Decrease In Groundwater Level Research Articles

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.

The Effect Of Groundwater Level And Organic Mulch Application On The Chemical Properties Of Peat Soil

 
 Peat as agricultural land has various obstacles, one of the problems is the decrease in groundwater level. This can have an impact on the availability of nutrients in the soil. Therefore, water management is an absolute necessity for agricultural activities on peatlands. Another effort that can be made to increase the fertility of peatlands as agricultural land is to use organic mulch. This study aims to analyze the effect of peat water level and application of organic mulch on the chemical properties of peat soil planted with corn. This research was conducted in Air Terbit Village, Riau Province and the Soil Laboratory, Faculty of Agriculture, University of Riau, from February to July 2021. This research used a factorial complete randomized design (CRD) method consisting of 2 factors. The first factor was the various heights of the groundwater level which consisted of 3 levels (30 cm, 40 cm and 50 cm), while the second factor was various types of organic mulch (without mulch, mulch of empty oil palm bunches, mulch of rice straw and mulch of corn stover). The results showed that the GWL 30 cm treatment and rice straw mulch increased the pH, Ca and Mg values ​​better than the other treatments, the N element also increased at GWL 30 cm. In general, the two treatment factors also increased the values ​​of P, CEC and Na in some experimental units. C-organic and K values ​​decreased after the treatment compared to the criteria of the soil before treatment.

Numerical Evaluation of Large-Scale Groundwater Extraction in Groundwater System at Wellfields in the Namwon Area of Jeju Island, South Korea

A regional water supply system in Jeju Island, South Korea, comprising 23 wellfields with 5 to 10 groundwater extraction wells (20–100 m spacing), provides water to the residents of the island. Regular large-scale groundwater pumping and excessive extraction in these wellfields have resulted in a decrease in groundwater levels. Using a numerical model, we aimed to assess the effect of large-scale groundwater extraction at four wellfields in Namwon, located in the southeastern part of the island. The numerical model estimated an approximately 0.16–0.21 m decline in water levels, which is consistent with field observations. Minor declines are inherently influenced by the regional hydrogeological setting of the study area, which involves high precipitation rates and a groundwater flow system that facilitates rapid groundwater replenishment. However, the model also shows that the decrease in groundwater levels is expected to intensify to 0.20–0.77 m in cases of extreme drought periods and increasing rates of groundwater pumping. In addition, this study suggests that sufficient well and wellfield separation distances should be considered to prevent well interference effects in areas, such as the western part of the island, with increased decline in water levels due to groundwater extraction.

MODELING OF GROUNDWATER LEVEL CHANGES DUE TO DEEP WELL EXTRACTION USING MODFLOW IN THE NORTH OF BANDAR LAMPUNG

The growth rate of urban areas in the north of Bandar Lampung has caused the extraction of groundwater resources through deep well pumping to increase. Therefore, it is necessary to study the impact of pumping to prevent groundwater depletion. This study performs numerical simulation modeling to identify the impact of deep well pumping on changes in groundwater levels in three sub-districts north of Bandar Lampung city. Modeling is done using MODFLOW-6 and ModelMuse as a graphical user interface (GUI). The simulation method uses steady-state and transient models with four stress periods in 2000, 2010, 2020, and 2030. A total of 30 data wells are used for model setup, and 15 of them as observation and validation points. The simulation results show that hydraulic head changes occur at depths of 10 m to more than 40 m. Drawdown and groundwater head changes are concentrated at deep well points with a radius of up to 1 km. The model also successfully identified a decrease in groundwater level to more than 8 m in the deepest well area DW1. Thus, it is necessary to take action that can overcome the impact of changes in groundwater level due to pumping from deep wells. Furthermore, groundwater storage engineering can be one solution by utilizing rainwater harvesting technology to recharge the groundwater aquifer system.

Analysis Of Land Subsidence Relationship With Groundwater Table Depletion In South Jakarta

Increased development activities and urbanization in South Jakarta have increased groundwater extraction. Continuous withdrawal of groundwater with poor management can cause a decrease in the groundwater level and trigger a subsidence. Therefore, a study is needed regarding the relationship of land subsidence with the decrease in groundwater levels that occur in South Jakarta. This research was conducted using secondary data in the form of drill log data to determine subsurface lithology, land subsidence measurement data using the GPS geodetic method, and groundwater level data in monitoring wells in Jakarta. The results of the study show that surface sediment deposits are dominated by a layer of clay which is still unconsolidated and relatively thickened to the north with a thickness of more than 300 m. This condition shows that the sediment layers in Jakarta are still undergoing a compaction process so that naturally subsidence occurs in the soil surface. Subsidence in the land surface in South Jakarta has a fairly strong correlation with the decline in the groundwater level, which is equal to 0.504, which means it has a fairly strong degree of correlation of 50.4%.
  

Effects of Yellow River Water Management Policies on Annual Irrigation Water Usage from Canals and Groundwater in Yucheng City, China

The Yellow River Water Allocation Management Method was put into place in 1998 to decrease the Yellow River water amount used by upstream areas and provide more water to downstream regions. Rainfall and Yellow River’s infiltration are the main groundwater supply in the downstream area of Yellow River. The groundwater table in the downstream area has continued to decrease since 1979, and the extracted groundwater for irrigation is the main reason for this. Whether the increased river water amount could improve the decreased groundwater level is uncertain. Therefore, we used remote sensing images, groundwater level observations, meteorological data, and unit mean irrigation rate to identify the irrigation events for river water and groundwater, estimate the annual river water irrigation amount and groundwater irrigation amount, and analyze the effects of river water allocation on the groundwater table. Our analysis showed that the area of double-irrigated farmland (farmland that could be irrigated by both groundwater and river water) tended to decrease, while well-irrigated farmland area (farmland that could only be irrigated by groundwater) remained unchanged during the study period. The number of annual irrigation events tended to increase, and the usage of river water remained consistent throughout this period. The increased number of well irrigation events caused annual groundwater usage for irrigation to increase. However, the usage of river water for irrigation remained stable. The increased usage of groundwater for irrigation led the groundwater table to continually decrease from 1998 to 2019. This indicates that there are shortcomings to the current water allocation policy, and that further improvements are needed to prevent continued decrease in groundwater levels.

Delineation of groundwater potential zone for sustainable water resources management using remote sensing-GIS and analytic hierarchy approach in the state of Jharkhand, India

Groundwater abstraction in many parts of India is highly unregulated which has caused a gradual decrease in groundwater levels over the years. Normally surface water storage structures or recharge zones are developed without knowing if all the groundwater is getting recharged. The issue becomes serious in the plateau region where most of the rainfall goes as surface runoff. Here an effort was made to identify the groundwater potential recharge zones of the entire Jharkhand state using Remote Sensing, GIS, and Analytic Hierarchy Approach techniques. Thematic layers which could contribute to the successful recharge of groundwater were prepared. The whole region was classified into four prospective groundwater potential zones: extremely low, low, moderate, and high. The results showed that approximately 3.28 and 77.34% of the total area falls under the High and average groundwater potential zones and the rest are under Low and Very low. Most of the high potential area is located in eight districts due to the alluvial plain region or a few mountains in that region namely Godda, Sahibganj, Pakur, Dumka, Purbi, Singhbhum, Saraikela-kharsawan and part of the Ranchi. The discharge data of 28 existing bore wells were used to endorse the groundwater potential zones. The further validation was made with an Area Under Curve (AUC) of 83%. According to the validation, the applied method produces a fairly dependable outcome for the state of Jharkhand.

Evaluating the sources and fate of nitrate in riparian aquifers under agricultural land using in situ-measured noble gases, stable isotopes, and metabolic genes

Riparian zones with their buffering ability and abundant water supply are often subjected to intensive agricultural activities. We investigated a riparian aquifer located near a stream in South Korea that recently experienced sharply decreasing groundwater levels and elevated nitrate (NO3–) concentrations, which were attributed to local agricultural activities. Our goal was to identify the predominant nitrogen sources and NO3– removal processes. Multiple approaches including geochemical and isotopic tracers, land-use analysis, metabolic gene quantification, and inert gas tracers were used to elucidate groundwater and nutrient dynamics in stream-side granitic aquifers. The dual isotopic composition of NO3– identified manure and sewage as the major sources of NO3– contamination. Denitrification was the dominant NO3– removal process in the aquifer, as demonstrated by the negative relationship between δ15N and δ18O values in NO3–and NO3–/Cl–. Denitrification and anammox genes were also observed in microbial communities of the aquifer throughout the study site, suggesting that these processes support effective natural NO3– attenuation in groundwater. A mixing model constructed using a catchment-scale dataset including SiO2 concentrations and δ18O-H2O suggested that mixing with paddy soil water was the major driver of denitrification in the aquifer at the study site, where impervious layers provided anaerobic conditions for natural NO3– attenuation. Denitrification reduced the NO3– flux into the nearby stream by up to 114.4 NO3– kg/ha/y (26 kg N/ha/y). The N2 generated by denitrification did not accumulate in the groundwater, but mostly escaped from groundwater to the atmosphere, as demonstrated by the degassed signature of dissolved inert gases below the air saturated water level. This study identified the predominant NO3– sources and conceptualized N cycling in the heavily developed agricultural riparian aquifer using multiple tracers, demonstrating that NO3– is partially removed through denitrification and possibly anammox while N2 mostly escapes into the atmosphere.

Optimal utilization of groundwater resources and artificial recharge system of Shahriar plain aquifer, Iran

Developments in agriculture, industry, population growth and climate change lead to increased utilization of groundwater resources, followed by a decrease in groundwater level and an increase in the concentration of pollution in aquifers. Accordingly, the objective of this study was to investigate the impact of optimal groundwater utilization and artificial recharge systems on groundwater level fluctuations and changes in pollution concentration of the Shahriar plain aquifer. Therefore, there was a need for a comprehensive multi-objective simulator-optimizer model that would be able to solve existing problem. For this purpose, a multi-objective modeling platform was developed that included two independent simulator-optimizer models. In the first model, the artificial neural network (ANN) was used to simulate the changes of groundwater level (GWL) and its quality as a function of the TDS index in the Shahriar Plain aquifer. The regression was then used to predict groundwater quality. Finally, the multi-objective genetic algorithm (NSGA-II) was used to optimize groundwater resources harvesting. The second model simulated the flood storage volume in the reservoirs of the artificial recharge system (ARS) using ANN and then optimized utilization of the artificial recharge system using (NSGA-II). The results of the first model showed that the optimal volume of water withdrawn from the aquifer and the optimal TDS value of the aquifer decreased by 29 and 18%, respectively, while the changes of the optimal groundwater level increased by 28 m. Furthermore, based on the second model results, the total volume of optimal recharge will increase by 119% in the studied period due to the artificial recharge system, followed by a 14% increase in the changes of the optimal groundwater level. Overall, it can be concluded that the multi-objective modeling platform method can meet the objectives of this research simultaneously.