Groundwater Monitoring Research Articles

Impact of hydrogeology factors on geotechnical conditions of the heritage Kyiv-Pechersk Lavra Monastery complex: Lessons from three decades of monitoring

Abstract The architectural ensemble of the Kyiv-Pechersk Lavra monastery located in the city of Kyiv on the Right Bank of the Dnipro River, which represents historical and cultural heritage of world significance, suffers from a wide range of hazardous geological processes. The review and analysis of data of the long-term (since the 1990s) groundwater monitoring studies of the Kyiv-Pechersk Lavra shows that hydrogeological hazards caused by a complex combination of natural and anthropogenic factors (as well as sometimes by engineering miscalculations) have led to a significant number of emergency situations that threaten the heritage architectural monuments. Monitoring data illustrate a wide range of hydrogeological hazards (flooding, subsidence, landslides, suffusion), and emphasize the importance of consideration of hydrogeological aspects for safeguarding architectural monuments in the urbanized context. The paper also summarizes experience in engineering measures aimed at mitigating of hydrogeological hazards and discusses the pending research tasks

Evaluating the impact of emerging hydro-geophysical technologies on sustainable water resource management

Emerging hydrogeophysical technologies are revolutionizing the management of water resources, providing unprecedented insights and enhancing sustainability practices. This article examines recent advancements in hydrogeophysical methods, focusing on time-lapse electromagnetic techniques, unmanned aerial vehicles (UAVs), and artificial intelligence (AI). Through a comprehensive review of the literature and practical case studies, including notable implementations in Africa, the paper highlights how these innovations improve groundwater monitoring, resource management, and predictive capabilities. Time-lapse electromagnetic methods have achieved up to 1-meter resolutions, significantly enhancing groundwater mapping accuracy (Binley & Kemna, 2005). With their high-resolution remote sensing capabilities, UAVs have facilitated detailed hydrological surveys, while AI-driven analyses optimize groundwater predictions and management strategies (Rennie et al., 2021). The study presents a cost-benefit analysis showing a 20-30% reduction in operational costs and a 40% increase in data accuracy. Challenges such as technical limitations and high initial costs are discussed, alongside potential solutions and prospects. The findings underscore the transformative potential of these technologies for achieving sustainable water resource management, offering actionable insights for policymakers, researchers, and practitioners in the field.

Guardians of the aquifers: ehancing Rome’s groundwater monitoring network

This paper proposes a methodology for managing groundwater monitoring directly in the field through a specific data entry system installed on mobile devices and a relational geographic database that allows the visualization and querying of data via a specific web interface. The study area is the city of Rome, where a monitoring system of approximately 150 piezometers and wells, currently manually monitored twice a year. The proposed method uses the Enterprise cloud platform (ESRI, 2024) managed by ISPRA-SNPA, which guarantees the repository of the data collected in an online cloud system and the use of Web applications. The data of the time series of levels and chemical-physical parameters such as temperature, pH, conductivity are freely accessible through attribute tables, graphs, and viewer elements. The results highlight numerous possibilities for expanding the network of active wells, enabling the use of groundwater resources for adaptation measures to address ongoing climate change.

Spatial Distribution of Groundwater Fluctuation Mapping Using Arc-GIS in Hosur-1 Micro-watershed of Karnataka, India

Groundwater is a primary source of freshwater and used mainly for agriculture and irrigation purposes. Recharge to groundwater is the most important component in all the water balance studies. In the present study krigging technique was used for interpolate the groundwater level of the Hosur-1 micro watershed (Kanakvad sub watershed) in Gadag district of Karnataka state. In Hosur-1 micro- watershed 41 wells are there in the vicinity of major stream of the micro- watershed. The mean depth of ground water levels in the micro- watershed were monitored at a monthly frequency during January-2023 to March-2024. It was found that the maximum average depth of bore wells are about 9.55 mts and lowest average depth of borewell about 4.64 mts. The groundwater table between 2.48 to 14.70 mbgl during summer season period and 3.18 to 21.50 mbgl during the Rabi season. The pH of ground water varied between 7.0-9.0, maximum pH was recorded as 8.9 and minimum was recorded as 7.29 and maximum conductivity >3.82 ds/m and minimum 0.87 ds/m was recorded at Hosur-1 micro-watershed. The average infiltration rate of clay soil 2.73 mm/hr and R2 value for the trend line reaches the value of 0.5876. In case of sandy clay loam average infiltration rate was 3.83 mm/hr and R2 value for the trend line reaches 0.6572. It necessitates continuous monitoring of groundwater for assessing the possible damage on salinity and alkalinity induced soil health.

Where has hydrogeologic science been, and where is it going? Research trends in hydrogeology publishing over the past 60 years

AbstractQuantifying historical research trends in the field of hydrogeology is not only generally informative for hydrogeologists but is essential for fostering interdisciplinary collaboration and assessing the relationship between academic study and societal interests in hydrogeologic issues. To address this, a topic model was applied to over 37,000 academic abstracts published in over 20 journals between 1963–2022 in the field of hydrogeology to study the evolution of topic trends through time. Model results were fed into the popular large-language model ChatGPT to assign topic names, representing an unsupervised method. The results indicate that, historically, popular topics related to methodological development and analytical and numerical models analytical and numerical methods in groundwater flow modeling and well hydraulics have given way to topics related to more increasingly complex models (groundwater monitoring and uncertainty estimation and groundwater modeling calibration and simulation) as data and computational capability becomes increasingly available. An insight into the period of boom-and-bust in contaminant hydrogeology is reflected by a shift in focus from topics related to assessment and characterization of contaminant sources toward topics related to degradation and remediation methods. Topics of emerging prevalence (sustainable groundwater resource management, catchment hydrology and runoff processes) in the current period reflect an increasing focus on treating the surface-water/groundwater system as a single system. In addition, results suggest that topic distribution within the field of hydrogeology has become more varied as time has progressed.

Mechanisms of evolution and pollution source identification in groundwater quality of the Fen River Basin driven by precipitation

Groundwater pollution has attracted widespread attention as a threat to human health and aquatic ecosystems. However, the mechanisms of pollutant enrichment and migration are unclear, and the spatiotemporal distributions of human health risks are poorly understood, indicating insufficient groundwater management and monitoring. This study assessed groundwater quality, human health risks, and pollutant sources in the Fen River Basin(FRB). Groundwater quality in the FRB is good, with approximately 87 % of groundwater samples rated as “excellent” or “good” in both the dry and rainy seasons. Significant precipitation elevates groundwater levels, making it more susceptible to human activities during the rainy season, slightly deteriorating water quality. Some sampling points in the southern of Taiyuan Basin are severely contaminated by mine drainage, with water quality index values up to 533.80, over twice the limit. Human health risks are mainly from As, F, NO3−, and Cr. Drinking water is the primary pathway of risk. From 2019 to 2020, the average non-carcinogenic risk of As, F, and NO3− increased by approximately 28 %, 170 % and 8.5 %, respectively. The average carcinogenic risk of As and Cr increased by 28 % and 786 %, the overall trend of human health risks is increasing. Source tracing indicates As and F mainly originate from geological factors, while NO3− and Cr are significantly influenced by human activities. Various natural factors, such as hydrogeochemical conditions and aquifer environments, and processes like evaporation, cation exchange, and nitrification/denitrification, affect pollutant concentrations. A multi-tracer approach, integrating hydrochemical and isotopic tracers, was employed to identify the groundwater pollution in the FRB, and the response of groundwater environment to pollutant enrichment. This study provides a scientific basis for the effective control of groundwater pollution at the watershed scale, which is very important in the Loess Plateau.

Protection of groundwater resources from multi-hazards: An integration of risk assessment and watershed management

The improving groundwater resource protection depends on aligning contamination risk mapping with aquifer protection measures. However, existing methods often fail to align with aquifer protection goals, hindering practical implementation. The study demonstrated integrating vulnerability assessment, hazard evaluation, and groundwater protection initiatives using an L-Matrix approach. Testing this model in a well-documented watershed with multiple hazards to illustrates its applicability, providing a reference for similar scenarios. The risk was assessed through evaluation of aquifer vulnerability, using the DRASTIC method, coupled with the evaluation of a hazard potential considering industrial, livestock/agriculture and urban infrastructure sources in separate. The L-Matrix diagrams consisted of cartesian representations of V versus H, ranging from 0 to 1, segmented into four quadrants bounded by the cut-off lines V = 0.5 and H = 0.5. The quadrants were then linked to aquifer protection measures, with site inspection (high V and H), groundwater monitoring (low V and high H), land use planning (high V and low H), and tolerable expansion of hazardous activities (low V and H). The Paraopeba River basin was used as test site. Mining areas are abundant in this basin and were allocated high values of H and low to high values of V, requesting implementation of groundwater monitoring and periodic inspection of mining sites, even more because groundwater contamination with iron could be clearly associated with the presence of mine-tailings. In the results, it was observed that the DRASTIC vulnerability map of the aquifers has a mean vulnerability around the central value (V = 0.48 ± 0.08). Regarding the distribution of hazards, the average rounds to the value for to (Hindustry = 0.41 ± 0.37, Hagriculture = 0.33 ± 0.09 and Hinfrastructure = 0.27 ± 0.14). Thus, it is noted that for industrial activities, the risk of contamination could be moderate to high, while for agricultural and livestock activities, the risk lies between low and moderate contamination impact.

The GIS framework is used to assess Lucknow City's groundwater quality using the water quality index [WQI

Monitoring groundwater quality continuously is essential to reducing the dangers of geochemical pollutants through suitable treatment techniques and guaranteeing safe drinking and irrigation. Thus, this study's main goal was to evaluate the appropriateness of the groundwater that was collected, from India's Lucknow for irrigation as well as drinking. To assess the quality of the groundwater in the research area, ten samples were taken from various locations. Analysis was done on some parameters, including pH, total dissolved solids (TDS), electrical conductivity (EC), total hardness, total alkalinity, BOD, COD, nitrate, total nitrogen, E. Coli, and ammonia. The water quality index (WQI) has arithmetical weights. Using a critical grading system that shows overall quality, the water's quality was evaluated and categorized as very good, good, moderate, bad, and unfit for consumption. Increasing public understanding and decision-making to make informed choices about efficient care, management, and long-term, sustainable social growth is greatly aided by this classification. To find relationships between the different parameter values, a correlation matrix was created and examined. As a result, the results imply that the groundwater in the investigated region is secure and appropriate for irrigation and consumption.

Direct and Remote Sensing Monitoring of Plant Salinity Stress in a Coastal Back-Barrier Environment: Mediterranean Pine Forest Stress and Mortality as a Case Study

The increase in atmospheric and soil temperatures in recent decades has led to unfavorable conditions for plants in many Mediterranean coastal environments. A typical example can be found along the coast of the Campania region in Italy, within the “Volturno Licola Falciano Natural Reserve”, where a pine forest suffered a dramatic loss of trees in 2021. New pines were planted in 2023 to replace the dead ones, with a larger tree layout and interspersed with Mediterranean bushes to replace the dead pine forest. A direct (in situ) monitoring program was planned to analyze the determinants of the pine salinity stress, coupled with Sentinel-2 L2A data; in particular, multispectral indices NDVI and NDMI were provided by the EU Copernicus service for plant status and water stress level information. Both the vadose zone and shallow groundwater were monitored with continuous logging probes. Vadose zone monitoring indicated that salinity peaked at a 30 cm soil depth, with values up to 1.9 g/L. These harsh conditions, combined with air temperatures reaching peaks of more than 40 °C, created severe difficulties for pine growth. The results of the shallow groundwater monitoring showed that the groundwater salinity was low (0.35–0.4 g/L) near the shoreline since the dune environment allowed rapid rainwater infiltration, preventing seawater intrusion. Meanwhile, salinity increased inland, reaching a peak at the end of the summer, with values up to 2.8 g/L. In November 2023, salts from storm-borne aerosols (“sea spray”) deposited on the soil caused the sea-facing portion of the newly planted pines to dry out. Differently, the pioneer vegetation of the Mediterranean dunes, directly facing the sea, was not affected by the massive deposition of sea spray. The NDMI and NDVI data were useful in distinguishing the old pine trees suffering from increasing stress and final death but were not accurate in detecting the stress conditions of newly planted, still rather short pine trees because their spectral reflectance largely interfered with the adjacent shrub growth. The proposed coupling of direct and remote sensing monitoring was successful and could be applied to detect the main drivers of plant stress in many other Mediterranean coastal environments.

Groundwater monitoring infrastructure: Evaluation of the shallow urban and coastal network in Ōtautahi Christchurch

Study regionŌtautahi Christchurch, New Zealand Study focusUrban shallow groundwater monitoring networks are becoming widespread in New Zealand and globally. A reliable groundwater monitoring infrastructure is important to develop knowledge on water table aquifers in coastal cities like Ōtautahi Christchurch. Previous investigations have shown shallow groundwater vulnerability to salinisation and contamination in urban settings, and shallow groundwater exacerbates flooding from climate change and the impact of rising sea levels. New hydrological insights for the regionFollowing the 2010–2011 Canterbury earthquake sequence, shallow groundwater data acquisition and the establishment of a geotechnical database in Ōtautahi Christchurch provided unprecedented information on subsurface conditions. The installation of the groundwater monitoring infrastructure opened the field of New Zealand-based urban hydrogeological studies, including continuous measurements of groundwater levels. This study presents the hydrogeological context of Ōtautahi Christchurch, provides an overview of seismic impacts on groundwater, and documents the monitoring network’s development. Methods for assessing the monitoring network included field surveys and digital information review. The overall good condition and robustness of the network mean the dataset held by the city and regional councils should be more widely used to benefit the community. Implications for researchers and network asset managers mean that the maintenance and availability of the data should be prioritised. Records from urban shallow groundwater monitoring networks are becoming an essential source of information to manage urban water resources under climate change and sea-level rise conditions.

Coordinated analysis of groundwater spatiotemporal chemical characteristics, water quality, and potential human health risks with sustainable development in semi-arid regions.

The emergence of large-scale time-series data and advancements in computational power have opened new avenues for analyzing the spatiotemporal evolution of groundwater chemistry, water quality, and human health risks. This paper utilizes hydrogeochemical methods to elucidate the controlling factors of water chemical components based on the test results of 124 groundwater samples collected from 31 monitoring wells in Fuxin City, Liaoning Province, China, from 2018 to 2021. By integrating the Random Forest and Enhanced Water Quality Index methods for water quality assessment and employing the Human Health Risk Assessment (HHRA) model to analyze human health risks, our findings indicate that the groundwater is mildly alkaline, with SO4·Cl-Ca·Mg and HCO3-Ca·Mg as the dominant hydrochemical types, primarily derived from the dissolution of carbonate and silicate minerals such as dolomite, limestone, and andesite, and cation exchange reactions. The EI_RF water quality evaluation model reveals that the overall water quality in the study area is poor, with Class I and II water quality zones mainly located in the northeastern and central parts of the study area, showing a gradual transition from Class I and II in the northeast to Classes IV and V in the southwest, significantly influenced by NO3-, TH, TDS, and SO42-. The HHRA model results indicate that the potential non-carcinogenic risk of groundwater nitrates has a severe impact on infants, with the spatial distribution being low in the northeast and high in the southwest. Due to industrial activities, agricultural practices, and population growth, certain areas in developing countries such as China and India exhibit nitrate concentrations significantly higher than those in most international regions, highlighting global environmental and public health challenges. This underscores the importance of enhancing groundwater monitoring and implementing measures to mitigate pollution. These research outcomes hold significant implications for the government in formulating rational protection and management measures to ensure the sustainable utilization of groundwater resources.

Analysis of the evolution and causes of groundwater chemistry after ecological water replenishment of the Jialu River, China

Ecological water replenishment is an important measure for conserving water sources and improving the water environment. To explore the evolution and causes of groundwater chemistry after ecological water replenishment in the Jialu River, this study utilized groundwater monitoring data from 2015 to 2019 following ecological water replenishment. Various methods, including Piper’s trilinear diagram, Gibbs diagram, principal component analysis, and ion ratio analysis, were employed for research purposes. The results indicate that (1) since the implementation of ecological water replenishment in the Jialu River, there has been a general downwards trend in total dissolved solids (TDS) in groundwater. The dominant cation in groundwater is Ca2+, whereas HCO3− is the dominant anion. The concentration of cations in groundwater has generally decreased, with noticeable reductions in SO42− and Cl− concentrations in the upper reaches of the recharge river contributing to improved groundwater quality. (2) A comparison with 2015 reveals a gradual transition at sampling points from chemical types such as HCO3-Ca·Mg and HCO3·Cl–Ca·Mg to an ecological water replenishment chemical type (HCO3-Ca).

Assessment of the Impact of Coal Mining on Water Resources in Middelburg, Mpumalanga Province, South Africa: Using Different Water Quality Indices

The objective of this study was to assess the water quality status of the surface water and groundwater resources in the Middelburg area, South Africa. The assessment was addressed using combined water quality indices, investigating selected chemical parameters over four different seasons for a period of five years from 2017 to 2021. A combination of the Canadian Council of Ministers of the Environment water quality index and the comprehensive pollution index was used to analyze the water quality status of surface water and groundwater of the town of Middelburg, situated near coal mining activities in Mpumalanga, South Africa. The combination of the indices indicated that some surface water monitoring sites ranged between poor to fair water quality. Groundwater monitoring points also showed a poor to fair ranking. The comprehensive pollution index confirmed that some sites showed very poor water quality in the summer seasons, exceeding expected limits for the period 2017 to 2021. The principal component analysis further showed that both surface water and groundwater sites had high levels of contamination with increased chemical parameters. The results were compared against the different water quality guidelines. In an extensive monitoring program, water management systems must be properly implemented to mitigate impacts on water resources.

Microbial Metagenomics Revealed the Diversity and Distribution Characteristics of Groundwater Microorganisms in the Middle and Lower Reaches of the Yangtze River Basin.

Groundwater is one of the important freshwater resources on Earth and is closely related to human activities. As a good biological vector, a more diverse repertory of antibiotic resistance genes in the water environment would have a profound impact on human medical health. Therefore, this study conducted a metagenomic sequencing analysis of water samples from groundwater monitoring points in the middle and lower reaches of the Yangtze River to characterize microbial community composition and antibiotic resistance in the groundwater environment. Our results show that different microbial communities and community composition were the driving factors in the groundwater environment, and a diversity of antibiotic resistance genes in the groundwater environment was detected. The main source of antibiotic resistance gene host was determined by correlation tests and analyses. In this study, metagenomics was used for the first time to comprehensively analyze microbial communities in groundwater systems in the middle and lower reaches of the Yangtze River basin. The data obtained from this study serve as an invaluable resource and represent the basic metagenomic characteristics of groundwater microbial communities in the middle and lower reaches of the Yangtze River basin. These findings will be useful tools and provide a basis for future research on water microbial community and quality, greatly expanding the depth and breadth of our understanding of groundwater.

Multi-decadal groundwater observations reveal surprisingly stable levels in southwestern Europe

Climate change and human activity are leading to water scarcity in southwestern Europe. Groundwater use is thought to be unsustainable in the region, yet regional assessments using measured data are missing. Here, we evaluate long-term trends and drivers of groundwater levels and found a more complex situation. Historical data (1960–2020) from 12,398 wells in Portugal, Spain, France, and Italy showed 20% with rising groundwater levels, 68% were stable, and only 12% were declining. Rising wells in temperate climates were due to increased precipitation. Recovering wells in semi-arid regions were attributed to improved groundwater management. Stable wells are concentrated in temperate climates with year-round high precipitation. Declining wells in semi-arid regions are primarily located near agricultural areas and experience prolonged summer soil moisture loss, whereas in temperate regions, the decline is associated with large urban areas. Systematic groundwater monitoring and data sharing are essential for sustainable and science-based water resources management.

Rising groundwater levels in Dare County, North Carolina: implications for onsite wastewater management for coastal communities

ABSTRACT Onsite wastewater treatment systems (OWTS) are a common wastewater treatment approach in coastal communities. Vertical separation distance (VSD) requirements between the drainfield and groundwater aim to ensure aerated soils for wastewater treatment. When the VSD declines, OWTS can fail. This study evaluated groundwater response to sea level rise (SLR) and the implications for OWTS. A groundwater monitoring network (13 wells) was used to evaluate groundwater depth in Dare County, North Carolina. Groundwater levels were measured with water level meters and pressure transducers. Trends in groundwater depth and SLR were analyzed to evaluate the influence of SLR on groundwater depth. From 1984–2022, mean groundwater levels have risen (∼7.6 mm/year) in response to SLR. Currently, sites at <2.7 m land elevation are most likely to have groundwater depths <1 m and inadequate VSD. Based on current precipitation and NOAA intermediate SLR projections, groundwater depth projections suggest that OWTS at lower elevations are more likely to experience groundwater inundation by 2040–2060. SLR has resulted in reduced VSD causing diminished wastewater treatment capacity in low-lying areas. OWTS VSD requirements are typically static due to regulatory constraints. Future management approaches should consider adapting to rising coastal groundwater levels because of increasing wastewater contamination risks.

Assessing the groundwater quality of El Fahs aquifer (NE Tunisia) using multivariate statistical techniques and geostatistical modeling

This study is the first attempt to characterize the quality status of El Fahs aquifer by combining graphical tools, multivariate statistical techniques and traditional geostatistical methods. Water samples are collected from thirty-six observation wells during April 2016 to characterize the physicochemical properties of the aquifer. Subsequently, these samples are partitioned into three hydrochemically distinct water classes (i.e., C1, C2, and C3) using the K-means clustering method. Principal Component Analysis is used to reduce the dimensionality of the dataset prior performing the clustering computations, resulting in clusters of higher quality than the non-reduced case in terms of Silhouette coefficient. Piper diagram is used to display the chemical composition of the samples, revealing the dominant role of Mg–Ca–Cl water type for all three classes, whereas Sodium and Sulfate were found to be the second most important cations and anions respectively. Indicator kriging (IK) is used to identify the probability of occurrence of the hydrochemical classes beyond the sampling locations. It is found that Class 1, associated with fresh groundwater component, is most probable to occur at the central part of the plain, mainly due to the presence of a dense hydrological network, whereas Classes 2 (agricultural activities) and 3 (dissolution of evaporate geological formations) are expected to occur at the southern and northern regions respectively. IK also identified the regions associated with high levels of uncertainty, mostly occurring in a large portion of the northern area due to the absence of available hydrochemical information. The results showed that integration of graphical methods, multivariate statistical techniques and geostatistical modeling, is an efficient approach for characterizing the hydrochemical status of the aquifer system, to spatially optimize the groundwater monitoring well networks and quantify the uncertainty levels of the water classes in a systematic way.

Geologic and Tectonic Controls on Deep Fracturing, Weathering, and Water Flow in the Central California Coast Range

AbstractThe creation of fractures in bedrock dictates water movement through the critical zone, controlling weathering, vadose zone water storage, and groundwater recharge. However, quantifying connections between fracturing, water flow, and chemical weathering remains challenging because of limited access to the deep critical zone. Here we overcome this challenge by coupling measurements from borehole drilling, groundwater monitoring, and seismic refraction surveys in the central California Coast Range. Our results show that the subsurface is highly fractured, which may be driven by the regional geologic and tectonic setting. The pervasively fractured rock facilitates infiltration of meteoric water down to a water table that aligns with oxidation in exhumed rock cores and is coincident with the adjacent intermittent first‐order stream channel. This work highlights the need to incorporate deep water flow and weathering due to pervasive fracturing into models of catchment water balances and critical zone weathering, especially in tectonically active landscapes.

Anomaly detection in groundwater monitoring data using LSTM-Autoencoder neural networks.

Groundwater monitoring data can be prone to errors and biases due to various factors like borehole and equipment malfunctions, or human mistakes. These inaccuracies can jeopardize the groundwater system, leading to reduced efficiency and potentially causing partial or complete failures in the monitoring system. Traditional anomaly detection methods, which rely on statistical and time-variant techniques, struggle to handle the complex and dynamic nature of anomalies. With advancements in artificial intelligence and the growing need for effective anomaly detection and prevention across different sectors, artificial neural network methods are emerging as capable of identifying more intricate anomalies by considering both temporal and contextual aspects. Nonetheless, there is still a shortage of comprehensive studies on groundwater anomaly detection. The intricate patterns of sequential data from groundwater present numerous challenges, necessitating sophisticated modeling techniques that combine mathematics, statistics, and machine learning for viable solutions. This paper introduces a model designed for high accuracy and efficient computation in detecting anomalies in groundwater monitoring data through a probabilistic approach. We employed the Monte Carlo method and SEAWAT numerical simulation to ascertain the uncertainty in groundwater salinity. Subsequently, a Long Short-Term Memory (LSTM)-Autoencoder model was trained and evaluated, forming the basis of an anomaly detection framework. Each piece of training data was assessed by the LSTM-Autoencoder using the Negative Log Likelihood (NLL) score and a predefined threshold to determine the data's abnormality percentage. The accuracy evaluation of the proposed LSTM-Autoencoder algorithm revealed that this approach achieved commendable performance, with an accuracy of 98.47% in anomaly detection.

Analyzing water level variability in Odisha: insights from multi-year data and spatial analysis

A comprehensive analysis of long-term water level trends is essential for freshwater sustainability. Given that Odisha heavily relies on agriculture, the monitoring and management of groundwater and its fluctuations are imperative for ensuring future sustainability in the state. Here, we analyzed the trend in Groundwater using water level data for a 30-year period (1990–2020) for the entire Odisha region. Moreover, to determine the long term variability, critical zones of future groundwater variability and controlling parameters of the water level change, we used spatio-temporal water level data of 746 locations. Water level rise of coastal districts during post-monsoon (POM), corresponds to the intensity of rainfall received, thus rising, however other districts of Odisha, showing decline in water level during the same season is due to shortage of rainfall, increase in population at a sudden, and over pumping due to industrial activities. Similarly, during pre-monsoon (PRM), water level shows an increasing trend in hard rock terrain of Odisha implying rabi crop irrigation, high density drainage network and lesser population density. Feature selection techniques were used in this study to know the parameters controlling most to this water level fluctuation in the entire Odisha state. Precipitation followed by landuse & landcover, lithology and population density are controlling the most for the long term water level change. Drainage, elevation, lithology and slope are positively related to the water level change while others are negatively related. It is also inferred that the districts like Mayurbhanj, Sundargarh, Keonjhar, Kandhamal, Boudh, Dhenkanal, Gajapati, Koraput and Kalahandi contain most of the high critical zone concerning future availability of groundwater while most of the coastal regions are safe.