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Abstract: Models that represent biophysical processes in hydrology, ecology and agricultural systems, when applied at specific locations, can make estimates with significant errors if meteorological input data are not representative of the sites. This is particularly important where the estimates from the models are used for decision support, strategic planning and policy development, due to the impacts of introduced uncertainty. This paper investigates the impacts of meteorological data sources on a cropping systems simulation model’s estimate of crop yield, and quantifies the uncertainty that arises when site-specific weather data are not available. In the UK, as elsewhere, many meteorological stations record precipitation and air temperature, but very few also record solar radiation, a key driving input data set. The impacts of using on-site observed precipitation and temperature with estimated solar radiation, and off-site entirely observed meteorological data was tested on the model’s yield estimates. This gave two scenarios: on-site observed versus partially modelled data; and on-site observed versus substitute data from neighbouring sites, for 24 meteorological stations in the UK. The analysis indicates that neighbouring meteorological stations can often be an inappropriate source of data. Of the 24 stations used, only 32% of the nearest neighbours were able to provide the best substitute off-site data. On-site modelled data provided better results than observed off-site data. The results demonstrate that the range of alternative data sources tested are capable of having both acceptable and unacceptable impacts on model performance across a range of assessment metrics, i.e. on-site data sources each produced yield over- or under-estimate errors greater than 2tha−1. A large amount of uncertainty can be introduced to the model estimates due to the data source. Therefore, the applications of models that represent biophysical process where meteorological data are required, need to include the quantification of input data errors and estimate of the uncertainty that imperfect data will introduce. [Copyright &y& Elsevier]

Abstract: This paper reports the outcomes of a deliberative workshop comparing land-use plans proposed by land-manager or domain experts with those derived using a computer-based decision support system (DSS). The DSS integrates four main components, a geographic information system, land-use systems simulation models, impact assessments and land-use planning tools. The land-use planning tools draw on the other components to generate and evaluate alternative patterns of land use and management. Since the land-use planning tools are based on multi-objective genetic algorithms (mGAs) it is possible to generate a range of alternative plans that define the structure of the trade-off between the objectives. The workshop tasked the delegates with specifying land-use plans that achieved the best compromise between two objectives known to be non-commensurable and conflicting. The nature of the best compromise was dependent on their individual perspectives. The delegates proposed allocations both as individuals and in researcher-facilitated sub-groups. The mGA allocations were then compared with those derived by delegates and were found to be broadly similar in performance. Differences in the range of allocations considered feasible were explained by the hard and soft constraints on allocations agreed between the delegates and articulated within the workshop process. The hypothesis that part of the difference in performance between the mGA and delegate allocations was due to the delegates blocking together fields with the same land use for convenience of management was proved. The analysis of the group allocations revealed that the decision-making process had failed to improve on the individual allocations. From these results it was concluded that there was a potential role for mGA based land-use planning tools in researching into, and deliberating on, the possible impacts of policy or other factors affecting land-use systems. It was further concluded that the tools should not be used in isolation since there was the need for stake-holder inputs to adequately define the range of feasible and practical land-use plans. [Copyright &y& Elsevier]