A CommonKADS Model Framework for Web Based Agricultural Decision Support System

Increased demand of farm products and depletion of natural resources compel the agriculture community to increase the use of Information and Communication Technology (ICT) in various farming processes. Agricultural Decision Support Systems (DSS) proved useful in this regard. The majority of available Agricultural DSSs are either crop or task specific. Less emphasis has been placed on the development of comprehensive DSS, which are non-specific regarding crops or farming processes. The crop or task specific DSSs are mainly developed with rule based or knowledge transfer based approaches. The DSSs based on these methodologies lack the ability for scaling up and generalization. The Knowledge engineering modeling approach is more suitable for the development of large and generalized DSS. Unfortunately the model based knowledge engineering approach is not much exploited for the development of Agricultural DSS. CommonKADS is one of the popular modeling frameworks used for the development of Knowledge Based System (KBS). The paper presents the organization, agent, task, communication, knowledge and design models based on the CommonKADS approach for the development of scalable Agricultural DSS. A specific web based DSS application is used for demonstrating the multi agent CommonKADS modeling approach. The system offers decision support for irrigation scheduling and weather based disease forecasting for the popular crops of India. The proposed framework along with the required expert knowledge, provides a platform on which the larger DSS can be built for any crop at a given location

Application of Large-Scale, Multi-Resolution Watershed Modeling Framework Using the Hydrologic and Water Quality System (HAWQS)

In recent years, large-scale watershed modeling has been implemented broadly in the field of water resources planning and management. Complex hydrological, sediment, and nutrient processes can be simulated by sophisticated watershed simulation models for important issues such as water resources allocation, sediment transport, and pollution control. Among commonly adopted models, the Soil and Water Assessment Tool (SWAT) has been demonstrated to provide superior performance with a large amount of referencing databases. However, it is cumbersome to perform tedious initialization steps such as preparing inputs and developing a model with each changing targeted study area. In this study, the Hydrologic and Water Quality System (HAWQS) is introduced to serve as a national-scale Decision Support System (DSS) to conduct challenging watershed modeling tasks. HAWQS is a web-based DSS developed and maintained by Texas A & M University, and supported by the U.S. Environmental Protection Agency. Three different spatial resolutions of Hydrologic Unit Code (HUC8, HUC10, and HUC12) and three temporal scales (time steps in daily/monthly/annual) are available as alternatives for general users. In addition, users can specify preferred values of model parameters instead of using the pre-defined sets. With the aid of HAWQS, users can generate a preliminarily calibrated SWAT project within a few minutes by only providing the ending HUC number of the targeted watershed and the simulation period. In the case study, HAWQS was implemented on the Illinois River Basin, USA, with graphical demonstrations and associated analytical results. Scientists and/or decision-makers can take advantage of the HAWQS framework while conducting relevant topics or policies in the future

DEVELOPMENT OF EXPERT SYSTEMS FOR THE MITIGATION OF NITROGEN POLLUTION AT FARM AND REGIONAL SCALE

Intensive agriculture and concentration of livestock activities represent critical factors in the environment, particularly in Lombardia region where nitrate vulnerable zones constitute 62% of Utilized Agricultural Area (UAA). In addition, the aquifer Po valley aquifer is one of the largest in Europe, for which it is estimated that over two-thirds of the nitrogen that reaches the surface and the subsoil is of agricultural origin. The problem of reduction of nitrogen losses into the environment, as leaching of nitrates into groundwater and ammonia emissions into atmosphere, can be only addressed through a critical and scientific analysis of manure entire production chain. As a consequence, the opportunity to develop software tools to analyze the current situation and the effects of possible scenarios arising from different regional policies relating to the release of nitrogen from agricultural sources. A decision support system (DSS) has been developed, to run simulation both at farm and territorial scale. The farm simulator is aimed at farmers and allows to analyze the management and technological alternatives available for the entire supply chain from animal feed to the distribution in the field for maximum utilization of the livestock waste. It is a free software downloaded from the website of the Lombardia Region, which collects the data of the structure and management of farm in the regional database; the speed of execution and the interface easily understandable make it "user friendly". The territorial simulator, available to regional authorities, works on a regional scale it is completely resident on the web and allows the evaluation of the impact of any regulatory measures and incentives simulated from the agronomic, environmental and economic point of view. Below, has been analyzed the regional database and have been drawn up reference tables, were also collected, reviewed and made consistent models already existing and validated for the various phases of manure production. Were then assessed and defined the agronomic, plant and economic alternatives. The basic unit of simulation is made by the single cadastral parcel; in case of a territorial scale simulation model is applied to all the parcels of the sample selected. The DSS provides data both in detail and in the form of synthetic indicators. In the first months of activity the DSS at farm scale, introduced in November 2011, has been used by 200 users of which around 65% are professional agronomists and farmers of large companies; therefore it represents an important opportunity for the Lombardia agriculture to combine environmental protection with economic and technical sustainability

MODELING AND MANAGEMENT OF WATER QUANTITY AND QUALITY IN COLD-CLIMATE PRAIRIE WATERSHEDS

Saskatchewan’s surface and ground water sources are vital to life in the province, not only as the supply of safe drinking water for the residents, but also as a key driver of economic activity. The Qu'Appelle and Assiniboine River Basins are among the highly valued water resources in the province as they supply water for more than one-third of the population of Saskatchewan and contain a chain of eight lakes that are major recreational and economically valued resources in the region. The health of several watersheds within these highly valued river basins is being degraded by intensive agricultural and other developmental activities. The decision making processes for sustainable water management in these watersheds is stunted by limited observed field data. As a result, for Saskatchewan watersheds in general, and the Qu’Appelle and Assiniboine River Basins in particular, a better understanding is required of the type, extent and sources of pollutant loadings, and effects of potential alternative management practices may have to mitigate water quality problems. Modeling approaches that have the capacity to analyze the quantity and quality of water resources, identify existing and potential watershed stressors, and the relative importance of best management options are therefore needed. With the intention of helping decision makers in the province, this thesis focuses on developing an eco-hydrological model, which is suitable for Canadian prairie watersheds and capable of simulating the long term effects of management practices. Following a review of several models, the Soil and Water Assessment Tool (SWAT) has been selected for this study. In order achieve the objectives, the SWAT model has been modified to suit site specific characteristics of the Canadian prairies. The first such modification was to incorporate the numerous landscape depressions that vary in storage capacity into SWAT. This was done by representing depression storage heterogeneity using a probability distribution using an algorithm called “Probability Distributed Landscape Depressions (PDLD)”. The modified model, called SWAT-PDLD, was tested over two prairie watersheds: the Assiniboine and Moose Jaw watersheds. An improved simulation for streamflow was achieved for both case study watersheds as compared to the original SWAT lumped storage approach. The other modification to SWAT was the incorporation of seasonally varying soil erodibility due to the cold climate conditions. This was done using a sediment module with a time variant soil erodibility factor that allows the value of soil erodibility to vary between seasons. The modified SWAT-PDLD along with seasonally varying soil erodibility was tested for sediment export simulation for the same two case study watersheds: the Assiniboine and Moose Jaw watersheds. Results show an improved sediment simulation for both case study watersheds when seasonally varying soil erodibility factors are considered as compared to the original SWAT model sediment module, which uses annual values of soil erodibility. The modified model was also used to simulate phosphorous and nitrogen export from the Assiniboine watershed and a satisfactorily model performance was obtained. In addition, the developed model was used to assess the impacts of three different management practices on the export of pollutants for the Assiniboine watershed. The scenarios considered were conservation tillage, a cover crop, and filter strips. Model results show that both the filter strips and cover crops decreased sediment, phosphorous, and nitrogen export, while conservation tillage increased phosphorous export in the study watershed. Finally, the study investigated the different sources of modeling uncertainty for the developed model. Parameter as well as precipitation, observed discharge, and model structure uncertainty of the SWAT-PDLD model was evaluated. Parameter uncertainty was quantified using three different techniques that include GLUE, ParaSol, and SUFI-2. Model structure uncertainty was assessed using a framework that combines the Bayesian Model Averaging (BMA) and Shuffled Complex Evolution (SCE). Results suggest that ignoring either input error or model structure uncertainty will lead to unrealistic model simulations and incorrect uncertainty bounds. The study also shows that prediction uncertainty bounds, posterior parameter distribution, and final parameter values vary between methods

INTEGRATED TERRITORIAL APPROACH FOR SUSTAINABLE AGRICULTURE: NITROGEN MANAGEMENT AND SOIL CARBON SEQUESTRATION IN LOMBARDY REGION

In the last years, intensive agriculture and high concentration of livestock activities have become two important environmental concerns, being partially responsible of nitrogen pollution and CO2 emissions caused by carbon loss from soil. That\u2019s particularly true in Lombardy region, due to the presence of more than 27% of cattle and 51% of pigs of the national livestock and due to the extent of area devoted to cereal cropping (about 63% of the utilized agricultural area - UAA). It is also to be remarked that cereals in Lombardy are commonly grown in continuous cropping systems. In this context, the aim to encourage sustainable agriculture led European Union to introduce regulations (e.g. Nitrates Directive 91/676/EEC), to define mandatory standards, and measures (Common Agricultural Policy), to promote the implementation of best management practices. Consequently, assessing the potential effects of different policies, prior to their introduction, has become very important. Several methods (direct measurements, simulation models, simple and composite indicators) have been developed and applied by traditional agronomic research, however there is still a need of up-scaling experimental results from the farm to the landscape scale. Moreover, it has to be taken into account that the impact of these measures also depends on the interaction between type of action, pedo-climatic factors and farm characteristics. An effective tool for territorial management and planning is then particularly needed in Lombardy, since the territorial approaches, supported by robust methodologies (e.g., extensive databases, models and geographical information systems (GIS)), have become more and more central in European policies. The aim of this work is to assess and investigate the important outcomes of a more territorially based approach, analysing the most important environmental issues, related to agriculture in Lombardy: manure management, nitrogen leaching and carbon sequestration by soils. Three examples of tools and applications are presented: i) Decision Support System (DSS) ValorE, to analyse and to evaluate manure management and technological alternatives, available for the entire supply chain from animal feed to the distribution in the field; ii) application of the ARMOSA cropping system simulation model to assess the potential risk of nitrate leaching towards groundwater in 3 Nitrate Vulnerable Zones (NVZs); iii) application of ARMOSA to evaluate carbon sequestration capacity of regional soils, under current and alternative scenarios, focusing the attention on the impact of different spread levels of conservation agriculture. The territorial approach proposed in this thesis, was based on robust methodologies, extensive databases, stand-alone models (e.g. ARMOSA), more complex structures (ValorE DSS) and GIS techniques. All these components led this approach to be an effective solution for investigating and supporting the regional agricultural management, as well as for assessing the potential impact of the regional policies, always keeping in mind that agricultural sector plays a key role in the climate change mitigation and in the environmental protection from biodiversity loss and from N pollution