scholarly journals Detection of Groundwater Levels Trends Using Innovative Trend Analysis Method in Temperate Climatic Conditions

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2129
Author(s):  
Ionuț Minea ◽  
Daniel Boicu ◽  
Oana-Elena Chelariu
Keyword(s):  
Trend Analysis ◽  
Groundwater Level ◽  
Global Climate ◽  
Groundwater Resources ◽  
Winter Season ◽  
Climatic Conditions ◽  
Positive Trend ◽  
Analysis Method ◽  
Groundwater Levels ◽  
Innovative Trend Analysis

The evolution of groundwater levels is difficult to predict over medium and long term in the context of global climate change. Innovative trend analysis method (ITA) was used to identify these trends, and ITA index was calculated to measure their magnitude. The data used are sourced from 71 hydrogeological wells that were dug between 1983 and 2018 and cover an area of over 8000 km2 developed in the temperate continental climate in the north-eastern part of Romania. The results obtained by applying the ITA show a general positive trend for groundwater level over 50% of wells for winter and spring seasons and annual values. The negative trends were observed for more than 43% of wells for the autumn season followed by the summer season (less than 40%). The magnitude of trends across the region shows a significant increase for spring season (0.742) followed by winter season (0.353). Important changes in the trends slopes and magnitudes have been identified for groundwater level depth between 0 and 4 m (for winter and spring seasons) and between 4 and 6 m (for summer and autumn seasons). The results can be implemented in groundwater resources management projects at local and regional level.

scholarly journals Long-Term Trends and Seasonality Detection of the Observed Flow in Yangtze River Using Mann-Kendall and Sen’s Innovative Trend Method

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1855 ◽  
Author(s):  
Ali ◽  
Kuriqi ◽  
Abubaker ◽  
Kisi
Keyword(s):  
Trend Analysis ◽  
Yangtze River ◽  
Winter Season ◽  
Trend Test ◽  
Analysis Method ◽  
Adaptation Measures ◽  
Minimum Flow ◽  
Mk Test ◽  
Innovative Trend Analysis ◽  
Increasing Trend

Trend analysis of streamflow provides practical information for better management of water resources on the eve of climate change. Thus, the objective of this study is to evaluate the presence of possible trends in the annual, seasonal, maximum, and minimum flow of Yangtze River at Cuntan and Zhutuo stations in China for the period 1980 to 2015. The assessment was carried out using the Mann–Kendall trend test, and the innovative trend analysis, while Sen’s slope is used to estimate the magnitude of the changes. The results of the study revealed that there were increasing and decreasing trends at Cuntan and Zhutuo stations in different months. The mean annual flow was found to decrease at a rate of −26.76 m3/s and −17.37 m3/s at both stations. The minimum flow was found to significantly increase at a rate of 30.57 m3/s and 16.37 m3/s, at a 95% level of confidence. Maximum annual flows showed an increasing trend in both regions of the Yangtze River. On the seasonal scale, the results showed that stations are more sensitive to seasonal flow variability suggesting a probable flooding aggravation. The winter season showed an increasing flow trend, while summer showed a decreasing trend. The spring flow was found to have an increasing trend by the Mann–Kendall test at both stations, but in the Zhutuo Station, a decreasing trend was found by way of the innovative trend analysis method. However, the autumn flow indicated a decreasing trend over the region by the Mann–Kendall (MK) test at both stations while it had an increasing trend in Cuntan by the innovative trend analysis method. The result showed nonstationary increasing and decreasing flow trends over the region. Innovative trend analysis method has the advantage of detecting the sub-trends in the flow time series because of its ability to present the results in graphical format. The results of the study indicate that decreasing trends may create water scarcity if proper adaptation measures are not taken.

scholarly journals Development of groundwater levels as a consequense of climate change

2012 ◽  
Vol 20 (1) ◽  
pp. 29-34
Author(s):  
M. Pásztorová ◽  
J. Skalová ◽  
J. Vitková ◽  
M. Juráková
Keyword(s):  
Climate Change ◽  
Groundwater Level ◽  
Groundwater Resources ◽  
Winter Season ◽  
Water Levels ◽  
Rainfall Regime ◽  
Wetland Ecosystems ◽  
Groundwater Levels ◽  
Run Off ◽  
The Impact

Development of groundwater levels as a consequense of climate changeClimate change poses a significant threat to many wetland ecosystems. Wetlands exist in a transition zone between aquatic and terrestrial environments and can be affected by slight alterations in regional hydrology, which can influence climate change through air temperature changes, regional changes in a rainfall regime, surface run-off, snow, duration of the winter season, groundwater resources and evapotranspiration.Climate change in wetland areas is most significantly reflected in water levels and adjacent groundwater levels, and it can significantly change the hydroecological proportions of wetland ecosystems and endanger rare wetland fauna and flora communities. The focus of this paper is the impact of climate change on the groundwater level in the Záhorie Protected Landscape area in the Zelienka national nature reservation. The impact of the climate change was solved through the meteorological characteristic changes adapted by the GISS98 and CCCM2000 climatic scenarios. The groundwater level was determined by the HYDRUS-ET model for the time frames 2010, 2030 and 2075 in 20-year time intervals and consequently compared to the reference period of 1971-1990.

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 Innovative Trend Analysis of Precipitation in the Lake Issyk-Kul Basin, Kyrgyzstan

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 332 ◽  
Author(s):  
Yilinuer Alifujiang ◽  
Jilili Abuduwaili ◽  
Balati Maihemuti ◽  
Bilal Emin ◽  
Michael Groll
Keyword(s):  
Trend Analysis ◽  
Resource Planning ◽  
Kendall Test ◽  
Trend Test ◽  
Lake Basin ◽  
Positive Trend ◽  
Monthly Precipitation ◽  
Innovative Trend Analysis ◽  
Mann Kendall Test ◽  
Increasing Trends

The analysis of various characteristics and trends of precipitation is an essential task to improve the utilization of water resources. Lake Issyk-Kul basin is an upper alpine catchment, which is more susceptible to the effects of climate variability, and identifying rainfall variations has vital importance for water resource planning and management in the lake basin. The well-known approaches linear regression, Şen’s slope, Spearman’s rho, and Mann-Kendall trend tests are applied frequently to try to identify trend variations, especially in rainfall, in most literature around the world. Recently, a newly developed method of Şen-innovative trend analysis (ITA) provides some advantages of visual-graphical illustrations and the identification of trends, which is one of the main focuses in this article. This study obtained the monthly precipitation data (between 1951 and 2012) from three meteorological stations (Balykchy, Cholpon-Ata, and Kyzyl-Suu) surrounding the Lake Issyk-Kul, and investigated the trends of precipitation variability by applying the ITA method. For comparison purposes, the traditional Mann–Kendall trend test also used the same time series. The main results of this study include the following. (1) According to the Mann-Kendall trend test, the precipitation of all months at the Balykchy station showed a positive trend (except in January (Zc = −0.784) and July (Zc = 0.079)). At the Cholpon-Ata and Kyzyl-Suu stations, monthly precipitation (with the same month of multiple years averaged) indicated a decreasing trend in January, June, August, and November. At the monthly scale, significant increasing trends (Zc > Z0.10 = 1.645) were detected in February and October for three stations. (2) The ITA method indicated that the rising trends were seen in 16 out of 36 months at the three stations, while six months showed decreasing patterns for “high” monthly precipitation. According to the “low” monthly precipitations, 14 months had an increasing trend, and four months showed a decreasing trend. Through the application of the ITA method (January, March, and August at Balykchy; December at Cholpon-Ata; and July and December at Kyzyl-Suu), there were some significant increasing trends, but the Mann-Kendall test found no significant trends. The significant trend occupies 19.4% in the Mann-Kendall test and 36.1% in the ITA method, which indicates that the ITA method displays more positive significant trends than Mann–Kendall Zc. (3) Compared with the classical Mann-Kendall trend results, the ITA method has some advantages. This approach allows more detailed interpretations about trend detection, which has benefits for identifying hidden variation trends of precipitation and the graphical illustration of the trend variability of extreme events, such as “high” and “low” values of monthly precipitation. In contrast, these cannot be discovered by applying traditional methods.

Trend Analysis of Temperature Data for Narayani River Basin, Nepal

Sci ◽  
2019 ◽  
Vol 1 (2) ◽  
pp. 38
Author(s):  
Mohan Bahadur Chand ◽  
Bikas Chandra Bhattarai ◽  
Prashant Baral ◽  
Niraj Shankar Pradhananga
Keyword(s):  
Trend Analysis ◽  
River Basin ◽  
Global Climate ◽  
Monsoon Season ◽  
Statistical Significance ◽  
Winter Season ◽  
Temperature Data ◽  
Lapse Rate ◽  
Seasonal Trends ◽  
Temperature Lapse Rate

Study of spatiotemporal dynamics of temperature is vital to assess changes in climate, especially in the Himalayan region where livelihoods of billions of people living downstream depends on water coming from the melting of snow and glacier ice. To this end, temperature trend analysis is carried out in Narayani river basin, a major river basin of Nepal characterized by three climatic regions: tropical, subtropical and alpine. Temperature data from six stations located within the basin were analyzed. The elevation of these stations ranges from 460 to 3800 m a.s.l. and the time period of available temperature data ranges from 1960–2015. Multiple regression and empirical mode decomposition (EMD) methods were applied to fill in missing data and to detect trends. Annual as well as seasonal trends were analyzed and a Mann-Kendall test was employed to test the statistical significance of detected trends. Results indicate significant cooling trends before 1970s, and warming trends after 1970s in the majority of the stations. The warming trends range from 0.028 °C year−1 to 0.035 °C year−1 with a mean increasing trend of 0.03 °C year−1 after 1971. Seasonal trends show highest warming trends in the monsoon season followed by winter, pre-monsoon, and the post-monsoon season. However, difference in warming rates between different seasons was not significant. An average temperature lapse rate of −0.006 °C m−1 with the steepest value (−0.0064 °C m−1) in pre-monsoon season and least negative (−0.0052 °C m−1) in winter season was observed for this basin. A comparative analysis of the gap-filled data with freely available global climate datasets shows reasonable correlation thus confirming the suitability of the gap filling methods.

Sustainable water resources management in the Long Bien district of Hanoi, Vietnam

2012 ◽  
Vol 12 (6) ◽  
pp. 737-746 ◽  
Author(s):  
C. Stefan ◽  
T. Fröhlich ◽  
L. Fuchs ◽  
R. Junghanns ◽  
H. M. Phan ◽  
...  
Keyword(s):  
Artificial Recharge ◽  
Positive Impact ◽  
Groundwater Resources ◽  
Climatic Conditions ◽  
Site Specific ◽  
Resources Management ◽  
Groundwater Levels ◽  
Sustainable Water Resources Management ◽  
High Population Growth ◽  
Local Water

The accelerated industrialization of Hanoi, Vietnam, coupled with a high population growth rate and changing climatic conditions create increasing pressure on the local water balance. Despite abundant precipitations, overexploitation endangers the groundwater resources, which are not able to sustain an adequate water supply. The present paper presents a sustainable approach for balancing the lowering of groundwater levels by increasing the rainwater percolation rates through enhanced infiltration. The efficiency of the method was assessed by a scenario analysis based on hydrological and hydrogeological models. Multi-criteria simulations revealed the optimum infiltration sites by considering technical and site-specific aspects and the positive impact of artificial recharge on seasonal groundwater budget.

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.

Trend Analysis of Temperature Data for Narayani River Basin, Nepal

Sci ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 21 ◽  
Author(s):  
Mohan Chand ◽  
Bikas Bhattarai ◽  
Prashant Baral ◽  
Niraj Pradhananga
Keyword(s):  
Trend Analysis ◽  
River Basin ◽  
Global Climate ◽  
Monsoon Season ◽  
Statistical Significance ◽  
Winter Season ◽  
Temperature Data ◽  
Lapse Rate ◽  
Climate Data ◽  
Seasonal Trends

Study of spatiotemporal dynamics of temperature is vital to assess changes in climate, especially in the Himalayan region where livelihoods of billions of people living downstream depends on water coming from the melting of snow and glacier. To this end, temperature trend analysis is carried out in Narayani river basin, a major river basin of Nepal characterized by three climatic regions: tropical, subtropical and alpine. Temperature data from six stations located within the basin are analyzed. The elevation of these stations ranges from 460 to 3800 m asl. and the time period of available temperature data ranges from 1960–2015. Multiple regression and empirical mode decomposition (EMD) methods are applied to fill in the missing data. Annual as well as seasonal trends are analyzed and Mann-Kendall test is employed for testing the statistical significance of detected trend. Results indicate significant cooling trends before 1970s, and warming trends after 1970s in the majority of the stations. The warming trends range from 0.028 ∘ C per year to 0.035 ∘ C per year with a mean increasing trend of 0.03 ∘ C per year after 1971. Seasonal trends show highest warming trends in monsoon season followed by winter, pre-monsoon, and post-monsoon season. However, difference in warming rates between different seasons isn’t sufficiently large. An average temperature lapse rate of −0.006 ∘ C per m with the steepest value (−0.0064 ∘ C per m) in pre-monsoon season and least negative (−0.0052 ∘ C per m) in winter season is observed for this basin. A comparative analysis of the gap-filled data with freely available global climate data sets shows reasonable correlation thus confirming the suitability of the gap filling methods.

Identifying anthropogenic effects into Doñana aquifer (SW Spain) through hydrogram clustering of piezometric database

2020 ◽  
Author(s):  
Carolina Guardiola-Albert ◽  
Nuria Naranjo-Fernández ◽  
Héctor Aguilera ◽  
Esperanza Montero-González
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Groundwater Resources ◽  
Data Series ◽  
Time Series Clustering ◽  
Missing Data Imputation ◽  
Groundwater Levels ◽  
Aquifer Systems ◽  
Visual Clustering ◽  
Selection Of

<p>Nowadays, the application of time series clustering is increasing in hydrogeology works. Groundwater level long data series provides a useful record to identify different hydrological behaviors and to validate the conceptual model of groundwater flow in aquifer systems. Piezometers also register the response to any changes that directly affect the amount of available groundwater resources (recharge or exploitation).</p><p>What are the expected variations of groundwater levels in an aquifer under high exploitation pressure? In this work, groundwater level time series from 160 piezometers in the hydrological years from 1975 to 2016 were analyzed. Especially, 24 piezometers are deeply studied. Data were preprocessed and transformed: selection of points, missing data imputation and data standardization. Visual clustering, k-means clustering and time series clustering were applied to classify groundwater level hydrographs using the available database. Six and seven groups of piezometers were identified to be associated with the different hydrofacies and extraction rates. Time series clustering was found to be the best method to analyze the studied piezometric database. Moreover, it was possible to characterize actual hydrodynamics, which will be useful for groundwater managers to make sustainable decisions.</p>

European vegetation during Marine Oxygen Isotope Stage-3

2003 ◽  
Vol 59 (2) ◽  
pp. 195-212 ◽  
Author(s):  
Brian Huntley ◽  
Mary Jo Alfano ◽  
Judy R.M Allen ◽  
Dave Pollard ◽  
Polychronis C Tzedakis ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Analytical Data ◽  
Winter Season ◽  
Climatic Conditions ◽  
Sensitivity Analyses ◽  
Climate Feedback ◽  
Vegetation Model ◽  
Oxygen Isotope Stage ◽  
Simulated Climate

AbstractEuropean vegetation during representative “warm” and “cold” intervals of stage-3 was inferred from pollen analytical data. The inferred vegetation differs in character and spatial pattern from that of both fully glacial and fully interglacial conditions and exhibits contrasts between warm and cold intervals, consistent with other evidence for stage-3 palaeoenvironmental fluctuations. European vegetation thus appears to have been an integral component of millennial environmental fluctuations during stage-3; vegetation responded to this scale of environmental change and through feedback mechanisms may have had effects upon the environment. The pollen-inferred vegetation was compared with vegetation simulated using the BIOME 3.5 vegetation model for climatic conditions simulated using a regional climate model (RegCM2) nested within a coupled global climate and vegetation model (GENESIS-BIOME). Despite some discrepancies in detail, both approaches capture the principal features of the present vegetation of Europe. The simulated vegetation for stage-3 differs markedly from that inferred from pollen analytical data, implying substantial discrepancy between the simulated climate and that actually prevailing. Sensitivity analyses indicate that the simulated climate is too warm and probably has too short a winter season. These discrepancies may reflect incorrect specification of sea surface temperature or sea-ice conditions and may be exacerbated by vegetation–climate feedback in the coupled global model.

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