Decrease In Groundwater Level Research Articles

Adaptation climate change through application of green infrastructure household scale rainwater harvesting in tropical coastal areas based fuzzy logic

Freshwater problems in coastal areas include the process of salt intrusion which occurs due to decreasing groundwater levels below sea level which can cause an increase in salt levels in groundwater so that the water cannot be used for water purposes, human consumption and agricultural needs. The main objective of this research is to implementation of RWH to fulfill clean water needs in tropical coastal area in Tanah Merah Village, Indragiri Hilir Regency, with the aim of providing clean water to coastal communities. The approach method used based on fuzzy logic (FL). The model input data includes the effective area of the house’s roof, annual rainfall, roof runoff coefficient, and water consumption based on the number of families. The BWS III Sumatera provided the rainfall data for this research, which was collected from the Keritang rainfall monitoring station during 2015 and 2021. The research findings show that FL based on household scale RWH technology is used to supply clean water in tropical coastal areas that the largest rainwater contribution for the 144 m2 house type for the number of residents in a house of four people with a tank capacity of 29 m2 is 99.45%.

Assessing the role of stakeholders in sustainable groundwater resources management using power-interest matrix (PIM): in Hamedan-Bahar plain, Iran

IntroductionMoral Intelligence (MI) as a concept has gained importance Increasing water scarcity as a result of climate change and its coincidence with population growth, economic development, and the resulting rising demand has become an important challenge in most parts of the world. In numerous nations, such as Iran, frequent occurrences of droughts, combined with the extensive utilization of surface and groundwater resources, have resulted in numerous environmental detriments, including a decrease in groundwater levels, land subsidence, deterioration of water quality, and, more recently, the emergence of dust storms due to soil erosion and desertification. In this situation, stakeholders can play an efficient role in water management and the alleviation of water scarcity and its negative environmental externalities in the context of good water governance.MethodThis investigation endeavored to examine the functions and importance of individuals or groups with a vested interest in groundwater resources within the Hamedan-Bahar Plain. Additionally, it aimed to evaluate their influence and motivations through the utilization of the power-interest matrix (PIM) and important-performance matrix techniques. A total of 86 people were identified who could and were allowed to be interviewed through the snowball method. Then a 10-point scale questionnaire was used to rate the questions. To examine the power and interest of the stakeholders, the IPM test was carried out using the smart pls.3 software, and the results were classified based on the average values and the overall impact. The results reveal that 20 institutions and agencies have an effective role in the governance of groundwater resources in the Hamedan-Bahar plain. Furthermore, the analysis of the PIM revealed that the most powerful organizations that play the most important role in the management of the groundwater resources of the studied area are the regional water organization, the representatives of the parliament, and the governor, respectively.Results and discussionBased on the research findings, the governance “power” index of organizations and institutions with power (39.77%) and total impact (0.516) is higher and more effective than the value of benefits with power (36.13%) and total impact (0.48). Accordingly, paying attention to the role and influence of the power of stakeholders will be an important and effective point in the plans and strategies for groundwater resources in the Hamadan-Bahar plain. In the end, strategies are suggested to each stakeholder for better implementation of the programs and strategies.

Optimizing Irrigation Systems for Water Efficiency and Groundwater Sustainability in the Coastal Nile Delta

This study investigates the replacement of traditional surface irrigation methods with modern irrigation systems (MIS) including horizontal sprinkler, central pivot, surface drip, and subsurface drip aimed at improving water efficiency in the Nile Delta, Egypt. The primary objectives were to determine the optimal agricultural area for implementing MIS and to assess the effects of these systems on groundwater quantity and quality in the region. To achieve this, the LINDO software was employed to optimize land allocation for each irrigation method. At the same time, the SEAWAT code was utilized to simulate saltwater intrusion (SWI) in the Nile Delta aquifer. The transition from traditional surface irrigation to MIS resulted in significant water savings, reaching 2.15 × 10^9 m³. However, groundwater modeling indicated a decrease in groundwater levels, leading to an 8 % increase in aquifer salinity due to reduced infiltration of recharge water. These findings underscore the urgent need to revise outdated irrigation practices and enhance water management strategies in the Nile Delta to mitigate salinity issues in coastal aquifers. This research's outcomes are crucial for decision-makers and stakeholders in selecting appropriate irrigation methods, particularly in arid and semi-arid regions, to ensure sustainable water use and agricultural productivity.

Geographical Information System for Groundwater Potential Zoning in a Peninsular Region of Bihar

Background: Exponential growth in population and over-exploitation has created groundwater stress situation in several regions globally. The peninsular area spread in the Bhagalpur and Khagaria districts of Bihar (India) is rich in groundwater, but decrease in groundwater level has been observed in the last decade. Methods: In this study, groundwater potential zones have been delineated using remote sensing and geographic information system (GIS) based AHP. The occurrence of groundwater in the study area is mainly affected by following factors- geomorphology, lithology, lineaments, drainage, soil, annual rainfall, slope, land use land cover and fluctuations in groundwater level. Above factors were considered as themes and were prioritized over each-other using the Analytic Hierarchy Process and merged in a GIS environment to delineate the groundwater potential zones. Result: Four different zones of groundwater potential- low, moderate, high and very high have been observed in the study area. The moderate and high groundwater potential zones cover 44% and 55%, respectively. The delineated potential zones have also been validated using the groundwater levels of the pre- and post-monsoon seasons, which match well. The areas at higher elevations were in the moderate potential zones.

Tree stem-atmosphere greenhouse gas fluxes in a boreal riparian forest

Tree stems exchange greenhouse gases with the atmosphere but the magnitude, variability and drivers of these fluxes remain poorly understood. Here, we report stem fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) in a boreal riparian forest, and investigate their spatiotemporal variability and ecosystem level importance. For two years, we measured CO2 and CH4 fluxes on a monthly basis in 14 spruces (Picea abies) and 14 birches (Betula pendula) growing near a headwater stream affected by historic ditching. We also measured N2O fluxes on three occasions. All tree stems were net emitters of CO2 and CH4, while N2O fluxes were around zero. CO2 fluxes correlated strongly with air temperature and peaked in summer. CH4 fluxes correlated modestly with air temperature and solar radiation and peaked in late winter and summer. Trees with larger stem diameter emitted more CO2 and less CH4 and trees closer to the stream emitted more CO2 and CH4. The CO2 and CH4 fluxes did not differ between spruce and birch, but correlations of CO2 fluxes with stem diameter and distance to stream differed between the tree species. The absence of vertical trends in CO2 and CH4 fluxes along the stems and their low correlation with groundwater levels and soil CO2 and CH4 partial pressures suggest tree internal production as the primary source of stem emissions. At the ecosystem level, the stem CO2, CH4 and N2O emissions represented 52 ± 16 % of the forest floor CO2 emissions and 3 ± 1 % and 11 ± 40 % of the forest floor CH4 and N2O uptake, respectively, during the snow-free period (median ± SE). The six month snow-cover period contributed 11 ± 45 % and 40 ± 29 % to annual stem CO2 and CH4 emissions, respectively. Overall, the stem gas fluxes were more typical for upland rather than wetland ecosystems likely due to historic ditching and subsequent groundwater level decrease.

Evaluating machine learning models in predicting GRI drought indicators (case study: Ajabshir area)

Examining the condition of groundwater resources and the impact of droughts is valuable for effective water resources management. Today, machine learning (ML) models are recognized as one of the useful tools in time series predictions. In this study, the groundwater condition of one of the most important aquifers in northwest Iran was investigated using MODFLOW, followed by estimating the groundwater resource index (GRI) utilizing the multivariate adaptive regression spline (MARS) and least squares support vector regression (LSSVR) for a period between 2001 and 2019. Meteorological and hydrological drought indicators along with precipitation and flow rate were used as input variables for prediction. The simulation results revealed a groundwater level decrease since the aquifer withdrawal amount is more than the recharge amount. Besides, results showed that there is a limited interaction between surface water and groundwater resources, mainly caused by the decrease in the river flow and aquifer groundwater level drop. Both ML models performed well in GRI estimation, using groundwater flow, streamflow drought index, standardized precipitation index, and runoff as input variables. The performance of the MARS model with RMSE, MAE, and NSE error evaluation criteria of 0.37, − 0.19, and 0.83, respectively, exerted slightly better results than LSSVR with RMSE, MAE, and NSE of 0.48, − 0.06, and 0.80, respectively. The findings reveal the appropriate performance of both models in forecasting drought indicators, highlighting the necessity of using ML models in hydrology and drought prediction problems.

Spatiotemporally non-stationary evolution of groundwater levels in Poyang Lake Basin driven by meteorological and hydrological factors

The complex relationship between wet-dry transition in the Poyang Lake basin and groundwater storage significantly affects the lake's hydrology, downstream ecological state, and overall security along the Yangtze River in China. There is, however, a notable lack of systematic exploration into how various factors drive spatiotemporal variability in groundwater level (GWL). Using local indicators of spatial association (LISA), spatial non-stationarity models, and multi-source data, our analysis explores the spatial distribution of GWL and quantifies the influence of driving factors on its spatiotemporal non-stationarity at annual and monthly scales. We also compare driving factor contributions in hilly, plain, and local areas within the Poyang Lake basin. Our findings reveal significant local clustering of GWL, indicating substantial spatial autocorrelation and geographic heterogeneity in GWL. Influencing factors exhibit non-stationary effects on GWL at spatial and temporal scales, with precipitation (P), ground surface elevation (GSE), and soil moisture (SM) being primary contributors, generally exerting positive effects. SM contributes most during dry years and normal periods. P and the Palmer Drought Severity Index (PDSI) have greater impacts in hilly areas, while GSE shows the opposite trend. Rainfall is a source of groundwater recharge, with a lagged response observed in GWL to rainfall in this basin. The lag time is about 1–2 months. Evapotranspiration is not the dominant discharge pathway. The decrease in GWL during the dry season is mainly due to reduced precipitation recharge and increased lateral groundwater discharge from areas of high hydraulic head to areas of low hydraulic head.

Assessing the Impact of Groundwater Recharge on Underground Reservoir Replenishment in Eastern Uttar Pradesh, India

Groundwater is considered a fresh resource of water and its uses have tremendously increased in the recent past due to an increase in population, rapid urbanization, and industrialization. In India, the groundwater level is declining in some parts of the country due to over-exploitation, low or negligible recharge of aquifer systems, and unsustainable development of groundwater resources. The groundwater modeling is an important tool for studying the past and present groundwater behavior and in the development of future strategies for sustainable groundwater management plans. To study the Impact of groundwater recharge on the replenishment of underground reservoir, Ballia district of Uttar Pradesh has been selected which is one of the districts of the most populous state of India, Uttar Pradesh. An attempt has been made to develop a groundwater model using Modflow software to simulate the groundwater trends and predict future groundwater heads. The calibration and validation of the model were done for 5 years and 3 years respectively. The correlation coefficient for calibration and validation was found 0.85 and root mean square errors vary from 2.89 to 3.2m variation in future trends of groundwater heads. The results of the study show that the developed model can be effectively used to predict the future groundwater heads. The groundwater flow was observed from the northwest to southeast direction. It was predicted from the study that groundwater draft will increase by 10% with a decrease in groundwater level by approximately 0.24 m in the north-west direction by the year 2025. However, no impact was observed in the south side of the district and it was predicted that the groundwater level would remain the same in this zone during the next 3 years.

DECOMPOSITION OF RIVER HYDROGRAPHS TAKING INTO ACCOUNT DATA OF HYDROGEOLOGICAL OBSERVATIONS

In the case of absence of reliable information on fluctuations of levels and hydraulic parameters of aquifers within a large catchment, the method of river hydrograph decomposition can be used to assess groundwater component and other constituents of river water recharge. The difficulties and shortcomings of this method, which relies on specific schematizations and assumptions, are analysed and discussed. We propose to take into account the results of calculations of lateral groundwater inflow to the river accomplished using the numerical method based on observations at representative balance sites in order to improve the accuracy of the method of decomposition of the river hydrograph. A proper schematization should also be justified for river catchment (or its part), which describes the interaction of surface water, shallow groundwater, and artesian (deep) interlayer waters, which provides rationale for defining or neglecting groundwater inflow to river during the flood periods. The most disputable issue remains the allocation of the phase of “reverse water inflow to river banks” during flood periods. The groundwater level rise at the beginning of the flood results from the infiltration recharge to the aquifer and from inflow of water from the river. The contribution of inflow to river bank to groundwater level rise is dependent from the distance from the river to the observation well. To establish hydraulic head gradient from the river towards the adjacent groundwater aquifer at flood peak, at least two observation wells are needed, one of which should be located 3–4 m from the river water edge on the elevated part of the bank which is not flooded, and the other should be located 50–70 m from the bank towards the watershed. It is proposed that the phase of maximum groundwater inflow to the river should be adjusted based on the dates of the beginning and ending of the groundwater level decrease during the recession of the river flow during the flood period. The combined application of the described above methods showed that the use of only hydrograph decomposition method underestimates the share of groundwater recharge to the river by 2–5%. Based on the analysis of the Pivdennyi Buh River hydrographs during the 1980–2020 period, general tendencies of changes in the shallow groundwater and deep subsurface recharge of the Pivdennyi Buh River in its upper basin (upstream of the city of Khmilnyk) have been established: deep subsurface recharge prevailed over the shallow groundwater component (33.4 compared to 25.0% of the total). At the same time, the total subsurface runoff constituted on average 58%.

Assessment of the impact of socio-economic policies on groundwater consumption using a multi-agent-based modeling approach

Abstract This study examines sustainable water management in the Eshtehard plain, Iran, addressing the impact of inappropriate groundwater use and the resulting decrease in groundwater levels. Using agent-based modeling, it evaluates stakeholder interactions to enhance groundwater management. This framework simulates farmers’ responses to changing water resources, considering agricultural demand and socio-economic factors. The study assesses the influence of governmental policies on farmers’ decisions across five scenarios, finding that implementing specific policies can reduce groundwater extraction and improve the hydrological–social situation, provided the government has necessary funding. The findings offer valuable insights for future planning, policy-making, and assessing the impact of management scenarios on water resources and farmers’ economic status. The proposed framework serves as a tool to support stakeholders in making informed decisions for sustainable groundwater management.

Determination of groundwater conservation zones study by considering groundwater recharge changes

This paper aims to find a new groundwater conservation zone concept in Indonesia by improving groundwater zoning by considering groundwater recharge changes. The previous zoning criteria only used groundwater level decrease and selected groundwater quality parameters. The ideas of this new concept are related to actual conditions, in terms of groundwater recharge changes due to global climate changes that control the precipitation frequency and in terms of land use changes that control groundwater recharge quantity. The changes are dynamically altered due to anthropogenic interactions. Based on Decree No. 31 2018, the groundwater conservation zone is based on three criteria: the decline of the groundwater table, the groundwater’s physical quality, and the apparent effect on the environment. This research will improve the criteria by suggesting some improvements to that approach: firstly, the application of modeling in calculating the groundwater decline rate, secondly the investigation of the effect of recharge decline due to land use change, and lastly to include recommendations on each zone in the groundwater conservation zone. This new concept is expected will revise the previous Decree that according to the consensus approach is not a scientific approach

Study of Spatial Variability of Groundwater Depth in Sirsa District of Western Agro Climatic Zone of Haryana

Groundwater plays a vital role in agriculture and industry in various sectors across India, especially in Haryana’s Sirsa district, where groundwater plays a vital role. Approximately 50% of the irrigated land is dependent on groundwater, while 60% of the food production is dependent on groundwater. The depletion of groundwater in Haryana is a major concern due to population growth and increasing water demand, which is further aggravated by water-intensive crops. Even though Haryana accounts for 1.4 % of the country's geographical area, food production in Haryana contributes significantly to the nation's GDP. The study concentrates on Haryana, where groundwater plays a key role, especially in the Sirsa district, where the availability of surface water is limited. From 1974 to 2022, there is a worrying trend of decreasing groundwater levels in the Sirsa district in four blocks, which is mainly attributed to unregulated groundwater extraction, especially for agriculture, which results in ecological damage. Sustainable water management strategies need to be implemented in order to mitigate groundwater depletion and ensure long-term agri-sustainability and water security in Haryana. These strategies include changing cropping patterns, awareness campaigns, conjunctive water use, rainwater harvesting, and minimizing conveyance and application losses. By taking these steps, we have a chance to reduce groundwater depletion and ensure long-term agri-sustainability and overall water.

The Impact of Climate Change and Urbanization on Groundwater Levels: A System Dynamics Model Analysis

Climate change and population growth have placed increasing stress on groundwater resources. Effective management of groundwater resources is crucial for promoting sustainable development, especially in areas heavily reliant on groundwater supply. However, sustainable groundwater management is more complex due to various factors affecting key drivers and their feedback interactions. In this regard, this study aims to examine the key driving forces and their interplay concerning fluctuations in groundwater levels within a study area in Illinois, United States, which heavily relies on groundwater for water supply. To achieve this objective, a system dynamics (SD) simulation model was developed, utilizing hydrology, climate, and urbanization data spanning from 2010 to 2020. Through calibration and validation of the SD model with historical data, the model demonstrated reliable simulation capabilities for groundwater levels. Additionally, sensitivity analysis and exploration of water resource scenarios were conducted to evaluate the critical factors influencing groundwater levels. Results revealed that population dynamics, agricultural land, and groundwater recharge were analyzed as key drivers influencing the change in groundwater level for the study area, among the climate and urbanization factors that had different contributions to the groundwater dynamics. A 10% increase in population, agricultural land, and groundwater recharge led to a decrease of approximately 5.5% and increases of 4.5% and 4.27% in groundwater levels, respectively. The results of the four-scenario analysis indicated that both climate change and urbanization exerted significant and adverse impacts on the groundwater level in the study area. These scenarios represented prominent and worst-case situations, highlighting the potential challenges and risks associated with the combination of these factors, which resulted in about a 77 mm decrease in groundwater levels by 2030. Overall, given limited data availability for SD model parameterization, the study emphasizes the need to consider the effects of both urbanization and climate change on groundwater supplies in decision-making for sustainable groundwater management, as well as the need for adequate management measures to maintain the long-term usage of groundwater resources.

Mapping of groundwater availability in dry areas of rural and urban regions in India using IOT assisted deep learning classification model

Groundwater is a crucial resource for fulfilling the water requirements of India's rural and urban areas. The heterogeneous nature of geological, hydrological, and climatic factors results in substantial variability in the accessibility of groundwater across disparate regions. The present investigation centers on the cartography of groundwater accessibility in arid zones of rural and urban Indian areas using a Deep Learning Classification Model (DL-GWCM) supported by the Internet of Things (IoT). The introductory section underscores the importance of groundwater in India, where groundwater sources cater to around 80% of rural and 50% of urban water demands. The text highlights statistical data derived from surveys that indicate a notable decrease in groundwater levels. This underscores the pressing necessity for implementing effective monitoring and management strategies. The DL-GWCM is a proposed solution that aims to enhance the precision and effectiveness of groundwater availability mapping by incorporating IoT technology and Deep Learning Classification. The DL-GWCM comprises multiple constituent elements, such as Groundwater Prediction, Water Quality Index, and Conventional Neural Network- Bidirectional Long Short-Term Memory (CNN–Bi LSTM) classification. The process of Groundwater Prediction involves the utilization of past data and environmental factors to make precise forecasts of groundwater levels. The Water Quality Index evaluates the quality of subsurface water resources, guaranteeing their secure and enduring utilization. The Deep Learning Classification Model with IoT technology was implemented for groundwater accessibility mapping in Indian arid zones. It integrates Groundwater Prediction, Water Quality Index, and CNN–Bi LSTM classification. The model makes precise forecasts using past data and environmental factors, ensuring secure water quality. Using the CNN–Bi LSTM classification model improves the precision of groundwater availability mapping due to its resilient classification capabilities. These findings suggest that the DL-GWCM outperforms conventional approaches. The mean values of all five metrics for the proposed method are presented as follows: The performance metrics of the model are as follows: Root Mean Square Error (RMSE) of 0.77%, Mean Absolute Error (MAE) of 2.13%, Relative Absolute Error (RAE) of 8.72%, Root Relative Squared Error (RRSE) of 0.92%, and Correlation Coefficient (CC) of 0.92. The results of the proposed methodology facilitate the discernment of regions with abundant or scarce groundwater accessibility, thereby supporting the sustainable management and planning of groundwater resources.

Groundwater Recharge from Below under Changing Hydro-Meteorological Conditions in a Forested and Grassland Site of the Great Hungarian Plain

The process of groundwater evapotranspiration and its subsequent recharge are fundamental aspects of the Earth’s natural water cycle and have significant implications for the preservation and functionality of various forested ecosystems. This study presents a case analysis examining the recent fluctuations in groundwater levels and their replenishment in two wells situated at a designated forested experimental area and a control site. The magnitude and temporal fluctuations of groundwater recharge were examined through the utilisation of a novel adaptation of the traditional White method, which was specifically tailored to the local context. We also tested the sensitivity of the White method as an indicator of the system’s behaviour because the signal has changed in relation to the access of the forests to groundwater under the conditions of regionally declining groundwater resources and a warming climate. The novelty of this approach is found in the examination of the temporal fluctuations in groundwater recharge, which are influenced by both a decrease in groundwater levels caused by forest evaporation in response to climate change and a regional reduction in groundwater supplies. As a result, the ongoing decrease in groundwater levels may have significant adverse effects on local forests.

Impact of Soil Surface Temperature on Changes in the Groundwater Level

The relationship between the soil surface temperature and groundwater level is complex and influenced by various factors. As the soil surface temperature increases, water evaporates quickly from the soil, which can lead to a decrease in the groundwater level. In this study, we analyzed the impact of soil surface temperature on changes in the groundwater level in the Bukhara region of Uzbekistan using data from 1991 to 2020. The Bukhara region experiences regular water shortages, increased soil salinization, and inefficient energy in lift-irrigated areas, which is a typical constellation of challenges to the water–energy–food–environment (WEFE) nexus. The soil surface temperature data were collected from the Hydrometeorological Service Agency, whereas groundwater level data were obtained from the database of the Amelioration Expedition under the Amu-Bukhara Basin Irrigation Systems Authority. We used linear regression analysis and Analysis of Variance (ANOVA) tests to establish the significance of the relationship between the soil surface temperature and groundwater level, as well as the impact of the location of the groundwater level measurements. The results indicate that the model was a good fit to the data, and both the intercept and the soil surface temperature were significant factors that affected groundwater level. The results further suggest that the strength of the relationship between solar radiation and soil surface temperature is very high, with a correlation coefficient of 0.840. This means that when solar radiation increases, soil surface temperature also tends to increase. The analysis also showed that 53.5% of the changes in groundwater level were observed by the regression model, indicating a moderately correlated relationship between the groundwater level and soil surface temperature. Finally, higher solar radiation leads to higher soil surface temperature and higher evapotranspiration rates, which can lead to a decrease in groundwater level. As a result, we observe that the soil surface temperature determines changes in the groundwater level in the study region.

CHORNOBYL’S CURRENT DENDROFLORA: ANALYSIS OF NATURAL SUCCESSIONS IN THE ABANDONED URBAN PHYTOCOENOSES

The research on the dendroflora of Chornobyl town 30 years after the accident at the Chornobyl nuclear power plant reveal that the taxonomic composition of the town green spaces comprises of 87 species and 8 decorative forms of 29 families, 26 orders, 2 divisions. The composition of plantations is dominated by trees (63%), bushes (30%) and winding plants (7%). Despite the natural succession processes over the past 30 years, the plantations of Chornobyl are dominated by introducers, which make up 57% of the total number of taxa. The study of test areas reveals successional changes in the abandoned phytocoenoses of the town, which led to the expansion of the alien invasive species Acer negundo L., Robinia pseudoacacia L., Fraxinus pennsylvanica L. and Parthenocissus quinquefolia (L.) Planch. The spread of alien invasive species is facilitated by droughts of long periods and the decrease in groundwater level. Climate change and the lack of proper agrotechnical care result in fungal diseases, damages caused by the semi-parasitic species Viscum album L. on decorative and fruit trees and bushes, both also leading to their expel from the town plantations.

Delineation and Mapping of Ground Water Quality in Kanchipuram District of Tamil Nadu Using GIS Techniques

Agriculture relies heavily on irrigation especially with groundwater which is a significant source in many countries. However, excessive use of groundwater can lead to a decrease in groundwater levels and cause scarcity of water. Irrigation requires good-quality water which is governed by dissolved ions. The groundwater quality is greatly influenced by global population growth, climate change and human activities including mining, agriculture, industrial effluents, seawater intrusion, household usage, etc., A study was conducted to evaluate the quality of groundwater for agriculture in various blocks of Kanchipuram district in Tamil Nadu. The sampling was done during March 2023 and about one hundred and fifty groundwater samples were collected from different blocks of the Kanchipuram district viz., Sriperumbudur(32 Nos), Kundrathur (28 Nos), Walajabad (34 Nos), Uthiramerur (29 Nos) and Kanchipuram (27 Nos). The physio-chemical (pH and EC) and chemical characteristics of the groundwater samples, including the cations Ca2+, Mg2+, Na+, and K+, as well as the anions CO32-, HCO3-, Cl-, and SO42-, were analyzed and the resulting properties were computed (SAR and RSC). The pH and EC values ranged from 3.29 to 8.49 and 0.09 to 5.22 dS m-1, respectively. The Residual Sodium Carbonate (RSC) ranged from nil to 32 meq L-1, while the Sodium Adsorption Ratio (SAR) ranged from 0.19 to 34.78 mmol L-1. According to the CSSRI, Karnal Water Quality Classification about 38 percent of the samples falls in the good quality category, alkali water was about 57.33 percent and Saline water was 4.67 percent in Kanchipuram district. The Good quality water was dominant in Uthiramerur block followed by the Sriperumbudur block. The Saline and Alkali water was dominant in Sriperumbudur and Kanchipuram blocks respectively.

Surface modification of polysulfone reverse osmosis membrane with chitosan-modified zinc oxide for water desalination

ABSTRACT Decreasing groundwater levels, increasing world population, and pollution of water resources by industries lead to the use of new technologies for augmenting the fresh water supply such as its desalination. Chitosan-modified zinc oxide (C-ZnO) nanoparticles were synthesized and used for surface modification of polysulfone (PSf) in water desalination. PSf /C-ZnO membrane was fabricated through the phase inversion method and characterized by Fourier transfer infrared (FTIR), X-Ray diffraction (XRD), field emission scanning electron microscope (FESEM), atomic force microscope (AFM), energy dispersive X-ray (EDX), Braunauer-Emmett-Teller (BET), and contact angle. The nanoparticle effect on the membrane properties was investigated by measuring the pure water flux and solute rejection under two constant pressures, at 6 and 10 bar, and the salts concentration of MgSO4, MgCl2, NaCl, and CaCl2 at 1 gL−1. The results showed that nanoparticles increased the hydrophilicity of the pristine PSf membrane while slightly decreasing the water permeability. Moreover, the salt rejection increased with the nanoparticle addition up to 0.2 wt.% while it decreased with 0.5 wt.% nanoparticle due to changing the membrane finger-like pores sublayer structure.

An analysis of terrestrial water storage changes of a karstic, endorheic basin in central Anatolia, Turkey

Water budget components of endorheic basins of semi-arid and karstic characters are difficult to assess. In this study, we attempt to estimate the water budget components of the Konya Endorheic Basin (KEB), which is a semi-arid, karstic basin in central Anatolia, using The Gravity Recovery and Climate Experiment mission (GRACE) observations and Global Land Data Assimilation System (GLDAS) data over the period 2002-2019. We also investigate the trends and sub-trends in the time series of the hydrometeorological parameters. The results indicate that the available water potential in the basin has a decreasing trend over the study period. Precipitation and evapotranspiration show increasing trends in the basin, however, the other hydrometeorological parameters demonstrate decreasing trends. Both Terrestrial Water Storage Anomaly (TWSA) and groundwater level decrease significantly (20.21 mm/yr and 122.34 mm/yr, respectively). The dry 2008 and subsequent wet year created a hydrological breaking point in the time series. The weights of soil moisture and groundwater storages are relatively large amongst the TWSA components (49.61% and 33.12%, respectively). The surface water storage anomaly comes at the third place with a 14% weight. It is assessed that the groundwater storage system responds to precipitation with a delay of 6 months. Limestone zones respond more sharply to groundwater depletion than alluvial zones. It should be noted that the GRACE and GLDAS data could be used together to successfully estimate the water budget components for sustainable management of the limited water resources of the basin.