Search

The production of biogas from animal, crops, or urban waste benefits environmental-friendly energy production, and it is also beneficial for sustainable agricultural production through the use of liquid organic fertiliser as a source of organic matter. A number of systems are available for the transportation and application of the liquid organic fertiliser but detailed in-field operations planning tools are necessary to establish safe conclusions on the advantages and disadvantages of each application system. Here, an algorithmic approach for the operational planning of liquid organic fertiliser application using the umbilical system is developed and presented. The approach provides all the key operational parameters necessary for the evaluation of a selected operational scenario, together with the relative significance of the various part operations involved, taking into account attributes of the operating environment. The whole system has been built as a web-based decision support system tool. A set of results demonstrated the use of the tool for supporting decisions on the adoption of the umbilical system as an operational system for the application of the organic fertiliser. A second set of results demonstrated the use of the tool for comparing an umbilical system in terms of cost and time with a tanker system. The comparison between these two systems quantified the benefit of such field operation models to accurately simulate in-field machine activities and provide precise case-based data rather than average norm based evaluations of selected field operation systems.

[EN] In decision-making processes, reliability and risk aversion play a decisive role. This paper presents a framework for stochastic optimization of control strategies for groundwater nitrate pollution from agriculture under hydraulic conductivity uncertainty. The main goal is to analyze the influence of uncertainty in the physical parameters of a heterogeneous groundwater diffuse pollution problem on the results of management strategies, and to introduce methods that integrate uncertainty and reliability in order to obtain strategies of spatial allocation of fertilizer use in agriculture. A hydro-economic modeling approach is used for obtaining the allocation of fertilizer reduction that complies with the maximum permissible concentration in groundwater while minimizes agricultural income losses. The model is based upon nonlinear programming and groundwater flow and mass transport numerical simulation, condensed on a pollutant concentration response matrix. The effects of the hydraulic conductivity uncertainty on the allocation of nitrogen reduction among agriculture pollution sources are analyzed using four formulations: Monte Carlo simulation with pre-assumed parameter field, Monte Carlo optimization, stacking management, and mixed-integer stochastic model with predefined reliability. The formulations were tested in an illustrative example for 100 hydraulic conductivity realizations with different variance. The results show a high probability of not meeting the groundwater quality standards when deriving a policy from just a deterministic analysis. To increase the reliability several realizations can be optimized at the same time. By using a mixed-integer stochastic formulation, the desired reliability level of the strategy can be fixed in advance. The approach allows deriving the trade-offs between the reliability of meeting the standard and the net benefits from agricultural production. In a risk-averse decision making, not only the reliability of meeting the standards counts, but also the probability distribution of the maximum pollutant concentrations. A sensitivity analysis was carried out to assess the influence of the variance of the hydraulic conductivity fields on the strategies. The results show that the larger the variance, the greater the range of maximum nitrate concentrations and the worst case (or maximum value) that could be reached for the same level of reliability. © 2011 Elsevier Ltd., The study has been partially supported by the European Community 7th Framework Project GENESIS (226536) on groundwater systems and from the Plan Nacional I+D+I 2008-2011 of the Spanish Ministry of Science and Innovation (subprojects CGL2009-13238-C02-01 and CGL2009-13238-C02-02). The authors thank the anonymous reviewers for their suggestions for improving the paper.