Abstract
The aim of this study is to evaluate the green, blue and grey water footprint (WF) of crops in the Duero river basin. For this purpose a spatial-explicit model, CWUModel, was developed. CWUModel is able to estimate the green and blue water consumed by crops and the water needed to assimilate the nitrogen leaching of fertilizer application. Thanks to the spatial analysis, blue water footprint has also been compared with the monthly water availability in the river basin, identifying the actual and future water stress level in different areas. By
incorporating economic criteria in the water footprint assessment, the water and land apparent productivity in agriculture was also estimated. A sensitivity analysis was developed to evaluate the effect of the uncertainty in the sources of information used on the predictions of the model.
The total WF of cereals in the Spanish Duero river basin was simulated in 9,473 Mm3/y (59% green, 19% blue and 21% grey). Cultivation of crops in rainfed lands is responsible of 5,548 Mm3/y of WF (86% green and 14% grey), whereas irrigated WF is established in 3,924 Mm3/y (20% green, 47% blue and 33% grey). Barley is the crop with the higher WF, with almost 37% of total, followed by wheat (17%). Although maize makes up 16% of the total WF of the basin, the blue and grey components reach the 36% of the total blue and grey WF of the basin.
Green water is also essential for irrigated crops such as long-cycle cereals, accounting for ore than 45% of their total water consumption. Nonetheless, blue water is a key omponent in the productivity of agriculture. The sustainability assessment shows that the lue WF of agriculture is responsible for water stress in 2-5 months of the year in the river bsin. The presumable expansion of irrigation in the next years could hamper the water anagement, despite being a relatively humid basin
incorporating economic criteria in the water footprint assessment, the water and land apparent productivity in agriculture was also estimated. A sensitivity analysis was developed to evaluate the effect of the uncertainty in the sources of information used on the predictions of the model.
The total WF of cereals in the Spanish Duero river basin was simulated in 9,473 Mm3/y (59% green, 19% blue and 21% grey). Cultivation of crops in rainfed lands is responsible of 5,548 Mm3/y of WF (86% green and 14% grey), whereas irrigated WF is established in 3,924 Mm3/y (20% green, 47% blue and 33% grey). Barley is the crop with the higher WF, with almost 37% of total, followed by wheat (17%). Although maize makes up 16% of the total WF of the basin, the blue and grey components reach the 36% of the total blue and grey WF of the basin.
Green water is also essential for irrigated crops such as long-cycle cereals, accounting for ore than 45% of their total water consumption. Nonetheless, blue water is a key omponent in the productivity of agriculture. The sustainability assessment shows that the lue WF of agriculture is responsible for water stress in 2-5 months of the year in the river bsin. The presumable expansion of irrigation in the next years could hamper the water anagement, despite being a relatively humid basin
| Original language | English |
|---|---|
| Title of host publication | Final EURO-AGRIWAT conference on Water Footprint of agricultural products: progress, challenges and solutions. Book of Abstracts |
| Editors | Joop Kroes, Pytrik Reidsma, Marius Heinen, Pieter van Oel, Johan Feenstra, Marjolijn Dannenburg, Ann-Marie Ryan |
| Publisher | COST |
| Pages | 20-20 |
| Publication status | Published - 2016 |
| Event | Final EURO-AGRIWAT conference: Water Footprint of agricultural products: progress, challenges and solutions - Orion Building, Wageningen, Netherlands Duration: 7 Mar 2016 → 9 Mar 2016 http://edepot.wur.nl/380126 |
Conference
| Conference | Final EURO-AGRIWAT conference: Water Footprint of agricultural products: progress, challenges and solutions |
|---|---|
| Country/Territory | Netherlands |
| City | Wageningen |
| Period | 7/03/16 → 9/03/16 |
| Internet address |
