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Title: Estimating Biofuel Feedstock Water Footprints Using System Dynamics

Abstract

Increased biofuel production has prompted concerns about the environmental tradeoffs of biofuels compared to petroleum-based fuels. Biofuel production in general, and feedstock production in particular, is under increased scrutiny. Water footprinting (measuring direct and indirect water use) has been proposed as one measure to evaluate water use in the context of concerns about depleting rural water supplies through activities such as irrigation for large-scale agriculture. Water footprinting literature has often been limited in one or more key aspects: complete assessment across multiple water stocks (e.g., vadose zone, surface, and ground water stocks), geographical resolution of data, consistent representation of many feedstocks, and flexibility to perform scenario analysis. We developed a model called BioSpatial H2O using a system dynamics modeling and database framework. BioSpatial H2O could be used to consistently evaluate the complete water footprints of multiple biomass feedstocks at high geospatial resolutions. BioSpatial H2O has the flexibility to perform simultaneous scenario analysis of current and potential future crops under alternative yield and climate conditions. In this proof-of-concept paper, we modeled corn grain (Zea mays L.) and soybeans (Glycine max) under current conditions as illustrative results. BioSpatial H2O links to a unique database that houses annual spatially explicit climate, soil, andmore » plant physiological data. Parameters from the database are used as inputs to our system dynamics model for estimating annual crop water requirements using daily time steps. Based on our review of the literature, estimated green water footprints are comparable to other modeled results, suggesting that BioSpatial H2O is computationally sound for future scenario analysis. Our modeling framework builds on previous water use analyses to provide a platform for scenario-based assessment. BioSpatial H2O's system dynamics is a flexible and user-friendly interface for on-demand, spatially explicit, water use scenario analysis for many US agricultural crops. Built-in controls permit users to quickly make modifications to the model assumptions, such as those affecting yield, and to see the implications of those results in real time. BioSpatial H2O's dynamic capabilities and adjustable climate data allow for analyses of water use and management scenarios to inform current and potential future bioenergy policies. The model could also be adapted for scenario analysis of alternative climatic conditions and comparison of multiple crops. The results of such an analysis would help identify risks associated with water use competition among feedstocks in certain regions. Results could also inform research and development efforts that seek to reduce water-related risks of biofuel pathways.« less

Authors:
; ; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Electricity Delivery and Energy Reliability
OSTI Identifier:
1290787
Report Number(s):
NREL/JA-6A20-60945
Journal ID: ISSN 0022-4561
DOE Contract Number:
AC36-08GO28308
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Soil and Water Conservation; Journal Volume: 71; Journal Issue: 4
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; 54 ENVIRONMENTAL SCIENCES; water; water use; water footprinting; system dynamics

Citation Formats

Inman, Daniel, Warner, Ethan, Stright, Dana, Macknick, Jordan, and Peck, Corey. Estimating Biofuel Feedstock Water Footprints Using System Dynamics. United States: N. p., 2016. Web. doi:10.2489/jswc.71.4.343.
Inman, Daniel, Warner, Ethan, Stright, Dana, Macknick, Jordan, & Peck, Corey. Estimating Biofuel Feedstock Water Footprints Using System Dynamics. United States. doi:10.2489/jswc.71.4.343.
Inman, Daniel, Warner, Ethan, Stright, Dana, Macknick, Jordan, and Peck, Corey. 2016. "Estimating Biofuel Feedstock Water Footprints Using System Dynamics". United States. doi:10.2489/jswc.71.4.343.
@article{osti_1290787,
title = {Estimating Biofuel Feedstock Water Footprints Using System Dynamics},
author = {Inman, Daniel and Warner, Ethan and Stright, Dana and Macknick, Jordan and Peck, Corey},
abstractNote = {Increased biofuel production has prompted concerns about the environmental tradeoffs of biofuels compared to petroleum-based fuels. Biofuel production in general, and feedstock production in particular, is under increased scrutiny. Water footprinting (measuring direct and indirect water use) has been proposed as one measure to evaluate water use in the context of concerns about depleting rural water supplies through activities such as irrigation for large-scale agriculture. Water footprinting literature has often been limited in one or more key aspects: complete assessment across multiple water stocks (e.g., vadose zone, surface, and ground water stocks), geographical resolution of data, consistent representation of many feedstocks, and flexibility to perform scenario analysis. We developed a model called BioSpatial H2O using a system dynamics modeling and database framework. BioSpatial H2O could be used to consistently evaluate the complete water footprints of multiple biomass feedstocks at high geospatial resolutions. BioSpatial H2O has the flexibility to perform simultaneous scenario analysis of current and potential future crops under alternative yield and climate conditions. In this proof-of-concept paper, we modeled corn grain (Zea mays L.) and soybeans (Glycine max) under current conditions as illustrative results. BioSpatial H2O links to a unique database that houses annual spatially explicit climate, soil, and plant physiological data. Parameters from the database are used as inputs to our system dynamics model for estimating annual crop water requirements using daily time steps. Based on our review of the literature, estimated green water footprints are comparable to other modeled results, suggesting that BioSpatial H2O is computationally sound for future scenario analysis. Our modeling framework builds on previous water use analyses to provide a platform for scenario-based assessment. BioSpatial H2O's system dynamics is a flexible and user-friendly interface for on-demand, spatially explicit, water use scenario analysis for many US agricultural crops. Built-in controls permit users to quickly make modifications to the model assumptions, such as those affecting yield, and to see the implications of those results in real time. BioSpatial H2O's dynamic capabilities and adjustable climate data allow for analyses of water use and management scenarios to inform current and potential future bioenergy policies. The model could also be adapted for scenario analysis of alternative climatic conditions and comparison of multiple crops. The results of such an analysis would help identify risks associated with water use competition among feedstocks in certain regions. Results could also inform research and development efforts that seek to reduce water-related risks of biofuel pathways.},
doi = {10.2489/jswc.71.4.343},
journal = {Journal of Soil and Water Conservation},
number = 4,
volume = 71,
place = {United States},
year = 2016,
month = 7
}
  • No abstract prepared.
  • Our study addresses the uncertainties related to potential changes in land use and management and associated impacts on hydrology and water quality resulting from increased production of biofuel from the conventional and cellulosic feedstock. The Soil Water Assessment Tool (SWAT) was then used to assess the impacts on regional and field scale evapotranspiration, soil moisture content, stream flow, sediment, and nutrient loadings in the Ohio River Basin. The model incorporates spatially and temporally detailed hydrologic, climate and agricultural practice data that are pertinent to simulate biofuel feedstock production, watershed hydrology and water quality. Three future biofuel production scenarios in themore » region were considered, including a feedstock projection from the DOE Billion-Ton (BT2) Study, a change in corn rotations to continuous corn, and harvest of 50% corn stover. The impacts were evaluated on the basis of relative changes in hydrology and water quality from historical baseline and future business-as-usual conditions of the basin. The overall impact on water quality is an order of magnitude higher than the impact on hydrology. For all the three future scenarios, the sub-basin results indicated an overall increase in annual evapotranspiration of up to 6%, a decrease in runoff up to 10% and minimal change in soil moisture. The sediment and phosphorous loading at both regional and field levels increased considerably (up to 40–90%) for all the biofuel feedstock scenario considered, while the nitrogen loading increased up to 45% in some regions under the BT2 Study scenario, decreased up to 10% when corn are grown continuously instead of in rotations, and changed minimally when 50% of the stover are harvested. Field level analyses revealed significant variability in hydrology and water quality impacts that can further be used to identify suitable locations for the feedstock productions without causing major impacts on water quantity and quality.« less
  • Our study addresses the uncertainties related to potential changes in land use and management and associated impacts on hydrology and water quality resulting from increased production of biofuel from the conventional and cellulosic feedstock. The Soil Water Assessment Tool (SWAT) was then used to assess the impacts on regional and field scale evapotranspiration, soil moisture content, stream flow, sediment, and nutrient loadings in the Ohio River Basin. The model incorporates spatially and temporally detailed hydrologic, climate and agricultural practice data that are pertinent to simulate biofuel feedstock production, watershed hydrology and water quality. Three future biofuel production scenarios in themore » region were considered, including a feedstock projection from the DOE Billion-Ton (BT2) Study, a change in corn rotations to continuous corn, and harvest of 50% corn stover. The impacts were evaluated on the basis of relative changes in hydrology and water quality from historical baseline and future business-as-usual conditions of the basin. The overall impact on water quality is an order of magnitude higher than the impact on hydrology. For all the three future scenarios, the sub-basin results indicated an overall increase in annual evapotranspiration of up to 6%, a decrease in runoff up to 10% and minimal change in soil moisture. The sediment and phosphorous loading at both regional and field levels increased considerably (up to 40–90%) for all the biofuel feedstock scenario considered, while the nitrogen loading increased up to 45% in some regions under the BT2 Study scenario, decreased up to 10% when corn are grown continuously instead of in rotations, and changed minimally when 50% of the stover are harvested. Field level analyses revealed significant variability in hydrology and water quality impacts that can further be used to identify suitable locations for the feedstock productions without causing major impacts on water quantity and quality.« less