Size optimization of constructed wetlands for phosphorus retention in agricultural areas

Sammanfattning: Eutrophication is one of the main threats to the Baltic Sea and Sweden is not expected to reach its environmental target of No Eutrophication by 2020. Phosphorus (P) lossfrom terrestrial systems is one of the principal causes of eutrophication in water recipients and the need to decrease P loss from agricultural land is pressing. One wayto reduce P losses from agricultural areas is by constructing wetlands (CW), with sedimentation as the primary process for P reduction. The efficiency of CWs is dependent on several factors regarding P load and hydraulic load (HL), which to a high degree is governed by CW area and shape as well as catchment area and land usedistribution. Today, the most common method of estimating catchment area is to use low-resolution topography maps. There is an increasing availability of digital elevationmodels (DEM) and databases that could aid the planning process of CWs by better estimating their catchment size and potential efficiency. The DEM of 2x2 m has been used to determine catchment areas of 39 CWs, showing that catchments are on average 8 % larger compared to earlier estimations based on low-resolution maps. Orthophotographs have been used to calculate current CW areas, to determine the ratio between wetland and catchment area (AW:AC). Using existing data on P accumulation in 8 previously studied CWs, the relation to several catchment and wetland factors was studied. Modelled runoff data from SMHI was used to calculate annual average, maximum and 95th percentiles of HL. Land use distribution in the associated catchments was determined using data from HELCOMs sixth pollution load compilation (PLC-6) as well as textural soil distributions of arable land from the Digital Arable Soil Map of Sweden (DSMS). The best modelledHL for estimation of P accumulation was long-term annual average (R2 = 0.93; p = 0.0006). However, trends were also found between accumulated P and other catchmentfactors. Multiple regression analyses showed that HL, AW:AC, and share of arable land within the catchment can be used to estimate CW efficiency in terms of potential P accumulated per CW area and year (R2 = 0.77; p = 0.03). However, the multiple regression analysis also showed that it is difficult to determine optimum values of studied parameters as they can compensate for one another. The result of the regression analysis was used to predict the P retention of a total of 39 CWs, showing a high variation of potential P accumulation, indicating the usefulness of estimating the potential P retention prior to construction to optimize CW size and location.