Annual U.S. production of bioethanol, primarily produced from corn starch in the U.S. Midwest, rose to 57 billion liters in 2021, which fulfilled the required conventional biofuel target set forth by the Energy Independence and Security Act (EISA) of 2007. At the same time, the U.S. fell short of the cellulosic or advanced biofuel target of 79 billion liters. The growth of bioenergy grasses (e.g., Miscanthus and switchgrass) across the Central and Eastern U.S. has the potential to feed enhanced cellulosic bioethanol production and, if successful, increase renewable fuel volumes. However, water consumption and climate change and its extremes are critical concerns in corn and bioenergy grass productivity. These concerns are compounded by the demands on potentially productive land areas and water devoted to producing biofuels. This is a fundamental Food-Energy-Water System (FEWS) nexus challenge. We apply a computational framework to estimate potential bioenergy yield and conversion to bioethanol yield across the U.S., based on crop field studies and conversion technology analysis for three crops—corn, Miscanthus, and two cultivars of switchgrass (Cave-in-Rock and Alamo). The current study identifies regions where each crop has its highest yield across the Center and Eastern U.S. While growing bioenergy grasses requires more water than corn, one advantage they have as a source of bioethanol is that they control nitrogen leaching relative to corn. Bioenergy grasses also maintain steadily high productivity under extreme climate conditions, such as drought and heatwaves in the year 2012 over the U.S. Midwest, because the perennial growing season and the deeper and denser roots can ameliorate the soil water stress. While the potential ethanol yield could be enhanced using energy grasses, their practical success in becoming a potential source of ethanol yield remains limited by socio-economic and operational constraints and concerns regarding competition with food production.
more »
« less
Valuing changes in the portfolio of service flows from climate-induced extremes on a linked food, energy, water system (C-FEWS)
Introduction: Recent work examining the impact of climate-change induced extremes on food-energy-water systems (FEWS) estimates the potential changes in physical flows of multiple elements of the systems. Climate adaptation decisions can involve tradeoffs between different system outcomes. Thus, it is important for decision makers to consider the potential changes in monetary value attributed to the observed changes in physical flows from these events, since the value to society of a unit change in an outcome varies widely between thing like food and energy production, water quality, and carbon sequestration. Methods: We develop a valuation tool (FEWSVT) that applies theoretically sound valuation techniques to estimates changes in value for four parameters within the food-energy-water nexus. We demonstrate the utility of the tool through the application of a case study that analyzes the monetary changes in value of a modelled heat wave scenario relative to historic (baseline) conditions in two study regions in the United States. Results: We find that food (corn and soybeans) comprises the majority (89%) of total changes in value, as heatwaves trigger physical changes in corn and soybeans yields. We also find that specifying overly simplified and incorrect valuation methods lead to monetary values that largely differ from FEWSVT results that use accepted valuation methods. Discussion: These results demonstrate the value in considering changes in monetary value instead of just physical flows when making decisions on how to distribute investments and address the many potential impacts of climate change-induced extremes.
more »
« less
- Award ID(s):
- 1856012
- PAR ID:
- 10430676
- Date Published:
- Journal Name:
- Frontiers in Environmental Science
- Volume:
- 11
- ISSN:
- 2296-665X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
High-resolution mapping of irrigated fields is needed to better estimate water and nutrient fluxes in the landscape, food production, and local to regional climate. However, this remains a challenge in humid to subhumid regions, where irrigation has been expanding into what was largely rainfed agriculture due to trends in climate, crop prices, technologies and practices. One such region is southwestern Michigan, USA, where groundwater is the main source of irrigation water for row crops (primarily corn and soybeans). Remote sensing of irrigated areas can be difficult in these regions as rainfed areas have similar characteristics. We present methods to address this challenge and enhance the contrast between neighboring rainfed and irrigated areas, including weather-sensitive scene selection, applying recently developed composite indices and calculating spatial anomalies. We create annual, 30m-resolution maps of irrigated corn and soybeans for southwestern Michigan from 2001 to 2016 using a machine learning method (random forest). The irrigation maps reasonably capture the spatial and temporal pattern of irrigation, with accuracies that exceed available products. Analysis of the irrigation maps showed that the irrigated area in southwestern Michigan tripled in the last 16 years. We also discuss the remaining challenges for irrigation mapping in humid to subhumid areas.more » « less
-
Change to global climate, including both its progressive character and episodic extremes, constitutes a critical societal challenge. We apply here a framework to analyze Climate-induced Extremes on the Food, Energy, Water System Nexus (C-FEWS), with particular emphasis on the roles and sensitivities of traditionally-engineered (TEI) and nature-based (NBI) infrastructures. The rationale and technical specifications for the overall C-FEWS framework, its component models and supporting datasets are detailed in an accompanying paper (Vörösmarty et al., this issue). We report here on initial results produced by applying this framework in two important macro-regions of the United States (Northeast, NE; Midwest, MW), where major decisions affecting global food production, biofuels, energy security and pollution abatement require critical scientific support. We present the essential FEWS-related hypotheses that organize our work with an overview of the methodologies and experimental designs applied. We report on initial C-FEWS framework results using five emblematic studies that highlight how various combinations of climate sensitivities, TEI-NBI deployments, technology, and environmental management have determined regional FEWS performance over a historical time period (1980–2019). Despite their relative simplicity, these initial scenario experiments yielded important insights. We found that FEWS performance was impacted by climate stress, but the sensitivity was strongly modified by technology choices applied to both ecosystems (e.g., cropland production using new cultivars) and engineered systems (e.g., thermoelectricity from different fuels and cooling types). We tabulated strong legacy effects stemming from decisions on managing NBI (e.g., multi-decade land conversions that limit long-term carbon sequestration). The framework also enabled us to reveal how broad-scale policies aimed at a particular net benefit can result in unintended and potentially negative consequences. For example, tradeoff modeling experiments identified the regional importance of TEI in the form wastewater treatment and NBI via aquatic self-purification. This finding, in turn, could be used to guide potential investments in point and/or non-point source water pollution control. Another example used a reduced complexity model to demonstrate a FEWS tradeoff in the context of water supply, electricity production, and thermal pollution. Such results demonstrated the importance of TEI and NBI in jointly determining historical FEWS performance, their vulnerabilities, and their resilience to extreme climate events. These infrastructures, plus technology and environmental management, constitute the “policy levers” which can actively be engaged to mitigate the challenge of contemporary and future climate change.more » « less
-
Abstract Crop phenology regulates seasonal carbon and water fluxes between croplands and the atmosphere and provides essential information for monitoring and predicting crop growth dynamics and productivity. However, under rapid climate change and more frequent extreme events, future changes in crop phenological shifts have not been well investigated and fully considered in earth system modeling and regional climate assessments. Here, we propose an innovative approach combining remote sensing imagery and machine learning (ML) with climate and survey data to predict future crop phenological shifts across the US corn and soybean systems. Specifically, our projected findings demonstrate distinct acceleration patterns—under the RCP 4.5/RCP 8.5 scenarios, corn planting, silking, maturity, and harvesting stages would significantly advance by 0.94/1.66, 1.13/2.45, 0.89/2.68, and 1.04/2.16 days/decade during 2021–2099, respectively. Soybeans exhibit more muted responses with phenological stages showing relatively smaller negative trends (0.59, 1.08, 0.07, and 0.64 days/decade under the RCP 4.5 vs. 1.24, 1.53, 0.92, and 1.04 days/decade under the RCP 8.5). These spatially explicit projections illustrate how crop phenology would respond to future climate change, highlighting widespread and progressively earlier phenological timing. Based on these findings, we call for a specific effort to quantify the cascading effects of future phenology shifts on crop yield and carbon, water, and energy balances and, accordingly, craft targeted adaptive strategies.more » « less
-
Climate change continues to challenge food, energy, and water systems (FEWS) across the globe and will figure prominently in shaping future decisions on how best to manage this nexus. In turn, traditionally engineered and natural infrastructures jointly support and hence determine FEWS performance, their vulnerabilities, and their resilience in light of extreme climate events. We present here a research framework to advance the modeling, data integration, and assessment capabilities that support hypothesis-driven research on FEWS dynamics cast at the macro-regional scale. The framework was developed to support studies on climate-induced extremes on food, energy, and water systems (C-FEWS) and designed to identify and evaluate response options to extreme climate events in the context of managing traditionally engineered (TEI) and nature-based infrastructures (NBI). This paper presents our strategy for a first stage of research using the framework to analyze contemporary FEWS and their sensitivity to climate drivers shaped by historical conditions (1980–2019). We offer a description of the computational framework, working definitions of the climate extremes analyzed, and example configurations of numerical experiments aimed at evaluating the importance of individual and combined driving variables. Single and multiple factor experiments involving the historical time series enable two categories of outputs to be analyzed: the first involving biogeophysical entities (e.g., crop production, carbon sequestered, nutrient and thermal pollution loads) and the second reflecting a portfolio of services provided by the region’s TEI and NBI, evaluated in economic terms. The framework is exercised in a series of companion papers in this special issue that focus on the Northeast and Midwest regions of the United States. Use of the C-FEWS framework to simulate historical conditions facilitates research to better identify existing FEWS linkages and how they function. The framework also enables a next stage of analysis to be pursued using future scenario pathways that will vary land use, technology deployments, regulatory objectives, and climate trends and extremes. It also supports a stakeholder engagement effort to co-design scenarios of interest beyond the research domain.more » « less
An official website of the United States government

