Suitability of Sustainable Agricultural Drainage Systems for adapting agriculture to climate change
This paper presents a comprehensive and practical method for Sustainable Agricultural Drainage Systems (SADS) design. It is aimed at studying the suitability of using surface runoff as irrigation source. The method determines the optimum amount of surface runoff to be used for irrigation considering...
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Veröffentlicht in: | The Science of the total environment 2022-01, Vol.805, p.150319-150319, Article 150319 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This paper presents a comprehensive and practical method for Sustainable Agricultural Drainage Systems (SADS) design. It is aimed at studying the suitability of using surface runoff as irrigation source. The method determines the optimum amount of surface runoff to be used for irrigation considering both environmental constraints (aquifers recharge, discharge to natural water courses) and investment and operation costs. The developed method has been applied to the Spanish irrigation district “Villalar de los Comuneros Sector 1” located in Valladolid. The estimation of the optimum SADS provision was calculated for most of the major crops at the irrigation district highlighting that SADS facilities can reduce the amount of external provision of water for irrigation while maintaining the aquifer's recharge and the natural discharge to water courses. The simulations run for climate change forecasting scenarios (Representative Concentration Pathways, RCP, RCP45, RCP60, RCP85) showed that optimum SADS would reduce irrigation requirements and would increase natural fluxes (both aquifers and natural water courses) therefore improving the general water cycle in rural environments with productive agriculture.
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•The suitability of using surface runoff for reducing irrigation necessities in agriculture is studied.•Active and passive methods for making surface runoff available for crops have been analysed.•The results are consistent with both historical data and different climate change forecasting scenarios |
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ISSN: | 0048-9697 1879-1026 |
DOI: | 10.1016/j.scitotenv.2021.150319 |