Quantifying the contribution of tile drainage to basin-scale water yield using analytical and numerical models

Wetland-mediated nitrate reductions attenuate downstream: Insights from a modeling study

Connections between agricultural runoff and excess nitrogen in the Upper Mississippi River Basin are well-documented, as is the potential role of constructed wetlands in mitigating this surplus nitrogen. However, limited knowledge exists about the "best" placement of these wetlands for downstream nitrogen reductions within a whole watershed context as well as how far downstream these benefits are realized. In this study, we simulate the cumulative impacts of diverse wetland restoration scenarios on downstream nitrate reductions in different subbasins of the Raccoon River Watershed, Iowa, USA, and spatially trace their relative effects downstream. Our simulated results underscore previous work demonstrating that the total area of wetlands and the wetland-catchment-to-wetland area ratio are both significant factors for determining the nitrate load reduction benefits of wetlands at subbasin scales. Simulated wetland conservation scenarios resulted in nitrate load decreases ranging from 7.5 to 43.2% of our baseline model loads. However, we found these wetland-mediated nitrate reduction benefits are quickly attenuated downstream: load reductions were <1% at the watershed outlet across all model scenarios, despite the magnitude of the subbasin-scale nitrate decreases. The relatively rapid attenuation of wetland effects is largely due to downstream nitrate load contributions from untreated subbasins. However, higher subbasin-scale nitrate reductions from wetland-based conservation practices resulted in longer downstream distances prior to attenuation. This study highlights the importance of considering the spatial location of constructed or restored wetlands relative to the area within the watershed where nitrogen reductions are most needed.

Prioritizing river basins for nutrient studies

Increases in fluxes of nitrogen (N) and phosphorus (P) in the environment have led to negative impacts affecting drinking water, eutrophication, harmful algal blooms, climate change, and biodiversity loss. Because of the importance, scale, and complexity of these issues, it may be useful to consider methods for prioritizing nutrient research in representative drainage basins within a regional or national context. Two systematic, quantitative approaches were developed to (1) identify basins that geospatial data suggest are most impacted by nutrients and (2) identify basins that have the most variability in factors affecting nutrient sources and transport in order to prioritize basins for studies that seek to understand the key drivers of nutrient impacts. The "impact" approach relied on geospatial variables representing surface-water and groundwater nutrient concentrations, sources of N and P, and potential impacts on receptors (i.e., ecosystems and human health). The "variability" approach relied on geospatial variables representing surface-water nutrient concentrations, factors affecting sources and transport of nutrients, model accuracy, and potential receptor impacts. One hundred and sixty-three drainage basins throughout the contiguous United States were ranked nationally and within 18 hydrologic regions. Nationally, the top-ranked basins from the impact approach were concentrated in the Midwest, while those from the variability approach were dispersed across the nation. Regionally, the top-ranked basin selected by the two approaches differed in 15 of the 18 regions, with top-ranked basins selected by the variability approach having lower minimum concentrations and larger ranges in concentrations than top-ranked basins selected by the impact approach. The highest ranked basins identified using the variability approach may have advantages for exploring how landscape factors affect surface-water quality and how surface-water quality may affect ecosystems. In contrast, the impact approach prioritized basins in terms of human development and nutrient concentrations in both surface water and groundwater, thereby targeting areas where actions to reduce nutrient concentrations could have the largest effect on improving water availability and reducing ecosystem impacts.

Runoff nitrogen losses under confluence and diverging drainage systems in the sloped plot scale: A comparative study

The drainage system is a key measure for regulating runoff nutrient losses on sloping farmlands. Confluence and diverging drainage systems are two drainage layouts representing natural water network systems and are widely distributed in sloping farmlands; however, the effects of these drainage systems on runoff nutrient losses in the sloped plots remain unclear. This study investigated the effects of different drainage systems on the characteristics of runoff nitrogen (N) losses in sloped plots using laboratory rainfall simulations. Three treatments, including bare slope (without drainage system, CK), confluence drainage system (T1), and diverging drainage system (T2), were used to compare the changes in concentrations and losses of total nitrogen (TN), dissolved nitrogen (DN), and particulate nitrogen (PN), and the DN:TN ratio in runoff under a combination of 1.8 mm min-1 rainfall intensity and three slope gradients (5°, 10°, and 15°). The results showed that the time to runoff was significantly delayed in T2 compared with that in CK and T1 across all slopes (p < 0.05). Accumulated runoff depth was considerably lower in T1 and T2 than in CK across all slopes (p < 0.05). The TN and PN concentrations in T1 were markedly lower than those in T2 on the 10° and 15° slopes (p < 0.05). The DN concentration in T1 was lowest at the 5° slope (p < 0.05). TN loss in T1 was 14.7-33.9% and 17.9-30.3% lower than those in CK and T2 across all slopes, respectively (p < 0.05). The PN loss in T1 was 56.7% and 53.3% lower than that in T2 on the 10° and 15° slopes, respectively (p < 0.05). DN loss in T1 was 39.3-72.5% lower than that in CK for all slopes (p < 0.05). DN:TN in T2 was lower than that in CK and T1 at the 10° and 15° slopes (p < 0.05). Our results confirm the effectiveness of drainage systems in reducing runoff nutrient losses in a sloped plot and demonstrate that the confluence drainage system is better at reducing N losses in runoff than diverging drainage systems.

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.

Dissolved inorganic and organic carbon export from tile-drained midwestern agricultural systems

While carbon is a critically important natural element cycling through the soil profile of agricultural systems, few studies have examined the flux of dissolved organic carbon (OC) and inorganic carbon (IC) through artificially-drained cropped fields. In this study, we monitored eight tile outlets, nine groundwater wells and the receiving stream during a March to November period in 2018 to quantify subsurface IC and OC flux from tiles and groundwater to a perennial stream from a single cropped field in north-central Iowa. Results showed that carbon export from the field was dominated by IC losses through subsurface drainage tiles that were 20× higher than dissolved OC concentration in tiles, groundwater and in Hardin Creek. IC loads from tiles comprised approximately 96 % of the total carbon export. Detailed soil sampling within the field quantified TC stocks to a 1.2 m depth (246,514 kg/ha), and based on the maximum annual rate of IC loss from the field (553 kg/ha per year), we estimated that approximately 0.23 % of the TC content (0.32 % of the TOC content and 0.70 % of the TIC content) of the shallow soils was lost in a single year. Loss of dissolved carbon from the field is likely offset by reduced tillage and additions of lime. Study results suggest that attention should be given to improved monitoring of aqueous total carbon export from fields for accurate accounting of carbon sequestration performance.

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.

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.

Paired riparian water table monitoring to quantify hydraulic loading to a saturated buffer

The use of saturated buffers for reducing NO₃-N loads from tile-drained croplands is increasing in the US Midwest and there is a need to develop options for estimating reductions at riparian sites. In this study, we present a paired water table monitoring approach to estimate hydraulic and NO₃-N loading into a saturated buffer in eastern Iowa. One well was located within the saturated buffer (treatment) and a second well was installed in the same section of the riparian buffer but without the saturated buffer (control). Over a season of monitoring, water table depths were remarkably consistent between the two wells but the water table beneath the saturated buffer was consistently 0.22 m higher than the non-saturated buffer control. The increase in water table height increased the amount of water discharged from a 162 m long buffer by 468.2 m³/year and, assuming concentration reduction of 15 mg/l, resulted in a N reduction of approximately 7 kg. Although more work is needed to document this paired monitoring approach elsewhere, the method may hold promise for inexpensively quantifying the performance of conservation practices at landowner-led sites.

Evaluating the contribution of subsurface drainage to watershed water yield using SWAT+ with groundwater modeling

Drainage outflow from artificial subsurface drains can be a significant contributor to watershed water yield in many humid regions of the world. Although many studies have undertaken to simulate hydrologic processes in drained watersheds, there is a need for a study that first, uses physically based spatially distributed modeling for both surface and subsurface processes; and second, quantifies the effect of surface and subsurface parameters on watershed drainage outflow. This study presents a modified version of the SWAT+ watershed model to address these objectives. The SWAT+ model includes the gwflow module, a new spatially distributed groundwater routine for calculating groundwater storage, groundwater head, and groundwater fluxes throughout the watershed using a grid cell approach, modified in this study to simulate the removal of groundwater by subsurface drains. The modeling approach is applied to the South Fork Watershed (583 km²), located in Iowa, USA, where most fields are drained artificially. The model is tested against measured streamflow, groundwater head at monitoring wells, and drainage outflow from a monitored subbasin. Sensitivity analysis is then applied to determine the land surface, subsurface, and drainage parameters that control subsurface drainage. Simulated drainage flow fractions (fraction of streamflow that originates from subsurface drainage) range from 0.37 to 0.54 during 2001-2012, with lower fractions occurring during years of high rainfall due to the increased volumes of surface runoff. Subsurface drainage comprises the vast majority of baseflow. Results indicate surface runoff and soil percolation parameters have the strongest effect on watershed-wide subsurface drainage rather than aquifer and drain properties, pointing to a holistic watershed approach to manage subsurface drainage. The modeling code presented herein can be used to simulate significant hydrologic fluxes in artificially drained watersheds worldwide.

Improving Hillslope Link Model Performance from Non-Linear Representation of Natural and Artificially Drained Subsurface Flows

This study evaluates the potential for a newly proposed non-linear subsurface flux equation to improve the performance of the hydrological Hillslope Link Model (HLM). The equation contains parameters that are functionally related to the hillslope steepness and the presence of tile drainage. As a result, the equation provides better representation of hydrograph recession curves, hydrograph timing, and total runoff volume. The authors explore the new parameterization’s potential by comparing a set of diagnostic and prognostic setups in HLM. In the diagnostic approach, they configure 12 different scenarios with spatially uniform parameters over the state of Iowa. In the prognostic case, they use information from topographical maps and known locations of tile drainage to distribute parameter values. To assess performance improvements, they compare simulation results to streamflow observations during a 17-year period (2002–2018) at 140 U.S. Geological Survey (USGS) gauging stations. The operational setup of the HLM model used at the Iowa Flood Center (IFC) serves as a benchmark to quantify the overall improvement of the model. In particular, the new equation provides better representation of recession curves and the total streamflow volumes. However, when comparing the diagnostic and prognostic setups, the authors found discrepancies in the spatial distribution of hillslope scale parameters. The results suggest that more work is required when using maps of physical attributes to parameterize hydrological models. The findings also demonstrate that the diagnostic approach is a useful strategy to evaluate models and assess changes in their formulations.

Influence of redox gradients on nitrate transport from the landscape to groundwater and streams

Increases in nitrogen applications to the land surface since the 1950s have led to a cascade of negative environmental impacts, including degradation of drinking water supplies, nutrient enrichment of aquatic ecosystems and contributions to global climate change. In this study, groundwater, streambed porewater, and stream sampling were used to establish trends in nitrate concentrations and how redox gradients influence nitrate transport across diverse glacial terranes. Decadal sampling has found that elevated nitrate concentrations in shallow groundwater beneath cropland have been sustained for decades. Redox gradients established in the saturated zone using dissolved O₂, iron, nitrate and excess N₂ from denitrification suggest that nitrate-bearing zones are thin in glacial terranes dominated by fine materials. These thin nitrate-bearing zones lead to suboxic, low nitrate streambed porewater and limit the contributions of nitrate to streams from slow-flow groundwater. In contrast, thick oxic zones in more coarse-grained glacial terranes allow nitrate to reach deeper groundwater, resulting in streambed porewater with elevated nitrate concentrations and causing a large portion of stream nitrate to be derived from slow-flow groundwater. Groundwater age tracer data indicate that denitrification occurs more quickly in the terrane dominated by fine material than in the more coarse-grained terrane. The quicker depletion of nitrate in the more fine-grained terrane suggests that the thinner oxic zone in this terrane is due, in part, to the greater availability and reactivity of electron donors in this terrane than in the more coarse-grained terrane. Groundwater age tracer data and hydrograph separation analysis suggest that saturated zone lag times between when changes in land use practices occur and when changes in stream water are fully observed may vary widely across hydrogeologic settings.

Important factors when simulating the water and nitrogen balance in a tile-drained agricultural field under long-term monitoring

Despite the effectiveness of tile drain systems as a water management practice in naturally poorly drained soils, they facilitate the transport of NO₃^--N to surface water bodies. In order to improve the risk assessment of this significant transport under increased applications of N fertilisers in agriculture, it is imperative to delineate the controlling factors and processes. The aim of this study was to acquire such knowledge using the 1D Daisy model to simulate water and N balance based on comprehensive data from a ten-year monitoring study of a tile-drained loamy field in Denmark under the actual crop rotation of winter wheat, sugar beet, spring barley, winter rape and maize. The model simulated the cumulative drainage and NO₃^--N leaching over the ten-year period satisfactorily with NSE of 1.00 and 0.87 respectively. While the annual N input to the model was 181 kg N ha^-1, an average of 139 kg N ha^-1 was harvested in the crop, 22 kg N ha^-1 was leached through deep percolation, 17 kg N ha^-1 was leached to the tile drains, and 14 kg N ha^-1 was lost due to denitrification. Although the model satisfactorily captured the monitored data, the results of this study highlight: (i) the requirement for improved parameterisation of winter crops, (ii) the need to give further consideration in the model to soil surface and macropore processes that govern water infiltration and (iii) that measured and simulated NO₃^--N concentrations in the drainage exceeded the limit defined by the European Drinking Water Directive and Nitrates Directive for drinking water and hence improved N management strategies are essential for tile-drained agricultural fields in temperate regions under conventional crop rotations.

Quantifying the effectiveness of a saturated buffer to reduce tile NO3-N concentrations in eastern Iowa

Agricultural drainage tiles are primary contributors to NO₃-N export from Iowa croplands. Saturated buffers are a relatively new conservation practice that diverts tile water into a distribution tile installed in a riparian buffer parallel to a stream with the intent of enhancing NO₃-N processing within the buffer. In this study, tile NO₃-N concentration reductions were characterized through two different saturated buffers at a working farm site in eastern Iowa. Study objectives were to (1) evaluate the hydrogeology and water quality patterns in the saturated buffer and (2) quantify the reduction in tile NO₃-N concentration from the saturated buffer installation. Results showed that the two saturated buffers are reducing NO₃-N concentrations in tile drainage water from input concentrations of approximately 15 mg/l to levels < 1.5 mg/l at the streamside well locations. The reduction occurs rapidly in the fine-textured and organic-rich alluvial soils with most of the reduction occurring within 1.5 m of the distribution line. Denitrification is hypothesized as being primarily responsible for the concentration reductions based on soil and water chemistry conditions, completion of a geophysical survey (quantifying low potential for N loss to deeper aquifers), and comparisons to other similar Iowa sites. The study provides more assurance to new adopters that this practice can be installed in many areas throughout the Midwestern Cornbelt region.

Analysis of alternative climate datasets and evapotranspiration methods for the Upper Mississippi River Basin using SWAT within HAWQS

This study reports the application of Soil and Water Assessment Tool (SWAT) within the Hydrologic and Water Quality System (HAWQS) on-line platform, for the Upper Mississippi River Basin (UMRB). The UMRB is an important ecosystem located in the north central U.S. that is experiencing a range of ecological stresses. Specifically, testing of SWAT was performed for: (1) Hargreaves (HG) and Penman-Monteith (PM) PET methods, and (2) Livneh, National Climatic Data Center (NCDC) and Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate datasets. The Livneh-PM combination resulted in the highest average annual water yield of 380.6 mm versus the lowest estimated water yield of 193.9 mm for the Livneh-HG combination, in response to 23-year uncalibrated simulations. Higher annual ET and PET values were predicted with HG method versus the PM method for all three weather datasets in response to the uncalibrated simulations, due primarily to higher HG-based estimates during the growing season. Based on these results, it was found that the HG method is the preferred PET option for the UMRB. Initial calibration of SWAT was performed using the Livneh data and HG method for three Mississippi River main stem gauge sites, which was followed by spatial validation at 10 other gauge sites located within the UMRB stream network. Overall satisfactory results were found for the calibration and validation gauge sites, with the majority of R2 values ranging between 0.61 and 0.82, Nash-Sutcliffe modeling efficiency (NSE) values ranging between 0.50 and 0.79, and Kling-Gupta efficiency (KGE) values ranging between 0.61 and 0.84. The results of an additional experimental suite of six scenarios, which represented different combinations of climate data sets and calibrated parameters, revealed that suggested statistical criteria were again satisfied by the different scenario combinations. Overall, the PRISM data exhibited the strongest reliability for the UMRB.