Increased Storage Capacity Research Articles

Evaluating flue gas geo-sequestration and EOR in fractured reservoirs through simulated synergistic reservoir characteristics and injection kinetics

The global reliance on hydrocarbon resources and fossil fuels has resulted in a significant surge in carbon dioxide emissions, necessitating urgent measures to mitigate greenhouse gas emissions. Integrating CO2 storage with enhanced oil recovery (EOR) presents a promising solution for reducing emissions and enhancing oil recovery by sequestering CO2 within oil reservoirs, especially in fractured carbonate reservoirs. The research utilized the Eclipse simulator to model different gas injection scenarios in a crude oil reservoir, focusing on assessing the effectiveness of CO2 and flue gas geo-sequestration and EOR, performing sensitivity analyses on reservoir characteristics, and evaluating the impact of varying injection rates on gas storage capacity and oil recovery factor. The findings demonstrated a superior capacity to store flue gas (150 MMSCF) in comparison to CO2 (85 MMSCF) and flue gas injection demonstrated better reservoir pressure maintenance than CO2 injection, while CO2 injection resulted in a higher oil recovery factor of 52% compared to flue gas injection at 36%. Additionally, analysis of reservoir characteristics in gas storage revealed that, an augmentation in reservoir porosity, permeability, and injection rate substantiated an increase in gas storage capacity for both CO2 and flue gas injection. Except for CO2 storage, which displayed a normal distribution trend in the permeability analysis. Additionally, it was elucidated that higher reservoir pressure and temperature in flue gas injection resulted in a reduction of gas storage capacity, while these variables exhibited relative stability in the context of CO2 injection. The scrutiny of gas storage in reservoir characteristics unveiled substantial alterations in porosity and injection rate, signifying their pivotal roles in influencing gas storage capacity. In the EOR study, heightened reservoir pressure, temperature, permeability, and injection rate collectively contributed to an amplified oil recovery for both flue gas and CO2, except CO2 injection demonstrated a normal distribution trend in oil recovery within the permeability analysis. Conversely, higher porosity was associated with a decrease in oil recovery. The findings of this research provide valuable insights into the feasibility and effectiveness of employing flue gas geo-sequestration and EOR in fractured carbonate reservoirs.

Solid-state Hydrogen storage: influence of storage capacity in physisorption

Abstract Hydrogen storage in solid-state is a promising alternative to conventional technologies to overcome some of their limitations, particularly in terms of the amount of hydrogen stored per unit volume. For instance, liquid hydrogen (stored at 1 bar and 20 K) is characterized by a 70.8 kg/m3 volumetric density, but a great amount of energy is required for liquefaction (about 12.5 kWh/kg); whereas, hydrogen stored as compressed gas (350 - 700 bar) at ambient temperature reaches a density ranging from 24.5 to 41.4 kg/m3, however the compression work is significant, and the high storage pressure determines safety issues. Regarding solid-state hydrogen storage, chemisorption is a solution, where hydrogen is stored at moderate pressure and temperature, reaching a volumetric density of 80-110 kg/m3, but between hydrogen and metal hydrides chemical bonds born, which require a significant amount of energy to be break them; moreover, the time required for absorption and desorption is very low. In the context of solid-state storage, carbon materials can be an interesting solution due to their low cost, and their ability to store hydrogen reversibly within a porous structure through physisorption mechanisms, under supercritical conditions. This study numerically investigates the effect of the variation of the tank capacity on the charging, dormancy, and discharging processes. Two similar axi-symmetric geometries are considered by doubling the tank volume from V 1 = 2.5 L to V 2 = 5 L. The physisorption mechanism has been modeled according to the modified Dubinin-Astakhov isotherm model. Initially, the CFD model has been validated on V 1 tank against experimental results available in the literature. Then, simulations have been carried out on V 2 tank to estimate the effect of a storage capacity increase. The simulations on the V 2 tank have been set keeping the same boundary conditions in terms of velocity, density, and temperature at the inlet by doubling the overall amount of hydrogen stored with respect to V 1 tank. The results show corresponding trends in temperature and pressure profiles with only slight differences in their behaviors; in particular, in the final stage of the charging process.

Quantum Spin Exchange Interactions Trigger O p Band Broadening for Enhanced Aqueous Zinc-Ion Battery Performance.

The pressing demand for large-scale energy storage solutions has propelled the development of advanced battery technologies, among which zinc-ion batteries (ZIBs) are prominent due to their resource abundance, high capacity, and safety in aqueous environments. However, the use of manganese oxide cathodes in ZIBs is challenged by their poor electrical conductivity and structural stability, stemming from the intrinsic properties of MnO2 and the destabilizing effects of ion intercalation. To overcome these limitations, our research delves into atomic-level engineering, emphasizing quantum spin exchange interactions (QSEI). These essential for modifying electronic characteristics, can significantly influence material efficiency and functionality. We demonstrate through density functional theory (DFT) calculations that enhanced QSEI in manganese oxides broadens the O p band, narrows the band gap, and optimizes both proton adsorption and electron transport. Empirical evidence is provided through the synthesis of Ru-MnO2 nanosheets, which display a marked increase in energy storage capacity, achieving 314.4 mAh g-1 at 0.2 A g-1 and maintaining high capacity after 2000 cycles. Our findings underscore the potential of QSEI to enhance the performance of TMO cathodes in ZIBs, pointing to new avenues for advancing battery technology.

The Regulation of Temperature Fluctuations and Energy Consumption in Buildings Using Phase Change Material–Gypsum Boards in Summer

This study examined the thermal performance of Comfortboard23, a commercial gypsum board from Knauf infused with phase change material (PCM). Structural characterization using XRD and SEM confirmed the presence of microencapsulated PCM within the gypsum matrix. The study does not provide a direct comparison between Comfortboard23 and other PCM-integrated gypsum boards on the market. This is a limitation of the research. A comprehensive comparison would involve testing multiple products under identical conditions, and evaluating factors such as thermal performance, cost-effectiveness, durability, and ease of installation. Thermal characterization involved a novel low-scale thermal chamber to measure U-value, thermal conductivity, heat storage capacity, and dynamic thermal response. Results showed incorporating PCM decreased the U-value by 2% compared to standard gypsum boards. Additionally, PCM inclusion increased heat storage capacity by around 45% and improved dynamic thermal characteristics by decreasing thermal stability coefficient from 0.92 to 0.76 and increasing thermal lag from 0.27 to 0.49 h. The 45% increase in heat storage capacity of Comfortboard23 could lead to a 10–20% reduction in heating and cooling energy consumption, improved thermal comfort, and potential HVAC downsizing. Exact benefits depend on climate, building design, and occupancy patterns, necessitating further research in diverse real-world settings. The findings demonstrate Comfortboard23’s potential for enhancing thermal energy storage in buildings, contributing to energy savings, improved thermal comfort, and reduced temperature fluctuations across varying daily temperatures. Overall, the study highlights the promise of Comfortboard23 as an energy-efficient PCM-integrated building material.

All‐Electronic Memristor Based on Charge Carrier Confinement in Bulk Semiconductor of Metal–Semiconductor–Metal Structure

AbstractMemristors have gained significant attention in recent years due to their potential applications in computing and memory technology by offering higher performance, lower power consumption, and increased storage capacity. In this paper, a new type of volatile memristor is presented by analyzing the dynamic behavior of charge carriers within a metal–semiconductor–metal (MSM) structure. It is shown that an all‐electronic memristor is achieved through the confinement of majority charge carriers within the bulk semiconductor by the favor of high barrier Schottky contacts. The findings reveal a remarkable current offset between forward and backward scans, along with exceptional current pulse consistency with a tunable current level using pulse frequency. These characteristics greatly simplify the process of designing electrical circuits incorporating this memristor variant. Furthermore, this research paves the way for the development of crystalline semiconductor‐based memristors. While various semiconductors with controllable doping densities can be considered as potential candidates for this type of memristor, the calculations using silicon demonstrate the integration of this semiconductor with the current technology holds significant promise for two terminal memristors.

Suitability Assessment and Optimization of Small Dams and Reservoirs in Northern Ghana

Water shortages, exacerbated by erratic rainfall, climate change, and population growth, pose significant challenges globally, particularly in semi-arid regions like northern Ghana. Despite the construction of numerous small dams in the region that were intended to provide reliable water for domestic and irrigation purposes, critical water issues persist during dry periods. Key drivers in this failure are attributed to the lack of studies and/or the number of inadequate studies on suitable dam siting. This study focused on assessing the sites of selected small dams in northern Ghana, employing various methods such as stream order analysis and the Analytic Hierarchy Process within a Geographic Information System framework. Results showed that many existing dams are poorly sited, with over half located far from major stream networks, resulting in drying out during the dry season and failing to meet sustainable water storage standards. This study proposed new dam locations that would allow achieving a significant increase in storage capacities from 30% to 60%. These results highlight the necessity for decision-makers to adopt research-based approaches to address water shortages effectively, balancing agricultural, domestic, economic, and environmental needs. Future research should integrate climate change considerations, long-term monitoring, environmental impact assessments, and advanced decision-making techniques such as machine learning.

Optimizing Underground Natural Gas Storage Capacity through Numerical Modeling and Strategic Well Placement

This study focuses on optimizing the storage capacity of an underground natural gas storage facility through numerical modeling and simulation techniques. The reservoir, characterized by an elongated dome structure, was discretized into approximately 16,000 cells. Simulations were conducted using key parameters such as permeability (10–70 mD) and porosity (12–26%) to assess the dynamics of gas injection and pressure distribution. The model incorporated core and petrophysical data to accurately represent the reservoir’s behavior. By integrating new wells in areas with storage deficits, the model demonstrated improvements in storage efficiency and pressure uniformity. The introduction of additional wells led to a significant increase in storage volume from 380 to 512 million Sm³ and optimized the injection process by reducing the storage period by 25%. The study concludes that reservoir performance can be enhanced with targeted well placement and customized flow rates, resulting in both increased storage capacity and economic benefits.

Comprehensive Resilience Assessment Framework for Water Distribution Networks

A novel comprehensive resilience assessment framework for drinking water systems is proposed integrating different resilience perspectives (i.e., robustness, autonomy, flexibility, reliability, preparedness and recovery), oriented by objectives, criteria and metrics, applicable at the tactical level. The resilience assessment framework is applied to a Portuguese real water distribution network, enabling the evaluation of the system’s resilience. The infrastructure dimension is the main contributor to the low resilience results, particularly in terms of infrastructural robustness, as the infrastructure has exceeded the average service life and has low rehabilitation rates. In terms of autonomy, the system highly depends on external water and energy sources. Regarding the service dimension, most of the drinking water available is used for non-potable uses (e.g., irrigation), without alternative sources. The detailed diagnosis identified network area R6 as the priority area. Assets rehabilitation, increasing storage capacity, finding alternative water and energy sources, and minimizing non-potable uses are relevant improvement measures that promote the reinforcement of the system’s resilience. The resilience assessment framework is a very useful tool for the daily and tactical management of drinking water systems.

Research on origin-based cold storage location and routing optimization of fresh agricultural products based on hybrid whale algorithm

With the focus on the insufficient origin-based cold storage in China, this study investigates the location and routing problem (LRP) of origin-based cold storage for fresh agricultural products. This study considers the loss of fresh agricultural products in different environments during transportation and presents a cold storage LRP model. To address this issue, a hybrid whale algorithm with heuristic rules is designed, and the effectiveness of the algorithm is verified by standard instances. Finally, taking Chenggu County as a practical case, the influence of cold storage capacity and farmers’ demand for refrigeration are analysed. Experimental results show that the proposed algorithm has a good effect in solving medium-scale LRP. As the storage capacity increases, the total cost of the system can be increased by 0.086%. As farmers’ demand for refrigeration increases, the total cost of the system can be increased by 34.034%. Farmers’ demand has a greater impact on the system’s total costs than the cold storage capacity. When optimizing the cold storage layout, changes in fresh agricultural product output in the next few years can be roughly predicted, and the most economical optimization scheme can be obtained.

A Survey: Systems and Applications Based on Cloud Computing

mobile cloud computing is an emerging technology that combines the power of cloud computing with the ubiquity of smartphones. This technology enables smart devices to access cloud computing resources. It offers various advantages, such as increased storage capacity, improved processing power, extended battery life, higher storage spaces, and faster response times. Mobile cloud computing has the potential to revolutionize mobile computing by providing users with anytime, anywhere access to cloud-based services and applications. However, mobile cloud computing faces many challenges, such as security, privacy, and network issues. This paper presents an overview of mobile cloud computing, its benefits, and challenges. We employed a descriptive approach to collect data on various programs and systems that rely on cloud computing, including automated video surveillance systems, health applications, MISSION SWACHHTA, car sharing for delivery and parcel customers, banking applications and systems, e-commerce platforms, big data systems, e-learning systems, and logistic systems.

QRGB+: Advanced QR Code Generator with RGB Color Method in Python to Expand Data Capacity

The present work entitled QRGB, consists of the development of an application in Python for the generation of QR codes using the additive color generation (RGB) method. This innovative method allows increasing the density of information stored in QR codes by using three color layers (red, green and blue), each representing a different set of data. QRGB offers an efficient and secure solution for storing and transmitting large amounts of information in limited spaces, significantly improving the capabilities of traditional black and white QR codes. By using three layers of colors, QRGB codes can store up to three times more information in the same space. This technique not only increases storage capacity but also improves information security, making it difficult to forge or manipulate the code. The overlay of multiple data layers allows redundancy to be implemented, increasing the robustness of the code against damage or reading errors. QRGBs are especially useful in applications that require the transmission of large amounts of data in limited spaces, such as in the packaging industry, digital business cards, and interactive advertising. Additionally, they have great potential in areas such as document and banknote security, where the authenticity and integrity of information are crucial. These points provide a solid foundation for understanding the innovation and advantages of colored QR codes (QRGB) compared to traditional QR codes, highlighting their applicability and potential in various sectors. This article presents a novel method for encoding and decoding information using a QRGB code, which involves the generation of three independent QR codes and their superimposition according to the additive color system (RGB). The research highlights the challenges encountered during the encoding and decoding processes due to the lack of specific libraries in Python, which required the creation of a custom solution using open source tools. The implementation takes advantage of Python and its libraries: qrcode[pil] to generate QR codes with the Pillow dependency for image manipulation, Pillow to open, manipulate and save different image formats, and opencv-python to perform tasks such as image processing and object detection. Despite facing issues with color mixing and accurate information retrieval, the proposed method demonstrates a significant increase in data density within a single QR code. Future work will focus on optimizing the algorithm and exploring potential applications in data security and high-density information storage. This Python script is designed to generate and decode QR codes with a logo overlay using a graphical user interface (GUI) built with Tkinter. The script combines several functionalities, such as creating QR codes, overlaying a logo, combining QR images of different colors, and manually decoding combined QR codes.

Multi-Load Topology Optimization Design for the Structural Safety Maintenance of Low- and Intermediate-Level Radioactive Waste Packaging Containers in the Case of a Collision.

This paper presents an optimized design approach using nonlinear dynamic analysis and finite element methods to ensure the structural integrity of square-shaped containers made from ductile cast iron for intermediate- and low-level radioactive waste packaging. Ductile cast iron, with its spherical graphite structure, effectively distributes stress throughout the material, leading to a storage capacity increase of approximately 18%. Considering the critical need for containers that maintain integrity under extreme conditions like earthquakes, the design focuses on mitigating stress concentrations at the corners of square structures. Nonlinear dynamic analyses were conducted in five drop directions: three specified by ASTM-D5276 standards and two additional directions to account for different load patterns. Fractures were observed in four out of the five scenarios. For each direction where fractures occurred, equivalent loads causing similar displacement fields were applied to linear static models, which were then used for multi-load topology optimization. Three optimized models were derived, each increasing the volume by 1.4% to 1.6% compared to the original model, and the design that best met the structural integrity requirements during drop scenarios was selected. To further enhance the optimization process, weights were assigned to different load conditions based on numerical analysis results, balancing the impact of maximum stress, average stress, and plastic deformation energy. The final model, with its increased storage capacity and enhanced structural integrity, offers a practical solution for radioactive waste management, overcoming limitations in previous designs by effectively addressing complex load conditions.

Hydrogen Storage Properties of Metal-Modified Graphene Materials

The absence of adequate methods for hydrogen storage has prevented the implementation of hydrogen as a major source of energy. Graphene-based materials have been considered for use as solid hydrogen storage, because of graphene’s high specific surface area. However, these materials alone do not meet the hydrogen storage standard of 6.5 wt.% set by the United States Department of Energy (DOE). They can, however, be easily modified through either decoration or doping to alter their chemical properties and increase their hydrogen storage capacity. This review is a compilation of various published reports on this topic and summarizes results from theoretical and experimental studies that explore the hydrogen storage properties of metal-modified graphene materials. The efficacy of alkali, alkaline earth metal, and transition metal decoration is examined. In addition, metal doping to further increase storage capacity is considered. Methods for hydrogen storage capacity measurements are later explained and the properties of an effective hydrogen storage material are summarized.

Flooding and flood water storage in karst systems of the Mediterranean region

Flooding is a recurring natural phenomenon that can have both life-giving and destructive aspects. In natural environments, floods are often an important element of the seasonal hydrologic cycle that provides water and nutrients to soil, supporting unique, rich and diverse ecosystems. However, flood events can also represent a destructive force that can endanger lives and cause significant damage in urban areas. Karst areas, in particular, are unique because of their special hydraulic characteristics in terms of flood occurrence, the dependence of ecosystems on such events, and attempts to actively store and manage floods. In this article, the hydraulic response of karst aquifers to heavy precipitation events, flood generation, and engineering interventions for flood control are discussed using several examples from karst areas in the Mediterranean region. Flooding mechanisms and regulatory structures in karst poljes are considered using several typical examples from the Dinaric mountain range. In addition, different variants of groundwater abstraction for increasing storage capacity and flood control are presented using examples from France and Montenegro. Managed aquifer recharge in karst areas and adjacent aquifers is demonstrated with examples from Jordan and Algeria. Finally, failed attempts at flood storage in karst reservoirs are presented with examples from Spain and Montenegro. These examples of flood retention in karst areas show the wide range of planning and technical measures and remind us of possible risks and failures in implementation as well as some positive and negative impacts on the environment and especially on ecosystems.

Resource allocation for content distribution in IoT edge cloud computing environments using deep reinforcement learning

This study presents a novel approach to optimize resource allocation, aiming to boost the efficiency of content distribution in Internet of Things (IoT) edge cloud computing environments. The proposed method termed the Caching-based Deep Q-Network (CbDQN) framework, dynamically allocates computational and storage resources across edge devices and cloud servers. Despite its need for increased storage capacity, the high cost of edge computing, and the inherent limitations of wireless networks connecting edge devices, the CbDQN strategy addresses these challenges. By considering constraints such as limited bandwidth and potential latency issues, it ensures efficient data transfer without compromising performance. The method focuses on mitigating inefficient resource usage, particularly crucial in cloud-based edge computing environments where resource costs are usage-based. To overcome these issues, the CbDQN method efficiently distributes limited resources, optimizing efficiency, minimizing costs, and enhancing overall performance. The approach improves content delivery, reduces latency, and minimizes network congestion. The simulation results substantiate the efficacy of the suggested method in optimizing resource utilization and enhancing system performance, showcasing its potential to address challenges associated with content spreading in IoT edge cloud calculating situations. Our proposed approach evaluated metrics achieves high values of Accuracy is 99.85%, Precision at 99.85%, specificity is 99.82%, sensitivity is 99.82%, F-score is 99.82% and AUC is 99.82%.

Post-harvest losses in marine fisheries of Bangladesh

Existing literature highlights significant income loss due to Post-Harvest Loss (PHL) across the fisheries value chain in developing countries like Bangladesh. This is attributed to inappropriate fishing tools, poor infrastructure, inadequate storage facilities, and inefficient transportation. This study estimated PHL and its determinants in Bangladesh's marine fisheries using the Questionnaire Loss Assessment Method (QLAM) based on data collected from 1132 respondents, including fishermen and traders, from October 2019 to March 2021. The results reveal that physical, market, and monetary PHL in marine fisheries are 0.82 %, 6.41 %, and $228.52 per ton, respectively. Annually, the country loses approximately $151 million due to PHL in marine fisheries, with the highest market losses in Snapper, Pomfret, and Hilsa fish. The main reasons for PHL include the duration of fish remain in the net after being caught, insufficient ice, lack of insulated containers and storage facilities, delayed marketing, and oversupply. The study suggests adopting modern harvesting technology, enforcing regulations for scientific gear, and increasing storage capacity at landing and selling points to reduce PHL in marine fisheries.

Numerical study of an energy storage unit based on zeolite-water adsorption for mobilized thermal energy storage

Mobile energy storage heating trucks present a promising solution to address current challenges associated with low energy utilization and reliance on a singular heat supply method. This technology seamlessly integrates waste heat recovery and thermal energy utilization, offering potential advantages such as streamlining construction cycles and providing timely energy supply in scenarios with diverse energy demands. To enhance the energy delivery efficiency of mobile heating, this paper employs computational fluid dynamics (CFD) simulation to thoroughly examine the heat accumulator at the core of an adsorption-based mobilized thermal energy storage. Furthermore, the paper conducts simulations and analyses of heat and mass transfer within a zeolite-water accumulator, closely scrutinizing variations in temperature, vapor content, and water content within the zeolite field. The results indicate that, during the heat storage process in the 3 m/s to 5 m/s system, the zeolite sensible heat storage capacity increases by 6.48 %, accompanied by a reduction in latent heat. Specifically, when the inlet steam velocity is 5 m/s compared to 3 m/s, the equilibrium heat transfer time shortens by 24.6 %. Furthermore, for an inlet steam temperature ranging from 180 °C to 220 °C, the average temperature can be elevated by 28.8 °C, resulting in a 10.6 % increase in sensible heat storage capacity. However, the heat storage time experiences a 3.4 % increase. In the exothermic process, with an inlet air velocity of 5 m/s compared to 3 m/s, there is a 22.2 % reduction in latent heat exothermic and a 16.7 % reduction in exothermic time. The inlet air temperature during the exothermic process is 8.9 °C lower than the final temperature of 20 °C, leading to a 3.2 % increase in exothermic quantity and a 20 % improvement in exothermic efficiency.

Spin Symmetry Breaking-Induced Hubbard Gap Near-Closure in N-Coordinated MnO2 for Enhanced Aqueous Zinc-Ion Battery Performance.

Transition metal oxides (TMOs) are promising cathode materials for aqueous zinc ion batteries (ZIBs), however, their performance is hindered by a substantial Hubbard gap, which limits electron transfer and battery cyclability. Addressing this, we introduce a heteroatom coordination approach, using triethanolamine to induce axial N coordination on Mn centers in MnO2, yielding N-coordinated MnO2 (TEAMO). This approach leverages the change of electronegativity disparity between Mn and ligands (O and N) to disrupt spin symmetry and augment spin polarization. This enhancement leads to the closure of the Hubbard gap, primarily driven by the intensified occupancy of the Mn eg orbitals. The resultant TEAMO exhibit a significant increase in storage capacity, reaching 351 mAh g-1 at 0.1 A g-1. Our findings suggest a viable strategy for optimizing the electronic structure of TMO cathodes, enhancing the potential of ZIBs in energy storage technology.

Spin Symmetry Breaking‐Induced Hubbard Gap Near‐Closure in N‐Coordinated MnO2 for Enhanced Aqueous Zinc‐Ion Battery Performance

AbstractTransition metal oxides (TMOs) are promising cathode materials for aqueous zinc ion batteries (ZIBs), however, their performance is hindered by a substantial Hubbard gap, which limits electron transfer and battery cyclability. Addressing this, we introduce a heteroatom coordination approach, using triethanolamine to induce axial N coordination on Mn centers in MnO2, yielding N‐coordinated MnO2 (TEAMO). This approach leverages the change of electronegativity disparity between Mn and ligands (O and N) to disrupt spin symmetry and augment spin polarization. This enhancement leads to the closure of the Hubbard gap, primarily driven by the intensified occupancy of the Mn eg orbitals. The resultant TEAMO exhibit a significant increase in storage capacity, reaching 351 mAh g−1 at 0.1 A g−1. Our findings suggest a viable strategy for optimizing the electronic structure of TMO cathodes, enhancing the potential of ZIBs in energy storage technology.

Evaluation of ecosystem services vis-à-vis perceptions and attitudes of local communities towards Wetland conservation in Kashmir Himalaya

Valuation of ecosystem services along with the perceptions and attitudes of local communities is crucial for sustainable management of wetlands. This study assesses changes in wetland area and bathymetry, and provides insights into local community's perceptions of ecosystem services, and attitudes towards wetland conservation in Kashmir Himalaya, India. High-resolution satellite data was used to assess land use land cover (LULC) changes within the wetland. The bathymetry changes were assessed by performing depth measurements before and after dredging in 2019 and 2022, respectively. Perceptions of ecosystem services and attitudes of residents towards wetland management were examined through surveys in 182 households from the target population of 334 families. The findings reveal that Khushalsar wetland provides important provisioning (food, fodder, thatching mats, fish, vegetables), regulating (flood control, carbon sequestration, water quality improvement), supporting (habitat, biomass and oxygen production, water and nutrient cycling), and cultural services (aesthetic, education, spiritual). The economic benefits from provisioning services range from 240 USD/yr for minor vegetables to 1201–1802 USD/0.05 ha/yr for Nelumbo nucifera. The analysis of LULC changes indicates a ∼16.5% reduction in wetland area from 1980 to 2017, with a further ∼10% decrease from 2017 to 2021, resulting in an overall loss of ∼25% (27.1 ha) in wetland area from 1980 to 2021. Bathymetric assessments reveal an increase in maximum depth from 427 cm in 2019 to 547 cm in 2022 following dredging activities. Socioeconomic analysis showed the significance of Khushalsar wetland as an important source of livelihood for local communities. Survey results indicate that all the respondents have positive attitudes towards the protection and management of the Khushalsar wetland. The study demonstrates that human conservation activities have significantly contributed to positive changes in the wetland such as increase in depth and flood storage capacity. The study concludes that government protection along with active participation of local communities is indispensable for sustainable management of wetlands.