Bio


The Fletcher lab aims to advance water resources management to promote resilient and equitable responses to a changing world. Our research integrates methods from hydrology, policy analysis, and data science to inform decision-making around critical environmental challenges. Our approach centers partnership for real-world impact.

Academic Appointments


Honors & Awards


  • Best Policy Oriented Paper, Journal of Water Resources Planning and Management (2024)
  • CAREER Award, National Science Foundation (2024)
  • Inspiring Early Academic Career Award, Stanford Faculty Women’s Forum (2024)
  • Young Investigator Lecture, Caltech Resnick Sustainability Institute (2023)
  • Editor’s Choice Paper, Journal of Water Resources Planning and Management (2022)
  • 1st Place Doctoral Thesis, Academic Achievement Award, American Water Works Association (2019)
  • Editor’s Choice Paper, Journal of Water Resources Planning and Management (2018)
  • Best Presentation, Technology Management and Policy Consortium (2017)
  • Outstanding Student Paper Award, AGU (2017)
  • Outstanding Student Paper Award, AGU (2016)
  • Graduate Research Fellowship, National Science Foundation (2015)
  • Best Thesis, MIT Technology and Policy Program (2012)

Professional Education


  • BA, University of Pennsylvania, Physics; Economics (2010)
  • MS, Massachusetts Institute of Technology, Technology and Policy (2012)
  • PhD, Massachusetts Institute of Technology, Engineering Systems (2018)

Current Research and Scholarly Interests


The Fletcher lab aims to advance water resources management to promote resilient and equitable responses to a changing world. We study water resources and climate change adaptation from a socio-technical systems perspective. Our research integrates methods from hydrology, policy analysis, and data science to inform decision-making around critical environmental challenges.

Stanford Advisees


All Publications


  • Alternative household water affordability metrics using water bill delinquency behavior ENVIRONMENTAL RESEARCH LETTERS Skerker, J. B., Verma, A., Edwards, M., Rachunok, B., Fletcher, S. 2024; 19 (7)
  • Quantifying the Value of Technology and Policy Innovation in Water Resource Portfolios EARTHS FUTURE Zaniolo, M., Fletcher, S., Mauter, M. S. 2024; 12 (5)
  • Equity and modeling in sustainability science: Examples and opportunities throughout the process. Proceedings of the National Academy of Sciences of the United States of America Giang, A., Edwards, M. R., Fletcher, S. M., Gardner-Frolick, R., Gryba, R., Mathias, J., Venier-Cambron, C., Anderies, J. M., Berglund, E., Carley, S., Erickson, J. S., Grubert, E., Hadjimichael, A., Hill, J., Mayfield, E., Nock, D., Pikok, K. K., Saari, R. K., Samudio Lezcano, M., Siddiqi, A., Skerker, J. B., Tessum, C. W. 2024; 121 (13): e2215688121

    Abstract

    Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.

    View details for DOI 10.1073/pnas.2215688121

    View details for PubMedID 38498705

  • Valuing Combinations of Flexible Planning, Design, and Operations in Water Supply Infrastructure WATER RESOURCES RESEARCH Willebrand, K., Zaniolo, M., Skerker, J., Fletcher, S. 2024; 60 (3)
  • Bayesian Estimation of Advanced Warning Time of Precipitation Emergence EARTHS FUTURE Lickley, M., Fletcher, S. 2024; 12 (2)
  • Predicting and understanding residential water use with interpretable machine learning ENVIRONMENTAL RESEARCH LETTERS Rachunok, B., Verma, A., Fletcher, S. 2024; 19 (1)
  • Socio-hydrological impacts of rate design on water affordability during drought ENVIRONMENTAL RESEARCH LETTERS Nayak, A., Rachunok, B., Thompson, B., Fletcher, S. 2023; 18 (12)
  • Climate oscillation impacts on water supply augmentation planning. Proceedings of the National Academy of Sciences of the United States of America Fletcher, S., Zaniolo, M., Zhang, M., Lickley, M. 2023; 120 (35): e2215681120

    Abstract

    Climate oscillations ranging from years to decades drive precipitation variability in many river basins globally. As a result, many regions will require new water infrastructure investments to maintain reliable water supply. However, current adaptation approaches focus on long-term trends, preparing for average climate conditions at mid- or end-of-century. The impact of climate oscillations, which bring prolonged and variable but temporary dry periods, on water supply augmentation needs is unknown. Current approaches for theory development in nature-society systems are limited in their ability to realistically capture the impacts of climate oscillations on water supply. Here, we develop an approach to build middle-range theory on how common climate oscillations affect low-cost, reliable water supply augmentation strategies. We extract contrasting climate oscillation patterns across sub-Saharan Africa and study their impacts on a generic water supply system. Our approach integrates climate model projections, nonstationary signal processing, stochastic weather generation, and reinforcement learning-based advances in stochastic dynamic control. We find that longer climate oscillations often require greater water supply augmentation capacity but benefit more from dynamic approaches. Therefore, in settings with the adaptive capacity to revisit planning decisions frequently, longer climate oscillations do not require greater capacity. By building theory on the relationship between climate oscillations and least-cost reliable water supply augmentation, our findings can help planners target scarce resources and guide water technology and policy innovation. This approach can be used to support climate adaptation planning across large spatial scales in sectors impacted by climate variability.

    View details for DOI 10.1073/pnas.2215681120

    View details for PubMedID 37599444

  • Quantifying the Value of Learning for Flexible Water Infrastructure Planning WATER RESOURCES RESEARCH Skerker, J. B., Zaniolo, M., Willebrand, K., Lickley, M., Fletcher, S. M. 2023; 59 (6)
  • Multi-scale planning model for robust urban drought response ENVIRONMENTAL RESEARCH LETTERS Zaniolo, M., Fletcher, S., Mauter, M. S. 2023; 18 (5)
  • FIND: A Synthetic weather generator to control drought Frequency, Intensity, and Duration ENVIRONMENTAL MODELLING & SOFTWARE Zaniolo, M., Fletcher, S., Mauter, M. 2023; 172
  • Equity in Water Resources Planning: A Path Forward for Decision Support Modelers JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT Fletcher, S., Hadjimichael, A., Quinn, J., Osman, K., Giuliani, M., Gold, D., Figueroa, A., Gordon, B. 2022; 148 (7)
  • Multicriteria, Multiresolution Modeling of Suburban Residential Landscape Alternatives: Water-Efficient Villas in the Arid Middle East JOURNAL OF URBAN PLANNING AND DEVELOPMENT Birge, D., Fletcher, S., Siddiqi, A., Al Sumaiti, A., Wescoat, J. L. 2022; 148 (2)
  • Spatiotemporal monsoon characteristics and maize yields in West Africa ENVIRONMENTAL RESEARCH COMMUNICATIONS Shiu, J., Fletcher, S., Entekhabi, D. 2021; 3 (12)
  • Joint inference of CFC lifetimes and banks suggests previously unidentified emissions. Nature communications Lickley, M., Fletcher, S., Rigby, M., Solomon, S. 2021; 12 (1): 2920

    Abstract

    Chlorofluorocarbons (CFCs) are harmful ozone depleting substances and greenhouse gases. CFC production was phased-out under the Montreal Protocol, however recent studies suggest new and unexpected emissions of CFC-11. Quantifying CFC emissions requires accurate estimates of both atmospheric lifetimes and ongoing emissions from old equipment (i.e. 'banks'). In a Bayesian framework we simultaneously infer lifetimes, banks and emissions of CFC-11, 12 and 113 using available constraints. We find lifetimes of all three gases are likely shorter than currently recommended values, suggesting that best estimates of inferred emissions are larger than recent evaluations. Our analysis indicates that bank emissions are decreasing faster than total emissions, and we estimate new, unexpected emissions during 2014-2016 were 23.2, 18.3, and 7.8 Gg/yr for CFC-11, 12 and 113, respectively. While recent studies have focused on unexpected CFC-11 emissions, our results call for further investigation of potential sources of emissions of CFC-12 and CFC-113, along with CFC-11.

    View details for DOI 10.1038/s41467-021-23229-2

    View details for PubMedID 34006851

  • The COVID-19 lockdowns: a window into the Earth System NATURE REVIEWS EARTH & ENVIRONMENT Diffenbaugh, N. S., Field, C. B., Appel, E. A., Azevedo, I. L., Baldocchi, D. D., Burke, M., Burney, J. A., Ciais, P., Davis, S. J., Fiore, A. M., Fletcher, S. M., Hertel, T. W., Horton, D. E., Hsiang, S. M., Jackson, R. B., Jin, X., Levi, M., Lobell, D. B., McKinley, G. A., Moore, F. C., Montgomery, A., Nadeau, K. C., Pataki, D. E., Randerson, J. T., Reichstein, M., Schnell, J. L., Seneviratne, S., Singh, D., Steiner, A. L., Wong-Parodi, G. 2020; 1 (9): 470-481