The water pollution in areas with intensive agriculture is growing rapidly. Computer model is a tool which can help in finding solutions for water pollution reduction and help in creation of catchment management plans. In this research the SWAT model (Soil and Water Assessment Tool) was used to test the influence of introduction of permanent grasslands into the catchment on nitrate nitrogen load in surface water. Small catchment of upper Zgłowiączka River in central Poland with intensive agriculture was chosen as a test site. Model was fed with data about land use, soils, weather, elevation and management practices and calibrated and validated using flow data and nitrate nitrogen loads data. Then 2 scenarios with land use change were tested. A part of arable land was changed into permanent grasslands. The results show that permanent grasslands are effective in reducing nitrate nitrogen load. The load was reduced by 19% when permanent grasslands constituted 10% of arable land and by 38% with permanent grasslands taking up 20% of arable land.
Poland, like other EU countries, is obliged to implement the Water Framework Directive (2000/60/WE) by the end of 2015. The main objective of the Directive is to provide normative quality of all water resources (surface, underground and coastal sea waters). To reach this goal, reduction of water pollutant emission to the environment is needed. Our project focuses on pollution from agricultural sources which share in global pollution, which is high and growing. This is due to both intensification of agricultural activities and ignoring Agricultural Good Practice Code rules by farmers. In view of the above, this project is expected to provide analysis of selected catchments; especially those exposed to agricultural pollution risk, and propose adjustment strategies for new trends, still keeping in mind environment protection. Our project concerns the area further called "sensitive area" (according to the rules of Regional Water Management Board in Warsaw). A part of Zglowiaczka river catchments in central Poland was defined as sensitive area (125.3 km 2 ) where reduction of nitrogen and phosphorus run-off from agricultural land to water resources is especially needed. This is a typical agricultural district characterized by good soil quality (predominance of black swampy soil with deep and fertile humus layers). Due to this, it is the first and foremost high quality agricultural land, and almost forestless. The main topic of the research, with the use of the SWAT model, is to propose different means for reduction of migration of P and N to surface waters. Another problem is retention of water for actual and future irrigations. After model verification, calibration and validation, several climatic changes and reclamation strategies will be tested and simulated by the model to find the most effective and profitable solutions. The project focuses on supporting administration and selfgovernmental organization in the implementation of effective strategies of catchments management based on a modeling approach. This method enables analysis of trends and early warning system against excessive pollution load. Enhancement of the ecological education level and activation of local population for implementation of EU directives are also very important factors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.