Co-I, DOE Office of Science, BER. Arctic SYNAPSE SFA – Scalable hYbrid iNtelligence for Assessment, Prediction, and Simulation of the arctic Environment. $9 million / 3 years
pending
JON SCHWENK
SCIENTIST 3
Los Alamos National Laboratory
Education
University of Minnesota
Advised by Efi Foufoula-Georgiou (currently UC-Irvine)
Ph.D., Civil, Environmental, and Geo-Engineering
2016
P.B.C., Stream Restoration Science and Engineering
2014
M.S., Civil, Environmental, and Geo-Engineering
2012
Tennessee Technological University
Advised by Faisal Hossain (currently U Washington)
B.Sc., Civil Engineering, cum laude
2008
Appointments & Research Experience
Los Alamos National Laboratory
Scientist 3, 2, and Director’s Postdoc
2017–present
Research Topics as PI
Climate impacts on water resources and infrastructure. Led interdisciplinary assessments of climate-change effects on water availability, hydropower generation, and permafrost-related infrastructure risk for U.S. government sponsors.
Adaptive reservoir operations. Led development of a reservoir simulation and reinforcement-learning framework to evaluate optimal hydropower and water-management strategies under operational constraints.
Hydrologic change and river prediction. Developed and evaluated streamflow models that account for watershed differences and human influences. Collaborated on studies of Arctic streamflow trends, river-temperature prediction, ice-breakup forecasting, and habitat-relevant river conditions.
Integrated river and watershed data. Led development of VotE, a river-centered geospatial platform for integrating environmental observations and supporting watershed analysis and modeling. Created RiverPIXELS, an expert-labeled Landsat dataset for mapping river water and in-channel sediment.
Permafrost observations and mapping. Led development and evaluation of high-resolution models of near-surface permafrost, examining their transferability across landscapes. Led synthesis of near-surface permafrost observations through the CommUnity near-Surface Permafrost (CUSP) dataset, including an agentic AI workflow for source discovery and curation, to support observational comparison and model evaluation.
Satellite observation of water quality. Led development of geographically informed estimates of Chesapeake Bay surface-water properties by integrating MODIS imagery with curated in situ observations.
Field observations of Arctic and restored landscapes. Led field work involving permafrost coring, frost probing, soil sampling, and sensor deployment in Arctic environments, including installation of radar corner reflectors. Collected soil samples for wetland-restoration monitoring in the Valles Caldera in New Mexico.
Research Topics as Co-I
River and delta channel networks. Developed methods for extracting channel-network topology and inferring flow directions, and contributed to global hydrography representing river bifurcations. Collaborated on studies of channel braiding, coastal network loops, discharge partitioning, and network controls on Arctic delta lake dynamics.
Arctic river dynamics and permafrost. Investigated how permafrost influences riverbank erosion across spatial scales and how river migration interacts with floodplain permafrost, drawing on field observations and synthesis of river erosion and migration records.
Satellite mapping of rivers and sediment. Mentored development of graph-based and active-learning methods to identify water and sediment in multispectral imagery while reducing labeled-data requirements.
River dynamics and biogeochemical processes. Collaborated on studies linking river migration and delta morphology with floodplain carbon burial, microbial communities, and nitrate retention.
Climate-ecology model integration. Co-led development of methods linking Earth system and ecological models across spatial scales to investigate mosquito population responses to climate change. Mentored predictive modeling of mosquito dynamics using climate-model output.
Societal instability and event forecasting. Integrated heterogeneous datasets with event records to model regional instability in Pakistan. Leading collaborative research on causal-inference approaches to conflict forecasting.
Sediment transport in delta wetlands. Mentored students in field investigations of sediment transport and accumulation in the resacas and adjacent alluvial basins of the Rio Grande Delta.
Scientific data standards for energy systems. Developed and tested a schema-generation workflow for MG-RAVENS, supporting consistent data exchange among microgrid and power-grid modeling tools in a DOE multi-laboratory collaboration.
University of California, Irvine, CA
Postdoctoral Researcher
2016
River response to channel cutoffs. Used satellite observations to quantify how meander cutoffs alter river migration and channel widening upstream and downstream.
University of Minnesota, Twin Cities, MN (Saint Anthony Falls Laboratory)
Graduate Student
2010–2016
Meander evolution and river form-dynamics. Combined numerical simulations with methods for tracking individual meander bends to relate channel geometry to migration histories and nonlinear river dynamics.
Satellite observation of river change. Led satellite-based analysis of Ucayali River evolution and developed RivMAP to quantify channel migration, width changes, and cutoff events from repeated imagery.
Hydrologic change in agricultural landscapes. Applied nonlinear time-series analysis to investigate how agricultural land conversion and artificial drainage altered watershed hydrology in the Minnesota River Basin.
River dynamics and freshwater ecology. Led modeling of freshwater mussel population responses to changes in streamflow and suspended sediment in Minnesota rivers.
Springburn Natural Engineering and Design, TN
Engineer in Training (EIT)
2008–2010
Urban watershed runoff modeling. Developed and calibrated a rainfall–runoff model for an urbanized watershed in Crossville, Tennessee, supported by field measurements of precipitation and water level.
Stream design for aquatic habitat. Defined physical habitat requirements for an endangered freshwater mussel and contributed to stream design with The Nature Conservancy.
Tennessee Technological University, TN
Master’s Student
2009
Hydraulic geometry and watershed scaling. Conducted channel surveys across the Nashville Basin to characterize relationships among discharge, watershed area, and river morphology.
Clarkson University, NY
Undergraduate Researcher
2006
Soil biogeochemistry. Combined field sampling and soil-column experiments to examine how redox conditions influence methylmercury production.
Awarded Funding
Listed funding indicates a significant contribution to the proposal and project. LDRD refers to Lab Directed Research and Development, a competitive internal funding program at LANL.
Co-I, LDRD Directed Research. Data driven instability and conflict forecasting for actionable intelligence. $6 million / 3 years
2025
Co-I, DOE ASCR. Principled, Structure-Preserving, and Uncertainty-Quantified Machine Learning for Scientific Data, $6 million / 3 years
2024
Co-I, NASA ROSES. Predicting flux partitioning in river delta networks using SWOT to produce global delta products and quantify the response of deltas to climate and human-induced change. $1.2 million / 4 years
2024
PI, LDRD Director’s Initiative. Innovations in permafrost and ground ice modeling for national security applications. $400k / 1 year
2024
PI, LDRD Exploratory Research. Responsive reservoir control for next-generation water security. $1 million / 3 years
2023
PI, Classified Sponsor. Permafrost and wildfire risk across the Arctic. $1 million / 9 months
2023
PI, Classified Sponsor. Climate and human impacts to streamflow in Southeast Asia. $1 million / 9 months
2023
Co-PI, LANL Tech Evaluation and Demonstration Project. Demonstration of rapid climate data access and analysis. $150k / 1 year
2023
Co-I, LDRD ER. Post-wildfire hydrology impacts: a tool for mitigating water security disasters. $1 million / 3 years
2023
Co-I, DOE FAIR. Evaluating water, sediment, and nutrient transport rates and accumulation patterns in alluvial ridge basins between the abandoned river channels (resacas) of the Rio Grande Delta. $1.5 million / 3 years
2023
PI, Center for Earth and Space Sciences. Discerning watershed impacts on streamflow with novel data and machine learning approaches. $150k / 2 years
2022
Co-PI, LDRD Director’s Initiative. Accelerating Arctic research through data-model integration using machine learning and optimized observational datasets. $500k / 1 year
2022
PI, LDRD Exploratory Research. A Global, High-Resolution River Network Model for Improved Flood Risk Prediction. $1 million / 3 years
2020
Co-I, LDRD Directed Research. Model-Driven Data Fusion for Infectious Disease Forecasting, $3.2 million / 3 years
2020
Co-I, LDRD Reserve. Human-Natural Systems Prediction under Climate Change, $500k / 1 year
2018
Co-I, ineligible to receive funding. NSF Award 1342994. Understanding deltas through the lens of their channel networks, $334k / 3 years
2018
PI, Director’s Postdoctoral Fellowship, LANL. Impacts of climate and land use on global river dynamics, $168k / 2 years
2017
PI, NSF Graduate Research Fellowship. Modeling river behavior at high spatial and temporal resolutions using a cellular automaton, $160k / 3 years
2010
Software
RivGraph Python Manuscript 1 Manuscript 2 GitHub
Extracts river network topology (nodes/links) from georeferenced binary mask rasters for deltas and braided rivers.
Automatically assigns link directionality and computes topologic + morphologic metrics for networks.
RivMAP/RivMAPy Matlab / Python Manuscript Mathworks GitHub
Toolbox for extracting planform river morphodynamics from binary channel masks.
Quantifies centerlines/banklines, width, migration rates, and cutoff events.
DeepReservoir-Navajo Python GitHub
Designed and co-implemented a deep reinforcement learning framework with Stable-Baselines3 for optimization.
Designed and built a virtual environment of a hydropower reservoir system.
VotE Python, PostgreSQL + PostGIS GitHub access upon request
A river-centric data platform + API enabling rapid querying, model building, and visualization at a global scale.
Includes an AI-ready geospatial schema and workflows for integrating river network–based datasets.
rabpro Python, GEE API Manuscript GitHub
Delineates watersheds globally and computes river profiles, slopes, and related longitudinal metrics.
Computes contributing-basin statistics for arbitrary raster inputs (e.g., topography, precipitation, vegetation) via GEE.
dapper Python, Google Earth Engine (GEE) API GitHub
Provides a toolset to curate, sample, and format datasets needed to run DOE’s E3SM Land Model (ELM).
Automates end-to-end data preparation workflows using Google Earth Engine and other APIs.
hillsloper Python GitHub access upon request
Partitions DEMs into constituent hillslopes for high-resolution terrestrial simulations.
Extracts a connected river network and maintains hillslope–channel connectivity for modeling workflows.
satval Python, GEE API GitHub access upon request
Samples multispectral satellite pixel features aligned in space/time with in-situ water-quality observations.
Aggregates observations within shared pixel footprints to support satellite–field validation and modeling.
Ecopopper Python GitHub
Generates unstructured grids to bridge scale mismatches between earth system models and ecological models.
Supports model coupling and scenario workflows requiring flexible mesh generation.
RiverMUSE Matlab Manuscript CSDMS
Simulates freshwater mussel population dynamics under changing suspended sediment and flow regimes.
Supports scenario experiments linking hydrology/sediment forcing to ecological response.
MG-RAVENS contributor Python, JSON Schema, UML/XML GitHub
Created a UML-to-JSON Schema pipeline extending DOE power-grid data models to microgrids.
Unified 1,000+ schema definitions under a single UML model, backed by regression tests.
Peer-Reviewed Publications
For real-time citation tracking, visit my Google Scholar Profile.
J. Schwenk, et al. (In prep) Deep reinforcement learning for Navajo Reservoir operations. Target: Water Resources Research
J. Schwenk, et al. (In prep) CUSP: A synthesis of near-surface permafrost observations. Target: Scientific Data
Coon, E., B. Gao, M. Cooper, J. Schwenk, T. Zhou (In review) A bespoke model of Arctic river basins based on hillslope delineation. Journal of Hydrology.
Shaftel, B., …, J. Schwenk, et al. (2026) Integrating climate data and river modeling to reveal Chinook salmon habitat conditions in Sub-Arctic river basins. Ecosphere. doi: 10.1002/ecs2.70399
Limber, R., …, J. Schwenk, et al. (2025) Long short-term memory model to forecast river ice breakup throughout Alaska, USA. Water Resources Research. doi: 10.1029/2025WR040635
Diepeveen, W., J. Schwenk, A. Bertozzi (2025) Latent Diffeomorphic Dynamic Mode Decomposition. Applied Mathematics Letters. doi: 10.1016/j.aml.2025.109701
Solander, K., T. Zhou, K. Bennett, J. Schwenk (2025) Evaluation of CMIP6 streamflow in the Arctic. Journal of Hydrometeorology. doi: 10.1175/JHM-D-24-0124.1
Nair, G., …, J. Schwenk, et al. (2025) Increasing mosquito abundance under global warming. Earth’s Future. doi: 10.1029/2024EF005629
Wortmann, M., …, J. Schwenk, et al. (2025) Global River Topology (GRIT): A bifurcating river hydrography. Water Resources Research. doi: 10.1029/2024WR038308
Chang, S., Solander, K., and J. Schwenk (2025) Deep learning advances Arctic river water temperature predictions. Water Resources Research. doi: 10.1029/2024WR039053
Maebius, S., K. Bennett, and J. Schwenk (2024) Machine learning classification strategy to improve streamflow estimates in diverse river basins in the Colorado River basin. Earth and Space Science. doi: 10.1029/2024EA003798
Chen, B., K. Miller, A. Bertozzi, and J. Schwenk (2024) CGAP: A hybrid contrastive and graph-based active learning pipeline to detect water and sediment in multispectral images. IEEE Applied Earth Observations. doi: 10.1109/JSTARS.2024.3493073
Abolt, C., …, J. Schwenk, et al. (2024) Topography drives variability in circumpolar permafrost thaw pond expansion. JGR Earth Surface. doi: 10.1029/2024JF007675
Douglas, M., …, J. Schwenk, et al. (2024) Permafrost formation in a meandering river floodplain. AGU Advances. doi: 10.1029/2024AV001175
Thaler, E., …, J. Schwenk, et al. (2024) High-resolution maps of near-surface permafrost for three watersheds on the Seward Peninsula, Alaska derived from machine learning. Earth and Space Science. doi: 10.1029/2023EA003015
Rowland, J., J. Schwenk, et al. (2023) Scale-dependent influence of permafrost on riverbank erosion rates. JGR Earth Surface. doi: 10.1029/2023JF007101
Chen, B., Miller, K., Bertozzi, A., and J. Schwenk (2023). Batch active learning for multispectral and hyperspectral image segmentation using similarity graphs. Communications on Applied Mathematics and Computation. doi: 10.1007/s42967-023-00284-8
Bennett, K., J. Schwenk, et al. (2023) Recent streamflow trends across permafrost basins of North America. Frontiers in Water. doi: 10.3389/frwa.2023.1099660
Chen, B., Miller, K., Bertozzi, A., and J. Schwenk (2023). Graph-based active learning for surface water and sediment detection in multispectral images. IGARSS 2023 IEEE International Geoscience and Remote Sensing Symposium. doi: 10.1109/IGARSS52108.2023.10282009
Knights, D., Piliouras, A., J. Schwenk, Hariharan, J., Russoniello, C. (2023). Seasonal and morphological controls on nitrate retention in Arctic deltas. Geophysical Research Letters. doi: 10.1029/2022GL102201
Cooper, M., …, J. Schwenk, et al. (2023). Detecting change in permafrost active layer thickness from nonlinear baseflow recession analysis. Water Resources Research. doi: 10.1029/2022WR033154
Beesley, L., …, J. Schwenk, et al. (2023). Multi-dimensional resilience: a quantitative exploration of disease outcomes and economic, political, and social resilience to the COVID-19 pandemic in six countries. PLOS ONE. doi: 10.1371/journal.pone.0279894
Stachelek, J., Avendano, S., and J. Schwenk (2022). Geographically-aware estimates of remotely-sensed water properties for Chesapeake Bay. Journal of Applied Remote Sensing. doi: 10.1117/1.JRS.16.044528
Tejedor, A., J. Schwenk, et al. (2022). The Entropic Braiding Index (eBI): a robust metric to account for the diversity of channel scales in multi-thread rivers. Geophysical Research Letters. doi: 10.1029/2022GL099681
Hariharan, J., A. Piliouras, J. Schwenk, P. Passalacqua (2022). Width-Based Discharge Partitioning in Distributary Networks: How Right We Are. Geophysical Research Letters. doi: 10.1029/2022GL097897
Schwenk, J., T. Zussman, J. Stachelek, and J. Rowland (2022) rabpro: global watershed boundaries, river elevation profiles, and catchment statistics. Journal of Open Source Software. doi: 10.21105/joss.04237
Konkol, A., J. Schwenk, E. Katifori, J. Shaw. (2021) Interplay of river and tidal forcings promotes loops in coastal channel networks. Geophysical Research Letters. doi: 10.1029/2022GL098284
Schwenk, J. and J. Hariharan. (2021). RivGraph: Automatic extraction and analysis of river and delta channel network topology. Journal of Open Source Software. doi: 10.21105/joss.02952
Limaye, A., E. Lazarus, Y. Li, and J. Schwenk. (2021) River sinuosity describes a continuum between randomness and ordered growth. Geology. doi: 10.1130/G49153.1
Douglas, M., …, J. Schwenk, et al. (2021) Organic carbon burial by river meandering partially offsets bank erosion carbon fluxes in a discontinuous permafrost floodplain. Earth Surface Dynamics. doi: 10.5194/esurf-2021-80.
Douglas, M., …, J. Schwenk, et al. (2021) Impact of river channel lateral migration on the microbial ecology of a discontinuous permafrost floodplain. Applied & Environmental Microbiology. doi: 10.1128/AEM.01339-21
Schwenk, J., A. Piliouras, J. Rowland. (2020). Determining flow directions in river channel networks using planform morphology and topology. Earth Surface Dynamics. doi: 10.5194/esurf-8-87-2020
Vulis, L., A. Tejedor, J. Schwenk, A. Piliouras, J. Rowland, E. Foufoula-Georgiou. (2020) Channel network control on seasonal lake area dynamics in Arctic Deltas. Geophysical Research Letters. doi: 10.1029/2019GL086710
Knights, D., …, J. Schwenk, et al. (2019) Nitrate removal across ecogeomorphic zones in Wax Lake Delta, Louisiana (USA). Water Resources Research. doi: 10.1029/2019WR026867
Gran, K., J. Schwenk, et al. (2019) The power of environmental observations for advancing multidisciplinary research, outreach, and decision support: the case of the Minnesota River Basin. Water Resources Research. doi: 10.1029/2018WR024211
Schwenk, J., E. Foufoula-Georgiou. (2017). Meander cutoffs nonlocally accelerate upstream and downstream migration and channel widening. Geophysical Research Letters, doi:10.1002/2016GL071670
Schwenk, J., A. Khandelwal, M. Fratkin, V. Kumar, E. Foufoula-Georgiou. (2017). High spatio-temporal resolution of river planform dynamics from Landsat: the RivMAP toolbox and results from the Ucayali River, Earth and Space Science, doi:10.1002/2016EA000196
Schwenk, J., E. Foufoula-Georgiou. (2017). Are process nonlinearities encoded in meandering river planform morphology? JGR Earth Surface, doi:10.1002/2016JF003929
Schwenk, J. (2016). Meandering rivers: interpreting dynamics from planform geometry and the secret lives of migrating meanders. Ph.D. Dissertation.
Schwenk, J., S. Lanzoni, and E. Foufoula-Georgiou. (2015). The life of a meander bend: connecting shape and dynamics via analysis of a numerical model. JGR Earth Surface, doi:10.1002/2014JF003252
E. Foufoula-Georgiou, P. Belmont, P. Wilcock, K. Gran, J. Finlay, P. Kumar, J. Czuba, J. Schwenk, Z. Takbiri (2016). Comment on “Climate and agricultural land use change impacts on streamflow in the upper midwestern United States” by Satish C. Gupta et al. Water Res. Research, doi:10.1002/2015WR018494
Foufoula-Georgiou, E., Z. Takbiri, J. Czuba, and J. Schwenk. (2015). The change of nature and the nature of change in agricultural landscapes: Hydrologic regime shifts modulate ecological transitions. Water Res. Research, doi:10.1002/2015WR017637
Hansen, A.T., J.A. Czuba, J. Schwenk, A. Longjas, M. Danesh-Yazdi, and E. Foufoula-Georgiou. (2015). Coupling freshwater mussel ecology and river dynamics using a simplified dynamic interaction model. Freshwater Science, doi:10.1086/684223
Schwenk, J., F. Hossain, D. Huddleston (2009). A computer-aided visualization tool for stochastic theory education in water resources engineering. Comp. App. in Eng. Edu., doi:10.1002/cae.20233
Reports
Schwenk, J. and A. Whelsky. (2025) The future of hydroelectric generation in Brazil. Classified document. Los Alamos National Laboratory.
Schwenk, J. et al. (2024) Permafrost impacts on infrastructure in the Arctic. Classified document. Los Alamos National Laboratory.
Schwenk, J. et al. (2024) Comprehensive modeling and evaluation of climate impacts on water dynamics in Southern Asia. Classified document. Los Alamos National Laboratory.
Fairchild, G., … J. Schwenk, et al. (2020) Forecasting Regional Stability (FoReSt): Predicting, Quantifying, and Mitigating Regional Stability. OUO document. Los Alamos National Laboratory.
Published Datasets
Farley, M., …, J. Schwenk, et al. (In review) A multi-resolution Arctic fractional shrub cover synthesis dataset derived from UAS and airborne SfM and LiDAR. Scientific Data.
Schwenk, J., J. Rowland, A. Piliouras (2023) Observations and machine-learned models of near-surface permafrost along the Koyukuk River, Alaska, USA. ESS-DIVE repository. doi: 10.15485/1922517
Rowland, J., B. Crosby, J. Schwenk, A. Piliouras, M. Douglas (2023) Riverbank temperatures on the Selawik River, Alaska 2010-2012, and Koyukuk River, Alaska June to July 2018. ESS-DIVE repository. doi: 10.15485/1922885
Schwenk, J. and J. Rowland (2022) RiverPIXELS: paired Landsat images and expert-labeled sediment and water pixels for a selection of rivers v1.0. ESS-DIVE repository. doi:10.15485/1865732
Hariharan, J., A. Piliouras, J. Schwenk, P. Passalacqua (2022) Discharge in Distributary NeTworks (DIDNT) Dataset. OSF Repository. doi: 10.17605/OSF.IO/U732J
Bennett, K., C. Talsma, J. Stachelek, J. Schwenk (2022) Historical and Future Extreme Event Indices for the Colorado River Basin. doi:10.15485/1862040
Prior, E., J. Schwenk, and J. Rowland (2022) VotE-Dams: a compilation of global dams’ locations and attributes (v1). ESS-DIVE repository. doi: 10.15485/1843541
Douglas, M., …, J. Schwenk, et al. (2022) Bulk density, grain size, carbon content and isotopes, and nitrogen content of floodplain sediment along the Koyukuk River, Alaska collected in Summer 2018. ESS-DIVE repository. doi: 10.15485/1910300
Rowland, J. and J. Schwenk. (2019) Global meta-analysis of published river bank erosion and migration rates. Incorporating the Hydrological Controls on Carbon Cycling in Floodplain Ecosystems into Earth System Models (ESMs). doi:10.15485/1571181
Teaching and Mentorship
Los Alamos National Laboratory
Student and Postdoc Mentor
2018–present
Postdoc Mentees
Shubhendu Singh reinforcement learning for reservoir operations Now AI4AI, Italy 2024–2026
Cansu Demir Arctic E3SM Land Model development Now LANL postdoc 2025–present
Tao Liu AI-enabled wildfire hydrology Now State of New Mexico 2023–2025
Rajiv Ranasinghe LSTM hydrology model development Now LANL Scientist 2023–2025
Chuck Abolt AI and computer vision Now Freshwater Trust 2021–2023
Jemma Stachelek Global hydrology Now LANL Scientist 2021–2023
Rachel Glade Solifluction Now University of Rochester Professor 2019–2021
Feng Yu Hydrology-focused GIS Now Bayer GIS Scientist 2018–2019
Student Mentees
Mark Reedy Causal AI for conflict modeling Now LANL GRA 2025–present
Maggie Farley Drone field observations for permafrost Now LANL GRA 2024–present
Shuyu Chang AI for river temperature prediction Now U Connecticut Professor 2024
Gokul Nair Mosquito dynamics under climate change Now traveling post-PhD 2022–2025
Sarah Maebius AI for hydrologic prediction in arid regions Now Princeton PhD student 2022–2024
Elizabeth Prior VotE dams creator Now Virginia Tech PhD student 2022
Sofia Avendano Water quality in Chesapeake Bay Now Elementary school teacher 2022
Jay Hariharan Flux partitioning in delta networks Now US Federal Government 2021–2022
Rachel Ulrich Arctic delta hydrology Now LANL staff 2021
Bohan Chen Graph learning for computer vision Now Caltech Postdoc 2021–2024
Tal Zussman rabpro development Now Columbia University PhD student 2020
Tabatha Clevenger Geospatial mapping Now Vassar College Academic Coach 2020
Ryan Herring ML + SAR for delta channel networks Now Math and Science instructor 2020
Gailin Pease CNNs for computer vision Now Singularity Energy Data Scientist 2019
Mulu Fratkin Geomorphology and hydrology Now State of Minnesota 2018–2020
Robert Sare Software development Now X/Google 2018
University of Minnesota, Twin Cities
Lecturer and TA
2015–2016
Lecturer: Stochastic Geomorphology (CE 8490)
Lecturer: Hydrologic Design (CE 4501)
Teaching Assistant: Fluid Mechanics (CE 3502); two semesters. Prepared weekly lectures and lab demonstrations, held office hours, and graded homework for 40 students.
Teaching Assistant: Hydrologic Design (CE 5401); two semesters. Created and presented weekly lectures, designed homework assignments, held office hours, and graded exams and homework for 75 students.
Honors and Awards
LANL SPOT awards (for inclusivity, collegiality, performance, emergency response)
2021, 2022, 2023, 2024, 2025, 2026
Los Alamos Awards Program – Excellence in Supporting LANL’s Climate Impacts for National Security Program, AML Leadership
2024, 2025, 2026
National Geospatial Intelligence Agency (NGA) Challenger Award (Frostbyte Team)
2026
R&D 100 Team Awards: (1) General Award and (2) Corporate Social Responsibility Award for EpiEarth technology
2025
Global Security-Intelligence & Emerging Threats Certificate of Outstanding Performance
2024
Large Team Distinguished Performance Award – Climate Impacts Team
2023
LANL Promotion to Scientist 3
2023
Director’s Fellow, Los Alamos National Laboratory
2017
Cover image, Earth and Space Science 4(2)
2017
Saint Anthony Falls Laboratory Alvin G. Anderson Award
2016
Cover image, JGR Earth Surface 120(4)
2015
Tsai Travel Award, University of Minnesota
2015
COGS Travel Fellowship, University of Minnesota
2015
Sommerfeld Travel Grant Award, University of Minnesota
2014
Merit Scholar, Tennessee Technological University
2004–2008
Student Government Association Senator of the Year, Tennessee Technological University
2008
Selected Presentations
J. Schwenk. “Envisioning the future of global hydrography data.” Global Hydrography Workshop. Oxford, UK. September, 2025. invited
Crumley, R., …, J. Schwenk. “Foundation models for long term weather prediction.” July, 2025. LANL IS&T Capability Review. invited
J. Schwenk, R. Fiorella, K. Bennett. “The search for optimal resolution in ELM modeling.” March, 2025. DOE ESSD PI Meeting.
Schwenk, J. et al. “Climate analysis of a mega-dam and downstream impacts.” US Government Agency meeting. December, 2023. invited
Schwenk, J. et al. “A Platform for the next generation of data-driven, river and watershed-centric modeling: Veins of the Earth.” Tri-labs (LANL, Sandia, Lawrence-Livermore) Climate Impacts on National Security workshop. December, 2022. invited
Schwenk, J. “Next-gen data fusion for water security.” LANL IS&T Capability External Review. July, 2022. invited
Schwenk, J. “The secret lives of rivers.” Teen Science Café, Los Alamos, NM. March, 2022. invited
Schwenk, J. et al. “How will a warming Arctic affect permafrost-modulated riverbank erosion?” Southern California Geomorphology Symposium. Irvine, CA. April, 2022. invited
Schwenk, J. et al. “A Platform for the next generation of data-driven, river and watershed-centric modeling: Veins of the Earth.” University of California, Irvine CEE Departmental Seminar. April, 2022. invited
Schwenk, J., J. Rowland, K. Kaufeld. “Watersheds as natural spatial units: modeling carbon fluxes from riverbank erosion.” Interagency Conference on Research in Watersheds. Virtual conference. November, 2020. invited
Schwenk, J. “Intersections between Earth System Models and remotely-sensed observations.” Climate, Ocean and Sea Ice Modeling (COSIM) webinar. August 2020. invited
Schwenk, J., A. Piliouras, Y. Zhang, M. Fratkin, J. Rowland, M. Douglas, A. Chadwick, M. Lamb. “Permafrost control on river migration along the Koyukuk River, AK.” AGU, San Francisco, CA. December 2019.
Schwenk, J., A. Tejedor, E. Foufoula-Georgiou, J. Rowland. “Automatic extraction of delta channel network topology.” AGU, Washington, D.C. December 2018.
Vulis, L., A. Tejedor, J. Schwenk, E. Foufoula-Georgiou. “Channel-lake connectivity in Arctic deltas.” AGU, Washington, D.C. December 2018.
Rowland, J., J. Schwenk, E. Shelef, U. Mishra, J. Muss, S. Stauffer. “Pan-arctic flux of soil organic carbon to rivers by river bank erosion.” AGU, Washington, D.C. December 2018.
Schwenk, J., “A meandering path toward global river morphodynamics.” Descartes Labs, November 2018. invited
Sare, R., J. Schwenk, J. Rowland. “Fluvial response to land use change measured in Landsat time series of migrating rivers.” LANL Student Symposium. August, 2018.
Schwenk, J., A. Khandelwal, M. Fratkin, V. Kumar, and E. Foufoula-Georgiou. “River Morphodynamics from Space: The Landsat Frontier.” EGU, Vienna, Austria, April 2017. invited
Schwenk, J., E. Foufoula-Georgiou, “A case of self-perturbation: channel responses to meander cutoffs.” EGU, Vienna, Austria, April 2017.
Schwenk, J., “It’s high time for high time resolution of river morphodynamics.” ACES in the Hole Seminar Series, Los Alamos National Laboratory, January 2017. invited
Schwenk, J. “Meandering rivers: interpreting dynamics from planform geometry and the secret lives of migrating meanders.” Summer Institute on Earth Surface Dynamics, August 2016. invited
Schwenk, J. “Bend- and Reach-Scale River Planform Dynamics.” NCED2 Computational Tools for Modeling Fluvial Processes from Grains to Landscapes, August 2016. invited
Schwenk, J., Mulu Fratkin, and E. Foufoula-Georgiou. “Accelerated Migration Due to Cutoffs in the Ucayali River.” American Geophysical Union, San Francisco, CA, December 2015.
Schwenk, J., and E. Foufoula-Georgiou. “A natural experiment: Geomorphic consequences of a massive, human-induced cutoff along the Ucayali River.” River Coastal and Estuarine Morphodynamics, 9th Symposium, Iquitos, Peru, September 2015.
Schwenk, J., E. Foufoula-Georgiou, and S. Lanzoni. “Revisiting nonlinearity in meandering river planform dynamics through Gradual Wavelet Reconstruction.” American Geophysical Union, San Francisco, CA, December 2014.
Schwenk, J., S. Lanzoni, and E. Foufoula-Georgiou. “A backwards-in-time Lagrangian framework for extraction of meander bend dynamics: use in meander classification, process diagnostics, and model comparison.” American Geophysical Union, San Francisco, CA, December 2013.
Schwenk, J., S. Baumgartner, A. Abeyta, S. Day. “Assessing the need for stream restoration efforts in Bassett Creek.” Upper Midwest Stream Restoration Symposium, Minneapolis, MN, March 2012.
Service
LDRD ER review panelist (ESA, DSMA)
2024–2025
Trail construction and maintenance – Los Alamos County
2021–present
Association for Women Geoscientists Laramide Chapter – Treasurer and Secretary
2021–present
Teen Science Café presenter for STEM-interested high-schoolers
2022
Instructor at “Wildfire Camp” for underrepresented undergrads
2020–2022
Vice-president, Los Alamos Postdoctoral Association
2017–2019
Los Alamos County Science Fair Judge
2017–present
Hour of code instructor at Barranca Mesa Elementary
2017
Association for Women Geoscientists fundraising organizer
2017–2021
Guest lecturer at Los Alamos High School
2017–2018
President, Saint Anthony Falls Laboratory Student Council
2014–2016
Co-Founder and Chair, Saint Anthony Falls Lab Bike Library
2014–2016
Senator, Tennessee Technological University Student Government
2007
Chair, Student Environmental Action Coalition, TN Tech
2006–2007
Reviewer for NSF, DOE, Geophysical Research Letters, Geology, Journal of Hydrology, JGR-Earth Surface, Water Resources Research, Journal of Hydraulic Engineering, Environmental Modelling & Software, Frontiers in Water, Land Degradation and Development, Remote Sensing, International Journal of Geo-Information
2015–present
Leadership
Los Alamos National Lab
2019–present
Advancing Machine Learning Fellowship PI: Lead organizer of a team that administers an intense, 10-week summer fellowship for graduate students
EES – IC Liaison: Connecting EES capabilities to national security/intelligence community leads
DOE’s AI future: Led LANL’s contributions to DOE’s AI4ES (earth system predictability) vision and report. LANL’s subject matter expert and contributor for DOE’s AI4SES (science, energy, and security) vision and report.
AGU Session Chair: Organized session on river dynamics at Fall 2021 AGU meeting.
LANL Postdoc Association: Represented >400 postdocs as Vice President to improve inclusivity and postdoc benefits and to foster community
University of Minnesota
2010–2017
Saint Anthony Falls Student Council: Represented >30 students as President and Vice President
SAFL Bike Library: Led a team of four volunteers to design, fund, and implement a bike library for the Saint Anthony Falls Lab student body
Landsat Analysis of Ucayali River: Led a team of five students in the computer science department to complete a complex, “big-data” analysis resulting in two papers.
Tennessee Technological University
2004–2007
Student Government Association: As Senator, introduced the most bills among the >30-member Senate, mostly in an effort to improve energy efficiency and sustainability measures
Student Environmental Action Coalition: As President, successfully campaigned for a student body self-imposed “green energy tax” that enabled the University to purchase renewable energy and implement energy efficiency upgrades
Technical Skills
AI / ML: graph learning, neural networks (e.g., CNN, LSTM, Transformers), deep reinforcement learning (PPO/TD3); sequential and regression modeling (LSTM, forests), computer vision, image analysis (SVM, eCognition)
Analysis and modeling: geospatial data; multiscale spectral analyses (Fourier transforms, wavelet decomposition); nonlinear dynamics; image processing; remote sensing; optimization; graph methods; rainfall-runoff modeling; earth system models, numerical simulation
Computation: high-performance computing; parallelization; database design, construction, and maintenance; *nix and Windows systems; git (GitHub/GitLab)
Scientific software: data model and schema design; JSON Schema; UML; IEC Common Information Model (CIM); XML parsing; schema generation and validation; automated testing and continuous integration
Languages: Python, SQL (Postgres/PostGIS), JavaScript (Google Earth Engine), R, Matlab, Slurm, LaTeX
Python packages: geospatial (gdal, geopandas, xarray, pyproj, shapely); image analysis (scikit-image, OpenCV, numpy), ML/DL (scikit-learn, tensorflow, pytorch, neuralhydrology); data/feature engineering (pandas, psycopg2, networkx)
Field work: topographic and channel surveys (total station and dGPS), sediment characterization via sieving and Wolman counts, bankfull identification, stage and flow measurements, soil and water sampling for chemistry and quality, habitat assessment, soil (permafrost) coring, ground control point installation, corner reflector installation, soil characterization