scholarly journals Self-optimizer data-mining method for aquifer level prediction

2019 ◽  
Vol 20 (2) ◽  
pp. 724-736
Author(s):  
Omid Bozorg-Haddad ◽  
Mohammad Delpasand ◽  
Hugo A. Loáiciga
Keyword(s):  
Groundwater Level ◽  
Hybrid Algorithm ◽  
Water Source ◽  
Support Vector ◽  
Mining Method ◽  
Parameter Calibration ◽  
Groundwater Levels ◽  
Municipal Water Supply ◽  
Predictive Skill ◽  
Observation Wells

Abstract Groundwater management requires accurate methods for simulating and predicting groundwater processes. Data-based methods can be applied to serve this purpose. Support vector regression (SVR) is a novel and powerful data-based method for predicting time series. This study proposes the genetic algorithm (GA)–SVR hybrid algorithm that combines the GA for parameter calibration and the SVR method for the simulation and prediction of groundwater levels. The GA–SVR algorithm is applied to three observation wells in the Karaj plain aquifer, a strategic water source for municipal water supply in Iran. The GA–SVR's groundwater-level predictions were compared to those from genetic programming (GP). Results show that the randomized approach of GA–SVR prediction yields R2 values ranging between 0.88 and 0.995, and root mean square error (RMSE) values ranging between 0.13 and 0.258 m, which indicates better groundwater-level predictive skill of GA-SVR compared to GP, whose R2 and RMSE values range between 0.48–0.91 and 0.15–0.44 m, respectively.

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 Modelling groundwater level fluctuation in an Indian coastal aquifer

Water SA ◽  
2020 ◽  
Vol 46 (4 October) ◽  
Author(s):  
Safieh Javadinejad ◽  
Rebwar Dara ◽  
Forough Jafary
Keyword(s):  
Groundwater Level ◽  
Coastal Aquifer ◽  
M5 Model Tree ◽  
Groundwater Levels ◽  
Proposed Model ◽  
Soft Computing Techniques ◽  
Input Variables ◽  
Lag Times ◽  
Observation Wells

Estimating groundwater level (GWL) fluctuations is a vital requirement in hydrology and hydraulic engineering, and is commonly addressed through artificial intelligence (AI) models. The purpose of this research was to estimate groundwater levels using new modelling methods. The implementation of two separate soft computing techniques, a multilayer perceptron neural network (MLPNN) and an M5 model tree (M5-MT), was examined. The models are used in the estimation of monthly GWLs observed in a shallow unconfined coastal aquifer. Data for the water level were collected from observation wells located near Ganjimatta, India, and used to estimate GWL fluctuation. To do this, two scenarios were provided to achieve optimal input variables for modelling the GWL at the present time. The input parameters applied for developing the proposed models were a monthly time-series of summed rainfall, the mean temperature (within its lag times that have an effect on groundwater), and historical GWL observations throughout the period 1996–2006. The efficiency of each proposed model for Ganjimatt was investigated in stages of trial and error. A performance evaluation showed that the M5-MT outperformed the MLPNN model in estimating the GWL in the aquifer case study. Based on the M5-MT approach, the development of this model gives acceptable results for the Indian coastal aquifers. It is recommended that water managers and decision makers apply these new methods to monitor groundwater conditions and inform future planning.

scholarly journals Comparing Approaches for Reconstructing Groundwater Levels in the Mountainous Regions of Interior British Columbia, Canada, Using Tree Ring Widths

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1374
Author(s):  
Stephanie C. Hunter ◽  
Diana M. Allen ◽  
Karen E. Kohfeld
Keyword(s):  
British Columbia ◽  
Tree Ring ◽  
Groundwater Level ◽  
High Elevation ◽  
Valuable Insight ◽  
Driven Systems ◽  
Groundwater Levels ◽  
Mountainous Regions ◽  
Tree Ring Data ◽  
Observation Wells

Observed groundwater level records are relatively short (<100 years), limiting long-term studies of groundwater variability that could provide valuable insight into climate change effects. This study uses tree ring data from the International Tree Ring Database (ITRDB) and groundwater level data from 22 provincial observation wells to evaluate different approaches for reconstructing groundwater levels from tree ring widths in the mountainous southern interior of British Columbia, Canada. The twenty-eight reconstruction models consider the selection of observation wells (e.g., regional average groundwater level vs. wells classified by recharge mechanism) and the search area for potential tree ring records (climate footprint vs. North American Ecoregions). Results show that if the climate footprint is used, reconstructions are statistically valid if the wells are grouped according to recharge mechanism, with streamflow-driven and high-elevation recharge-driven wells (both snowmelt-dominated) producing valid models. Of all the ecoregions considered, only the Coast Mountain Ecoregion models are statistically valid for both the regional average groundwater level and high-elevation recharge-driven systems. No model is statistically valid for low-elevation recharge-driven systems (rainfall-dominated). The longest models extend the groundwater level record to the year 1500, with the highest confidence in the later portions of the reconstructions going back to the year 1800.

Comparison study of artificial intelligence method for short term groundwater level prediction in the northeast Gachsaran unconfined aquifer

2020 ◽  
Vol 20 (3) ◽  
pp. 909-921 ◽  
Author(s):  
Akbar Khedri ◽  
Nasrollah Kalantari ◽  
Meysam Vadiati
Keyword(s):  
Groundwater Level ◽  
Unconfined Aquifer ◽  
Least Square ◽  
Data Driven ◽  
Coefficient Of Determination ◽  
Support Vector ◽  
Data Set ◽  
Groundwater Levels ◽  
Statistical Performance Evaluation ◽  
Groundwater Level Prediction

Abstract Accurate and reliable groundwater level prediction is an important issue in groundwater resource management. The objective of this research is to compare groundwater level prediction of several data-driven models for different prediction periods. Five different data-driven methods are compared to evaluate their performances to predict groundwater levels with 1-, 2- and 3-month lead times. The four quantitative standard statistical performance evaluation measures showed that while all models could provide acceptable predictions of groundwater level, the least square support vector machine (LSSVM) model was the most accurate. We developed a set of input combinations based on different levels of groundwater, total precipitation, average temperature and total evapotranspiration at monthly intervals. For each model, the antecedent inputs that included Ht-1, Ht-2, Ht-3, Tt, ETt, Pt, Pt-1 produced the best-fit model for 1-month lead time. The coefficient of determination (R2) and the root mean square error (RMSE) were calculated as 0.99%, 1.05 meters for the train data set, and 95%, 2.3 meters for the test data set, respectively. It was also demonstrated that many combinations the above-mentioned approaches could model groundwater levels for 1 and 2 months ahead appropriately, but for 3 months ahead the performance of the models was not satisfactory.

Reactivity of southern Quebec aquifers to meteorological and hydrological conditions

2021 ◽  
Author(s):  
Trong Ahn Vu ◽  
Marie Larocque ◽  
Sylvain Gagné ◽  
Marc-André Bourgault
Keyword(s):  
Land Use ◽  
Groundwater Level ◽  
River Flow ◽  
Correlation Coefficients ◽  
Flow Rates ◽  
Groundwater Levels ◽  
Hydrological Conditions ◽  
Observation Network ◽  
Observation Wells

&lt;p&gt;Groundwater represents an important source of drinking water for 25% of the population in the province of Quebec (Canada) and for 80% of its rural population. The deployment of the Quebec Groundwater Observation Network (R&amp;#233;seau de suivi des eaux souterraines du Qu&amp;#233;bec &amp;#8211; RSESQ) since the start of the millennia provides important data on the dynamics of piezometric heads throughout southern Quebec. This study aims to use the wealth of available groundwater data available to better understand the resilience of groundwater resources to changes in meteorological and hydrological conditions. The study area is located between the St. Lawrence River and the Canada-USA border, and between the Quebec-Ontario border and Quebec City (36,000 km&amp;#178;). Available data consist of groundwater level time series from 81 observation wells (2000-2018; 43 in confined aquifers, 15 in semi-confined aquifers and 23 in unconfined aquifers), total flow rates from 179 hydrometric stations (1960-2017), and meteorological data from a spatially interpolated 10&amp;#160;km&amp;#160;x&amp;#160;10&amp;#160;km&amp;#160;grid (1960-2017). Statistical analyses (Mann Kendall and Sen&amp;#8217;s slope) were used to understand if groundwater levels and flow rates are declining or rising, what is their short-, medium- and long-term memory and what are the geomorphological, land use, and climate controls of this reactivity. The results show that groundwater levels since 2007 exhibit statistically significant negative annual trends for most observation wells. Since 1960, river flow rates, total precipitation and air temperature all show significant increases. Trends calculated on five-year sliding windows confirm that groundwater levels and river flow rates are significantly correlated to the climate indices Southern Oscillation index (SOI), NINO-3 and Pacific Decadal Oscillation index (PDO). Autocorrelations of flow rates and groundwater level data indicate that rivers and aquifers have a short hydrological memory rarely extending beyond the hydrological year. Cross-correlations of flow rates and groundwater levels with temperature show high correlation coefficients with a lag of up to 60 days, indicating a season-long effect of temperature changes. As expected, cross-correlation analysis of the two data sets with precipitation shows smaller correlation coefficients and a shorter reaction time (10 days). Standard deviations of daily groundwater levels are significantly higher in shallower wells and in wells where groundwater levels are closer to the ground. This confirms the presence of highly dynamic shallow aquifers reacting rapidly to surface processes. &amp;#160;Analyses are under way to test if spatially distributed parameters (e.g., geological setting, slope, land use) and well-related parameters (e.g.: depth, confined or unconfined) are explaining factors of trends and variations in groundwater levels and flow rates. One key observation from this study is that the RSESQ is highly valuable to understand groundwater dynamics and should be maintained on a long-term horizon. This detailed analysis has allowed to identify external influences (e.g., pumping) on some observation wells that do not reflect natural conditions and could be removed from the observation network. Recommendations also include the need for new observation wells in specific locations to improve the representativity of groundwater flow conditions in the study area.&lt;/p&gt;

scholarly journals Investigating Groundwater Condition and Seawater Intrusion Status in Coastal Aquifer Systems of Eastern India

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1952
Author(s):  
Subrata Halder ◽  
Lingaraj Dhal ◽  
Madan K. Jha
Keyword(s):  
Groundwater Quality ◽  
Seawater Intrusion ◽  
Groundwater Level ◽  
Coastal Aquifer ◽  
Quality Data ◽  
Confined Aquifer ◽  
Groundwater Levels ◽  
Post Monsoon ◽  
Aquifer Systems ◽  
Sustainable Water Supply

Providing sustainable water supply for domestic needs and irrigated agriculture is one of the most significant challenges for the current century. This challenge is more daunting in coastal regions. Groundwater plays a pivotal role in addressing this challenge and hence, it is under growing stress in several parts of the world. To address this challenge, a proper understanding of groundwater characteristics in an area is essential. In this study, spatio-temporal analyses of pre-monsoon and post-monsoon groundwater-levels of two coastal aquifer systems (upper leaky confined and underlying confined) were carried out in Purba Medinipur District, West Bengal, India. Trend analysis of seasonal groundwater-levels of the two aquifers systems was also performed using Mann-Kendall test, Linear Regression test, and Innovative Trend test. Finally, the status of seawater intrusion in the two aquifers was evaluated using available groundwater-quality data of Chloride (Cl−) and Total Dissolve Solids (TDS). Considerable spatial and temporal variability was found in the seasonal groundwater-levels of the two aquifers. Further, decreasing trends were spotted in the pre-monsoon and post-monsoon groundwater-level time series of the leaky confined and confined aquifers, except pre-monsoon groundwater-levels in Contai-I and Deshpran blocks, and the post-monsoon groundwater-level in Ramnagar-I block for the leaky confined aquifer. The leaky confined aquifer in Contai-I, Contai-III, and Deshpran blocks and the confined aquifer in Nandigram-I and Nandigram-II blocks are vulnerable to seawater intrusion. There is an urgent need for the real-time monitoring of groundwater-levels and groundwater quality in both the aquifer systems, which can ensure efficient management of coastal groundwater reserves.

scholarly journals Evaluation of Seasonal Groundwater Quality Changes Associated with Groundwater Pumping and Level Fluctuations in an Agricultural Area, Korea

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 51
Author(s):  
Kyoochul Ha ◽  
Eunhee Lee ◽  
Hyowon An ◽  
Sunghyun Kim ◽  
Changhui Park ◽  
...  
Keyword(s):  
Water Quality ◽  
Groundwater Quality ◽  
Groundwater Level ◽  
Irrigation Water ◽  
Agricultural Area ◽  
Water Type ◽  
Quality Changes ◽  
Groundwater Pumping ◽  
Rice Paddies ◽  
Groundwater Levels

This study was conducted to evaluate seasonal groundwater quality due to groundwater pumping and hydrochemical characteristics with groundwater level fluctuations in an agricultural area in Korea. Groundwater levels were observed for about one year using automatic monitoring sensors, and groundwater uses were estimated based on the monitoring data. Groundwater use in the area is closely related to irrigation for rice farming, and rising groundwater levels occur during the pumping, which may be caused by the irrigation water of rice paddies. Hydrochemical analysis results for two separate times (17 July and 1 October 2019) show that the dissolved components in groundwater decreased overall due to dilution, especially at wells in the alluvial aquifer and shallow depth. More than 50% of the samples were classified as CaHCO3 water type, and changes in water type occurred depending on the well location. Water quality changes were small at most wells, but changes at some wells were evident. In addition, the groundwater quality was confirmed to have the effect of saltwater supplied during the 2018 drought by comparison with seawater. According to principal component analysis (PCA), the water quality from July to October was confirmed to have changed due to dilution, and the effect was strong at shallow wells. In the study areas where rice paddy farming is active in summer, irrigation water may be one of the important factors changing the groundwater quality. These results provide a qualitative and quantitative basis for groundwater quality change in agricultural areas, particularly rice paddies areas, along with groundwater level and usage.

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.

Sign in / Sign up

Export Citation Format

Share Document