Uncertainty of the agricultural grey water footprint based on high resolution primary data
Bojacá, Carlos Ricardo
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The water footprint has been established as an indicator to assess water use by a product. However, the grey component of the water footprint (GWF) has received the least focus compared to the green and blue components. In developing countries, the GWF estimation is restricted by the availability of data concerning crop practices. The various biophysical and socioeconomic settings configure a system difficult to standardize even for small areas. The objective of this study was to assess the GWF uncertainty due to primary data for the main greenhouse tomato production from Colombia. The GWF for N and P fertilizers and pesticides were estimated based on detailed crop information collected from 2010 to 2013. The uncertainty was evaluated by fitting univariate theoretical distributions to the empirical distributions of the pollutants’ GWFs. Growers applied on average 419.2 and 201.9 kg ha−1 of N and P fertilizers per cycle, respectively. The average rates of application for fungicides and insecticides were 11.8 and 3.5 kg ha−1, respectively. The average GWF for N and P fertilizers and pesticides were 79, 6182.1 and 223.2 m3 t−1, respectively. The empirical distributions of the GWF for N fertilizer and pesticides were fitted to a lognormal distribution while for P fertilizer the Weibull distribution showed the best fit. The pesticides GWF showed the highest coefficient of variation (615.3%), however the results for N and P fertilizers were also high with values of 79.8 and 74.1%, respectively. Additional to the methodological choices involved in the GWF estimation, the primary data is a relevant uncertainty source, which should be considered for systems operating under unstandardized practices. The decision making process to regulate the pollutants losses from the agroecosystem, based on environmental assessments such as the GWF, should consider all sources of uncertainty and address its implications in a quantitatively form.
Link to resourcehttps://link.springer.com/article/10.1007/s11269-017-1674-x
- Año 2017 
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