التفاصيل البيبلوغرافية
| العنوان: |
Selective improvement of global datasets for the computation of locally relevant environmental indicators: A method based on global sensitivity analysis. |
| المؤلفون: |
Uwizeye, Aimable1,2,3 aimable.uwizeye@outlook.com, Gerber, Pierre J.1,2, Groen, Evelyne A.1, Dolman, Mark A.1,4, Schulte, Rogier P.O.3,4, de Boer, Imke J.M.1 |
| المصدر: |
Environmental Modelling & Software. Oct2017, Vol. 96, p58-67. 10p. |
| مصطلحات موضوعية: |
*ENVIRONMENTAL indicators, *SENSITIVITY analysis, *SUPPLY chains, *ATMOSPHERIC models, *DECISION making in environmental policy |
| مستخلص: |
Several global datasets are available for environmental modelling, but information provided is hardly used for decision-making at a country-level. Here we propose a method, which relies on global sensitivity analysis, to improve local relevance of environmental indicators from global datasets. This method is tested on nitrogen use framework for two contrasted case studies: mixed dairy supply chains in Rwanda and the Netherlands. To achieve this, we evaluate how indicators computed from a global dataset diverge from same indicators computed from survey data. Second, we identify important input parameters that explain the variance of indicators. Subsequently, we fix non-important ones to their average values and substitute important ones with field data. Finally, we evaluate the effect of this substitution. This method improved relevance of nitrogen use indicators; therefore, it can be applied to any environmental modelling using global datasets to improve their relevance by prioritizing important parameters for additional data collection. [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
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