Comparison and Evaluation of Model Structures for the Simulation of Pollution Fluxes in a Tile-Drained River Basin

Abstract

The European Union Water Framework Directive requires an integrated pollution prevention plan at the river basin level. Hydrological river basin modeling tools are therefore promising tools to support the quantification of pollution originating from different sources. A limited number of studies have reported on the use of these models to predict pollution fluxes in tile-drained basins. This study focused on evaluating different modeling tools and modeling concepts to quantify the flow and nitrate fluxes in the Odense River basin using DAISY-MIKE SHE (DMS) and the Soil and Water Assessment Tool (SWAT). The results show that SWAT accurately predicted flow for daily and monthly time steps, whereas simulation of nitrate fluxes were more accurate at a monthly time step. In comparison to the DMS model, which takes into account the uncertainty of soil hydraulic and slurry parameters, SWAT results for flow and nitrate fit well within the range of DMS simulated values in high-flow periods but were slightly lower in low-flow periods. Despite the similarities of simulated flow and nitrate fluxes at the basin outlet, the two models predicted very different separations into flow components (overland flow, tile drainage, and groundwater flow) as well as nitrate fluxes from flow components. It was concluded that the assessment on which the model provides a better representation of the reality in terms of flow paths should not only be based on standard statistical metrics for the entire river basin but also needs to consider additional data, field experiments, and opinions of field experts.

Applications of the SWAT Model Special Section: Overview and Insights

“…Other input data issues include uncertainties related to assumed half-life and other key pesticide properties , as well as a lack of accounting for septic tank effects (Aouissi et al, 2014). Hoang et al (2014) note that SWAT simulated overall accurate nitrate loads but that the model simulated twice as much nitrate transport via groundwater flow compared with tile drain flow, which is inconsistent with other studies in the region. They also state that inaccurate partitioning among flow components likely contributed to the weaker replication of daily nitrate fluxes.…”

“…However, the results presented by Hoang et al (2014) indicate that SWAT apparently underpredicted subsurface tile drainage flows. Fohrer et al (2014) also comment on the need to decouple SWAT tile drainage pesticide transport from subsurface lateral transport.…”

“…However, several studies explicitly state, or show via hydrograph comparisons, that daily and/or monthly peak flows were typically underestimated (Bieger et al, 2014;Boithias et al, 2014;Cerro et al, 2014;Fohrer et al, 2014;Hoang et al, 2014;Molina-Navarro et al, 2014;Pagliero et al, 2014;Santhi et al, 2014;Watson and Putz, 2014;Zabaleta et al, 2014). In contrast, some studies report overprediction of peak flows (Bieger et al, 2014;Hoang et al, 2014;Piniewski et al, 2014), weaknesses in seasonal representation of streamflows (Piniewski et al, 2014), or underprediction of low flow periods (Hoang et al, 2014). Hoang et al (2014) also note that SWAT accurately replicated measured daily hydrographs but overpredicted surface runoff and conversely underpredicted subsurface drainage flow.…”

“…These authors provide further insights regarding input data uncertainty and/or structural limitations of SWAT for their respective analyses. Cerro et al (2014), Hoang et al (2014), White et al (2014b), and Fohrer et al (2014) report mostly strong daily and monthly nutrient or pesticide baseline NSE statistics for their respective studies, the majority of which ranged from 0.37 to 0.88. Hoang et al (2014) note a weaker daily nitrate NSE of 0.37 for reasons discussed below.…”

“…Cerro et al (2014), Hoang et al (2014), White et al (2014b), and Fohrer et al (2014) report mostly strong daily and monthly nutrient or pesticide baseline NSE statistics for their respective studies, the majority of which ranged from 0.37 to 0.88. Hoang et al (2014) note a weaker daily nitrate NSE of 0.37 for reasons discussed below. Fohrer et al (2014) report stronger daily statistics for the pesticide Metazachlor (NSE = 0.68; R 2 = 0.62) compared with the pesticide Flufenacet (NSE = 0.13; R 2 = 0.51), but graphical comparisons indicate that simulation of both pesticides replicated overall measured trends.…”