Suitability Of Groundwater For Irrigation Research Articles

Multivariate Statistical Analysis and Geospatial Mapping for Assessing Irrigation Water Quality in the Aquifers of the South-Atlas Tinghir-Errachidia-Boudenib basin (Pre-African Trough, Morocco)

This study investigates the hydrogeochemical characteristics of the South-Atlas Tinghir-Errachidia-Boudenib trough situated in the arid southeastern region of Morocco. The primary objective is to assess the quality of groundwater intended for both drinking and irrigation purposes. Advanced multivariate statistical techniques such as Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) will be utilized to decipher the hydrogeochemical processes influencing groundwater mineralization. Furthermore, the research will determine the suitability of groundwater for irrigation using various indices, including Sodium Adsorption Ratio (SAR), Percent Sodium (Na%), Permeability Index (PI), and the Piper trilinear diagram.During February 2023, a systematic collection of fifty groundwater samples took place, spanning different aquifers such as those from the Senonian, Infracenomanian, Quaternary, and Paleozoic formations. These samples were subjected to thorough analysis to evaluate their quality, typology, origin, and irrigation suitability.The study's findings reveal that the majority of groundwater constituents in the South- Atlas Tinghir-Errachidia-Boudenib trough exceed the World Health Organization's (WHO) drinking water standards. The Piper diagram shows three major types of hydrogeochemical facies detected in different aquifers of the study area. The majority of the samples belonged to Ca-Mg-Cl-SO4 followed by Na-K-Cl-SO4 and Ca-Mg-HCO3. Three unique processes governing groundwater hydrochemistry were identified using multivariate techniques: The first group (which matches PC1), which consists of [EC, Na+, Cl-, TDS, TH, Mg2+, SO42-, and Ca2+], represents the mineralization axis found in the southern portion of the research area's Infracenomanian aquifer (between Aoufous and Erfoud) and the Goulmima region in the south. Al, K+, and pH are found in the second group (matches PC2), which is situated in the southern portion of the research area on the Paleozoic aquifer. Some samples are also found on the Senonian aquifer in the eastern Boudnib region. The third group (PC3 matches) is made up of [HCO3- and Fe2+], and it is mostly found in the Senonian aquifer in the northeastern region of the study area (Boudenib and its surroundings). The Senonian samples demonstrated excellent SAR, Na%, and PI, values, whereas most groundwater samples from other aquifers showed good to permissible suitability for irrigation. Furthermore, the water-rock interactions and agricultural fertilizers were highlighted as key factors influencing groundwater compositions.

A Novel Integrated Approach to Assess Groundwater Appropriateness for Agricultural Uses in the Eastern Coastal Region of India

Due to the increase in demand for water, the rapid growth of urbanization and industrialization is the main threat to the source and quality of groundwater. The present study aimed to assess the suitability of groundwater for agricultural purposes in coastal regions using integrated approaches such as the saltwater mixing index (SWMI), the mineral saturation index (MSI), the agriculture suitability index (ASI), and unsupervised machine learning (USML) techniques. The result of the SWMI revealed that 20 and 17 sample locations were highly affected by saltwater intrusion in the study region’s northern and southeastern parts during the pre- and post-monsoon seasons. The detailed analysis of electrical conductivity in groundwater revealed that 19.64% and 14.29% of the samples were unfit for irrigation purposes, especially five sample locations, during both seasons. Regarding the overall suitability of groundwater for irrigation uses, the ASI values divulged that 8.9% of the samples were unsuitable for irrigation purposes. The spatial analysis of the ASI value indicated that 43.19 and 85.33 sq. km of area were unsuitable for irrigation practices. Additionally, the USML techniques identified the most influenced parameters such as Ca2+, Mg2+, Cl−, and SO42− during both seasons. The present study results help maintain proper, sustainable water management in the study region.

Groundwater suitability for irrigation and domestic use applying CCME WQI model and GIS in East El-Owainat, Egypt

Groundwater suitability for irrigation and domestic use applying CCME WQI model and GIS in East El-Owainat, Egypt

Comprehensive Analysis of Groundwater Suitability for Irrigation in Rural Hyderabad, Sindh, Pakistan

An irrigation quality assessment for rural Hyderabad was made by determining the pH, EC, TDS and TH beside major cations and anions. This study employed various parameters to determine the suitability of groundwater for irrigation and its hydrochemistry. Permissible limits of major cations and anions revealed that approximately 26% of samples exceeded acceptable levels for Electrical Conductivity (EC), 87% for Ca2+, 89% for Mg2+, and 60% for Na+, while none exceeded the limits for K+. Conversely, 47% of samples for HCO3−, 91% for Cl−, and 100% for SO42−, NO3−, and CO32− proved suitability for irrigation. Notably, irrigation indices highlighted favorable results, with 100% conformity for SAR, SSP, RSP, and PI values, and substantial percentages of 78% and 85% for MH and KR values, respectively, affirming their suitability for irrigation practices. Employing the USSL diagram, 22%, 65%, and 11% of samples fall into the C2S1, C3S1, and C4S1 categories. According to the Wilcox diagram, 25%, 43%, 30%, and 2% are classified under C1, C2, C3, and C4 categories, respectively. The Gibbs ratio shows a concentration within the evaporation dominance, and CAI values showed positive ion exchange. Overall, Hyderabad’s rural areas are generally suitable for irrigation, apart from certain areas where water quality may not be acceptable for plants lacking high salt tolerance.

Groundwater assessment for sustainable development in the Wadi Al-Hamd Basin, Al-Madinah Al-Munawarah, KSA

This study relied on well monitoring many drilled wells data in the Wadi Al-Hamd Basin to determine water level and chemical properties from field measurements. The characteristics of groundwater must be assessed in terms of present and future eases and stresses to ensure sustainable development. Hydrogeological, hydrochemical, groundwater quality indices and Geographic Information Systems (GIS) data sets have been integrated to assess the groundwater aquifer in the study area. To implement this work, we measured the depth to the water table from eighty-eight drilled wells. Also, the major ions were determined from 82 water samples to evaluate the physicochemical properties, groundwater facies, and controlling mechanisms using diagrams such as the modified Piper proposed by Chadha, Total Ionic Salinity (TIS), and Gibbs. In this study, five irrigation water quality indicators (IWQI), including total dissolved solids (TDS), sodium adsorption ratio (SAR), potential salinity (PS), magnesium hazard (MH), and residual sodium carbonate (RSC) have been determined to assess the suitability of groundwater for irrigation. Based on the findings of this study, groundwater flows from the southeast and northwest to the west and south, respectively. In this basin, 56% of water samples have TDS greater than 2000 mg/L, while 62% of water points are categorised as Na–Cl water type, which indicates that evaporation and rock–groundwater interaction influenced groundwater quality evolution. Almost 87% of samples were rated good to excellent for irrigation use with respect to SAR. On the other hand, all water points are suitable for irrigation based on RSC. Likewise, groundwater is suitable for irrigation purposes despite the relatively high PS levels (>5 meq/L in about 49% of samples) and some small spots with high levels of MH (>50% in about 12% of samples), especially in the southern and central portions of the studied basin.

Hydrogeochemical investigation of irrigation water in the vicinity of metallic ore deposits in Kiraz‐İzmir, Turkey: Understanding the crucial nexus between “geology and food safety”

AbstractThe increasing drought due to climate change poses a threat to issues such as safe and accessible drinking water, food safety, and protection from diseases. The provision of water supply is vital for agricultural and livestock activities, which are commonly practiced around natural ore deposits. Examining traditional “irrigation water quality” methods alone is insufficient; investigating potentially toxic metal content in the region's waters is vital, especially around metallic ore deposits. This study focused on the Kiraz district in Turkey, known for its agricultural activities, to assess the impact of geogenic water pollution on irrigation water quality and its implications for food safety and human health. Geology determines nutrient availability, water resources, and land suitability for agriculture. Conventional irrigation water quality parameters indicate groundwater suitability for irrigation in the study area, considering Na%, sodium adsorption ratio, residual sodium carbonate, permeability index, Kelly ratio, magnesium hazard, and potential salinity. However, when examining the potential toxic metal content in the region, it was determined that the values of Al ranged from 96 to 8676 ppb, Ni values ranged from 27 to 360 ppb, and Sb concentrations varied between 9 and 53 432 ppb. Utilizing geogenically contaminated water for irrigation and its indiscriminate use in livestock, dairy, and food industries can lead to foodborne illnesses (cancer, endocrine disruptors, tuberculosis, antimony spots, thyroid tumors, goiter, neurologic and cardiovascular diseases) that endanger human health. The use of low‐quality water throughout the agricultural sector and food production chain increases food safety risks.

Evaluating the suitability of groundwater for irrigation in parts of mid-Gangetic plains, Bihar

Irrigation water quality is critical for crop production. The present study focuses on assessment of suitability of groundwater for irrigation purposes in four blocks of Samastipur district, Bihar lying in the mid Gangetic plains. In this district most of the people are dependent upon agriculture.

Using groundwater quality index for categorizing the groundwater suitability for irrigation in the south Nile Delta region, Egypt

ABSTRACT Groundwater is considered one of the most important sources of water all over the world. It can be used for different purposes of life, depending on its quality. The quality can be categorized for irrigation based on many items such as sodium percentage, permeability index (PI), magnesium hazard (MH), Kelley ratio (KR), and water quality index (WQI). Those items can be expressed and presented in Geographic Information System (GIS) format. This study aims to compare the WQI with the other items for expressing the suitability of groundwater for irrigation in GIS format. This study is conducted in the south Nile Delta region, Egypt. Seventy-two groundwater samples are collected and analyzed for pH, EC, total dissolved solids, soluble cations and soluble anions, iron, and manganese. These parameters are used to calculate the WQI considering their permissible limits of FAO, while the other items were calculated using some parameters based on their equations. The results reveal that, due to sodium percentage, there are three orders from five orders, of which 53% are good, 39% are permissible, and 8% are doubtful. Considering PI, the results were 7% for class 1 and 93% for class 2. Regarding MH, the results ranged between 6% (not suitable for irrigation) and 94% (suitable for irrigation). Depending on KR, 82% of the samples are suitable for irrigation, while 18% are not suitable for irrigation. The results of WQI illustrate that 76.4% of the total studied samples are excellent for irrigation and 23.6 are good for irrigation. All the results are represented using ArcGIS 10.1 program to clear the spatial distribution of the groundwater suitability for irrigation. The use of WQI with GIS is considered the best tool to represent and categorize the suitability of groundwater for irrigation.

Hydrochemistry and Groundwater Quality Assessment for Drinking and Irrigation Purposes in Kakarveni River Basin, Vikarabad District, Telangana, India

Abstract: This study aims to assess the hydrochemistry and groundwater quality in the Kakarveni river basin in Vikarabad district, Telangana, India. Groundwater is a vital natural resource for human, agricultural, and ecological needs. Understanding hydrochemistry and groundwater quality is essential for identifying potential contaminants for selecting water treatment and agricultural management practices. The study will analyse hydro-chemical parameters such as pH, electrical conductivity, total dissolved solids, and major ions, and collect water samples from different locations to assess permeability index, Kelly’s index, magnesium hazard, sodium percentage, residual sodium carbonate, or Eaton's index. The research methodology involves field sampling and laboratory analysis to ensure accurate and reliable results. The study area is about 192 sq. km and includes agricultural fields, forests, and human settlements. The geology and hydrology of the area are crucial for sustainable development and effective water resource management. The study found significant variations in measured parameters between pre-monsoon and post-monsoon seasons, with slightly acidic pH levels and higher electrical conductivity and total dissolved solids during the post-monsoon season. The study analyses water samples during the pre-monsoon and postmonsoon periods and compares them with the WHO's drinking water quality standards. The study computes the findings and arrives at the suitability of groundwater for irrigation.

Groundwater Quality Assessment for Drinking and Irrigation Purposes at Al-Jouf Area in KSA Using Artificial Neural Network, GIS, and Multivariate Statistical Techniques

Groundwater is an essential resource for drinking and agricultural purposes in the Al-Jouf region, Saudi Arabia. The main objective of this study is to assess groundwater quality for drinking and irrigation purposes in the Al-Jouf region. Physicochemical characteristics of groundwater were determined, including total dissolved solids (TDS), pH, electric conductivity (EC), hardness, and various anions and cations. The groundwater quality index (WQI) was calculated to determine the suitability of groundwater for drinking purposes. The EC, sodium percentage (Na+ %), magnesium hazard (MH), sodium adsorption ratio (SAR), potential salinity (PS), and Kelley’s ratio (KR) were assessed to evaluate the suitability of groundwater for irrigation. Effective statistical tests and Feed-forward neural network (FFNN) modeling were applied to reveal the correlation between parameters and predict WQI. The results indicated that approximately all samples are appropriate for drinking and irrigation uses except samples of the Al Qaryat region. The ionic abundance ranking was Na+ > Ca2+ > Mg2+ > K+ for cations, and Cl− > SO42− > NO3− for anions. Moreover, the groundwater is dominated by alkali metals (K+ and Na+) and controlled by the rock–water interaction process. The indicators of groundwater quality for irrigation and drinking according to the following criteria (Na+ %, SAR, KR, MH, PS, WQI (WHO), and WQI (BIS)) can be predicted by the FFNN with root mean square errors (RMSE) of 0.136, 0.070, 0.022, 0.073, 2.45 × 10−3, 1.45 × 10−2, and 1.18 × 10−2, respectively, and R2 of 0.99, 1.00, 0.99, 0.99, 1.00, 1.00, and 1.00, respectively.

Diagnosis of Groundwater Quality in North Assiut Province, Egypt, for Drinking and Irrigation Uses by Applying Multivariate Statistics and Hydrochemical Methods

Globally, groundwater is a valuable natural resource that may be relied upon for irrigation and drinking needs. The main purpose of this study is to investigate the groundwater geochemistry in the West of El Qusiya, Assuit, Egypt. Groundwater suitability for irrigation has been estimated with some methods, for instance, electrical conductivity (EC), sodium adsorption ratio (SAR), residual sodium carbonate (RSC), Killey ratio (KR), magnesium hazard (MH), permeability index (PI), Piper trilinear diagram, and USSL diagram. The Piper diagram shows that the sodium and potassium (Na+K) kind dominates the water chemistry, followed by the mixed type. The principal coordinate analysis (PCoA), cluster analysis (CA), principal component analysis (PCA), and Pearson correlation matrix analysis (PCMA) statistical methods reveal that the physicochemical parameters of water collected from the Eocene and Pleistocene aquifers are produced from mixed origins. The geogenic origin reflects the lithologic impact of aquifers matrix and water interactions, in addition to anthropogenic sources caused by infiltration of secondary salts initiated due to fertilizers and agriculture water. These factors are the controller for groundwater’s ionic (Na+, Ca2+, Mg2+, K+, Cl−, SO42−, and HCO3−) variation in the area studied. Based on SAR, KR, and PI results, groundwater is acceptable for irrigation. Consistent with RSC, MH, and Na% results, approximately 50% of the groundwater samples are unsuitable for irrigation use.

Assessment and Characterization of Groundwater Quality of Malabar Coast in Kerala, India

A study was conducted to assess and characterize the groundwater quality of coastal aquifer of the Vatakara-Koyilandy stretch in the Kozhikode district of Kerala. Mann-Kendall Test was used for analysing the trend in groundwater levels. The Piper diagram was applied to determine the chemical facies of the groundwater and identify the evolution of hydrochemical parameters of groundwater sources. The source of the dissolved ions in the groundwater was described by the Gibbs diagram. The suitability of groundwater for irrigation was determined using the United States Salinity Laboratory diagram. Geostatistical tools were used to describe the spatial variability of groundwater levels and salinity and the ordinary kriging method was used to plot the spatial variability maps. It was found that Na+ was the predominant cation with maximum concentration varying from 455.6 mg/l to 1844 mg/l during pre-monsoon and post-monsoon; respectively. Concentration of Cl- in pre-monsoon and post-monsoon varied from 184 mg/l to 2417 mg/l and 99 mg/l to 714 mg/l; respectively. Other anions in the groundwater were SO42- and HCO3- with an average concentration of 239.79 mg/l and 129.59 mg/l in pre-monsoon and 110.73 mg/l and 75 mg/l in post-monsoon; respectively. The trend in groundwater in confined and semi-confined aquifers showed negative trends whereas eight wells resulted in a significantly negative trend. However, a significant decreasing trend was observed in wells near the coasts. The most dominant cations were (Na+, and K+) and the dominant anions were SO42- and Cl-. The dominant cations and anions were from the mixing of seawater with the groundwater. The Na+ ions were also found to be from the same source. In most of the area, the groundwater was highly to very high highly saline with medium sodium and not suitable for irrigation. In the unconfined aquifer, 25.2% and, in the semi-confined aquifer 24.0% area was found to be unfit for irrigation.

Assessing the Quality of Treated Wastewater for Irrigation: A Case Study of Ain Sefra Wastewater Treatment Plant

This study aimed to assess the water quality parameters in the wastewater treatment plant (WWTP) of Ain Sefra, southwestern Algeria. Various methods were employed to analyze the performance and suitability of the WWTP for irrigation. The results revealed effective removal of nitrates, with levels below the limit set for irrigation water. The dissolved oxygen content showed efficient biological processes and good degradation of organic matter. Phosphate levels were found to be within FAO and Algerian irrigation standards. However, elevated ammonia levels were observed, exceeding typical ranges for irrigation. The suitability of groundwater for irrigation was evaluated by calculating groundwater suitability indices. These indices categorized all samples as either excellent or good based on their Sodium Adsorption Ratio (SAR) and Kelly’s ratio. However, the sodium percentage values raised concerns about potential negative effects on the soil. Some samples were deemed unsuitable for irrigation because of high magnesium hazard and potential salinity values. These findings offer valuable insights into the performance and suitability of treated wastewater for irrigation in the Ain Sefra region. They can inform decision makers and stakeholders involved in agriculture and water management.

Evaluation of Groundwater Quality and Suitability for Irrigation Purposes and Human Consumption in Saudi Arabia

Studying groundwater quality is crucial for ensuring its safety because it is widely used for drinking and for domestic, agricultural, and industrial purposes. Owing to the lack of surface water in the Tabuk area of Saudi Arabia, here groundwater wells are one of the primary sources of water for drinking, agriculture, and industry. Groundwater quality is determined by the aquifer characteristics of the regional geology, and it is extensively influenced by both natural and anthropogenic activities. To understand the geochemical evolution and assess the suitability of groundwater for irrigation, major ion geochemistry was utilized to characterize the chemical composition of groundwater in the Tabuk area, which is considered a semiarid plateau region. Depending on its mineral composition, irrigation water’s quality reflects how it affects plants and soil. In total, 80 groundwater samples have been collected and analyzed in laboratory for major cations and anions. Temperature, alkalinity (ALK), pH, total dissolved solids (TDS), electric conductivity (EC), total hardness (TH), oxidation reduction potential (ORP), and cation and anion concentrations were measured. Water chemistry classification was carried out by using a Piper diagram and a Gibbs diagram. In the current study, statistical methods, combined with geochemical modeling and conventional plots, have been used to investigate groundwater and related geochemical processes in the Tabuk area of Saudi Arabia. Applications and calculations of hydrogeochemical parameters, specifically SAR, RSC, PI, CR, MH, Na%, KR, and HI, showed that 92.5% of the collected groundwater well samples are suitable for drinking and irrigation purposes after treatment processes.

Groundwater quality appraisal using IWQI and PCA for irrigation uses

ABSTRACT This study used data collected over 19 sites to assess groundwater quality status of Kurukshetra (Haryana state, India) for irrigation purposes. Irrigation Water Quality Index (IWQI), Wilcox diagram, and principal component analysis were considered to determine current water quality. ArcGIS was used for spatial distribution of irrigation parameters. Results suggest that out of total samples, 5.3% of groundwater samples fall under ‘High Restriction,’ 68.42% of groundwater samples under ‘Moderate Restriction,’ and 26.28% of groundwater samples under ‘Low Restriction.’ Results of Wilcox and USSL diagrams suggested the suitability of groundwater for irrigation. Wilcox diagram indicated that 78.9% of groundwater samples fall in the Excellent-to-Good region, whereas USSL diagram classified all groundwater samples in low-to-medium or from medium-to-high class range. The results of PCA approach demonstrated that first five principal components (PCs) consisting of nine input variable represent 79.23% of total variance in groundwater quality.

Unraveling the hydrogeochemical evolution and pollution sources of shallow aquifer using multivariate statistical analysis and hydrogeochemical techniques: a case study of the Quaternary aquifer in Beni Suef area, Egypt

This study integrates multivariate statistical analysis and hydrogeochemical modeling to investigate the processes controlling the groundwater composition of a shallow aquifer where increased pumping rates and anthropogenic impacts were prevalent. Eighteen groundwater samples were collected and analyzed for major elements and selected heavy metals. The data were classified on the basis of multivariate statistical analysis into three clusters: C1 (Na-Cl facies), C2 (Ca-SO4 facies), and C3 (Ca-HCO3 facies). The application of factor analysis gave four factors affecting the groundwater chemistry, namely the salinization factor, anthropogenic/secondary enrichment factor, the secondary and the micro-nutrient fertilizers, and the aluminum fertilizer factor. The hydrogeochemical study of the groundwater revealed that the processes controlling the groundwater chemistry in the study area are mainly affected by the groundwater occurrence either to the east or to the west of Bahr Youssef Canal. Generally, the dominant hydrogeochemical processes affecting the groundwater are silicate weathering, ion exchange, irrigation return flow, gypsum applications in soil, and evaporation. The groundwater quality evaluation shows that water quality varies from fair to excellent for drinking purposes, where the best water is located in the northern and central parts of the study area. The suitability of groundwater for irrigation was evaluated using several indices indicating that groundwater is suitable for irrigation in the northwest and western parts of the study area. As some groundwater samples lie in high salinity classes on the US Salinity diagram, it is recommended to use this water for plants with good salt tolerance under good drainage conditions. The integration between the statistical and geochemical tools helps reveal the dominant processes through data reduction and classification.

Prediction of Sodium Hazard of Irrigation Purpose using Artificial Neural Network Modelling

The present study was carried out using artificial neural network (ANN) model for predicting the sodium hazardness, i.e., sodium adsorption ratio (SAR), percent sodium (%Na) residual, Kelly’s ratio (KR), and residual sodium carbonate (RSC) in the groundwater of the Pratapgarh district of Southern Rajasthan, India. This study focuses on verifying the suitability of water for irrigational purpose, wherein more groundwater decline coupled with water quality problems compared to the other areas are observed. The southern part of the Rajasthan State is more populated as compared to the rest of the parts. The southern part of the Rajasthan is more populated as compared to the rest of the Rajasthan, which leads to the industrialization, urbanization, and evolutionary changes in the agricultural production in the southern region. Therefore, it is necessary to propose innovative methods for analyzing and predicting the water quality (WQ) for agricultural use. The study aims to develop an optimized artificial neural network (ANN) model to predict the sodium hazardness of groundwater for irrigation purposes. The ANN model was developed using ‘nntool’ in MATLAB software. The ANN model was trained and validated for ten years (2010–2020) of water quality data. An L-M 3-layer back propagation technique was adopted in ANN architecture to develop a reliable and accurate model for predicting the suitability of groundwater for irrigation. Furthermore, statistical performance indicators, such as RMSE, IA, R, and MBE, were used to check the consistency of ANN prediction results. The developed ANN model, i.e., ANN4 (3-12-1), ANN4 (4-15-1), ANN1 (4-5-1), and ANN4 (3-12-1), were found best suited for SAR, %Na, RSC, and KR water quality indicators for the Pratapgarh district. The performance analysis of the developed model (3-12-1) led to a correlation coefficient = 1, IA = 1, RMS = 0.14, and MBE = 0.0050. Hence, the proposed model provides a satisfactory match to the empirically generated datasets in the observed wells. This development of water quality modeling using an ANN model may help to useful for the planning of sustainable management and groundwater resources with crop suitability plans as per water quality.

Effects of Seawater Intrusion on the Groundwater Quality of Multi-Layered Aquifers in Eastern Saudi Arabia

The degradation of groundwater (GW) quality due to seawater intrusion (SWI) is a major water security issue in water-scarce regions. This study aims to delineate the impact of SWI on the GW quality of a multilayered aquifer system in the eastern coastal region of Saudi Arabia. The physical and chemical properties of the GW were determined via field investigations and laboratory analyses. Irrigation indices (electrical conductivity (EC), potential salinity (PS), sodium adsorption ratio (SAR), Na%, Kelly's ratio (KR), magnesium adsorption ratio (MAR), and permeability index (PI)) and a SWI index (fsea) were obtained to assess the suitability of GW for irrigation. K-mean clustering, correlation analysis, and principal component analysis (PCA) were used to determine the relationship between irrigation hazard indices and the degree of SWI. The tested GW samples were grouped into four clusters (C1, C2, C3, and C4), with average SWI degrees of 15%, 8%, 5%, and 2%, respectively. The results showed that the tested GW was unsuitable for irrigation due to salinity hazards. However, a noticeable increase in sodium and magnesium hazards was also observed. Moreover, increasing the degree of SWI (fsea) was associated with increasing salinity, sodium, and magnesium, with higher values observed in the GW samples in cluster C1, followed by clusters C2, C3, and C4. The correlation analysis and PCA results illustrated that the irrigation indices, including EC, PS, SAR, and MAR, were grouped with the SWI index (fsea), indicating the possibility of using them as primary irrigation indices to reflect the impact of SWI on GW quality in coastal regions. The results of this study will help guide decision-makers toward proper management practices for SWI mitigation and enhancing GW quality for irrigation.

Hydrogeo-Chemical Processess and Evaluation of Groundwater Quality for Drinking and Irrigation Purposes in Afzalpur Taluk, Karnataka, India.

To determine the geochemical processes impacting groundwater geochemistry and its appropriateness for drinking and irrigational uses, a thorough examination of groundwater is conducted in some areas of the Afzalpur taluk. According to the results of a thorough chemical analysis, the research area's groundwater has a pH average between 6.7 and 6.3, making it fairly acidic. Mg2+ and Ca2+ cations and HCO3- anions are also present in high amounts. Ion-exchange and rock weathering mechanisms were perceived to dominate the groundwater chemistry, with anthropogenic sources playing a minor role. Particularly, the electrical conductivity, total hardness (TH), and concentrations of Na+ and HCO3- exceeded the BIS and WHO water quality standards' acceptable limits. Groundwater suitability for irrigation was assessed on the basis of sodium adsorption ratio, Na%, magnesium hazard (MH), residual sodium carbonate (RSC), and Kelley's index (KI). Above parameters revealed that nearly 40 to 50 % of the groundwater in the sampling sites was of high-quality for irrigation purpose.

Estimation of groundwater quality using an integration of water quality index, artificial intelligence methods and GIS: Case study, Central Mediterranean Region of Turkey

Groundwater is one of the most important natural resources in the world and is widely used for irrigation purposes. Groundwater quality is affected by various natural heterogeneities and anthropogenic activities. Consequently, monitoring groundwater quality and assessing its suitability are crucial for sustainable agricultural irrigation. In this study, the suitability of groundwater for irrigation was determined by using sodium adsorption ratio (SAR), residual sodium carbonate (RSC), Kelly index (KI), percentage of sodium (Na%), magnesium ratio (MR), potential salinity (PS) and permeability index (PI). The groundwater samples were collected and analyzed from 37 different sampling stations for this purpose. Along with suitability analysis, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models were used to predict irrigation water quality parameters. The models were evaluated by comparing the measured values and the predicted values using the statistical criteria [coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE) and Nash–Sutcliffe efficiency (NS)]. In the estimation of all irrigation water quality parameters, the ANN model has performed much higher compared with the ANFIS model. Spatial distribution maps were generated for measured and ANN model-estimated irrigation water quality indices using the IDW interpolation method. Spatial distributions of groundwater quality indices revealed that MR was higher than the allowable limits in most of the study areas and the other quality criteria were within the permissible limits. It has been determined that the interpolation maps obtained as a result of artificial intelligence methods have appropriate sensitivity when compared with the observed maps. Based on the present findings, ANN models could be used as an efficient tool for estimating groundwater quality indices in unsampled sections of the study area and the other regions with similar conditions.