Member Since 1978
Rich M. Vogel
Professor Emeritus and Research Professor, Tufts University
AGU Research
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When Heavy Tails Disrupt Hydrologic Modeling
WALTER B. LANGBEIN LECTURE
hydrology | 12 december 2023
Richard M. Vogel
Heavy tails (HT) appear in a myriad of hydrologic applications and their presence can disrupt hydrologic modeling as well as common statistical and ma...
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Stochastic Watershed Model Ensembles for Long‐Range Planning: Verification and Validation
WATER RESOURCES RESEARCH
06 february 2023
Ghazal Shabestanipour, Zachary Brodeur, William H....
Deterministic watershed models (DWMs) are used in nearly all hydrologic planning, design, and management activities, yet they cannot generate strea...
Independent, identically distributed residual errors of watershed models enable uncertainty evaluation and risk-based management
ADVANCING HYDROLOGICAL MODELING AND PREDICTION USING LARGE-DOMAIN METEOROLOGICAL AND HYDROLOGICAL DATA SETS AND MODELS II ORAL
hydrology | 15 december 2022
William H. Farmer, Richard M. Vogel
Because of the inherent spatial and temporal heterogeneity of climatological, meteorological, and hydrological conditions, large-domain hydrological d...
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The abuse of popular performance metrics in hydrologic modeling
DIAGNOSTICS, SENSITIVITY, AND UNCERTAINTY ANALYSIS OF EARTH AND ENVIRONMENTAL MODELS I ORAL
hydrology | 17 december 2021
Martyn P. Clark, Richard M. Vogel, Jonathan Lamont...
This presentation will critically evaluate the use of popular performance metrics in hydrologic modeling. We focus on the Nash-Sutcliffe Efficiency (N...
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A Parsimonious Stochastic Watershed Model for Risk-based Decision Making
ADVANCEMENTS IN WATERSHED MODELING TO SUPPORT WATER MANAGEMENT III ORAL
hydrology | 14 december 2021
Ghazal Shabestanipour, Zachary Brodeur, William H....
Hydrologic models are important tools for quantifying risk in long term infrastructure planning, particularly for climate impact assessments. In pract...
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The Abuse of Popular Performance Metrics in Hydrologic Modeling
WATER RESOURCES RESEARCH
20 september 2021
Martyn P. Clark, Richard M. Vogel, Jonathan Lamont...
The goal of this commentary is to critically evaluate the use of popular performance metrics in hydrologic modeling. We focus on the Nash‐Sut...
Improved estimators of model goodness-of-fit
DIAGNOSTICS, SENSITIVITY, AND UNCERTAINTY ANALYSIS OF EARTH AND ENVIRONMENTAL MODELS III POSTERS
hydrology | 16 december 2020
Jonathan Lamontagne, Richard M. Vogel
Reliable metrics are needed to summarize the degree to which simulation model output reproduces observations. Two of the most widely used metrics are ...
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Improved Estimators of Model Performance Efficiency for Skewed Hydrologic Data
WATER RESOURCES RESEARCH
20 september 2020
Jonathan Lamontagne, Caitline Barber, Richard M. V...
The Nash‐Sutcliffe efficiency (NSE) and the Kling‐Gupta efficiency (KGE) are now the most widely used indices in hydrology for evaluati...