The Impact of a Gridded Streamflow Measure on Drought Variation in the Conterminous United States
Abstract
Models for droughts draw on a wide range of meteorological and hydrological inputs. Stakeholders classify droughts according to different purposes and priorities, and accordingly rely on different measures to explain and predict the onset of drought. While many meteorological inputs are available as gridded data products, hydrological streamflow measurements are often only available as point-referenced gauge measurements. This leads to an issue of misalignment for studies relying on both areal meteorological and point-referenced hydrological data. Such gauge data can also have notable spatial and/or temporal missingness. Many areas remain ungauged, and where gauges exist, equipment malfunctions cause temporal gaps. In this study, we document the value of an existing gridded streamflow measure for the conterminous United States, one which was specifically designed to match the spatio-temporal support of publicly available meteorological and ordinal drought measurements. We use this homogenized database to assess the relative importance of this streamflow measure in explaining US drought variability. This assessment first requires that we address autocorrelation and variability in the variance of observed droughts, two extensions to existing statistical methodology. After suitably controlling for both, our results show that the streamflow measure is often the most statistically important explanatory variable from among a wide set of meteorological variables. We explore the spatial variation and some drivers of this result.
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BibTeX
@misc{erhardt2026impact,
title = {{The Impact of a Gridded Streamflow Measure on Drought Variation in the Conterminous United States}},
author = {Rob Erhardt and Courtney Di Vittorio and Staci Hepler and Mostafa Shams and Wendy Wei and James Zhao},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.10275},
eprint = {2609.10275},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.10275},
}
RIS
TY - UNPB
TI - The Impact of a Gridded Streamflow Measure on Drought Variation in the Conterminous United States
AU - Rob Erhardt
AU - Courtney Di Vittorio
AU - Staci Hepler
AU - Mostafa Shams
AU - Wendy Wei
AU - James Zhao
PY - 2026
DA - 2026/09/09
PB - arXiv
DO - 10.48550/arxiv.2609.10275
UR - https://arxiv.org/abs/2609.10275
AB - Models for droughts draw on a wide range of meteorological and hydrological inputs. Stakeholders classify droughts according to different purposes and priorities, and accordingly rely on different measures to explain and predict the onset of drought. While many meteorological inputs are available as gridded data products, hydrological streamflow measurements are often only available as point-referenced gauge measurements. This leads to an issue of misalignment for studies relying on both areal meteorological and point-referenced hydrological data. Such gauge data can also have notable spatial and/or temporal missingness. Many areas remain ungauged, and where gauges exist, equipment malfunctions cause temporal gaps. In this study, we document the value of an existing gridded streamflow measure for the conterminous United States, one which was specifically designed to match the spatio-temporal support of publicly available meteorological and ordinal drought measurements. We use this homogenized database to assess the relative importance of this streamflow measure in explaining US drought variability. This assessment first requires that we address autocorrelation and variability in the variance of observed droughts, two extensions to existing statistical methodology. After suitably controlling for both, our results show that the streamflow measure is often the most statistically important explanatory variable from among a wide set of meteorological variables. We explore the spatial variation and some drivers of this result.
ER -