research address the design of innovative agricultural production systems at the farm level? A review

In trying to respond to societal demands for sustainable development, farming systems worldwide face a range of environmental, technical and economic challenges. These challenges call for renewed methodologies that can be used to support farmers in designing innovative agricultural production systems at the farm level. This paper aims to analyze the various methods described in scientific literature. The review is based on the analysis of 80 reference papers published in international scientific journals between 1999 and 2010. We focused in particular on the purpose of the research, which fell into two broad categories: “design” and “design support”. We also examined the use of models to represent production systems and to evaluate ex-ante the impact of innovations on these systems’ functioning and performance. In so doing, we developed a classification system to organize the studies into five sub-categories according to the type of methodology followed, namely: prototyping and design modelling for design orientated studies; participation, support modelling and advisory for design-support orientated studies. We found that very few studies attempt to address the three main components of an innovation process in agricultural production systems (biotechnical processes, farm management, and advisory services) within a single research framework. We therefore developed such a framework by connecting the design and design support orientations together with biotechnical research and conducting integrated research both at farm and advisory service levels.     

Emerging consensus on desirable characteristics of tools to support farmers’ management of climate risk in Australia

The prospect that decision support systems (DSS) can help farmers adjust their management to suit seasonal conditions by putting scientific knowledge and rational risk management algorithms at farmers’ fingertips continues to challenge the science and extension community. A number of reviews of agricultural DSS have called for a re-appraisal of the field and for the need to reflect on past mistakes and to learn from social and management theory. The objective of this paper was to investigate whether there is an emerging consensus, among stakeholders in DSS for Australian agriculture, about the lessons learned from past experience with DSS tools. This investigation was conducted in three parts. The first part was a distillation of suggestions for best practice from the relevant literature. The second part was a reflection on what the champions of five current DSS development and delivery efforts in Australia learned from their recent efforts. The third part tested the level of support for the combined findings from the first and second approaches by surveying 23 stakeholders in the research, development, delivery and funding of DSS.The key propositions relating to best practice that were supported by the survey, listed according to the strength of support, were: 1. It is essential to have a plan for delivery of the DSS beyond the initial funding period. 2. DSS need to be embedded in a support network consisting of farmers, consultants and researchers. 3. DSS development requires the commitment of a critical mass of appropriately skilled people. 4. A DSS should aim to educate farmers’ intuition rather than replace it with optimised recommendations. 5. A DSS should enable users to experiment with options that satisfy their needs rather than attempt to present ‘optimised’ solutions. 6. DSS tools stand on the quality and authority of their underlying science and require ongoing improvement, testing and validation. 7. DSS development should not commence unless it is backed by marketing information and a plan for delivery of the DSS beyond the initial funding period.While the DSS stakeholders supported the proposition that it is essential to have a plan for delivery of a DSS beyond the funding period, the majority resisted the notion of DSS development being market-driven and especially commercial delivery of DSS. We argue that since public funding of the delivery of DSS for farmers’ management of climate risk is highly unlikely, reaping the benefits of lessons learned from past efforts will require that DSS stakeholders change their perception of the commercial delivery model or find an alternative way to fund the delivery of DSS beyond the R&D phase.     

An ecology of a DSS: reflections on managing wheat crops in the northeastern Australian grains region with WHEATMAN

An ecological framework is used to study the reinforcing and limiting processes on a computerised decision support system (DSS) designed for winter cropping decisions in the northeastern Australian Grains-belt (WHEATMAN). We found that WHEATMAN has had a significant impact on how many advisers structure their thinking and much of their advice on winter cropping in the region, but the number of routine users of WHEATMAN remains relatively low. Computer hardware was the most obvious limiting factor to widespread use during the early stages of the 15 year history of the project. However, despite a dramatic increase in the availability of computers on grain farms (from 5 to 75%), a maximum of 250 out of an estimated 4500 grain farmers in the region with computers directly use WHEATMAN. Another common limiting factor for adoption of DSS is a failure to engage with end users; yet from early days the WHEATMAN project had a high degree of extension agronomist and farmer input. We suggest that just as the debate on the adoption of DSS was dominated by discussions of computerisation in the late 1980s, notions of user involvement have dominated current debate. Experiences with WHEATMAN suggest that well designed software and a focused development team approach, good access to hardware and representative end user involvement are necessary requirements to help explain the comparative longevity of the project. On their own these are not sufficient requirements for widespread adoption or impact. We argue that the perception of farmers of the nature of dryland farm management in general, and the specific decisions addressed by WHEATMAN are the primary limitations to the routine use of a computerised DSS for tactical decision making.     

农艺与物联网下的智慧农业

农业物联网在大棚控制系统中的运用实现了农作物增产、改善品质、调节生长周期和提高经济效益的目的。从物联网出发,结合农艺技术和物联网技术,提出了智慧农业系统结构总体框架,为用户实时监控农田并进行信息决策提供了技术支持,真正实现了农业管理的智能化,符合现代农业的发展。      

A conceptual framework for guiding the participatory development of agricultural decision support systems

Scientists develop decision support systems (DSSs) to make agricultural science more accessible for farmers and extension officers. Despite the growing use of participatory approaches in agricultural DSS development, reflection on this endeavour has largely focused on the ‘doing’ of participation or the ‘problem of implementation’ when DSSs have not been adopted by stakeholders. There has been little reference to relevant theoretical approaches to the social processes involved in ‘participation’ or ‘implementation’. However, if DSS use is to reach its full potential, a more conceptually informed understanding of how stakeholders collaborate in the participatory development of DSSs is required. To contribute to this conceptualisation, we developed a framework based on three concepts drawn from the field of science and technology studies: technological frames, interpretative flexibility and boundary objects. The framework highlights the importance and value of social learning for participatory DSS development, which relies upon exploring the participating parties’ different perspectives on the agricultural system represented in the DSS. Our framework provides a broad definition of success for participatory DSS development, placing greater weight on learning during the participatory process compared with subsequent use of the DSS by farmers and/or advisors. Two case studies of stakeholder collaboration to develop an irrigation scheduling DSS for sugarcane production were used to explore the relevance of the framework. The concepts in the framework were clearly displayed during the case studies. At the conclusion of the studies there were contrasting outcomes for the DSS. One group of farmers was keen to apply it in their ongoing irrigation management, while another saw little relative advantage in use of the DSS. In both instances co-learning occurred amongst case study participants, so the participatory process was clearly a success.     

基于CLIPS的农业灌溉专家系统研究

在干旱区高效用水灌溉决策支持系统研究过程中,农业灌溉过程中的很多问题无法用数学模型来求解,而必须使用农业专家的专家知识来对其进行解答。而早期由于专家系统不普及和开发困难等原因,致使农业灌溉专家系统应用不多。在对现行诸多专家系统进行详细了解后,决定采用CLIPS专家系统作为农业灌溉专家系统的支持平台。采用CLIPS组件和Visual C 语言开发出了农业灌溉专家系统,解决了农业灌溉过程中的诸多问题。同时介绍了将CLIPS组件嵌入到Visual C 中的方法。     

Integrated participatory modelling of actual farms to support policy making on sustainable intensification

On the tropical island of La Réunion, population growth, increasing demand in food products, agricultural densification, and the resulting pressure on the environment are representative of what is expected to happen in the majority of the world’s regions in the next decades. Crop-livestock integration is a possible solution for the sustainable intensification of farming systems.GAMEDE, a whole-farm model, was designed and used with six representative dairy farmers on the island to ex-ante assess differences in farm sustainability of various degrees of crop-livestock integration and to support discussions with farmers about these options. The model details the dynamics of the main biophysical and decisional processes affecting labour, gross margin, and energy and nutrient flows within the farm.We propose a method based on typology, modelling and participatory techniques to support policy making. All its methodological stages integrate both quantitative and qualitative data. The large majority of farm model implementation cases reported in the literature refers to constructed synthetic farms. However, in our case, actual farm simulation was particularly useful for capturing farmers’ expert knowledge and providing insights into how agro-ecosystems are really managed. This approach enabled taking farm diversity into account in defining relevant interventions. The reliability of extrapolations and recommendations for policy formulation based on farm-level simulation were verified by a rigorous evaluation of the representativeness of the farm sample, crossing expert data with data stemming from a multi-variate analysis. Our research indicates that actual farms can also be typical.     

A cognitive systems framework to inform delivery of analytic support for farmers’ intuitive management under seasonal climatic variability

The idea of the decision support system (DSS) for farmers remains an enigma. Clever technology to bridge the gap between agricultural science and farming practice still seems appropriate. Many more of the conditions for success appear to exist today than ever before. Yet the DSS has yet to significantly colonise farm decision making practice. This paper comes late in a long program of research conducted to see if, and under what conditions, computer simulation of farming scenarios, on which a DSS generally depends, can be valued by farmers.The research approach used an unconventional prototypic information system (IS), comprising local measurements, models, and facilitated discussions that evolved in an action research program. The aim has been to elucidate the means by which successful simulation-based decision support intervention can take place and why it usually does not. This required a significant expansion of the researchers’ concept of the farm as a system to include the farmer’s internal system of practical knowing and learning. This paper reports on a cognitive framework model with transactions at interfaces with both the production system and the analytical IS. Its coarse structure is the classical perception-action cycle influenced by goals and outcome feedback. In the highly uncertain production environment of Australian dryland farming, personal judgement plays a significant mediating role between perception and action, and theory of a continuum between the judgement modes of intuition and analysis adds to framework structure. Further structure comes from the theoretical distinctions between holistic and arbitrary intuition, and between causal and probabilistic analysis. Analytic interventions influence: (a) awareness of current situation conditions and (b) expectations of future conditions and action outcomes, and these serve as primary cognitive resources for evaluation of possible actions in planning and decision making. A theory that matches our research experience in bridging the gap between analytic intervention and intuitive practice posits that virtual situations simulated with analytic models and outputs represented graphically can facilitate vicarious experiential learning. This dovetails with theory concerning the education of intuition.The paper concludes by applying criteria from the field of cognitive engineering to test whether the framework presents a concept of mind that is workable for informing practical model-based research and development aimed at supporting farmers’ judgments and decisions.     

A robust modeling approach for regional water management under multiple uncertainties

In regional water management systems, various uncertainties may be derived from random feature of resource conditions and natural processes, errors in estimated modeling parameters, as well as imprecision or fuzziness human-induced. This leads to difficulties in formulating and solving the resulting regional water management problems. In this study, a robust multistage interval-stochastic programming (RISP) method is developed for dealing with vague and random information in regional water management systems. The decision variables are useful for justifying and/or adjusting the decision schemes for agricultural activities through the incorporation of their implicit knowledge on regional water management. Different policies for agricultural water supply have been analyzed. The results can help to identify desired water-allocation schemes for agricultural sustainable development that the prerequisite water demand for supporting crops’ survival can be guaranteed when the water resource is scarce.     

Zoning of sustainable agricultural development in China

Based on relative advantage assessment, the zoning of sustainable agricultural development in China is exammed. An index system of sustainable development is constructed, consisting of five supporting systems: (1) agricultural resources, (2) agricultural development, (3) environment and ecosystem, (4) rural society, and (5) science, education and management. Included in the five supporting systems are 95 factors that are selected at the provincial level as basic indices. A method of assessing relative assets/debts is then used to calculate the net assets (i.e. relative advantage) for each provincial unit. This is done for both the five supporting systems and their total capability. The assessment results are then ranked, and the geographical patterns mapped. Based on the above assessment results, the whole country is divided into nine agricultural development regions (first-level), and 22 sub-regions (second-level). The first-level zones reflect each region’s direction for future sustainable agricultural development and management. The second-level zones reflect their level of development, and whether or not each sub-region has reached the basic criteria of sustainable agricultural development. A zoning at provincial level for sustainable agricultural development in China is, thereby, established.     

Extending results from agricultural fields with intensively monitored data to surrounding areas for water quality management

A 45% reduction in riverine total nitrogen flux from the 1980-1996 time period is needed to meet water quality goals in the Mississippi Basin and Gulf of Mexico. This paper addresses the goal of reducing nitrogen in the Mississippi River through three objectives. First, the paper outlines an approach to the site-specific quantification of management effects on nitrogen loading from tile drained agriculture using a simulation model and expert review. Second, information about the net returns to farmers is integrated with the nitrogen loading information to assess the incentives to adopt alternative management systems. Third, the results are presented in a decision support framework that compares the rankings of management systems based on observed and simulated values for net returns and nitrogen loading. The specific question addressed is how information about the physical and biological processes at Iowa State University’s Northeast Research Farm near Nashua, Iowa, could be applied over a large area to help farmers select management systems to reduce nitrogen loading in tile drained areas. Previous research has documented the parameterization and calibration of the RZWQM model at Nashua to simulate 35 management system effects on corn and soybean yields and N loading in tileflow from 1990 to 2003. As most management systems were studied for a 6 year period and in some cases weather had substantial impacts, a set of 30 alternative management systems were also simulated using a common 1974-2003 input climate dataset. To integrate an understanding of the economics of N management, we calculated net returns for all management systems using the DevTreks social budgeting tool. We ranked the 35 observed systems in the Facilitator decision support tool using N loading and net returns and found that rankings from simulated results were very similar to those from the observed results from both an onsite and offsite perspective. We analyzed the effects of tillage, crop rotation, cover crops, and N application method, timing, and amount for the 30 long term simulations on net returns and N loading. The primary contribution of this paper is an approach to creating a quality assured database of management effects on nitrogen loading and net returns for tile drained agriculture in the Mississippi Basin. Such a database would systematically extend data from intensively monitored agricultural fields to the larger area those fields represent.     

An innovation systems perspective on strengthening agricultural education and training in sub-Saharan Africa

This paper examines the role of postsecondary agricultural education and training (AET) in sub-Saharan Africa in the context of the region’s agricultural innovation systems. Specifically, the paper looks at how AET in sub-Saharan Africa can contribute to agricultural development by strengthening innovative capacity, or the ability of individuals and organisations to introduce new products and processes that are socially or economically relevant, particularly with respect to smallholder farmers who represent the largest group of agricultural producers in the region. The paper argues that while AET is conventionally viewed in terms of its role in building human and scientific capital, its also has a vital role to play in building the capacity of organisations and individuals to transmit and adapt new applications of existing information, new products and processes, and new organisational cultures and behaviours. The paper emphasizes the importance of improving AET systems by strengthening the innovative capabilities of AET organisations and professionals; changing organisational cultures, behaviours, and incentives; and building innovation networks and linkages. Specific recommendations in support of this include aligning the mandates of AET organisations with national development aspirations by promoting new educational programs that are more strategically attuned to the different needs of society; inducing change in the cultures of AET organisations through the introduction of educational programs and linkages beyond the formal AET system; and strengthening individual and organisational capacity by improving the incentives to forge stronger linkages between AET and diverse user communities, knowledge sources, and private industry.     

Using a role-playing game to inform the development of land-use models for the study of a complex socio-ecological system

We present an integrated methodology composed of a role-playing game on land adjudication from which we extract narrative and spatially explicit drivers of land-use decisions. We show how geographic information systems (GIS), qualitative decision-matrix analyses, a simple rule-based model using multi-criteria evaluations (MCE), and a machine learning-based land-transformation model (LTM) can be used harmoniously to study complex socio-ecological systems. We evaluate how each technique performs in the study of complex socio-ecological systems using a multi-tier framework detailing how each method analyzes the resource system, resource units, governance system, users and interactions and outcomes in the system. We show that each approach enhances our understanding of the land-use decision making process. Each method provides various information on the drivers of land-use decision, some focusing more on spatial components of socio-ecological systems (resource system and resource unit) and other having a strong emphasis on social mechanisms (governance system, users, interactions and outcomes). Furthermore, we shed light into the existence of a flow of information between the various methods enhancing our understanding of land-use drivers. We end with a discussion on methodological tradeoffs between models and the value of our more holistic approach to modeling land-use drivers and decisions.     

作物生长模型研究现状与展望

作物生长模型由最初的作物生长发育模型发展到农业决策支持模型,在科学研究、农业管理、政策制定等方面发挥着越来越重要的作用。本文首先回顾了作物生长模型的发展过程,并按照模型主要驱动因子,将作物生长模型分为土壤因子、光合作用因子和人为因子驱动3类并分别进行了归纳阐述;然后对典型的模型分别从模型模块、时空尺度、可模拟的作物类型等方面进行列表式对比;并对作物生长模型在气候变化评估、生产管理决策支持、资源管理优化等方面的应用,以及面临的极端条件、复杂农业景观和模型复杂度等挑战进行了总结,在此基础上认为遥感数据同化和孪生农场是其发展方向。     

Development and evaluation of an integrated simulation model for assessing smallholder crop-livestock production in Yucatán, Mexico

Mixed farming systems constitute a large proportion of agricultural production in the tropics, and provide multiple benefits for the world’s poor. However, our understanding of the functioning of these systems is limited. Modeling offers the best approach to quantify outcomes from many interacting causal variables in these systems. The objective of this study was to develop an integrated crop-livestock model to assess biophysical and economic consequences of farming practices exhibited in sheep systems of Yucatán state, Mexico. A Vensim™ dynamic stock-flow feedback model was developed to integrate scientific and practical knowledge of management, flock dynamics, sheep production, partitioning of nutrients, labor, and economic components. The model accesses sheep production and manure quantity and quality data generated using the Small Ruminant Nutrition System (SRNS), and interfaces on a daily basis with an Agricultural Production Systems Simulator (APSIM) model that simulates weather, crop, and soil dynamics. Model evaluation indicated that the integrated model adequately represents the complex interactions that occur between farmers, crops, and livestock.     

Online decision support for irrigation for farmers

Online decision support for irrigation has been available in Denmark since 1996. This paper describes an Internet implementation of a previous stand-alone PC-program; the Internet version has undergone several modifications and upgrades. The system has a morphological model for crop development based on temperature sums, and a hydrological model for calculating soil water balance. Weather data are supplied automatically from weather databases, precipitation data can be overrode by user inputs. Users can initiate the system with data on fields and crops, and add data on irrigations. Irrigation advice and explanation are provided in tables and graphics. The system had 322 active users in 2004 and 490 in 2005.     

Infusing the use of seasonal climate forecasting into crop management practice in North East Australia using discussion support software

Seasonal climate forecasting offers potential for improving management of crop production risks in the cropping systems of NE Australia. But how is this capability best connected to management practice? Over the past decade, we have pursued participative systems approaches involving simulation-aided discussion with advisers and decision-makers. This has led to the development of discussion support software as a key vehicle for facilitating infusion of forecasting capability into practice. In this paper, we set out the basis of our approach, its implementation and preliminary evaluation. We outline the development of the discussion support software Whopper Cropper, which was designed for, and in close consultation with, public and private advisers. Whopper Cropper consists of a database of simulation output and a graphical user interface to generate analyses of risks associated with crop management options. The charts produced provide conversation pieces for advisers to use with their farmer clients in relation to the significant decisions they face. An example application, detail of the software development process and an initial survey of user needs are presented. We suggest that discussion support software is about moving beyond traditional notions of supply-driven decision support systems. Discussion support software is largely demand-driven and can compliment participatory action research programs by providing cost-effective general delivery of simulation-aided discussions about relevant management actions. The critical role of farm management advisers and dialogue among key players is highlighted. We argue that the discussion support concept, as exemplified by the software tool Whopper Cropper and the group processes surrounding it, provides an effective means to infuse innovations, like seasonal climate forecasting, into farming practice.     

Fuzzy multi-objective linear programming applying to crop area planning

Crop area planning plays significant role in agricultural water management. During the planning, because of ambiguous or uncertain information caused by the vagueness of decision makers’ subjective preference or the uncertainty of objective information, conventional multi-objective linear programming (MOLP) model is not suitable for such decision-making in such fuzzy environment. In this study, we proposed the fuzzy multi-objective linear programming (FMOLP) model with triangular fuzzy numbers and transformed the FMOLP model and its corresponding fuzzy goal programming (FGP) problem to crisp ones which can be solved by the conventional programming methods. The FMOLP model was applied to crop area planning of Liang Zhou region, Gansu province of northwest China, and then the optimal cropping patterns under different water-saving levels and satisfaction grades for water resources availability of the decision makers (DM) were obtained. Compared to the MOLP model, the FMOLP model itself expresses the fuzzy information effectively, and its solutions can represent the DMs satisfactory degree of the subjective preference and propose alternative solutions for better decision support when applied in the crop area planning.