Evaluation of bioenergy crop growth and the impacts of bioenergy crops on streamflow, tile drain flow and nutrient losses in an extensively tile-drained watershed using SWAT

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.

Effect of alfalfa on subsurface (tile) nitrogen and phosphorus loss in Ohio, USA

Growing annual crops such as corn (Zea mays L.) can lead to considerable nutrient losses through subsurface drainage in agricultural fields, posing a serious threat to surface water quality in the midwestern United States. Perennial crops have the potential to reduce these nutrient losses. However, more comprehensive data are needed on the nutrient loss effect of perennial crops. We examined the effect of alfalfa (Medicago sativa L.) on nitrate-nitrogen (NO₃ ^- -N), total nitrogen (TN), dissolved reactive phosphorus (DRP), and total phosphorus (TP) in subsurface drainage using a before-after-control-impact (BACI) experimental design with one control field (with annual crops) and one impact field (with alfalfa) each on two farms (Sites A and B) located in northwestern Ohio. The "Before" period (prior to planting alfalfa at the impact field) extended for 4 yr (2013-2017) at Site A and 6 yr (2011-2017) at Site B; the "After" period extended for an additional 2 yr at both sites. Reductions in the mean monthly discharge and loads of NO₃ ^- -N, TN, DRP, and TP were significant at Site A, whereas the only significant change at site B was a reduction in the mean monthly TP load. Significant reductions in NO₃ ^- -N loads were observed during spring and winter at Site A. In addition, alfalfa reduced the variability of discharge and nutrient loads through subsurface drainage at both sites. Our findings suggest that introducing alfalfa into annual crop rotations has the potential to reduce subsurface nutrient loads and increase the resiliency of agricultural systems.

Response of Surface Runoff and Sediment to the Conversion of a Marginal Grassland to a Switchgrass (Panicum virgatum) Bioenergy Feedstock System

The land systems between the humid and arid zones around the globe are critical to agricultural production and are characterized by a strong integration of the land use and water dynamics. In the southern Great Plains (SGP) of the United States, lakes and farm ponds are essential components in the land systems, and they provide unique habitats for wildlife, and critical water resources for irrigation and municipal water supplies. The conversion of the marginal grasslands to switchgrass (Panicum virgatum) biofuel feedstock for energy production has been proposed in the region. However, we have limited experimental data to assess the impact of this potential land-use change on the surface runoff, which is the primary water source for surface impoundments. Here, we report the results from a paired experimental watershed study that compared the runoff and sediment responses that were related to the conversion of prairie to a low-input biomass production system. The results show no significant change in the relationship between the event-based runoff and the precipitation. There was a substantial increase in the sediment yield (328%) during the conversion phase that was associated with the switchgrass establishment (i.e., the site preparation, herbicide application, and switchgrass planting). Once the switchgrass was established, the sediment yield was 21% lower than the nonconverted watershed. Our site-specific observations suggest that switchgrass biofuel production systems will have a minimum impact on the existing land and water systems. It may potentially serve as an environmentally friendly and economically viable alternative land use for slowing woody encroachment on marginal lands in the SGP.

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.

Improvement of simulating sub-daily hydrological impacts of rainwater harvesting for landscape irrigation with rain barrels/cisterns in the SWAT model

Rain barrels/cisterns, a popular type of low impact development (LID) practice, can restore urban hydrological processes and decrease municipal water use by harvesting roof runoff for later use, such as landscape irrigation. However, tools to assist decision makers in creating efficient rainwater harvesting and reuse strategies are limited. This study improved the Soil and Water Assessment Tool (SWAT) in simulating the subdaily hydrological impacts of rainwater harvesting for landscape irrigation with rain barrels/cisterns, including the simulation of rainwater harvesting with rain barrels/cisterns, rainwater reuse for auto landscape irrigation, evapotranspiration, initial abstraction, impervious area, soil profile, and lawn management operation. The improved SWAT was applied in the urbanized Brentwood watershed (Austin, TX) to evaluate its applicability and investigate the impacts of rainwater harvesting and reuse strategies on the reductions and reduction efficiencies (reductions per volume of rain barrels/cisterns implemented) of field scale runoff (peak and depth) and watershed scale streamflow (peak and volume) for two storm events. Scenarios explored included different sizes of rain barrels/cisterns, percentages of rooftop areas with rain barrels/cisterns implemented, auto landscape irrigation rates, and landscape irrigation starting times. The performance of rainwater harvesting and reuse strategies, which is determined by features of fields, watersheds, and storm events, varied for different reduction goals (streamflow or runoff, and peak or depth/volume). For instance, the scenario with rain barrel/cistern sizes of 7.5 mm (design runoff depth from treated roof area) and the scenario with 10% of suitable area implemented with rain barrels/cisterns provided the highest peak streamflow reduction efficiency and total streamflow volume reduction efficiency at the watershed scale, respectively for the smaller storm event. To achieve sustainable urban stormwater management, the improved SWAT model has enhanced capability to help stakeholders create efficient rainwater harvesting and reuse strategies to reduce field scale runoff and watershed scale streamflow.

Water Quality Effects of Economically Viable Land Use Change in the Mississippi River Basin under the Renewable Fuel Standard

Demand for biofuel production driven by the Renewable Fuel Standard (RFS2) has coincided with increased land in corn production and increasing nitrogen (N) loss to the Gulf of Mexico. Diversifying cropland with perennial energy crops (miscanthus and switchgrass) may reduce N loss and improve water quality. However, the extent of these benefits depends on the mix of biomass feedstocks (corn stover, perennials) incentivized by the RFS2 and the extent to which energy crops displace N-intensive row crops. We developed an integrated economic-biophysical model to quantify the water quality impacts of three potential policy scenarios that provided corn ethanol at levels before the RFS2 (RFS1 baseline); 15 billion gallons of corn ethanol (corn ethanol only); or 16 billion gallons of cellulosic ethanol in addition to corn ethanol (corn + cellulosic ethanol). Our results showed that economically optimal locations for perennial energy crop production were distributed across idle cropland with lower intrinsic N loss than active cropland. We found stover removal incentivized by the RFS2 offset N loss benefits of perennial energy crops. This finding suggests that targeted incentives for N loss reduction are needed to supplement the RFS2 to induce displacement of N-intensive row crops with energy crops to reduce N losses.

Less Agricultural Phosphorus Applied in 2019 Led to Less Dissolved Phosphorus Transported to Lake Erie

Extreme precipitation events affect water quantity and quality in various regions of the world. Heavy precipitation in 2019 resulted in a record high area of unplanted agricultural fields in the U.S. and especially in the Maumee River Watershed (MRW). March-July phosphorus (P) loads from the MRW drive harmful algal bloom (HAB) severity in Lake Erie; hence changes in management that influence P export can ultimately affect HAB severity. In this study, we found that the 2019 dissolved reactive P (DRP) load from March-July was 29% lower than predicted, while the particulate P (PP) load was similar to the predicted value. Furthermore, the reduced DRP load resulted in a less severe HAB than predicted based on discharge volume. The 29% reduction in DRP loss in the MRW occurred with a 62% reduction in applied P, emphasizing the strong influence of recently applied P and subsequent incidental P losses on watershed P loading. Other possible contributing factors to this reduced load include lower precipitation intensity, altered tillage practices, and effects of fallow soils, but more data is needed to assess their importance. We recommend conservation practices focusing on P application techniques and timing and improving resiliency against extreme precipitation events.

Crop growth, hydrology, and water quality dynamics in agricultural fields across the Western Lake Erie Basin: Multi-site verification of the Nutrient Tracking Tool (NTT)

Agricultural field- and watershed-scale water quality models are used to assess the potential impact of management practices to reduce nutrient and sediment exports. However, observed data are often not available to calibrate and verify these models. Three years of data from the U.S. Department of Agriculture-Agricultural Research Service's 12 paired edge-of-field sites in northwest Ohio were used to calibrate and validate the Nutrient Tracking Tool. The goal of this study was to identify a single optimal parameter set for the Nutrient Tracking Tool in simulating annual crop yields, water balance, and nutrient loads across the Western Lake Erie Basin. A multi-site and multi-objective auto-calibration subroutine was developed in R to perform model calibration across the edge-of-field sites. The statistical metrics and evaluation criteria used in comparing the simulated results with the observed data were: Cohen's D Effect Size (Cohen's D < 0.20) and Percent bias (PBIAS ± 10% for crop yields, subsurface (tile) discharge, and surface runoff and ± 25% for dissolved reactive phosphorus (DRP) and nitrate‑nitrogen (nitrate-N) in tile discharge, and DRP, particulate phosphorus, and nitrate-N in surface runoff). In both calibration and validation, the Cohen's D and PBIAS for annual crop yields, tile discharge, surface runoff, DRP, particulate P, and nitrate-N showed that the average simulated results were similar to the average observed values for each variable. The calibrated model simulated well the annual averages of crop yields, flows, and nutrient losses across fields. The tile drainage and phosphorus transport subroutines in the Nutrient Tracking Tool should be further improved to better simulate the dynamics of discharge and phosphorus transport through subsurface drainage. Stakeholders can use the verified model to evaluate the effectiveness of conservation practices in improving the water quality across the Western Lake Erie Basin.

A SWAT-based optimization tool for obtaining cost-effective strategies for agricultural conservation practice implementation at watershed scales

To address the harmful algal blooms problem in Lake Erie, one solution is to determine the most cost-effective strategies for implementing agricultural best management practices (BMPs) in the Maumee River watershed. An optimization tool, which combines multi-objective optimization algorithms, SWAT (Soil and Water Assessment Tool), and a computational efficient framework, was created to optimally identify agricultural BMPs at watershed scales. The optimization tool was demonstrated in the Matson Ditch watershed, an agricultural watershed in the Maumee River basin considering critical areas (25% of the watershed with the greatest pollutant loadings per area) and the entire watershed. The initial implementation of BMPs with low expenditures greatly reduced pollutant loadings; beyond certain levels of pollutant reductions, additional expenditures resulted in less significant reductions in pollutant loadings. Compared to optimization for the entire watershed, optimization in critical areas can greatly reduce computational time and obtain similar optimization results for initial reductions in pollutant loadings, which were 10% for Dissolved Reactive Phosphorus (DRP) and 38% for Total Phosphorus (TP); however, for greater reductions in pollutant loadings, critical area optimization was less cost-effective. With the target of simultaneously reducing March-July DRP/TP losses by 40%, the optimized scenario that reduced DRP losses by 40% was found to reduce 51.1% of TP; however, the optimized scenario that reduced TP losses by 40% can only decrease 11.3% of DRP. The optimization tool can help stakeholders identify optimal types, quantities, and spatial locations of BMPs that can maximize reductions in pollutant loadings with the lowest BMP costs.

Soil & Water Assessment Tool (SWAT) simulated hydrological impacts of land use change from temperate grassland to energy crops: A case study in western UK

When considering the large-scale deployment of bioenergy crops, it is important to understand the implication for ecosystem hydrological processes and the influences of crop type and location. Based on the potential for future land use change (LUC), the 10,280 km2 West Wales Water Framework Directive River Basin District (UK) was selected as a typical grassland dominated district, and the Soil & Water Assessment Tool (SWAT) hydrology model with a geographic information systems interface was used to investigate implications for different bioenergy deployment scenarios. The study area was delineated into 855 sub-basins and 7,108 hydrological response units based on rivers, soil type, land use, and slope. Changes in hydrological components for two bioenergy crops (Miscanthus and short rotation coppice, SRC) planted on 50% (2,192 km2) or 25% (1,096 km2) of existing improved pasture are quantified. Across the study area as a whole, only surface run-off with SRC planted at the 50% level was significantly impacted, where it was reduced by up to 23% (during April). However, results varied spatially and a comparison of annual means for each sub-basin and scenario revealed surface run-off was significantly decreased and baseflow significantly increased (by a maximum of 40%) with both Miscanthus and SRC. Evapotranspiration was significantly increased with SRC (at both planting levels) and water yield was significantly reduced with SRC (at the 50% level) by up to 5%. Effects on streamflow were limited, varying between -5% and +5% change (compared to baseline) in the majority of sub-basins. The results suggest that for mesic temperate grasslands, adverse effects from the drying of soil and alterations to streamflow may not arise, and with surface run-off reduced and baseflow increased, there could, depending on crop location, be potential benefits for flood and erosion mitigation.

Regenerating Agricultural Landscapes with Perennial Groundcover for Intensive Crop Production

The Midwestern U.S. landscape is one of the most highly altered and intensively managed ecosystems in the country. The predominant crops grown are maize (Zea mays L.) and soybean [Glycine max (L.) Merr]. They are typically grown as monocrops in a simple yearly rotation or with multiple years of maize (2 to 3) followed by a single year of soybean. This system is highly productive because the crops and management systems have been well adapted to the regional growing conditions through substantial public and private investment. Furthermore, markets and supporting infrastructure are highly developed for both crops. As maize and soybean production have intensified, a number of concerns have arisen due to the unintended environmental impacts on the ecosystem. Many areas across the Midwest are experiencing negative impacts on water quality, soil degradation, and increased flood risk due to changes in regional hydrology. The water quality impacts extend even further downstream. We propose the development of an innovative system for growing maize and soybean with perennial groundcover to recover ecosystem services historically provided naturally by predominantly perennial native plant communities. Reincorporating perennial plants into annual cropping systems has the potential of restoring ecosystem services without negatively impacting grain crop production and offers the prospect of increasing grain crop productivity through improving the biological functioning of the system.

Nitrate Runoff Contributing from the Agriculturally Intensive San Joaquin River Watershed to Bay-Delta in California

Nitrogen loading from agricultural landscapes can trigger a cascade of detrimental effects on aquatic ecosystems. Recently, the spread of aquatic weed infestations (Eichhornia crassipes, Egeria densa, Ludwigia spp., and Onagraceae) in the Sacramento-San Joaquin Delta of northern California has raised concerns, and nitrogen loading from California’s intensive farming regions is considered as one of the major contributors. In this study, we employed the Soil and Water Assessment Tool (SWAT) to simulate nitrogen exports from the agriculturally intensive San Joaquin River watershed to the Delta. The alternate tile drainage routine in SWAT was tested against monitoring data in the tile-drained area of the watershed to examine the suitability of the new routine for a tile nitrate simulation. We found that the physically based Hooghoudt and Kirkham tile drain routine improved model performance in representing tile nitrate runoff, which contributed to 40% of the nitrate loading to the San Joaquin River. Calibration results show that the simulated riverine nitrate loads matched the observed data fairly well. According to model simulation, the San Joaquin River plays a critical role in exporting nitrogen to the Delta by exporting 3135 tons of nitrate-nitrogen annually, which has a strong ecological implication in supporting the growth of aquatic weeds, which has impeded water flow, impairs commercial navigation and recreational activities, and degrades water quality in Bay-Delta waterways. Since nitrate loadings contributed by upstream runoff are an important nutrient to facilitate weed development, our study results should be seen as a prerequisite to evaluate the potential growth impact of aquatic weeds and scientific evidence for area-wide weed control decisions.

Linking watershed modeling and bacterial source tracking to better assess E. coli sources

Terrestrial fate and transport processes of E. coli can be complicated by human activities like urbanization or livestock grazing. There is a critical need to address contributing sources of bacterial contamination, properly assess the management of critical sources, and ultimately reduce E. coli concentrations in impaired water bodies. In particular, characterization of wildlife animal contributions and other "background" input sources of microbial pollution are highly uncertain and data are scarce. This study attempts to identify critical sources of E. coli and the efficacy of conservation practices for mitigating E. coli concentrations in the Arroyo Colorado watershed, Texas, using a process-based hydrologic and water quality model. We propose to incorporate a bacterial source tracking assessment into the modeling framework to fill the gap in data on wildlife and human contribution. In addition, other sources identified through a GIS survey, national census, and local expert knowledge were incorporated into the model as E. coli sources. Results suggest that simulated distribution of E. coli sources significantly improved after incorporating this enhanced data on E. coli sources into the model (R² = 0.90) compared to the SWAT result without BST (R² = 0.59). Scenario assessments indicate that wildlife contributions may remain significant despite land use change and urbanization, expected to mostly occur in agricultural and range lands. A combination of nonpoint source management measures, voluntary implementation of advanced treatment by wastewater plants where possible, and installation of aerators in the zone of impairment were demonstrated to be effective measures for restoring the recreation and aquatic life uses of the Arroyo Colorado.

Analysis of Moisture Content in Beetroot using Fourier Transform Infrared Spectroscopy and by Principal Component Analysis

The moisture content of beetroot varies during long-term cold storage. In this work, we propose a strategy to identify the moisture content and age of beetroot using principal component analysis coupled Fourier transform infrared spectroscopy (FTIR). Frequent FTIR measurements were recorded directly from the beetroot sample surface over a period of 34 days for analysing its moisture content employing attenuated total reflectance in the spectral ranges of 2614–4000 and 1465–1853 cm⁻¹ with a spectral resolution of 8 cm⁻¹. In order to estimate the transmittance peak height (T_p) and area under the transmittance curve \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$({\int }_{{\bar{\nu }}_{i}}^{{\bar{\nu }}_{f}}{T}_{p}d\bar{\nu })$$\end{document}(∫ν¯iν¯fTpdν¯) over the spectral ranges of 2614–4000 and 1465–1853 cm⁻¹, Gaussian curve fitting algorithm was performed on FTIR data. Principal component and nonlinear regression analyses were utilized for FTIR data analysis. Score plot over the ranges of 2614–4000 and 1465–1853 cm⁻¹ allowed beetroot quality discrimination. Beetroot quality predictive models were developed by employing biphasic dose response function. Validation experiment results confirmed that the accuracy of the beetroot quality predictive model reached 97.5%. This research work proves that FTIR spectroscopy in combination with principal component analysis and beetroot quality predictive models could serve as an effective tool for discriminating moisture content in fresh, half and completely spoiled stages of beetroot samples and for providing status alerts.