Tile Flow Research Articles

Subsurface influences on watershed nutrient concentrations and loading in a clay dominated agricultural system

Water quality issues in the Great Lakes Basin persist despite management and monitoring efforts. With changing land use and climatic conditions, the need for improved understanding of nutrient loss from agricultural field to surface water is imperative to reduce consequences on human and aquatic life, such as perpetual algal blooms and contaminated drinking water. There remains a gap in holistic rural water management studies that investigate the understanding of the water cycle in rural settings and the interconnections between different components of the water cycle, including artificial drainage. In the current study, a year-round paired investigation of subsurface and nutrient dynamics was conducted in a small, intensively managed agricultural watershed within southwestern Ontario, Canada. Nutrients (Nitrate and Phosphorus) and stable isotopes of water (δ2H and δ18O) were sampled at varying scales (i.e., field and watershed), from multiple hydrologic components (e.g., groundwater, surface water, tile flow, and soil water), from 2020 to 2022. Results indicate that nutrient concentrations in surface water were elevated during the growing season, while nutrient loading was greater during the non-growing season in surface water. Monthly nitrate loads were found to be significantly (p < 0.01) related to groundwater elevation, soil moisture and tile flow, whereas total phosphorus loading was found to be significantly (p < 0.01) related to soil moisture and tile flow. δ2H and δ18O signatures revealed that during the growing season nutrient movement was predominantly through interflow pathways (including tile drainage) comprised of event-water. In the non-growing season, there was an increased subsurface influence on nutrient transport. This study highlights the importance of including subsurface characterization in nutrient management studies. A comprehensive understanding of varying seasonal hydrologic mechanisms that control nutrient movement within an agricultural watershed is essential to sustain growing rural communities.

Drainage water management, woodchip bioreactor, and saturated riparian buffer as stacked conservation practices for improving crop yields and water quality

Stacking edge-of-field practices may improve nutrient removal from crops. To examine the effects of stacking edge-of-field conservation practices, a woodchip bioreactor (WBR) and saturated riparian buffer (SRB) were installed in series by intercepting tile flow from a field having a drainage water management system. Nutrient monitoring from 5 years evaluated nutrient export annually and based on the precipitation intensity. Drainage water was monitored for total suspended solids (TSS), nitrate-N, total-P, total-N, and ortho-P at the inlet and outlet of WBR and control structure of SRB. Nutrient export reductions of WBR and SRB were determined for precipitation events that were categorized as low <12.7 mm, mid 12.7–25.4 mm, high 25.4–50.8 mm, and very high >50.8 mm. Over the five seasons, nitrate-N export was reduced 88 % at the WBR outlet and 78 % at SRB outlet when used in a stacked series configuration. The efficacy of edge-of-field practices was affected by the intensity of precipitation events. The low and mid-intensity precipitation events generated 67 % of the total discharge from the subsurface drainage system which accounted for 74 % of the influent nitrate-N. During low and mid-intensity precipitation events, discharge was reduced by 58–65 %, nitrate-N was reduced by 49–88 % and total-P was reduced by 65–73 % by using stacked practice of WBR and SRB. During high and very high-intensity precipitation events only nitrate-N export was reduced by 61–66 %. This indicates that when designing stacked edge-of-the-field practices the cumulative effect of the practices and their performance during different precipitation events should be taken into account when managing conservation practice-based cropping systems.

Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada

Abstract. Systematic tile drainage is used extensively in poorly drained agricultural lands to remove excess water and improve crop growth; however, tiles can also transfer nutrients from farmlands to downstream surface water bodies, leading to water quality problems. Thus, there is a need to simulate the hydrological behaviour of tile drains to understand the impacts of climate or land management change on agricultural surface and subsurface runoff. The Cold Regions Hydrological Model (CRHM) is a physically based, modular modelling system developed for cold regions. Here, a tile drainage module is developed for CRHM. A multi-variable, multi-criteria model performance evaluation strategy was deployed to examine the ability of the module to capture tile discharge under both winter and summer conditions (NSE &gt; 0.29, RSR &lt; 0.84 and PBias &lt; 20 for tile flow and saturated storage simulations). Initial model simulations run at a 15 min interval did not satisfactorily represent tile discharge; however, model simulations improved when the time step was lengthened to hourly but also with the explicit representation of capillary rise for moisture interactions between the rooting zone and groundwater, demonstrating the significance of capillary rise above the saturated storage layer in the hydrology of tile drains in loam soils. Novel aspects of this module include the sub-daily time step, which is shorter than most existing models, and the use of field capacity and its corresponding pressure head to provide estimates of drainable water and the thickness of the capillary fringe, rather than using detailed soil retention curves that may not always be available. An additional novel aspect is the demonstration that flows in some tile drain systems can be better represented and simulated when related to shallow saturated storage dynamics.

Assessing SWAT+ Performance in Simulating Drainage Water Management and Parameter Transferability for Watershed-Scale Applications

Drainage Water Management (DWM) is widely implemented to mitigate nutrient outflow from tile-drained croplands. However, the performance of process-based hydrological models in simulating DWM remains untested. This study aimed to assess the Soil and Water Assessment Tool (SWAT+) in simulating daily tile flow for a paired DWM field site in eastern South Dakota. Additionally, it sought to develop a method for determining the transferability of field-scale model parameterization to the surrounding watershed. Field-scale SWAT+ yielded satisfactory results during the calibration period (2016–2017) (East: NSE = 0.82, PBIAS = -26.8, RSR = 0.42; West: NSE = 0.75, PBIAS = -30.5, RSR = 0.5) and validation period (2018) (East: NSE = 0.71, PBIAS = -17, RSR = 0.55; West: NSE = 0.81, PBIAS = -4.6, RSR = 0.44) for each half of the experimental site. Further, ten-year SWAT+ simulations for the calibrated site showed an average annual reduction of 6.5 ± 1.7 mm in tile flow across the field due to DWM. Additionally, the study utilized remotely sensed Evapotranspiration to demonstrate that the calibrated site’s model parametrization could be transferred to only 28 % to 46 % of surrounding croplands each year. Overall, the implications of the study extend beyond South Dakota, making the proposed research applicable to other geographical regions with tiled croplands as well.

Saturated buffers: Improvements and issues.

Saturated buffers are a newly developed agricultural best management practice used to redirect tile flow away from waterways, thereby mitigating nutrient losses and downstream eutrophication. This study evaluated the potential benefits of a novel saturated buffer design, which included pitchfork-shaped (PF) dispersion lines and a backflow check valve, that was installed alongside a traditional or standard (ST) buffer on a field in Moultrie County, Illinois, in the spring of 2019. Daily flow measurements and routine water samples were used to monitor the movement of water through both buffers and estimate nutrient loads. During observation days in 2020 and 2021, the PF buffer diverted 35% and 1.9% of incoming tile flow, respectively, while the ST buffer increased effluent rates by 116% and 137% over the same period. Both the PF and ST buffers experienced backflow from 30% to 47% of the monitoring period, well above the often reported 5%. Ultimately, the efficacy of saturated buffers could be improved with minimal, low-cost additions to their designs. Check valves are a simple supplement to saturated buffer design that can enhance flow diversion and potential nutrient removal. Added dispersion lines provide more opportunity for diversion of tile flow; however, they require more land to be removed from agricultural production and could increase backflow volumes, so the costs and benefits should be weighed.

Modeling the Potential Influence of Subsurface Tile Drainage Systems on Downstream Flooding in a Midwestern Agricultural Watershed

Highlights Tile flow was simulated to study the impacts of tile drainage on watershed hydrology and downstream flood days. Three tile drainage scenarios with varied extents of drained land were compared with a baseline scenario. The depth of tile flow contributing to streamflow was found to increase as the area of drained land increased. Results suggest that drainage systems decrease flood days when compared to the baseline scenario. Abstract. Subsurface tile drainage systems are common in agricultural regions of the Midwestern United States. Drainage systems remove excess water from the surface and soil profile of agricultural fields, allowing crop production in previously unsuitable locations. However, these systems impact watershed hydrology and could influence flooding events. Therefore, this study aimed to determine whether tile drainage systems influence downstream flood days in a Midwestern agricultural watershed, specifically the Skunk Creek watershed. The Soil and Water Assessment Tool (SWAT) model was used to simulate the hydrologic processes of the Skunk Creek Watershed for an 18-year period (2004–2021). The model was calibrated and validated using observed daily streamflow data with the SWAT Calibration and Uncertainty Program (SWAT-CUP) software and through the manual modification of missed precipitation data. Three tile drainage scenarios—ranging from 15% to 75% tile-drained agricultural land—were individually incorporated into the model. Results indicated that with increased tile drainage, surface runoff, groundwater flow, deep aquifer recharge, and percolation decreased, whereas lateral soil flow, tile flow, evapotranspiration, and water yield increased. A comparison of tile drainage scenarios suggests that increasing the area of tile-drained agricultural land decreases total flood days. However, the impact of tile drainage systems on downstream peak flood flows varied by event, with large precipitation events initiating flood days across all scenarios. While tile flow decreased flood days on a daily time step, flash floods might have occurred on a sub-daily time step but were not captured in this study. Future studies can replicate the approach with a sub-daily time step for simulating hourly flood events with various tile drainage scenarios. Keywords: Midwestern United States, Streamflow, SWAT, Tile drainage, Watershed hydrology.

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.

Improving model capability in simulating spatiotemporal variations and flow contributions of nitrate export in tile-drained catchments

It is essential to identify the dominant flow paths, hot spots and hot periods of hydrological nitrate-nitrogen (NO3-N) losses for developing nitrogen loads reduction strategies in agricultural watersheds. Coupled biogeochemical transformations and hydrological connectivity regulate the spatiotemporal dynamics of water and NO3-N export along surface and subsurface flows. However, modeling performance is usually limited by the oversimplification of natural and human-managed processes and insufficient representation of spatiotemporally varied hydrological and biogeochemical cycles in agricultural watersheds. In this study, we improved a spatially distributed process-based hydro-ecological model (DLEM-catchment) and applied the model to four tile-drained catchments with mixed agricultural management and diverse landscape in Iowa, Midwestern US. The quantitative statistics show that the improved model well reproduced the daily and monthly water discharge, NO3-N concentration and loading measured from 2015 to 2019 in all four catchments. The model estimation shows that subsurface flow (tile flow + lateral flow) dominates the discharge (70–75%) and NO3-N loading (77–82%) over the years. However, the contributions of tile drainage and lateral flow vary remarkably among catchments due to different tile-drained area percentages and the presence of farmed potholes (former depressional wetlands that have been drained for agricultural production). Furthermore, we found that agricultural management (e.g. tillage and fertilizer management) and catchment characteristics (e.g. soil properties, farmed potholes, and tile drainage) play important roles in predicting the spatial distributions of NO3-N leaching and loading. The simulated results reveal that the model improvements in representing water retention capacity (snow processes, soil roughness, and farmed potholes) and tile drainage improved model performance in estimating discharge and NO3-N export at a daily time step, while improvement of agricultural management mainly impacts NO3-N export prediction. This study underlines the necessity of characterizing catchment properties, agricultural management practices, flow-specific NO3-N movement, and spatial heterogeneity of NO3-N fluxes for accurately simulating water quality dynamics and predicting the impacts of agricultural conservation nutrient reduction strategies.

Development and application of a parsimonious statistical model to predict tile flow in minerogenic soils

Development and application of a parsimonious statistical model to predict tile flow in minerogenic soils

Sustainability of cover cropping practice with changing climate in Illinois

Climate change could adversely impact the best management practices (BMPs) designed to build a sustainable agro-ecological environment. Cover cropping is a conservation practice capable of reducing nitrate-nitrogen (NO3–N) loadings by consuming water and nitrate from the soil. The objective of this study was to investigate how climate change would impact the proven water quality benefits of cereal rye as a winter cover crop (CC) over the climate divisions of Illinois using the DSSAT model. Moreover, this study explores the sustainability of the CC with the changing climate conditions by using five regional climate models (RCMs) projections of two warming scenarios-rcp45 (a medium emission scenario - radiative forcing of 4.5 W/m2) and rcp85 (a high emission scenario - radiative forcing of 8.5 W/m2)). The CC impact simulated in the warming scenarios for the near-term (2021–2040) and the far-term future (2041–2060) were compared with the baseline scenario (2001–2020). Our results conclude that the climate change may negatively impact [average of CC and no CC (NCC)] maize yield (−6.6%) while positively affecting soybean yield (17.6%) and CC biomass (73.0%) by the mid-century. Increased mineralization caused by rising temperature could increase the nitrate loss via tile flow (NLoss) and nitrate leached (NLeached) up to 26.3% and 7.6% on average by the mid-century in Illinois. Increasing CC biomass could reduce the NLoss more considerably in all the scenarios compared to the baselines. Nevertheless, the NLoss level in the CC treatment can increase from the near-term to far-term future and could get closer to the baseline levels in the NCC treatment. These results suggest that CC alone may not address nitrate loss goals via subsurface drainage (caused by increasing N mineralization) in future. Therefore, more robust and cost-effective BMPs are needed to aid the CC benefits in preventing nutrient loss from the agricultural fields.

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 water‑nitrogen (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.

Performance evaluation and modeling of active tile in raised-floor data centers: An empirical study on the single tile case

Raised-floor data centers usually suffer from the local hotspots resulted from uneven cool air delivery. These hotspots not only degrade server performance, but also threat equipment reliability. The commonly used industrial practice of increasing the Computer Room Air Conditioner (CRAC) blower speed for removing hotspots is energy inefficient and may lead to overcooling of some servers. In this paper, we explore the potential of active tiles in data center cooling management. In particular, we deploy a prototype of active tile in a production data center and conduct extensive experiments to investigate the cooling performance. It is shown that deploying the active tiles with even 10% fan speed increases the tile flow by 49%, and sealing the under-rack gap reduces the rack bottom temperature by up to 6°C. Moreover, three machine learning techniques, i.e., Gaussian Process Regression (GPR), Artificial Neural Network (ANN), and Multivariate Linear Regression (MLR) are employed to construct end-to-end data-driven thermal models for the active tile. Using field measured data as training and testing data sets, it is concluded that GPR and ANN are competent for accurate thermal modeling of active tiles. Specifically, GPR achieves the smallest prediction error which is around 0.3°C.

Technical note: Extending the SWAT model to transport chemicals through tile and groundwater flow

Abstract. The Soil and Water Assessment Tool (SWAT) is frequently used to simulate the transport of water-soluble chemicals in the environment such as pesticides and their metabolites originating from agricultural applications. However, the model does not simulate the transport of chemicals through subsurface tile drains and groundwater. This limitation is particularly significant in lowland regions and when simulating stable chemicals that can leach into and accumulate in groundwater. To fill this gap, the publicly available SWAT code was modified to complement the simulation of chemicals by adding transport capabilities through tile and groundwater flow. The extended model was tested in two agricultural catchments with a typically used pesticide and one of its metabolites. Results show that the transport of the pesticide is mainly governed by surface runoff and that shallow surface tile flow contributions can be significant. Metabolite concentrations in streamflow are, however, driven by a complex spatiotemporal interplay of all surface and subsurface transport components. This highlights the advantages of applying the modified code in catchment-scale environmental exposure studies and for developing best management practices or mitigation strategies. The new code is made available as an electronic supplement to this technical note.

Advanced practice-aided tile drain configuration: A solution to achieving environmentally sustainable agricultural production

Alternatives to conventional crop production practices are needed to achieve environmental sustainability. Because tile-drained crop production systems in the Midwestern United States are one of the single largest contributors to environmental degradation, we explored alternative tile drain configurations by changing the tile spacing and depth of tile-drained fields in central Illinois and then by evaluating comprehensively the impacts of different tile drain configurations on crop productivity and environmental sustainability using the Root Zone Water Quality Model 2 (RZWQM2). An analytic hierarchy process (AHP), which is a multicriteria decision analysis (MCDA) tool, was used to evaluate the optimum tile spacing and depth scenario. The model simulations and AHP tested three management schemes designated as “agricultural productivity” (AP), “environmental sustainability” (ES), and “advance in technology” (AT). The schemes were designed based on three criteria: operational cost, crop profit, and environmental control. Analysis showed that deeper tiles and narrower tile spacing resulted in decreases in flow and nitrate loss from runoff, seepage (SP), and lateral flow (LF), and increases in tile flow, total nitrate loss, and crop yields. On the basis of MCDA, the AP management scheme resulted in higher CP and total nitrate loss, whereas opposite outcomes were generated by the ES management scheme. Under the AT management scheme, higher ranked scenarios resulted in higher CP and lower total amounts of nitrate entering streams. Our analysis indicates that the AT scheme can simultaneously enhance crop production and ES through advances in tile drainage water treatment.

High‐resolution simulated water balance and streamflow data set for 1951–2020 for the territory of Poland

AbstractLong‐term simulated water balance and streamflow data for the territory of Poland with high spatio‐temporal resolution were reconstructed for the period 1951–2020 with a daily time step, using the Soil and Water Assessment Tool (SWAT) hydrological model. The spatial structure includes 4,381 sub‐basins and 47,725 hydrological response units. The SWAT model was extensively calibrated and validated following a two‐stage, multi‐site calibration method for 88 gauging stations across Poland. The simulations show satisfactory performance with a median Kling–Gupta efficiency of 0.73 and 0.7 in the calibration and validation period respectively. The model performance exceeded that of its predecessor, the SWAT model of the Vistula and Odra basins. The simulated hydrological data set covers daily water balance components at the sub‐basin level, including precipitation total, snowfall, snowmelt, evapotranspiration (actual and potential), surface runoff, soil water, percolation, groundwater recharge, groundwater flow, tile flow and water yield (all components in mm), and daily streamflow (m3/s) at the reach level. The data set is stored in an online, publicly available research data archive 4TU.Research Data (Marcinkowski, P., Kardel, I., Płaczkowska, E., Giełczewski, M., Osuch, P., Okruszko, T., Venegas‐Cordero, N., Ignar, S. &amp; Piniewski, M (2021). PL‐SWAT‐51_20: a high‐resolution simulated water balance and streamflow data set for 1951‐2020 for the territory of Poland, 4TU.ResearchData. dataset, https://doi.org/10.4121/16843183).

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.

Simplified CFD Model for Perforated Tile with Distorted Outflow

Most of the perforated tile flow CFD models in the literature so far assume the air velocity coming out of the tile openings (pores) is uniform. However, in typical applications, such as data centers and indoor environments, perforated tile or diffuser outflow can be highly non-uniform due to many reasons (e.g., spatial variation of plenum pressure or varying local tile geometrical patterns). For an ideal (uniform) tile flow velocity that has the same flow rate as the non-uniform tile flow velocity, the tile flow momentum of the latter will always be greater because momentum scales with velocity squared. To illustrate the effect of tile flow velocity distortion, two generic CFD cases (one with uniform velocity and the other with non-uniform velocity) with multiple openings model are presented here. Their CFD results are compared to the momentum source model results and validated against previously published data of an isolated tile flow measurement. The momentum source model is one of the simplest/most practical CFD models that uses a body-force value for correcting the momentum deficit between perforated and fully open areas. Initially, the momentum source model results show good agreement with results of the uniform velocity case only. Thus, due to velocity distortion (non-uniform velocity) in the tile flow, the CFD results presented in this paper show a potential reason to modify the body-force value in the momentum source model with an adjustment factor (C). Several values of C factor are numerically investigated for the present distorted tile flow CFD case, and the best match is found to be at C, equaling approximately 1.6.

Antecedent Conditions Control Thresholds of Tile‐Runoff Generation and Nitrogen Export in Intensively Managed Landscapes

AbstractThreshold changes in rainfall‐runoff generation commonly represent shifts in runoff mechanisms and hydrologic connectivity controlling water and solute transport and transformation. In watersheds with limited human influence, threshold runoff responses reflect interaction between precipitation event and antecedent soil moisture. Similar analyses are lacking in intensively managed landscapes where installation of subsurface drainage tiles has altered connectivity between the land surface, groundwater, and streams, and where application of fertilizer has created significant stores of subsurface nitrogen. In this study, we identify threshold patterns of tile‐runoff generation for a drained agricultural field in Illinois and evaluate how antecedent conditions—including shallow soil moisture, groundwater table depth, and the presence or absence of crops—control tile response. We relate tile‐runoff thresholds to patterns of event nitrate load observed across multiple storm events and evaluate how antecedent conditions control within‐event nitrate concentration‐discharge relationships. Our results demonstrate that an event tile‐runoff threshold emerges relative to the sum of gross precipitation and indices of antecedent shallow soil moisture and antecedent below‐tile groundwater moisture deficit, indicating that both shallow soil and below‐tile storages must be filled to generate significant runoff. In turn, event nitrate load shows a linear dependence on runoff for most time periods, suggesting that subsurface nitrate export and storage can be estimated using runoff threshold relationships and long‐term average nitrate concentrations. Finally, within‐event nitrate concentration‐discharge relationships are controlled by event size and the antecedent tile flow state because these factors dictate the sequence of flow path activation and tile connectivity over a storm event.

Development of a data-assimilation system to forecast agricultural systems: A case study of constraining soil water and soil nitrogen dynamics in the APSIM model

As we face today's large-scale agricultural issues, the need for robust methods of agricultural forecasting has never been clearer. Yet, the accuracy and precision of our forecasts remains limited by current tools and methods. To overcome the limitations of process-based models and observed data, we iteratively designed and tested a generalizable and robust data-assimilation system that systematically constrains state variables in the APSIM model to improve forecast accuracy and precision. Our final novel system utilizes the Ensemble Kalman Filter to constrain model states and update model parameters at observed time steps and incorporates an algorithm that improves system performance through the joint estimation of system error matrices. We tested this system at the Energy Farm, a well-monitored research site in central Illinois, where we assimilated observed in situ soil moisture at daily time steps for two years and evaluated how assimilation impacted model forecasts of soil moisture, yield, leaf area index, tile flow, and nitrate leaching by comparing estimates with in situ observations. The system improved the accuracy and precision of soil moisture estimates for the assimilation layers by an average of 42% and 48%, respectively, when compared to the free model. Such improvements led to changes in the model's soil water and nitrogen processes and, on average, increased accuracy in forecasts of annual tile flow by 43% and annual nitrate loads by 10%. Forecasts of aboveground measures did not dramatically change with assimilation, a fact which highlights the limited potential of soil moisture as a constraint for a site with no water stress. Extending the scope of previous work, our results demonstrate the power of data assimilation to constrain important model estimates beyond the assimilated state variable, such as nitrate leaching. Replication of this study is necessary to further define the limitations and opportunities of the developed system.

Development and Application of a Parsimonious Statistical Model to Predict Tile Flow in Minerogenic Soils

Development and Application of a Parsimonious Statistical Model to Predict Tile Flow in Minerogenic Soils