NO3-N Loads Research Articles

Effectiveness of a newly reconstructed floodplain oxbow to reduce NO3-N loads from a spring flood

Enhancing NO3-N processing in floodplains offers opportunities to achieve water quality improvements in agricultural watersheds but few studies have quantified the effectiveness of newly reconstructed oxbows to reduce loads delivered from floods. In this study, we evaluated NO3-N retention during a spring storm water runoff event in a newly reconstructed oxbow (<1 year old) located along Morgan Creek in eastern Iowa. A 30-h flood connected the oxbow to the creek for approximately nine hours and delivered 14.7 kg of NO3-N into the oxbow. Using a NO3-N sensor, oxbow NO3-N concentrations were observed to increase from 0.7 to 5.3 mg/l after the flood event, but decreased to background conditions over the next 21 days. We estimated NO3-N retention to be 0.30 g N m−2 d−1 and the NO3-N retention efficiency to be 74.2% for the single flood event. The NO3-N mass reduction in the oxbow intersected with predicted mass reduction from a first-order denitrification decay model after 21 days which suggests that denitrification was largely responsible for the observed NO3-N decrease. However, the effectiveness of the oxbow for reducing watershed-scale N loads appears to be limited, since the oxbow is located in a low-nutrient floodplain and would only retain NO3-N loads when delivered to the oxbow via flooding. Study results suggest that oxbows provides valuable ecosystem services during non-flooding periods and are activated for NO3-N load reduction during floods.

Assessing uncertainty in annual nitrogen, phosphorus, and suspended sediment load estimates in three agricultural streams using a 21-year dataset.

Accurate estimation of constituent loads is important for studies of ecosystem mass balance or total maximum daily loads. In response, there has been an effort to develop methods to increase both accuracy and precision of constituent load estimates. The relationship between constituent concentration and stream discharge is often complicated, potentially leading to high uncertainty in load estimates for certain constituents, especially at longer-term (annual) scales. We used the loadflex R package to compare uncertainty in annual load estimates from concentration vs. discharge relationships in constituents of interest in agricultural systems, including ammonium as nitrogen (NH4-N), nitrate as nitrogen (NO3-N), soluble reactive phosphorus (SRP), and suspended sediments (SS). We predicted that uncertainty would be greatest in NO3-N and SS due to complex relationships between constituent concentration and discharge. We also predicted lower uncertainty with a composite method compared to regression or interpolation methods. Contrary to predictions, we observed the lowest uncertainty in annual NO3-N load estimates (relative error 1.5-23%); however, uncertainty was greatest in SS load estimates, consistent with predictions (relative error 19-96%). For all constituents, we also generally observed reductions in uncertainty by up to 34% using the composite method compared to regression and interpolation approaches, as predicted. These results highlight differences in uncertainty among different constituents and will aid in model selection for future studies requiring accurate and precise estimates of constituent load.

Influence of sampling frequency and load calculation methods on quantification of annual river nutrient and suspended solids loads.

Better management of water quality in streams, rivers and lakes requires precise and accurate estimates of different contaminant loads. We assessed four sampling frequencies (2days, weekly, fortnightly and monthly) and five load calculation methods (global mean (GM), rating curve (RC), ratio estimator (RE), flow-stratified (FS) and flow-weighted (FW)) to quantify loads of nitrate-nitrogen (NO3--N), soluble inorganic nitrogen (SIN), total nitrogen (TN), dissolved reactive phosphorus (DRP), total phosphorus (TP) and total suspended solids (TSS), in the Manawatu River, New Zealand. The estimated annual river loads were compared to the reference 'true' loads, calculated using daily measurements of flow and water quality from May 2010 to April 2011, to quantify bias (i.e. accuracy) and root mean square error 'RMSE' (i.e. accuracy and precision). The GM method resulted into relatively higher RMSE values and a consistent negative bias (i.e. underestimation) in estimates of annual river loads across all sampling frequencies. The RC method resulted in the lowest RMSE for TN, TP and TSS at monthly sampling frequency. Yet, RC highly overestimated the loads for parameters that showed dilution effect such as NO3--N and SIN. The FW and RE methods gave similar results, and there was no essential improvement in using RE over FW. In general, FW and RE performed better than FS in terms of bias, but FS performed slightly better than FW and RE in terms of RMSE for most of the water quality parameters (DRP, TP, TN and TSS) using a monthly sampling frequency. We found no significant decrease in RMSE values for estimates of NO3-N, SIN, TN and DRP loads when the sampling frequency was increased from monthly to fortnightly. The bias and RMSE values in estimates of TP and TSS loads (estimated by FW, RE and FS), however, showed a significant decrease in the case of weekly or 2-day sampling. This suggests potential for a higher sampling frequency during flow peaks for more precise and accurate estimates of annual river loads for TP and TSS, in the study river and other similar conditions.

Best management practices to reduce nitrate pollution in a rural watershed in Germany

Water pollution by nitrogen originates at diffuse and point sources. In surface aquatic systems, nitrate is one of the most problematic forms of nitrogen, causing phytoplankton and macrophyte growth and consequently water eutrophication. This study evaluated whether the Soil and Water Assessment Tool (SWAT) model can simulate nitrate load in a rural watershed in daily and monthly time increments. The study investigated 462 km² of the upper part of the Stör catchment, a typical rural lowland catchment located in Northern Germany. The results showed that simulations of nitrate load at monthly increments are better predictors of observed data than daily simulations. The most effective practices to minimize the NO3-N load were the reduction of nitrogen fertilizer application and the increasing of conservation areas, such as field filter strips.

Anthropogenic increases of catchment nitrogen and phosphorus loads in New Zealand

ABSTRACTSpatial regression models were used to predict yields (kg ha−1 yr−1) of nitrogen (N) and phosphorus (P) discharged from catchments throughout New Zealand under natural and current conditions. The models were derived using loads (kg yr−1) of TN, NO3-N, TP and DRP calculated for 592 river water quality monitoring sites. Anthropogenic increases in yields above natural levels were associated with the proportions of catchments occupied by the intensive agricultural land cover and were unevenly distributed across regions. Anthropogenic increases in national loads of TN, NO3-N, TP and DRP exported to the ocean were 74%, 159%, 48% and 18%, respectively. Increases in loads exported to the ocean varied considerably at smaller scales, with catchments having significant load increases between 4- and 26-fold for N and 6- to 9-fold for P. Predictions of yields and loads reported here have utility in the development of strategies to manage nutrients.

Tracking the fate of nitrate through pulse-flow wetlands: A mesocosm scale 15N enrichment tracer study

Quantitative information about the fate of applied nitrate (NO3-N) in pulse-flow constructed wetlands is essential for designing wetland treatment systems and assessing their nitrogen removal services for agricultural and stormwater applications. Although many studies have documented NO3-N losses in wetlands, controlled experiments indicating the relative importance of different processes and N sinks are scarce. In the current study, 15NO3-N isotope enrichment tracer experiments were conducted in wetland mesocosms of two different wetland soil types at two realistic agricultural NO3-N source loads. The 15N label was traced from the source NO3-N into plant biomass, soil (including organic matter and ammonium), and N-gas constituents over 7–10day study periods. All sinks responded positively to higher NO3-N loading. Plant uptake exceeded denitrification 2–3 fold in the low NO3-N loading experiments, while both fates were nearly equivalent in the high loading experiments. One to two years later, soils largely retained the assimilated tracer N, whereas plants had lost much of it. Results demonstrated that plant and microbial assimilation in the soil (temporary N sinks) can exceed denitrification (permanentN loss) in pulse-flow environments and must be considered by wetland designers and managers for optimizing nitrogen removal potential.

Modelling Nutrient Load Changes from Fertilizer Application Scenarios in Six Catchments around the Baltic Sea

The main environmental stressor of the Baltic Sea is elevated riverine nutrient loads, mainly originating from diffuse agricultural sources. Agricultural practices, intensities, and nutrient losses vary across the Baltic Sea drainage basin (1.75 × 106 km2, 14 countries and 85 million inhabitants). Six “Soil and Water Assessment Tool” (SWAT) models were set up for catchments representing the major agricultural systems, and covering the different climate gradients in the Baltic Sea drainage basin. Four fertilizer application scenarios were run for each catchment to evaluate the sensitivity of changed fertilizer applications. Increasing sensitivity was found for catchments with an increasing proportion of agricultural land use and increased amounts of applied fertilizers. A change in chemical fertilizer use of ±20% was found to affect watershed NO3-N loads between zero effect and ±13%, while a change in manure application of ±20% affected watershed NO3-N loads between zero effect and −6% to +7%.

Adaption of the AmaizeN model for nitrogen management in sweet corn (Zea mays L.)

Production of irrigated sweet corn on sandy soils requires ample N inputs and results in substantial leaching of nitrate to groundwater. The irrigation infrastructure of this system provides the opportunity for fertilizer additions throughout the season, opening the prospect for adaptive, real-time and site-specific management that might synchronize N availability with crop demand, minimizing leaching. This requires validated process-based and mechanistic simulations of the crop N budget and soil N cycling. We adapted the AmaizeN model to sweet corn, validated the model for groundwater NO3-N leaching estimation on sandy soils, and assessed the potential of model application for adaptive, in-season N management in this cropping system. The model was calibrated and tested with a two-season dataset by comparing predicted and measured leaf area index (LAI), above ground biomass (AGB), yield, and cumulative crop N uptake (CNUP). The model prediction and measurement comparisons yielded high coefficients of determination (R2, 0.82–0.95) and low root-mean-square errors (RMSE, 6.0–9.5%) for the whole range of the target crop attributes across years and wide-ranging N treatments. The difference between simulated and measured groundwater NO3-N loadings from lysimeter experiments ranged from 2.1–19.8% as relative absolute errors in 2014, and 1.7–7.2% in 2015. The adaptive N management strategy was proposed and demonstrated in a moderate-N treatment using the model prediction for real-time soil N availability and crop N demand dynamics. This approach significantly enhanced crop productivity by approximately 40% compared to conventional practice, while reducing N fertilizer inputs and NO3-N loading by 30–48% and 27–52%, respectively, relative to the highest N input treatments. The adaptive strategy shows potential to achieve target crop yields while minimizing NO3-N leaching.

Variability of nitrate-nitrogen load estimation results will make quantifying load reduction strategies difficult in Iowa

Many states within the Upper Mississippi River Basin are developing strategies to reduce nutrient loads to rivers. Reliable load estimation methods are needed to track progress toward nutrient reduction goals. We evaluated the variability of commonly used interpolation and extrapolation models to estimate nitrate-nitrogen (NO3-N) loads in 11 Iowa rivers. Results showed that the overall consistency between models of annual mean daily loads was low. Differences among the methods were particularly pronounced in May when the greatest NO3-N loads normally occur. The disparity in N load estimation among different methods is troubling given that states, federal agencies, or interest groups must have confidence in NO3-N load estimation procedures if the public is to believe that the load reductions strategies are working.

Water Quality Effects of Switchgrass Intercropping on Pine Forest in Coastal North Carolina

Abstract. Interplanting a cellulosic bioenergy crop (switchgrass, L.) between loblolly pine ( L.) rows could potentially provide a sustainable source of bio-feedstock without competing for land currently in food production. The objectives of this study were to: (1) quantify the concentrations and loads of drainage water nitrogen (N) and phosphorus (phosphate) associated with establishment and growth of switchgrass treatments and compare them with those for a mid-rotation pine forest (control), and (2) quantify the treatment effects on drainage water N and phosphate (IC) and switchgrass only (SG). Thinned mid-rotation loblolly pine with natural understory (MP) was used as the control. Pretreatment calibration equations for nutrients were obtained using a paired watershed approach and bootstrap geometric regression with 2007-2008 data, when pine on all sites had reached canopy closure. Treatment effects were calculated as the difference between expected values from the pretreatment relationship and measured data for the treatment period. Precipitation, outflow, and N and phosphate concentrations in the outflow were measured during calibration (Jan. 2007 to Dec. 2008), site preparation for switchgrass establishment (Nov. 2009 to Mar. 2012), and switchgrass growth (Apr. 2012 to Apr. 2014). Mean NO3-N concentrations and loads were significantly (a = 0.05) greater for SG than for IC during the switchgrass growth period. Average treatment concentrations with standard errors and total load effects during switchgrass growth for NO3-N followed the trends SG (-0.002 ±0.01 mg L-1) &amp;gt; IC (-0.12 ±0.04 mg L-1) and SG (0.75kg ha-1) &amp;gt; IC (0.23kg ha-1), respectively. For phosphate average concentrations and loads, the treatment effects during switchgrass growth followed the trends SG (-0.004 ± mg L-1) &amp;gt;IC ( -0.02 ± mg L-1) and IC (-0.43 kg ha-1) &amp;gt; SG (-0.70 kg ha-1), respectively. Average concentration effects for NO3-N and phosphate and total load effects for phosphate significantly (a = 0.05) decreased for IC compared to the MP control. These results suggest that the intercropping treatment (IC) with loblolly pine and switchgrass improved water quality by reducing NO3-N and phosphate concentrations and phosphate loads. Keywords: Bioenergy crop, Bootstrap geometric regression, Loblolly pine, Nutrients, Paired watershed.

Challenges in modelling of water quantity and quality in two contrasting meso-scale catchments in Poland

AbstractThis study presents an application of the SWAT model (Soil and Water Assessment Tool) in two meso-scale catchments in Poland (Upper Narew and Barycz), contrasting in terms of human pressures on water quantity and quality. The main objective was multi-variable and multi-site calibration and validation of the model against daily discharge, sediment and nutrient loads as well as discussion of challenges encountered in calibration phase. Multi-site calibration and validation gave varied results ranging from very good (daily discharge) to acceptable (sediment, nitrogen and phosphorus loads in most of gauges) and rather poor (individual gauges for all variables) in both catchments. The calibrated models enabled spatial quantification of water yield, sediment and nutrient loads, indicating areas of special concern in terms of pollution, as well as estimation of contribution of pollution from different sources, indicating agriculture as the most important source in both catchments. During the calibration process a number of significant issues were encountered: (i) global vs. local parametrization, (ii) simulation of different pools of water quality parameters in reservoirs and streams and (iii) underestimation of NO3-N loads in winter due to farmers practices. Discussion of these issues is hoped to aid SWAT model users in Poland in a deeper understanding of mechanisms of multi-variable and multi-site calibration.

Assessing an Enhanced Version of SWAT on Water Quantity and Quality Simulation in Regions with Seasonal Snow Cover

Winter soil-temperature simulations with soil and water assessment tool (SWAT) are generally inaccurate in snow-dominated areas of the word, because the existing empirically-based soil-temperature module in SWAT does not account for snow-insulation effects. This problem, in turn, leads to all subsequent projections including water flow and nutrient loading biased. To address this issue, a physically-based soil-temperature module was developed and incorporated into SWAT as an alternative to the empirical formulation, which was found generate better overall estimates of winter soil temperature in a previous study. In the current study, we continue to examine the modified version of SWAT performance on watershed modeling by making pairwise comparisons between the outputs from the original and modified versions of SWAT against related field measurements in a testing watershed. Results show that the physically-based soil-temperature formulation helps to dramatically improve SWAT estimations of base flow discharge and NO3-N loading for the watershed as a result of improvement in modeled winter soil temperatures. Compared with the original version of SWAT, the new version of SWAT predicted overall lower surface runoff and soil moisture content, as well as higher percolation and lateral flow in winter, resulting in clear differences in modeled flow paths and fate of chemical pollutants. Adding a physically-based treatment of soil temperature in SWAT is an important generalization that has potential of making the model more relevant to snow-dominated areas of the world.

Impacts of Watershed Characteristics and Crop Rotations on Winter Cover Crop Nitrate-Nitrogen Uptake Capacity within Agricultural Watersheds in the Chesapeake Bay Region.

The adoption rate of winter cover crops (WCCs) as an effective conservation management practice to help reduce agricultural nutrient loads in the Chesapeake Bay (CB) is increasing. However, the WCC potential for water quality improvement has not been fully realized at the watershed scale. This study was conducted to evaluate the long-term impact of WCCs on hydrology and NO3-N loads in two adjacent watersheds and to identify key management factors that affect the effectiveness of WCCs using the Soil and Water Assessment Tool (SWAT) and statistical methods. Simulation results indicated that WCCs are effective for reducing NO3-N loads and their performance varied based on planting date, species, soil characteristics, and crop rotations. Early-planted WCCs outperformed late-planted WCCs on the reduction of NO3-N loads and early-planted rye (RE) reduced NO3-N loads by ~49.3% compared to the baseline (no WCC). The WCCs were more effective in a watershed dominated by well-drained soils with increased reductions in NO3-N fluxes of ~2.5 kg N·ha-1 delivered to streams and ~10.1 kg N·ha-1 leached into groundwater compared to poorly-drained soils. Well-drained agricultural lands had higher transport of NO3-N in the soil profile and groundwater due to increased N leaching. Poorly-drained agricultural lands had lower NO3-N due to extensive drainage ditches and anaerobic soil conditions promoting denitrification. The performance of WCCs varied by crop rotations (i.e., continuous corn and corn-soybean), with increased N uptake following soybean crops due to the increased soil mineral N availability by mineralization of soybean residue compared to corn residue. The WCCs can reduce N leaching where baseline NO3-N loads are high in well-drained soils and/or when residual and mineralized N availability is high due to the cropping practices. The findings suggested that WCC implementation plans should be established in watersheds according to local edaphic and agronomic characteristics for reducing N leaching.

Calibration and validation of SWAT model for estimating water balance and nitrogen losses in a small agricultural watershed in central Poland

Abstract Soil and Water Assessment Tool (SWAT) ver. 2005 was applied to study water balance and nitrogen load pathways in a small agricultural watershed in the lowlands of central Poland. The natural flow regime of the Zgłowiączka River was strongly modified by human activity (deforestation and installation of a subsurface drainage system) to facilitate stable crop production. SWAT was calibrated for daily and monthly discharge and monthly nitrate nitrogen load. Model efficiency was tested using manual techniques (subjective) and evaluation statistics (objective). Values of Nash–Sutcliffe efficiency coefficient (NSE), coefficient of determination (R2) and percentage of bias for daily/monthly discharge simulations and monthly load indicated good or very good fit of simulated discharge and nitrate nitrogen load to the observed data set. Model precision and accuracy of fit was proved in validation. The calibrated and validated SWAT was used to assess water balance and nitrogen fluxes in the watershed. According to the results, the share of tile drainage in water yield is equal to 78%. The model analysis indicated the most significant pathway of NO3-N to surface waters in the study area, namely the tile drainage combined with lateral flow. Its share in total NO3-N load amounted to 89%. Identification of nitrogen fluxes in the watershed is crucial for decision makers in order to manage water resources and to implement the most effective measures to limit diffuse pollution from arable land to surface waters.

Crop rotation and Raccoon River nitrate

Previous research predicted that the biofuel-driven expansion of corn (Zea mays L.) area would increase riverine export of nitrate-nitrogen (NO3-N) in the Mississippi River Basin. Accurate information about water quality trends in agricultural watersheds is needed to better inform agricultural policy and to help quantify the effectiveness of field and landscape management practices. This study was designed to (1) characterize possible NO3-N trends within the Raccoon River watershed (RRWS) of central Iowa, and (2) explore links between the relative areas planted to corn and soybean (Glycine max) and water quality. We examined NO3-N concentration and loading data from more than 60 main stem river and tributary locations in the RRWS for the period 1999 to 2014. In addition, we assessed the role of climate, crop rotations, and simplified annual N budgets on NO3-N concentrations and loads to show that expansion of corn area has not increased Raccoon River NO3-N levels. Nitrate-N concentrations have not increased as corn area increased 19% and fertilizer N inputs increased 24% since 1999. We conclude that expansion of corn area at the expense of soybean may be affecting water quality. Better management of soybean in a corn–soybean rotation should reduce NO3-N export from the watershed, and reducing throughput of water in this artificially drained system will improve water quality.

Effect of variable annual precipitation and nutrient input on nitrogen and phosphorus transport from two Midwestern agricultural watersheds

Precipitation patterns and nutrient inputs affect transport of nitrate (NO3-N) and phosphorus (TP) from Midwest watersheds. Nutrient concentrations and yields from two subsurface-drained watersheds, the Little Cobb River (LCR) in southern Minnesota and the South Fork Iowa River (SFIR) in northern Iowa, were evaluated during 1996–2007 to document relative differences in timings and amounts of nutrients transported. Both watersheds are located in the prairie pothole region, but the SFIR exhibits a longer growing season and more livestock production. The SFIR yielded significantly more NO3-N than the LCR watershed (31.2 versus 21.3kgNO3-Nha−1y−1). The SFIR watershed also yielded more TP than the LCR watershed (1.13 versus 0.51kgTPha−1yr−1), despite greater TP concentrations in the LCR. About 65% of NO3-N and 50% of TP loads were transported during April–June, and <20% of the annual loads were transported later in the growing season from July–September. Monthly NO3-N and TP loads peaked in April from the LCR but peaked in June from the SFIR; this difference was attributed to greater snowmelt runoff in the LCR. The annual NO3-N yield increased with increasing annual runoff at a similar rate in both watersheds, but the LCR watershed yielded less annual NO3-N than the SFIR for a similar annual runoff. These two watersheds are within 150 km of one another and have similar dominant agricultural systems, but differences in climate and cropping inputs affected amounts and timing of nutrient transport.

Biological denitrification using poly(butanediol succinate) as electron donor

Poly(butanediol succinate) (PBS), a biodegradable polymer, was used as both solid carbon source and biofilm carrier for biological nitrate removal process, in which PBS was filled in a packed-bed bioreactor. The denitrification performance and the microbial diversity of biofilm attached on the surface of PBS were investigated. The experimental results showed that the volumetric denitrification rate was 0.60kgm(-3)day(-1) when NO3-N loading rate was 0.63kgm(-3)day(-1), and the average NO2-N concentration was below 0.20mgL(-1). The effluent pH value decreased slightly from a range of 6.98-7.87 to 6.46-7.18. The analysis of microbial community structure of biofilm by pyrosequencing method showed that Proteobacteria was the most abundant phylum (89.87%), and β-Proteobacteria represented the most abundant class. Among the 76 identified genera, Dechloromonas (10.26%), Alicycliphilus (9.15%), Azospira (8.92%), and Sinobacteraceae-uncultured (8.75%) were the abundant genera. PBS, as a promising alternative carbon source, is a suitable solid carbon source and biofilm carrier for nitrate removal.

Co-Kriging Estimation of Nitrate-Nitrogen Loads in an Agricultural River

Daily nitrate-nitrogen (NO3-N) loads in the Raccoon River, Iowa, were estimated using Ordinary kriging (OK), Cokriging (CK), and a standard rating curve method (LOADEST) based on a dataset of 3451 measurements of NO3-N concentration collected over 19 years. The CK estimation utilizes the temporal correlation of NO3-N load with daily discharge and honors the measured points to improve estimation relative to regression based models. Loads were estimated using the observed concentrations and three subsets of the measured data that correspond to three frequencies (weekly, biweekly, and monthly). Results indicated that daily NO3-N loads were best estimated by CK using measured loads with daily discharge. Daily load estimates produced by OK using weekly data matched well with measured values, but discrepancies emerged when samples were collected less frequently, e.g., biweekly and monthly. For the entire 19-year dataset, compared to measured loads, the estimated total NO3-N load decreased using OK when samples were collected monthly, but increased using CK. Load estimation using the seven-parameter LOADEST model did not perform well for the Raccoon River because the correlation of NO3-N concentration to river discharge was poor. For the site studied, weekly and biweekly sampling may be sufficient to estimate daily NO3-N loads with CK when daily discharge data is available.

Water and nonpoint source pollution estimation in the watershed with limited data availability based on hydrological simulation and regression model.

Nonpoint source (NPS) pollution is considered as the main reason for water quality deterioration; thus, to quantify the NPS loads reliably is the key to implement watershed management practices. In this study, water quality and NPS loads from a watershed with limited data availability were studied in a mountainous area in China. Instantaneous water discharge was measured through the velocity-area method, and samples were taken for water quality analysis in both flood and nonflood days in 2010. The streamflow simulated by Hydrological Simulation Program-Fortran (HSPF) from 1995 to 2013 and a regression model were used to estimate total annual loads of various water quality parameters. The concentrations of total phosphorus (TP) and total nitrogen (TN) were much higher during the flood seasons, but the concentrations of ammonia nitrogen (NH3-N) and nitrate nitrogen (NO3-N) were lower during the flood seasons. Nevertheless, only TP concentration was positively correlated with the flow rate. The fluctuation of annual load from this watershed was significant. Statistical results indicated the significant contribution of pollutant fluxes during flood seasons to annual fluxes. The loads of TP, TN, NH3-N, and NO3-N in the flood seasons were accounted for 58-85, 60-82, 63-88, 64-81% of the total annual loads, respectively. This study presented a new method for estimation of the water and NPS loads in the watershed with limited data availability, which simplified data collection to watershed model and overcame the scale problem of field experiment method.

Spatial Quantification of Non-Point Source Pollution in a Meso-Scale Catchment for an Assessment of Buffer Zones Efficiency

The objective of this paper was to spatially quantify diffuse pollution sources and estimate the potential efficiency of applying riparian buffer zones as a conservation practice for mitigating chemical pollutant losses. This study was conducted using a semi-distributed Soil and Water Assessment Tool (SWAT) model that underwent extensive calibration and validation in the Sulejów Reservoir catchment (SRC), which occupies 4900 km2 in central Poland. The model was calibrated and validated against daily discharges (10 gauges), NO3-N and TP loads (7 gauges). Overall, the model generally performed well during the calibration period but not during the validation period for simulating discharge and loading of NO3-N and TP. Diffuse agricultural sources appeared to be the main contributors to the elevated NO3-N and TP loads in the streams. The existing, default representation of buffer zones in SWAT uses a VFS sub-model that only affects the contaminants present in surface runoff. The results of an extensive monitoring program carried out in 2011–2013 in the SRC suggest that buffer zones are highly efficient for reducing NO3-N and TP concentrations in shallow groundwater. On average, reductions of 56% and 76% were observed, respectively. An improved simulation of buffer zones in SWAT was achieved through empirical upscaling of the measurement results. The mean values of the sub-basin level reductions are 0.16 kg NO3/ha (5.9%) and 0.03 kg TP/ha (19.4%). The buffer zones simulated using this approach contributed 24% for NO3-N and 54% for TP to the total achieved mean reduction at the sub-basin level. This result suggests that additional measures are needed to achieve acceptable water quality status in all water bodies of the SRC, despite the fact that the buffer zones have a high potential for reducing contaminant emissions.