scholarly journals Integration of observed and model derived groundwater levels in landslide threshold models in Rwanda

2021 ◽  
Author(s):  
Judith Uwihirwe ◽  
Markus Hrachowitz ◽  
Thom Bogaard
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Early Warning Systems ◽  
False Alarms ◽  
Threshold Models ◽  
Single Variable ◽  
Landslide Prediction ◽  
Groundwater Levels ◽  
Variable Threshold ◽  
Regional Groundwater

Abstract. Incorporation of specific regional hydrological characteristics in empirical statistical landslide threshold models has considerable potential to improve the quality of landslide predictions towards reliable early warning systems. The objective of this research was to test the value of regional groundwater level information, as a proxy for water storage fluctuations, to improve regional landslide predictions with empirical models based on the concept of threshold levels. Specifically, we investigated: i) the use of a data driven time series approach to model the regional groundwater levels based on short duration monitoring observations; ii) the predictive power of single variable and bilinear threshold landslide prediction models derived from groundwater levels and precipitation. Based on statistical measures of the model fit (R2 and RMSE), the groundwater level dynamics estimated by the transfer function noise time series model are broadly consistent with the observed groundwater levels. The single variable threshold models derived from groundwater levels exhibited the highest landslide prediction power with 82–93 % of true positive alarms despite the quite high rate of false alarms with about 26–38 %. Further combination as bilinear threshold models reduced the rate of false alarms by about 18–28 % at the expense of reduced true alarms by about 9–29 % and thus, being less advantageous than single variable threshold models. In contrast to precipitation based thresholds, relying on threshold models exclusively defined using hydrological variables such as groundwater levels can lead to improved landslide predictions due to their implicit consideration of long-term antecedent conditions until the day of landslide occurrence.

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>

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>

scholarly journals Characterising hillslope–stream connectivity with a joint event analysis of stream and groundwater levels

2020 ◽  
Vol 24 (12) ◽  
pp. 5713-5744
Author(s):  
Daniel Beiter ◽  
Markus Weiler ◽  
Theresa Blume
Keyword(s):  
Time Series ◽  
Water Level ◽  
Groundwater Level ◽  
Stream Water ◽  
Water Levels ◽  
Joint Analysis ◽  
Strong Increase ◽  
Groundwater Levels ◽  
The Relationship ◽  
Insight Into

Abstract. Hillslope–stream connectivity controls runoff generation, during events and during baseflow conditions. However, assessing subsurface connectivity is a challenging task, as it occurs in the hidden subsurface domain where water flow can not be easily observed. We therefore investigated if the results of a joint analysis of rainfall event responses of near-stream groundwater levels and stream water levels could serve as a viable proxy for hillslope–stream connectivity. The analysis focuses on the extent of response, correlations, lag times and synchronicity. As a first step, a new data analysis scheme was developed, separating the aspects of (a) response timing and (b) extent of water level change. This provides new perspectives on the relationship between groundwater and stream responses. In a second step we investigated if this analysis can give an indication of hillslope–stream connectivity at the catchment scale. Stream water levels and groundwater levels were measured at five different hillslopes over 5 to 6 years. Using a new detection algorithm, we extracted 706 rainfall response events for subsequent analysis. Carrying out this analysis in two different geological regions (schist and marls) allowed us to test the usefulness of the proxy under different hydrological settings while also providing insight into the geologically driven differences in response behaviour. For rainfall events with low initial groundwater level, groundwater level responses often lag behind the stream with respect to the start of rise and the time of peak. This lag disappears at high antecedent groundwater levels. At low groundwater levels the relationship between groundwater and stream water level responses to rainfall are highly variable, while at high groundwater levels, above a certain threshold, this relationship tends to become more uniform. The same threshold was able to predict increased likelihood for high runoff coefficients, indicating a strong increase in connectivity once the groundwater level threshold was surpassed. The joint analysis of shallow near-stream groundwater and stream water levels provided information on the presence or absence and to a certain extent also on the degree of subsurface hillslope–stream connectivity. The underlying threshold processes were interpreted as transmissivity feedback in the marls and fill-and-spill in the schist. The value of these measurements is high; however, time series of several years and a large number of events are necessary to produce representative results. We also find that locally measured thresholds in groundwater levels can provide insight into the connectivity and event response of the corresponding headwater catchments. If the location of the well is chosen wisely, a single time series of shallow groundwater can indicate if the catchment is in a state of high or low connectivity.

Development and testing of a remote sensing-based model for estimating groundwater levels in aeolian desert areas of China

2011 ◽  
Vol 91 (1) ◽  
pp. 29-37 ◽  
Author(s):  
Aidi Huo ◽  
Xunhong Chen ◽  
Huike Li ◽  
Ming Hou ◽  
Xiaojing Hou
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Groundwater Level ◽  
Remote Sensing Data ◽  
Water Levels ◽  
Desert Area ◽  
Groundwater Levels ◽  
Sensing Data ◽  
Desert Areas ◽  
Regional Groundwater

Huo, A., Chen, X., Li, H., Hou, M. and Hou, X. 2011. Development and testing of a remote sensing-based model for estimating groundwater levels in aeolian desert areas of China. Can. J. Soil Sci. 91: 29–37. Regional groundwater level is an important data set for understanding the relationships between groundwater resources and regional ecological environments. The decline in water table levels leads to vegetation degradation and thus affects the ecological environment. Such a negative effect is especially apparent in the desertification areas. In this study, a remote-sensing based method was proposed to predict the distribution of the regional groundwater level in an aeolian desert area in northern China. The study used the Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data and field investigations. Based on field investigation of groundwater level, soil moisture, and other supporting information in the aeolian desert area, as well as the soil moisture distribution derived from the MODIS images, empirical equations describing the relationship between the soil moisture and groundwater level were obtained. The groundwater levels derived using the MODIS image data were verified by groundwater levels measured from 58 wells. The results show that the correlation coefficient between the measured groundwater levels and the remote sensing-based estimated water levels was 0.868, indicating that the error is small and the predictions closely reflect the real water levels. This model can be used to predict groundwater levels in aeolian desert areas based on remote sensing data sets.

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..

scholarly journals Characterizing hillslope-stream connectivity with a joint event analysis of stream and groundwater levels

2020 ◽  
Author(s):  
Daniel Beiter ◽  
Markus Weiler ◽  
Theresa Blume
Keyword(s):  
Time Series ◽  
Water Level ◽  
Groundwater Level ◽  
Stream Water ◽  
Water Levels ◽  
Joint Analysis ◽  
Catchment Scale ◽  
Groundwater Levels ◽  
The Relationship ◽  
Insight Into

Abstract. Hillslope-stream connectivity controls runoff generation, both during events and baseflow conditions. However, assessing subsurface connectivity is a challenging task, as it occurs in the hidden subsurface domain where water flow cannot be easily observed. We therefore investigated if the results of a joint analysis of rainfall event responses of near-stream groundwater levels and stream water levels could serve as a viable proxy for hillslope-stream connectivity. The analysis focuses on the extent of response, correlations, lag times and synchronicity. A newly developed data analysis scheme of separating the aspects of (a) response timing and (b) extent of water level change provides new perspectives on the relationship between groundwater and stream responses. In a second step we investigated if this analysis can give an indication of hillslope-stream connectivity at the catchment scale. Stream- and groundwater levels were measured at five different hillslopes over 5 to 6 years. Using a new detection algorithm we extracted 706 rainfall response events for subsequent analysis. Carrying out this analysis in two different geological regions (schist and marls) allowed us to test the usefulness of the proxy under different hydrological settings while also providing insight into the geologically-driven differences in response behaviour. For rainfall events with low initial groundwater level, groundwater level responses often lag behind the stream with respect to the start of rise and the time of peak. This lag disappears at high antecedent groundwater levels. At low groundwater levels the relationship between groundwater and stream water level responses to rainfall are highly variable, while at high groundwater levels, above a certain threshold, this relationship tends to become more uniform. The same threshold was able to predict increased likelihood for high runoff coefficients, indicating a strong increase in connectivity once the groundwater level threshold was surpassed. The joint analysis of shallow near-stream groundwater and stream water levels provided information on the presence or absence and to a certain extent also on the degree of subsurface hillslope-stream connectivity. The underlying threshold processes were interpreted as transmissivity feedback in the marls and fill-and-spill in the schist. The value of these measurements is high, however, time series of several years and a large number of events are necessary to produce representative results. We also find that locally measured thresholds in groundwater levels can provide insight into catchment-scale connectivity and event response. If the location of the well is chosen wisely, a single time series of shallow groundwater can indicate if the catchment is in a state of high or low connectivity.

scholarly journals REAKCJA WÓD POWIERZCHNIOWYCH I PODZIEMNYCH NA OPADY W ZLEWNI RÓŻANEGO STRUMIENIA

1970 ◽  
pp. 7-19
Author(s):  
ALEKSANDRA CZUCHAJ ◽  
FILIP WOLNY ◽  
MAREK MARCINIAK
Keyword(s):  
Time Series ◽  
Surface Water ◽  
Water Level ◽  
Correlation Coefficient ◽  
Groundwater Level ◽  
Water Levels ◽  
Groundwater Levels

The aim of the presented research was to analyze the relation between three variables: the daily sum of precipitation, the surface water level and the groundwater level in the Różany Strumień basin located in Poznań, Poland. The correlation coefficient for the subsequent lags for each pair of variables time series has been calculated. The delay with which waters of the basin respond to precipitation varies significantly. Generally, stronger response to rainfall is observed for surface water levels as opposed to groundwater levels.

Analysis and prediction of groundwater level time series with Autoregressive Linear Models

2016 ◽  
Vol 39 ◽  
pp. 109-112
Author(s):  
Mirko Ginocchi ◽  
Giovanni Franco Crosta ◽  
Marco Rotiroti ◽  
Tullia Bonomi
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Linear Models

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.

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