Groundwater Susceptibility Research Articles

Assessment of groundwater susceptibility to contamination using GIS-based modified DRASTIC model in the Rib watershed, Upper Abay Basin, Ethiopia

ABSTRACT Groundwater is one of the most important sources of freshwater, contributing significantly for drinking and other domestic activities around the world. However, its quality is deteriorating over time due to overexploitation and anthropogenic activities. Rib watershed is located in the Tana basin (Ethiopia), is intensively cultivated and urbanizing area. Therefore, this study attempted to assess groundwater vulnerability to pollution using the GIS-based Modified DRASTIC Model. The modified DRASTIC model was selected due to it incorporates both hydrogeological parameters and anthropogenic factors for assessment. The necessary data were collected from the field, and downloaded from websites and laboratory experiments (No3 -). The results showed that more than 73.24% of the watershed is under medium to high vulnerability. Highly vulnerable areas of the watershed (22.48%) was confined to the Southern parts of the watershed (under built-up and cultivated areas). Based on single parameter sensitivity analysis, its vulnerability was highly influenced by aquifer media (24.1%), net recharge (21.75%), land use/land cover (15.1%), and depth of groundwater table (13.6%). The Modified drastic model was validated based on the observed data of nitrate concentration in groundwater. Based on the observed data of nitrate concentration, high-vulnerable areas were more contaminated than medium and low-vulnerable areas. The modified drastic index has a strong correlation with nitrate concentration with (r = 0.76) and (P < 0.043). Therefore, the result indicated that the area is vulnerable to contamination calling for appropriate groundwater management. Hence, this finding helps to plan and minimize future contamination of groundwater by considering its vulnerability before high-risk activities are allowed.

Evaluation of groundwater quality for drinking water using a quality index in Abyi Adi, Tigrai, Northern Ethiopia

High quality, safe and sufficient drinking water is essential for public health and well-being. However, the war on Tigrai damaged the water sources of communities and pose people to health problems. Therefore, the aim of the present study was to assess the quality of water of the town of Abyi Adi, Tigrai, Northern Ethiopia using physicochemical and biological parameters and water quality indices. A total of 36 water samples were collected from four major water sources. The physicochemical and biological parameters were determined using standard analytical procedures for water analysis. The mean values of electrical conductivity and pH ranged from 273.63 to 881.27 μS/cm and 6.68 to 7.42, respectively. Moreover, the experimental results of major cations (Na+ = 3.70–14.77 mg/L and Ca2+ = 8.50–15.77 mg/L), and anions (HCO3− = 21.52–40.77 mg/L, Cl− = 13.56–40.29 mg/L, NO3− = 0.14–0.25 mg/L, NO2− = 0.24–0.76 mg/L and PO43− = 0.34–1.32 mg/L) were recorded below the World Health Organization (WHO) permissible limits set for drinking water. The water quality index (WQI) that is determined using a weighted arithmetic water quality index method (WAWQIM) was also found in the range of 5.3–37.2. Subsequently, all groundwater sources except Adibakla are classified as excellent or “A” rating. However, the total coliform of Maylomin and Chiny water sources were found to be 6.33 MPN/100 mL and 3.67 MPN/100 mL, respectively. Both are higher than the WHO permissible limit set for drinking water. Considering the susceptibility of groundwater to pollution and its impact to human health, regular monitoring and supervision should be performed to keep the water safe for drinking. Accordingly, chlorination water treatment process is recommended to provide safe drinking water.

Assessment of groundwater vulnerability using GOD index and Dar Zarrouk parameters: A case study of OAUSTECH main campus, Okitipupa, Ondo State

Groundwater is essential for efficient management of groundwater to prevent the deterioration of its quality. The objective of this study is to evaluate the vulnerability of the primary campus of (Olusegun Agagu University of Science and Technology) OAUSTECH in Okitipupa, Ondo State, Nigeria. This was done by analysing the GOD index and the Dar Zarrouk parameters of conductance and transverse resistance. A total of 24 Vertical Electrical Sounding (VES) data points were gathered, with AB/2 values varying from 200 to 225. These data points were then analysed utilising partial curve matching and computer iteration techniques to determine geoelectric characteristics, including resistivity and thickness. The computed characteristics, longitudinal conductance and transverse resistance, suggest that the aquifer's ability to defend against contamination in the research area is generally insufficient. The longitudinal conductance values range from 0.02 to 0.6, with most values below 0.1. Using the GOD method, the study shows that the GOD index value varies from 0.2 to 0.6, with an average of 0.325, suggesting a moderate to high level of vulnerability in the groundwater. The association between the GOD index and longitudinal conductance results in a 60 % accuracy in predicting groundwater susceptibility. This research emphasises that the groundwater within the main campus of OAUSTECH is moderately to highly vulnerable.

Utilizing Geological and Geoelectrical methods in a GIS-based DRASTIC model of the Probable Groundwater Vulnerability in the Southern Nigerian Raffia Metropolis of Ikot Ekpene and its Surroundings

The city of Ikot Ekpene is facing a significant issue with groundwater contamination. This is due to the rising amount of home and industrial waste caused by the increasing human population and various business operations in the area. This study seeks to evaluate the susceptibility of groundwater in the metropolis of Ikot Ekpene and its surrounding areas in southern Nigeria. It will utilize integrated geoelectrical and geological approaches within the GIS-based DRASTIC model. A total of twenty vertical electrical soundings (VES) were conducted in the region using the Schlumberger array. Based on the geological drilling data, the interpretation of the VES data suggests that the area consists of 3-4 geoelectric layers. The lithological succession in the area exhibits a range of sediment types, including fine and coarse sand as well as gravelly sands. Additionally, there are localized occurrences of clay intercalations. The third geoelectric layer, located at a depth of 9.0–86.6 m, is the primary aquifer that can be utilized in the region. The DRASTIC model included seven environmental parameters, including depth to the water table, net recharge, aquifer medium, topography, impact of vadose zone, and hydraulic conductivity, with the purpose of conducting a vulnerability assessment. The assessment of groundwater vulnerability ratings (GVR) reveals that 75% of the research region is classified as high vulnerability, 20% as moderate vulnerability, and the remaining 5% as low vulnerability. The studied area is predominantly characterized by moderate to high Groundwater Vulnerability Rating (GVR), which is likely attributed to the generally gentle topography and the presence of highly permeable geomaterials in the upper levels of the water table.

Graphical, statistical and index-based techniques integrated for identifying the hydrochemical fingerprints and groundwater quality of In Salah, Algerian Sahara.

Groundwater, a predominant reservoir of freshwater, plays a critical role in providing a sustainable potable water and water for agricultural and industry uses in the In Salah desert region of Algeria. This research collected 82 underground water samples from Albian aquifers to assess water quality and identify hydrogeochemical processes influencing mineralization. To achieve this objective, various methods were employed to evaluate water quality based on its intended uses. The drinking water quality index utilized revealed the water potability status, while the indicators of irrigation potability were employed to evaluate its quality for agricultural purposes. Additionally, an assessment of groundwater susceptibility to corrosion and scaling in an industrial context was conducted using several indices, e.g., Langelier index, Larson-Skold index, Ryznar index, chloride-sulfate mass ratio, Puckorius index, aggressiveness index, and the Revelle index. The findings of this study revealed thatthe groundwater quality for consumption fell into four categories: good (2.44%), fair (29.27%), poor (65.85%), and non-potable (2.44%). Concerning agricultural irrigation, the indexical results indicated that 15.85% of the waters exhibited adequate quality, while 84.15% were questionable for irrigation. Calculations based on various corrosion and scaling evaluation indices showed that most wells were prone to corrosion, with a tendency for calcium bicarbonate deposit formation. Furthermore, the hydrochemical study identified three water types: Na-Cl (53.66%), Ca-Mg-Cl (37.80%), and Ca-Cl (8.54%) waters. Analyses of correlation matrices, R-type clustering, factor loadings, Gibbs diagrams, scatterplots, and chloro-alkaline indices highlighted that the chemistry of the Albian groundwater is fundamentally impacted by a number of processes such as silicate weathering, evaporite dissolution, ionic exchange, and anthropogenic inputs, that played impactful role in the aquifer's water chemistry.

GROUNDWATER VULNERABILITY MAP OF BASARA BASIN, SULAIMANI GOVERNORATE, IRAQI KURDISTAN REGION

The Basara basin which is one of the most promising hydrogeological basin in Iraqi Kurdistan Region, located in north east of Iraq, 25 km west of Sulaimani city, between the 496652 - 537752 East and 3911038 - 3951906 North in Universal Transverse Mercator (UTM) and lie in Zone 38N. The basin has a rectangular shape and covering an area of 571 km². The present hydrogeological investigations have revealed three inhomogeneous and anisotropic water bearing formations: Eocene Karstic Fissured Aquifer (EKFA), Intergranular Aquifer represented by Alluvium and Pliocene (AIA) &amp; (PIA), as well as Miocene Complex Aquifer (MCA).For the first time, not only in Kurdistan but also in Iraq, Groundwater Vulnerability Map has been constructed in this study, using DRASTIC method with the assistance of Geographic Information System (GIS) to show zonation area of high and low groundwater susceptibility to pollution. Accordingly, vulnerability classes of the study area were classified into four classes. Most of the basin shows the highest extension of the zones with very low and low vulnerability zones, in contrast the zones with high vulnerability are distributed mainly in the mountain areas, solely in the eastern Uloblagh and Kuwaik mountains, in addition to that small zones in the farthest northern corner and south western corner of the area have less or no human activity.

Spatial evaluation of groundwater vulnerability using the DRASTIC-L model with the analytic hierarchy process (AHP) and GIS approaches in Edo State, Nigeria

The drinking of contaminated water is potentially hazardous to the well-being of humanity. Effective groundwater management depends on detecting groundwater contamination before it hits a critical point. The DRASTIC framework, modified globally to include land use (L), is utilized to evaluate groundwater vulnerability in various regions. In this study, an assessment of groundwater's susceptibility to contamination and a water quality index map to determine its fitness for Edo State have been done using the DRASTIC, DRASTIC-AHP, and DRASTIC-L-AHP models. The distinction of potential-risk water zones in Edo State, Nigeria, was made possible by the GIS that was used to create and combine several attribute maps. Results established that in the study area, very low (1,741.683 km2; 45%), low (1,741.683 km2; 10%), moderate (3,483.366 km2; 20%), and high (4,354.2075 km2; 25%) risk zones of groundwater contamination were identified on the overall DRASTIC-L-AHP map. The study found a significant pollution risk in one-fourth of the area, primarily in the Edo north and south regions of the study area. The significance of each factor for groundwater susceptibility and contamination risk was evaluated through a sensitivity analysis (SA). The SA indicated that the impact of the vadose zone is the most efficient variable in the DRASTIC-L-AHP model, with an effective weight value of 33.45% that is much larger than the theoretical value of 21.51%. The DRASTIC-L-AHP model, validated through hydrochemical analysis, is the least inaccurate and suitable for the current study area, serving as a useful pre-decisional tool for managing and preserving groundwater.

A Critical Review of Climate Change Impacts on Groundwater Resources: A Focus on the Current Status, Future Possibilities, and Role of Simulation Models

The Earth’s water resources, totalling 1.386 billion cubic kilometres, predominantly consist of saltwater in oceans. Groundwater plays a pivotal role, with 99% of usable freshwater supporting 1.5–3 billion people as a drinking water source and 60–70% for irrigation. Climate change, with temperature increases and altered precipitation patterns, directly impacts groundwater systems, affecting recharge, discharge, and temperature. Hydrological models are crucial for assessing climate change effects on groundwater, aiding in management decisions. Advanced hydrological models, incorporating data assimilation and improved process representation, contribute to understanding complex systems. Recent studies employ numerical models to assess climate change impacts on groundwater recharge that could help in the management of groundwater. Groundwater vulnerability assessments vary with the spatial and temporal considerations, as well as assumptions in modelling groundwater susceptibility. This review assesses the vulnerability of groundwater to climate change and stresses the importance of accurate assessments for sustainable water resource management. It highlights challenges in assumptions related to soil and aquifer properties, multiple stressors, adaptive capacity, topography and groundwater contamination processes, gradual sea level rise scenarios, and realistic representations of the region of study. With the advancements in hydrological modelling, including the integration of uncertainty quantification and remote sensing data, artificial intelligence could assist in the efforts to improve models for assessing the impacts of climate change on hydrological modelling.

Groundwater quality index development using the ANN model of Delhi Metropolitan City, India.

Groundwater is widely recognized as a vital source of fresh drinking water worldwide. However, the rapid, unregulated population growth and increased industrialization, coupled with a rise in human activities, have significantly harmed the quality of groundwater. Changes in the local topography and drainage systems in an area have negative impacts on both the quality and quantity of groundwater. This underscores the critical need to assess the susceptibility of groundwater to pollution and implement measures to mitigate these risks. The water quality index (WQI) is an approach that simulates the water quality at peculiar locations for a particular period of time. The artificial neural network (ANN) model approach is such an idealistic methodology that can be utilized for WQI development and provides better results for specific locations in optimum time. Therefore, the goal of the current study is to provide a unique way for using artificial neural networks (ANN) to characterize the groundwater quality of Delhi Metropolitan City, India. In order to make the water fit for residential and drinking use, the research also pinpoints the geographical variability and spots where the contaminated region has to be sufficiently cleaned. A minimum WQI of 41.51 was obtained at the Jagatpur location while a maximum value of 779.01 was at the Peeragarhi location. During the training phase, the results obtained using the ANN model were highly favorable, demonstrating a strong association with an R-value of 98.10%, thus highlighting the program's exceptional efficiency. However, in accordance with the correlation regression findings, the prediction outcomes of the ANN model in testing are observed to be an R-value of 99.99-100%. This study confirms the promise and advantages of employing advanced artificial intelligence in managing groundwater quality in the studied area.

Multi-isotopic and hydrochemical evidence of water resources evolution and recharge estimation in the tropical coastal aquifer

The study integrates hydrochemical and isotopic (δ18O, δ2H, 3H, and δ13C) techniques to investigate water evolution in the North Kelantan River basin. Groundwater facies were mainly classified as Ca–Mg–Cl, Ca–Mg–Cl–HCO3, and Na–Cl during the rainy season and shift toward Ca–Mg–HCO3 and Na–Ca–HCO3–Cl during the dry season in surface water and shallow aquifer, while facies in intermediate and deep aquifers were classified as Na–HCO3 and Na–Cl. The δ18O and δ2H compositions of most groundwater samples have not deviated significantly from NKMWL (δ2H = 8.4 δ18O + 11.5) with slightly depleted isotopic values due to the humid climate. Isotopically, evaporation does not impact recharged water significantly. However, shallow aquifers are slightly enriched than deep aquifers of the study area. The estimated recharge was 20.17% and 22.52% of annual rainfall based on the CMB and δ18O values, respectively. The recharge mainly occurs during the wet season and is influenced mostly by the amount of rain. Aquifers clustered in distinct groups based on their isotopic signatures and hydrochemical results. The decomposition of organic matter is the primary carbon source in the study area. Building on this, by utilizing isotope hydrology to study water resources, we can gain a deeper insight into the susceptibility of groundwater in coastal aquifers of monsoonal tropical humid regions.

Groundwater vulnerability assessment in central Iran: Integration of GIS-based DRASTIC model and a machine learning approach

The study try to evaluate the susceptibility of groundwater. The DRASTIC model was implemented through GIS. Various input variables, such as water table depth, net recharge, aquifer and soil media, topography, vadose zone impact, and hydraulic conductivity, were evaluated within the model to generate a groundwater vulnerability map. Subsequently, machine-learning algorithms (SVM, RF, and GLM) employed using the SDM package in R software to optimize the DRASTIC method. To assess the performance of groundwater pollution risk models, training and validation datasets were evaluated using the ROC curve. The results revealed that approximately 40% of the study area fell within the high vulnerability range, while around 30% exhibited moderate pollution risk. Evaluation of the machine learning models indicated their effectiveness in model development. The RF model demonstrated the highest predictive power, achieving an AUC of 0.98. Additionally, the GLM and SVM algorithms achieved AUC values of approximately 76%. These algorithms can serve as efficient techniques for evaluating and managing groundwater resources. The findings underscored relatively poor groundwater quality in the study area, with excessive aquifer exploitation by the agricultural sector and infiltration of urban sewage and industrial waste identified as the primary causes of groundwater pollution. The implications of these findings are crucial for devising strategies and implementing preventive measures to mitigate water resource vulnerability and associated health risks in central Iran.

DRASTIC model developed with lineament density to map groundwater susceptibility: a case study in part of Coimbatore district, Tamilnadu, India

DRASTIC model developed with lineament density to map groundwater susceptibility: a case study in part of Coimbatore district, Tamilnadu, India

Z-numbers based novel method for assessing groundwater specific vulnerability

Groundwater vulnerability assessment systems are developed to achieve a suitable method for protecting groundwater resources from contaminants. One of the well-known approaches for determining groundwater susceptibility is the DRASTIC method. This method considers seven effective parameters to evaluate groundwater vulnerability. Since groundwater contamination is often associated with uncertainty, this study applied the concept of the Z-number as a new generation of Fuzzy Logic (FL) to estimate the specific vulnerability of the aquifers. Unlike conventional FL models, which do not incorporate reliability, the Z-numbers include information constraint and reliability and can effectively explain uncertainty in human knowledge. To highlight this approach, the DRASTIC parameters (inputs) and nitrate concentration values (output) were used through two scenarios to estimate the specific vulnerability of the Ardabil and the Qorveh-Dehgolan plains (QDP) and the obtained results were compared with DRASTIC model as a benchmark model. The analysis of the results showed that the Z-number Based Modeling (ZBM), in addition to superiority to DRASTIC model, improved the quality of results compared to the classic FL by 53% (using seven inputs), 184% (using four inputs) in the Ardabil plain, and 127% (using seven inputs), 311% (using four inputs) in the QDP due to the consideration of data reliability and appropriate weighting of the rules. Also, the quality of the extracted Z-number-based rules in plains with high CV may be lower (such as the high CV of the Ardabil compared to the QDP). Therefore, the results of ZBM may not show a significant improvement over the conventional FL.

Groundwater susceptibility assessment using the GIS based DRASTIC-LU model in the Noyyal river area of South India

Various human activities have the potential to contaminate groundwater. The characteristics of an aquifer, as well as those of the rocks and soils above it, as well as its thickness in the unsaturated zone and any pollutants, all affect how vulnerable it is. The water contains natural antibiotic minerals. Water from the entire Orathuppalayam Dam overflows into the villages of Tirupur District every time it rains, contaminating them. The aquifer's susceptibility is intended by hydrogeological physiognomies and the DRASTIC LU index, anarithmetical notch that enhances up all of the important hydrogeological influences that affect groundwater movement laterally vertical outlines at a specific site. According to DRASTIC-LU research, the high and very high are additional exposed to susceptible for groundwater contamination, accounting for 11.90% (176.35 km2) and 25.40% (376.19 km2) of the total study area, respectively. During the Sensitive analysis, high vulnerability zones include 155, 110, 134, 141, 129, 127, and 141 in the categories of D, R, A, S, T, I, C, and LU layers. Sensitivity analysis reveals that the following percentages differ from the DRASTIC-LU vulnerability model: 55, 68, 71, 65, 78, 67, 79, and 85%. Kunnathur, Ingur, and Mudalipalaiyam are the zones fall under very low vulnerability and Arachalur, Kolappalur, Nasiyanur and Kanjikoil are the zones fall under the very high vulnerability zones in this study area.

Groundwater Vulnerability Assessment Phenomenon using DRASTIC &amp; Modified DRASTIC Modeling validated with Nitrate Concentration.

&lt;p&gt;Urbanized areas groundwater vulnerability and contamination are serious issues that require due attention. There are other models, notably the DRASTIC models employed to assess the vulnerability of groundwater. In a modified version of the DRASTIC model known as anthropogenic influence was incorporated into DRASTICA as a model parameter. The research used a cutting-edge methodology to define the anthropogenic employing satellite data of nighttime lighting to have an impact using human settlements as a stand-in and the Palani Taluk's surrounding land use/landcover. The spatial integration of various parameter maps was done using a geographic information system. According to data on groundwater vulnerability to pollution, around 29.98% of the area is in a very high vulnerability zone, followed by 23.68% of area covers high vulnerability, 25.18% comes under the range of moderate vulnerability, 12.14% covers the area in the zones of low vulnerability, and 8.97% area covers the total area in the ranges of very low vulnerability. Utilizing the amount of nitrate in ground water, the findings were confirmed. It was determined that in an urban environment, the suggested DRASTICA model achieved enhanced than the conservative DRASTIC model. The classifications are as follows: extremely high, high, medium, and low. Very high Vulnerability zones account for 214 values in Palani taluk, the research region, whereas very low vulnerability zones account for 3 values in Palani taluk. Urbanization index showed that anthropogenic impact and the depth of the water table had a substantial impact on groundwater susceptibility to contamination, indicating that manmade effect must be carefully taken into consideration in such studies. This study's modified-DRASTIC/DRASTICA model will aid in better classifying groundwater sensitive areas to contamination where manmade pollution is high, especially in and near metropolitan centers. The groundwater susceptibility possible map that is produced can be more successfully used as the main tool for managing, organizing, and safeguarding groundwater resources. Low nitrate concentrations are found in forests and arid terrain, whereas high nitrate values are found in urban areas. The majority of the Palani taluk has low to moderate nitrate concentrations. The Melkaraipatty and Thalaiyuthu Palani Taluk's urban areas are considered by high sensitivity because of low water levels and strong manmade effect.&lt;/p&gt;&#x0D;

AHP GIS-supported overlay/index models in Okeigbo, southwestern Nigeria, for groundwater susceptibility zonation

This study assessed the level of groundwater vulnerability and zonation in Okeigbo, southwestern Nigeria, using AVI, GOD, DRASTIC, and DRASTIC-LU models. The GOD categorized the area into three vulnerability zones, with predominant very low/low vulnerability zone constituting 96%; which is in contrast to two vulnerability zones of extremely high (55%) and high (45%) vulnerability zones delineated by the AVI. The DRASTIC map distinctly distinguished the area into four zones: high vulnerability zones (9%); the low vulnerable zone (6%); moderate (71%) of the study area; while moderately low susceptibility (14%). Similarly, DRASTIC-LU/LC model categorized as, moderately low, moderate, moderately high, and high vulnerability zones with aerial extent of 12%, 68%, 13%, and 7% respectively. Therefore, there is good correlation between the DRASTIC, DRASTIC-LU and AVI models as they all showed predominant moderate vulnerability zone. The nitrate concentration validated the high vulnerability zones of AVI, DRASTIC, and DRASTIC-LU models.

Groundwater quality assessment and its vulnerability to pollution: a study of district Nowshera, Khyber Pakhtunkhwa, Pakistan.

Groundwater is the drinking water source for the majority of rural settlements of district Nowshera, Khyber Pakhtunkhwa, Pakistan. The study aimed to analyze the groundwater quality and its vulnerability to pollution and to develop its spatial distribution mapping. For this purpose, forty-eight groundwater samples were collected from dug wells, tube wells, and hand pumps of sixteen villages andanalyzed for physicochemical parameters. The XY coordinates of the sample's sourcesweremarked by Magellan Triton 1500 handheld global positioning system (GPS). The results were compared with WHO and Pak-EPAguidelines. The results of the majority of selected parameters were found within the WHO and Pak-EPA guidelines; however, in certain areas the concentration of total dissolved solids (TDS), chlorides(Cl-), and alkalinity were higher than the guideline limits. Based on cumulative water quality the excellent water quality prevails over an area of 376 km2(21% of district area), good water quality 726 km2(42%), poor 424 km2(24%), very poor 116 km2(6%), and unfit for drinking 84 km2(4%). The water of the Nizampur and Rashaki areas were categorized unfit for drinking. The groundwater quality of nearly one-half of the district varies from poor to very poor, and the soil type and vadose zone sediment/material was found the key reason for groundwater contamination. Based on the infiltration capacity of vadose zone material, the study area was divided into four water pollution vulnerable zones. The low vulnerable zone covers an area of 104 km2, moderate 862 km2, high 667 km2,and very high 93 km2. The most important factor which determines the vulnerability of the groundwater to contamination is the vadose zone material/sediment which in turn determines the soil infiltration capacity. The generated groundwater susceptibility and water quality maps provide critical information for identifying optimal locations for supply wells.

Mapping the groundwater memory across Ireland: A step towards a groundwater drought susceptibility assessment

The occurrence of groundwater drought is closely linked to the meteorological input but also to the surface and subsurface properties, which function as lagging filter for the input signal.Knowledge about the potential occurrence of groundwater droughts is relevant for existing and future groundwater users, particularly in regions where climate change is expected to extend or increase the number of dry periods. This study proposes a method to quantify the groundwater memory as basis for characterising the intrinsic susceptibility of groundwater to drought.The memory of groundwater was estimated using a sliding window autocorrelation function applied on 114 groundwater level time series. A Random Forest regressor then modelled the groundwater memory across Ireland, using national digital maps as input files.The key variables explaining groundwater memory are: the relative and absolute surface topography and a thick overburden (>10 m). Accordingly, the lowest memory appears in elevated areas with overburden thicknesses of <10 m, and vice versa. Areas of low, moderate and high groundwater memory relate to high, moderate and low groundwater drought susceptibility. The uncertainty of the results is lowest in areas of low memory and highest in areas of high memory, presumably related to the distribution of the observations.The results are considered relevant in the context of water resources planning across sectors (agriculture, industry, domestic), particularly in the context of climate change adaptation.

WITHDRAWN: Mapping the groundwater memory across Ireland: a step towards a groundwater drought susceptibility assessment

• National assessment of the memory of groundwater across the Republic of Ireland. • The machine learning model is able to simulate the observed memory. • The study provides a first known high resolution map of the groundwater memory. • Groundwater memory informs on the susceptibility of groundwater to drought. • Lowest drought susceptibility appears in low-elevated areas with thick overburden, and vice versa. The occurrence of groundwater drought is closely linked to the meteorological input but also to the surface and subsurface properties, which function as lagging filter for the input signal. Knowledge about the potential occurrence of groundwater droughts is relevant for existing and future groundwater users, particularly in regions where climate change is expected to extend or increase the number of dry periods. This study proposes a method to quantify the groundwater memory as basis for characterising the intrinsic susceptibility of groundwater to drought. The memory of groundwater was estimated using a sliding window autocorrelation function applied on 114 groundwater level time series. A Random Forest regressor then modelled the groundwater memory across Ireland, using national digital maps as input files. The key variables explaining groundwater memory are: the relative and absolute surface topography and a thick overburden (>10 metres). Accordingly, the lowest memory appears in elevated areas with overburden thicknesses of less than 10 m, and vice versa. Areas of low, moderate and high groundwater memory relate to high, moderate and low groundwater drought susceptibility. The uncertainty of the results is lowest in areas of low memory and highest in areas of high memory, presumably related to the distribution of the observations. The results are considered relevant in the context of water resources planning across sectors (agriculture, industry, domestic), particularly in the context of climate change adaptation.

Influence of pyrolysis temperature on rice straw biochar properties and corresponding effects on dynamic changes in bispyribac-sodium adsorption and leaching behavior in soil

Bispyribac-sodium is a weakly acidic herbicide with high water solubility and is thus a potential source of groundwater contamination. Considering the risk inherent to the use of this herbicide, this study assessed the impacts of rice straw (RS) and biochar amendments on the adsorption and leaching behavior of bispyribac-sodium in soil. Biochars were produced from RS at different pyrolysis temperatures and characterized using various spectral techniques. Rice straw had a surface area of 3.996 × 104 m2 kg–1, which increased under pyrolysis; biochars prepared at 350 and 550 °C (RS350 and RS550) in a closed furnace with limited oxygen supply had a surface area of 5.763 × 104 and 6.890 × 104 m2 kg–1, respectively, and biochar prepared by purging the pyroformer with N2 (RSC) had the highest surface area of 12.173 × 104 m2 kg–1. After amendment with RS and biochar, soil Freundlich adsorption capacity (KFads) increased to varying extents in the order RSC > RS350 > RS550, from 2.89 × 103 to 29.57 × 103 mg1–1/n kg–1 L1/n, compared to 1.55 × 103 mg1–1/n kg–1 L1/n in unamended soil. The variability in KFads of bispyribac-sodium amongst the RS- and biochar-amended soils was dependent on the surface area of the amendments. The desorption of bispyribac-sodium decreased in the RS- and biochar-amended soils and varied from 90.45% to 95.20% in unamended soils and from 60.95% to 89.50% in amended soils. The adsorption and desorption of bispyribac-sodium varied significantly depending on its concentration and the type and application rate of soil amendment. Different leaching risk evaluation indices, viz., modified leach index (M.LEACH), leach index (LEACH), groundwater ubiquity score (GUS), Hornsby index (HI), leaching index (LIN), and pesticide leaching potential (PLP) index, were used to assess the susceptibility of groundwater to herbicide leaching. To reduce the repetitive effects of common parameters in each index, a new index was developed by employing principal component analysis (PCA) to condense their information into a single ranking. The results of the PCA indicated that RS and biochar amendments could be an effective management practice for controlling the leaching potential of bispyribac-sodium in soil.