Dr. Jessica Driscoll is currently the Science Program Officer for the Rocky Mountain Region.
Professional Experience
Science Program Officer, U.S. Geological Survey, Rocky Mountain Region (2022 - present)
Hydrologist, U.S. Geological Survey, Water Resources Mission Area, Integrated Modeling and Prediction Division (2019 - 2022)
Hydrologist, U.S. Geological Survey, Rocky Mountain Region, New Mexico Water Science Center (2014 - 2019)
Education and Certifications
PhD: Hydrology, The University of Arizona, Tucson, Arizona. Thesis: Impacts of climate change in snowmelt-dominated catchments: development and application of comparative methods to quantify the ...
Graduate Certificates: Water Policy, Geographic Information Systems
MS: Hydrology, The University of Arizona, Tucson, Arizona. Thesis: Use of a reaction path model to identify hydrologic structure in an alpine catchment, Colorado, USA.
BA: Geology, cum laude, Amherst College, Amherst, Massachusetts. Thesis: Aragonite pseudomorphs as kinematic indicators of Syros Island, Greece.
Science and Products
Integrated Water Availability Assessments (IWAAs)
National Hydrologic Model Infrastructure
Improved hydrologic forecasting through synthesis of critical storage components and timescales across watersheds worldwide
National Water Census
National Hydrologic Model Alaska Domain parameter database, version 1
Geospatial Fabric for the National Hydrologic Model Alaska Domain, version 1
Data release in support of Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model
Base flow estimation via optimal hydrograph separation at CONUS watersheds and comparison to the National Hydrologic Model - Precipitation-Runoff Modeling System by HRU calibrated version
High resolution SnowModel simulations reveal future elevation-dependent snow loss and earlier, flashier surface water input for the Upper Colorado River Basin
HydroBench: Jupyter supported reproducible hydrological model benchmarking and diagnostic tool
Evaluating hydrologic region assignment techniques for ungaged basins in Alaska, USA
Strength and memory of precipitation's control over streamflow across the conterminous United States
Implications of model selection: A comparison of publicly available, conterminous US-extent hydrologic component estimates
Prioritizing river basins for intensive monitoring and assessment by the US Geological Survey
Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model
Spatiotemporal variability of modeled watershed scale surface-depression storage and runoff for the conterminous United States
Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models
Simulation of water availability in the Southeastern United States for historical and potential future climate and land-cover conditions
GRACE storage change characteristics (2003–2016) over major surface basins and principal aquifers in the Conterminous United States
Event-response ellipses: A method to quantify and compare the role of dynamic storage at the catchment scale in snowmelt-dominated systems
Science and Products
- Science
Integrated Water Availability Assessments (IWAAs)
The USGS Integrated Water Availability Assessments (IWAAs) are a multi-extent, stakeholder driven, near real-time census and prediction of water availability for both human and ecological uses at regional and national extents.National Hydrologic Model Infrastructure
The USGS National Hydrologic Model (NHM) infrastructure supports the efficient construction of local-, regional-, and national-scale hydrologic models. The NHM infrastructure consists of: 1) an underlying geospatial fabric of modeling units with an associated parameter database, 2) a model input data archive, and 3) a repository of the physical model simulation code bases.Improved hydrologic forecasting through synthesis of critical storage components and timescales across watersheds worldwide
Models that predict the flow of rivers and streams are critically important for planning flood control, hydropower, and reservoir operations, as well as for management of fish and wildlife populations. As temperatures and precipitation regimes change globally, the need to improve and develop these models for a wider spatial coverage and higher spatial fidelity becomes more imperative. Currently, oNational Water Census
The National Water Census is a USGS research program on national water availability and use that develops new water accounting tools and assesses water availability at the regional and national scales. Through the Water Census, USGS is integrating diverse research on water availability and use and enhancing the understanding of connection between water quality and water availability. - Data
National Hydrologic Model Alaska Domain parameter database, version 1
This data release contains input data for hydrologic simulations of the Alaska Domain application of the U.S. Geological Survey (USGS) Precipitation Runoff Modelling System (PRMS) as implemented in the National Hydrologic Model (NHM) infrastructure (Regan and others, 2018). The NHM Alaska Domain parameter database consists of 114 parameter files in ASCII format (CSV), two files needed to run the AGeospatial Fabric for the National Hydrologic Model Alaska Domain, version 1
This metadata record documents a geospatial dataset for the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS) used to drive the National Hydrologic Model (NHM). The Alaska Geospatial Fabric v1 is the spatial representation of the hydrologic response units (HRUs) used for the PRMS NHM Alaska domain. These HRUs were generated using the twelve-digit Hydrologic Unit Code (HUC12) waterData release in support of Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model
This data release includes simulation output from a modeling experiment conducted using the initial calibration of the conterminous United States (CONUS) application of the Precipitation-Runoff Modeling System (PRMS) (Hay, 2019) as implemented in the National Hydrologic Model (NHM) infrastructure (Regan et al, 2018). The study associated with this data release (Sexstone et al., 2019) used the sameBase flow estimation via optimal hydrograph separation at CONUS watersheds and comparison to the National Hydrologic Model - Precipitation-Runoff Modeling System by HRU calibrated version
Optimal hydrograph separation (OHS) is a two-component, hydrograph separation method that uses a two-parameter, recursive digital filter (RDF) constrained via chemical mass balance to estimate the base flow contribution to a stream or river (Rimmer and Hartman, 2014; Raffensperger et al., 2017). A recursive digital filter distinguishes between high-frequency and low-frequency discharge data within - Multimedia
- Publications
Filter Total Items: 16
High resolution SnowModel simulations reveal future elevation-dependent snow loss and earlier, flashier surface water input for the Upper Colorado River Basin
Continued climate warming is reducing seasonal snowpacks in the western United States, where >50% of historical water supplies were snowmelt-derived. In the Upper Colorado River Basin, declining snow water equivalent (SWE) and altered surface water input (SWI, rainfall and snowmelt available to enter the soil) timing and magnitude affect streamflow generation and water availability. To adapt effecAuthorsJohn C. Hammond, Graham A. Sexstone, Annie Laura Putman, Theodore B. Barnhart, David Rey, Jessica M. Driscoll, Glen Liston, Kristen L. Rasmussen, Daniel McGrath, Steven R. Fassnacht, Stephanie K. KampfHydroBench: Jupyter supported reproducible hydrological model benchmarking and diagnostic tool
Evaluating whether hydrological models are right for the right reasons demands reproducible model benchmarking and diagnostics that evaluate not just statistical predictive model performance but also internal processes. Such model benchmarking and diagnostic efforts will benefit from standardized methods and ready-to-use toolkits. Using the Jupyter platform, this work presents HydroBench, a model-AuthorsEdom Moges, Benjamin Ruddell, Liang Zhang, Jessica M. Driscoll, Parker A. Norton, Fernando Perez, Laurel LarsenEvaluating hydrologic region assignment techniques for ungaged basins in Alaska, USA
Building continental-scale hydrologic models in data-sparse regions requires an understanding of spatial variation in hydrologic processes. Extending these models to ungaged locations requires techniques to group ungaged locations with gaged ones to make process importance and model parameter transfer decisions to ungaged locations. This analysis (1) tested the utility of fundamental streamflow stAuthorsTheodore B. Barnhart, William Farmer, John C. Hammond, Graham A. Sexstone, Janet H. Curran, Joshua C. Koch, Jessica M. DriscollStrength and memory of precipitation's control over streamflow across the conterminous United States
How precipitation (P) is translated into streamflow (Q) and over what timescales (i.e., “memory”) is difficult to predict without calibration of site-specific models or using geochemical approaches, posing barriers to prediction in ungauged basins or advancement of general theories. Here, we used a data-driven approach to identify regional patterns and exogenous controls on P–Q interactions. We apAuthorsEdom Moges, Benjamin L. Ruddell, Liang Zhang, Jessica M. Driscoll, Laurel LarsenImplications of model selection: A comparison of publicly available, conterminous US-extent hydrologic component estimates
Spatiotemporally continuous estimates of the hydrologic cycle are often generated through hydrologic modeling, reanalysis, or remote sensing (RS) methods and are commonly applied as a supplement to, or a substitute for, in situ measurements when observational data are sparse or unavailable. This study compares estimates of precipitation (P), actual evapotranspiration (ET), runoff (R), snow water eAuthorsSamuel Saxe, William Farmer, Jessica M. Driscoll, Terri S. HoguePrioritizing river basins for intensive monitoring and assessment by the US Geological Survey
The US Geological Survey (USGS) is currently (2020) integrating its water science programs to better address the nation’s greatest water resource challenges now and into the future. This integration will rely, in part, on data from 10 or more intensively monitored river basins from across the USA. A team of USGS scientists was convened to develop a systematic, quantitative approach to prioritize cAuthorsPeter C. Van Metre, Sharon Qi, Jeffrey R. Deacon, Cheryl A. Dieter, Jessica M. Driscoll, Michael N. Fienen, Terry A. Kenney, Patrick M. Lambert, David P. Lesmes, Christopher Allen Mason, Anke Mueller-Solger, MaryLynn Musgrove, Jaime A. Painter, Donald O. Rosenberry, Lori A. Sprague, Anthony J. Tesoriero, Lisamarie Windham-Myers, David M. WolockRunoff sensitivity to snow depletion curve representation within a continental scale hydrologic model
The spatial variability of snow water equivalent (SWE) can exert a strong influence on the timing and magnitude of snowmelt delivery to a watershed. Therefore, the representation of subgrid or subwatershed snow variability in hydrologic models is important for accurately simulating snowmelt dynamics and runoff response. The U.S. Geological Survey National Hydrologic Model infrastructure with the PAuthorsGraham A. Sexstone, Jessica M. Driscoll, Lauren Hay, John C. Hammond, Theodore B. BarnhartSpatiotemporal variability of modeled watershed scale surface-depression storage and runoff for the conterminous United States
This study uses the explores the viability of a proxy model calibration strategy through assessment of the spatiotemporal variability of surface-depression storage and runoff generated with the U.S. Geological Survey’s National Hydrologic Model (NHM) infrastructure for hydrologic response units (HRUs; n=109,951) across the conterminous United States (CONUS). Simulated values for each HRU of dailyAuthorsJessica M. Driscoll, Lauren Hay, Melanie K. Vanderhoof, Roland J. VigerEstimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models
Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) stream gages across the conterminous United States to examine the range/distribuAuthorsSydney Foks, Jeff Raffensperger, Colin A. Penn, Jessica M. DriscollSimulation of water availability in the Southeastern United States for historical and potential future climate and land-cover conditions
A study was conducted by the U.S. Geological Survey (USGS), in cooperation with the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) and the Department of the Interior Southeast Climate Adaptation Science Center, to evaluate the hydrologic response of a daily time step hydrologic model to historical observations and projections of potential climate and land-cover changeAuthorsJacob H. LaFontaine, Rheannon M. Hart, Lauren E. Hay, William H. Farmer, Andy R. Bock, Roland J. Viger, Steven L. Markstrom, R. Steven Regan, Jessica M. DriscollGRACE storage change characteristics (2003–2016) over major surface basins and principal aquifers in the Conterminous United States
In this research, we characterized the changes in Gravity Recovery and Climate Experiment’s (GRACE) monthly total water storage anomaly (TWSA) in 18 surface basins and 12 principal aquifers in the Conterminous United States (CONUS) over 2003–2016. Regions with high variability in storage were identified. Ten basins and 4 aquifers showed significant change in storage. Eight surface basins and 8 aquAuthorsNaga Manohar Velpuri, Gabriel Senay, Jessica M. Driscoll, Samuel Saxe, Lauren E. Hay, William H. Farmer, Julie E. KiangEvent-response ellipses: A method to quantify and compare the role of dynamic storage at the catchment scale in snowmelt-dominated systems
A method for quantifying the role of dynamic storage as a physical buffer between snowmelt and streamflow at the catchment scale is introduced in this paper. The method describes a quantitative relation between hydrologic events (e.g., snowmelt) and responses (e.g., streamflow) by generating event-response ellipses that can be used to (a) characterize and compare catchment-scale dynamic storage prAuthorsJessica M. Driscoll, Thomas Meixner, Noah P. Molotch, Ty P. A. Ferre, Mark W. Williams, James O. Sickman