Integrating water quality responses to best management practices in Portugal
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Nutrient nonpoint pollution has a significant impact on water resources worldwide. The main challenge of this work was to assess the application of best management practices in agricultural land to comply with water quality legislation for surface waters. The Hydrological Simulation Program—FORTRAN was used to evaluate water quality of Ave River in Portugal. Best management practices (infiltration basin) (BMP) were applied to agricultural land (for 3, 6, 9, 12, and 15% area) with removal efficiencies of 50% for fecal coliforms and 30% for nitrogen, phosphorus, and biochemical oxygen demand. The inflow of water quality constituents was reduced for all scenarios, with fecal coliforms achieving the highest reduction between 5.8 and 28.9% and nutrients and biochemical oxygen demand between 2 and 13%. Biochemical oxygen demand and orthophosphates concentrations achieved a good water quality status according to the European Legislation for scenarios of BMP applied to 3 and 12% agricultural area, respectively. Fecal coliform levels in Ave River basin require further treatment to fall below the established value in the abovementioned legislation. This study shows that agricultural watersheds such as Ave basins demand special attention in regard to nonpoint pollution sources effects on water quality and nutrient loads.
KeywordsHSPF model Water quality modeling Nonpoint pollution source Best management practices
Vítor J.P. Vilar acknowledges the FCT Investigator 2013 Programme (IF/00273/2013). André R. Fonseca aslo acknowledges his doctoral fellowship (SFRH/BD/69654/2010) supported by FCT.
This work was financially supported by Project POCI-01-0145-FEDER-006984—Associate Laboratory LSRE-LCM funded by FEDER through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCT—Fundação para a Ciência e a Tecnologia. This work was also supported the R&D project INTERACT—Integrative Research in Environment, Agro-Chain and Technology—in its research line BEST, NORTE-01-0145-FEDER-000017, co-funded by FEDER/NORTE 2020 (Programa Operacional Regional do Norte 2014/2020). It was also supported by FEDER/COMPETE/POCI—Operational Competitiveness and Internationalization Programme, POCI-01-0145-FEDER-006958, and by FCT—Portuguese Foundation for Science and Technology, UID/AGR/04033/2013.
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