Evaluating groundwater resources trends through multiple conceptual models and GRACE satellite data

Yidana, Sandow Mark; Dzikunoo, Elikplim Abla; Mejida, Richard Adams; Ackom, Edward Kofi; Chegbeleh, Larry Pax; Loh, Yvonne Sena Akosua; Banoeng-Yakubo, Bruce Kofi; Akabzaa, Thomas Mba

doi:10.1007/s10661-024-12457-w

Cited by 2 publications

(1 citation statement)

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“…For large basins, they developed the GRACE Groundwater Subsetting Tool (GGST) that uses data from the NASA Gravity Recovery and Climate Experiment (GRACE) mission combined with simulated terrestrial water datasets from the Global Land Data Assimilation System (GLDAS) to derive groundwater storage change estimates [34,35]. This system has been used to assess groundwater storage changes resulting from climate change in West Africa and other locations [36][37][38]. While this method works well for large aquifers, the resulting groundwater storage anomaly grid resolution is at a scale of 1o x 1o making it too coarse for use with smaller basins such as the Williamson basin.…”

Section: Prior Researchmentioning

confidence: 99%

Application of a Novel Groundwater Storage Analysis Tool to Assess Drought Impacts in a Groundwater-Driven Basin in the Klamath Watershed, Oregon, USA

Shepard,

Jones,

Williams

2024

Preprint

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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.

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