scholarly journals Evaluation of Drought Effect on Groundwater System using Groundwater Level Data in Jeju Island

2014 ◽  
Vol 23 (4) ◽  
pp. 637-647 ◽  
Author(s):  
Sung-Ho Song ◽  
Byung-Sun Lee ◽  
Kwang-Jun Choi ◽  
Jin-Sung Kim ◽  
Gi-Pyo Kim
2019 ◽  
Vol 2 (1) ◽  
pp. 25-44 ◽  
Author(s):  
S. Mohanasundaram ◽  
G. Suresh Kumar ◽  
Balaji Narasimhan

Abstract Groundwater level prediction and forecasting using univariate time series models are useful for effective groundwater management under data limiting conditions. The seasonal autoregressive integrated moving average (SARIMA) models are widely used for modeling groundwater level data as the groundwater level signals possess the seasonality pattern. Alternatively, deseasonalized autoregressive and moving average models (Ds-ARMA) can be modeled with deseasonalized groundwater level signals in which the seasonal component is estimated and removed from the raw groundwater level signals. The seasonal component is traditionally estimated by calculating long-term averaging values of the corresponding months in the year. This traditional way of estimating seasonal component may not be appropriate for non-stationary groundwater level signals. Thus, in this study, an improved way of estimating the seasonal component by adopting a 13-month moving average trend and corresponding confidence interval approach has been attempted. To test the proposed approach, two representative observation wells from Adyar basin, India were modeled by both traditional and proposed methods. It was observed from this study that the proposed model prediction performance was better than the traditional model's performance with R2 values of 0.82 and 0.93 for the corresponding wells' groundwater level data.


2011 ◽  
Vol 16 (2) ◽  
pp. 41-51 ◽  
Author(s):  
Soo-Hyoung Lee ◽  
Se-Yeong Hamm ◽  
Kyoo-Chul Ha ◽  
Yong-Cheol Kim ◽  
Beom-Keun Cheong ◽  
...  

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Mara Meggiorin ◽  
Giulia Passadore ◽  
Silvia Bertoldo ◽  
Andrea Sottani ◽  
Andrea Rinaldo

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.


Author(s):  
Ya Sun ◽  
Shiguo Xu ◽  
Qin Wang ◽  
Suduan Hu ◽  
Guoshuai Qin ◽  
...  

With a shifting climate pattern and enhancement of human activities, coastal areas are exposed to threats of groundwater environmental issues. This work takes the eastern coast of Laizhou Bay as a research area to study the response of a coastal groundwater system to natural and human impacts with a combination of statistical, hydrogeochemical, and fuzzy classification methods. First, the groundwater level dynamics from 1980 to 2017 were analyzed. The average annual groundwater level dropped 13.16 m with a descent rate of 0.379 m/a. The main external environmental factors that affected the groundwater level were extracted, including natural factors (rainfall and temperature), as well as human activities (irrigated area, water-saving irrigated area, sown area of high-water-consumption crops, etc.). Back-propagation artificial neural network was used to model the response of groundwater level to the above driving factors, and sensitivity analysis was conducted to measure the extent of impact of these factors on groundwater level. The results verified that human factors including irrigated area and water-saving irrigated area were the most important influencing factors on groundwater level dynamics, followed by annual precipitation. Further, groundwater samples were collected over the study area to analyze the groundwater hydrogeochemical signatures. With the hydrochemical diagrams and ion ratios, the formation of groundwater, the sources of groundwater components, and the main hydrogeochemical processes controlling the groundwater evolution were discussed to understand the natural background of groundwater environment. The fuzzy C-means clustering method was adopted to classify the groundwater samples into four clusters based on their hydrochemical characteristics to reveal the spatial variation of groundwater quality in the research area. Each cluster was spatially continuous, and there were great differences in groundwater hydrochemical and pollution characteristics between different clusters. The natural and human factors resulted in this difference were discussed based on the natural background of the groundwater environment, and the types and intensity of human activity.


HydroResearch ◽  
2020 ◽  
Vol 3 ◽  
pp. 118-123
Author(s):  
M. Senthilkumar ◽  
D. Gnanasundar ◽  
B. Mohapatra ◽  
A.K. Jain ◽  
Anoop Nagar ◽  
...  

2020 ◽  
Author(s):  
Jānis Bikše ◽  
Andis Kalvāns ◽  
Inga Retike ◽  
Alise Babre ◽  
Konrāds Popovs ◽  
...  

<p>More severe and frequent drought events are one of the challenges faced worldwide in the context of climate change. There are multiple anecdotal evidence of dug wells and small streams running dry during  drought events in years 2015 and 2018 in Latvia. However, no comprehensive research has been made to assess groundwater drought and its ecological and socioeconomic impacts in Latvia and wider Baltic region. More intensive irrigation can further exaggerate the groundwater drought problem in the future. </p><p>We aim to analyse past drought events from meteorological and groundwater drought perspective. Groundwater drought development and propagation is complex, however, we try to find the best simple predictors that can be used for evaluating purposes. We examine groundwater level data set from “Dricani” monitoring station with 14 groundwater wells uncovering unconfined heterogenous quaternary aquifer with well depths ranging from 2.5 to 15 m and monthly data records starting from 1970.-ies. Such a high number of wells in a single monitoring station permit detailed groundwater level analysis with a focus on local scale disturbances and groundwater drought propagation that could be caused by heterogeneous sediments in the aquifer, terrain and other drivers. </p><p>We us “Dricani” groundwater level data series to calculate Standardized groundwater level index (SGI) (Bloomfield, Marchant 2013) revealing several major groundwater drought events during the last 50 years. Although largest groundwater drought events shows similar pattern within all the wells, minor changes in SGI can be identified that can be attributed to different depths of groundwater wells. </p><p>The study is supported by fundamental and applied science research programme, project No. lzp-2019/1-0165 “Spatial and temporal prediction of groundwater drought with mixed models for multilayer sedimentary basin under climate change”.</p><p>References</p><p>Bloomfield JP, Marchant BP. 2013. Analysis of groundwater drought building on the standardised precipitation index approach. Hydrology and Earth System Sciences 17 (12): 4769–4787 DOI: 10.5194/hess-17-4769-2013</p>


2007 ◽  
Vol 4 (6) ◽  
pp. 4265-4295 ◽  
Author(s):  
J. Dams ◽  
S. T. Woldeamlak ◽  
O. Batelaan

Abstract. Land-use change and climate change, along with groundwater pumping are frequently indicated to be the main human-induced factors influencing the groundwater system. Up till now, research has mainly been focusing on the effect of the water quality of these human-induced changes on the groundwater system, often neglecting changes in quantity. The focus in this study is on the impact of land-use changes in the near future, from 2000 until 2020, on the groundwater quantity and the general hydrologic balance of a sub-catchment of the Kleine Nete, Belgium. This study tests a new methodology which involves coupling a land-use change model with a water balance model and a groundwater model. The future land-use is modelled with the CLUE-S model. Four scenarios (A1, A2, B1 and B2) based on the Special Report on Emission Scenarios (SRES) are used for the land-use modelling. Water balance components, groundwater level and baseflow are simulated using the WetSpass model in conjunction with a MODFLOW groundwater model. Results show that the average recharge slowly decreases for all scenarios, the decreases are 2.9, 1.6, 1.8 and 0.8% for respectively scenario A1, A2, B1 and B2. The predicted reduction in recharge results in a small decrease of the average groundwater level, ranging from 2.5 cm for scenario A1 to 0.9 cm for scenario B2, and a reduction of the total baseflow with maximum 2.3% and minimum 0.7% respectively for scenario A1 and B2. Although these average values do not indicate significant changes for the groundwater system, spatial analysis of the changes shows the changes are concentrated in the neighbourhood of the major cities in the study areas. It is therefore important for spatial managers to take the groundwater system into account for reducing the negative impacts of land-use and climate change as much as possible.


2021 ◽  
Vol 3 ◽  
Author(s):  
Hsin-Fu Yeh

In recent years, Taiwan has been facing severe water shortages due to extreme drought. In addition, changes in rainfall patterns have resulted in an increasingly notable drought phenomenon, which affects the management and utilization of water resources. Therefore, this work examines basins in Central Taiwan. Long-term records from 13 rainfall and 17 groundwater stations were selected. The Standardized Precipitation Index (SPI) and Standardized Groundwater Level Index (SGI) were used to analyze the drought characteristics of this region. The rainfall and groundwater level data from basins in Central Taiwan were analyzed in this study. The results show that the year 2015 experienced extreme drought conditions due to a correlation with SPI and SGI signals. In addition, with regard to groundwater drought, more drought events occurred in the Da'an River basin; however, the duration and intensity of these events were relatively low, in contrast to those of the Wu River basin. Finally, the correlation between SPI and SGI was observed to vary in different basins, but a certain degree of correlation was observed in all basins. The results show that drought intensity increases with longer drought durations. Moreover, severe droughts caused by rainfall tend to occur at a greater frequency than those caused by groundwater.


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