water quality

Logging and mill residues are currently the largest sources of woody biomass for bioenergy in the US, but short-rotation woody crops (SRWCs) are expected to become a larger contributor to biomass production, primarily on lands marginal for food production. However, there are very few studies on the environmental effects of SRWCs, and most have been conducted at stand rather than at watershed scales. In this manuscript, we review the potential environmental effects of SRWCs relative to current forestry or agricultural practices and best management practices (BMPs) in the southeast US and identify priorities and constraints for monitoring and modeling these effects. Plot-scale field studies and a watershed-scale modeling study found improved water quality with SRWCs compared to agricultural crops. Further, a recent watershed-scale experiment suggests that conventional forestry BMPs are sufficient to protect water quality from SRWC silvicultural activities, but the duration of these studies is short with respect to travel times of groundwater transporting nitrate to streams. While the effects of SRWC production on carbon (C) and water budgets depend on both soil properties and previous land management, woody crops will typically sequester more C when compared with agricultural crops. The overall C offset by SRWCs will depend on a variety of management practices, the number of rotations, and climate. Effects of SRWCs on biodiversity, especially aquatic organisms, are not well studied, but a meta-analysis found that bird and mammal biodiversity is lower in SRWC stands than unmanaged forests. Long-term (i.e., over multiple rotations) water quality, water use, C dynamics, and soil quality studies are needed, as are larger-scale (i.e., landscape scale) biodiversity studies, to evaluate the potential effects of SRWC production. Such research should couple field measurement and modeling approaches due to the temporal (i.e., multiple rotations) and spatial (i.e., heterogeneous landscape) scaling issues involved with SRWC production.

Advanced biomass feedstocks tend to provide more non-fuel ecosystem goods and services (ES) than 1st-generation alternatives. We explore the idea that payment for non-fuel ES could facilitate market penetration of advanced biofuels by closing the profitability gap. As a specific example, we discuss the Mississippi-Atchafalaya River Basin (MARB), where 1st-generation bioenergy feedstocks (e.g., corn-grain) have been integrated into the agricultural landscape. Downstream, the MARB drains to the Gulf of Mexico, where the most-valuable fishery in the US is impacted by annual formation of a large hypoxic "Dead zone." We suggest that advanced biomass production systems in the MARB can increase and stabilize the provision of ES derived from the coastal and marine ecosystems of the Gulf-of-Mexico. Upstream, we suggest that choosing feedstocks based on their resistance or resilience to disturbance (e.g., perennials, diverse feedstocks) can increase reliability in ES provision over time. Direct feedbacks to incentivize producers of advanced feedstocks are currently lacking. Perhaps a shift from first-generation biofuels to perennial-based fuels and other advanced bioenergy systems (e.g., algal diesel, biogas from animal wastes) can be encouraged by bringing downstream environmental externalities into the market for upstream producers. In future, we can create such feedbacks through payments for ES, but significant research is needed to pave the way.

Join the U.S. Department of Energy’s Bioenergy Technologies Office on Dec. 6, 2018, at 1 p.m. CST for a webinar on “Biomass Production and Water Quality in the Mississippi River Basin.” In this webinar, Argonne National Laboratory and Oak Ridge National Laboratory will jointly present modeling and analyses of potential implications of biomass production on nutrients and sediments in each of the six tributaries of the Mississippi River Basin. Presenters will describe the methodology, system boundary, and data sources and present water quality estimates for nitrogen, phosphorus, and suspended sediments under historical land use in the Upper Mississippi River Basin, Missouri River Basin, Ohio River Basin, Arkansas White and Red River Basin, Tennessee River Basin, and Lower Mississippi River Basin. The webinar will also provide an estimate of potential changes in water quality and quantity under future biomass production scenarios and discuss opportunities for integrating conservation practices with biomass production. The webinar will include a 15 minute Q&A segment.

Model-data comparisons are always challenging, especially when working at a large spatial scale and evaluating multiple response variables. We implemented the Soil and Water Assessment Tool (SWAT) to simulate water quantity and quality for the Tennessee River Basin. We developed three innovations to overcome hurdles associated with limited data for model evaluation: 1) we implemented an auto-calibration approach to allow simultaneous calibration against multiple responses, including synthetic response variables, such as the HUC8 runoff as an area-weighted average of runoff in multiple subbasins; 2) we identified empirical spatiotemporal datasets to use in our comparison; and 3) we compared functional patterns in landuse-nutrient relationships between SWAT and empirical data. In addition, twenty-two (22) reservoirs in the TRB were included in the SWAT setup, which is conducive to a more realistic modeling of runoff and water quality. We used the 2009 Cropland Data Layer (CDL-2009) (USDA-NASS, 2014) to represent the baseline (i.e., Scenario Base) land use/land cover. The SWAT model was calibrated and validated under Scenario Base. We further applied SWAT to project water quantity and quality under Scenario BC1 and HH3 by replacing the baseline landuse with corresponding future landuse map. This protocol created a total of 4026, 3702, and 4115 distinct HRUs in 55 subbasins under Scenario Base, BC1, and HH3, respectively.

Tennessee River Basin
1. GIS data:
1.1 River basin boundaries, subbasin boundaries, stream network data, landuse/cover, and soil: https://github.com/wanggangsheng/TRB_GIS_data.git
1.2 Additional data (e.g., DEM) can be obtained by contacting the author at wangg@ornl.gov

2. SWAT input files for 3 landuse scenarios
2.1 baseline scenario: https://github.com/wanggangsheng/SWATIO_TRB_Base_updateAll.git
2.2 BC1 scenario: https://github.com/wanggangsheng/SWATIO_TRB_BC1_updateAll.git
2.3 HH3 scenario: https://github.com/wanggangsheng/SWATIO_TRB_HH3_updateAll.git

Model code:
https://bioenergykdf.net/content/swatopt-auto-calibration-tools-swat-20…

References:
Wang G, Jager HI, Baskaran LM, Brandt CC. Hydrologic and water quality responses to biomass production in the Tennessee river basin. GCB Bioenergy. 2018;00:1–17. https://doi.org/10.1111/gcbb.12537.

This dataset reports the pre-treatment hydrology and pre- and post-treatment water quality data from a watershed-scale experiment that is evaluating the effects of growing short-rotation loblolly pine for bioenergy on water quality and quantity in the southeastern U.S. The experiment is taking place on the Savannah River Site, near New Ellenton, South Carolina, USA.  Beginning in 2010, water quality and hydrology were measured for two years in 3 watersheds (R, B, C). At the end of February 2012, 40% of two treatment watersheds (B, C) were harvested and loblolly pine seedlings were planted and managed for bioenergy (including multiple applications of herbicides and fertilizers). Water samples were collected from stream water (weekly), riparian groundwater (monthly), groundwater beneath the uplands (monthly), throughfall (weekly), and trenches that collected shallow subsurface flow (during storms), and these data are available for the pre- and post-treatment periods. Water samples were also collected from three concentrated flow tracks that formed in watersheds B and C in the post-treatment period. Water samples were analyzed for nitrate-N, ammonium-N, soluble reactive phosphorus (SRP), and dissolved organic carbon (DOC) concentrations. Stream water samples only were analyzed for total nitrogen and total phosphorus concentrations, and select samples (usually collected seasonally) were analyzed for pesticide concentrations. Water samples were also analyzed for stable isotopes of nitrate (δ15N, δ18O), and these data are available for the pre-treatment period. Stream flow and trench flow were measured every 10-15 minutes, and these data are available for the pre-treatment period.

The pre-treatment data were presented in a manuscript (Griffiths et al. 2016) that utilized stable isotope of nitrate data to describe hydrological and biological drivers of watershed N cycling and sources of stream water nitrate in the 3 study watersheds. Both the pre-treatment and post-treatment water quality data were presented in a manuscript (Griffiths et al. 2017) that examined the water quality responses to short-rotation pine production for bioenergy.

Griffiths, N.A., C.R. Jackson, J.J. McDonnell, J. Klaus, E. Du, and M.M. Bitew. 2016. Dual nitrate isotopes clarify the role of biological processing and hydrologic flowpaths on nitrogen cycling in subtropical low-gradient watersheds. JGR-Biogeosciences 131:422-437.

Griffiths, N.A., C.R. Jackson, M.M. Bitew, A.M. Fortner, K.L. Fouts, K. McCracken, and J.R. Phillips. 2017. Water quality effects of short-rotation pine management for bioenergy feedstocks in the southeastern United States. Forest Ecology and Management 400:181-198.

Acknowledgements: This research was supported by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725.

Water consumption and water quality continue to be key factors affecting environmental sustainability in biofuel production. This review covers the findings from biofuel water analyses published over the past 2 years to underscore the progress made, and to highlight advancements in understanding the interactions among increased production and water demand, water resource availability, and potential changes in water quality. We focus on two key areas: water footprint assessment and watershed modeling. Results revealed that miscanthus-, switchgrass-, and forest wood-based biofuels all have promising blue and grey water footprints. Alternative water resources have been explored for algae production, and challenges remain. A most noticeable improvement in the analysis of life-cycle water consumption is the adoption of geospatial analysis and watershed modeling to generate a spatially explicit water footprint at a finer scale (e.g., multi-state region, state, and county scales) to address the impacts of land use change and climate on the water footprint in a landscape with a mixed biofuel feedstock.

Global development of the biofuel sector is proceeding rapidly. Biofuel feedstock continues to be produced from a variety of agricultural and forestry resources. Large-scale feedstock production for biofuels could change the landscape structure and affect water quantity, water quality, and ecosystem services in positive or negative ways. With rapid advancements in computation technologies and science, field- and watershed-scale models have become a vital tool for quantifying water quality and ecosystem responses to bioenergy landscape and management practices. This paper presents a brief review of the development and application of field- and watershed-scale models in quantifying water quality and management practices and then discusses a number of critical issues associated with applying these models. In conclusion, the paper identifies specific areas that need improvement and new capabilities for currently used models and addresses challenges in enhancing existing models or developing more sophisticated new models

Using the Soil and Water Assessment Tool (SWAT) for large-scale watershed modeling could be useful for evaluating the quality of the water in regions that are dominated by nonpoint sources in order to identify potential “hot spots” for which mitigating strategies could be further developed. An analysis of water quality under future scenarios in which changes in land use would be made to accommodate increased biofuel production was developed for the Missouri River Basin (MoRB) based on a SWAT model application. The analysis covered major agricultural crops and biofuel feedstock in the MoRB, including pasture land, hay, corn, soybeans, wheat, and switchgrass. The analysis examined, at multiple temporal and spatial scales, how nitrate, organic nitrogen, and total nitrogen; phosphorus, organic phosphorus, inorganic phosphorus, and total phosphorus; suspended sediments; and water flow (water yield) would respond to the shifts in land use that would occur under proposed future scenarios. The analysis was conducted at three geospatial scales: (1) large tributary basin scale (two: Upper MoRB and Lower MoRB); (2) regional watershed scale (seven: Upper Missouri River, Middle Missouri River, Middle Lower Missouri River, Lower Missouri River, Yellowstone River, Platte River, and Kansas River); and (3) eight-digit hydrologic unit (HUC-8) subbasin scale (307 subbasins). Results showed that subbasin-level variations were substantial. Nitrogen loadings decreased across the entire Upper MoRB, and they increased in several subbasins in the Lower MoRB. Most nitrate reductions occurred in lateral flow. Also at the subbasin level, phosphorus in organic, sediment, and soluble forms was reduced by 35%, 45%, and 65%, respectively. Suspended sediments increased in 68% of the subbasins. The water yield decreased in 62% of the subbasins. In the Kansas River watershed, the water quality improved significantly with regard to every nitrogen and phosphorus compound. The improvement was clearly attributable to the conversion of a large amount of land to switchgrass. The Middle Lower Missouri River and Lower Missouri River were identified as hot regions. Further analysis identified four subbasins (10240002, 10230007, 10290402, and 10300200) as being the most vulnerable in terms of sediment, nitrogen, and phosphorus loadings. Overall, results suggest that increasing the amount of switchgrass acreage in the hot spots should be considered to mitigate the nutrient loads. The study provides an analytical method to support stakeholders in making informed decisions that balance biofuel production and water sustainability.

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.

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.