Version 1
: Received: 24 July 2024 / Approved: 25 July 2024 / Online: 25 July 2024 (07:35:19 CEST)
How to cite:
Shepard, D.; Jones, N. L.; Williams, G. P. Application of a Novel Groundwater Storage Analysis Tool to Assess Drought Impacts in a Groundwater-Driven Basin in the Klamath Watershed, Oregon, USA. Preprints2024, 2024072013. https://doi.org/10.20944/preprints202407.2013.v1
Shepard, D.; Jones, N. L.; Williams, G. P. Application of a Novel Groundwater Storage Analysis Tool to Assess Drought Impacts in a Groundwater-Driven Basin in the Klamath Watershed, Oregon, USA. Preprints 2024, 2024072013. https://doi.org/10.20944/preprints202407.2013.v1
Shepard, D.; Jones, N. L.; Williams, G. P. Application of a Novel Groundwater Storage Analysis Tool to Assess Drought Impacts in a Groundwater-Driven Basin in the Klamath Watershed, Oregon, USA. Preprints2024, 2024072013. https://doi.org/10.20944/preprints202407.2013.v1
APA Style
Shepard, D., Jones, N. L., & Williams, G. P. (2024). Application of a Novel Groundwater Storage Analysis Tool to Assess Drought Impacts in a Groundwater-Driven Basin in the Klamath Watershed, Oregon, USA. Preprints. https://doi.org/10.20944/preprints202407.2013.v1
Chicago/Turabian Style
Shepard, D., Norman L Jones and Gustavious P. Williams. 2024 "Application of a Novel Groundwater Storage Analysis Tool to Assess Drought Impacts in a Groundwater-Driven Basin in the Klamath Watershed, Oregon, USA" Preprints. https://doi.org/10.20944/preprints202407.2013.v1
Abstract
Groundwater is becoming increasingly important in the Pacific Northwest of the USA due to declining snowpack volumes and shifts in precipitation type and timing, all connected with climate change. The Upper Williamson Basin of the Klamath Watershed is a groundwater dominated watershed with massive fluctuations in year-to-year streamflow volumes over the past four decades, including the complete absence of any live flow for several years. The precise relationship between groundwater and streamflow in the basin has been difficult to assess due to a limited number of monitoring wells and significant gaps in the water level time history. To address this challenge, we use a novel imputation technique that leverages Earth observations and machine learning to impute gaps in water level records. We use these more complete datasets to compute a groundwater storage change time series for the basin. We show that groundwater storage is highly correlated to streamflow and that groundwater storage is correlated to rainfall with a three- to four-year delay that appears variable depending on groundwater storage volumes. The tools and relationships we present make it possible for water managers to estimate when streamflows will return to the basin and be more informed to support better management.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
