Impact of Groundwater Level Change on Natural Frequencies of RC Buildings

Structural health monitoring (SHM) provides an opportunity to assess and predict changes in the technical condition of structures during the operation of a building. Structural damage, as well as several operational and environmental conditions, causes changes in modal parameters. Temperature is the most popular environmental condition which is used for research. However, to the authors’ knowledge, this is the first investigation that highlights the effect of groundwater level change on the natural frequencies of the buildings and the impact of possible damage detection features. Groundwater level change can influence structural health monitoring measurements and cause faulty structural damage identification using vibration-based methods. This paper aims to analyse the impact of the groundwater level changes on the modal parameters of mid-rise reinforced concrete buildings. The modal parameters of mid-rise reinforced concrete buildings are determined using finite element (FE) models. Three different FE models of structural system types of nine-storey reinforced concrete (RC) buildings with shallow foundations are used to determine the impact of groundwater level fluctuation on the values of the buildings’ natural frequencies. Changes in the groundwater level have an impact on the natural frequencies of the mid-rise reinforced concrete buildings. This research proposes a new environmental condition that has to be considered to identify the structural damage using the vibration-based method. It is found that groundwater level rise causes a decrease in the natural frequency value. In this research, it is established that the influence of the groundwater level on the natural frequencies of the buildings can change abruptly, and there is a non-linear correlation between groundwater level change and natural frequencies of the buildings. The natural frequencies of the buildings can change under varying environmental conditions as well as in the case of structural damage. To identify structural damage in the long-term structural health monitoring measurements, it is recommended to select features which are sensitive to structural damage but are not affected by groundwater level change. Data normalisation and elimination using linear correlation methods can be used for short-term SHM under varying seasonal groundwater level change.

The Relationship between Surface Displacement and Groundwater Level Change and Its Hydrogeological Implications in an Alluvial Fan: Case Study of the Choshui River, Taiwan

Balancing the demand of groundwater resources and the mitigation of land subsidence is particularly important, yet challenging, in populated alluvial fan areas. In this study, we combine multiple monitoring data derived from Multi-Temporal InSAR (MTI), GNSS (Global Navigation Satellite System), precise leveling, groundwater level, and compaction monitoring wells, in order to analyze the relationship between surface displacement and groundwater level change within the alluvial fan of the Choshui River in Taiwan. Our combined time-series analyses suggest, in a yearly time scale, that groundwater level increases with the vertical surface displacement when the effect of pore water pressure dominates. Conversely, this relationship is negative when the effect of water-mass loading predominates over pore water pressure. However, the correlation between the vertical surface displacement and the groundwater level change is consistently positive over the time scale of two decades. It is interpreted that the alluvial fan sequence in the subsurface is not fully elastic, and compaction is greater than rebound in this process. These findings were not well reported and discussed by previous studies because of insufficient monitoring data and analyses. Understanding the combined effect of groundwater level change and vertical surface displacement is very helpful for management of land subsidence and usage of groundwater resources. The spatial and temporal integration of multi-sensors can be applied to overcome the limitations associated with the single technique and provides further insights into land surface changes, particularly in highly populated alluvial fan areas.

Seasonal and transient surface displacements in the Kumamoto area, Japan, associated with the 2016 Kumamoto earthquake: implications for seismic-induced groundwater level change

The 2016 Kumamoto earthquake sequence on April 14 (Mw 6.2) and April 16 (Mw 7.0) altered the regional groundwater level. To better understand the relationship between groundwater level change and surface displacement, we estimated surface displacement in the Kumamoto area (Japan) using persistent scatterer interferometry from 19 ALOS/PALSAR images acquired between January 7, 2007 and March 5, 2011, 28 ALOS-2/PALSAR-2 images acquired between April 17, 2016 and December 10, 2018, and 113 Sentinel-1 images acquired between May 26, 2016 and December 30, 2018. Our estimation shows that transient surface displacement occurred following the 2016 Kumamoto earthquake sequence, together with seasonal surface displacement that was not detected from the 2007–2011 images. We suggest that a portion of the transient displacement occurred via groundwater drawdown through new ruptures that formed owing to the 2016 Kumamoto earthquake sequence and sediment compaction. Seasonal surface displacements detected after the 2016 Kumamoto earthquake sequence are linked to groundwater level variations.

Importance of spatial and depth-dependent drivers in groundwater level modeling through machine learning

The water and food security of South Asia is embedded in the groundwater resources of the transboundary aquifer system of Indus-Ganges-Brahmaputra-Meghna (IGBM) rivers, which has been subjected to diverse natural and anthropogenic triggers. Thus, understanding the relative importance of such triggers in groundwater level change and developing a prediction framework is essential to sustain future stress. Although a number of studies on groundwater level prediction and simulation exist in the literature, characterization of predictive performances of groundwater level modeling using a large network of ground-based observations (n = 2303) is not yet reported. To identify the spatial and depth-wise predictors influence, here, we used linear regression based dominance analysis and machine learning methods (Support Vector Machine and Artificial Neural network) on long term (1985–2015) GWLs and/or climatic variables in the parts of IGBM basin aquifers. The results from the dominance analysis show that groundwater level change is primarily influenced by abstraction and population in most of the IGBM, whereas in the Brahmaputra basin, precipitation exhibits greater influence. Our results show a large proportion of the observation wells (n > 50 % for ANN and n > 65 % for SVM) demonstrate good correlation (r > 0.6, p 0.65), and normalized root mean square error (RMSEn

The research of Meinong earthquake induced hydrological anomalies and increased vertical permeability in southwestern Taiwan

<p>Hydrological anomalies induced by the earthquakes are valuable research data to understand the hydrogeology structure. At the same time, a complete hydrogeological data is the key to the study of earthquake hydrology. In this research, we collected the anomalous hydrological data after the M<sub>w</sub> 6.4 2016 Meinong Earthquake in Taiwan. The main purpose is to know the mechanism of hydrological changes triggered by earthquake and understand the local hydrogeological characteristics in the southern Taiwan.</p><p>From the distribution of the groundwater level change in the same location but different depths of aquifer, as well as the location of the rupture and liquefaction, it could be found that the co-seismic groundwater level change is large in Chianan Plain in the northwest of the epicenter and accompanied with a lot of ruptures and liquefactions located along the Hsinhua Fault. However, the observations in several wells around the Hsinhua Fault show a different water level change pattern compared with the other wells in Chianan Plain. Actually, these wells show that the co-seismic groundwater level decreases in the deep aquifer and increase in the shallow aquifer. It is shown that the Meinong Earthquake may enhance the connectivity between different aquifers near the fault zone and produce an increased vertical pressure gradient. The anomalous hydrological phenomenon also reflected in the river flow. Based on the river flow data we collected from five stations in the Zengwun River watershed, the river flow at two stations in the upstream dose not change after earthquake. There is a little increase at the midstream station. However, a large river flow increase is observed at the downstream station. After excluding the influence of rainfall, we think that the large amount of anomalous flow is caused by the rise of the co-seismic groundwater level between the middle and downstream sections, and a large amount of liquefaction in this area can prove this hypothesis.</p><p>The hypothesis of connectivity changes between different aquifers can be verified by analyzing the tidal response of different aquifers. Many studies have used the tide analysis to obtain the aquifer permeability and compressibility, and compared the changes in the analysis results before and after the earthquake. We think that if different aquifers are vertically connected after earthquake, the tidal analysis results should show a consistent permeability. Tidal analysis is executing now and the results will be provided at conference.</p>