How groundwater time series and aquifer property data explain heterogeneity in the Permo-Triassic sandstone aquifers of the Eden Valley, Cumbria, UK

AbstractA novel investigation of the impact of meteorological and geological heterogeneity within the Permo-Triassic Sandstone aquifers of the River Eden catchment, Cumbria (UK), is described. Quantifying the impact of heterogeneity on the water cycle is increasingly important to sustainably manage water resources and minimise flood risk. Traditional investigations on heterogeneity at the catchment scale require a considerable amount of data, and this has led to the analysis of available time series to interpret the impact of heterogeneity. The current research integrated groundwater-level and meteorological time series in conjunction with aquifer property data at 11 borehole locations to quantify the impact of heterogeneity and inform the hydrogeological conceptual understanding. The study visually categorised and used seasonal trend decomposition by LOESS (STL) on 11 groundwater and meteorological time series. Decomposition components of the different time series were compared using variance ratios. Though the Eden catchment exhibits highly heterogeneous rainfall distribution, comparative analysis at borehole locations showed that (1) meteorological drivers at borehole locations are broadly homogeneous and (2) the meteorological drivers are not sufficient to generate the variation observed in the groundwater-level time series. Three distinct hydrogeological regimes were identified and shown to coincide with heterogeneous features in the southern Brockram facies, which is the northern silicified region of the Penrith Sandstone and the St Bees Sandstone. The use of STL analysis in combination with detailed aquifer property data is a low-impact insightful investigative tool that helps guide the development of hydrogeological conceptual models.

Download Full-text

Using Remotely Sensed Information to Improve Vegetation Parameterization in a Semi-Distributed Hydrological Model (SMART) for Upland Catchments in Australia

Remote Sensing ◽

10.3390/rs12183051 ◽

2020 ◽

Vol 12 (18) ◽

pp. 3051

Author(s):

Seokhyeon Kim ◽

Hoori Ajami ◽

Ashish Sharma

Keyword(s):

Time Series ◽

Soil Moisture ◽

Vegetation Dynamics ◽

Pearson Correlation ◽

Hydrologic Model ◽

Catchment Scale ◽

Simple Method ◽

Area Index ◽

The Impact ◽

Upland Catchments

Appropriate representation of the vegetation dynamics is crucial in hydrological modelling. To improve an existing limited vegetation parameterization in a semi-distributed hydrologic model, called the Soil Moisture and Runoff simulation Toolkit (SMART), this study proposed a simple method to incorporate daily leaf area index (LAI) dynamics into the model using mean monthly LAI climatology and mean rainfall. The LAI-rainfall sensitivity is governed by a parameter that is optimized by maximizing the Pearson correlation coefficient (R) between the estimated and satellite-derived LAI time series. As a result, the LAI-rainfall sensitivity is smallest for forest, shrub, and woodland regions across Australia, and increases for grasslands and croplands. The impact of the proposed method on catchment-scale simulations of soil moisture (SM), evapotranspiration (ET) and discharge (Q) in SMART was examined across six eco-hydrologically contrasted upland catchments in Australia. Results showed that the proposed method produces almost identical results compared to simulations by the satellite-derived LAI time series. In addition, the simulation results were considerably improved in nutrient/light limited catchments compared to the cases with the default vegetation parameterization. The results showed promise, with possibilities of extension to other hydrologic models that need similar specifications for inbuilt vegetation dynamics.

Download Full-text

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

10.5194/hess-2020-33 ◽

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.

Download Full-text

Stochastic and Artificial Intelligence Models for Climate Change Investigation and Groundwater Level Assessment of Gaza Coastal Aquifer (Palestine)

10.22541/au.161252402.20503328/v1 ◽

2021 ◽

Author(s):

Hassan Al-Najjar ◽

Gokmen Ceribasi ◽

Emrah Dogan ◽

Khalid Qahman ◽

Mazen Abualtayef ◽

...

Keyword(s):

Climate Change ◽

Time Series ◽

Stochastic Models ◽

Groundwater Level ◽

Coastal Aquifer ◽

Anthropogenic Activities ◽

Gaza Strip ◽

Groundwater Abstraction ◽

The Gaza Strip ◽

The Impact

The Gaza coastal aquifer is a critical resource for the supply of water to the Gaza Strip and continues to be depleted as a result of the effects of climate change and the anthropogenic activities. Therefore, this study tends to investigate the impact of climate change and groundwater withdrawal practices on the oscillation of the Gaza Coastal Aquifer water table level by recruiting the power of the stochastic time-series models in exemplifying the autoregression of data and by leveraging the efficiency of the artificial neural networks (ANNs) in expressing the nonlinear regression between the different meteorological and hydrological factors. The climate stochastic models reveal that the Gaza Strip region will face a decline in the precipitation by -5.2% and an increase in the temperature by +1˚C in the timeframe of 2020-2040. The potential evaporation and the sunshine period will increase by about 111 mm and 5 hours, respectively during the next 20 years. However, the atmosphere is predicted to be drier where the relative humidity will fall by a trend of -8% in 20 years. The stochastic models developed for the groundwater abstraction time series show that the groundwater pumping processes would increase by about 55 % by 2040, compared to the 124 million cubic meters of groundwater that was withdrawn in 2020. The stochastic model of structure (2,1,5) (4,1,2)12 was defined to extend the time series of the groundwater level up to 2040. In order to form an integrated stochastic-ANN model, the combination of the time series of climate factors, groundwater abstraction and groundwater level were emerged into a one hidden layer ANN of 20-neurons. The performance of the model was high in term of training and in forecasting the future where the correlation coefficient (r) = 0.95-0.99 and the root mean square error (RMSE) = 0.09-0.21.

Download Full-text

Ecohydrology: An Integrative Sustainability Science

Hydrology ◽

10.5772/intechopen.94169 ◽

2021 ◽

Author(s):

Maciej Zalewski

Keyword(s):

Water Management ◽

Industrial Development ◽

Water Cycle ◽

Plant Cover ◽

Ecosystem Dynamics ◽

Catchment Scale ◽

Mechanistic Approach ◽

Key Driver ◽

New Perspective ◽

The Impact

The dynamic of the water cycle in catchments is determined by climate, geology, geomorphology, plant cover ad modified by agriculture, urbanisation, industrial development and hydroengineering infrastructure. Up until the end of the 20th century, water management was dominated by a mechanistic approach, focused on the elimination of threats such as floods and droughts and providing resources for the society with little to no regard for the impact this approach had on the ecosystem. Highlighting of water as a key driver of ecosystem dynamics, and further ecohydrology which highlights water/biota interactions from molecular to catchment scale provide a new perspective, new tools and new systemic solutions for enhancement of catchment sustainability potential WBSRCE (consisting of 5 elements: Water, Biodiversity, Ecosystem Services for Society, Resilience and Culture and Education).

Download Full-text

Asymmetric impact of groundwater use on groundwater droughts

10.5194/hess-2020-22 ◽

2020 ◽

Cited By ~ 1

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.

Download Full-text

Climate change effect on decline groundwater level using Entropy wavelet (case study of Khorramabad city)

Water Science & Technology Water Supply ◽

10.2166/ws.2021.377 ◽

2021 ◽

Author(s):

Reza Hassanzadeh ◽

Mehdi Komasi ◽

Alireza Derikvand

Keyword(s):

Time Series ◽

Groundwater Level ◽

Hydrological Cycle ◽

Climatic Factors ◽

Global Climate ◽

Affecting Factors ◽

The Third ◽

Temperature And Precipitation ◽

Time Period ◽

The Impact

Abstract Changing global climate predicts a warmer future which may alter the hydrological cycle, surface water as well as groundwater resource. The Entropy wavelet criterion is a new indicator to analyze the time series fluctuations. In this study, the effective factors of decreasing the groundwater level in Khorramabad city during the years 2005–2018 have been evaluated by the use of Entropy wavelet criterion. In general, it can be said that the decreasing of Entropy wavelet criterion or time series complexity of a phenomenon shows the time series decrease of fluctuations natural amounts, which it leads to an unfavorable trend. In this regard, in order to identify the affecting factors of the groundwater level decrease in Khorramabad, the groundwater level has been divided into 4 time periods, and after being investigated, the monthly time series of runoff, temperature, and precipitation of this city were divided into 4 periods. Each of these subset were decomposed into other several subsets at different time scales under the wavelet transform, and finally, after calculation of the normalized wavelet energy for this subset, its Entropy wavelet criterion was calculated for each period. Investigation of Entropy wavelet complexity shows a 21.3% decrease in groundwater level in the second period, but in the third and fourth periods, it has increased by 145 and 272%, respectively. Also, according to the results of Entropy wavelet changes analyzing for the precipitation time series, 35.2, 32.8, and 10.06% decrease in the second, third, and fourth periods were shown. The air temperature time series complexity decreased of 26.8% only in the third time period and in the second and fourth period, it shows an increase of 29.65 and 34.7%, respectively. However, the runoff time series did not show any reduction complexity according to the entropy wavelet criterion. These results indicate that the impact of climatic factors has been more effective than human factors in reducing the groundwater level of Khorramabad.

Download Full-text

The Impact of Irrigation Diverting from Yellow River Water on Regional Water Cycle in Shandong Province

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.212-213.514 ◽

2012 ◽

Vol 212-213 ◽

pp. 514-517 ◽

Cited By ~ 1

Author(s):

Shi Song Qu ◽

Zhong Zhu Zhu ◽

Ning Qiu ◽

Wei Ping Wang

Keyword(s):

River Water ◽

Groundwater Level ◽

Surface Runoff ◽

Water Cycle ◽

Yellow River ◽

Shandong Province ◽

Water Diversion ◽

Runoff Coefficient ◽

The Impact ◽

Regional Water

Yellow River water diversion is an effective way to alleviate agricultural irrigation water shortage and promote agricultural production around Shandong Yellow River diversion area. It also plays a role in improving regional water cycle, including effects on evaporation, precipitation, surface runoff coefficient, and groundwater level of intake area. The paper studied the development of Yellow River water diversion in Shandong province, and qualitatively analysized the impact on the regional temperature, evaporation. And then the surface runoff coefficient and groundwater level before and after large-scale diversion in the area were quantitatively analysized. The results show that irrigation diversion from Yellow River can increase surface runoff coefficient and groundwater level, bring an enormous benefit to eco-environment, and provide an irreplaceable support role of the sustainable socio-economic development in Shandong province.

Download Full-text

Detecting Groundwater Level Changes with Radar Interferometry

10.5194/egusphere-egu2020-15736 ◽

2020 ◽

Author(s):

Floris Heuff ◽

Ramon Hanssen

Keyword(s):

Time Series ◽

Greenhouse Gases ◽

Groundwater Level ◽

Peat Soil ◽

Dynamical Behavior ◽

Weather Conditions ◽

Radar Interferometry ◽

Peat Soils ◽

Rainfall Deficit ◽

The Impact

The Dutch are known for their dewatered peat pastures known as polders. These pastures are used for heavy agricultural and have to be continuously drained to compensate for the subsiding top layer due to oxidation. Additionally, the top part of the peat soil responds to changes in temperature and precipitation. Driven by moisture changes, the peat soils shrink as water is evaporated during dry, warm periods, while they swell in periods with lots of precipitation. During these dry periods, the groundwater level drops as well, mirroring the behavior of the surface. As the groundwater level drops, more organic material is exposed to air and more greenhouse gases are emitted. Monitoring the movement of the surface of the pasture could provide indirect measurements of the groundwater level and used to reveal areas that are more or less affected by a rainfall deficit. Efforts to reduce emissions can then be focused on more vulnerable areas. However, this dynamical behavior is hard to monitor with conventional geodetic means, as it is near impossible to install the required benchmarks on the soft surface of the pastures, which are needed for repeated surveying. &#160;Radar Interferometry presents an opportunity to observe this dynamic behavior without the need of installing equipment. The Sentinel-1a/b satellites pass the Dutch peat soils four times per week, providing the data necessary to observe the shrinking and swelling of the soils. We applied the technique to two study areas in the Netherlands, one between Delft and Rotterdam, where most of the pastures are situated on peat or peaty soils, and one above Zwolle in the center of Netherlands, near Staphorst, a peat-rich area. We processed all radar acquisitions between 2017 and 2019, which were averaged to 200 by 200 meter square windows to suppress noise. This is than further processed to obtain deformation time series. Based on these time series, areas more vulnerable to droughts were identified. Notably, 2018 &#8211; a very dry year, with a very large rainfall deficit &#8211; caused significantly more shrinkage than observed in 2017. We estimate that some areas shrunk up to 50 percent more. The associated drop in groundwater level exposed fresh peat to air for the first time, potentially increasing the emission of greenhouse gases significantly.Climate change exposes peat soils to new and more extreme weather conditions. Radar Interferometry can monitor the impact of these conditions on the soils and can be used to reduce greenhouse emissions more effectively.

Download Full-text