Spatio-temporal variation of depth to groundwater level and its driving factors in arid and semi-arid regions of India

Climate change and increasing anthropogenic activities,such as over-exploitation of groundwater,are exerting unavoidable stress on groundwater resources.This study investigated the spatio-temporal variation of depth to groundwater level(DGWL)and the impacts of climatic(precipitation,maximum temperature,and minimum temperature)and anthropogenic(gross district product(GDP),population,and net irrigated area(NIA))variables on DGWL during 1994-2020.The study considered DGWL in 113 observation wells and piezometers located in arid western plains(Barmer and Jodhpur districts)and semi-arid eastern plains(Jaipur,Ajmer,Dausa,and Tonk districts)of Rajasthan State,India.Statistical methods were employed to examine the annual and seasonal patterns of DGWL,and the generalized additive model(GAM)was used to determine the impacts of climatic and anthropogenic variables on DGWL.During 1994-2020,except for Barmer District,where the mean annual DGWL was almost constant(around 26.50 m),all other districts exhibited increase in DGWL,with Ajmer District experiencing the most increase.The results also revealed that 36 observation wells and piezometers showed a statistically significant annual increasing trend in DGWL and 34 observation wells and piezometers exhibited a statistically significant decreasing trend in DGWL.Similarly,32 observation wells and piezometers showed an statistically significant increasing trend and 37 observation wells and piezometers showed a statistically significant decreasing trend in winter;33 observation wells and piezometers indicated a statistically significant increasing trend and 34 had a statistically significant decreasing trend in post-monsoon;35 observation wells and piezometers exhibited a statistically significant increasing trend and 32 observation wells and piezometers showed a statistically significant decreasing trend in pre-monsoon;and 36 observation wells and piezometers reflected a statistically significant increasing trend and 30 observation wells and piezometers reflected a statistically significant decreasing trend in monsoon.Interestingly,most of the observation wells and piezometers with increasing trends of DGWL were located in Dausa and Jaipur districts.Furthermore,the GAM analysis revealed that climatic variables,such as precipitation,significantly affected DGWL in Barmer District,and DGWL in all other districts was influenced by anthropogenic variables,including GDP,NIA,and population.As a result,stringent regulations should be implemented to curb excessive groundwater extraction,manage agricultural water demand,initiate proactive aquifer recharge programs,and strengthen sustainable management in these water-scarce regions.

Using the concept of ecological groundwater level to evaluate shallow groundwater resources in hyperarid desert regions

This paper, based on the analysis and calculation of the groundwater resources in an arid region from 1980 to 2001, put forward the concept of ecological groundwater level threshold for either salinity control or the determination of ecological warning. The surveys suggest that soil moisture and soil salinity are the most important environmental factors in determining the distribution and changes in vegetation. The groundwater level threshold of ecological warning can be determined by using a network of groundwater depth observation sites that monitor the environmental moisture gradient as reflected by plant physiological characteristics. According to long-term field observations within the Ejin oases, the groundwater level threshold for salinity control varied between 0.5 m and 1.5 m, and the ecological warning threshold varied between 3.5 m and 4.0 m. The quantity of groundwater re- sources （renewable water resources, ecological water resources, and exploitable water resources） in arid areas can be calculated from regional groundwater level information, without localized hydrogeological data. The concept of groundwater level threshold of ecological warning was established according to water development and water re- sources supply, and available groundwater resources were calculated. The concept not only enriches and broadens the content of groundwater studies, but also helps in predicting the prospects for water resources development.

Influence of groundwater level change on vegetation coverage and their spatial variation in arid regions

Sampling and testing are conducted on groundwater depth and vegetation coverage in the 670 km2 of the Sangong River Basin and semi-variance function analysis is made afterwards on the data obtained by the application of geo-statistics. Results showed that the variance curve of the groundwater depth and vegetation coverage displays an exponential model. Analysis of sampling data in 2003 indicates that the groundwater depth and vegetation coverage change similarly in space in this area. The Sangong River Basin is composed of upper oasis, middle ecotone and lower sand dune. In oasis and ecotone, influenced by irrigation of the adjoining oasis, groundwater level has been raised and soil water content also increased compared with sand dune nearby, vegetation developed well. But in the lower reaches of the Sangong River Basin, because of descending of groundwater level, soil water content decreased and vegetation degenerated. From oasis to abandoned land and desert grassland, vegetation coverage and groundwater level changed greatly with significant difference respectively in spatial variation. Distinct but similar spatial variability exists among the groundwater depth and vegetation coverage in the study area, namely, the vegetation coverage decreasing (increasing) as the groundwater depth increases (decreases). This illustrates the great dependence of vegetation coverage on groundwater depth in arid regions and further implies that among the great number of factors affecting vegetation coverage in arid regions, groundwater depth turns out to be the most determinant one.

Effects of groundwater level on vegetation in the arid area of western China

At present,investigation about the relationship between the change of groundwater level and vegetation mostly focuses on specific watersheds,i.e.limited in river catchment scale.Understanding the change of groundwater level on vegetation in the basin or large scale,be urgently needed.To fill this gap,two typical arid areas in the west of China(Tarim Basin and Qaidam Basin)were chosen the a typical research area.The vegetation status was evaluated via normalization difference vegetation index(NDVI)from 2000 to 2016,sourced from MODN1F dataset.The data used to reflect climate change were download from CMDSC(http://data.cma.cn).Groundwater level data was collected from monitor wells.Then,the relationship of vegetation and climate change was established with univariate linear regression and correlation analysis approach.Results show that:Generally,NDVI value in the study area decreased before 2004 then increased in the research period.Severe degradation was observed in the center of the basin.The area with an NDVI value>0.5 decreased from 12%to 6%between 2000 and 2004.From 2004 to 2014,the vegetation in the study area was gradually restored.The whole coverage of Qaidam Basin was low.And the NDVI around East Taigener salt-lake degraded significantly,from 0.596 to 0.005,2014 and 2016,respectively.The fluctuation of groundwater level is the main reason for the change of surface vegetation coverage during the vegetation degradation in the basin.However,the average annual precipitation in the study area is low,which is not enough to have a significant impact on vegetation growth.The annual average precipitation showed an increase trend during the vegetation restoration in the basin,which alleviates the water shortage of vegetation growth in the region.Meanwhile,the dependence of surface vegetation on groundwater is obviously weakened with the correlation index is−0.248.The research results are of some significance to eco-environment protection in the arid area of western China.

Dynamic Variations and Influencing Factors of Groundwater Levels in Lhasa City

This paper focuses on the dynamic variation of groundwater level in Lhasacity. According to the data, the obvious characteristic of the groundwater level of the city is thatit is changing seasonally. Lhasa is divided into three districts according to hydrogeologicalconditions: the alluvial plain of the Lhasa-river, the alluvial plain of the Doilung-river, and thealluvial fan of inter mountain, which presents a downward trend, a slight upward trend and basicallystabilizing trend over the years individually. The analysis indicates that meteorological andhydrological factors lead to the obvious dynamic change of the groundwater level. However, more andmore human activities and over-exploitation of the groundwater cause the downward trend inthegroundwater level.

Study on the change rule of groundwater level and its impacts on vegetation at arid mining area

The shallow groundwater in Shendong mining area was broken because of large-scale underground mining activities. Selecting 32201 working-face as research area, analyzed the change rule of groundwater level and aquifer thickness under mining impact with a large number of water level observation data. Then, the impacts of groundwater level change on vegetation were analyzed by the relationship theory of arid area groundwater and vegetation. The results show that the aquifer structure and the water condition of supply flow and drainage are changed by the water proof mining. The groundwater level recovere only a little compared with the original groundwater level in two years. But the great change of groundwater level do not have notable influences on vegetation of this mining area, and further study indicates that there are certain conditions where groundwater level change impacted on vegetation. When the influence of groundwater level change was evaluated, the plant ecological water level, warning water level and spatial distribution character of original groundwater and mining-impacted groundwater-level change should be integrated.

Effects of urbanization on groundwater level in aquifers of Binh Duong Province,Vietnam

The purpose of this paper was to assess the impact of urbanization on the groundwater level(GWL)in aquifers of Binh Duong(BD)Province.The research method is to analyze the trend of GWL,the recharge capacity of surface over time and the relationship between them.The data of the GWL used in the study are the average values in the dry and rainy seasons of 35 observation wells from 2011 to 2018,which are in Pleistocene and Pliocene aquifers.The ability to recharge groundwater from the surface in this study was represented by the curve number(CN),a parameter used in hydrology for calculating direct runoff or infiltration from rainfall.The land use data to identify the CN was analyzed from the Landsat images.The results show that besides over-exploitation,the change of surface characteristic due to the urbanization development process is also the cause of the GWL decline.The analysis of seasonal GWL data shows that the increase in impervious surface area is the cause of GWL decline in the Pleistocene aquifer,which is more evident in the rainy season than in the dry season.The statistical results also show that in the rainy season and in shallow aquifers,a higher CN change can be found with the wells that had a remarkable GWL decline compared to the remaining wells.

Groundwater level prediction of landslide based on classification and regression tree

According to groundwater level monitoring data of Shuping landslide in the Three Gorges Reservoir area, based on the response relationship between influential factors such as rainfall and reservoir level and the change of groundwater level, the influential factors of groundwater level were selected. Then the classification and regression tree（CART） model was constructed by the subset and used to predict the groundwater level. Through the verification, the predictive results of the test sample were consistent with the actually measured values, and the mean absolute error and relative error is 0.28 m and 1.15%respectively. To compare the support vector machine（SVM） model constructed using the same set of factors, the mean absolute error and relative error of predicted results is 1.53 m and 6.11% respectively. It is indicated that CART model has not only better fitting and generalization ability, but also strong advantages in the analysis of landslide groundwater dynamic characteristics and the screening of important variables. It is an effective method for prediction of ground water level in landslides.

Inclusive Multiple Models(IMM)for predicting groundwater levels and treating heterogeneity

An explicit model management framework is introduced for predictive Groundwater Levels(GWL),particularly suitable to Observation Wells(OWs)with sparse and possibly heterogeneous data.The framework implements Multiple Models(MM)under the architecture of organising them at levels,as follows:(i)Level 0:treat heterogeneity in the data,e.g.Self-Organised Mapping(SOM)to classify the OWs;and decide on model structure,e.g.formulate a grey box model to predict GWLs.(ii)Level 1:construct MMs,e.g.two Fuzzy Logic(FL)and one Neurofuzzy(NF)models.(iii)Level 2:formulate strategies to combine the MM at Level 1,for which the paper uses Artificial Neural Networks(Strategy 1)and simple averaging(Strategy 2).Whilst the above model management strategy is novel,a critical view is presented,according to which modelling practices are:Inclusive Multiple Modelling(IMM)practices contrasted with existing practices,branded by the paper as Exclusionary Multiple Modelling(EMM).Scientific thinking over IMMs is captured as a framework with four dimensions:Model Reuse(MR),Hierarchical Recursion(HR),Elastic Learning Environment(ELE)and Goal Orientation(GO)and these together make the acronym of RHEO.Therefore,IMM-RHEO is piloted in the aquifer of Tabriz Plain with sparse and possibly heterogeneous data.The results provide some evidence that(i)IMM at two levels improves on the accuracy of individual models;and(ii)model combinations in IMM practices bring‘model-learning’into fashion for learning with the goal to explain baseline conditions and impacts of subsequent management changes.

Groundwater level prediction based on hybrid hierarchy genetic algorithm and RBF neural network

As the traditional non-linear systems generally based on gradient descent optimization method have some shortage in the field of groundwater level prediction, the paper, according to structure, algorithm and shortcoming of the conventional radial basis function neural network （RBF NN）, presented a new improved genetic algorithm （GA）： hybrid hierarchy genetic algorithm （HHGA）. In training RBF NN, the algorithm can automatically determine the structure and parameters of RBF based on the given sample data. Compared with the traditional groundwater level prediction model based on back propagation （BP） or RBF NN, the new prediction model based on HHGA and RBF NN can greatly increase the convergence speed and precision.

Assessment of prediction performances of stochastic models:Monthly groundwater level prediction in Southern Italy

Stochastic modelling of hydrological time series with insufficient length and data gaps is a serious challenge since these problems significantly affect the reliability of statistical models predicting and forecasting skills.In this paper,we proposed a method for searching the seasonal autoregressive integrated moving average(SARIMA)model parameters to predict the behavior of groundwater time series affected by the issues mentioned.Based on the analysis of statistical indices,8 stations among 44 available within the Campania region(Italy)have been selected as the highest quality measurements.Different SARIMA models,with different autoregressive,moving average and differentiation orders had been used.By reviewing the criteria used to determine the consistency and goodness-of-fit of the model,it is revealed that the model with specific combination of parameters,SARIMA(0,1,3)(0,1,2)_(12),has a high R^(2) value,larger than 92%,for each of the 8 selected stations.The same model has also good performances for what concern the forecasting skills,with an average NSE of about 96%.Therefore,this study has the potential to provide a new horizon for the simulation and reconstruction of groundwater time series within the investigated area.

Simulation of groundwater level recovery in abandoned mines, Fengfeng coalfield, China

Abandoned mines are of high potential risk as they could be a large underground storage of pollutants(heavy metals and organic wastes, etc.). Various physical, chemical and biological reactions would take place when groundwater flows into underground spaces, which makes abandoned mine a huge potential hazard to groundwater environment. The recovery of groundwater level is one of the key elements controlling the reactions and causing such hazards. This paper simulated groundwater level recovery processes in the abandoned mines, Fengfeng coalfield by using the computer program FEFLOW. The paper integrated the pipe flow model, "three zones" model and groundwater inrush(discharge) model in the simulation of groundwater in the complex laneway-aquifer system. Groundwater flow in the laneway systems was considered pipe flow and described in Bernoulli equation. The water-bearing medium(coal seam roof) overlying the laneway systems was divided into "three zones" composed of the caving zone, fissure zone and bending zone based on the disruption degrees of previous mining. Groundwater in the Ordovician limestone aquifer(bottom of coal seam) flowing into laneway systems was considered a major inrush/recharge source, and its flow rate was calculated by an inrush(discharge) model which was newly developed in this study and incorporated into FEFLOW. The results showed that it would take approximately 95 days for groundwater in abandoned mines to recover to regional groundwater level elevation, and the total amount of water filling up would be about 1.41195×10~7 m^3, which is consistent with the actual data. The study could be of theoretical and practical significance to mitigate abandoned mines' hazards and improve mine groundwater utilization.

NARX neural network approach for the monthly prediction of groundwater levels in Sylhet Sadar, Bangladesh

Groundwater is important for managing the water supply in agricultural countries like Bangladesh. Therefore, the ability to predict the changes of groundwater level is necessary for jointly planning the uses of groundwater resources. In this study, a new nonlinear autoregressive with exogenous inputs(NARX) network has been applied to simulate monthly groundwater levels in a well of Sylhet Sadar at a local scale. The Levenberg-Marquardt(LM) and Bayesian Regularization(BR) algorithms were used to train the NARX network, and the results were compared to determine the best architecture for predicting monthly groundwater levels over time. The comparison between LM and BR showed that NARX-BR has advantages over predicting monthly levels based on the Mean Squared Error(MSE), coefficient of determination(R^2), and Nash-Sutcliffe coefficient of efficiency(NSE). The results show that BR is the most accurate method for predicting groundwater levels with an error of ± 0.35 m. This method is applied to the management of irrigation water source, which provides important information for the prediction of local groundwater fluctuation at local level during a short period.

Rainfall and Obtaining Information Regarding Earthquake Development Processes from Groundwater Level

Many factors can cause changes of groundwater level,such as the development process of an earthquake,rainfall,solid earth tides etc.Among these we are interested in information regarding earthquake development processes.Eliminating the influence of various disturbance factors is an effective way to obtain seismic development process information contained in the groundwater level.This paper provides two different ways to remove the rainfall effect,and compares the two methods by means of correlation analysis.Furthermore,based on these a logistic regression model is established to describe the seismicity level.

Using River Altitude Determined from a SRTM DEM to Estimate Groundwater Levels of the Tokwe and Mutirikwi Watersheds in Zimbabwe

Groundwater resources provide most of the domestic water supply in rural Zimbabwe and support poverty reduction through irrigation facilities. Most agricultural and environmental plans need water table depth analysis as an input in designing best management strategies. There are limited direct measurements of groundwater levels in Zimbabwe due to high costs and the limited human expertise. The study is aimed at coming up with a proof of concept that altitude of rivers as determined by an SRTM digital elevation model can be used to estimate the levels of groundwater in parts of Mutirikwi and Runde sub catchments of southern Zimbabwe. The study also maps the groundwater levels of the area as determined by river altitude from the digital elevation model. Firstly, the groundwater levels for nine boreholes are measured. Secondly, the altitude of a river bed nearest to each borehole site is extracted from a digital elevation model. Finally, the Spearman’s correlation coefficient is used to determine the nature and strength of the relationship between the two variables. Linear regression analysis was also used to obtain the predictive equation of the relationship and its coefficient of determination. After the relationship between groundwater and river altitude is established, 9 new random points of river altitude are generated across the study area interpolated using kriging interpolation to give the estimated altitude of river altitude. The altitude of groundwater is then determined by running the predictive equation Y = 0.8736 * X + 0.852 obtained from regression analysis. The depth to groundwater level of area is obtained by subtracting the determined groundwater altitude from the SRTM DEM. The results show strong positive and statistically significant (ρ = 0.000, α = 0.01) correlation coefficient of 0.971 between measured groundwater levels and altitude of rivers. The regression model shows a coefficient of determination (r2) of 0.975. The research therefore determines that altitude of rivers and use of geostatistics can produce physically plausible estimates of groundwater levels in the study area.

Attribution analysis of groundwater level fluctuation in the Xinxiang section of the Lower Yellow River's suspended river after the construction of the Xiaolangdi Reservoir

The clear identification and quantification of the factors affecting groundwater systems is crucial for protecting groundwater resources and ensuring safety in agricultural production.The Lower Yellow River(LYR)is a suspended river that replenishes groundwater continuously due to clear differences in the water head,especially in the Xinxiang section.Since its construction,the Xiaolangdi Reservoir has reversed the LYR’s deposition.To accurately determine the factors influencing the groundwater level(GWL),the study area was divided into five subzones based on hydrogeology.A dynamic factor model(DFM),variational mode decomposition(VMD),and a multiple linear regression model were used to identify and quantify the factors influencing the GWL.The impact of the suspended river on the groundwater before and after the construction of the Xiaolangdi Reservoir was examined.The results show that:(1)The rate of decrease in the GWL was 8.53×10^(–4)m/month,and the rate of decrease in the Yellow River water level(RWL)was 4.63×10^(–4)m/month.(2)Mountain front recharge(MFR)(scale=3 months)and precipitation(scale=9 months)were the dominant factors in subzones I and II,accounting for more than 40%of the fluctuation in the GWL.Subzone III was dominated by exploitation(scale=7 months)and precipitation(scale=12months),accounting for 28.43%,and 23.44%of changes in the GWL,respectively.In subzone IV,agricultural irrigation(scale=12 months)was the major factor,accounting for32.47%of GWL changes,while in subzone V,the RWL(scale=12 months)accounted for52.52%of these changes.(3)The Xiaolangdi Reservoir has increased the lateral seepage of the suspended river and altered the inter-annual distribution.The results of this study can provide a valuable reference for controlling groundwater overexploitation and ensuring water supply security.

Experimental analysis on the interaction between underground structures and sand layer under groundwater level change

Groundwater level change stands a momentous role in affecting the geotechnical construction stability and safety of underground structures.Global warming and active underground construction cause conspicuous changes in the groundwater level,which further leaves an impact on the underground structures’serviceability.To reveal the interaction between underground structure and soil under groundwater level change in the sand layer,model tests of circular transportation tunnel and rectangular utility tunnel were carried out.With the self-designed experimental equipment and innovative experimental methods,the changes in tunnel stress,bending moment,buoyancy,and vertical displacement of the rise and drawdown of the groundwater level in the sand layer were studied.The results revealed the developments of concentrated structural forces during the rising and falling process of the groundwater water level,indi-cating critical locations that should be strengthened.Meanwhile,both tunnels showed the same movement trend:settling first,floating afterwards and settling at last.And it is concluded that no reduction is required when calculating buoyancy in sands using measured pore pressure.Conclusions can provide a notable reference for future related research and engineering designs.

Physiological Responses of Three Contrasting Plant Species to Groundwater Level Changes in an Arid Environment

Plants growing on both sides of the Tarim River in western China serve as a natural barrier containing the deserts and protecting the oasis, and their growth is greatly affected by water conditions In their local habitat. We studied the physiological responses of three different types plants （i.e. Populus euphratlca Oliver, Tamarix ramosissima L., and Apocynum venetumas Linn） to changing groundwater levels by analyzing changes in chlorophyll, soluble sugar, proline （Pro）, malondialdehyde （MDA）, superoxlde dlsmutase （SOD）, peroxidase （POD）, indoleacetic acid （IAA）, giberellic acid, abscisic acid （ABA） and cytokinin （CK）. Relationships between these physiological characteristics and groundwater levels were analyzed in order to assess the drought tolerance of the three plant species based on the values of average membership function. We found that MDA, SOD and ABA were more susceptible to changes in groundwater level, followed by POD, IAA and CK. Among the three plant species, Populus euphratica responded physiologically less to changing groundwater level than T. ramosissima and A. venetumas.

Removing barometric pressure effects from groundwater level and identifying main influential constituents

Changes in barometric pressure can affect the micro-dynamic state of groundwater level.The groundwater level data carry a lot of important information of tectonic activity and earthquakes.It is very significant to eliminate the barometric pressure effects from the groundwater level data in order to recognize seismic anomalies effectively.With the analysis of the main influential constituents of barometric pressure and their changes,we can have a better understanding of the changes of the aquifer medium,which can provide useful information for earthquake prediction.Taking the May 12,2008 Wenchuan earthquake as an example,this paper deals with the influence of barometric pressure on groundwater level based on observational data from Nanxi,Qionglai and Chaohu wells.The methods of the linear regression and the deconvolution regression were employed to remove the barometric pressure from the groundwater level data.The harmonic analysis and the spectral analysis were used to recognize the main influential waves of barometric pressure effect.A comparison was conducted on the main influential waves before and after the earthquake.The results showed that the main influential waves of barometric pressure effect changed and the amplitudes of all constituents also changed.This phenomenon may result from the characteristics of the influential constituents of pressure,or from the changes of the aquifer medium,which were caused by the earthquake.

Groundwater Level Predictions Using Artificial Neural Networks

The prediction of groundwater level is important for the use and management of groundwater resources. In this paper, the artificial neural networks (ANN) were used to predict groundwater level in the Dawu Aquifer of Zibo in Eastern China. The first step was an auto-correlation analysis of the groundwater level which showed that the monthly groundwater level was time dependent. An auto-regression type ANN (ARANN) model and a regression-auto-regression type ANN (RARANN) model using back-propagation algorithm were then used to predict the groundwater level. Monthly data from June 1988 to May 1998 was used for the network training and testing. The results show that the RARANN model is more reliable than the ARANN model, especially in the testing period, which indicates that the RARANN model can describe the relationship between the groundwater fluctuation and main factors that currently influence the groundwater level. The results suggest that the model is suitable for predicting groundwater level fluctuations in this area for similar conditions in the future.