Basin-scale evaluation of current and future climate influences on groundwater variations using satellite and model observations
File version
Version of Record (VoR)
Author(s)
Ndehedehe, Christopher E
Ferreira, Vagner G
Adeyeri, Oluwafemi E
Okwuashi, Onuwa
Kennard, Mark J
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
Size
File type(s)
Location
Abstract
Study region The Murray Darling Basin (MDB), Southeast Australia Study focus An integrated approach involving satellite and model observations is applied to understand groundwater trends in drought-susceptible regions. This research advanced the understanding of hydrological and climatic factors responsible for the groundwater behaviour over the MDB using Gravity Recovery and Climate Experiment (GRACE), Global Land Data Assimilation System (GLDAS) data and in-situ groundwater records. Also, a 5-year forecast of groundwater trends over this region is made using feedforward neural network algorithm. New hydrological insights for the region With the use of new data from the global land water storage model, GLDAS-CLSM-F2.5, and the Australian Water Outlook (AWO) model, an improved understanding of groundwater behaviour over the MDB is revealed. We found that deep drainage (DD), evapotranspiration (ET), and the Oceanic Nino Index (ONI) were major contributors to the drought period witnessed in the region from 2003 to 2009 and from 2013 to 2019, while runoff, El Nino Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) contributed significantly to the wet periods witnessed from 2010 to 2012 and from 2020 to 2024. Also, we observed that the interaction between surface and groundwater storages in the region was minimal during drought episodes but was strongest during the wet seasons, which means that strong connections exist between them. This means that the MDB’s groundwater resources contribute to sustaining streams and surface water during the dry seasons and benefit from infiltration and recharge from surface water resources during the wet seasons. The feedforward neural network algorithm used to predict groundwater in the region showed that the MDB will witness an upward groundwater trend of 0.32 mm/month between 2024 and 2029 based on a 95 % confidence interval.
Journal Title
Journal of Hydrology: Regional Studies
Conference Title
Book Title
Edition
Volume
62
Issue
Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
ARC
Grant identifier(s)
DE230101327
Rights Statement
Rights Statement
© 2025 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Item Access Status
Note
Access the data
Related item(s)
Subject
Groundwater hydrology
Climate change impacts and adaptation
Hydrology
Physical geography and environmental geoscience
Persistent link to this record
Citation
Kalu, I; Ndehedehe, CE; Ferreira, VG; Adeyeri, OE; Okwuashi, O; Kennard, MJ, Basin-scale evaluation of current and future climate influences on groundwater variations using satellite and model observations, Journal of Hydrology: Regional Studies, 2025, 62, pp. 102832