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

2020 ◽  
Author(s):  
Pragnaditya Malakar ◽  
Abhijit Mukherjee ◽  
Soumendra N. Bhanja ◽  
Dipankar Saha ◽  
Ranjan Kumar Ray ◽  
...  
Keyword(s):  
Machine Learning ◽  
Groundwater Level ◽  
Groundwater Resources ◽  
Support Vector ◽  
Large Network ◽  
Dominance Analysis ◽  
Aquifer System ◽  
Level Change ◽  
Prediction And Simulation ◽  
Groundwater Level Change

Abstract. 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 

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

2020 ◽  
Vol 12 (20) ◽  
pp. 3315
Author(s):  
Chiao-Yin Lu ◽  
Jyr-Ching Hu ◽  
Yu-Chang Chan ◽  
Yuan-Fong Su ◽  
Chih-Hsin Chang
Keyword(s):  
Groundwater Level ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Groundwater Resources ◽  
Surface Displacement ◽  
Vertical Surface ◽  
Alluvial Fan ◽  
Level Change ◽  
The Relationship ◽  
Groundwater Level Change

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.

scholarly journals Seismically induced changes in groundwater levels and temperatures following the ML5.8 (ML5.1) Gyeongju earthquake in South Korea

2021 ◽  
Author(s):  
Soo-Hyoung Lee ◽  
Jae Min Lee ◽  
Sang-Ho Moon ◽  
Kyoochul Ha ◽  
Yongcheol Kim ◽  
...  
Keyword(s):  
South Korea ◽  
Groundwater Level ◽  
Seismic Waves ◽  
Groundwater Resources ◽  
Fluid Pressure ◽  
Water Levels ◽  
Aquifer System ◽  
Groundwater Levels ◽  
Monitoring Wells ◽  
Gyeongju Earthquake

AbstractHydrogeological responses to earthquakes such as changes in groundwater level, temperature, and chemistry, have been observed for several decades. This study examines behavior associated with ML 5.8 and ML 5.1 earthquakes that occurred on 12 September 2016 near Gyeongju, a city located on the southeast coast of the Korean peninsula. The ML 5.8 event stands as the largest recorded earthquake in South Korea since the advent of modern recording systems. There was considerable damage associated with the earthquakes and many aftershocks. Records from monitoring wells located about 135 km west of the epicenter displayed various patterns of change in both water level and temperature. There were transient-type, step-like-type (up and down), and persistent-type (rise and fall) changes in water levels. The water temperature changes were of transient, shift-change, and tendency-change types. Transient changes in the groundwater level and temperature were particularly well developed in monitoring wells installed along a major boundary fault that bisected the study area. These changes were interpreted as representing an aquifer system deformed by seismic waves. The various patterns in groundwater level and temperature, therefore, suggested that seismic waves impacted the fractured units through the reactivation of fractures, joints, and microcracks, which resulted from a pulse in fluid pressure. This study points to the value of long-term monitoring efforts, which in this case were able to provide detailed information needed to manage the groundwater resources in areas potentially affected by further earthquakes.

scholarly journals Assessing the long-term sustainability of the groundwater resources in the Bacchiglione basin (Veneto, Italy) with the Mann–Kendall test: suggestions for higher reliability

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Mara Meggiorin ◽  
Giulia Passadore ◽  
Silvia Bertoldo ◽  
Andrea Sottani ◽  
Andrea Rinaldo
Keyword(s):  
Groundwater Level ◽  
Water Cycle ◽  
Groundwater Resources ◽  
Sustainable Use ◽  
Kendall Test ◽  
Groundwater System ◽  
Aquifer System ◽  
Mann Kendall Test ◽  
Status Assessment

The social, economic, and ecological importance of the aquifer system within the Bacchiglione basin (Veneto, IT) is noteworthy, and there is considerable disagreement among previous studies over its sustainable use. Investigating the long-term quantitative sustainability of the groundwater system, this study presents a statistical methodology that can be applied to similar cases. Using a combination of robust and widely used techniques, we apply the seasonal Mann–Kendall test and the Sen’s slope estimator to the recorded groundwater level timeseries. The analysis is carried out on a large and heterogeneous proprietary dataset gathering hourly groundwater level timeseries at 79 control points, acquired during the period 2005–2019. The test identifies significant decreasing trends for most of the available records, unlike previous studies on the quantitative status of the same resource which covered the domain investigated here for a slightly different period: 2000–2014. The present study questions the reason for such diverging results by focusing on the method’s accuracy. After carrying out a Fourier analysis on the longest available timeseries, for studies of groundwater status assessment this work suggests applying the Mann–Kendall test to timeseries longer than 20 years (because otherwise the analysis would be affected by interannual periodicities of the water cycle). A further analysis of two 60-year-long monthly timeseries between 1960 and 2020 supports the actual sustainable use of the groundwater resource, the past deployment of the groundwater resources notwithstanding. Results thus prove more reliable, and meaningful inferences on the longterm sustainability of the groundwater system are possible.

scholarly journals Assessing the suitability of extreme learning machines (ELM) for groundwater level prediction

2017 ◽  
Vol 32 (1) ◽  
pp. 103-112 ◽  
Author(s):  
Basant Yadav ◽  
Sudheer Ch ◽  
Shashi Mathur ◽  
Jan Adamowski
Keyword(s):  
Soft Computing ◽  
Groundwater Level ◽  
Groundwater Resources ◽  
Support Vector ◽  
Complex Nature ◽  
Data Set ◽  
Groundwater Levels ◽  
Soft Computing Techniques ◽  
Learning Machine ◽  
The Comparative Study

Abstract Fluctuation of groundwater levels around the world is an important theme in hydrological research. Rising water demand, faulty irrigation practices, mismanagement of soil and uncontrolled exploitation of aquifers are some of the reasons why groundwater levels are fluctuating. In order to effectively manage groundwater resources, it is important to have accurate readings and forecasts of groundwater levels. Due to the uncertain and complex nature of groundwater systems, the development of soft computing techniques (data-driven models) in the field of hydrology has significant potential. This study employs two soft computing techniques, namely, extreme learning machine (ELM) and support vector machine (SVM) to forecast groundwater levels at two observation wells located in Canada. A monthly data set of eight years from 2006 to 2014 consisting of both hydrological and meteorological parameters (rainfall, temperature, evapotranspiration and groundwater level) was used for the comparative study of the models. These variables were used in various combinations for univariate and multivariate analysis of the models. The study demonstrates that the proposed ELM model has better forecasting ability compared to the SVM model for monthly groundwater level forecasting.

scholarly journals Spatial variation of groundwater response to multiple drivers in a depleting alluvial aquifer system, northwestern India

2019 ◽  
Vol 44 (1) ◽  
pp. 94-119 ◽  
Author(s):  
Wout M van Dijk ◽  
Alexander L Densmore ◽  
Christopher R Jackson ◽  
Jonathan D Mackay ◽  
Suneel K Joshi ◽  
...  
Keyword(s):  
Groundwater Level ◽  
Potential Evapotranspiration ◽  
Groundwater Resources ◽  
Alluvial Aquifer ◽  
Groundwater Depletion ◽  
Impulse Response Functions ◽  
Canal Irrigation ◽  
Geological Heterogeneity ◽  
Aquifer System ◽  
Northwestern India

Unsustainable exploitation of groundwater in northwestern India has led to extreme but spatially variable depletion of the alluvial aquifer system in the region. Mitigation and management of groundwater resources require an understanding of the drivers behind the pattern and magnitude of groundwater depletion, but a regional perspective on these drivers has been lacking. The objectives of this study are to (1) understand the extent to which the observed pattern of groundwater level change can be explained by the drivers of precipitation, potential evapotranspiration, abstraction, and canal irrigation, and (2) understand how the impacts of these drivers may vary depending on the underlying geological heterogeneity of the system. We used a transfer function-noise (TFN) time series approach to quantify the effect of the various driver components in the period 1974–2010, based on predefined impulse response functions ( θ). The dynamic response to abstraction, summarized by the zeroth moment of the response M0, is spatially variable but is generally large across the proximal and middle parts of the study area, particularly where abstraction is high but alluvial aquifer bodies are less abundant. In contrast, the precipitation response is rapid and fairly uniform across the study area. At larger distances from the Himalayan front, observed groundwater level rise can be explained predominantly by canal irrigation. We conclude that the geological heterogeneity of the aquifer system, which is imposed by the geomorphic setting, affects the response of the aquifer system to the imposed drivers. This heterogeneity thus provides a useful framework that can guide mitigation efforts; for example, efforts to decrease abstraction rates should be focused on areas with thinner and less abundant aquifer bodies.

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