Surface Water Bodies Research Articles

Melamine - A PMT/vPvM substance as a generic indicator for anthropogenic activity and urbanisation? An explorative study on melamine in the water cycle and soil.

Melamine has a high production volume today and is spread ubiquitously in the anthropogenic technosphere. It is released steadily to the water cycle by many sources. Even though melamine has low direct toxicity, chronic exposure can cause nephrolithiasis and disrupt the endocrine system. Most data on melamine is based on case studies with, when compared, partially contradictive implications. As melamine is a compound of many sources (SMS), very persistent, mobile (vPvM), and toxic (PMT) it has the potential to break through natural barriers posing a potential risk to drinking water resources. This study combines existing data with own measurements gathered through various individual monitoring campaigns with the aim to gain new insights into its environmental behaviour and hotspots. Samples from surface water bodies, groundwater, wastewater (treated, untreated), and soil samples were analysed regarding their melamine concentration via liquid chromatography coupled with tandem mass spectrometry (LC-MSMS). Besides three drinking water samples, melamine could be found in all water samples (n=632) of this study, with a maximum concentration of 1289ng/L in drinking water and 1120ng/L in groundwater. While a constant baseline melamine concentration with an event-based release could be observed in most surface water bodies, higher concentrations towards Western Europe (urbanisation and chemical industry) was observed for wastewater. A similar pattern was found in the spatial distribution of melamine in agricultural soils towards an urban/suburban area. As, in general, melamine concentrations were higher towards urbans centers melamine can also be classified as an indicator of anthropogenic activity and urbanisation, but also spotlights on these areas as hotspots for potentially many compounds of the human technosphere. We call policy to shift from the existing one-size-fits-all solution to more flexible and risk-based approaches to prepare for future challenges.

Polystyrene nanoplastics are unlikely to aggregate in freshwater bodies.

The fate and toxicity of nanoplastics (NPs) in the environment is largely determined by their stability. We explored how water composition, nanoplastic size, and surface carboxyl group density influenced the aggregation of polystyrene (PS) NPs in fresh water. Unfunctionalized 200, 300, 500, and 1000nmPS NPs and 310nm carboxylated PS NPs with carboxyl group densities of 0.35 and 0.6mmolg-1 were used to simulate pristine and aged NPs. Natural water matrices tested in this study include synthetic surface water (SSW), water from the Schie canal (Netherlands) and tap water. Suwannee River Natural Organic Matter (SRNOM) was included to mimic organic matter concentrations. In CaCl2, we found PS NPs are more stable as their size increases with the increase of the critical coagulation concentration (CCC) from 44mM to 59mM and 77mM for NP sizes of 200nm, 300nm and 500nm. Conversely, 1000nmPS NPs remained stable even at 100mM CaCl2. Increasing the carboxyl group density decreased the stability of NPs as a result of the interaction between Ca2+ and the carboxyl group. These results were consistent with the mass of Ca2+ adsorbed per mass of NPs. The presence of SRNOM decreased the stability of PS NPs via particle bridging facilitated by SRNOM. However, in SSW, Schie water and tap water with low divalent cation concentrations, the hydrodynamic size of PS NPs did not change, even at prolonged durations up to one week. We concluded that PS NPs are unlikely to aggregate in water with low divalent cation concentrations, like natural freshwater bodies. Ecotoxicologists and water treatment engineers will have to consider treating PS NPs as colloidally stable particles as the lack of aggregation in fresh surface water bodies will affect their ecotoxicity and may pose challenges to their removal in water treatment.

Purification mechanism of emergent aquatic plants on polluted water: A review.

Nitrogen and phosphorus inputs to surface water bodies lead to a decline in water quality and a disruption in the balance of aquatic ecosystems. Emergent aquatic plants were widely used for their high efficiency in removing nitrogen and phosphorus from surface waters. However, there was a lack of systematic analyses on the purification of surface waters by emergent aquatic plants, and the mechanism of differences in nitrogen and phosphorus removal by different plants needs to be further revealed. By preferentially selecting emergent aquatic plants, the removal effects of 15 selected aquatic plants on five pollutant indicators (total nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus, and chemical oxygen demand) were analyzed at different concentrations, and the characteristics of the removal of pollutants by different aquatic plants were explored. At the same time, combined with the morphology and synergistic action of microorganisms, in-depth research on the purification mechanism of water bodies by emergent aquatic plants was conducted. Differences were found in the purification of different water-supporting aquatic plants for different concentrations of pollutants. The comprehensive evaluation results of the membership function showed that the combined purification ability of Acorus calamus, Cyperus involucratus, Iris pseudacorus and Typha orientalis was better for the conventional pollutants. This study provides an important reference for the preferential selection of emergent aquatic plants to enhance water pollution purification and further promote the progress of ecological water treatment technology.

Integration of Machine Learning and Remote Sensing for Water Quality Monitoring and Prediction: A Review

Aquatic ecosystems play a crucial role in sustaining life and supporting key green and blue economic sectors globally. However, the growing population and increasing anthropogenic pressures are significantly degrading terrestrial water resources, threatening their ability to provide essential socioeconomic services. To safeguard these ecosystems and their benefits, it is critical to continuously monitor changes in water quality. Remote sensing technologies, which offer high-resolution spatial and temporal data over large geographic areas, including surface water bodies, have become indispensable for these monitoring efforts. They enable the observation of various physical, chemical, and biological water quality indicators, which are essential for assessing ecosystem health. Machine learning algorithms are well suited to handle the complex and often non-linear relationships between remote sensing data and water quality parameters. By integrating remote sensing with machine learning techniques, it is possible to develop predictive models that enhance the accuracy and efficiency of water quality assessments. These models can identify and predict trends in water quality, supporting timely interventions to protect aquatic ecosystems. This paper provides a thorough review of the major remote sensing techniques for estimating water quality indicators (e.g., chlorophyll-a, turbidity, temperature, total nitrogen and total phosphorous, dissolved organic, total suspended solids, dissolved oxygen, and hydrogen power). It examines how machine learning can improve water quality assessments. Additionally, it identifies key research gaps in current methodologies and suggests future directions to address challenges in water quality monitoring, aiming to improve the precision and scope of these critical efforts.

Using Polyvinyl Chloride and Screen-Printed Electrodes for the Determination of Levofloxacin in the Presence of Its Main Photo-Degradants in River Water: A Comparative Study

The application of membrane sensors for the detection and quantification of pharmaceutical environmental contaminants has become a significant goal in recent years. Due to the widespread application of levofloxacin hemihydrate (LEVO) in medicine, its occurrence in the environment, especially in surface water bodies like rivers, is quite likely. Extended exposure of river water to sunlight and the photo-degradability of LEVO may facilitate its photo-degradation. To measure LEVO in the presence of its principal photo-degradants, two sensitive and selective membrane electrodes were designed. A polyvinyl chloride electrode (PVCE) and a screen-printed electrode (SPE) were constructed for the selective analysis of the investigated drug. Phosphomolybdic acid was used to prepare a lipophilic ion pair with the studied drug. All test parameters were optimized to achieve the best electrochemical performance. The electrodes demonstrated a linear range from 1 × 10−6 M to 1 × 10−2 M. The PVCE and SPE demonstrated slopes of 55.80 ± 0.70 mV/decade and 56.90 ± 0.50 mV/decade, respectively. The aforementioned sensors demonstrated satisfactory performance within a pH range of 3.0 to 5.0. The fabricated sensors were successfully utilized to accurately quantify LEVO in the presence of its primary photo-degradants. The membranes were effectively utilized to measure LEVO in river water samples without requiring pre-treatment processes.

Monthly drought monitoring of the surface water area of Sawa Lake, Iraq during 2016-2022 using remote sensing data

Drought is a common phenomenon in Iraq's environment, and the country has experienced severe drought events exacerbated by the threat of climate change (low rainfall and high temperatures) over the past two decades. Iraq is located in a semi-arid region whose water resources have been restricted and mostly shared with its neighbours. To investigate the effect of drought on the surface water area of Sawa lake, we analysed 52 Sentinel-2 images from May 2016 to July 2022 using an open-source SNAP toolbox to map the boundary of the surface-water body of the lake. The results indicate that the surface water area of Sawa lake has de-creased significantly over the last six years with the most extreme decline beginning in May 2021, when the area of the lake lost about 51% of its initial size (May 2016). By March 2022, the lake had disappeared and about 96% of the water's surface area had been lost. To better understand the potential causes of droughts, further analysis has been conducted on the effects of precipitation and human activities (vegetation cover and Al-Samawah saltpan for salt production) on the lake. Investigations revealed that the rapid expansion of agricultural areas around the lake by 254% and the increase in salt production from the Al-Samawah saltpan by about 121% are among the direct causes of the drought. In addition, the results of the statistical test anal-ysis between the estimated surface water area of Sawa lake and human activities were significant at a 95% level of confidence. The findings of this study can assist decision-makers to understand the interaction be-tween human activities and the lake's environment to design a strategic plan for lake recovery and a sustain-able water resource management system in southern Iraq.

Dynamics of pollution and trophic status in selected sub-tropical surface water bodies in Haridwar district, India.

This study provides a detailed approach to evaluating water quality in the Haridwar district, Uttarakhand, India, by integrating physicochemical and microbiological investigations. It employs multivariate analysis and applies water quality and trophic state indices to evaluate the current state of the water and identify potential sources of contamination. The results from the correlation matrix highlight the dynamic interactions between different water quality parameters. Dissolved oxygen, total alkalinity, total suspended solids, biochemical oxygen demand, ammonium nitrogen, fecal coliform, pH, nitrate, and temperature exhibited varying temporal associations. Furthermore, principal component analysis (PCA) identified pH, temperature, and total alkalinity as key influencers across all seasons, while sewage pollution and agricultural runoff were recurring concerns. The enumeration of NSF WQI (National Sanitation Foundation Water Quality Index) (observed from 33.0 to 41.7) further affirmed consistently poor water quality and provided a quantitative metric for a comprehensive assessment. Trophic state index (ranged from 58.6 to 94.2) analysis indicated hyper-eutrophic conditions driven by nutrient concentrations in specific sites, which was further validated by phytoplankton analysis, which revealed the widespread occurrence of cyanobacteria in nearly all water bodies, signaling severe nutrient enrichment and the risk of potential eutrophication. Despite high nutrient levels causing pollution, the water in these water bodies consistently fell within the safe category for irrigation based on estimated sodium percentage, sodium adsorption ratio, and Wilcox diagram. However, it is not recommended to use these surface water bodies for irrigation due to the presence of high levels of organic pollution and a significant load of pathogenic bacteria.

Continuous Flow Electrocoagulation System for Enhanced Phosphorous Removal in Decentralized Wastewater Treatment Systems

Decentralized wastewater treatment systems (DWTS) are significant contributors to the eutrophication of surface water bodies due to a lack of treatment mechanisms that target dissolved phosphorus removal. Existing advanced treatment systems are expensive to operate, large in nature, and require frequent maintenance, making them unattractive to DWTS owners. This study aims to investigate the development of a continuous flow treatment system that uses electrocoagulation (EC) to remove dissolved phosphorus from small wastewater streams such as septic tank effluent (STE). Operational parameters, including system hydraulic retention time (HRT), applied current density, and wastewater composition, were optimized to maximize total phosphorus (TP) removal most cost-effectively. Using an HRT of 10 min, an applied current density of 2.0 mA/cm2, and an influent concentration of 20 mg/L, the orthophosphate (OP) and TP removal percentages achieved were 99.9 and 88.1%, respectively. Under these conditions, the average effluent Al3+ concentration in the treated effluent was measured to be 1.0 mg/L while the total suspended solids concentration was measured to be 51 mg/L. The operation cost was estimated to be 0.056 CAD/m3. The results demonstrate that the EC reactor is effective in removing dissolved phosphorus from wastewater and is therefore a viable option in mitigating the risk of downstream eutrophication caused by inadequately treated STE.

Dynamic coupling of qualitative–quantitative models for operation of water resources based on environmental criteria

Concerning issues include the distribution of scarce water resources, the quality of utilized water, environmental repercussions, and regulations for the sustainable use of water resources. In the management of water resources, optimal qualitative–quantitative exploitation of surface water bodies is regarded as a desirable strategy. The Dez River surface water system from the Dez regulatory dam to Band-e-Ghir is selected in the current paper to create a qualitative–quantitative model that can determine the best exploitation strategies. A dynamic linkage between qualitative and quantitative models is built in order to simulate the current exploitation conditions under the umbrella of the best-case scenario. In this coupled system, hydraulic relationships are established between all of the system’s components. The available data are shared between two models in this structure to simulate the qualitative and quantitative effects of surface water. Then, a new structure is produced to derive the best policies for exploiting the dam and the river by connecting the multi-objective particle swarm optimization algorithm with the qualitative–quantitative coupled model body. The monthly river environmental demand is one of the decision variables in the ideal scenario, and the goals include boosting the percentage of supply demands and minimizing the violation of quality standards. The best-case scenario’s implementation increases the likelihood that all plain demands will be met, regardless of priority. Furthermore, in comparison with the reference scenario, the results of the optimal scenario show that not only are the concentrations of contaminants and qualitative parameters increased, but there are also only minimal violations of the quality and pollution standards of the river water in the majority of river points, particularly in the locations of agricultural withdrawals. The findings demonstrate that using the qualitative–quantitative dynamic relationship between water resources and the development of the coupled model using the NSGA-II algorithm allows us to better plan for the appropriate use of existing water resources by taking into account all stakeholders in such a way that, in addition to meeting needs, maintains the river quality close to standard limits throughout the exploitation period. By using this strategy, users will be informed of the negative effects of their actions, as well as the encroachment on river boundaries and associated consequences.

New modeling framework for describing the effects of landscape pattern changes on nutrient pollution transport.

Landscape pattern plays a crucial role in regulating hydrological and pollutant migration processes. However, there is a lack of quantitative tools to describe the nutrient pollution transport process under the influence of different landscape patterns. To fill this gap, this study presents a new modeling framework, namely the Landscape Pattern-Source Flow Sink model (LP-SFS). The model consists of three modules: nutrient pollution emission, land transport, and river transport. Each module is implemented using a separate calculation program. It characterizes the transport path of pollutants on landscape units conceptually and operationally and focuses on quantifying the blocking effect of grid-scale landscape units on nutrients. The framework takes the Luanhe River Basin in the North China Plain as an exemplary case. The simulation results of the new framework indicated that in regions predominantly occupied by forest and urban (FU), the intensity of terrestrial pollutant migration attained the highest level. In the slope zone ranging from 25 to 35°, owing to the relatively strong responsiveness of water flow and gravity to the slope, soil erosion is inclined to occur, thereby causing the intensity of terrestrial nutrient pollution transport in this slope zone to reach the maximum value of 4.55kg/km2. Furthermore, in the elevation zone <700m, urban and cultivated land was concentratedly distributed, which leads to more pollutants entering surface water bodies and increases the intensity of terrestrial migration of pollutants. The complex boundary shape of forestland and grassland in the watershed weakened the transport capacity of nutrients, resulting in pollutants remaining in the soil and being difficult to be transported to surface water bodies. This new method is applicable to large-scale watersheds with strong spatial heterogeneity and severe landscape fragmentation and can provide technical support for nutrient pollution control and optimization of land resource allocation in large-scale watersheds.

On the flow behaviour of unconfined dual porosity aquifers with sloping base

The flow in an unconfined double-porosity aquifer with a sloping base is investigated and equations are developed for its description. In order to obtain a relatively simple description of the problem, similar assumptions as in Moutsopoulos (2021) have been adopted; the pressure in the unsaturated zone, especially in the fractures’ network, is considered to be atmospheric, and the Dupuit-Forchheimer approximation is invoked, reducing the dimensionality by eliminating the vertical direction. The derived equations have been linearized and solved analytically for a problem involving interaction between an inclined aquifer and an adjacent surface water body similar to the one examined by Akylas and Koussis (2007). The analytical solution has been checked against results obtained with state-of-the-art numerical codes. The agreement between the two approaches is excellent. The solution tools were used to gain insight in the influence of the aquifer's base inclination on the flow quantities.

POST PROCESSING OF PREDICTIONS TO IMPROVE THE QUALITY OF RECOGNITION OF WATER SURFACE OBJECTS

Context. The significance of this work stems from the growing need for UAV technologies integrated with artificial intelligence, aimed at detecting and identifying objects on the surface of water bodies. Modern needs in water body monitoring, especially in the context of environmental monitoring, protection and resource management, require accurate and reliable solutions. This work demonstrates methods for improving the performance of neural networks and offers approaches for processing NN predictions, even if they are trained on irrelevant data, which increases the versatility and efficiency of the technology. Objective. The goal of the work is to solve the problem of false recognition of objects on the surface of water bodies, which is due to a decrease in the accuracy threshold for the neural network. This provides more accurate and reliable detection, reducing the number of false positive predictions and increasing the efficiency of the system in general. Method. It is proposed to add a stage of post-processing of NN predictions, which inherits concepts of min-max suppression used by YOLO models. This algorithm suppresses the re-detection of the object by the network and relies on the cross-sectional area of the detected rectangles. It uses a threshold value of 0.8 for the two points of the rectangle, which can effectively reduce the number of re-predictions and improve the accuracy. Results. As a result of the implementation of the proposed algorithm and the script created on its basis, a result was achieved in which groups from several predictions are combined and filtered. The received data is stored in the database as found and detected objects. The proposed post-processing algorithm effectively removes redundant predictions while maintaining forecast accuracy. This ensures the reliability of the system and increases its performance in real conditions. Conclusions. Detected images of objects on the surface of water bodies are stored in the database in the form of records with unique file name identifiers. After tests with pre-taken images algorithm proved it`s persistence against data duplication scenarios. This increases the efficiency and reliability of the monitoring system, ensuring accurate and timely detection of objects on the surface of water bodies.

Water softening technologies for small and medium capacity systems

The current state of water resources is largely determined by human activities. The discharge of polluted waters into surface water bodies significantly reduces their quality and complicates direct usage. One of the main sources of increasing mineralization and hardness of surface waters is the discharge of spent regeneration solutions after ion-exchange softening, which creates a closed cycle of sodium, calcium, and magnesium chlorides. The need to reduce the intensity of this cycle and decrease environmental pollution has arisen long ago. Studying the standard soda-sodium softening method has shown its low suitability for systems with small and medium productivity due to the need for water heating and subsequent pH correction. Using phosphate anions as precipitants proved to be more effective, successfully removing calcium and magnesium ions over a wide range of temperatures and pH levels. Research has revealed that the formed solid phase in such treatment is poorly separated from the liquid. As one of the solutions to this problem, the use of anionic flocculants is proposed, which provide effective separation of the formed solid particles from the water. A technological scheme has been developed, which involves usage at the stage of preliminary water treatment for reverse osmosis systems with small and medium productivity.

Коррекция и усвоение данных гидрологических наблюдений температуры водных объектов

The paper proposes an algorithm for correcting the data of hydrological observations of water temperature and an algorithm for assimilating corrected data for calculations of water body surface temperatures in Russia. The temperatures are used in initial data for computing global medium-range weather forecasts with the new version of the SLAV10 model with a grid spacing of about 10 km. The correction algorithm for hydrological observations of water temperature makes it possible to eliminate ambiguity in temperature coding at most gauging stations. The assimilation of corrected hydrological observations allows reducing water body surface temperature errors in the SLAV10 model initial data as compared to specifying water temperature from the data of the nearest land points.

Recent Progress on Surface Water Quality Models Utilizing Machine Learning Techniques

Surface waterbodies are heavily exposed to pollutants caused by natural disasters and human activities. Empowering sensor technologies in water quality monitoring, sufficient measurements have become available to develop machine learning (ML) models. Numerous ML models have quickly been adopted to predict water quality indicators in various surface waterbodies. This paper reviews 78 recent articles from 2022 to October 2024, categorizing water quality models utilizing ML into three groups: Point-to-Point (P2P), which estimates the current target value based on other measurements at the same time point; Sequence-to-Point (S2P), which utilizes previous time series data to predict the target value at one time point ahead; and Sequence-to-Sequence (S2S), which uses previous time series data to forecast sequential target values in the future. The ML models used in each group are classified and compared according to water quality indicators, data availability, and model performance. Widely used strategies for improving performance, including feature engineering, hyperparameter tuning, and transfer learning, are recognized and described to enhance model effectiveness. The interpretability limitations of ML applications are discussed. This review provides a perspective on emerging ML for surface water quality models.

Analysis of domestic wastewater disinfection methods using chlorine dioxide and sodium hypochlorite

Pollution of surface water bodies poses a threat to the environment and human health. After improper wastewater treatment at municipal enterprises, mineral and organic pollutants gradually accumulate in water bodies, which in turn worsens the ecological situation and leads to outbreaks of infectious diseases. The reason for periodic violations of the operation of treatment plants is the imperfection of the technological regime. Therefore, there is an urgent need to improve the efficiency of existing biological treatment facilities by means of measures that ensure compliance with environmental requirements for urban wastewater treatment. Chlorine or its compounds are used as disinfectants: chlorine dioxide, sodium hypochlorite, calcium hypochlorite and others. Methods of wastewater disinfection using chlorine dioxide and sodium hypochlorite are considered in the work. The main advantages and problems of using these methods in comparison with the traditional use of chlorine are highlighted.

Analysis and Future Projections of Land Use and Land Cover Changes in the Hindon River Basin, India Using the CA-Markov Model

Land use and land cover change is a significant issue in emerging countries. The enormous rate of population growth, industrialization, and urbanization is responsible for these developments. Monitoring and mapping of changes in land cover and land use is essential to the sustainable development and management of the area. The study attempts to track changes in LULC pattern for the years 2002, 2013, and 2023 in the Hindon River Basin, a major tributary of the Yamuna River, using remote sensing and geographic information system techniques. Images obtained from Landsat data were employed to extract historical land use and land cover maps. Additionally, the CA-Markov model was implemented to forecast future land use and land cover patterns. This study examines the historical and predicted LULC in the area. Field observations and site-specific interviews were used to confirm and determine the ground realities. High-resolution images were used to evaluate the accuracy of the classified map. According to the results, the agricultural land decreased from 60.98% in 2002 to 54.70% in 2050, while built-up areas increased from 12.95% to 21.25% during the same period. By 2050, vegetation is predicted to increase to 2.58%, whereas surface water, fallow land, barren areas, and dry water bodies are predicted to decrease to 0.58%, 18.87%, 1.20%, and 0.83%, respectively. The rapid pace of urbanization is facilitating economic growth within the country; however, this development is occurring at the expense of the natural landscape, which subsequently diminishes the overall quality of human life. In order to maintain sustainable development in the Hindon Basin, proper urban planning is essential. Important policy implications for the sustainable management of land use and conservation in the Hindon River basin are highlighted by the study’s research and findings.

Link Quality Fluctuation in Wireless Networks Deployed on the Surface of Different Water Bodies

Link Quality Fluctuation in Wireless Networks Deployed on the Surface of Different Water Bodies

Comparing Global Violations of Environmentally Critical Groundwater Discharge Thresholds

AbstractGroundwater is a crucial resource to support surface water bodies via groundwater discharge. In this study, we applied two methods of estimating global environmentally critical groundwater discharge, defined as the flux of groundwater to streamflow necessary to maintain a healthy environment, from 1960 to 2010: the Presumptive Standard stipulates that a standard proportion of groundwater discharge should be maintained at all timesteps, while the Q* is a low‐flow index that focuses on critical periods. We calculated these critical flow thresholds using simulated natural groundwater discharge, and estimated violations of the thresholds when human‐impacted groundwater discharge dropped too low. Our global assessment of the frequency and severity of violations over all timesteps in our study period showed that the Presumptive Standard estimated more frequent and severe violations than the Q*, but that the spatial patterns were similar for both methods. During low‐flow periods, when the relative importance of groundwater to support streamflow is greatest, both methods estimated similar magnitudes of violation frequency and severity. We further compared our results to a method of estimating environmentally critical streamflow, Variable Monthly Flow, which does not explicitly consider groundwater. From the differences in violation frequency between these groundwater‐centric and surface water‐centric methods, we evaluated the influence of including groundwater contributions to streamflow in environmental flow assessments. Our results show that including groundwater in such assessments is particularly important for regions with high groundwater demands in the drier climates of the world, while it is less important for regions with low groundwater demands and more humid climates.

Groundwater flow system of the Abijata-Langano-Ziway lakes basin, Ethiopia

The Abijata-Langano-Ziway Lakes Basin (ALZLB) is situated in the Central part of the Main Ethiopian Rift. The availability and dynamics of groundwater in the Abijata-Langano-Ziway Lakes Basin (ALZLB) are primarily controlled by its geological and hydrogeological characteristics, shaped by volcanic-tectonic and sedimentary processes. The basin faces significant challenges, including drastic change in land use pattern, rapid population growth sustained by subsistence farming, over-extraction of water resources, and vulnerability to climate change and fragile ecosystems. These issues emphasize the urgent need for effective water resource management.To understand this complex system, a numerical groundwater flow model was employed to characterize the groundwater flow system within the ALZLB and examine its interaction with surface water bodies. The MODFLOW model translates the conceptual understanding of the basin's hydrogeology into a mathematical representation, allowing for numerical analysis. The model incorporates input parameters such as hydraulic conductivity and boundary conditions representing groundwater inflow and outflow. Steady-state numerical calculation was used to characterize the qualitative hydrogeological conceptual model into numerical representation and thereby describe the groundwater system.The calibrated model exhibited excellent agreement between simulated and observed groundwater levels. Statistical measures indicated a strong correlation (R2 = 0.98) and high efficiency (NSE = 0.97) in replicating the observed data. Additionally, the Mean Error (ME) of −8.3 m suggests minimal bias in the simulations. Further analysis of the histogram residuals revealed that a significant portion of the simulated values (65 % and 82 %) fell within ±20 m and ±30 m of the observed groundwater levels, respectively. This revealed the model's accuracy in capturing the groundwater system's behavior.The model identified groundwater recharge and constant head boundaries as the primary sources of groundwater inflow, contributing 445 million cubic meters per year (MCM/year) and 90 MCM/year, respectively. Conversely, constant head boundaries represented the most significant outflow pathway, with a simulated discharge of 519 MCM/year. The calibrated balance between inflow and outflow (discrepancy of −0.75 %) confirms that the model effectively simulates steady-state groundwater flow conditions. The calibrated model demonstrates the model's capability to accurately represent the basin's groundwater system.