Progress 09/01/23 to 08/31/24
Outputs
Target Audience:Although it has been less than 3 years and 9 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 4 years and 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the pandemic, our efforts have already reached multiple target audiences during the current reporting period. . During the current reporting period (Year 5), we participated and presented at events in which we delivered science-based knowledge to people, stakeholders, and target audiences. . Team members participated and shared draft research results with the Cornell Cooperative Extension Agriculture-Solar group of educators during monthly meetings throughout the year. . We also participated in multiple meetings of the Cornell University Agrivoltaic Research Group to share draft results and information. . In January 2023, we presented our work remotely to the Alfred P. Sloan Foundation. . In April 2024, we presented our work to the Power System Planning Group of the New York Independent System Operator (NYISO). . Our work was featured on NYISO PowerTrends Podcast Episode 32 in April 2024. . In March 2024, we presented our work at the Independent Power Producers of New York (IPPNY) Annual Meeting. . In December, we presented our work at the New York State Department of Public Service, Zero By 2040 Tech Conference. . During the current reporting period (Year 5), we have also presented our work at the SRA Annual Meeting (December 2023), the INFORMS Annual Meeting (October 2023), Texas A&M University (October 2023), the 56th Annual Hawaii International Conference on System Sciences (January 2023), the University of Michigan (April 2024), the Power Engineering Research Center (PSERC) Webinar (November 2023), and the ASABE Annual International Meeting (July 2024). . During the current reporting period, our research has had a beneficial educational impact on the doctoral students and postdoctoral researchers who are providing research assistance in all project phases in both disciplinary and transdisciplinary research, including gathering and analyzing data; developing, estimating, and running the models; writing papers; and presenting at meetings and conferences. . Changes/Problems:Although it has been less than 3 years and 9 months since NIFA released all the funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 4 years and 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the pandemic, we have made many notable accomplishments under the major goals of our project. . Nevertheless, due to several factors, there are remaining tasks that we need to complete under our work plan. These include: . - Continuing to develop and refine our model framework for understanding how renewable energy infrastructure investments on rural private lands will alter the food-energy-water system throughout NY. . - Developing and estimating a novel, cutting-edge, and interdisciplinary dynamic structural econometric model that combines economics, econometrics, dynamic optimization, game theory, engineering, hydrology, ecology, and soil and crop sciences to model and analyze land use decision-making behavior. . - Coupling the land use market, power system, and hydrologic models to analyze how ag-to-energy scenarios under land market dynamics will impact different facets of the NYS food-energy-water system, and how those impacts might feed back into land use dynamics for ag-to-energy transitions. . - Using our coupled models to explore how to design policies to promote FEW sustainability and resilience under ag-to-energy land conversions. . - Completing and publishing some of the analyses above, including: (1) how demand for land for solar and wind projects will affect agricultural production; (2) effects of prior land use on GHG benefits of solar energy projects; (3) climate change impacts on electricity prices in a highly renewable NYS power system. . - Completing policy briefs on (1) effects of renewable development on agricultural production and (2) effects of prior land use on GHG benefits of solar energy projects, including leakage. . . There are several causes for the delay in completing the above tasks. . First, the release of funding from USDA NIFA for Year 1 of the project was significantly delayed (released March 2020; project start date of September 2019). This 6-month delay prevented the project team from being able to begin work on the project, and also complicated the hiring process for the 2019-2020 academic year. . Second, although the project start date was September 2019, and although our Year 1 funds were released for our expenditure 6 months after the start date in March 2020, when we did receive the Year 1 funds 6 months later it was still uncertain whether we would receive all 3 years of funding. Uncertainty about whether we would receive all 3 years of funding for our 3-year project made it difficult for us to make the long-term investments needed for our project, and made it difficult for us to recruit, hire, and train the needed personnel for our project, since we did not have the funds available to commit to funding any needed personnel beyond Year 1. . Furthermore, when the funds for Year 1 were released in March 2020, the COVID-19 pandemic caused widespread closure of campus activities and a dramatic shift of work responsibilities and capacity for all members of the project team. The challenges associated with the pandemic further hindered our ability to recruit, hire, and train the needed personnel for our project; and adversely affected the ability of project team members to interact with one another and with stakeholders. . Moreover, although the project start date was September 2019, and although our Year 1 funds were released for our expenditure 6 months after the start date in March 2020, we did not receive the Year 2 and Year 3 funds for our 3-year project until 1.25 years (15 months) after the start date, in December 2020. This 1.25-year delay in the full funding for our 3-year project prevented the project team from making the long-term investments to recruit, hire, and train the needed personnel for our project during both the 2019-2020 and 2020-2021 academic years. . In addition, after the onset of the pandemic, Cornell imposed a campus-wide hiring freeze that further delayed our hiring of research staff for the project. . The project team has also faced a few other delays, including one failed post-doc search once hiring restrictions were lifted, and a medical emergency for one graduate student working on the project that delayed progress for several months. . Furthermore, while we have received a 1-year no-cost extension to August 31, 2023, since we will need 3 additional years to complete the project objectives, and since no-cost extensions can only be processed one 12-month time frame at a time, it has been uncertain whether we will be able to receive a 3-year no-cost extension for the 3 additional years we need to complete the project objectives. Uncertainty about whether we would receive a 3-year no-cost extension for the 3 additional years we need to complete the project has continued to make it difficult for us to make the long-term investments needed for our project, and has continued to make it difficult for us to recruit, hire, and train the needed personnel for our project during the 2022-2023 academic year, since it has continued to be uncertain whether we will be able to commit to funding any needed personnel beyond August 31, 2023. . Similarly, while we have received a 1-year no-cost extension to August 31, 2024, since we will need 3 additional years to complete the project objectives, and since no-cost extensions can only be processed one 12-month time frame at a time, it has been uncertain whether we will be able to receive a 3-year no-cost extension for the 3 additional years we need to complete the project objectives. Uncertainty about whether we would receive a 3-year no-cost extension for the 3 additional years we need to complete the project has continued to make it difficult for us to make the long-term investments needed for our project, and has continued to make it difficult for us to recruit, hire, and train the needed personnel for our project during the 2023-2024 academic year, since it has continued to be uncertain whether we will be able to commit to funding any needed personnel beyond August 31, 2024. . Owing to the delays in the release of the funds; the challenges associated with the pandemic; and the resulting difficulty in recruiting, hiring, and training the needed personnel for our project, we estimate that by the end of August 31, 2024, we will still have approximately $560,000 of the funds awarded to us for our 3-year project remaining. . Despite all of these delays, the project team has made strong progress on all of the components of the project. Nevertheless, these delays have slowed our original timeline, and we will need 3 additional years to complete the project objectives. We would therefore like to request a 3-year no-cost extension, so that the end date of our project is August 31, 2028 instead of August 31, 2025, to help the team complete all components of the project. . What opportunities for training and professional development has the project provided?During the current reporting period (Year 5), our project has provided a beneficial educational impact on and opportunities for training and professional development to the doctoral students and postdoctoral researchers who are providing research assistance in all project phases in both disciplinary and transdisciplinary research, including gathering and analyzing data; developing, estimating, and running the models; writing papers; and presenting at meetings and conferences. . How have the results been disseminated to communities of interest?Although it has been less than 3 years and 9 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 4 years and 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the pandemic, we have already disseminated our research to multiple communities of interest during the current reporting period. . During the current reporting period (Year 5), we participated and presented at events in which we delivered science-based knowledge to people, stakeholders, and target audiences. Team members participated and shared draft research results with the Cornell Cooperative Extension Agriculture-Solar group of educators during monthly meetings throughout the year. We also participated in multiple meetings of the Cornell University Agrivoltaic Research Group to share draft results and information. In January 2023, we presented our work remotely to the Alfred P. Sloan Foundation. In April 2024, we presented our work to the Power System Planning Group of the New York Independent System Operator (NYISO). Our work was featured on NYISO PowerTrends Podcast Episode 32 in April 2024. In March 2024, we presented our work at the Independent Power Producers of New York (IPPNY) Annual Meeting. In December, we presented our work at the New York State Department of Public Service, Zero By 2040 Tech Conference. . During the current reporting period (Year 5), we have also presented our work at the SRA Annual Meeting (December 2023), the INFORMS Annual Meeting (October 2023), Texas A&M University (October 2023), the 56th Annual Hawaii International Conference on System Sciences (January 2023), the University of Michigan (April 2024), the Power Engineering Research Center (PSERC) Webinar (November 2023), and the ASABE Annual International Meeting (July 2024). . During the current reporting period (Year 5), we have also met with representatives of New York State agencies repeatedly to discuss the intersection of agriculture and renewable energy development as the state works to meet the requirements of the Climate Leadership and Community Protection Act. . What do you plan to do during the next reporting period to accomplish the goals?During the next reporting period (Year 6), in order to accomplish the goals, we plan to continue working on Objectives 1, 2, and 3. . During the next reporting period (Year 6), as part of Objective 1, we plan to use our detailed, comprehensive spatial geo-coded annual parcel-level panel data set on land use, crop choice, wind installations, solar installations, and electric substations in all of New York State to develop and estimate a novel, interdisciplinary dynamic structural econometric model to analyze land use decision-making behavior; to continue to develop and refine our modeling framework for understanding how renewable energy infrastructure investments on rural private lands will alter the food-energy-water system throughout NY; and to continue to work on addressing Q1.1 to Q1.10. . During the next reporting period (Year 6), as part of Objectives 1 and 3, we plan to work on and preparing for submission to a peer-reviewed journal an analysis analysis of how solar development will affect agricultural land use to date and also in the future to meet climate goals. . As part of Objectives 1, 2, and 3, during the next reporting period (Year 6), we will continue to develop our land use market, power system, and hydrologic models in preparation for us to eventually couple the land use market, power system, and hydrologic models developed across the project team to analyze how ag-to-energy scenarios under land market dynamics will impact different facets of the NYS food-energy-water system, and how those impacts might feed back into land use dynamics for ag-to-energy transitions. . As part of Objectives 1, 2, and 3, during the next reporting period (Year 6), we will continue to develop our innovative FEW system modeling framework to investigate how ag-to-energy land use transitions will propagate through the dynamics of land markets, and how such transitions will generate feed-forward and feed-back effects on agricultural production, water quality and quantity, and electrical grid operational efficiency, under impacts from climate and other exogenous factors. . In addition to the many notable Year 5 accomplishments we described above, we also have several publications during the current reporting period (Year 5). As it has been less than 3 years and 9 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, and as it has been less than 4 years and 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, many of the publications for our research during the current reporting period (Year 5) proceeded without NIFA support. During the next reporting period (Year 6), as we continue working on Objectives 1, 2, and 3, we plan to publish more publications and products that result from and acknowledge NIFA support. .
Impacts
What was accomplished under these goals?
Agriculture-to-energy land-use conversions -- putting solar panels or wind turbines on arable farmland -- have the potential to impact food production, energy prices, water quality, and resilience to changes in climate. To understand how the food-energy-water (FEW) system is being transformed through ag-to-energy land conversions, as well as the potential implications, we are developing a novel econometric model of land use dynamics, loosely coupled with landscape-scale, process-level models of agricultural, water, and energy systems. We are applying the modeling framework to New York State, an ideal test-bed due to the state's incentives to achieve 70% renewable electricity by 2030 and its recent Climate Leadership and Community Protection Act (CLCPA) requiring zero-emissions electricity generation by 2040; a water system that is largely self-contained within state boundaries; and a thriving agricultural sector at higher risk in recent years due to climate impacts. The results of this work will provide a scientific basis to improve national, state, and regional policy decisions related to land use, agriculture, renewable energy, and energy prices over time and space to promote FEW system sustainability and resilience and maximize net benefits to society. . Although it has been less than 3 years and 9 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 4 years and 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the pandemic, we have made many notable accomplishments under these goals during the reporting period. . During the current reporting period (Year 5), as part of Objective 1, we have constructed a detailed, comprehensive spatial geo-coded annual parcel-level panel data set on land use, crop choice, wind installations, solar installations, and electric substations for all of New York State (NY). To do so, we merged our detailed, comprehensive spatial geo-coded data set of agriculture and energy for all of NY with our parcel boundary data. We merged the farm boundaries with the geo-coded wind turbine and solar installation location data to determine which farms have converted to solar and wind, and when. We then selected and streamlined the agricultural and other land uses we will focus on. We also collected geo-coded data on the location of electric substations, and merged our spatial geo-coded annual parcel-level panel data set with geo-coded electric substation location data. We are currently working on using the annual parcel-level panel data to develop and estimate a novel, interdisciplinary dynamic structural econometric model to model and analyze land use decision-making behavior; and to continue to develop and refine our model framework for understanding how renewable energy infrastructure investments on rural private lands will alter the FEW system throughout NY. . Also as part of Objective 1, during the current reporting period, we have developed a statewide, spatially explicit model that simulates power generation, load, transmission, and electricity prices within the New York State (NYS) grid under different scenarios of renewable power penetration. We have used variants of this model in three separate analyses of power system reliability under climate variability and change. In the first analysis, as part of Objectives 1-3, we evaluated the impact of multi-scale hydroclimatic variability on the reliability of a zero-emissions power system in New York State (NYS), which recently passed the Climate Leadership and Community Protection Act (CLCPA) requiring zero-emissions electricity generation by 2040. In our second analysis, as part of Objectives 1 and 2, we further explored how the variability and intermittency of renewable energy sources pose several challenges for power systems operations in New York State, this time focusing on energy curtailment and price volatility. In our third analysis, as part of Objectives 1-3, we shifted our focus to the vulnerabilities of the proposed zero-carbon power grid for NYS under climatic and technological changes. . During the current reporting period, as part of Objectives 1 and 2, we investigated signals of climate change in the Northeast US. Specifically, we explored how extreme precipitation scales with dewpoint temperature across the northeastern United States, both in the observational record and in a set of downscaled climate projections. This relationship is key to future flooding and associated impacts (e.g., water quality degradation) in the region. We evaluated the spatiotemporal relationships between dewpoint temperature and extreme precipitation, as well as extreme precipitation-temperature scaling rates on annual and seasonal scales using nonstationary extreme value analysis. . During the current reporting period, as part of Objective 1, we have conducted an analysis of how solar development will affect agricultural land use to date and also in the future to meet climate goals. We investigated land use trends for existing and planned utility-scale solar (USS) sites in New York State, utilizing manual and automated techniques to digitize USS site boundaries. We also employed Monte-Carlo analysis and Maximum Entropy (MaxEnt) modeling techniques to project likely future land use changes to meet a zero-carbon electricity goal by 2040. . During the current reporting period, as part of Objective 1, we have conducted an analysis of how land-based wind power development will affect agricultural land use to date and to meet future climate goals. Here, we analyze the effect of large-scale (20 MW or greater) land-based wind energy on current and projected future agriculture and forest land use in New York State. Annual land-based wind power capacity for large scale (20 MW or greater) wind power from 2000 to 2027 was calculated from national and state databases and future projected capacity was extracted from state planning documents. The area of land required and the types of land used for wind power projects was calculated based on data reported for 13 existing projects in the state. . As part of Objectives 1-3, during the reporting period we have reviewed state mandated goals, state and local policies, and current patterns of solar and wind development in order to develop scenarios of how much land of different land cover types may be required by 2030 and 2050. We have also met with representatives of New York State agencies repeatedly to discuss the intersection of agriculture and renewable energy development as the state works to meet the requirements of the Climate Leadership and Community Protection Act.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Kabir, E., V. Srikrishnan, M.V. Liu, Scott Steinschneider, and C. Lindsay Anderson. (2024). Quantifying the impact of multi-scale climate variability on electricity prices in a renewable-dominated power grid, Renewable Energy, 223.
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Taylor, W., Z. Brodeur, Scott Steinschneider, and J.D. Herman. (2024). Variability, attributes, and drivers of optimal forecast-informed reservoir operating policies for water supply and flood control in California, Journal of Water Resources Planning and Management, 150 (10).
- Type:
Journal Articles
Status:
Accepted
Year Published:
2024
Citation:
Najibi, N., A.J. Perez, W. Arnold, A. Schwarz, R. Maendly, and Scott Steinschneider. (2024). A Statewide, Weather-Regime based Stochastic Weather Generator for Process-Based Bottom-Up Climate Risk Assessments in California Part I: Model Evaluation, Climate Services, Accepted.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2024
Citation:
Najibi, N., A.J. Perez, W. Arnold, A. Schwarz, R. Maendly, Scott Steinschneider. (2024). A Statewide, Weather-Regime based Stochastic Weather Generator for Process-Based Bottom-Up Climate Risk Assessments in California Part II: Thermodynamic and Dynamic Climate Change Scenarios, Climate Services, Accepted.
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Brodeur, Z., S. Wi, G. Shabestanipour, J. Lamontagne, and Scott Steinschneider. (2024). A hybrid, non-stationary stochastic watershed model (SWM) for uncertain hydrologic simulations under climate change. Water Resources Research, 60, e2023WR035042.
- Type:
Journal Articles
Status:
Under Review
Year Published:
2024
Citation:
Liu, M.V., V. Srikrishnan, K. Doering, E. Kabir, Scott Steinschneider, and C. Lindsay Anderson. Heterogeneous Vulnerability of Zero-Carbon Power Grids under Climate-Technological Changes, Joule, under review
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Shabestanipour, G., Z. Brodeur, B. Manoli, A. Birnbaum, Scott Steinschneider, and J.R. Lamontagne. (2024). Risk-based hydrologic design under climate change using stochastic weather and watershed modeling, Frontiers in Water, 6.
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Brodeur, Z.P., C. Delaney, B. Whitin, and Scott Steinschneider. (2024). Synthetic forecast ensembles for evaluating forecast informed reservoir operations. Water Resources Research, 60, e2023WR034898.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Semmendinger, K., and Scott Steinschneider. (2023). Influence of Subseasonal-to-Annual Water Supply Forecasts on Many-Objective Water System Robustness under Long-Term Change, Journal of Water Resources Planning and Management, 150 (5).
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Gupta, R.S., Scott Steinschneider, and P.M. Reed. (2023). Understanding Contributions of Paleo-Informed Natural Variability and Climate Changes on Hydroclimate Extremes in the San Joaquin Valley of California, Earths Future, 11, e2023EF003909.
- Type:
Journal Articles
Status:
Published
Year Published:
2024
Citation:
Wi, S., and Scott Steinschneider. (2024). On the need for physical constraints in deep learning rainfall-runoff projections under climate change, Hydrol. Earth Syst. Sci., 28, 479503.
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Progress 09/01/22 to 08/31/23
Outputs
Target Audience:Although it has been less than 2 years and 9 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 3 years and 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the pandemic, our efforts have already reached multiple target audiences during the current reporting period. During the current reporting period (Year 4), we participated and presented at events in which we delivered science-based knowledge to people, stakeholders, and target audiences. In November 2022, we gave an invited oral webinar presentation and discussion for the Cornell Cooperative Extension Agriculture-Solar group of educators on "Agriculture to solar land use change in New York State". During the current reporting period (Year 4), we have also met with representatives of New York State agencies repeatedly to discuss the intersection of agriculture and renewable energy development as the state works to meet the requirements of the Climate Leadership and Community Protection Act. These scenarios will contribute to Objectives 1 and 3 of our project. During the current reporting period, our research has had a beneficial educational impact on the doctoral students and postdoctoral researchers who are providing research assistance in all project phases in both disciplinary and transdisciplinary research, including gathering and analyzing data; developing, estimating, and running the models; writing papers; and presenting at meetings and conferences. Changes/Problems:Although it has been less than 2 years and 9 months since NIFA released all the funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 3 years and 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the pandemic, we have made many notable accomplishments under the major goals of our project. Nevertheless, due to several factors, there are remaining tasks that we need to complete under our work plan. These include: - Continuing to develop and refine our model framework for understanding how renewable energy infrastructure investments on rural private lands will alter the food-energy-water system throughout NY. - Developing and estimating a novel, cutting-edge, and interdisciplinary dynamic structural econometric model that combines economics, econometrics, dynamic optimization, game theory, engineering, hydrology, ecology, and soil and crop sciences to model and analyze land use decision-making behavior. - Coupling the land use market, power system, and hydrologic models to analyze how ag-to-energy scenarios under land market dynamics will impact different facets of the NYS food-energy-water system, and how those impacts might feed back into land use dynamics for ag-to-energy transitions. - Using our coupled models to explore how to design policies to promote FEW sustainability and resilience under ag-to-energy land conversions. - Completing and publishing some of the analyses above, including: (1) how demand for land for solar and wind projects will affect agricultural production; (2) effects of prior land use on GHG benefits of solar energy projects; (3) climate change impacts on electricity prices in a highly renewable NYS power system. - Completing policy briefs on (1) effects of renewable development on agricultural production and (2) effects of prior land use on GHG benefits of solar energy projects, including leakage. There are several causes for the delay in completing the above tasks. - First, the release of funding from USDA for Year 1 of the project was significantly delayed (released March 2020; project start date of September 2019). This 6-month delay prevented the project team from being able to begin work on the project, and also complicated the hiring process for the 2019-2020 academic year. - Second, although the project start date was September 2019, and although our Year 1 funds were released for our expenditure 6 months after the start date in March 2020, when we did receive the Year 1 funds 6 months later it was still uncertain whether we would receive all 3 years of funding. Uncertainty about whether we would receive all 3 years of funding for our 3-year project made it difficult for us to make the long-term investments needed for our project, and made it difficult for us to recruit, hire, and train the needed personnel for our project, since we did not have the funds available to commit to funding any needed personnel beyond Year 1. - Third, when the funds for Year 1 were released in March 2020, the COVID-19 pandemic caused widespread closure of campus activities and a dramatic shift of work responsibilities and capacity for all members of the project team. The challenges associated with the pandemic further hindered our ability to recruit, hire, and train the needed personnel for our project; and adversely affected the ability of project team members to interact with one another and with stakeholders. - Fourth, although the project start date was September 2019, and although our Year 1 funds were released for our expenditure 6 months after the start date in March 2020, we did not receive the Year 2 and Year 3 funds for our 3-year project until 1.25 years (15 months) after the start date, in December 2020. This 1.25-year delay in the full funding for our 3-year project prevented the project team from making the long-term investments to recruit, hire, and train the needed personnel for our project during both the 2019-2020 and 2020-2021 academic years. - Fifth, after the onset of the pandemic, Cornell imposed a campus-wide hiring freeze that further delayed our hiring of research staff for the project during both the 2020-2021 and 2021-2022 academic years. - Sixth, the project team faced additional delays during the 2020-2021 and 2021-2022 academic years, including one failed post-doc search once hiring restrictions were lifted, and a medical emergency for one graduate student working on the project that delayed progress for several months. -Seventh, the project team faced a second failed post-doc search owing to uncertainty over whether we would receive a 3-year no-cost extension for the 3 additional years we need to complete the project. Uncertainty about whether we would receive a 3-year no-cost extension for the 3 additional years we need to complete the project has continued to make it difficult for us to make the long-term investments needed for our project, and has made it difficult for us to recruit, hire, and train the needed personnel for our project during the 2022-2023 academic year, since it has continued to be uncertain whether we will be able to commit to funding any needed personnel beyond August 31, 2023. -Furthermore, while we have received a 1-year no-cost extension to August 31, 2023, and another 1-year no-cost extension to August 31, 2024, we will need 3 additional years to complete the project objectives, and over each of the past 2 years it has been uncertain whether we will be able to receive a 3-year no-cost extension for the 3 additional years we need to complete the project objectives. Uncertainty about whether we would receive a 3-year no-cost extension for the 3 additional years we need to complete the project has continued to make it difficult for us to make the long-term investments needed for our project, and continues to make it difficult for us to recruit, hire, and train the needed personnel for our project, since it is uncertain whether we will be able to commit to funding any needed personnel beyond August 31, 2024. Despite all of these delays, the project team has made strong progress on all of the components of the project. Nevertheless, these delays have slowed our original timeline, and we will need 3 additional years to complete the project objectives. We would therefore like to request a 3-year no-cost extension, so that the end date of our project is August 31, 2027 instead of August 31, 2024, to help the team complete all components of the project. What opportunities for training and professional development has the project provided?During the current reporting period (Year 4), our project has provided a beneficial educational impact on and opportunities for training and professional development to the doctoral students and postdoctoral researchers who are providing research assistance in all project phases in both disciplinary and transdisciplinary research, including gathering and analyzing data; developing, estimating, and running the models; writing papers; and presenting at meetings and conferences. How have the results been disseminated to communities of interest?Although it has been less than 2 years and 9 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 3 years and 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the pandemic, we have already disseminated our research to multiple communities of interest during the current reporting period. During the current reporting period (Year 4), we participated and presented at events in which we delivered science-based knowledge to people, stakeholders, and target audiences. For example, in November 2022, we gave an invited oral webinar presentation and discussion for the Cornell Cooperative Extension Agriculture-Solar group of educators on "Agriculture to solar land use change in New York State". During the current reporting period (Year 4), we have also met with representatives of New York State agencies repeatedly to discuss the intersection of agriculture and renewable energy development as the state works to meet the requirements of the Climate Leadership and Community Protection Act. What do you plan to do during the next reporting period to accomplish the goals?During the next reporting period (Year 5), in order to accomplish the goals, we plan to continue working on Objectives 1, 2, and 3. During the next reporting period (Year 5), as part of Objective 1, we plan to use our detailed, comprehensive spatial geo-coded annual parcel-level panel data set on land use, crop choice, wind installations, solar installations, and electric substations in all of New York State to develop and estimate a novel, interdisciplinary dynamic structural econometric model to analyze land use decision-making behavior; to continue to develop and refine our modeling framework for understanding how renewable energy infrastructure investments on rural private lands will alter the food-energy-water system throughout NY; and to continue to work on addressing Q1.1 to Q1.10. During the next reporting period (Year 5), as part of Objectives 1 and 3, we plan to work on and preparing for submission to a peer-reviewed journal an analysis of the effects of prior land use on GHG benefits of solar energy projects. We also plan to work on policy briefs on the effects of prior land use on GHG benefits of solar energy projects, including leakage. As part of Objectives 1, 2, and 3, during the next reporting period (Year 5), we will continue to develop our land use market, power system, and hydrologic models in preparation for us to eventually couple the land use market, power system, and hydrologic models developed across the project team to analyze how ag-to-energy scenarios under land market dynamics will impact different facets of the NYS food-energy-water system, and how those impacts might feed back into land use dynamics for ag-to-energy transitions. As part of Objectives 1, 2, and 3, during the next reporting period (Year 5), we will continue to develop our innovative FEW system modeling framework to investigate how ag-to-energy land use transitions will propagate through the dynamics of land markets, and how such transitions will generate feed-forward and feed-back effects on agricultural production, water quality and quantity, and electrical grid operational efficiency, under impacts from climate and other exogenous factors. In addition to the many notable Year 4 accomplishments we described above, we also have several publications during the current reporting period (Year 4). As it has been less than 2 years and 9 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, and as it has been less than 3 years and 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, many of the publications for our research during the current reporting period (Year 4) proceeded without NIFA support. During the next reporting period (Year 5), as we continue working on Objectives 1, 2, and 3, we plan to publish more publications and products that result from and acknowledge NIFA support.
Impacts
What was accomplished under these goals?
Agriculture-to-energy land-use conversions -- putting solar panels or wind turbines on arable farmland -- have the potential to impact food production, energy prices, water quality, and resilience to changes in climate. To understand how the food-energy-water (FEW) system is being transformed through ag-to-energy land conversions, as well as the potential implications, we are developing a novel econometric model of land use dynamics, loosely coupled with landscape-scale, process-level models of agricultural, water, and energy systems. We are applying the modeling framework to New York State, an ideal test-bed due to the state's incentives to achieve 70% renewable electricity by 2030 and its recent Climate Leadership and Community Protection Act (CLCPA) requiring zero-emissions electricity generation by 2040; a water system that is largely self-contained within state boundaries; and a thriving agricultural sector at higher risk in recent years due to climate impacts. The results of this work will provide a scientific basis to improve national, state, and regional policy decisions related to land use, agriculture, renewable energy, and energy prices over time and space to promote FEW system sustainability and resilience and maximize net benefits to society. Although it has been less than 2 years and 9 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 3 years and 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the pandemic, we have made many notable accomplishments under these goals during the reporting period. During the current reporting period (Year 4), as part of Objective 1, we have constructed a detailed, comprehensive spatial geo-coded annual parcel-level panel data set on land use, crop choice, wind installations, solar installations, and electric substations for all of New York (NY) State (NYS). To do so, we merged our detailed, comprehensive spatial geo-coded data set of agriculture and energy for all of NY with our parcel boundary data. We merged the farm boundaries with the geo-coded wind turbine and solar installation location data to determine which farms have converted to solar and wind, and when. We then selected and streamlined the agricultural and other land uses we will focus on. We also collected geo-coded data on the location of electric substations, and merged our spatial geo-coded annual parcel-level panel data set with geo-coded electric substation location data. We are currently working on using the annual parcel-level panel data to develop and estimate a novel, interdisciplinary dynamic structural econometric model to model and analyze land use decision-making behavior; and to continue to develop and refine our model framework for understanding how renewable energy infrastructure investments on rural private lands will alter the FEW system throughout NY. Also as part of Objective 1, during the current reporting period, we have developed a statewide, spatially explicit model that simulates power generation, load, transmission, and electricity prices within the New York State (NYS) grid under different scenarios of renewable power penetration. We have used variants of this model in three separate analyses of power system reliability under climate variability and change. In the first analysis, as part of Objectives 1-3, we evaluated the impact of multi-scale hydroclimatic variability on the reliability of a zero-emissions power system in New York State (NYS), which recently passed the Climate Leadership and Community Protection Act (CLCPA) requiring zero-emissions electricity generation by 2040. We first analyzed covariation between renewable energy generation and energy demand, including large-scale hydropower generation on the Great Lakes, and developed a stochastic generator to simulate an ensemble of plausible realizations of this joint variability. Using a simplified energy balance model of the NYS power system, we show that the covariability between load and wind can lead to major short-term resource gaps, which is exacerbated by transmission constraints. In our second analysis, as part of Objectives 1 and 2, we further explored how the variability and intermittency of renewable energy sources pose several challenges for power systems operations in New York State, this time focusing on energy curtailment and price volatility. We used an accurate, reduced-form representation of the New York power system, which integrates additional wind, and solar power resources to meet the state's energy targets through 2030. On an hourly basis, renewable volatility may vary up to 100% above and below average. While yearly average price volatility is influenced mainly by hydropower availability, daily and hourly price volatility is influenced by solar and wind availability. In our third analysis, as part of Objectives 1-3, we shifted our focus to the vulnerabilities of the proposed zero-carbon power grid for NYS under climatic and technological changes. This work used a large ensemble of 300 different future scenarios of temperature increase and associated changes to the capacity and timing of hydropower availability, capacity for other renewable resources, and electrification rates for buildings and transportation in different regions. Our findings revealed a need for 30-65% more firm, zero-emission capacity to ensure system reliability than is currently being considered in NYS plans for a future, zero-carbon power grid. Merely increasing wind and solar capacity is ineffective in improving reliability due to the spatial and temporal variations in vulnerabilities. The results of this work underscore the importance of considering spatiotemporal dynamics and operational constraints when making decisions regarding additional investments in renewable resources. During the current reporting period, as part of Objectives 1 and 2, we also investigated signals of climate change in the Northeast US. Specifically, we explored how extreme precipitation scales with dewpoint temperature across the northeastern United States, both in the observational record and in a set of downscaled climate projections. As part of Objectives 1-3, during the reporting period we have reviewed state mandated goals, state and local policies, and current patterns of solar and wind development in order to develop scenarios of how much land of different land cover types may be required by 2030 and 2050. We have also met with representatives of New York State agencies repeatedly to discuss the intersection of agriculture and renewable energy development as the state works to meet the requirements of the Climate Leadership and Community Protection Act. As part of Objectives 1 and 3 of our project, we have been analyzing how demand for land for solar farms will affect agricultural production and greenhouse gas (GHG) emissions. A major motivation for development of renewable energy is to mitigate GHG emissions. Solar farms require large amounts of land and often replace agricultural and forest production, however, and compete with other mitigation options such as afforestation and bioenergy feedstock production. We are analyzing how these land use changes affect the GHG benefits of solar farms when placed on idle former agricultural land, current agricultural land, or current forest land in New York State. We have also conducted geospatial analysis of idle former agricultural land the could be available for renewable energy development or for expanded agricultural production.
Publications
- Type:
Other
Status:
Published
Year Published:
2022
Citation:
Peter B. Woodbury. (2022). Agriculture to solar land use change in New York State . Invited oral webinar presentation and discussion for the Cornell Cooperative Extension Agriculture-Solar group of educators. 9 November 2022.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
K. Doering, C. Lindsay Anderson, and Scott Steinschneider. (2023). Evaluating the intensity, duration, and frequency of flexible energy resources needed in a zero-emission, hydropower reliant power system Oxford Open Energy, 1, oiad003.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
N. Najibi and Scott Steinschneider. (2023). Extreme precipitation-temperature scaling in California: The role of atmospheric rivers. Geophysical Research Letters, 50, e2023GL104606.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
M.V. Liu, B. Yuan, Z. Wang, J.A. Sward, K.M. Zhang, and C. Lindsay Anderson. (2023). An open source representation for the NYS electric grid to support power grid and market transition studies. IEEE Transactions on Power Systems, 38 (4), 3293-3303.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
S.S. Borkotoky, A.P. Williams, and Scott Steinschneider. (2023). Six hundred years of reconstructed atmospheric river activity along the US west coast. Journal of Geophysical Research: Atmospheres, 128, e2022JD038321.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
J.K. Israel, Z. Zhang, Y. Sang, P.M. McGuire, Scott Steinschneider, and M.C. Reid. (2023). Climate change effects on denitrification performance of woodchip bioreactors treating agricultural tile drainage. Water Research, 242, 120202.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
S. Mukhopadhyay, M. Leung, L. Cagigal, J. Kucharski, P. Ruggiero, and Scott Steinschneider. (2023). Understanding the natural variability of still water levels in the San Francisco Bay over the past 500 yr: Implications for future coastal flood risk. Journal of Geophysical Research: Oceans, 128, e2022JC019012.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
G. Shabestanipour, Z. Brodeur, W.H. Farmer, Scott Steinschneider, R.M. Vogel, and J.R. Lamontagne. (2023). Stochastic watershed model ensembles for long-range planning: Verification and validation. Water Resources Research, 59, e2022WR032201.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
R. Sayess and Scott Steinschneider. (2023). Characterization and drivers of haloacetic acids in New York State. AWWA Water Science, e1321.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Scott Steinschneider, J.D. Herman, J. Kucharski, M. Abellera, and P. Ruggiero. (2023). Uncertainty decomposition to understand the influence of water systems model error in climate vulnerability assessments. Water Resources Research, 59, e2022WR032349.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
K.E. Thome and C.-Y. Cynthia Lin Lawell. (2022). Corn ethanol in the Midwestern USA: Local competition, entry and agglomeration. Journal of Economic Geography, 22 (6), 1247-1273.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Z. Li and Ariel Ortiz?Bobea. (2022). On the timing of relevantweather conditions in agriculture. Journal of the Agricultural and Applied Economics Association, 1, 180195.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
K. Wang and Scott Steinschneider. (2022). Characterization of multi-scale fluvial suspended sediment transport dynamics across the United States using turbidity and dynamic regression. Water Resources Research, 58, e2021WR031863.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
S. Blom, Ariel Ortiz-Bobea, and J. Hoddinott. (2022). Temperature and childrens nutrition: Evidence from West Africa. Journal of Environmental Economics and Management, 155, 102698.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
A. Ernst, L.-H. Wang, S. Worland, B. Marfil-Garza, X. Wang, W. Liu, A. Chiu, T. Kin, D. O'Gorman, Scott Steinschneider, A. Datta, K. Papas, A.M.J. Shapiro, and M. Ma. (2022). A predictive computational platform for optimizing the design of bioartificial pancreas devices. Nature Communications, 13, 6031.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
C. Zhang, Z. Brodeur, Scott Steinschneider, and J. Herman. (2022). Leveraging spatial patterns in precipitation forecasts using deep learning to support regional water management. Water Resources Research, 58, e2021WR031910.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
S. Wi and Scott Steinschneider. (2022). Assessing the physical realism of deep learning hydrologic model projections under climate change. Water Resources Research, 58, e2022WR032123.
|
Progress 09/01/21 to 08/31/22
Outputs
Target Audience:Although it has been less than 1 year and 8 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 2 years and 5 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the ongoing pandemic, our efforts have already reached multiple target audiences during the current reporting period. During the current reporting period (Year 3), we participated and presented at 4 events in which we delivered science-based knowledge to people, stakeholders, and target audiences. In February 2022, we presented our research at the 2022 INFEWS PI Workshop. In March 2022, we presented our research in a webinar presentation hosted by RTI International Center for Climate Solutions to an audience of 86 participants. In April 2022, we presented a webinar as part of the Cornell University Greenhouse Gases & Working Lands Webinar Series. Cornell University. In May 2022, we led a webinar presentation and discussion on our research with a class of 14 high school students from a local high school in Dryden, New York. During the current reporting period (Year 3), we have also met with representatives of New York State (NYS) agencies repeatedly to discuss the intersection of agriculture and renewable energy development as the state works to meet the requirements of the Climate Leadership and Community Protection Act. These scenarios will contribute to Objectives 1 and 3 of our project. During the current reporting period, our research has had a beneficial educational impact on the doctoral students and postdoctoral researchers who are providing research assistance in all project phases in both disciplinary and transdisciplinary research, including gathering and analyzing data; developing, estimating, and running the models; writing papers; and presenting at meetings and conferences. Changes/Problems:Although it has been less than 1 year and 8 months since NIFA released all the funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 2 years and 5 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the ongoing pandemic, we have made many notable accomplishments under the major goals of our project. Nevertheless, due to several factors, there are remaining tasks that we need to complete under our work plan. These include: - Continuing to develop and refine our model framework for understanding how renewable energy infrastructure investments on rural private lands will alter the food-energy-water system throughout NY. - Developing and estimating a novel, cutting-edge, and interdisciplinary dynamic structural econometric model that combines economics, econometrics, dynamic optimization, game theory, engineering, hydrology, ecology, and soil and crop sciences to model and analyze land use decision-making behavior. - Coupling the land use market, power system, and hydrologic models to analyze how ag-to-energy scenarios under land market dynamics will impact different facets of the NYS food-energy-water system, and how those impacts might feed back into land use dynamics for ag-to-energy transitions. - Using our coupled models to explore how to design policies to promote FEW sustainability and resilience under ag-to-energy land conversions. - Completing and publishing some of the analyses above, including: (1) how demand for land for solar and wind projects will affect agricultural production; (2) effects of prior land use on GHG benefits of solar energy projects; (3) climate change impacts on electricity prices in a highly renewable NYS power system; (4) how ag-to-energy scenarios under land market dynamics will impact different facets of the NYS food-energy-water system; and (5) how to design policies to promote FEW sustainability and resilience under ag-to-energy land conversions. - Completing policy briefs on the analyses above, including: (1) effects of renewable development on agricultural production; (2) effects of prior land use on GHG benefits of solar energy projects, including leakage; and (3) how to design policies to promote FEW sustainability and resilience under ag-to-energy land conversions. There are several causes for the delay in completing the above tasks. - First, the release of funding from USDA for Year 1 of the project was significantly delayed (released March 2020; project start date of September 2019). This 6-month delay prevented the project team from being able to begin work on the project, and also complicated the hiring process for the 2019-2020 academic year. - Second, although the project start date was September 2019, and although our Year 1 funds were released for our expenditure 6 months after the start date in March 2020, when we did receive the Year 1 funds 6 months later it was still uncertain whether we would receive all 3 years of funding. Uncertainty about whether we would receive all 3 years of funding for our 3-year project made it difficult for us to make the long-term investments needed for our project, and made it difficult for us to recruit, hire, and train the needed personnel for our project, since we did not have the funds available to commit to funding any needed personnel beyond Year 1. - Third, when the funds for Year 1 were released in March 2020, the COVID-19 pandemic caused widespread closure of campus activities and a dramatic shift of work responsibilities and capacity for all members of the project team. The challenges associated with the ongoing pandemic further hindered our ability to recruit, hire, and train the needed personnel for our project; and adversely affected the ability of project team members to interact with one another and with stakeholders. - Fourth, although the project start date was September 2019, and although our Year 1 funds were released for our expenditure 6 months after the start date in March 2020, we did not receive the Year 2 and Year 3 funds for our 3-year project until 1.25 years (15 months) after the start date, in December 2020. This 1.25 -year delay in the full funding for our 3-year project prevented the project team from making the long-term investments to recruit, hire, and train the needed personnel for our project during both the 2019-2020 and 2020-2021 academic years. - Fifth, after the onset of the pandemic, Cornell imposed a campus-wide hiring freeze that further delayed our hiring of research staff for the project. - Sixth, the project team faced a few other delays, including one failed post-doc search once hiring restrictions were lifted, and a medical emergency for one graduate student working on the project that delayed progress for several months. Despite all of these delays, the project team has made strong progress on all of the components of the project. Nevertheless, these delays have slowed our original timeline, and we will need 3 additional years to complete the project objectives. We would therefore like to request a 3-year no-cost extension, so that the end date of our project is August 31, 2025 instead of August 31, 2022, to help the team complete all components of the project. What opportunities for training and professional development has the project provided?During the current reporting period (Year 3), our project has provided a beneficial educational impact on and opportunities for training and professional development to the doctoral students and postdoctoral researchers who are providing research assistance in all project phases in both disciplinary and transdisciplinary research, including gathering and analyzing data; developing, estimating, and running the models; writing papers; and presenting at meetings and conferences. . How have the results been disseminated to communities of interest?Although it has been less than 1 year and 8 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 2 years and 5 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the ongoing pandemic, we have already disseminated our research to multiple communities of interest during the current reporting period. During the current reporting period (Year 3), we participated and presented at several events in which we delivered science-based knowledge to people, stakeholders, and target audiences. For example, in February 2022, we presented our research at the 2022 INFEWS PI Workshop. In March 2022, we presented our research in a webinar presentation hosted by RTI International Center for Climate Solutions to an audience of 86 participants. In April 2022, we presented a webinar as part of the Cornell University Greenhouse Gases & Working Lands Webinar Series. Cornell University. During the current reporting period (Year 3), we have also undertaken outreach activities to reach members of communities who are not usually aware of these research activities for the purpose of enhancing public understanding and increasing interest in learning and careers in science, technology, and the humanities. For example, in May 2022, we led a webinar presentation and discussion on our research with a class of 14 high school students from rural town of Dryden, New York. During the current reporting period (Year 3), we have also met with representatives of NYS agencies repeatedly to discuss the intersection of agriculture and renewable energy development as the state works to meet the requirements of the Climate Leadership and Community Protection Act. What do you plan to do during the next reporting period to accomplish the goals?During the next reporting period (Year 4), in order to accomplish the goals, we plan to continue working on Objectives 1, 2, and 3. During the next reporting period (Year 4), as part of Objective 1, we plan to use detailed, comprehensive spatial geo-coded annual parcel-level panel data set on land use, crop choice, wind installations, and solar installations in all of NYS to develop and estimate a novel, interdisciplinary dynamic structural econometric model to analyze land use decision-making behavior; to continue to develop and refine our modeling framework for understanding how renewable energy infrastructure investments on rural private lands will alter the food-energy-water system throughout NY; and to continue to work on addressing Q1.1 to Q1.10. During the next reporting period (Year 4), as part of Objective 1, we plan to work on and publish our analysis on electricity price sensitivity to decadal renewable energy resource variability and the placement and capacity of renewable generators across the state. We also plan to work on and publish an analysis on climate change impacts on electricity prices and power system reliability in a highly renewable NYS power system. Major climate change impacts will include changes to the profile of Great Lakes hydropower, changes in load under electrification and warmer temperatures, the impacts of warming on power line efficiency, and possibly scenarios of wind speed changes. We intend to explore both the vulnerability of the system under climate change, as well as design measures to mitigate those vulnerabilities (e.g., changing the mix and placement of renewables; changing the planned capacity of battery resources). During the next reporting period (Year 4), as part of Objectives 1 and 3, we plan to work on and preparing for submission to a peer-reviewed journal an analysis of the effects of prior land use on GHG benefits of solar energy projects. We also plan to work on policy briefs on the effects of prior land use on GHG benefits of solar energy projects, including leakage. As part of Objectives 1, 2, and 3, during the next reporting period (Year 4), we will continue to develop our land use market, power system, and hydrologic models in preparation for us to eventually couple the land use market, power system, and hydrologic models developed across the project team to analyze how ag-to-energy scenarios under land market dynamics will impact different facets of the NYS food-energy-water system, and how those impacts might feed back into land use dynamics for ag-to-energy transitions. As part of Objectives 1, 2, and 3, during the next reporting period (Year 4), we will continue to develop our innovative FEW system modeling framework to investigate how ag-to-energy land use transitions will propagate through the dynamics of land markets, and how such transitions will generate feed-forward and feed-back effects on agricultural production, water quality and quantity, and electrical grid operational efficiency, under impacts from climate and other exogenous factors. In addition to the many notable Year 3 accomplishments we described above, we also have several publications during the current reporting period (Year 3). As it has been less than 1 year and 8 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, and as it has been less than 2 years and 5 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, many of the publications for our research during the current reporting period (Year 3) proceeded without NIFA support. During the next reporting period (Year 4), as we continue working on Objectives 1, 2, and 3, we plan to publish more publications and products that result from and acknowledge NIFA support.
Impacts
What was accomplished under these goals?
Agriculture-to-energy land-use conversions -- putting solar panels or wind turbines on arable farmland -- have the potential to impact food production, energy prices, water quality, and resilience to changes in climate. To understand how the food-energy-water (FEW) system is being transformed through ag-to-energy land conversions, as well as the potential implications, we are developing a novel econometric model of land use dynamics, loosely coupled with landscape-scale, process-level models of agricultural, water, and energy systems. We are applying the modeling framework to NYS, an ideal test-bed due to the state's incentives to achieve 70% renewable electricity by 2030; a water system that is largely self-contained within state boundaries; and a thriving agricultural sector at higher risk in recent years due to climate impacts. The results of this work will provide a scientific basis to improve national, state, and regional policy decisions related to land use, agriculture, renewable energy, and energy prices over time and space to promote FEW system sustainability and resilience and maximize net benefits to society. Although it has been less than 1 year and 8 months since NIFA released the Year 2 and Year 3 funds for our 3-year project to us in December 2020 for our expenditure, although it has been less than 2 years and 5 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the ongoing pandemic, we have made many notable accomplishments under these goals during the reporting period. During the current reporting period (Year 3), as part of Objective 1, we have constructed a detailed, comprehensive spatial geo-coded annual parcel-level panel data set on land use, crop choice, wind installations, and solar installations for all of NYS. To do so, we merged our detailed, comprehensive spatial geo-coded data set of agriculture and energy for all of NY with our parcel boundary data. We merged the farm boundaries with the geo-coded wind turbine and solar installation location data to determine which farms have converted to solar and wind, and when. We then selected and streamlined the agricultural and other land uses we will focus on. We are currently working on using the annual parcel-level panel data to develop and estimate a novel, interdisciplinary dynamic structural econometric model to model and analyze land use decision-making behavior; and to continue to develop and refine our model framework for understanding how renewable energy infrastructure investments on rural private lands will alter the FEW system throughout NY. Also, as part of Objective 1, during the current reporting period we have developed a statewide, spatially explicit model that simulates power generation, load, transmission, and electricity prices within the NYS grid under different scenarios of renewable power penetration. There are two versions of this model - an energy balance model and a power systems model - that were built in parallel to answer different questions regarding power system performance. The energy balance model was developed to model how a fully renewable power system composed of hydro, wind, and solar power could be used in conjunction with batteries, imports, and enhanced transfer capacity to balance load across the entire state. The model represents the system as a simplified 11-node network, with each node representing a load zone. Wind capacity is placed throughout NY at sampled locations from the NREL Wind Took Kit, where locations were sampled based on the spatial distribution of wind resource potential. Similarly, solar power capacity is placed at locations within the NREL Solar Integration National Dataset. Load is modeled as a function of temperature using neural networks for each of the 11 zones and based on historical load data from NY Independent System Operator (NYISO). Multiple scenarios of load and renewable capacity have been parameterized into the model to reflect different planning assumptions for NY, all of which are based on the studies and reports from NYISO. As part of Objectives 1 and 2, during the current reporting period, we coupled our energy balance model with a stochastic hydroclimate model, also developed for this project, that simulates future renewable energy resources (wind speeds, insolation, hydropower potential) and drivers of demand (temperature) across the state, both under climate variability and climate change. Using both of these tools, we conducted an analysis of power system reliability in a completely carbon-free NY power system. Our power systems model was developed as a reduced form of a 140-bus Northeast Power Coordinating Council model that includes the NY power system. This power systems model represents generators in NY, accounts for fuel costs, represents existing thermal generators, simulates locational marginal prices, and provides spatial granularity in load and generation across the state. The model is easily adjustable for future configurations and scenarios, including those related to future capacity and placement of renewable generators. Using this model, we are in the process of completing an assessment of electricity price sensitivity to decadal renewable energy resource variability and the placement and capacity of renewable generators across the state. This analysis is leveraging much of the data and analysis conducted for the energy balance model described above, including the placement and capacity scenarios of renewable energy resources, batteries, and models of load. As part of Objectives 1 and 2, we are in the process of expanding the stochastic hydroclimate model to generate internally consistent simulations of wind speeds, insolation, temperatures, and Great Lakes hydropower under an ensemble of future climate change projections from CMIP6 (the most recent generation of global climate model projections). This effort includes modeling Great Lakes hydrology in order to simulate hydropower from that system, which comprises a large fraction of New York's current renewable energy portfolio. As part of Objectives 1-3, during the reporting period we have reviewed state mandated goals, state and local policies, and current patterns of solar and wind development in order to develop scenarios of how much land of different land cover types may be required by 2030 and 2050. We have also met with representatives of NYS agencies repeatedly to discuss the intersection of agriculture and renewable energy development as the state works to meet the requirements of the Climate Leadership and Community Protection Act. As part of Objectives 1 and 3 of our project, we have been analyzing how demand for land for solar farms will affect agricultural production and greenhouse gas (GHG) emissions. A major motivation for development of renewable energy is to mitigate GHG emissions. Solar farms require large amounts of land and often replace agricultural and forest production, however, and compete with other mitigation options such as afforestation and bioenergy feedstock production. We are analyzing how these land use changes affect the GHG benefits of solar farms when placed on idle former agricultural land, current agricultural land, or current forest land in NYS. We have also conducted geospatial analysis of idle former agricultural land that could be available for renewable energy development or for expanded agricultural production. Afforestation and bioenergy feedstock production are being analyzed by NY as opportunities to meet State mandates for GHG mitigation by 2030 and 2050. As part of Objective 1, we are developing scenarios of the amount of land that could be required for these mitigation opportunities, as well as analyzing the GHG benefits compared to solar energy development.
Publications
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2022
Citation:
T. Wu, C. Lindsay Anderson, C.-Y. Cynthia Lin Lawell, Ariel Ortiz-Bobea, Scott Steinschneider, M. Todd Walter, and Peter B. Woodbury. (2022). Agricultural-to-Energy Land Use Transitions: A FEW System . Resources and Sustainability: Deep Dive. 2022 INFEWS PI Workshop. Princeton University. February 2022.
- Type:
Other
Status:
Other
Year Published:
2022
Citation:
J. Woollacott, K. Austin, Z. Majumdar, C. Jahns, Peter B. Woodbury, B. Steinmuller, B. Ellis, and S. Hunt. (2022). Climate Changes Agriculture & Forestry -- Economic Impacts of Investing in Climate Mitigation in New York Forests & Agriculture . Invited panelist in webinar presentation hosted by RTI International Center for Climate Solutions. 8 March 2022.
- Type:
Other
Status:
Other
Year Published:
2022
Citation:
Peter B. Woodbury. (2022). A researchers perspective on climate solutions in agriculture and forestry . Webinar presentation and discussion with Travis Crockers Climate Change Class at Dryden High School, Dryden NY. 11 May 2022.
- Type:
Other
Status:
Other
Year Published:
2022
Citation:
Peter B. Woodbury and J. Wightman. (2022). Using former agricultural land to help meet New York States climate goals . Land Use & Greenhouse Gases Webinar. Part of the GHG & Working Lands Webinar Series. Cornell University. 12 April 2022.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
N. Najibi and Scott Steinschneider. (2022). Observed and Projected Scaling of Daily Extreme Precipitation with Dew Point Temperature at Annual and Seasonal Scales across the Northeast United States. Journal of Hydrometeorology, 23 (3), 403-419.
- Type:
Other
Status:
Published
Year Published:
2021
Citation:
V. Liu, B. Yuan, Z. Wang, J.A. Sward, K.M. Zhang, and C. Lindsay Anderson. (2021). An open source representation for the NYS electric grid to support power grid and market transition studies. arXiv preprint arXiv:2112.06756.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
R. Gupta, Scott Steinschneider, and P.M. Reed. (2022). A Multi-Objective Paleo-Informed Reconstruction of Western U.S. Weather Regimes Over the Past 600 Years. Climate Dynamics.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
K. Semmendinger, D. Lee, L. Fry, and Scott Steinschneider. (2022). Establishing Opportunities and Limitations of Forecast Use in the Operational Management of Highly Constrained, Multi-Objective Water Systems. Journal of Water Resources Planning and Management, 148 (8).
- Type:
Journal Articles
Status:
Accepted
Year Published:
2022
Citation:
K.E. Thome and C.-Y. Cynthia Lin Lawell. (2022). Corn ethanol in the Midwestern USA: Local competition, entry and agglomeration. Journal of Economic Geography, forthcoming.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
N. Najibi and Scott Steinschneider. (2022). Precipitation Scaling with Temperature in the Northeast US: Variations by Weather Regime, Season, and Precipitation Intensity. Geophysical Research Letters, 49 (8), 1-14, e2021GL097100.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
S.H. Rahat, Scott Steinschneider, J. Kucharski, W. Arnold, J. Olzewski, W. Walker, R. Maendly, A. Wasti, and P. Ray. (2022). Characterizing Hydrologic Vulnerability under Non-Stationary Climate and Antecedent Conditions using a Process-Informed Stochastic Weather Generator. Journal of Water Resources Planning and Management, 148 (6).
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
E. Potash and Scott Steinschneider. (2022). A Bayesian Approach to Recreational Water Quality Model Validation and Comparison in the Presence of Measurement Error. Water Resources Research, accepted. 58, e2021WR031115.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
M. Aghaei and C.-Y. Cynthia Lin Lawell. (2022). Energy, economic growth, inequality, and poverty in Iran. Singapore Economic Review, 67 (2), 733-754.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
A. Flecker, ...., Scott Steinschneider, et al. (2022). Reducing adverse impacts of Amazon hydropower expansion. Science, 375 (6582), 753-760.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
K. Malek, P.M. Reed, H. Zeff, A. Hamilton, M. Wrzesien, N. Holtzman, Scott Steinschneider, J. Herman, and T. Pavelsky. (2022). Bias Correction of Hydrologic Projections Strongly Impacts Inferred Climate Vulnerabilities in Institutionally Complex Water Systems. Journal of Water Resources Planning and Management, 148 (1).
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
K. Wang, D. Davis, and Scott Steinschneider. (2021). Evaluating suspended sediment and turbidity reduction projects in a glacially conditioned catchment through dynamic regression and fluvial process-based modelling. Hydrological Processes, 35( 9), e14351.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
M. Rezagholizadeh, C.-Y. Cynthia Lin Lawell, and K. Yavari. (2022). An analysis of the conditional relationship between risk and return in the Tehran Stock Exchange. Iranian Economic Review, 26 (1), 79-107.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
E. Carter, D.A. Herrera, and Scott Steinschneider. (2021). Feature Engineering for Subseasonal-to-Seasonal Warm-Season Precipitation Forecasts in the Midwestern United States: Toward a Unifying Hypothesis of Anomalous Warm-Season Hydroclimatic Circulation. Journal of Climate, 34 (20), 8291-8318.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
S.S. Borkotoky, A.P. Williams, E.R. Cook, and Scott Steinschneider. (2021). Reconstructing extreme precipitation in the Sacramento River Watershed using tree-ring based proxies of cold-season precipitation. Water Resources Research, 57, e2020WR028824.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Scott Steinschneider. (2021). A hierarchical Bayesian model of storm surge and total water levels across the Great Lakes shoreline - Lake Ontario. Journal of Great Lakes Research, 47 (3), 829-843.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
K. Wang, R.K. Gelda, R. Mukundan, and Scott Steinschneider. (2021). Inter-model Comparison of Turbidity-Discharge Rating Curves and the Implications for Reservoir Operations Management. Journal of the American Water Resources Association 57 (3), 430-448.
|
Progress 09/01/20 to 08/31/21
Outputs
Target Audience:Although the current reporting period (Year 2) was only the second year of our 3-year project, and despite the challenges associated with the ongoing pandemic, our efforts have already reached multiple target audiences during the current reporting period. During the current reporting period (Year 2), we participated in 8 Stakeholder meetings, each averaging 25 participants and led by a non-governmental group (the American Farmland Trust). Major topics of discussion included the following. (1) New York (NY) State laws and regulations for solar and wind development including the NY Office of Renewable Energy siting proposal and the Public Service CommissionHost Community Benefit Proposal. (2) Local land use regulations including Payments in Lieu of Taxes (PILOT) to encourage siting of renewables on land that is less valuable for agriculture. (3) Dual use of land for both agriculture and photovoltaics, including sheep grazing, which is occurring on many solar farms in New York State. This stakeholder input will contribute to Objective 3 of our project. In April 2021, we visited a local dairy farmer to get his perspectives on how solar farming might hinder their nutrient management. In July 2021, we participated in a site tour and shared information with Cornell Cooperative Extension educators at a solar facility that has a Cornell led research project to evaluate co-locating grazing sheep with solar panels. During the current reporting period, our research has had a beneficial educational impact on the doctoral students and postdoctoral researchers who are providing research assistance in all project phases in both disciplinary and transdisciplinary research, including gathering and analyzing data; developing, estimating, and running the models; writing papers; and presenting at meetings and conferences. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?During the current reporting period (Year 2), our project has provided a beneficial educational impact on and opportunities for training and professional development to the doctoral students and postdoctoral researchers who are providing research assistance in all project phases in both disciplinary and transdisciplinary research, including gathering and analyzing data; developing, estimating, and running the models; writing papers; and presenting at meetings and conferences. How have the results been disseminated to communities of interest? Although the current reporting period was only the second year of our 3-year project, and despite the challenges associated with the ongoing pandemic, we have already disseminated our research to multiple communities of interest during the current reporting period. During the current reporting period, we presented our research at an invited statewide webinar presentation on Community & Regional Impacts of Solar during the Ag & Solar Summit 2021. The event gave extension educators an opportunity to learn all about new large-scale solar developments, which bring both opportunities and concerns to farmers and others across the state; and provided them with the basic knowledge they need to help the various community stakeholders they work with, as well as the tools to know where to turn for additional information or resources. Our 1-hour webinar presentation was attended by 60 participants, and was also recorded and published online. We participated in 8 Stakeholder meetings during the current reporting period, each averaging 25 participants and led by a non-governmental group (the American Farmland Trust). Major topics of discussion included the following. (1) New York State laws and regulations for solar and wind development including the NY Office of Renewable Energy siting proposal and the Public Service CommissionHost Community Benefit Proposal. (2) Local land use regulations including Payments in Lieu of Taxes (PILOT) to encourage siting of renewables on land that is less valuable for agriculture. (3) Dual use of land for both agriculture and photovoltaics, including sheep grazing, which is occurring on many solar farms in New York State. This stakeholder input will contribute to Objective 3 of our project. We have also delivered science-based knowledge to multiple target audiences and stakeholders during the current reporting period. For example, in April 2021, we visited a local dairy farmer to get his perspectives on how solar farming might hinder their nutrient management. In July 2021, we participated in a site tour and shared information with Cornell Cooperative Extension educators at a solar facility that has a Cornell led research project to evaluate co-locating grazing sheep with solar panels. What do you plan to do during the next reporting period to accomplish the goals?During the next reporting period of our 3-year project, in order to accomplish the goals, we plan to continue working on Objectives 1, 2, and 3. During the next reporting period (Year 3), as part of Objective 1, we plan to use the detailed, comprehensive spatial geo-coded data set we have collected, compiled, and constructed in Year 2 on agriculture and energy in all of New York State to create a detailed, comprehensive spatial geo-coded field level panel data set on land use, crop choice, wind installations, and solar installations in all of New York State. To do so, we plan to merge our detailed, comprehensive spatial geo-coded data set of agriculture and energy for all of New York State (NY) with our parcel boundary data. We will merge the farm boundaries with the geo-coded wind turbine and solar installation location data to determine which farms have converted to solar and when, and when. We will then use our detailed, comprehensive spatial geo-coded field level panel data set on land use, crop choice, wind installations, and solar installations in all of New York State to continue to develop a modeling framework to understand how renewable energy infrastructure investments on rural private lands will alter the food-energy-water system throughout NY, and to continue to work on addressing Q1.1 to Q1.10. As part of Objectives 1 and 2, during the next reporting period we will complete a modeling exercise to assess the hydrological and water quality impacts of several ag-to-energy scenarios. We will initiate combining these modeling analysis with economic and power system dimensions of this project, which we anticipate fully developing over the next 24 months. We will also complete our field-based analysis of hydrological impacts of a solar farm. As part of Objectives 2 and 3, during the next reporting period we intend to complete our risk assessment of multivariate energy droughts for a fully renewable NYS power system. The ultimate goal of this work will be to identify the intensity-duration-frequency behavior of power deficits within the system, .i.e., to determine the frequency with which power deficits of varying intensities (as a percent of demand) occur for different durations of time. We will be testing the hypothesis that long-duration (multi-month) power deficits of concerning magnitudes (e.g., 10% of demand) are both possible and relatively frequent (e.g., once every 10 years) due to co-variability between long-memory aspects of Great Lakes water supply and hydropower and other renewables within NYS. In addition, we intend to link our energy balance model with simulations of renewable energy infrastructure on rural lands. In particular, we will reconfigure the location of wind turbines and solar farms within the energy balance model to match the spatial distribution simulated by the land use / land market model. This will enable us to explore how land market controls over the placement of renewables influence the reliability of a fully renewable NYS power system. Building on the baseline model of the NY power grid, as part of Objectives 2 and 3, we intend to develop a stochastic scenario generator for renewable resources that captures the spatial-temporal correlations. The NY power grid currently has less than 2,000MW of wind and solar capacities but plans to integrate 15,000 MW more in the next two decades. The goal of the stochastic scenario generator is to provide realistic alternative scenarios for such high penetration level of wind and solar resources and further assist the power grid expansion and operation under increasing uncertainties. With a better model to capture the uncertainties, we intend to further investigate how converting agriculture farms to solar farms would impact the dynamic of the electricity markets. We collected data for solar farms that are already in operation or will be in operation shortly with Latitude-longitude coordinates, capacity, (targeted) operational data and annual capacity factor (if available). The data will be coupled with the baseline model to explore the dynamic of the marginal profits of the converting process and the reliability of the future NYS power grid with a tremendous amount of intermittent renewable energies. As part of Objectives 1, 2, and 3, during the next reporting period we will continue to develop our innovative FEW system modeling framework to investigate how ag-to-energy land use transitions will propagate through the dynamics of land markets, and how such transitions will generate feed-forward and feed-back effects on agricultural production, water quality and quantity, and electrical grid operational efficiency, under impacts from climate and other exogenous factors. In addition to the many notable Year 2 accomplishments we described above, we also have several publications during the current reporting period (Year 2). As it has been less than 9 months since NIFA released the Year 2 and Year 3 funds for our project to us in December 2020 for our expenditure, and as it has been less than 18 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, many of the publications for our research during the current reporting period (Year 2) proceeded without NIFA support. During the next reporting period (Year 3), as we continue working on Objectives 1, 2, and 3, we plan to publish more publications and products that result from and acknowledge NIFA support.
Impacts
What was accomplished under these goals?
Agriculture-to-energy land-use conversions -- putting solar panels or wind turbines on arable farmland -- have the potential to impact food production, energy prices, water quality, and resilience to changes in climate. To understand how the food-energy-water system is being transformed through ag-to-energy land conversions, as well as the potential implications, we are developing a novel econometric model of land use dynamics, loosely coupled with landscape-scale, process-level models of agricultural, water, and energy systems. We are applying the modeling framework to New York State, an ideal test-bed due to the state's incentives to achieve 70% renewable electricity by 2030; a water system that is largely self-contained within state boundaries; and a thriving agricultural sector at higher risk in recent years due to climate impacts. The results of this work will provide a scientific basis to improve national, state, and regional policy decisions related to land use, agriculture, renewable energy, and energy prices over time and space to promote FEW system sustainability and resilience and maximize net benefits to society. Although the current reporting period (Year 2) was only the second year of our 3-year project, although it has been less than 9 months since NIFA released the Year 2 and Year 3 funds for our project to us in December 2020 for our expenditure, although it has been less than 18 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, and despite the challenges associated with the ongoing pandemic, we have made many notable accomplishments under these goals during the reporting period. During the current reporting period (Year 2), as part of Objective 1, we have collected, compiled, and constructed a detailed, comprehensive spatial geo-coded data set of agriculture and energy for all of New York State (NY) that we will use to develop a model framework to understand how renewable energy infrastructure investments on rural private lands will alter the food-energy-water system throughout NY. We have also collected geospatial farm parcel boundary data for all states in New York from the Farm Services Administration (FSA) from 2007. The data are called "common land units". Newer data are not available because legislation in 2008 prevented FSA from sharing the data. We are currently working on merging our detailed, comprehensive spatial geo-coded data set of agriculture and energy for all of New York State (NY) with our parcel boundary data; and on developing and refining our model framework for understanding how renewable energy infrastructure investments on rural private lands will alter the food-energy-water system throughout NY. Also as part of Objective 1, during the current reporting period we have developed an energy balance model of the New York State power systems network. This model represents the system as an 11-node network, with each node representing a load zone, and is designed to explore the risk of multivariate energy droughts, i.e., the likelihood that multiple renewable resources are in deficit for a sufficient duration to stress the ability of the system to meet demand. The model has 57 buses in total, where 46 buses represent the 11 load zones in NY and 11 buses indicate the connecting proxies with neighboring power grids -- PJM, NE-ISO and Ontario. Load and generation sources are allocated to each bus based on the NYISO Gold Book - Load and Capacity Data (2019). The model is formulated as a linear program and models how a fully renewable power system composed of hydro, wind, and solar power could be used in conjunction with batteries, imports, and enhanced transfer capacity to balance load across the entire state. Multiple scenarios of load and renewable capacity have been parameterized into the model to reflect different planning assumptions for NY, all of which are based on the NY Independent System Operator (NYISO) Congestion Assessment and Resource Integration Study (CARIS) and follow-on NYISO reports. Within the model, wind capacity is placed throughout NYS at sampled locations from the NREL Wind Took Kit, where locations were sampled based on the spatial distribution of wind resource potential. Similarly, solar power capacity is placed at locations within the NREL Solar Integration National Dataset. Load is modeled as a function of temperature using neural networks for each of the 11 zones and based on historical load data from NYISO. We complied hourly generation profiles for 227 traditional generating sources from the Regional Greenhouse Gas Initiative (RGGI) and estimated the individual generation profiles for existing renewable generation sources based on the aggregated hourly data from NYISO of 2019. Major interface power flows are compared with historical records to validate the fidelity of our model. The baseline model not only has high feasibility for all test conditions but also demonstrates promising simulation accuracy of approximately 90% of typical hours in 2019. To further assist market operation and investment, cost curves are fitted for different types of generators with fluctuating fuel prices. Assuming the generators are bidding honestly in the market, a DC optimal power flow problem is solved to compare the simulated Locational Marginal Price (LMP) for each load zone with historical LMP. The energy balance model runs at an hourly time step and is computationally efficient, which enables ensemble simulations under a variety of climate scenarios to explore system risk, which is a core task under Objective 2. Hourly series of wind speeds, solar radiation, and temperatures across NY are synthetically generated using nonparametric methods that rely on techniques developed in the stochastic weather generator reported for this project in the Year 1 annual report. The energy budget model is then simulated under this large ensemble to identify the frequency of energy deficits of different durations. We are currently working to finish this large ensemble of simulations and to identify the types of climate scenarios that lead to greatest stress on the power system. As Objectives 1 and 2 require understanding how ag-to-energy transitions will alter underpinning regional hydrology and associated water quality implications, during the current reporting period we have been focused the water component of our research on developing regional Soil and Water Assessment Tool (SWAT) models for assessing watershed-scale and, collectively, regional-scale impacts of ag-to-energy transitions on water quality and runoff hazards in NY. We have finished calibrating the SWAT model to several central NY watersheds. We will be using this model to explore potential water quality and flooding impacts of different ag-the-to energy manifestations. We are also finishing the hydrological analysis of a local solar farm, which should be published later this year. As part of Objectives 1-3, during the reporting period we have been reviewing State mandated goals, state and local policies, and current patterns of solar and wind development in order to develop scenarios of how much land of different land cover types may be required by 2030 and 2050. Since solar farms require large amounts of land and often replace agricultural and forest production, and compete with other mitigation options such as afforestation and bioenergy feedstock production, we are analyzing how these land use changes affect the GHG benefits of solar farms when placed on idle former agricultural land, current agricultural land, or current forest land in New York State. We are developing scenarios of the amount of land that could be required for afforestation and bioenergy feedstock production GHG mitigation opportunities, as well as analyzing the GHG benefits compared to solar energy development.
Publications
- Type:
Other
Status:
Published
Year Published:
2021
Citation:
Peter B. Woodbury. (2021). Community & Regional Impacts of Solar . Invited statewide webinar presentation in Ag & Solar Summit 2021. Cornell Cooperative Extension, Cornell University. 4-5 May 2021.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Ariel Ortiz-Bobea. (2020). The Role of Nonfarm Influences in Ricardian Estimates of Climate Change Impacts on US Agriculture. American Journal of Agricultural Economics, 102 (3), 934-959.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
G.E. Lade and C.-Y. Cynthia Lin Lawell. (2021). The design of renewable fuel mandates and cost containment mechanisms. Environmental and Resource Economics, 79, 213-247.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
K. Doering, L. Sendelbach, Scott Steinschneider, and C. Lindsay Anderson. (2021). The effects of wind generation and other market determinants on price spikes. Applied Energy, 300, 117316.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
G. Guo, L. Zephyr, J. Morillo, Z. Wang, and C. Lindsay Anderson. (2021). Chance Constrained Unit Commitment Approximation under Stochastic Wind Energy. Computers & Operations Research, 105398.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Z. Wang and C. Lindsay Anderson. (2021). A Progressive Period Optimal Power Flow for Systems with High Penetration of Variable Renewable Energy Sources. Energies, 14 (10), 2815.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
A. Golla, R.J. Meinke, M. Liu, P. Staudt, C. Lindsay Anderson, and C. Weinhardt. (2021). Direct Policy Search for Multiobjective Optimization of the Sizing and Operation of Citizen Energy Communities. In Proceedings of the Hawaii International Conference on System Sciences (pp. 1-10).
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
S.V. Nagpal, M.V. Liu, and C. Lindsay Anderson. (2021). A comparison of deterministic refinement techniques for wind farm layout optimization. Renewable Energy, 168, 581-592.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
M. Liu, P. Reed, and C. Lindsay Anderson. (2021) Stochastic Synthetic Data Generation for Electric Net Load and Its Application. In Proceedings of the Hawaii International Conference on System Sciences.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
C.R. Galantino, S. Beyers, C. Lindsay Anderson, and J.W. Tester. (2020). Optimizing Cornells future geothermal district heating performance through systems engineering and simulation. Energy and Buildings, 110529.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
J.L. Morillo, L. Z�phyr, J.F. P�rez, C. Lindsay Anderson, and � Cadena. (2020). Risk-averse stochastic dual dynamic programming approach for the operation of a hydro-dominated power system in the presence of wind uncertainty. International Journal of Electrical Power & Energy Systems, 115, 105469.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
A. Gupta, M. Liu, D. Gold, P. Reed, and C. Lindsay Anderson. (2020). Exploring a Direct Policy Search Framework for Multiobjective Optimization of a Microgrid Energy Management System. In Proceedings of the 53rd Hawaii International Conference on System Sciences.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
J. Addoum, D. Ng, and Ariel Ortiz-Bobea. (2020). Temperature Shocks and Establishment Sales. Review of Financial Studies, 33 (3), 1331-1366.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
E. Bertone Oehninger and C.-Y. Cynthia Lin Lawell. (2021). Property rights and groundwater management in the High Plains Aquifer. Resource and Energy Economics, 63, 101147.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
S. Si, M. Lyu, C.-Y. Cynthia Lin Lawell, and S. Chen. (2021). The effects of environmental policies in China on GDP, output, and profits. Energy Economics, 94, 105082.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2021
Citation:
K. Wang, W. Davis, and Scott Steinschneider. (2021). Evaluating suspended sediment and turbidity reduction projects in a glacially-conditioned catchment through dynamic regression and fluvial process-based modeling. Hydrological Processes, accepted.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2021
Citation:
E. Carter, D.A. Herrera, and Scott Steinschneider. (2021). Feature engineering for subseasonal to seasonal warm-season precipitation forecasts in the Midwestern US: towards a unifying hypothesis of anomalous warm-season hydroclimatic circulation. Journal of Climate, accepted.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Z.P. Brodeur and Scott Steinschneider. (2021). A multivariate approach to generate synthetic short-to-medium range hydro-meteorological forecasts across locations, variables, and lead times. Water Resources Research, 57, e2020WR029453.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2021
Citation:
S. Borkotoky, A.P. Williams, E.R. Cook, and Scott Steinschneider. (2021). Reconstructing extreme precipitation in the Sacramento River Watershed using tree-ring based proxies of cold-season precipitation. Water Resources Research, accepted.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2021
Citation:
Scott Steinschneider. (2021). A hierarchical Bayesian model of storm surge and total water levels across the Great Lakes shoreline - Lake Ontario. Journal of Great Lakes Research, accepted.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2021
Citation:
K. Wang, R. Gelda, R. Mukundan, and S. Steinschneider. (2021). Inter-model Comparison of Turbidity-Discharge Rating Curves and the Implications for Reservoir Operations Management. Journal of the American Water Resources Association, accepted.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
K. Doering, J. Quinn, P.M. Reed, and Scott Steinschneider. (2021). Diagnosing the time-varying value of forecasts in multi-objective reservoir control. Journal of Water Resources Planning and Management, 147 (7).
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
N. Najibi, S. Mukhopadhyay, and Scott Steinschneider. (2020). Identifying weather regimes for regional-scale stochastic weather generators. International Journal of Climatology, 1-24.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
K. Semmendinger, J. Foley, and Scott Steinschneider. (2020). A Probabilistic, Parcel-Level Inundation Prediction Tool for Medium-Range Flood Forecasting in Large Lake Systems. Journal of the American Water Resources Association, 1-18.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
M. McRae, R.A. Lee, Scott Steinschneider, and F. Galgano. (2020). Assessing Aircraft Performance in a Warming Climate. Weather, Climate, and Society, 13 (1), 39-55.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
J.D. Quinn, A. Hadjimichael, P.M. Reed, and Scott Steinschneider. (2020). Can exploratory modeling of water scarcity vulnerabilities and robustness be scenario neutral?. Earths Future, 8, e2020EF001650.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Z. Brodeur, J. Herman, and Scott Steinschneider. (2020). Bootstrap aggregation and cross-validation methods to reduce overfitting in reservoir control policy search. Water Resources Research, 56, e2020WR027184.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Z. Brodeur, and Scott Steinschneider. (2020). Spatial bias in medium-range forecasts of heavy precipitation in the Sacramento River basin: Implications for water management. Journal of Hydrometeorology, 21 (7), 1405-1423.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
X. Peng, Scott Steinschneider, and J. Albertson. (2020). Investigating Long-Range Seasonal Predictability of East African Short Rains: Influence of the Mascarene High on Indian Ocean Walker Cell, Journal of Applied Meteorology and Climatology, 59 (6), 1077-1090.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
W. Pluer, M. Todd Walter, and Scott Steinschneider. (2020). Understanding complex flow pathways within lab-scale denitrifying bioreactors with a conservative tracer, Transactions of the ASABE, 63 (2), 417-427.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
J.D. Herman, J.D. Quinn, Scott Steinschneider, M. Giuliani, and S. Fletcher, S. (2020). Climate adaptation as a control problem: Review and perspectives on dynamic water resources planning under uncertainty. Water Resources Research, 56, e24389.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
G. Bulltail and M. Todd Walter. (2020). Impacts of coal resource development on surface water quality in a multi?jurisdictional watershed in the western United States. Journal of Contemporary Water Research & Education, 169 (1), 79-91.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
C.B. Georgakakos, B.J. Hicks, and M. Todd Walter. (2021). Farmer perceptions of dairy farm antibiotic use and transport pathways as determinants of contaminant loads to the environment. Journal of Environmental Management, 281, 111880.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
C.B. Georgakakos, B.J. Hicks, and M. Todd Walter. (2021). Dairy farmer perceptions of antibiotic transport and usage in animal agriculture dataset. Data in Brief, 106785.
- Type:
Other
Status:
Published
Year Published:
2021
Citation:
C.B. Georgakakos, B.J. Hicks, and M. Todd Walter. (2021). Dairy farmer perceptions of antibiotic transport and use interview dataset. Mendeley Data, V2.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2021
Citation:
C.B. Georgakakos, J.F. Cerra, S. Allred, K. Williams, M. Todd Walter, E. LoGiudice, and G. Smith. (2021). Cross-disciplinary learning in environmental engineering and landscape architecture. International Journal of Collaborative Engineering, accepted.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
J.O. Knighton, K. Sing, V. Souter-Kline, M. Todd Walter. (2020). Hammond Hill Research Catchment: Supporting Hydrologic Investigations of Rooting Zone and Vegetation Water Dynamics under Climate Change. Hydrological Processes Special Issue, 34 (24), 4755-4758.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
M.S. Lisboa, R.L. Schneider, P. Sullivan, and M. Todd Walter. (2020). Drought and post-drought rain effect on stream nutrient losses in the Northeastern USA. Journal of Hydrology Regional Studies, 28, 100672.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
O. Pietz M. Augenstein, C.B. Georgakakos, K. Singha, M. McDonald, and M. Todd Walter. (2021). Macroplastic accumulation in roadside ditches of New York States Finger Lakes region (USA) across land uses and the COVID-19 pandemic. Journal of Environmental Management, 298.
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
E.M. Pluer, R.L. Schneider, W. Pluer, S.J. Morreale, and M. Todd Walter. (2021). Returning degraded soils to productivity: Water and nitrogen cycling in degraded soils amended with coarse woody material. Ecological Engineering, 157.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
E.M. Pluer, R.L. Schneider, S.J. Morreale, M.A. Liebig, J. Li, C.X. Li, and M. Todd Walter. (2020). Returning degraded soils to productivity: An examination of the potential of coarse woody amendments for improved water retention and nutrient holding capacity. Water, Air, & Soil Pollution, 231, 15.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
W. Pluer, M. Todd Walter, and Scott Steinschneider. (2020). Understanding complex flow pathways within lab-scale denitrifying bioreactors with a conservative tracer. Transactions of ASABE, 63 (2), 417-427
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
D. Rosero-L�pez, M. Todd Walter, B. De Bi�vre, D. Gonz�lez-Zeas, A.S. Flecker, D.F. Ontaneda, and O. Dangles. (2021). Standardization of instantaneous fluoroprobe measurements of benthic algal biomass and composition in streams. Ecological Indicators, 121, 107185.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
D. Rosero-L�pez, E.A. Cowen, M. Todd Walter, A.S. Flecker, R. Osorio, and O. Dangles. (2020). Design of a paired-weir system for experimental manipulation of environmental flows in streams. Journal of Ecohydraulics.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2021
Citation:
S.M. Saia, H.J. Carrick, A.R. Buda, J.M. Regan, and M. Todd Walter. (2021). A critical review of polyphosphate and polyphosphate accumulating organisms for agricultural water quality management. Environmental Science & Technology, accepted.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
K. Singh, J.O. Knighton, M. Whitmore, M. Todd Walter, and J.P. Lassoie. (2020). Simulation and statistical modelling approaches to investigate hydrologic regime transformations following Eastern Hemlock decline. Hydrological Processes, 34 (5), 1198-1212.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
A.M. Truhlar, R.D. Marjerison, D.F. Gold, L.M. Watkins, J.A. Archibald, M.E. Lung, A. Meyer, and M. Todd Walter. (2020). Rapid, remote assessment of culvert flooding risk. ASCE Journal of Sustainable Water in the Built Environment, 6 (2).
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Progress 09/01/19 to 08/31/20
Outputs
Target Audience:Although the current reporting period (Year 1) was only the first year of our 3-year project, our efforts have already reached multiple target audiences during the current reporting period. During the current reporting period (Year 1), we presented our research at the New York State Energy Research and Development Authority (NYSERDA) Clean Energy for Agriculture Task Force Meeting. The audience at the meeting included the New York State Energy Research and Development Authority, the New York State Department of Agriculture and Markets, the New York State Department of Environmental Conservation, the New York State Department of Public Service, the New York (NY) Farm Bureau, American Farmland Trust, National Grid, and Cornell University Extension partners. We are continuing to engage, interact, discuss, and disseminate our research to the multiple target audiences, stakeholders, networks, and contacts we met at this meeting. During the current reporting period, we participated in meetings with the American Farmland Trust on greenhouse gas mitigation on NY farms. We attended the American Farmland Trust conference on "Combatting Climate Change: Solar Energy, Farming and the Future in New York", where we met with state and local leaders from New York and Massachusetts, farmers, renewable energy developers, researchers, and practitioners in the field to discuss smart solar siting on farmland, how farmers can be a critical part of the solution to climate change, and the opportunities and challenges of collocating solar energy generation with farming in New York State, or agrivoltaics as it is often called. We have also delivered science-based knowledge to multiple target audiences and stakeholders during the current reporting period. For example, during the current reporting period, we disseminated our research to a farmer who is opposed to a solar development on prime agricultural land that they rent, and who had contacted us looking for help quantifying greenhouse gas benefits or disbenefits of replacing ag with solar. During the current reporting period, we disseminated our research to multiple target audiences, and our project was featured and discussed in multiple media outlets and organizations, including the Cornell Chronicle, the American Association for the Advancement of Science (AAAS), and Food & Drink International. During the current reporting period, our research has had a beneficial educational impact on the doctoral students and postdoctoral researchers who are providing research assistance in all project phases in both disciplinary and transdisciplinary research, including gathering and analyzing data; developing, estimating, and running the models; writing papers; and presenting at meetings and conferences. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?During the current reporting period, our project has provided a beneficial educational impact on and opportunities for training and professional development to the doctoral students and postdoctoral researchers who are providing research assistance in all project phases in both disciplinary and transdisciplinary research, including gathering and analyzing data; developing, estimating, and running the models; writing papers; and presenting at meetings and conferences. How have the results been disseminated to communities of interest?Although the current reporting period was only the first year of our 3-year project, we have already disseminated our research to multiple communities of interest during the current reporting period. During the current reporting period, we presented our research at the New York State Energy Research and Development Authority (NYSERDA) Clean Energy for Agriculture Task Force Meeting. The audience at the meeting included the New York State Energy Research and Development Authority, the New York State Department of Agriculture and Markets, the New York State Department of Environmental Conservation, the New York State Department of Public Service, the NY Farm Bureau, American Farmland Trust, National Grid, and Cornell University Extension partners. We are continuing to engage, interact, discuss, and disseminate our research to the multiple target audiences, stakeholders, networks, and contacts we met at this meeting. During the current reporting period, we participated in meetings with the American Farmland Trust on greenhouse gas mitigation on NY farms. We attended the American Farmland Trust conference on "Combatting Climate Change: Solar Energy, Farming and the Future in New York", where we met with state and local leaders from New York and Massachusetts, farmers, renewable energy developers, researchers, and practitioners in the field to discuss smart solar siting on farmland, how farmers can be a critical part of the solution to climate change, and the opportunities and challenges of collocating solar energy generation with farming in New York State, or agrivoltaics as it is often called. We have also delivered science-based knowledge to multiple target audiences and stakeholders during the current reporting period. For example, during the current reporting period, we disseminated our research to a farmer who is opposed to a solar development on prime agricultural land that they rent, and who had contacted us looking for help quantifying greenhouse gas benefits or disbenefits of replacing ag with solar. During the current reporting period, we disseminated our research to multiple target audiences, and our project was featured and discussed in multiple media outlets and organizations, including the Cornell Chronicle, the American Association for the Advancement of Science (AAAS), and Food & Drink International. What do you plan to do during the next reporting period to accomplish the goals? During the next reporting period (Year 2) of our 3-year project, in order to accomplish the goals, we plan to continue working on Objectives 1 and 2, and to begin working on Objective 3. During the next reporting period (Year 2), as part of Objective 1, we plan to use the detailed, comprehensive spatial geo-coded data set we have collected, compiled, and constructed in Year 1 on agriculture and energy in all of New York State to create a detailed, comprehensive spatial geo-coded field level panel data set on land use, crop choice, wind installations, and solar installations in all of New York State. To do so, we plan to refine and validate our algorithm for approximating the farm boundaries by comparing our approximations of the farm boundaries with the actual parcel boundaries for the 22 counties with both parcel centroids and parcel boundaries. After refining and validating our algorithm for approximating the farm boundaries, we plan to superimpose the publicly available tax parcel data available online from the New York State Department of Tax and Finance's Office of Real Property Tax Services (ORPTS) on the USDA NASS Cropland Data Layer data to delineate farms and farm boundaries, enabling us to include all farms in New York in our field-level panel data set and econometric estimation, including farms that have converted to wind or solar, as well as farms that have not converted. We will then merge the farm boundaries with the geo-coded wind turbine and solar installation location data to determine which farms have converted, and when. We will then use our detailed, comprehensive spatial geo-coded field level panel data set on land use, crop choice, wind installations, and solar installations in all of New York State to continue to develop a modeling framework to understand how renewable energy infrastructure investments on rural private lands will alter the food-energy-water system throughout NY, and to continue to work on addressing Q1.1 to Q1.10. As part of Objective 2, the results from our Year 1 effort suggest that the stochastic weather generator is a suitable tool for the creation of climate scenarios across the state. Nevertheless, additional work is needed to improve inter-annual variance in the model. One strategy we will pursue during the next reporting period (Year 2) includes a more sophisticated model of the weather regimes themselves. That is, instead of our current approach (a first-order Markov chain with seasonal harmonics), we will explore the use of Markov-switching autoregressive models that may better capture persistence characteristics on seasonal time scales. In addition, our initial Year 1 analysis suggests that a standard Clausius-Clapeyron (C-C) scaling rate is appropriate for use across the state. During the next reporting period (Year 2), we will examine whether climate projections over New York also indicate a standard C-C scaling rate. In addition, we will examine projected changes to the frequency of weather regimes. These changes will then be parameterized into the weather generator in order to produce simulations of future NY climate that can be used to drive the resiliency assessment of the NY FEW system. Also as part of Objective 2, during the next reporting period (Year 2) we will begin to estimate functional relationships between FEW system components and climate. Specifically, we will develop a multi-level Bayesian model for electricity demand conditional on climate, developed using hourly load data from 2001 to present that are available for load centers from the New York Independent System Operator (NYISO). We expect climate variables like maximum and minimum daily temperatures, relative humidity, and cooling and heating degree-days to impact demand for electricity for heating and cooling. During the next reporting period (Year 2), we will continue to develop our innovative FEW system modeling framework to investigate how ag-to-energy land use transitions will propagate through the dynamics of land markets, and how such transitions will generate feed-forward and feed-back effects on agricultural production, water quality and quantity, and electrical grid operational efficiency, under impacts from climate and other exogenous factors. In addition to the many notable Year 1 accomplishments we described above, we also have several publications during the current reporting period (Year 1). As it has been less than 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, most of the publications for our research during the current reporting period (Year 1) proceeded without NIFA support. During the next reporting period (Year 2), as we continue working on Objectives 1 and 2, and begin working on Objective 3, we plan to publish more publications and products that result from and acknowledge NIFA support.
Impacts
What was accomplished under these goals?
Agriculture-to-energy land-use conversions -- putting solar panels or wind turbines on arable farmland -- have the potential to impact food production, energy prices, water quality, and resilience to changes in climate. To understand how the food-energy-water system is being transformed through ag-to-energy land conversions, as well as the potential implications, we are developing a novel econometric model of land use dynamics, loosely coupled with landscape-scale, process-level models of agricultural, water, and energy systems. We are applying the modeling framework to New York State, an ideal test-bed due to the state's incentives to achieve 50% renewable electricity by 2030; a water system that is largely self-contained within state boundaries; and a thriving agricultural sector at higher risk in recent years due to climate impacts. The results of this work will provide a scientific basis to improve national, state, and regional policy decisions related to land use, agriculture, renewable energy, and energy prices over time and space to promote FEW system sustainability and resilience and maximize net benefits to society. Although the current reporting period (Year 1) was only the first year of our 3-year project, and although it has been less than 6 months since NIFA released the Year 1 funds for our project to us in March 2020 for our expenditure, we have made many notable accomplishments under these goals during the reporting period, particularly for Objectives 1 and 2. During the current reporting period (Year 1), as part of Objective 1, we have collected, compiled, and constructed a detailed, comprehensive spatial geo-coded data set of agriculture and energy for all of New York State (NY) that we will use to develop a model framework to understand how renewable energy infrastructure investments on rural private lands will alter the food-energy-water system throughout NY. We have collected, compiled, and constructed a detailed, comprehensive spatial geo-coded data set of all the wind turbines in NY that became operational and began providing power at some point over the years from 2000 to the first quarter of 2020. Our data set includes 1,142 wind turbines that became operational and began providing power at some point over the years from 2000 to the first quarter of 2020 from the U.S. Wind Turbine Database; and 22 large-scale wind projects reported by the New York State Energy Research and Development Authority (NYSERDA), some of which are under development. The total capacity under development is 1708.48 MW, and the total installed capacity is 2446.94 MW. We have similarly collected, compiled, and constructed a detailed, comprehensive spatial geo-coded data set on all solar installations in NY. Our data set includes 106,758 solar electric projects either completed or in the pipeline (not yet installed) in the Incentive Program from December 2000 to July 2020, as reported by NYSERDA; 406 solar Distributed Energy Resources facilities installed in NY, many of which received State incentives and report performance data to NYSERDA; and 53 large-scale solar projects reported by NYSERDA, including projects that are under development. The total completed solar generation capacity is 2403.34 MW. For agriculture, we have collected, compiled, and constructed a detailed, comprehensive spatial geo-coded data set on land use and crop choice using the Cropland Data Layer (CDL) from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS), which is a raster, geo-referenced, crop-specific land cover data layer created annually for the United States using moderate resolution satellite imagery and agricultural survey data. We have also collected publicly available tax parcel data available online from the New York State Department of Tax and Finance's Office of Real Property Tax Services (ORPTS), and have been superimposing this on the USDA NASS Cropland Data Layer data to delineate farms and farm boundaries. We have collected parcel centroid location data for all 62 New York State counties. We have also collected parcel boundaries for all 22 of these 62 counties for which parcel boundary data is publicly available from the ORPTS. For the parcels for which we have parcel centroid data but not parcel boundaries, we have been working on developing an algorithm to approximate the farm boundaries using the parcel centroid data, data on the distribution of farm size in NY, USDA cropland data, and the property ownership information from the ORPTS. We are currently developing and evaluating algorithms based on centroid and Voronoi techniques. We are refining and validating our algorithm for approximating the farm boundaries by comparing our approximations of the farm boundaries with the actual parcel boundaries for the 22 counties with both parcel centroids and parcel boundaries. As Objectives 1 and 2 require understanding how ag-to-energy transitions will alter underpinning regional hydrology and associated water quality implications, during the current reporting period we have been focused the water component of our research on developing regional Soil and Water Assessment Tool (SWAT) models for assessing watershed-scale and, collectively, regional-scale impacts of ag-to-energy transitions on water quality and runoff hazards in NY. As such, we have been calibrating SWAT to the Owasco Lake and Canandaigua Lake watersheds to complement our Cayuga Lake SWAT watershed modeling. These models will provide regional parameterizations, which will be extrapolated to cover the most intensively farmed parts of the state. We have also requested SWAT parameter sets from the Genesee River watershed and Skaneateles Lake watershed. We are also working on an empirical study of hydrological impacts of solar farm development on agricultural land in NY to assess how solar farms alter the spatial patterns of runoff generation and associated nutrient and sediment transport. For Objective 2, to explore the future resiliency of the NY FEW system to multi-scale climate variability and change and other uncertain system drivers, our primary focus during the current reporting period (Year 1) has been on addressing Q2.1 and Q.2.2 by simulating modes of climate variability, and by starting to inform simulations with climate change projections. In particular, we are developing a latent variable Hidden Markov Model as a unifying statistical framework to simulate high-frequency variations of precipitation, wind speeds, insolation, and temperature based on slowly varying components of the climate system. To test the proposed model for NY, we identified six basins that are distributed across the state. To evaluate the model, we examined how well simulations reproduced a wide variety of weather characteristics across each of the basins. In comparing observed versus simulated precipitation moments, along with the simulated ensemble spread, for each of the grid cells (i.e., at-site statistics), as well as for basin-average statistics, we find that, overall, many of the historical moments are well preserved in the simulations, including the at-site mean, standard deviation, and skew, as well as cross-correlations between sites. To assess model performance across all basins, we focus on five key performance statistics, including the daily mean of precipitation, average length of dry and wet spells, standard deviation of seasonal precipitation totals, and daily maxima. Results across the six basins suggests that weather generator performance across the state is adequate and relatively consistent. We also analyze the spatial variation of historic Clausius-Clapeyron (C-C) scaling rates across NY in order to better understand how storm intensity and temperature vary in the state and how this process should be modeled in simulations of future climate.
Publications
- Type:
Other
Status:
Published
Year Published:
2020
Citation:
Diane Bertok, T.C. McDonnell, T.J. Sullivan, Peter B. Woodbury, J.L. Wightman, G.M. Domke, C.M. Beier, and C. Trettin. (2020). Sources and Sinks of Major Greenhouse Gases Associated with New York States Natural and Working Lands: Forests, Farms, and Wetlands. New York State Energy and Research Development Authority (NYSERDA) Report Number 20-06.
- Type:
Other
Status:
Published
Year Published:
2020
Citation:
Jenifer L. Wightman and Peter B. Woodbury. (2020). New York Agriculture and Climate Change: Key Opportunities for Mitigation, Resilience, and Adaptation. Final Report on Carbon Farming project for the New York State Department of Agriculture and Markets.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Jenifer L. Wightman and Peter B. Woodbury. (2019). Maximizing social benefit from finite energy resource allocation. Energy, Sustainability and Society, 9, 30.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Jialin Liu, Luckny Z�phyr, and C. Lindsay Anderson. (2020). Optimal Operation of Microgrids with Load-Differentiated Demand Response and Renewable Resources. Journal of Energy Engineering 146 (4), 04020027.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Ariel Ortiz-Bobea, Haoying Wang, Carlos M. Carrillo, and Toby R. Ault. (2019). Unpacking the climatic drivers of US agricultural yields. Environmental Research Letters, 14 (6).
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
J.O. Knighton, G. Pleiss, E. Carter, S. Lyon, M. Todd Walter, and Scott Steinschneider. (2019). Potential predictability of regional precipitation and discharge extremes using synoptic-scale climate information via machine learning: An evaluation for the Eastern Continental United States. Journal of Hydrometeorology, 20 (5), 883900.
- Type:
Book Chapters
Status:
Published
Year Published:
2019
Citation:
Christine L. Carroll, Colin A. Carter, Rachael E. Goodhue, and C.-Y. Cynthia Lin Lawell. (2019). Crop disease and agricultural productivity: Evidence from a dynamic structural model of Verticillium wilt management. In Wolfram Schlenker (Ed.), Agricultural Productivity and Producer Behavior (pp. 217-249). Chicago: University of Chicago Press.
- Type:
Other
Status:
Other
Year Published:
2019
Citation:
C.-Y. Cynthia Lin Lawell. (2019). Agricultural-to-energy land use transitions: A FEW system modeling framework . New York State Energy Research and Development Authority (NYSERDA) Clean Energy for Agriculture Task Force Meeting. November 2019.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Jonathan A. Cook and C.-Y. Cynthia Lin Lawell. (2020). Wind turbine shutdowns and upgrades in Denmark: Timing decisions and the impact of government policy. Energy Journal, 41 (3), 81-118.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Louis Sears, David Lim, and C.-Y. Cynthia Lin Lawell. (2019). Spatial groundwater management: A dynamic game framework and application to California. Water Economics and Policy, 5 (1), 1850019.
- Type:
Book Chapters
Status:
Published
Year Published:
2019
Citation:
Louis Sears and C.-Y. Cynthia Lin Lawell. (2019). Water management and economics. In Gail L. Cramer, Krishna P. Paudel, and Andrew Schmitz (Eds.), The Routledge Handbook of Agricultural Economics (pp. 269-284). London: Routledge.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Haoying Wang and Ariel Ortiz-Bobea. (2019). Market-Driven Corn Monocropping in the U.S. Midwest. Agricultural and Resource Economics Review, 48 (2), 274-296.
- Type:
Journal Articles
Status:
Accepted
Year Published:
2020
Citation:
Ariel Ortiz-Bobea. (2020). The Role of Nonfarm Influences in Ricardian Estimates of Climate Change Impacts on US Agriculture. American Journal of Agricultural Economics.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Scott Steinschneider, P. Ray, S.H. Rahat, and J. Kucharski. (2019). A weather-regime based stochastic weather generator for climate vulnerability assessments of water systems in the Western United States. Water Resources Research, 55.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
S.C. Worland, Scott Steinschneider, W. Farmer, W. Asquith, and R. Knight. (2019). Copula theory as a generalized framework for flow-duration curve based streamflow estimates in ungaged and partially gaged catchments. Water Resources Research, 55.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
S. Worland, Scott Steinschneider, W. Asquith, R. Knight, and M. Wieczorek. (2019). Prediction and inference of flow-duration curves using multi-output neural networks. Water Resources Research, 5.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
J. Doss-Gollin, D.J. Farnham, Scott Steinschneider, and U. Lall. (2019). Robust Adaptation to Multi-Scale Climate Variability. Earths Future, 7.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
K.-H. Ahn and Scott Steinschneider. (2019). Seasonal predictability and change of large-scale summer precipitation patterns over the Northeast United States. Journal of Hydrometeorology, 20 (7), 12751292.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
K.-H. Ahn and Scott Steinschneider. (2019). Time-varying, nonlinear suspended sediment rating curves to characterize trends in water quality: An application to the Upper Hudson and Mohawk Rivers, New York. Hydrological Processes, 33, 18651882.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Scott Steinschneider, A. Styler, R. Stedman, and M. Austerman. (2019). A Rapid Response Survey to Characterize the Impacts of the 2017 High Water Event on Lake Ontario. Journal of the American Water Resources Association, 10651079.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Y. Ling, M. Klemes, Scott Steinschneider, W. Dichtel, and D. Helbling. (2019). QSARs to predict adsorption affinity of organic micropollutants for activated carbon and �-cyclodextrin polymer adsorbents. Water Research, 154, 217-226.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
K.-H. Ahn and Scott Steinschneider. (2019). A hierarchical Bayesian model for streamflow estimation at ungauged sites via spatial scaling in the Great Lakes basin. Journal of Water Resources Planning and Management, 145 (8).
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Y. Harada, T.H. Whitlow, J. Russell-Anelli, M. Todd Walter, N.L. Bassuk, and M.A. Rutzke. (2019). The heavy metal budget of an urban rooftop farm. Science of the Total Environment, 660, 115-125.
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