Data-Driven Approach to Assess Spatial-Temporal Interactions of Groundwater and Precipitation in Choushui River Groundwater Basin, Taiwan

The scarcity of groundwater and precipitation stations has limited accurate assessments of basin-scale groundwater systems. This study proposes a workflow that integrates satellite and on-site observations to improve the spatial and temporal resolution of the groundwater level and enable recharge estimations for the Choushui River groundwater basin (CRGB) in Western Taiwan. The workflow involves multiple data processing steps, including analysis of correlation, evaluation of residuals, and geostatistical interpolation based on kriging methods. The observed groundwater levels and recharge are then the basis to assess spatial-temporal interactions between groundwater and recharge in the CRGB from 2006 to 2015. Results of correlation analyses show the high correlation between the groundwater level and the land surface elevation in the study area. However, the multicollinearity problem exists for the additional precipitation data added in the correlation analyses. The correlation coefficient, root mean square error, and normalized root mean square parameters indicate that the Regression Kriging (RK) performs better the groundwater variations than the Ordinary Kriging (OK) dose. The data-driven approach estimates an annual groundwater recharge of approximately 1.40 billion tons, representing 37% of the yearly precipitation. The correlation between groundwater levels and groundwater recharge exhibits low or negative correlation zones in the groundwater basin. These zones might have resulted from multipurpose pumping activities and the river and drainage networks in the area. The event-based precipitation and groundwater level have shown strong recharge behavior in the low-land area of the basin. Artificial weir operations at the high-land mountain pass might considerably influence the groundwater and surface water interactions.

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Spatio-temporal impact of climate change on the groundwater system

Hydrology and Earth System Sciences ◽

10.5194/hess-16-1517-2012 ◽

2012 ◽

Vol 16 (5) ◽

pp. 1517-1531 ◽

Cited By ~ 38

Author(s):

J. Dams ◽

E. Salvadore ◽

T. Van Daele ◽

V. Ntegeka ◽

P. Willems ◽

...

Keyword(s):

Climate Change ◽

Groundwater Recharge ◽

Groundwater Level ◽

Climate Change Scenarios ◽

Close Monitoring ◽

Reference Period ◽

Groundwater System ◽

Groundwater Levels ◽

Impact Of Climate Change ◽

The Impact

Abstract. Given the importance of groundwater for food production and drinking water supply, but also for the survival of groundwater dependent terrestrial ecosystems (GWDTEs) it is essential to assess the impact of climate change on this freshwater resource. In this paper we study with high temporal and spatial resolution the impact of 28 climate change scenarios on the groundwater system of a lowland catchment in Belgium. Our results show for the scenario period 2070–2101 compared with the reference period 1960–1991, a change in annual groundwater recharge between −20% and +7%. On average annual groundwater recharge decreases 7%. In most scenarios the recharge increases during winter but decreases during summer. The altered recharge patterns cause the groundwater level to decrease significantly from September to January. On average the groundwater level decreases about 7 cm with a standard deviation between the scenarios of 5 cm. Groundwater levels in interfluves and upstream areas are more sensitive to climate change than groundwater levels in the river valley. Groundwater discharge to GWDTEs is expected to decrease during late summer and autumn as much as 10%, though the discharge remains at reference-period level during winter and early spring. As GWDTEs are strongly influenced by temporal dynamics of the groundwater system, close monitoring of groundwater and implementation of adaptive management measures are required to prevent ecological loss.

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The Effect Of Rainfall Relationship periode 2003 – 2013 Of Groundwater South Jakarta Region

Jurnal Lingkungan dan Bencana Geologi ◽

10.34126/jlbg.v11i3.301 ◽

2020 ◽

Vol 11 (3) ◽

pp. 125

Author(s):

Arini Dian ◽

Nana Sulaksana ◽

A. Asseggaf

Keyword(s):

Groundwater Level ◽

Rainy Season ◽

Rainfall Intensity ◽

Rainfall Event ◽

Clean Water ◽

Aquifer System ◽

Groundwater Levels ◽

Groundwater Level Fluctuations ◽

Fine Grained ◽

Groundwater Basin

ABSTRAKKebutuhan air bersih di Jakarta sangat meningkat sehingga pemerintah daerah mulai melakukan pengamatan muka airtanah. Penelitian ini dilakukan dengan menganalisis fluktuasi muka airtanah pada AWLR, intensitas curah hujan, dan penampang bawah permukaan pada beberapa buah titik logbor selama tahun 2003 - 2013 di wilayah Jakarta Selatan. Jumlah curah hujan di daerah penelitian berkisar antara 0,2 - 831,4 mm/bulan. Dari data AWLR dapat diketahui ketinggian muka airtanah berkisar antara 9,29 - 13,97 m aml, terdangkal terjadi pada bulan Oktober - Febuari (ketika musim penghujan) dan ketinggian muka airtanah terdalam berkisar antara14,60 - 20,41 m aml terjadi pada bulan Maret - September (ketika musim kemarau). Penelitian ini dilakukan untuk mengidentifikasi adanya pengaruh hubungan curah hujan dan muka airtanah dengan karakteristik sistem akuifer yang berada pada daerah penelitian sekitarnya khususnya di Jakarta Selatan. Berdasarkan analisis tenggang waktu dan fluktuasi muka airtanah yang dipengaruhi oleh intensitas curah hujan.Serta adanya lapisan akuitar pada penampang geologi dan posisi muka airtanah yang terdapat dibagian atas lapisan akuifer, maka dapat dikatakan bahwa sistem akuifer yang terdapat di daerah penelitian bersifat semi tertekan. Sistem akuifer tersebut pada bagian atasnya merupakan material berbutir halus (akuitar) sehingga airtanah masih memungkinkan untuk bergerak di dalamnya.Kata kunci: airtanah, AWLR, curah hujan, fluktuasi, JakartaABSTRACTThe need for clean water in Jakarta has increased significantly, so the groundwater levels of Jakarta Groundwater Basin need to be researched. This research was conducted by analyzing the fluctuation of the groundwater level using the AWLR data, rainfall intensity, and subsurface sections to several logbor during the year of 2003 - 2013 in South Jakarta area. Rainfall event in the area is in range of 0.2 mm/year up to 831.4 mm/year. From the AWLR data, the highest groundwater level were at 9.29 - 13.97 masl in October - Febuari (during rainy season) and the deepest groundwater level were at 14.60 - 20.41 masl) in March - September (during dry season). Based on the analysis of the timescale and the groundwater level fluctuations that influenced by rainfall, and the aquitard layer in the geology section, and groundwater level exist above the aquifer, so that the aquifer system in this regions is classified as semi depressed aquifer. In this aquifer system, the underlying material is fine grained (aquitard) that allows groundwater moving inside the layer.Keywords: groundwater, AWLR, rainfall, fluctuation, Jakarta

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Optimal Missing Value Estimation Algorithm for Groundwater Levels

Proceedings ◽

10.3390/proceedings2110698 ◽

2018 ◽

Vol 2 (11) ◽

pp. 698 ◽

Cited By ~ 1

Author(s):

Klemen Kenda ◽

Filip Koprivec ◽

Dunja Mladenić

Keyword(s):

Missing Data ◽

Missing Values ◽

Estimation Algorithm ◽

Data Driven ◽

Data Imputation ◽

Missing Data Imputation ◽

Groundwater Levels ◽

Data Driven Approach ◽

Value Estimation ◽

Missing Value Estimation

In this study an algorithm for missing data imputation is presented. The algorithm uses measurements from neighboring sensors to estimate the missing values. Data-driven approach is used and methodology chooses the optimal available combination of modeling algorithm and available measurements to produce an estimate from the model with lowest error. The methodology was tested on Ljubljana polje aquifer data and has produced close to perfect results.

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Groundwater recharge trends in CanadaGeological Survey of Canada Contribution 20090009.

Canadian Journal of Earth Sciences ◽

10.1139/e09-056 ◽

2009 ◽

Vol 46 (11) ◽

pp. 841-854 ◽

Cited By ~ 22

Author(s):

Christine Rivard ◽

Harold Vigneault ◽

Andrew R. Piggott ◽

Marie Larocque ◽

François Anctil

Keyword(s):

Groundwater Recharge ◽

Groundwater Level ◽

Data Sets ◽

Series Length ◽

Groundwater Levels ◽

Monitoring Wells ◽

Historical Series ◽

Social And Economic Development ◽

Level Versus ◽

Southern Half

Groundwater plays a major role in social and economic development and in human and ecosystem health. However, little is known about the potential impacts of climate change on this resource in Canada, namely if groundwater recharge is increasing or decreasing over time. This paper focuses on trend statistical analysis of historical series of baseflow and groundwater levels and their field significance as indicators of recharge. Monitoring wells are mainly located in the southern half of western Canada, where few gauging stations either are available or provide significant trends. Both data sets are thus complementary. Results show that most available groundwater level series have significant trends (80%), whereas most available baseflow series have not (3%–33%). However, groundwater level series usually show smaller slope magnitudes than baseflow series. Mixed trends are often observed across Canada for a given variable, period, or series length, although some regions can have marked trends. For instance, values below the 55°N latitude, and especially values in Atlantic Canada, show mostly downward trends (decreasing recharge). Values north of the 55° parallel often show upward trends. All groundwater level results are field significant at the 10% level, versus only 35% for baseflow results, but they show mixed results. Baseflow values show a majority of downward trends for annual values and the summer period for 40- and 50-year series, thus showing field significance, whereas mixed results are observed for 30-year series and the spring, fall, and winter seasons.

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Spatio-temporal impact of climate change on the groundwater system

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-8-10195-2011 ◽

2011 ◽

Vol 8 (6) ◽

pp. 10195-10223 ◽

Cited By ~ 4

Author(s):

J. Dams ◽

E. Salvadore ◽

T. Van Daele ◽

V. Ntegeka ◽

P. Willems ◽

...

Keyword(s):

Climate Change ◽

Groundwater Recharge ◽

Groundwater Level ◽

Climate Change Scenarios ◽

Close Monitoring ◽

Reference Period ◽

Groundwater System ◽

Groundwater Levels ◽

Impact Of Climate Change ◽

The Impact

Abstract. Given the importance of groundwater for food production and drinking water supply, but also for the survival of groundwater dependent terrestrial ecosystems (GWDTEs) it is essential to assess the impact of climate change on this freshwater resource. In this paper we study with high temporal and spatial resolution the impact of 28 climate change scenarios on the groundwater system of a lowland catchment in Belgium. Our results show for the scenario period 2070–2101 compared with the reference period 1960–1991, a change in annual groundwater recharge between −20% and +7%. On average annual groundwater recharge decreases 7%. Seasonally, in most scenarios the recharge increases during winter but decreases during summer. The altered recharge patterns cause the groundwater level to decrease significantly from September to January. On average the groundwater level decreases about 7 cm with a standard deviation between the scenarios of 5 cm. Groundwater levels in interfluves and upstream areas are more sensitive to climate change than groundwater levels in the river valley. Groundwater discharge to GWDTEs is expected to decrease during late summer and autumn as much as 10%, though the discharge remains at reference-period level during winter and early spring. As GWDTEs are strongly influenced by temporal dynamics of the groundwater system, close monitoring of groundwater and implementation of adaptive management measures are required to prevent ecological loss.

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APLIKASI GEOSPASIAL ANALISIS UNTUK PENENTUAN ZONA IMBUHAN AIRTANAH DI CAT WONOSOBO, PROVINSI JAWA TENGAH

Jurnal Tataloka ◽

10.14710/tataloka.19.3.175-191 ◽

2017 ◽

Vol 19 (3) ◽

pp. 175 ◽

Cited By ~ 2

Author(s):

Thomas Triadi Putranto ◽

Wahju Krishna Hidajat ◽

Annita Kusuma Wardhani

Keyword(s):

Hydraulic Conductivity ◽

Groundwater Recharge ◽

Groundwater Management ◽

Groundwater Level ◽

Soil Type ◽

Soil Cover ◽

Groundwater Discharge ◽

Geospatial Analysis ◽

Discharge Zone ◽

Groundwater Basin

Groundwater is the valuable resources for supplying daily necessity of human’s life that is going to increase in line with the increasing number of population. Therefore, groundwater needs to be well managed. Groundwater management can be done thoroughly within a groundwater basin for defining groundwater recharge zone. The groundwater recharge zone was conducted by applying geospatial analysis using weighted and scoring approach. This method was accomplished by overlaying the score of some parameters (hydraulic conductivity, precipitation, soil cover, slope, and groundwater depth of water table) using ArcGIS 10.3 software. The parameters were permeability of rocks, rainfall, soil type, slope and depth of superficial groundwater level. The result of geospatial analysis can be divided into two zones which are groundwater recharge zone and groundwater discharge zone.

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

Water Science & Technology Water Supply ◽

10.2166/ws.2020.015 ◽

2020 ◽

Vol 20 (3) ◽

pp. 909-921 ◽

Cited By ~ 3

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.

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