Important Role of Overland Flows and Tile Field Pathways in Nutrient Transport.

Nitrogen and phosphorus pollution is of great concern to aquatic life and human well-being. While most of these nutrients are applied to the landscape, little is known about the complex interplay among nutrient applications, transport attenuation processes, and coastal loads. Here, we enhance and apply the Spatially Explicit Nutrient Source Estimate and Flux model (SENSEflux) to simulate the total annual nitrogen and phosphorus loads from the US Great Lakes Basin to the coastline, identify nutrient delivery hotspots, and estimate the relative contributions of different sources and pathways at a high resolution (120 m). In addition to in-stream uptake, the main novelty of this model is that SENSEflux explicitly describes nutrient attenuation through four distinct pathways that are seldom described jointly in other models: runoff from tile-drained agricultural fields, overland runoff, groundwater flow, and septic plumes within groundwater. Our analysis shows that agricultural sources are dominant for both total nitrogen (TN) (58%) and total phosphorus (TP) (46%) deliveries to the Great Lakes. In addition, this study reveals that the surface pathways (sum of overland flow and tile field drainage) dominate nutrient delivery, transporting 66% of the TN and 76% of the TP loads to the US Great Lakes coastline. Importantly, this study provides the first basin-wide estimates of both nonseptic groundwater (TN: 26%; TP: 5%) and septic-plume groundwater (TN: 4%; TP: 2%) deliveries of nutrients to the lakes. This work provides valuable information for environmental managers to target efforts to reduce nutrient loads to the Great Lakes, which could be transferred to other regions worldwide that are facing similar nutrient management challenges.

Effects of different drainage conditions on nitrogen losses of an agricultural sandy loam soil.

Prolonged waterlogging in agricultural fields has severe consequences for the crop development and growth, and could potentially lead to higher N losses. In this study, a 3.93 ha agricultural field in Denmark was separated into two parts of well-drained (WD) and poorly-drained (PD) based on the installation depth of the tile drains. The field was continuously monitored for drainage, soil water dynamics, nitrogen leaching through the drains, and grain dry matter and nitrogen yields in a 4-year period (2017-2020). Furthermore, denitrification potential of the top 1 m of the soil at both parts of the field was measured through the denitrifying enzyme activity assay, and a 1D Daisy model was utilized to capture the differences between water and nitrogen balances at WD and PD. Results indicated that on average over the 4 years, annual harvested nitrogen in the crops at PD was 14% lower compared to WD, with a significant reduction of 33% in 2017-2018, that coincided with the longest period of waterlogging at PD. Moreover, greater losses of nitrogen through leaching from drainage and other pathways were measured at the PD (109 kg N ha-1 ya-1) compared to the WD (95 kg N ha-1 ya-1). Based on the simulations, losses through preferential flow pathways to the drains dominated at PD and most of the denitrification is expected to occur within the topsoil. Future studies could significantly benefit from monitoring the redox dynamics in the top 30 cm of the PD soils, and increasing the depth of tiles drains by redrainage could reduce the N losses of poorly drained agricultural soils.

Paired denitrifying bioreactors with wide orientation for increased drainage flow capacity.

Denitrifying bioreactors are a conservation drainage practice for reducing nitrate loads in subsurface agricultural drainage. Bioreactor hydraulic capacity is limited by cross-sectional area perpendicular to flow through the woodchip bed, with excess bypass flow untreated. Paired bioreactors with wide orientations were built in 2017 in Illinois, USA, to treat drainage from a relatively large 29 ha field. The paired design consisted of: a larger, Main bioreactor (LWD: 6.1 × 18.3 × 0.9 m) for treating base flow, and 2) a smaller, Booster bioreactor (7.8 × 13.1 × 0.9 m) receiving bypass flow from the Main bioreactor during periods of high flow. Over three years of monitoring, the paired bioreactor captured 84-92% of the annual drainage discharge which demonstrated an expanded cross-sectional area could improve bioreactor flow capture, even for a large drainage area. However, the paired bioreactors removed 6-28% of the annual N load leaving the field (1.8-5.6 kg N ha-1 removed; 52-161 kg N), which was not a notable improvement compared to bioreactors treating smaller drainage areas. The design operated as intended at low annual flow-weighted hydraulic retention times (HRTs) of usually ≤2 h, but these short HRTs ultimately limited bioreactor nitrate removal efficiency. Daily HRTs of <2 h often resulted in nitrate flushing. The Main bioreactor had higher hydraulic loading as intended and was responsible for the majority of flow captured in each year although not always the most nitrate mass removal. The Booster bioreactor provided better nitrate removal than the Main at HRTs of 3.0-11.9 h, possibly due to its drying cycles which may have liberated more available carbon. This new design approach tested at the field-scale illustrated tradeoffs between greater flow capacity (via increased bioreactor width) and longer HRT (via increased length), given a consistent bioreactor surface footprint.

Analysis of reactive phosphorus treatment by filter materials at the edge of tile-drained agricultural catchments: A global view of the current status and challenges.

Phosphorus losses from agriculture have long generated concern due to the ecological impact on surface waters. Here tile-drained agricultural catchments are a critical source for concentrating and transporting phosphorus bioavailable forms or dissolved reactive phosphorus (DRP). Hence, edge-of-field technologies have been introduced to reduce DRP loads. Filter systems have received special attention due to their targeted approach using a permeable filter material (FM) rich in DRP sorbents. This review explores the performance and applicability of FMs in the aforementioned context because of the growing number of studies. An overall analysis revealed that sorption is preferable to precipitation for DRP retention at the edge-of-field, and that FM pH and particle size affect sorption properties and subsequently DRP retention and lifetime. Thus, FMs with predominant amounts of iron and/or aluminium can be recommended. Such materials generally have an appreciable availability of DRP binding sites, strong bonds with DRP and short reaction times, as well as low desorption, which lead to good operation. On the other hand, FMs with predominant amounts of calcium and/or magnesium are restricted to catchments with favourable conditions unless they have optimal reactivity for DRP. The review also found that hydraulic retention time plays a key role in the performance and applicability of FMs, especially in those dependent on precipitation reactions. Therefore, it is crucial that FMs are designed, constructed and managed according to the catchment conditions-including normally varying flow rates and DRP concentrations-in order to ensure successful operation. This reflects in long-term, high and steady net DRP retention along with low costs, thus improving the FM cost-effectiveness, besides discharging non-harmful effluents to aquatic ecosystems.

Managing nitrate-nitrogen in the intensively drained upper Mississippi River Basin, USA under uncertainty: a perennial path forward.

The upper Mississippi River basin has been identified as the most significant contributor of excessive nutrients to the hypoxic zone in the Gulf of Mexico. The land-use changes from an internally drained prairie-wetland complex to an intensively managed corn-soybean production system drained by subsurface tile drainage system in the north-central Iowa and south-central Minnesota are the primary cause of nutrient loads into the Mississippi River and many other environmental stresses. The present study summarizes the water-quality degradation from land-use change and offers a fuzzy logic-based decision support for assessing degree of suitability of the four recommended perennial plant options for managing water and nitrate-nitrogen export. These options are designed based on landscape position that currently fails to produce high yielding row crops and scale: (1) marginal upland depressions for water storage by planting deep-rooted perennial grasses and fast-growing woody poplar, willow, and alder in poorly drained swales; (2) saturated buffers and/or subtle changes in landscape slope for draining high nitrate-nitrogen subsurface (through multi-species phytoremediation treatment buffers or strips of perennial vegetation); (3) two-stage ditches with linear floodplains planted with perennial grasses; and (4) riparian and in-channel ecologically engineered trees, shrubs, and grasses to better connect meander belt width to frequent peak stream flows at larger scales. When applied throughout a typical (Des Moines Lobe Till) DMLT watershed, each option can have positive cumulative environmental effects. Fuzzy logic enhanced the precision in watershed decision-making by incorporating the uncertainty associated with factors like cost effectiveness, nitrate reduction potential, water quality improvement, and level of acceptance.

Mapping of Agricultural Subsurface Drainage Systems Using Unmanned Aerial Vehicle Imagery and Ground Penetrating Radar.

Agricultural subsurface drainage systems are commonly installed on farmland to remove the excess water from poorly drained soils. Conventional methods for drainage mapping such as tile probes and trenching equipment are laborious, cause pipe damage, and are often inefficient to apply at large spatial scales. Knowledge of locations of an existing drainage network is crucial to understand the increased leaching and offsite release of drainage discharge and to retrofit the new drain lines within the existing drainage system. Recent technological developments in non-destructive techniques might provide a potential alternative solution. The objective of this study was to determine the suitability of unmanned aerial vehicle (UAV) imagery collected using three different cameras (visible-color, multispectral, and thermal infrared) and ground penetrating radar (GPR) for subsurface drainage mapping. Both the techniques are complementary in terms of their usage, applicability, and the properties they measure and were applied at four different sites in the Midwest USA. At Site-1, both the UAV imagery and GPR were equally successful across the entire field, while at Site-2, the UAV imagery was successful in one section of the field, and GPR proved to be useful in the other section where the UAV imagery failed to capture the drainage pipes' location. At Site-3, less to no success was observed in finding the drain lines using UAV imagery captured on bare ground conditions, whereas good success was achieved using GPR. Conversely, at Site-4, the UAV imagery was successful and GPR failed to capture the drainage pipes' location. Although UAV imagery seems to be an attractive solution for mapping agricultural subsurface drainage systems as it is cost-effective and can cover large field areas, the results suggest the usefulness of GPR to complement the former as both a mapping and validation technique. Hence, this case study compares and contrasts the suitability of both the methods, provides guidance on the optimal survey timing, and recommends their combined usage given both the technologies are available to deploy for drainage mapping purposes.

How climate scenarios alter future predictions of field-scale water and nitrogen dynamics and crop yields.

Climate change scenarios are widely used for exploring future changes in environmental systems. However, many aspects of the uncertainties associated with the use of climate change scenarios in environmental systems modeling have not yet been studied sufficiently. We explore how the way that baseline scenarios are defined and general circulation model (GCM) outputs are used affects climate change impact assessments of agricultural systems. Our study builds on a previously validated agricultural systems model, the Root Zone Water Quality Model (RZWQM), coupled with the Decision Support System for Agrotechnology Transfer (DSSAT), which models a tiled-drained field in central Illinois of the United States and uses nine GCM outputs to investigate the effects. Our model simulations demonstrated the following three results. Firstly, the evaluation of climate change impacts presented a significant difference between the types of baseline used. The baseline scenario should be defined using the bias-corrected retrospective GCM outputs. Secondly, once GCM outputs are bias-corrected, the selective use of GCM outputs did not add significant value over using all available GCM outputs to provide more plausible future descriptions of agricultural systems' responses. Notably, however, selective use may have impacts comparable to carbon dioxide (CO2) emission scenarios in the field-scale agricultural climate change impact assessments. Thirdly, raw GCM outputs should be avoided for the predictions of field-scale agricultural systems' responses to climate change. Our findings can help provide a clearer picture of how GCM outputs should be used in agricultural systems modeling and might enable us to have more plausible descriptions of how future agricultural systems might unfold.

Hydrograph separation of subsurface tile discharge.

Baseflow is an important component of streamflow and watershed hydrologic budgets, yet quantifying the baseflow fraction of tile drainage has rarely been reported. In this study, we used two common hydrograph separation methods (local minimum method, recursive digital filter) to separate the discharge hydrographs from three drainage district tiles located in Iowa. Based on data collected from 2009 to 2013, annual baseflow ranged from 116 to 162 mm and comprised approximately 60% of the annual discharge. Baseflow was greatest during June (average of 34% of annual baseflow) and the March through August period produced 86% of the total annual baseflow. We found that the two methods of hydrograph separation produced similar results but the digital filter method was less erratic in estimating baseflow fraction. Study results can be used to better quantify hydrologic pathways in tiled landscapes and improve the design, implementation, and evaluation of nutrient reduction strategies.

Performance of an under-loaded denitrifying bioreactor with biochar amendment.

Denitrifying bioreactors are recently-established agricultural best management practices with growing acceptance in the US Midwest but less studied in other agriculturally significant regions, such as the US Mid-Atlantic. A bioreactor was installed in the Virginia Coastal Plain to evaluate performance in this geographically novel region facing challenges managing nutrient pollution. The 25.3 m3 woodchip bed amended with 10% biochar (v/v) intercepted subsurface drainage from 6.5 ha cultivated in soy. Influent and effluent nitrate-nitrogen (NO3-N) and total phosphorus (TP) concentrations and flowrate were monitored intensively during the second year of operation. Bed surface fluxes of greenhouse gases (GHGs) nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2) were measured periodically with the closed dynamic chamber technique. The bioreactor did not have a statistically or environmentally significant effect on TP export. Cumulative NO3-N removal efficiency (9.5%) and average removal rate (0.56 ±â€¯0.25 g m-3 d-1) were low relative to Midwest tile bioreactors, but comparable to installations in the Maryland Coastal Plain. Underperformance was attributed mainly to low NO3-N loading (mean 9.4 ±â€¯4.4 kg ha-1 yr-1), although intermittent flow, periods of low HRT, and low pH (mean 5.3) also likely contributed. N removal rates were correlated with influent NO3-N concentration and temperature, but decreased with hydraulic residence time, indicating that removal was often N-limited. GHG emissions were similar to other bioreactors and constructed wetlands and not considered environmentally concerning. This study suggests that expectations of NO3-N removal efficiency developed from bioreactors receiving moderate to high NO3-N loading with influent concentrations exceeding 10-20 mg L-1 are unlikely to be met by systems where N-limitation becomes significant.

Estimation of tile drainage contribution to streamflow and nutrient loads at the watershed scale based on continuously monitored data.

Nitrogen losses from artificially drained watersheds degrade water quality at local and regional scales. In this study, we used an end-member mixing analysis (EMMA) together with high temporal resolution water quality and streamflow data collected in the 122 km2 Otter Creek watershed located in northeast Iowa. We estimated the contribution of three end-members (groundwater, tile drainage, and quick flow) to streamflow and nitrogen loads and tested several combinations of possible nitrate concentrations for the end-members. Results indicated that subsurface tile drainage is responsible for at least 50% of the watershed nitrogen load between April 15 and November 1, 2015. Tiles delivered up to 80% of the stream N load while providing only 15-43% of the streamflow, whereas quick flows only marginally contributed to N loading. Data collected offer guidance about areas of the watershed that should be targeted for nitrogen export mitigation strategies.

Effects of tillage and poultry manure application rates on Salmonella and fecal indicator bacteria concentrations in tiles draining Des Moines Lobe soils.

Application of poultry manure (PM) to cropland as fertilizer is a common practice in artificially drained regions of the Upper Midwest United States. Tile-waters have the potential to contribute pathogenic bacteria to downstream waters. This 3-year study (2010-2012) was designed to evaluate the impacts of manure management and tillage practices on bacteria losses to drainage tiles under a wide range of field conditions. PM was applied annually in spring, prior to planting corn, at application rates ranging from 5 to 40 kg/ha to achieve target rates of 112 and 224 kg/ha nitrogen (PM1 and PM2). Control plots received no manure (PM0). Each treatment was replicated on three chisel-plowed (CP) plots and one no-till (NT) plot. Tile-water grab samples were collected weekly when tiles were flowing beginning 30 days before manure application to 100 days post application, and additional grab samples were obtained to target the full spectrum of flow conditions. Manure and tile-water samples were analyzed for the pathogen, Salmonella spp. (SALM), and fecal indicator bacteria (FIB), Escherichia coli (EC), and enterococci (ENT). All three bacterial genera were detected more frequently, and at significantly higher concentrations, in tile-waters draining NT plots compared to CP plots. Transport of bacteria to NT tiles was most likely facilitated by macropores, which were significantly more numerous above tiles in NT plots in 2012 as determined by smoke-testing. While post-manure samples contained higher concentrations of bacteria than pre-manure samples, significant differences were not seen between low (PM1) and high (PM2) rates of PM application. The highest concentrations were observed under the NT PM2 plot in 2010 (6.6 × 10(3) cfu/100 mL EC, 6.6 × 10(5) cfu/100 mL ENT, and 2.8 × 10(3) cfu/100 mL SALM). Individual and 30-day geometric mean ENT concentrations correlated more strongly to SALM than EC; however, SALM were present in samples with little or no FIB.

Nitrous oxide and methane production and consumption at five full-size denitrifying bioreactors treating subsurface drainage water.

Nitrate (NO3-) removal in denitrifying bioreactors is influenced by flow, water chemistry, and design, but it is not known how these widely varying factors impact the production of nitrous oxide (N2O) or methane (CH4) across sites. Woodchip bioreactors link the hydrosphere and atmosphere in this respect, so five full-size bioreactors in Illinois, USA, were monitored for NO3-, N2O, and CH4 to better document where this water treatment technology resides along the pollution swapping to climate smart spectrum. Both surface fluxes and dissolved forms of N2O and CH4 were measured (n = 7-11 sampling campaigns per site) at bioreactors ranging from <1 to nearly 5 years old and treating subsurface drainage areas from between 6.9 and 29 ha. Across all sites, N2O surface and dissolved volumetric production rates averaged 1.0 ± 1.6 mg N2O-N/m3-d and 24 ± 62 mg dN2O-N/m3-d, respectively, and CH4 production rates averaged 6.0 ± 26 mg CH4-C/m3-d and 310 ± 520 mg dCH4-C/m3-d for surface and dissolved, respectively. However, N2O was consistently consumed at one bioreactor, and only three of the five sites produced notable CH4. Surface fluxes of CH4 were significantly reduced by the presence of a soil cover. Bioreactor denitrification was relatively efficient, with only 0.51 ± 3.5 % of removed nitrate emitted as N2O (n = 48). Modeled indirect N2O emissions factors were significantly lower when a bioreactor was present versus absent (EF5: 0.0055 versus 0.0062 kg N2O-N/kg NO3-N; p = 0.0011). While further greenhouse gas research on bioreactors is recommended, this should not be used as an excuse to slow adoption efforts. Bioreactors provide a practical option for voluntary water quality improvement in the heavily tile-drained US Midwest and elsewhere.

Evaluation of long-term impact of cereal rye as a winter cover crop in Illinois.

Extensive tile drainage usage combined with excess nitrogen fertilization has triggered nutrient loss and water quality issues in Illinois, which over time endorsed the hypoxia formation in the Gulf of Mexico. Past research reported that the use of cereal rye as a winter cover crop (CC) could be beneficial in reducing nutrient loss and improving water quality. The extensive use of CC may aid in reducing the hypoxic zone in the Gulf of Mexico. The objective of this study is to analyze the long-term impact of cereal rye on soil water­nitrogen (N) dynamics and cash crops growth in the maize-soybean agroecosystem in the state of Illinois. A gridded simulation approach was developed using the DSSAT model for the CC impact analysis. The CC impacts were estimated for the last two decades (2001-2020) for two fertilization scheduling (FA-SD = Fall and side-dress N and SP-SD = Spring pre-plant and side-dress N) comparing between CC scenario (FA-SD-C/SP-SD-C) with no CC (NCC) scenario (FA-SD-N/SP-SD-N). Our results suggest that the nitrate-N loss (via tile flow) and leaching reduced by 30.6 % and 29.4 %, assuming extensive adaptation of cover crop. The tile flow and deep percolation decreased by 20.8 % and 5.3 %, respectively, due to cereal rye inclusion. The model performance was relatively poor in simulating the CC impact on soil water dynamics in the hilly topography of southern Illinois. Generalizing changes in the soil properties (due to cereal rye inclusion) from the field scale to whole state (regardless of soil type) could be one of the possible limitations in this research. Overall, these findings substantiated the long-term benefits of cereal rye as a winter cover crop and found the spring N fertilizer application reduced nitrate-N loss compared to fall N application. These results could be helpful in promoting the practice in the Upper Mississippi River basin.

Improving nitrate load simulation of the SWAT model in an extensively tile-drained watershed.

Subsurface drainage systems are effective management practices employed to remove excess soil water, thereby improving soil aeration and crop productivity. However, these systems can also contribute to water quality issues by enhancing nitrate leaching and loads from agricultural fields. The Soil and Water Assessment Tool (SWAT) is commonly used to assess nitrate loads and long-term water quality impacts from agricultural watersheds. However, the current SWAT model oversimplifies nitrate transport processes by assuming a linear relationship between nitrate concentrations in tile flow and soil nitrate content. It also neglects the time lag between nitrate loading and transport with the flow. This study aimed to enhance the accuracy of nitrate load prediction by revising the subsurface drainage routine in the SWAT model. The revised routine was tested using flow and nitrate load measurements from a typical tile-drained watershed in east-central Illinois, U.S. The results demonstrated that the revised SWAT nitrate routine outperformed the current one in simulating nitrate transport at field and watershed scales. The revised routine improved the nitrate load prediction from an "unacceptable" to a "satisfactory" or "good" rating on the field scale. A sensitivity analysis conducted using the revised nitrate module showed the parameters directly associated with transpiration, groundwater discharge to the reach, the lag time of tile flow, and channel flow hydraulics were the most sensitive in nitrate load simulation. In addition, different tile depth scenarios were modeled to evaluate variation in the amount of surface runoff, tile flow, and nitrate loads by the surface flow and tile flow. The results of tile configuration scenarios agreed with understanding the tile flow process. The test results demonstrated the potential of the revised SWAT nitrate module as a tool to accurately evaluate the effects of tile drainage systems on water quality.

The role of agricultural drainage, storm-events, and natural filtration on the biogeochemical cycling capacity of aquatic and sediment environments in Lake Erie's drainage basin.

Lake Erie is the most at risk of the Great Lakes for degraded water quality due to non-point source pollution caused by agricultural activities in the lake's watershed. The extent and temporal patterns of nutrient loading from these agricultural activities is influenced by the timing of agronomic events, precipitation events, and water flow through areas of natural filtration within the watershed. Downstream impacts of these nutrient loading events may be moderated by the co-loading of functionally relevant biogeochemical cycling microbial communities from agricultural soils. This study quantified loading patterns of these communities from tile drain sources, assessed whether functional communities from agricultural sources influenced downstream microbial functionality, and investigated how distance from agricultural sources, storm events, and areas of natural filtration altered nutrient cycling and nutrient fluxes in aquatic and sediment environments. Water and sediment samples were collected in the Wigle Creek watershed in Ontario, from tile drains through to Lake Erie, from May to November 2021, and microbial nitrogen (N) and phosphorous (P) cycling capacity (quantitative PCR), and nutrient levels were evaluated. Results showed that N and P functional groups were co-loaded with nutrients, with increased loading occurring during storm events and during agricultural activities including fertilization and harvest. Overall functional capacity in the aquatic environment decreased with distance from the agricultural sources and as water transited through natural filtration areas. In contrast, the sediment environment was more resilient to both agricultural disturbances and abiotic factors. This study expands our understanding of when and where different stages of N and P cycling occurs in agriculturally impacted watersheds, and identifies both seasons and regions to target with nutrient mitigation strategies.

Long-term phosphorus removal by Ca and Fe-rich drainage filter materials under variable flow and inlet concentrations.

Phosphorus (P) losses from tile-drained agricultural fields may degrade surface water quality by accelerating eutrophication. Among the different edge-of-field technologies, compact filter systems using different filter materials have been identified as potentially effective solutions for removing P from drainage water before discharge downstream. This study investigated the long-term (>696 days) P removal efficiency of 5 different filter materials in a column setup, using artificial drainage water (pH 6). Filter materials included two iron-based granulates (calcinated diatomaceous earth (CDE), ferric hydroxide granules (CFH)), and three calcium-based granulates (seashells, limestone, calcinated silicate/calcium oxide (Filtralite-P)). Experiments were performed under variable flow rates (0.037 and 1.52 L h-1; hydraulic retention time of 26-43 min and 18-30 h) and inlet P concentrations (0.14 and 0.7 mg L-1). An overall analysis revealed that the Fe-based materials achieved higher P retention than Ca-based materials. In particular, CFH was capable of retaining 99 and 98 % of the high and low inlet P concentrations, respectively. Conversely, limestone retained only 25 % of the high P load. CDE performed moderately well, independently of the inlet P concentration. Filtralite-P and Seashells performed well at high inlet P concentration but relatively poorly at low P concentration. The sensitivity of filter material P removal efficiency to variations in P loading was generally lowest for CFH and highest for limestone.

Agricultural intensification leads to higher nitrate levels in Lake Ontario tributaries.

Eutrophication remains the most widespread water quality impairment globally and is commonly associated with excess nitrogen (N) and phosphorus (P) inputs to surface waters from agricultural runoff. In southern Ontario, Canada, increases in nitrate (NO3-N) concentrations as well as declines in total phosphorus (TP) concentration have been observed over the past four decades at predominantly agricultural watersheds, where major expansions in row crop production at the expense of pasture and forage have occurred. This study used a space-for-time approach to test whether 'agricultural intensification', herein defined as increases in row crop area (primarily corn-soybean-winter wheat rotation) at the expense of mixed livestock and forage/pasture, could explain increases in NO3-N and declines in TP over time. We found a clear, positive relationship between the extent of row crop area within watersheds and NO3-N losses, such that tributary NO3-N concentrations and export were predicted to increase by ~0.4 mg/L and ~130 kg/km2 respectively, for every 10% expansion in row crop area. There was also a significant positive relationship between row crop area and total dissolved phosphorus (TDP) concentration, but not export, and TP was not correlated with any form of landcover. Instead, TP was strongly associated with storm events, and was more sensitive to hydrologic condition than to landcover. These results suggest that pervasive shifts toward tile-drained corn and soybean production could explain increases in tributary NO3-N levels in this region. The relationship between changes in agriculture and P is less clear, but the significant association between dissolved P and row crop area suggests that increased adoption of reduced tillage practices and tile drainage may enhance subsurface losses of P.

Crop improvement influences on water quantity and quality processes in an agricultural watershed.

Field crop traits have and are experiencing significant changes due to genetic and agronomic improvements. How these changes affect regional water quantity and quality processes has not been clarified. The St. Joseph River Watershed (SJRW) located in the U.S. Corn Belt was selected as a case study area. Crop (corn and soybean) trait improvements in the past decades were reviewed and summarized and include changes of growing degree days (GDD), leaf area index (LAI), light utilization (LU), drought tolerance (DT), nutrient content (NC), and harvest index (HI). Based on a calibrated 9-year (from 2011 to 2019) SWAT (Soil and Water Assessment Tool) simulation in SJRW, sensitivities of the above crop traits to yield, ETa, stream flow, tile flow, surface runoff, and nutrient loads (NO3N, TN, soluble-P, and TP) were analyzed. Crop traits and their corresponding SWAT parameters for the 2010s were obtained from model calibration and used as the baseline/current scenario; for the 1980s, they were summarized from literature review and used as an historical scenario, while those for the 2040s were determined by assuming crop traits are changing linearly with time and projected as the future scenario. Water quantity and quality changes under the historical and future crop scenarios were compared with the baseline/current simulation. Results showed LU and DT were the most sensitive crop traits to water quantity (i.e., ETa, stream flow, tile flow, and surface runoff), while HI was the most sensitive to nutrient loads. The impacts of crop improvements on nutrient loads were more significant than on water budgets. Compared with the baseline, the historical and future scenarios resulted in 1.5 - 2.0% changes of stream flow, 6.8 - 18.6% changes of nitrogen loads (NO3N and TN) and 2.6 - 3.9% changes of phosphorus loads (soluble-P, and TP) in the stream flow, annually. Moreover, in certain months, these changes can reach about 12% for stream flow, 42% for nitrogen loads, and 12% for phosphorus loads. Nitrogen losses by tile drainage and percolation, and phosphorus losses by surface runoff and tile drainage were most significantly affected by the crop improvements. Future work should consider expected crop improvements when studying long-term hydrology and nutrient cycles in agricultural watersheds.

Phosphorus removal by steel slag from tile drainage water: Lab and field evaluations.

Basic oxygen furnace (BOF) and blast furnace (BF) steel slags are well suited for phosphorous (P) removal from nonpoint sources such as agricultural runoff. However, the reported mechanism(s) of removal varies from study to study which complicates implementation for unique environmental conditions that may interfere with the removal mechanism(s). This work compared laboratory column experiments and field filter experiments to provide insights on the influence of relevant field conditions (water alkalinity, slag grain size distribution, BF:BOF slag ratio, and water stagnation) on P removal by BF and BOF steel slag mixtures. Alkalinity was the most influential variable in lab-scale slag columns that received 250 mg/L alkalinity water and achieved complete P removal throughout the 3-h experiment, while identical columns receiving 500 mg/L alkalinity water averaged 52% P removal and only 14% removal after 2.5 h. Batch regeneration and adsorption experiments were conducted on the exhumed BOF/BF slag mixture from the field filter to evaluate strategies for increasing field P removal capacity. The adsorption capacity of steel slags was effectively regenerated by 0.01 M Al2(SO4)3, which allowed for an additional 34% P removal in batch adsorption tests. The acid neutralization capacity of slag samples was effectively regenerated by 1 M NaOH, which allowed previously expended slag to reach a pH of 9.7 even in high alkalinity test water. The results presented here show that BF slag and Al2(SO4)3 regeneration of BF slag is best suited for high alkalinity influent conditions and removes P through adsorption while BOF slag and NaOH regeneration perform best under low alkalinity conditions and removes P through mineral precipitation.

Determination of accurate baseline representation for three Central Iowa watersheds within a HAWQS-based SWAT analyses.

Improving food systems to address food insecurity and minimize environmental impacts is still a challenge in the 21st century. Ecohydrological models are a key tool for accurate system representation and impact measurement. We used a multi-phase testing approach to represent baseline hydrologic conditions across three agricultural basins that drain parts of north central and central Iowa, U.S.: the Des Moines River Basin (DMRB), the South Skunk River Basin (SSRB), and the North Skunk River Basin (NSRB). The Soil and Water Assessment Tool (SWAT) ecohydrological model was applied using a framework consisting of the Hydrologic and Water Quality System (HAWQS) online platform, 40 streamflow gauges, the alternative runoff curve number method, additional tile drainage and fertilizer application. In addition, ten SWAT baselines were created to analyze both the HAWQS parameters (baseline 1) and nine alternative baseline configurations (considering the framework). Most of the models achieved acceptable statistical replication of measured (close to the outlet) streamflows, with Nash-Sutcliffe (NS) values ranging up to 0.80 for baseline 9 in the DMRB and SSRB, and 0.78 for baseline 7 in the NSRB. However, water balance and other hydrologic indicators revealed that careful selection of management data and other inputs are essential for obtaining the most accurate representation of baseline conditions for the simulated stream systems. Using cumulative distribution curves as a criterion, baselines 7 to 10 showed the best fit for the SSRB and NSRB, but none of the baselines accurately represented 20% of low flows for the DMRB. Analysis of snowmelt and growing season periods showed that baselines 3 and 4 resulted in poor simulations across all three basins using four common statistical measures (NS, KGE, Pbias, and R2), and that baseline 9 was characterized by the most satisfactory statistical results, followed by baselines 5, 7 and 1.