Rescue of groundwater level time series: how to identify and treat errors

2021 ◽  
Author(s):  
Jānis Bikše ◽  
Inga Retike ◽  
Andis Kalvāns ◽  
Aija Dēliņa ◽  
Alise Babre ◽  
...  
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Monitoring Network ◽  
Observation Data ◽  
Automatic Data ◽  
Mean Values ◽  
Temporal Prediction ◽  
National Monitoring ◽  
Groundwater Drought

<p>Groundwater level time series are the basis for various groundwater-related studies. The most valuable are long term, gapless and evenly spatially distributed datasets. However, most historical datasets have been acquired during a long-term period by various operators and database maintainers, using different data collection methods (manual measurements or automatic data loggers) and usually contain gaps and errors, that can originate both from measurement process and data processing. The easiest way is to eliminate the time series with obvious errors from further analysis, but then most of the valuable dataset may be lost, decreasing spatial and time coverage. Some gaps can be easily replaced by traditional methods (e.g. by mean values), but filling longer observation gaps (missing months, years) is complicated and often leads to false results. Thus, an effort should be made to retain as much as possible actual observation data.</p><p>In this study we present (1) most typical data errors found in long-term groundwater level monitoring datasets, (2) provide techniques to visually identify such errors and finally, (3) propose best ways of how to treat such errors. The approach also includes confidence levels for identification and decision-making process. The aim of the study was to pre-treat groundwater level time series obtained from the national monitoring network in Latvia for further use in groundwater drought modelling studies.</p><p>This research is funded by the Latvian Council of Science, project “Spatial and temporal prediction of groundwater drought with mixed models for multilayer sedimentary basin under climate change”, project No. lzp-2019/1-0165.</p>

scholarly journals Asymmetric impact of groundwater use on groundwater droughts

2020 ◽  
Author(s):  
Doris E. Wendt ◽  
Anne F. Van Loon ◽  
John P. Bloomfield ◽  
David M. Hannah
Keyword(s):  
Water Management ◽  
Time Series ◽  
Groundwater Level ◽  
Management Units ◽  
Groundwater Use ◽  
Groundwater Drought ◽  
Asymmetric Impact ◽  
The Uk ◽  
The Impact

Abstract. Groundwater use affects groundwater storage continuously, as the removal of water changes both short-term and long-term variation in groundwater level. This has implications for groundwater droughts, i.e. a below-normal groundwater level. The impact of groundwater use on groundwater droughts remains unknown. Hence, the aim of this study is to investigate the impact of groundwater use on groundwater droughts adopting a methodological framework that consists of two approaches. The first approach compares groundwater monitoring sites that are potentially influenced by abstraction to uninfluenced sites. Observed groundwater droughts are compared in terms of drought occurrence, magnitude, and duration. The second approach consists of a groundwater trend test that investigates the impact of groundwater use on long-term groundwater level variation. This framework was applied to a case study of the UK. Four regional water management units in the UK were used, in which groundwater is monitored and abstractions are licensed. The potential influence of groundwater use was identified on the basis of relatively poor correlations between accumulated standardised precipitation and standardised groundwater level time series over a 30-year period from 1984 to 2014. Results of the first approach show two main patterns in groundwater drought characteristics. The first pattern shows an increase of shorter drought events, mostly during heatwaves or prior to a long drought event for influenced sites compared to uninfluenced sites. This pattern is found in three water management units where the long-term water balance is generally positive and annual average groundwater abstractions are smaller than recharge. The second pattern is found in one water management unit where temporarily groundwater abstractions exceeded recharge. In this case, groundwater droughts are lengthened and intensified in influenced sites. Results of the second approach show that nearly half of the groundwater time series have a significant trend, whilst trends in precipitation and potential evapotranspiration time series are negligible. Detected significant trends are both positive en negative, although positive trends dominate in most water management units. These positive trends, indicating rising groundwater levels, align with changes in water use regulation. This suggests that groundwater abstractions have reduced during the period of investigation. Further research is required to assess the impact of this change in groundwater abstractions on drought characteristics. The overall impact of groundwater use is summarised in a conceptual typology that illustrates the asymmetric impact of groundwater use on groundwater drought occurrence, duration, and magnitude. The long-term balance between groundwater abstraction and recharge appears to be influencing this asymmetric impact, which highlights the relation between long-term and short-term sustainable groundwater use.

scholarly journals Analysis of long-term observations of the groundwater level In an aseismic region

2019 ◽  
pp. 47-67
Author(s):  
A. A. Lyubushin ◽  
O. S. Kazantseva ◽  
A. B. Manukin
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Atmospheric Pressure ◽  
Active Regions ◽  
Sampling Interval ◽  
Pressure Effects ◽  
Adaptive Compensation ◽  
Groundwater Level Fluctuations ◽  
And Cluster Analysis

The results of the analysis of continuous precise time series of atmospheric pressure and groundwater level fluctuations in a well drilled to a depth of 400 m in the territory of Moscow are presented. The observations are remarkable in terms of their duration of more than 22 years (from February 2, 1993 to April 4, 2015) and by the sampling interval of 10 min. These long observations are suitable for exploring the stationarity of the properties of hydrogeological time series in a seismically quiet region, which is important from the methodological standpoint for interpreting the similar observations in seismically active regions aimed at earthquake prediction. Factor and cluster analysis applied to the sequence of multivariate vectors ofthe statistical properties of groundwater level time series in the successive 10-day windows after adaptive compensation for atmospheric pressure effects distinguish five different statistically significant states of the time series with the transitions between them. An attempt to geophysically interpret the revealed states is made. Two significant periods – 46 and 275 days – are established by spectral analysis of the sequence of the transitions times between the clusters.

scholarly journals Brewer spectrometer total ozone column measurements in Sodankylä

2016 ◽  
Vol 5 (1) ◽  
pp. 229-239 ◽  
Author(s):  
Tomi Karppinen ◽  
Kaisa Lakkala ◽  
Juha M. Karhu ◽  
Pauli Heikkinen ◽  
Rigel Kivi ◽  
...  
Keyword(s):  
Time Series ◽  
Total Ozone ◽  
Montreal Protocol ◽  
High Quality ◽  
Automatic Data ◽  
Mean Values ◽  
Total Ozone Column ◽  
Measurement Practices ◽  
Ozone Column

Abstract. Brewer total ozone column measurements started in Sodankylä in May 1988, 9 months after the signing of The Montreal Protocol. The Brewer instrument has been well maintained and frequently calibrated since then to produce a high-quality ozone time series now spanning more than 25 years. The data have now been uniformly reprocessed between 1988 and 2014. The quality of the data has been assured by automatic data rejection rules as well as by manual checking. Daily mean values calculated from the highest-quality direct sun measurements are available 77 % of time with up to 75 measurements per day on clear days. Zenith sky measurements fill another 14 % of the time series and winter months are sparsely covered by moon measurements. The time series provides information to survey the evolution of Arctic ozone layer and can be used as a reference point for assessing other total ozone column measurement practices.

scholarly journals An Automatic Online Disaster Monitoring Network: Network Architecture and a Case Study Monitoring Slope Stability

2018 ◽  
Vol 14 (03) ◽  
pp. 4 ◽  
Author(s):  
Jianmin Wang ◽  
Xiaoqin Yang
Keyword(s):  
Network Architecture ◽  
Monitoring Network ◽  
Observation Data ◽  
Application Layer ◽  
Heterogeneous Wireless Sensor Networks ◽  
Development Direction ◽  
Disaster Monitoring ◽  
Study Monitoring

Geosensor networks(GSN) is an important development direction of the disaster monitoring in the future. An online automatic unattended disaster monitoring system can prevent and reduce the geology disaster to protect the safety of life and property. At present, most GSN are independent and usually service for respective community. The observations data of GSN are bigger and complex , and GSN is mostly heterogeneous wireless sensor networks. So this paper proposes a novel GSN disaster monitoring overall architecture, This architecture can seamlessly integrate sensors for long- term, remote, and near-real-time monitoring. In the architecture, there are four layers are used to collect, manage , transport and processing observation data. Among them, the data server layer applies the OGC SWE standards to integrate and share heterogeneous monitoring data. sensor metadata and observation data are packaged into a virtual sensor that are is transported from data center to application layer through Sensor Observation Service (SOS). To demonstrates the applicability of our proposed method, we use a case named PS-MDMs which are developed and deployed to support mine disaster monitoring and modeling research.

Preliminary identification of groundwater drought events in unconfined aquifer with standardized drought indices in single multilevel groundwater station

2020 ◽  
Author(s):  
Jānis Bikše ◽  
Andis Kalvāns ◽  
Inga Retike ◽  
Alise Babre ◽  
Konrāds Popovs ◽  
...  
Keyword(s):  
Climate Change ◽  
Groundwater Level ◽  
Monitoring Station ◽  
Data Set ◽  
Temporal Prediction ◽  
Level Data ◽  
Small Streams ◽  
Groundwater Drought ◽  
Standardised Precipitation Index ◽  
Groundwater Wells

<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>

scholarly journals Spatiotemporal Variation of the Meteorological and Groundwater Droughts in Central Taiwan

2021 ◽  
Vol 3 ◽  
Author(s):  
Hsin-Fu Yeh
Keyword(s):  
River Basin ◽  
Groundwater Level ◽  
Standardized Precipitation Index ◽  
Extreme Drought ◽  
Water Shortages ◽  
Level Data ◽  
Groundwater Drought ◽  
Central Taiwan ◽  
The Standardized Precipitation Index

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.

Time series study for groundwater level evaluation in monitoring well

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
Rubens Oliveira da Cunha Júnior ◽  
João Victor Mariano da Silva
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Sedimentary Basin ◽  
Precipitation Data ◽  
Environmental Aspects ◽  
Aquifer System ◽  
Groundwater Levels ◽  
Monitoring Well ◽  
Series Study

Climate and hydrogeological conditions of the Brazilian semi-arid demand sustainable and efficient water solutions. Groundwater monitoring programs are tools to subsidize the decision-making in this sense. In Ceará state, the monitoring of Araripe sedimentary basin aquifers is important for the development of the region. In this scenario, the present work aimed to study the groundwater level through an exploratory analysis of time series. The study area covered the eastern portion of the Araripe sedimentary basin, in the municipality of Milagres, in Ceará state. As the object of this study, it was obtained the time series of monthly average groundwater levels in a monitoring well of RIMAS/CPRM and installed in the Middle Aquifer System. Graphical and numerical methods were applied for the identification and description of time series main characteristics. Precipitation data in the study area were used to evaluate the system recharge. Results were discussed according to the environmental aspects of the study area. As a result, it was possible the identification and description of time series patterns such as trend and seasonality through the applied methods. It is also highlighted the sharp drawdown of groundwater levels in long term in the time series, reflecting the quantitative state of the aquifer system, as well as the groundwater recharge during the rainy season of the region, evidenced by the study of time series seasonality together with the precipitation data..

Seasonal forecasting of groundwater levels in Europe using Pastas time series models and ECMWF SEAS5 forecasts

2021 ◽  
Author(s):  
Raoul Collenteur ◽  
Steffen Birk
Keyword(s):  
Time Series ◽  
Early Warning ◽  
Groundwater Level ◽  
Early Warning Systems ◽  
Seasonal Forecasts ◽  
Groundwater System ◽  
Groundwater Levels ◽  
Informed Decisions ◽  
Groundwater Drought ◽  
Forecast Quality

<p>Groundwater level monitoring is an important way for water resource managers to obtain information on the state of the groundwater system and make informed decisions. In many countries around Europe the right to abstract groundwater (e.g., for drinking water or irrigation purposes) is bound to observed groundwater levels. In particular during and after periods of drought such rights to abstract groundwater may be temporarily denied. As climate change is expected to increase the frequency and intensity of hydrological extremes, severe drought events become more likely, potentially increasing the gap between groundwater demand and supply. An early warning system of a potential groundwater drought could help water managers make informed decisions in advance, to try and counteract the effects of drought. In this study we investigate the use of seasonal forecasts from the ECMWF SEAS5 system to forecast groundwater levels around Europe. The groundwater levels are simulated using a non-linear time series model using impulse response functions as implemented in Pastas (https://github.com/pastas/pastas). Forecasts are compared to groundwater level simulations based on historic meteorological data from the E-OBS database. The methods are tested on 10 long-term (30 years) groundwater level time series. The use of the Standardized Groundwater Index (SGI) is tested to assess the forecast quality and communicate results with decision makers. Bias-correction of the SEAS5 forecasts is found to be necessary to forecast groundwater levels at this local scale. Preliminary results show that the forecast quality depends on the memory effect of the groundwater system, which can be characterized by the auto-correlation of the time series. In addition, it is found that the groundwater levels forecasts have smaller ranges in spring then in the winter months. This may be explained by the fact that groundwater levels in spring are more dependent on evaporation than on precipitation and that forecast of the first are better than those of the latter. The results from this study may be used to improve early warning systems that forecast groundwater droughts.</p>

scholarly journals Analysis of groundwater drought building on the standardised precipitation index approach

2013 ◽  
Vol 17 (12) ◽  
pp. 4769-4787 ◽  
Author(s):  
J. P. Bloomfield ◽  
B. P. Marchant
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Precipitation Index ◽  
Monitoring Networks ◽  
Level Data ◽  
Index Approach ◽  
Groundwater Drought ◽  
Standardised Precipitation Index ◽  
Positive Linear Correlation ◽  
And Storage

Abstract. A new index for standardising groundwater level time series and characterising groundwater droughts, the Standardised Groundwater level Index (SGI), is described. The SGI builds on the Standardised Precipitation Index (SPI) to account for differences in the form and characteristics of groundwater level and precipitation time series. The SGI is estimated using a non-parametric normal scores transform of groundwater level data for each calendar month. These monthly estimates are then merged to form a continuous index. The SGI has been calculated for 14 relatively long, up to 103 yr, groundwater level hydrographs from a variety of aquifers and compared with SPI for the same sites. The relationship between SGI and SPI is site specific and the SPI accumulation period which leads to the strongest correlation between SGI and SPI, qmax, varies between sites. However, there is a consistent positive linear correlation between a measure of the range of significant autocorrelation in the SGI series, mmax, and qmax across all sites. Given this correlation between SGI mmax and SPI qmax, and given that periods of low values of SGI can be shown to coincide with previously independently documented droughts, SGI is taken to be a robust and meaningful index of groundwater drought. The maximum length of groundwater droughts defined by SGI is an increasing function of mmax, meaning that relatively long groundwater droughts are generally more prevalent at sites where SGI has a relatively long autocorrelation range. Based on correlations between mmax, average unsaturated zone thickness and aquifer hydraulic diffusivity, the source of autocorrelation in SGI is inferred to be dependent on dominant aquifer flow and storage characteristics. For fractured aquifers, such as the Cretaceous Chalk, autocorrelation in SGI is inferred to be primarily related to autocorrelation in the recharge time series, while in granular aquifers, such as the Permo–Triassic sandstones, autocorrelation in SGI is inferred to be primarily a function of intrinsic saturated flow and storage properties of aquifer. These results highlight the need to take into account the hydrogeological context of groundwater monitoring sites when designing and interpreting data from groundwater drought monitoring networks.

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