Long-Term Observations of Nitrogen and Phosphorus Export in Paired-Agricultural Watersheds under Controlled and Conventional Tile Drainage

Evaluating best management practices for nutrient load reductions in tile-drained watersheds of the Laurentian Great Lakes Basin: A literature review

Tile drainage systems are extensively implemented across the Laurentian Great Lakes Basin (GLB) to enhance agricultural productivity on poorly drained soils. However, these systems substantially contribute to excess nutrient runoff, particularly phosphorus (P) and nitrogen (N), exacerbating eutrophication and harmful algal blooms in the Great Lakes. This literature review synthesized current knowledge on nutrient loadings from tile-drained agricultural watersheds and evaluated the effectiveness of various agricultural best management practices (BMPs) in mitigating nutrient losses in the GLB. Through a meta-synthesis of field and watershed scale monitoring and modeling studies and statistical analysis using Box-Whisker plots and Monte Carlo simulations, we assessed the nutrient reduction potential of representative BMPs, including cover cropping, nutrient management, controlled drainage, and constructed wetlands in tile-drained landscapes. Findings indicated that individual BMPs substantially reduced nutrient loadings, but the effectiveness of these BMPs depended on site-specific factors, including climate conditions, soil type, and drainage system design. Integrated approaches at field, edge-of-field, and watershed scales with a combination of multiple BMPs enhanced nutrient reduction benefits, aligning with regional water quality targets. The review also highlighted the challenges of climate change that may undermine BMP performance by altering precipitation patterns and increasing extreme weather events. To address these complexities, we proposed a framework for developing adaptive BMP scenarios tailored to specific watershed conditions, emphasizing the need for long-term monitoring and hydrologic model enhancements. This framework was designed to help policymakers, stakeholders, and farmers protect water quality and balance agricultural productivity in the GLB and similar agricultural regions globally.

The functions and factors governing fungal communities and diversity in agricultural waters: insights into the ecosystem services aquatic mycobiota provide

Introduction

Fungi are essential to the aquatic food web, nutrient cycling, energy flow, and ecosystem regulation. Fungal community structures in water can be influenced by adjacent terrestrial environments, which drive and control some ecosystem services they provide. However, the roles of freshwater fungal communities remain underexplored compared to bacterial communities in this context.

Methods

We assessed the impact of anthropological and environmental factors on freshwater mycobiota in an agriculturally dominated water basin in eastern Ontario, Canada. We undertook bi-weekly surface water sampling from 2016 to 2021 and conducted fungal internal transcribed spacer 2 (ITS2) metabarcoding on the samples, complemented by ancillary data, including water physicochemical properties, upstream land use, hydrology, and weather conditions.

Results

Our study yielded 6,571 OTUs from 503 water samples, spanning 15 fungal phyla, dominated by Ascomycota, Basidiomycota, and Chytridiomycota. Agricultural land use was associated with decreased mycobiota alpha diversity and distinct fungal communities were observed at agricultural drainage ditch and mixed-land use sites compared to a forested site that had minimal anthropogenic activities in catchment. Notably, river discharge emerged as a predominant influencer of both community diversity and composition, likely amplified by precipitation-induced erosion and drainage from adjacent terrestrial environments.

Discussion

Water physicochemical properties, including stream fungicide levels, explained a small proportion of the variation in mycobiota communities, underscoring the significance of unmeasured factors, alongside stochastic community assembly processes. Nevertheless, stream mycobiota demonstrated functional resilience for critical ecological processes under different environmental conditions. Altogether, these results highlight the complex interplay of factors influencing the freshwater mycobiota, which is essential for elevated understanding of the ecosystem services these fungi provide.

Phosphorus and iron-oxide transport from a hydrologically isolated grassland hillslope

Dissolved reactive phosphorus (DRP) loss from agricultural soils can negatively affect water quality. Shallow subsurface pathways can dominate P losses in grassland soils, especially in wetter months when waterlogging is common. This study investigated the processes controlling intra- and inter-event and seasonal DRP losses from poorly drained permanent grassland hillslope plots. Temporal flow related water samples were taken from surface runoff and subsurface (in-field pipe) discharge, analysed, and related to the likelihood of anaerobic conditions and redoximorphic species including nitrate (NO₃^-) over time. Subsurface drainage accounted for 89% of total losses. Simple linear regression and correlation matrices showed positive relationships between DRP and iron and soil moisture deficit; and negative relationships between these three factors and NO₃^- concentrations in drainage. These data indicate that waterlogging and low NO₃^- concentrations control the release of P in drainage, potentially via reductive dissolution. The relationship between DRP and metal release was less obvious in surface runoff, as nutrients gathered from P-rich topsoil camoflaged redox reactions. The data suggest a threshold in NO₃^- concentrations that could exacerbate P losses, even in low P soils. Knowledge of how nutrients interact with soil drainage throughout the year can be used to better time soil N and P inputs via, for example, fertiliser or grazing to avoid to excessive P loss that could harm water quality.

Stacked conservation practices reduce nitrogen loss: A paired watershed study

Combinations of best management practices (BMPs) are needed to achieve nutrient reduction goals in the Mississippi/Atchafalaya River Basin (MARB), but field results are crucial to encourage stacked adoption of BMPs. A paired catchment-scale study (2015-18) was done to assess the impact of (i) BMPs, (ii) precipitation patterns, and (iii) seasonality on nitrogen (N) export. Flow-weighted samples were collected and analyzed for total ammonia nitrogen (TAN), nitrate (NO₃-N), and total nitrogen (TN). Catchments Low-BMP 11 and High-BMP 12 had 27.6% and 87.6% areal coverage of BMPs, respectively. No significant difference (p > 0.05) in TAN concentrations was found between Low-BMP 11 (0.023 mg L^-1) and High-BMP 12 (0.020 mg L^-1). However, NO₃-N and TN concentrations were significantly higher (p < 0.05) at Low-BMP 11 (NO₃-N: 26.0 mg L^-1, TN: 28.7 mg L^-1) than at High-BMP 12 (NO₃-N: 8.8 mg L^-1, TN: 9.2 mg L^-1). Two precipitation factors that affected N export patterns were observed. First, N flushing could continue for several years after a drought as elevated NO₃-N concentrations were observed in 2015 (i.e., two years after the 2011-2013 drought). Second, higher annual N export was observed when more precipitation occurred during the pre-planting or early-growing season versus later periods. For both catchments, the highest 50% of flows were responsible for majority of the NO₃-N export. We estimated that 33-37%, 61-62%, and 82-85% of the NO₃-N loads occurred in the 90th, 75th, and 50th flow percentiles, respectively. As demonstrated in High-BMP 12, stacked BMP application effectively lowered NO₃-N and TN loads by 60.3% and 59.1%, respectively, relative to Low-BMP 11. Although 27.6% BMP coverage area in Low-BMP 11 was considered low for this study, this coverage area is higher than many other parts of the MARB. This research highlights the importance of joint efforts between landowners in a watershed to meet downstream water quality goals.

The Effects of Ditch Management in Agroecosystems on Embryonic and Tadpole Survival, Growth, and Development of Northern Leopard Frogs (Lithobates pipiens)

Agricultural drainage ditches help remove excess water from fields and provide habitat for wildlife. Drainage ditch management, which includes various forms of vegetation clearing and sediment dredging, can variably affect the ecological function of these systems. To determine whether ditch conditions following dredging/vegetation clearing management affected the survival, growth, and development of embryos and tadpoles of northern leopard frogs (Lithobates pipiens), we conducted three field studies using in situ cages over 2 years. We measured nutrients, pesticides, and other water quality properties in vegetated/unmanaged (i.e., no clearing or dredging) and newly cleared/dredged (i.e., treeless, then dredged), clay-bottomed drainage ditches in a river basin in Eastern Ontario, Canada. Nutrients, atrazine, and total neonicotinoid concentrations were generally lower at the cleared/dredged sites, whereas glyphosate was at higher concentrations. In contrast, water-quality variables measured in situ, particularly temperature, dissolved oxygen, and turbidity, tended to be higher in the cleared/dredged sites. Total phosphorous and total organic carbon concentrations at all sites were above the recommended limits for amphibian assays. No significant differences were detected in the survival, hatching success, or development of embryos among the ditch management treatments, but premature hatching was observed at one vegetated/unmanaged site where high specific conductivity may have been formative. We found the cleared/dredged sites supported earlier tadpole growth and development, likely as a result of the higher water temperatures. Increased temperature may have offset other growth/development stressors, such as those related to water chemistry. However, the long-term consequences of these differences on amphibian populations requires further study.

Evaluating management options to reduce Lake Erie algal blooms using an ensemble of watershed models

Reducing harmful algal blooms in Lake Erie, situated between the United States and Canada, requires implementing best management practices to decrease nutrient loading from upstream sources. Bi-national water quality targets have been set for total and dissolved phosphorus loads, with the ultimate goal of reaching these targets in 9-out-of-10 years. Row crop agriculture dominates the land use in the Western Lake Erie Basin thus requiring efforts to mitigate nutrient loads from agricultural systems. To determine the types and extent of agricultural management practices needed to reach the water quality goals, we used five independently developed Soil and Water Assessment Tool models to evaluate the effects of 18 management scenarios over a 10-year period on nutrient export. Guidance from a stakeholder group was provided throughout the project, and resulted in improved data, development of realistic scenarios, and expanded outreach. Subsurface placement of phosphorus fertilizers, cover crops, riparian buffers, and wetlands were among the most effective management options. But, only in one realistic scenario did a majority (3/5) of the models predict that the total phosphorus loading target would be met in 9-out-of-10 years. Further, the dissolved phosphorus loading target was predicted to meet the 9-out-of-10-year goal by only one model and only in three scenarios. In all scenarios evaluated, the 9-out-of-10-year goal was not met based on the average of model predictions. Ensemble modeling revealed general agreement about the effects of several practices although some scenarios resulted in a wide range of uncertainty. Overall, our results demonstrate that there are multiple pathways to approach the established water quality goals, but greater adoption rates of practices than those tested here will likely be needed to attain the management targets.

Soil salinization management for sustainable development: A review

The expansion of irrigated agriculture is of paramount importance to feed the burgeoning global population. However, without proper management, this expansion can result in environmental problems of irrigation-induced soil salinization. A recent FAO estimate reported that a large portion of total global soil resources are degraded and this problem is persistently expanding. Many irrigated areas of the world are facing the twin problems of soil salinization and waterlogging and presently over 20% of the total global irrigated area is negatively affected by these problems. And, if left unattended, this problem could expand to over 50% of the total global irrigated areas by 2050. The proper management of the aforementioned soil salinization is imperative for achieving most of the Sustainable Development Goals (SDGs) of the United Nations. For example, soil salinization management is vital for achieving the 'Zero Hunger' (SDG2) and 'Life on Land' (SDG15) among other SDGs. This paper provides a comprehensive review of different measures used for managing the environmental problems of soil salinization. All the possible sources of related and up to date literature have been accessed and over 250 publications were collected and thoroughly analyzed for this review. The centrality of the environmental problems is provided. The background of the problems, managing rising water table to control soil salinization, the role of drainage frameworks, the conjunctive use of diverse water sources, utilization of numerical models, and the use of remote sensing and GIS systems are described. And the application of the aforementioned techniques and methods in various case study regions across the globe are discussed which is followed by discussion and research gaps. Derived from the literature analysis and based on the identified research gaps, some key recommendations for future research have been made which could be useful for the stakeholders. The literature analysis revealed that an all-inclusive approach for dealing with the aforesaid environmental problems has been barely considered in the previous studies. Similarly, the continuing impacts of growing salt-tolerant plants on soil characteristics and the environment in total have not been widely considered in the previous investigations. Likewise, better irrigation practices and improved cropping systems along with the long-term environmental impacts of a particular approach has not been extensively covered in these studies. Also, previous studies have scarcely incorporated economic, social, and environmental aspects of the salinization problem altogether in their analysis. The analysis suggested that an inclusive feedback-supported simulation model for managing soil salinization should be considered in future research as the existing models scarcely considered some vital aspects of the problem. It is also suggested to enhance the sensing methods besides retrieval systems to facilitate direct detection of salinization and waterlogging parameters at large-scales. The existing time-lag between occurrence and recording of various data is also suggested to improve in the future scenario by the usage of information from multiple satellites that lessens the problems of spatial resolution by increasing the system efficiency.

Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields

Crop yield prediction prior to harvest is important for crop income and insurance projections, and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and predictor variables, especially at the field scale. In this study, an artificial neural network (ANN) method was used: (1) to evaluate the relative importance of predictor variables for the prediction of within-field corn and soybean end-of-season yield and (2) to evaluate the performance of the ANN models with a minimal optimized variable dataset for their capacity to predict corn and soybean yield over multiple years at the within-field level. Several satellite derived vegetation indices (normalized difference vegetation index—NDVI, red edge NDVI and simple ratio—SR) and elevation derived variables (slope, flow accumulation, aspect) were used as crop yield predictor variables, hypothesizing that the different variables reflect different crop and site conditions. The study identified the SR index and the slope as the most important predictor variables for both crop types during two training and testing years (2011, 2012). The dates of the most important SR images, however, were different for the two crop types and corresponded to their critical crop developmental stages (phenology). The relative mean absolute errors were overall smaller for corn compared to soybean: all of the 2011 corn study fields had errors below 10%; 75% of the fields had errors below 10% in 2012. The errors were more variable for soybean. In 2011, 37% of the fields had errors below 10%, while in 2012, 100% of the fields had errors below 20%. The results are promising and can provide yield estimates at the farm level, which could be useful in refining broader scale (e.g., county, region) yield projections.

Do reductions in agricultural field drainage during the growing season impact bacterial densities and loads in small tile-fed watersheds?

Predicting bacterial levels in watersheds in response to agricultural beneficial management practices (BMPs) requires understanding the germane processes at both the watershed and field scale. Controlling subsurface tile drainage (CTD) is a highly effective BMP at reducing nutrient losses from fields, and watersheds when employed en masse, but little work has been conducted on CTD effects on bacterial loads and densities in a watershed context. This study compared fecal indicator bacteria (FIB) [E. coli, Enterococcus, Fecal coliform, Total coliform, Clostridium perfringens] densities and unit area loads (UAL) from a pair of flat tile-drained watersheds (∼250-467 ha catchment areas) during the growing season over a 10-year monitoring period, using a before-after-control-impact (BACI) design (i.e., test CTD watershed vs. reference uncontrolled tile drainage (UCTD) watershed during a pre CTD intervention period and a CTD-intervention period where the test CTD watershed had CTD deployed on over 80% of the fields). With no tile drainage management, upstream tile drainage to ditches comprised ∼90% of total ditch discharge. We also examined FIB loads from a subset of tile drained fields to determine field load contributions to the watershed drainage ditches. Statistical evidence of a CTD effect on FIB UAL in the surface water systems was not strong; however, there was statistical evidence of increased FIB densities [pronounced when E. coli >200 most probable number (MPN) 100 mL^-1] in the test CTD watershed during the CTD-intervention period. This was likely a result of reduced dilution/flushing in the test CTD watershed ditch due to CTD significantly decreasing the amount of tile drainage water entering the surface water system. Tile E. coli load contributions to the ditches were low; for example, during the 6-yr CTD-intervention period they amounted to on average only ∼3 and ∼9% of the ditch loads for the test CTD and reference UCTD watersheds, respectively. This suggests in-stream, or off-field FIB reservoirs and bacteria mobilization drivers, dominated ditch E. coli loads in the watersheds during the growing season. Overall, this study suggested that decision making regarding deployment of CTD en masse in tile-fed watersheds should consider drainage practice effects on bacterial densities and loads, as well as CTD's documented capacity to boost crop yields and reduce seasonal nutrient pollution.

Life in the slow drain: Landscape structure affects farm ditch water quality

Agrichemical contamination is a major threat to aquatic ecosystems in farmland. There is a need to better understand the influence of the surrounding landscape on farm wetlands to recommend land management options that minimize water quality impacts from agricultural practices. We tested hypothesized relationships between landscape structure and multiple water quality measures in farm drainage ditches in a multi-landscape study in Eastern Ontario, Canada. We measured physicochemical water quality (levels of atrazine, glyphosate, neonicotinoid insecticides, inorganic nitrogen, and dissolved oxygen), and biological water quality indicators (aquatic macroinvertebrate richness, leaf litter decomposition, and Ceriodaphnia dubia population responses) in 27 farm ditches, and measured the amounts of forest cover and high-intensity crop cover (landscape composition), and field edge cover (landscape configuration) in 1-km radius landscapes surrounding each ditch sampling site. We used confirmatory path analysis to simultaneously model the direct and indirect relationships between the landscape predictors and water quality variables. Landscape composition measures were the strongest predictors of water quality: pesticides decreased as surrounding forest cover increased, and nitrogen increased with increasing amounts of high-intensity crop cover. Crop cover was also indirectly negatively related to macroinvertebrate richness via its effects on nitrogen and dissolved oxygen. We found no effects of landscape configuration on agrichemical levels, but there was some support for a positive relationship between macroinvertebrate richness and field edge cover. Our results indicate that aquatic macroinvertebrate richness is strongly impacted by fertilizer use in our region, and that macroinvertebrate richness is a more sensitive biotic indicator of farmland water quality than leaf litter decomposition or C. dubia responses. We conclude that, in our region, landscape management to improve farmland water quality should focus primarily on landscape composition. Such management should aim to increase amounts of non-crop cover such as forest, and reduce amounts of crop cover with high agrichemical inputs.

Aquatic Bacterial Communities Associated With Land Use and Environmental Factors in Agricultural Landscapes Using a Metabarcoding Approach

This study applied a 16S rRNA gene metabarcoding approach to characterize bacterial community compositional and functional attributes for surface water samples collected within, primarily, agriculturally dominated watersheds in Ontario and Québec, Canada. Compositional heterogeneity was best explained by stream order, season, and watercourse discharge. Generally, community diversity was higher at agriculturally dominated lower order streams, compared to larger stream order systems such as small to large rivers. However, during times of lower relative water flow and cumulative 2-day rainfall, modestly higher relative diversity was found in the larger watercourses. Bacterial community assemblages were more sensitive to environmental/land use changes in the smaller watercourses, relative to small-to-large river systems, where the proximity of the sampled water column to bacteria reservoirs in the sediments and adjacent terrestrial environment was greater. Stream discharge was the environmental variable most significantly correlated (all positive) with bacterial functional groups, such as C/N cycling and plant pathogens. Comparison of the community structural similarity via network analyses helped to discriminate sources of bacteria in freshwater derived from, for example, wastewater treatment plant effluent and intensity and type of agricultural land uses (e.g., intensive swine production vs. dairy dominated cash/livestock cropping systems). When using metabarcoding approaches, bacterial community composition and coexisting pattern rather than individual taxonomic lineages, were better indicators of environmental/land use conditions (e.g., upstream land use) and bacterial sources in watershed settings. Overall, monitoring changes and differences in aquatic microbial communities at regional and local watershed scales has promise for enhancing environmental footprinting and for better understanding nutrient cycling and ecological function of aquatic systems impacted by a multitude of stressors and land uses.

Alternative futures of dissolved inorganic nitrogen export from the Mississippi River Basin: influence of crop management, atmospheric deposition, and population growth

Nitrogen (N) export from the Mississippi River Basin contributes to seasonal hypoxia in the Gulf of Mexico (GOM). We explored monthly dissolved inorganic N (DIN) export to the GOM for a historical year (2002) and two future scenarios (year 2022) by linking macroeonomic energy, agriculture market, air quality, and agriculture land management models to a DIN export model. Future scenarios considered policies aimed at encouraging bioenergy crop production and reducing atmospheric N-emissions, as well as the effect of population growth and the states' infrastructure plans on sewage fluxes. Model-derived DIN export decreased by about 9% (from 279 to 254 kg N km-2 year-1) between 2002 and 2022 due to a 28% increase in area planted with corn, 24% improvement in crop N-recovery efficiency (NRE, to 0.52), 22% reduction in atmospheric N deposition, and 23% increase in sewage inputs. Changes in atmospheric and sewage inputs had a relatively small effect on DIN export and the effect of bioenergy crop production depended on nutrient management practices. Without improved NRE, increased production of corn would have increased DIN export by about 14% (to 289 kg N km-2 year-1) between 2002 and 2022. Model results suggest that meeting future crop demand while reducing the areal extent of hypoxia could require aggressive actions, such improving basin-level crop NRE to 0.62 or upgrading N-removal capabilities in waste water treatment plants beyond current plans. Tile-drained cropland could contribute up to half of DIN export; thus, practices that reduce N losses from tile drains could also have substantial benefit.

Evaluation of Phosphorus Filter Media for an Inline Subsurface Drainage Treatment System

Subsurface drainage from agricultural land has been identified as a contributor of both N and P into surface waters, leading to water quality degradation and eutrophication. This study evaluates the ability of P sorption media (PSM; expanded shale, expanded clay, furnace slag, and natural soil) to sorb P in both batch and column tests. Batch sorption tests estimated sorption of 3.4, 1.2, and 0.5 g P kg for expanded shale, expanded clay, and natural soil, respectively. Furnace slag sorption was evaluated for fine (FS), small (FS), and large (FS) particle sizes, with estimated sorption of 6.8, 5.1, and 3.8 g P kg, respectively. Phosphorus removal for the three furnace slag particle sizes and natural soil were tested in flow-through columns operated at residence times of 50, 17, and 7 s. A decrease in residence time reduced P removal in all columns evaluated. Following all trials, the average P removal from influent was 50% for FS, followed by 27% for FS (furnace slag-coated pea gravel), 22% for FS, and 6% for sandy loam-coated pea gravel. The data from this study provides crucial information for developing and sizing an inline tile drainage treatment system to remove P from tile drainage outlets before reaching surface waters.