switchgrass

Reducing dependence on fossil‐based energy has raised interest in biofuels as a potential energy source, but concerns have been raised about potential implications for water quality. These effects may vary regionally depending on the biomass feedstocks and changes in land management. Here, we focused on the Tennessee River Basin (TRB), USA. According to the recent 2016 Billion‐Ton Report (BT16) by the US Department of Energy, under two future scenarios (base‐case and high‐yield), three perennial feedstocks show high potential for growing profitably in the TRB: switchgrass (Panicum virgatum), miscanthus (Miscanthus × giganteus), and willow (Salix spp.). We used the Soil & Water Assessment Tool (SWAT) to compare hydrology and water quality for a current landscape with those simulated for two future BT16 landscapes. We combined publicly available temporal and geospatial datasets with local land and water management information to realistically represent physical characteristics of the watershed. We developed a new autocalibration tool (SWATopt) to calibrate and evaluate SWAT in the TRB with reservoir operations, including comparison against synthetic and intermediate response variables derived from gage measurements. Our spatiotemporal evaluation enables to more realistically simulate the current situation, which gives us more confidence to project the effects of land‐use changes on water quality. Under both future BT16 scenarios, simulated nitrate and total nitrogen loadings and concentrations were greatly reduced relative to the current landscape, whereas runoff, sediment, and phosphorus showed only small changes. Difference between simulated water results for the two future scenarios was small. The influence of biomass production on water quantity and quality depended on the crop, area planted, and management practices, as well as on site‐specific characteristics. These results offer hope that bioenergy production in the TRB could help to protect the region's rivers from nitrogen pollution by providing a market for perennial crops with low nutrient input requirements.

Price Scenarios at $54 and $119 were simulated for Switchgrass, Miscanthus and Willow production from 2017 to 2040. These analyses were used in Woodbury, Peter B., et al. 2018. "Improving water quality in the Chesapeake Bay using payments for ecosystem services for perennial biomass for bioenergy and biofuel production." Biomass and Bioenergy 114:132-142. doi: https://doi.org/10.1016/j.biombioe.2017.01.024.

Net benefits of bioenergy crops, including maize and perennial grasses such as switchgrass, are a function of several factors including the soil organic carbon (SOC) sequestered by these crops. Life cycle assessments (LCA) for bioenergy crops have been conducted using models in which SOC information is usually from the top 30 to 40 cm. Information on the effects of crop management practices on SOC has been limited so LCA models have largely not included any management practice effects. In the first 9 years of a long-term C sequestration study in eastern Nebraska, USA, switchgrass and maize with best management practices had average annual increases in SOC per hectare that exceed 2 Mg C year−1 (7.3 Mg CO2 year−1) for the 0 to 150 soil depth. For both switchgrass and maize, over 50 % of the increase in SOC was below the 30 cm depth. SOC sequestration by switchgrass was twofold to fourfold greater than that used in models to date which also assumed no SOC sequestration by maize. The results indicate that N fertilizer rates and harvest management regimes can affect the magnitude of SOC sequestration. The use of uniform soil C effects for bioenergy crops from sampling depths of 30 to 40 cm across agro-ecoregions for large scale LCA is questionable.

This paper connects the science of sustainability theory with applied aspects of sustainability deployment. A suite of 35 sustainability indicators spanning six environmental, three economic, and three social categories has been proposed for comparing the sustainability of bioenergy production systems across different feedstock types and locations.   A recent demonstration-scale switchgrass-to-ethanol production system located in East Tennessee is used to assess the availability of sustainability indicator data and associated measurements for the feedstock production and logistics portions of the biofuel supply chain.  Knowledge pertaining to the available indicators is distributed within a hierarchical decision tree framework to generate an assessment of the overall sustainability of this no-till switchgrass production system relative to two alternative business-as-usual scenarios of unmanaged pasture and tilled corn production.  The relative contributions of the social, economic and environmental information are determined for the overall trajectory of this bioenergy system’s sustainability under each scenario.  Within this East Tennessee context, switchgrass production shows potential for improving environmental and social sustainability trajectories without adverse economic impacts, thereby leading to potential for overall enhancement in sustainability within this local agricultural system.  Given the early stages of cellulosic ethanol production, it is currently difficult to determine quantitative values for all 35 sustainability indicators across the entire biofuel supply chain.  This case study demonstrates that integration of qualitative sustainability indicator ratings may increase holistic understanding of a bioenergy system in the absence of complete information.

ABSTRACT. Adding bioenergy to the U.S. energy portfolio requires long‐term profitability for bioenergy producers and long‐term protection of affected ecosystems. In this study, we present steps along the path toward evaluating both sides of the sustainability equation (production and environmental) for switchgrass (Panicum virgatum) using the Soil and Water Assessment Tool (SWAT). We modeled production of switchgrass and river flow using SWAT for current landscapes at a regional scale. To quantify feedstock production, we compared lowland switchgrass yields simulated by SWAT with estimates from a model based on empirical data for the eastern U.S. The two produced similar geographic patterns. Average yields reported in field trials tended to be higher than average SWAT‐predicted yields, which may nevertheless be more
representative of production‐scale yields. As a preliminary step toward quantifying bioenergy‐related changes in water quality, we evaluated flow predictions by the SWAT model for the Arkansas‐White‐Red river basin. We compared monthly SWAT flow predictions to USGS measurements from 86 subbasins across the region. Although agreement was good, we conducted an analysis of residuals (functional validation) seeking patterns to guide future model improvements. The analysis indicated that differences between SWAT flow predictions and field data increased in downstream subbasins and in subbasins with higher percentage of water. Together, these analyses have moved us closer to our ultimate goal of identifying areas with high economic and environmental potential for sustainable feedstock production.

In 2013 a series of meetings was held across the US with each of the Sun Grant Regional Feedstock Partnership crop teams and the resource assessment team, led by the Oregon State University and Oak Ridge National Laboratory, to review, standardize, and verify energy crop yield trials from 2007-2012 and assimilate their outcomes into a national model of biomass yield suitability. The meetings provided a way to “ground truth” yield estimates in order to accurately capture interactions of climate and soils for dedicated energy crops, including energycane, upland and lowland switchgrass, biomass sorghum, CRP grasses, hybrid poplar, willow, pine, and miscanthus x giganteus (in 2014). The verification of yield data included generating a standardized set of management assumptions for each crop and summarizing site potential yield according to the agreed cultural practices to establish, manage, and harvest each crop. From these sets of funded trials and historical data, yield was estimated across spatial gradients according to soil characteristics and climate history at a 2-week interval. The resulting national grids provide critical information for policymakers and planners of the potential productivity of these pre-commercial crops. This document summarizes the crop model and county-level results from the mapping activities (draft of document, July 31, 2014)

This document provides presentation style maps of potential crop yield of dedicated bioenergy crops from the publication "Productivity Potential of Bioenergy Crops from the Sun Grant Regional Feedstock Partnership." 2013. Eaton, Laurence, Chris Daly, Mike Halbleib, Vance Owens, Bryce Stokes. ORNL/TM-2013/574.

Abstract:
In 2013 a series of meetings was held across the US with each of the crop teams and the resource assessment team, led by the Oregon State University and Oak Ridge National Laboratory, to review, standardize, and verify yield trials from 2007-2012 crop years and assimilate their outcomes into a national model of biomass yield suitability. The meetings provided a way to “ground truth” yield estimates in order to accurately capture interactions of climate and soils for dedicated energy crops, including switchgrass, energycane, biomass sorghum, CRP grasses, miscanthus x giganteus, hybrid poplar, willow, and pine. The verification of yield data included generating a standardized set of management assumptions for each crop and summarizing site potential yield according to the agreed cultural practices to establish, manage, and harvest each crop. From these sets of funded trials and historical data, yield was estimated across spatial gradients according to soil characteristics and climate history at a 2-week interval. The resulting national grids provide critical information for policymakers and planners of the potential productivity of these pre-commercial crops.

An efficient and sustainable biomass feedstock production system is critical for the success of the biomass based energy sector. An integrated systems analysis framework to coordinate various feedstock production related activities is, therefore, highly desirable. This article presents research conducted towards the creation of such a framework. A breadth level mixed integer linear programming model, named BioFeed, is proposed that simulates different feedstock production operations such as harvesting, packing, storage, handling and transportation, with the objective of determining the optimal system level configuration on a regional basis. The decision variables include the design/planning as well as management level decisions. The model was applied to a case study of switchgrass production as an energy crop in southern Illinois. The results illustrated that the total cost varied between 45 and 49 $ Mg
1 depending on the collection area and the sustainable biorefinery capacity was about 1.4 Gg d
1. The transportation fleet consisted of 66 trucks and the average utilization of the fleet was 86%. On-farm covered storage of biomass was highly beneficial for the system. Lack of on-farm open storage and centralized storage reduced the system profit by 17% and 5%, respectively. Increase in the fraction of larger farms within the system reduced the cost and increased the biorefinery capacity, suggesting that co-operative farming is beneficial. The optimization of the harvesting schedule led to 30% increase in the total profit. Sensitivity analysis showed that the reduction in truck idling time as well as increase in baling throughput and output density significantly increased the profit.

Abstract: Unfavorable weather can significantly impact the production and provision of agriculture-based biomass feedstocks such as Miscanthus and switchgrass. This work quantified the impact of regional weather on the feedstock production systems using the BioFeed modeling framework. Weather effects were incorporated in BioFeed by including the probability of working day (pwd) parameter in the model, which defined the fraction of days in a specific period such as two weeks that were suitable for field operations. Model simulations were conducted for Miscanthus and switchgrass for values of pwd between 20 and 100% and intended biorefinery capacities between 1000 and 5000 Mg d–1; and the impact on total cost and farm machinery requirements was quantified. Results indicated that using production and provision systems designed assuming 100% pwd for lower pwd values increased the cost exponentially by up to 64% for Miscanthus and 85% for switchgrass. It also decreased the supportable biorefinery capacity for the collection region by up to 60%. If the systems were instead optimized for specific values of pwd, the original biorefinery capacity was maintained and the total cost increase was less than 5%. The resulting optimal systems required up to 40% higher investment in farm machinery. For Illinois, production systems designed for regional pwd values required a 34% increase in farm machinery investment for Miscanthus while only a 12% increase for switchgrass. Initiating Miscanthus harvesting in November instead of January reduced the farm machinery investment increase to 17%, which suggests that such an alternative should be rigorously evaluated.

The increasing demand for bioenergy crops presents our society with the opportunity to design more sustainable landscapes. We have created a Biomass Location for Optimal Sustainability Model (BLOSM) to test the hypothesis that landscape design of cellulosic bioenergy crop plantings may simultaneously improve water quality (i.e. decrease concentrations of sediment, total phosphorus, and total nitrogen) and increase profits for farmer-producers while achieving a feedstock-production goal. BLOSM was run using six scenarios to identify switchgrass (Panicum virgatum) planting locations that might supply a commercial-scale biorefinery planned for the Lower Little Tennessee (LLT) watershed. Each scenario sought to achieve different sustainability goals: improving water quality through reduced nitrogen, phosphorus, or sediment concentrations; maximizing profit; a balance of these conditions; or a balance of these conditions with the additional constraint of converting no more than 25% of agricultural land. Scenario results were compared to a baseline case of no land-use conversion. BLOSM results indicate that a combined economic and environmental optimization approach can achieve multiple objectives simultaneously when a small proportion (1.3%) of the LLT watershed is planted with perennial switchgrass. The multimetric optimization approach described here can be used as a research tool to consider bioenergy plantings for other feedstocks, sustainability criteria, and regions.