CV

Education

• PhD in Earth System Science, Stanford University, 2024
• B.S. with Honors in Geological Sciences, University of North Carolina at Chapel Hill, 2016

Experience

• 2024-present: Senior Member of Technical Staff at The Aerospace Corporation (El Segundo, CA)
  • Physical Sciences Laboratories - Microelectronics Technology Department
• Summer 2023: Data Science Intern at The Aerospace Corporation (El Segundo, CA)
  • Developed algorithms for state estimation and uncertainty quantification in satellite position/navigation/timing
• 2018-2024: Graduate Researcher at Stanford Remote Sensing Ecohydrology Lab (Stanford, CA)
  • Developed spatiotemporal statistical methods to interpret global microwave remote sensing data
  • Built a Bayesian model-data fusion algorithm to combine satellite observations with computational models of water flow in plants and soil
  • Developed a novel model of plant water use based on classical reinforcement learning
  • Coordinated and carried out a week-long field campaign to measure plant water stress in a forest
  • Supervisor: Prof. Alexandra Konings
• 2016-2018: Research Associate at UNC Institute for the Environment (Chapel Hill, NC)
  • Modified the precipitation and soil modules within a climate model to simulate snowmelt-driven runoff more accurately
  • Developed interactive web app to visualize climate model output
  • Worked with civil engineering researchers to study effects of climate model uncertainty on future hydropower scenarios
  • Supervisor: Prof. Tamlin Pavelsky

Skills

• Python
• Julia
• R

Awards

• FINESST (Future Investigators in NASA Earth and Space Science and Technology), a 3-year graduate fellowship
• Colonel Robinson Scholarship, a 4-year full-tuition scholarship to UNC-Chapel Hill for students in STEM fields

Publications

Tailoring WRF and Noah‐MP to Improve Process Representation of Sierra Nevada Runoff: Diagnostic Evaluation and Applications

Holtzman N, Pavelsky T, Cohen J, Wrzesien M, Herman J. (2020). Tailoring WRF and Noah‐MP to Improve Process Representation of Sierra Nevada Runoff: Diagnostic Evaluation and Applications. Journal of Advances in Modeling Earth Systems

SMAP Detects Soil Moisture under Temperate Forest Canopies

Colliander A, Cosh MH, Kelly VR, Kraatz S, Bourgeau-Chavez L, Siqueira P, Roy A, Konings AG, Holtzman N, Misra S, Entekhabi D, O’Neill P, Yueh SH (2020). SMAP detects soil moisture under temperate forest canopies. Geophysical Research Letters.

L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand

Holtzman N, Anderegg LDL, Kraatz S, Mavrovic A, Sonnentag O, Pappas C, Cosh MH, Langlois A, Lakhankar T, Tesser D, Steiner N, Colliander A, Roy A, Konings AG (2021). L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand. Biogeosciences.

Global ecosystem-scale plant hydraulic traits retrieved using model-data fusion

Liu Y, Holtzman N, Konings AG (2021). Global ecosystem-scale plant hydraulic traits retrieved using model-data fusion. Hydrology and Earth System Science.

Interannual variations of vegetation optical depth are due to both water stress and biomass changes

Konings AG, Holtzman N, Rao K, Xu L, Saatchi S (2021). Interannual variations of vegetation optical depth are due to both water stress and biomass changes. Geophysical Research Letters.

Detecting forest response to droughts with global observations of vegetation water content.

Konings AG, and 36 other authors including Holtzman N (2021). Detecting forest response to droughts with global observations of vegetation water content. Global Change Biology.

Bias correction of hydrologic projections strongly impacts inferred climate vulnerabilities in institutionally complex water systems

Malek K, Reed P, Zeff H, Hamilton A, Wrzesien M, Holtzman N, Steinschneider S, Herman J, Pavelsky T (2022). Bias correction of hydrologic projections strongly impacts inferred climate vulnerabilities in institutionally complex water systems. Journal of Water Resources Planning and Management.

Constraining Plant Hydraulics With Microwave Radiometry in a Land Surface Model: Impacts of Temporal Resolution

Holtzman N, Wang Y, Wood JD, Frankenberg C, Konings AG (2023). Constraining Plant Hydraulics With Microwave Radiometry in a Land Surface Model: Impacts of Temporal Resolution. Water Resources Research.

Investigating diurnal and seasonal cycles of Vegetation Optical Depth retrieved from GNSS signals in a broadleaf forest

Yao Y, Humphrey V, Konings AG, Wang Y, Yin Y, Holtzman N, Wood JD, Bar‐On Y, Frankenberg C (2024). Investigating diurnal and seasonal cycles of Vegetation Optical Depth retrieved from GNSS signals in a broadleaf forest. Geophysical Research Letters.

Ecosystem Water-Saving Timescale Varies Spatially With Typical Drydown Length

Holtzman N, Sloan B, Potkay A, Katul G, Feng X, Konings AG (2024). Ecosystem Water-Saving Timescale Varies Spatially With Typical Drydown Length. AGU Advances.

Talks

Predicting lake depth from topography to map global lake volume

December 01, 2016

Poster at AGU 2016 Fall Meeting, San Francisco, California

Ensemble simulation of Sierra Nevada snowmelt runoff using a regional climate modeling approach

December 01, 2017

Poster at 2017 AGU Fall Meeting, New Orleans, LA

Towards microwave remote sensing of plant hydraulic behavior: Insights from a field campaign

February 01, 2020

Oral presentation at Stanford Hydrology Seminar, Stanford, CA

Constraining Plant Hydraulics with Microwave Radiometry in a Land Surface Model: Impacts of Temporal Resolution and Wavelength of Observations.

December 01, 2021

Oral presentation at AGU 2021 Fall Meeting, New Orleans, LA

Teaching

Remote Sensing of Hydrology

The Water Course