Dynamic Changes in Groundwater Level under Climate Changes in the Gnangara Region, Western Australia

Abstract

The groundwater-dependent ecosystem in the Gnangara region is confronted with great threats due to the decline in groundwater level since the 1970s. The aim of this study is to apply multiple trend analysis methods at 351 monitoring bores to detect the trends in groundwater level using spatial, temporal and Hydrograph Analysis: Rainfall and Time Trend models, which were applied to evaluate the impacts of rainfall on the groundwater level in the Gnangara region, Western Australia. In the period of 1977–2017, the groundwater level decreased from the Gnangara’s edge to the central-north area, with a maximum trend magnitude of −0.28 m/year. The groundwater level in 1998–2017 exhibited an increasing trend in December–March and a decreasing trend in April–November with the exception of September when compared to 1978–1997. The rainfall + time model based on the cumulative annual residual rainfall technique with a one-month lag during 1990–2017 was determined as the best model. Rainfall had great impacts on the groundwater level in central Gnangara, with the highest impact coefficient being 0.00473, and the impacts reduced gradually from the central area to the boundary region. Other factors such as pine plantation, the topography and landforms, the Tamala Limestone formation, and aquifer groundwater abstraction also had important influences on the groundwater level.

Groundwater exhibits spatially opposing trends during the Australian Millennium Drought

“…This decade-long drought severely affected Australia, particularly the southeast (King et al 2020). Problems caused by the long-term drought include dust storms, reduced surface water, well depletion, lower agricultural productivity, forest fires, and higher electricity prices (van Dijk et al 2013, O'Loingsigh et al 2015, Vliet et al 2016, Le Brocque et al 2018, Sheng and Xu 2019, Xu et al 2022.…”

“…In Condamine, a sub-watershed system of MDB, Le Brocque et al (2018) observed decreasing groundwater trends, while Fu et al (2019) examined the roles of both climatic and non-climatic factors in groundwater replenishment in southeastern South Australia (SA). The impact of rainfall on groundwater in Western Australia's Gnangara region was explored by Kong et al (2022), who also considered the effects of vegetation and landforms. Further, analysis of the Murray-Darling Basin's (MDB) alluvial systems by Fu et al (2022) connected groundwater depletion with reduced rainfall and increased evapotranspiration.…”

Assessment of spatial and temporal variability of groundwater level in the aquifer system on the flanks of Mount Meru, Northern Tanzania

“…Groundwater level monitoring is essential for uncovering the spatial-temporal variation of groundwater levels in a studied aquifer, helping discussions on the sustainable use and management of groundwater resources. The spatial-temporal variation of groundwater levels in the aquifer is influenced by a variety of factors such as climate, hydrology, geology and human activities (Cui et al, 2020;Marques et al, 2020;Kong et al, 2022). The different hydrologic factors which can simultaneously play an important role in groundwater level fluctuations can be grouped into two groups: natural and anthropogenic.…”

Groundwater Response to Tide Fluctuation and Rainfall in Coastal Reclamation Area

“…However, this study made a unified assumption for the actual GWL of each slope element, which may lead to deviation in the calculated value and inaccuracy of the model [46]. Kong et al (2022) investigated the variation in the GWL using four trend analysis methods and its response and lag corresponding to rainfall by the HARTT model in the Gnangara region. However, the GWL needs no missing value and is continuous in time to meet the requirements of the model [47].…”

“…Kong et al (2022) investigated the variation in the GWL using four trend analysis methods and its response and lag corresponding to rainfall by the HARTT model in the Gnangara region. However, the GWL needs no missing value and is continuous in time to meet the requirements of the model [47].…”