Environmental And Agricultural Modelling

Agriculture increasingly faces the challenge of balancing its multiple functions in a sustainable way. Integrated assessment and modelling (IAM) can provide insight into the potential impacts of policy changes. However, concepts to address the wide range of issues and functions typical for agriculture are still scarce. Environmental and Agricultural Modelling reviews and presents our current understanding of integrated and working tools to assess and compute, ex-ante, alternative agricultural and environmental policy options, allowing: 1. Analysis at the full range of scales (farm to European Union and global) whilst focusing on the most important issues emerging at each scale; 2. Analysis of the environmental, economic and social contributions of agricultural systems towards sustainable rural development and rural viability; 3. Analysis of a broad range of issues and agents of change, such as climate change, environmental policies, rural development options, effects of an enlarging EU, international competition, and effects on developing countries.

Recent developments in computer science, data mining and big data analytics have resulted in new operational frameworks in agriculture, food and the environment, which in fact, share a strong link between them. A key challenge for researchers is to extract new data patterns and utilize them in decision making. Managers, policy makers, and practitioners have to be aware of these methodologies in order to establish efficient and effective working groups for the tasks to be resolved. The book reviews the complexity of the interrelationship between agriculture, food production and processing, and environmental issues. It also highlights the prospects of modeling in various cases of problem solving in these sectors, and reviews the new and future challenges. Consumer awareness in food production and processing practices is continually increasing and the necessity for advanced behavioural tools follows the same trend. Furthermore, the value chain management challenge is becoming one of the most crucial tasks due to the increased importance of new parameters like the origin of products, its environmental footprint and the enhancement of local production, etc. The book addresses these topics in a holistic approach, merging modeling with advanced marketing practices in a coherent and innovative manner, being an effective tool in a continuously demanding world.

Food Systems Modelling emphasizes sustainability, including the impact of agriculture and food production on profits, people and environment, with a particular focus on the ability of humanity to continue producing food in the midst of global environmental change. Sections introduce the purpose of models, the definition of a food system, the importance of disciplinary, interdisciplinary, and transdisciplinary inquiry, cover specific branches of modeling in the sustainability of food systems, and wrestle with the challenge of communicating modeling research and appropriately integrating multiple dimensions of sustainability. This book will be a welcomed reference for food scientists, agricultural scientists, nutritionists, environmental scientists, ecologists, economists, those working in agribusiness and food supply chain management, community and public health, and urban and regional planning, as well as academicians and graduate students interested in the sustainability of food systems. Emphasizes sustainability, including the impact of agriculture and food production on profits Focuses on the ability of humanity to continue producing food in the midst of global environmental change Deciphers what models can teach us about food system sustainability

Systems Analysis and Modeling in Food and Agriculture is a component of Encyclopedia of Food and Agricultural Sciences, Engineering and Technology Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Systems analysis and modeling is being used increasingly in understanding and solving problems in food and agriculture. The purpose of systems analysis is to support decisions by emphasizing the interactions of processes and components within a system. Frequently investigated systems level questions in agriculture and food are relevant to the 6 E's: Environment, Energy, Ecology, Economics, Education, and Efficiency. The theme on Systems Analysis and Modeling in Food and Agriculture with contributions from distinguished experts in the field provides information on key topics related to food and agricultural system. The coverage include an overview of food system; system level aspects related to energy, environment, and social/policy issues; knowledge bases and decision support; computer models for crops, food processing, water resources, and agricultural meteorology; collection and analysis methods for data from field experiments; use of models and information systems. This volume is aimed at the following a wide spectrum of audiences from the merely curious to those seeking in-depth knowledge: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.

Modeling Environmental Policy demonstrates the link between physical models of the environment and policy analysis in support of policy making. Each chapter addresses an environmental policy issue using a quantitative modeling approach. The volume addresses three general areas of environmental policy - non-point source pollution in the agricultural sector, pollution generated in the extractive industries, and transboundary pollutants from burning fossil fuels. The book concludes by discussing the modeling efforts and the use of mathematical models in general.

This book will help decision makers model nature-based solutions to the complex problem of sustainable development, locally and globally.

Crop modelling has huge potential to improve decision making in farming. This collection reviews advances in next-generation models focused on user needs at the whole farm system and landscape scale.

Mathematical models are being used more and more widely to study complex dynamic systems (global weather, ecological systems, hydrological systems, nuclear reactors etc. including the specific subject of this book, crop-soil systems). The models are important aids in understanding, predicting and managing these systems. Such models are complex and imperfect. One fundamental research direction is to seek a better understanding of how these systems function, and to propose mathematical expressions embodying that understanding. However, this is not sufficient. It is also essential to have tools (often mathematical and statistical methods) to aid in developing, improving and using the models built from those equations. The book is specifically concerned with the application of methods to crop models, but much of the material is also applicable to dynamic system models in other fields. The goal of this book is to fill that gap. * State-of-the-art methods explained simply and illustrated specifically for crop models * Parameter estimation – applying statistical methods to the complex case of crop models, including Bayesian methods * Includes model evaluation, understanding and estimating prediction error * Offers a unique data assimilation by using the Kalman filter and beyond