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Controlled drainage (CD), sometimes called drainage water management, is a practice whereby the drainage system outflow is managed during specific periods to retain more water in the field. Although CD has been shown to reduce downstream nitrate-N (NO3--N) load, seasonal patterns have been less consistent which can potentially impact the effectiveness of conservation practices. The main objective of this study was to assess the regional and seasonal impact of conventional free drainage (FD) and CD on drainage flow and nitrate-N load. Using experimental data from ongoing and historical CD experiments across the Corn Belt and in North Carolina, we evaluated subsurface drain flow, nitrate-N load, and performance of CD systems. Across the data set and regions, there was little difference in annual flow from FD conditions. Seasonally, more northern and western sites experienced a greater percentage of the annual flow occurring in the spring. There was no nitrate-N concentration reduction with CD. Flow and nitrate-N load reductions with CD did not vary by plant hardiness zone across the region, but the season with the greatest reduction did shift from winter to spring moving north and west in the study area. Absolute flow reductions (in mm) were similar regardless of precipitation category. Consequently, the percent reduction was lower as the amount of precipitation (category) increased. Overall, this analysis found CD to be an effective practice for reducing drain flow and nitrate-N loading directly delivered by the drains to downstream water bodies across the region.

Controlled drainage (CD) has recently been proposed as a best management practice for reducing nutrient export from drained cropland in the U.S. Midwest to the Mississippi River and the Gulf of Mexico. We conducted a 25-year simulation study using the hydrological model, DRAINMOD, and the carbon and nitrogen (N) model, DRAINMOD-NII, to evaluate the performance of CD at 48 locations across the U.S. Midwest. Hydrological and Nitrogen predictions of this simulation study were compared to RZWQM-DSSAT predictions by Thorp et al. (2008) . Simulation results showed that CD reduced annual subsurface drainage by 86 mm (30%) and annual N drainage losses by 10.9 kg N ha−1 (32%), on average over the 48 sites. DRAINMOD predicted highest reductions in drain flow at the south and southeast locations and lowest reductions at the northwest locations. The large reductions in drain flow in the south and southeast locations resulted in a large increase in surface runoff, which could increase soil erosion and sediment transport to surface water. In the north and northwest locations, the smaller amount of water that did not pass through the drainage system because of CD was primarily lost as evapotranspiration. DRAINMOD-NII predictions of annual reductions in N drainage loss followed the same trend of annual reductions in drainage flow. DRAINMOD-NII predictions show that reductions in N drainage loss under CD were mainly attributed to increase in denitrification. The declining trend in predicted annual denitrification from the southern to the northern locations of the Midwest region is most likely attributed to the lower temperature and less precipitation at the northern locations. RZWQM-DSSAT predicted reductions in annual drainage and N loss under CD conditions showed a similar trend to DRAINMOD/DRAINMOD-NII predictions. RZWQM-DSSAT, however, predicted substantially higher reductions in both drain flow (regional average of 151 mm yr−1, 53%) and N drainage losses (regional average of 18.9 kg N ha−1 yr−1, 51%). The discrepancies between DRAINMOD/DRAINMOD-NII and RZWQM-DSSAT predictions of annual reductions in drain flow and N loss under CD conditions were caused by differences in model predictions of individual components of the water and nitrogen balances under both free drainage and controlled drainage scenarios. Overall, this simulation study showed that climate variation across the region has a substantial impact on CD efficacy for reducing N drainage loss.

Controlled drainage (CD) has been identified as a sustainable management practice whereby more soil water can be conserved and less nutrients are leached; alongside its potential benefit of alleviating drought stress and increasing yield. More than 12 million hectare of cropland in the US Midwest are suitable for implementing CD; however, the effectiveness of the practice can vary across the region with the variation in environmental conditions and management practices. The main objective of this study is to evaluate the performance of the integrated agro-ecosystem model; DRAINMOD-DSSAT, for simulating the effects of CD on drainage flow, nitrogen losses via drainage water and crop yield. Herein, we utilized a 4-yr dataset (2006–2009) that was collected from a corn–soybean cropping system near Story City, Iowa. This site was artificially drained under free drainage (FD) and CD treatments. The model was calibrated using the data collected from the FD plots, and validated for the CD plots. DRAINMOD-DSSAT predictions of drainage flow and nitrate-nitrogen (NO3-N) losses were in good agreement with measured values under FD and CD, with the former treatment showed slightly better performance. The modeling efficiencies (NSE’s) for simulating monthly drainage flows were 0.81 and 0.60 for FD and CD, respectively. Monthly NO3–N mass losses were simulated with NSE’s of 0.76 and 0.66 for FD and CD, respectively. DRAINMOD-DSSAT well simulated CD-induced percent reductions in annual drainage flow (measured = 24.6%, simulated = 27.1%), and NO3-N losses (measured = 34.8%, simulated = 33.5%). Low percent error (PE) values were associated with the model predictions of corn yields (−1.3 ≤ PE ≤ 1.3) and soybean yields (−6.0 ≤ PE ≤ 12.6). Overall, results obtained from this relatively short-term modeling study demonstrated the potential use of DRAINMOD-DSSAT as a management design tool. Yet, further model testing CD effectiveness under different conditions is critically needed to establish a higher credibility in model predictions and to allow for further model improvement and expansion.

HERMES is a widely used agricultural system model; however, it has never been tested for simulating N loss to subsurface drainage. Here, we integrated a simple drain flow component into HERMES. We then compared the predictions to four years of data (2002–2005) from central Iowa fields in corn-oybean with winter rye as a cover crop (CC) and without winter rye (NCC). We also compared the HERMES predictions to the more complex Root Zone Water Quality Model (RZWQM) predictions for the same dataset. The average annual observed and simulated N loss to drain flow were 43.8 and 44.4 kg N/ha (NCC) and 17.6 and 18.9 kg N/ha (CC). The slightly over predicted N loss for CC was because of over predicted nitrate concentration, which may be partly caused by slightly under predicted average annual rye shoot N (observed and simulated values were 47.8 and 46.0 kg N/ha). Also, recent research from the site suggests that the soil field capacity may be greater in CC while we used the same soil parameters for both treatments. A local sensitivity analysis suggests that increased field capacity affects HERMES simulations, which includes reduced drain flow nitrate concentrations, increased denitrification, and reduced drain flow volume. HERMES-simulated cumulative monthly drain flow and annual drain flow were reasonable compared to field data and HERMES performance was comparable to other published drainage model tests. Unlike the RZWQM simulations, however, the modified HERMES did not accurately simulate the year to year variability in nitrate concentration difference between NCC and CC, possibly due in part to the lack of partial mixing and displacement of the soil solution. The results suggest that 1) the relatively simple model HERMES is a promising tool to estimate annual N loss to drain flow under corn-soybean rotations with winter rye as a cover crop and 2) soil field capacity is a critical parameter to investigate to more thoroughly understand and appropriately model denitrification and N losses to subsurface drainage.

The Midwestern United States, a region that produces one-third of maize and one-quarter of soybean grain globally, is projected to experience increasing rainfall variability. One approach to mitigate climate impacts is to utilize crop and soil management practices that enhance soil water storage and reduce the risks of flooding as well as drought-induced crop water stress. While some research indicates that a winter cover crop in maize-soybean rotations increases soil water availability, producers continue to be concerned that water use by cover crops will reduce water for a following cash crop. We analyzed continuous in-field soil water measurements from 2008 to 2014 at a Central Iowa research site that has included a winter rye cover crop in a maize-soybean rotation for thirteen years. This period of study included years in the top third of the wettest on record (2008, 2010, 2014) as well as drier years in the bottom third (2012, 2013). We found the cover crop treatment to have significantly higher soil water storage at the 0–30 cm depth from 2012 to 2014 when compared to the no cover crop treatment and in most years greater soil water content on individual days analyzed during the cash crop growing season. We further found that the cover crop significantly increased the field capacity water content by 10–11% and plant available water by 21–22%. Finally, in 2013 and 2014, we measured maize and soybean biomass every 2–3 weeks and did not see treatment differences in crop growth, leaf area or nitrogen uptake. Final crop yields were not statistically different between the cover and no cover crop treatment in any of the seven years of this analysis. This research indicates that the long-term use of a winter rye cover crop can improve soil water dynamics without sacrificing cash crop growth in maize-soybean crop rotations in the Midwestern United States.

Using chlorophyll meters, crop sensors, or aerial photography to fine-tune sidedress N application rates have been proposed for optimizing and perhaps reducing overall N fertilizer use on corn ( Zea mays L.) and thereby improving water quality by reducing NO 3 losses to surface and ground waters. However, numerous studies have shown that a range of sensors are unable to detect nitrogen deficiencies until at least the middle of and often late in the growing season. Sidedressing N early in the growing season has proven to be a sound strategy for optimizing yields and minimizing nitrate losses in tile drains. However, delaying sidedressing until mid-season (just before reproductive growth) has been shown to negate much of the yield and nitrate leaching loss benefits. For four years in an Iowa production field (2006–2009), we measured the crop yield and nitrate leaching losses to subsurface drain pipes in a corn–soybean [ Glycine max (L.) Merr.] rotation when N fertilizer was sidedressed to corn at three different crop development stages. The first treatment had all of the N fertilizer applied when the corn was at the 2 leaf stage (V2). The other two treatments split the N fertilizer application equally between the V2 stage and when six corn leaves were fully extended (V6) or when 12 corn leaves were fully extended (V12). Waiting until the V12 stage to sidedress the remaining N is a compromise between when plant sensors may be sensitive to N deficiencies and when sidedressing may still provide a water quality benefit without a detrimental impact on corn yield. We found no consistent yield differences for corn among the three treatments with significantly decreasing corn yields in the order of V12 > V2 > V6 in 2008 but no differences in 2006 or when averaged over both years. Similarly, none of the N treatments affected soybean yields grown the following year. When averaged over all years, there were no significant differences in nitrate concentration or leaching losses in subsurface drains among the treatments. Thus, if crop sensors can provide N rate information for sidedressing by the V12 growth stage, optimization of N fertilizer rates for crop yield and minimization of nitrate leaching may be possible.

a b s t r a c t Much of the NO3 in the riverine waters of the upper Mississippi River basin in the United States originates from agricultural land used for corn (Zea mays L.) and soybean (Glycine max [L.] Merr.) production. Cover crops grown between maturity and planting of these crops are one approach for reducing losses of NO3. In this experiment, we evaluated the effectiveness of oat (Avena sativa L.) and rye (Secale cereale L.) cover crops in reducing NO3 concentrations and loads in subsurface drainage water. The oat fall cover crop was broadcast seeded into living corn and soybean crops before harvest in late August or early September and was killed by cold temperatures in late November or early December The rye winter cover crop, which had already been used annually for four years, was planted with a grain drill after corn and soybean harvest, overwintered, grew again in the spring, and was killed with herbicides before main crop planting. These treatments were evaluated in subsurface-drained field plots with an automated system for measuring drainage flow and collecting proportional samples for analysis of NO3 concentrations from each plot. The rye winter cover crop significantly reduced drainage water NO3 concentrations by 48% over five years, but this was less than the 58% reduction observed in its first four years of use. The oat fall cover crop reduced NO3 concentrations by 26% or about half of the reduction of the rye cover crop. Neither cover crop significantly reduced cumulative drainage or nitrate loads because of variability in cumulative annual drainage among plots. Both oat and rye cover crops are viable management options for significantly reducing NO3 losses to surface waters from agricultural drainage systems used for corn and soybean production. Published by Elsevier B.V.

Controlled subsurface drainage can reduce nitrate loss to tile flow, but the effects may vary with different N application rates and weather conditions. Interactions between these factors can be understood better via combinations of field experiments and modeling. Using an automated parameter estimation method (PEST), the Root Zone Water Quality Model (RZWQM2) was calibrated with measured monthly tile flow, N loss and flow weighted nitrate-N concentration (FWNC) from 2006 to 2008 in a corn and soybean rotation system with free drainage (FD) management. Similar data from 2006 to 2008 with controlled drainage (CD) management were used to evaluate the model. Changing from FD to CD reduced the annual N loss in tile flow by 22 and 32% based on measured and RZWQM2 simulated results, respectively. The model over-predicted the CD effect possibly because of the slope of the field, which reduces the effect of CD but is not simulated by the model. Long-term RZWQM2 simulations (1996–2008) suggest that N loss can be reduced by about 40% in both FD and CD by decreasing N rate from 245 to 140 kg N ha −1 with little effect on corn yield. A further reduction in N loss of 39% (9.3 kg N ha −1 ) was simulated by implementing CD at the reduced N rate, and the reduced N loss to tile flow was mainly associated with increased N loss to seepage (lateral flow) and crop N uptake. The percent of N loss reduction using CD relative to FD was magnified with increased rainfall (from approximately 20 to 50% with annual rainfall ranging from 600 to 1100 mm), but the reduction varied only between 38 and 40% under different N rates (0–250 kg N ha −1 ). The results indicate that RZWQM2 accurately responded to CD compared to field measurements, and CD management in combination with reduced N application rates can substantially reduce N loss to the environment with little negative effect on corn yield.

Studies quantifying winter annual cover crop effects on water quality are mostly limited to short-term studies at the plot scale. Long-term studies scaling-up water quality effects of cover crops to the watershed scale provide more integrated spatial responses from the landscape. The objective of this research was to quantify N loads from artificial subsurface drainage (tile drains) in a subbasin of the Walnut Creek, Iowa (Story county) watershed using the hybrid RZWQ-DSSAT model for a maize ( Zea mays L.)-soybean [ Glycine max (L.) Merr.] and maize–maize–soybean rotations in all phases with and without a winter wheat ( Triticum aestivum L.) cover crop during a 25-year period from 1981 to 2005. Simulated cover crop dry matter (DM) and N uptake averaged 1854 and 36 kg ha −1 in the spring in the maize–soybean phase of the 2-year rotation and 1895 and 36 kg ha −1 in the soybean–maize phase during 1981–2005. In the 3-year rotation, cover crop DM and N uptake averaged 2047 and 44 kg ha −1 in the maize–maize–soybean phase, 2039 and 43 kg ha −1 in the soybean–maize–maize phase, and 1963 and 43 kg ha −1 in the maize–soybean–maize phase during the same period. Annual N loads to tile drains averaged 29 kg ha −1 in the maize–soybean phase and 25 kg ha −1 in the soybean–maize phase compared to 21 and 20 kg ha −1 in the same phases with a cover crop. In the 3-year rotation, annual N loads averaged 46, 43, and 45 kg ha −1 in each phase of the rotation without a cover crop and 37, 35, and 35 kg ha −1 with a cover crop. These results indicate using a winter annual cover crop can reduce annual N loads to tile drains 20–28% in the 2-year rotation and 19–22% in the 3-year rotation at the watershed subbasin scale over a 25-year period.

Adequate knowledge on the movement of nutrients under various agricultural practices is essential for developing remedial measures to reduce nonpoint source pollution. Mathematical models, after extensive calibration and validation, are useful to derive such knowledge and to identify site-specific alternative agricultural management practices. A spatial-process model that uses GIS and ADAPT, a field scale daily time-step continuous water table management model, was calibrated and validated for flow and nitrate-N discharges from a 365 ha agricultural watershed in central Iowa, in the Midwestern United States. This watershed was monitored for nitrate-N losses from 1991 to 1997. Spatial patterns in crops, topography, fertilizer applications and climate were used as input to drive the model. The first half of the monitored data was used for calibration and the other half was used in validation of the model. For the calibration period, the observed and predicted flow and nitrate-N discharges were in excellent agreement with r2 values of 0.88 and 0.74, respectively. During the validation period, the observed and predicted flow and nitrate-N discharges were in good agreement with r2 values of 0.71 and 0.50, respectively. For all 6 years of data, the observed annual nitrate-N losses of 26 kg ha-1 for the entire simulation were in excellent agreement with predicted nitrate-N losses of 24.2 kg ha-1. The calibrated model was used to investigate the long-term impacts of nitrate-N losses to changes in the rate and timing of fertilizer application. Results indicate that nitrate-N losses were sensitive to rate and timing of fertilizer application. Modeled annual nitrate-N losses showed a 17% reduction in nitrate-N losses by reducing the fertilizer application rate by 20% and switching the application timing from fall to spring. Further reductions in nitrate-N losses require conversion of row cropland to pasture and/or replacement of continuous corn or corn�soybean rotation systems with alternative crops.

Spatial variability in soils and surface elevation is an important consideration in the design and management of surface irrigated level basin systems. Field studies were conducted on a variable sandy loam soil in central Arizona to evaluate how the nonuniformities in the antecedent soil water content (prior to irrigation) and field surface level affected the uniformity of infiltrated water for a level basin irrigation system. Relationships between the soil water content and the sand, silt and clay fractions were described for a 4.2-ha experimental site, which was separated into 12 basins and planted to wheat in 1985 and 1986. Measured water distribution uniformities (average low quarter infiltrated depth/average infiltrated depth) were between 13–27% lower than that of an idealized uniformity of 98% where only infiltration opportunity time differences affect infiltrated depth uniformity. However, 0.51 to 0.68 of the variability in infiltrated depth could be explained by differences in the antecedent soil water content (0–1.0 m soil depth), while as much as 0.23 of the infiltrated depth variability, and 0.60 of the variability in deep percolation, was explained by nonuniformities in surface elevation. For a properly designed level basin system on sandy loam, distribution uniformities of 85% or more should be attained when 85% of the basin elevation is within ± 15 mm of the mean, provided the antecedent water content variability is on the order of 0.15 or less. However, those proposing to use level basins which have more extensive soil and water content variability should maintain a leveling precision, such that 100% of the basin is within ± 15 mm to attain high distribution uniformities.