Increasing Water Demand Research Articles

Review of water treatment methods with a focus on energy consumption

Water and energy are substantial mediums which allow to gain comfort and civilization development. Recently, humanity is facing a water scarcity problem as well as an energy crisis. Those factors forced to looking for alternative water sources and low energy solutions. In this paper water treatment technologies methods were described. Energy demand and cost of particular methods were analyzed. It was shown that conventional methods like coagulation and sedimentation are characterized by quite low energy demand. Whereas more advanced membrane techniques consumed much more energy. On the other hand they were able to obtain high removal efficiencies. It was noted that the most energy-intensive stage during water treatment was pumping. Whereas energy for performing purification stated only about a few percent of total energy demand. One of the newest approaches in water treatment is using renewable energy sources like wind, solar radiation or geothermal energy. It allows to decrease water treatment costs as well as reduces greenhouse gasses emission (expressed as carbon footprint). During designing water treatment plants water increase in water and energy demand supposed to be considered.

Analysis of the possibility of energy self-sufficiency of water pumping stations with the use of PV installations

The research aimed to check the possibility of achieving energy self-sufficiency in the water pumping station by implementing a photovoltaic installation. The research included field tests of pressure and flow in the water supply network along with hydrant tests, measurements of the pumping station's demand for electricity related to pumping water, and the amount of electricity produced from the tested PV installation. The collected data was used to develop a mathematical model of the water supply network, its calibration, and the implementation of water supply network development scenarios, including an increase in water demand. Work simulations of various variants of PV installation power were performed: 12.3 kW, 15.0 kW, 30.0 kW, and 40.0 kW. Tests and simulations have shown that in the tested facility it will not be possible to achieve energy self-sufficiency of the water pumping station of the PV micro-installation (i.e. up to 40.0 kW) throughout the year. Depending on the power of the PV installation, the pumping station will achieve self-sufficiency with the current water demand from 6 to 7 months, and in the scenarios of expanding the water supply network, it will achieve energy self-sufficiency from 4 to 7 months.

Framework for Assessing Collective Irrigation Systems Resilience to Climate Change—The Maiorga Case Study

In order to increase water productivity at the Collective Irrigation System (CIS) level it is crucial to adapt the existing irrigation infrastructure, enhancing water intake at the source, as well as its transport and delivery efficiency. Rehabilitation may involve structural changes and thus, a large capital investment. This investment should be proportionate to the increase in climate resilience associated to different rehabilitation alternatives. A methodology framework was developed to evaluate CIS resilience to climate change considering different rehabilitation alternatives. The assessed components were: (i) crop production systems; (ii) on-farm irrigation systems; and (iii) project rehabilitation alternatives for the conveyance and distribution of the irrigation water from the source to the farmer fields. This framework was applied to the Maiorga CIS, in central Portugal, to test the methodology performance in assessing the impacts of climate change on the supply-demand balance of the proposed rehabilitation alternatives and to evaluate their climate resilience, for the representative concentration pathways, RCP4.5 and RCP8.5, and two time periods, 2041–2070 and 2071–2100. For each scenario, period, and rehabilitation alternative, irrigation requirements at the source (demand) and stream flows (supply) were computed and the supply-demand balance was performed. Projected increases in irrigation water demand varied between 5.5% for RCP4.5/2071–2100 and 35.7% for RCP8.5/2071–2100. For RCP4.5, 11% (2050) and 9% (2080) reductions in irrigation water supply were projected, while for RCP8.5 the reduction ranges between 13% (2050) and 30% (2080). The proposed framework determined that the rehabilitation alternatives considering just one type of water source, without flow regularization and with open channel distribution to the farmer’s field, have proved to be unviable due to low resilience to climate change.

Modeling impacts of projected land use and climate changes on the water balance in the Baro basin, Ethiopia

In terms of land use and climate, the world is changing at an unprecedented rate and these changes have a significant influence on our water resources. This study was conducted to examine the individual and combined potential impacts of land use and climate change on the water balance of the Baro basin in Ethiopia for the baseline period (1985–2002) and near-future period (2023–2040) using the Soil and Water Assessment Tool (SWAT). The plausible land use scenarios considering current (CUR), business as usual (BAU), and further expansion of altitudinal forest and watershed management practices (CON), as well as climate change scenarios from regional climate model outputs (RCMs) under two representative concentration pathways (RCP4.5 and RCP8.5) for the 2023–2040 time frame, were used as inputs to the models. The monthly calibrated and validated SWAT model produced an acceptable result, which was then used for water balance simulations. Findings show that forest decreased from 54.5% to 48.9% and 41.2% while agricultural land increased from 21.8% to 29.7% and 39.8% under the CUR and BAU land use change scenarios, respectively. The results from the ensemble mean showed an increase in maximum and minimum temperatures and a decrease in rainfall under the RCP4.5 and RCP8.5 climate change scenarios, which in turn resulted in an increase in evapotranspiration (ET) and a decrease in water availability. Climate change outweighed the impact of land-use change, thus indicating an increase in annual ET by up to 12% and a decrease of 42% in surface runoff (SURQ) under the RCP8.5 scenario. The BAU land use scenario projection triggers a respective increase of 18% in annual SURQ and reduction of ET by 2%. However, under the CON land use scenario, SURQ decreased by 24%. The study concluded that future land use and climate change will further challenge the basin's water supply capacity to meet the increased water demand. Understanding the changes in the basin's water balance is critical for mitigation and adaptation options. As a result, this study proposes restoration efforts and climate-resilient water management strategies that can increase the resilience of the river basin.

Water-energy-carbon emissions nexus analysis of crop production in the Tarim river basin, Northwest China

The water-energy-carbon emissions (WEC) nexus plays an important role in the sustainable production of crops. Changes to cropping patterns, along with an increase in water and energy demand and rising pressure to reduce carbon emissions, are severely challenging the WEC nexus in the Tarim River Basin (TRB). This study establishes the WEC nexus framework in crop production by analyzing spatio-temporal variations in key indicator trends using the footprint and nexus approach. The study also evaluates the coupling coordination development level of the WEC system based on the coupling coordination degree model. The results reveal the following: (1) The TRB is dominated by blue water irrigation resources, which account for 90% of total water consumption (AWC). There was an overall trend of increasing energy inputs per hectare for major crops in the TRB during 1990–2019. In particular, the energy input per hectare in Bayingol increased significantly and reached the highest level in 2016, at 4.39 × 104 MJ ha−1. Meanwhile, carbon footprint (CF) exhibited obvious spatial differences at the basin scale. Kizilsu Kirghiz had the lowest average CF, at 0.79 kg CO2_eq·kg−1. (2) The coupling degree of the WEC system in the study area is greater than 0.8, maintaining high-level coupling. The coupling coordination degree of Kizilsu Kirghiz had a clear upward trend and was stable at high levels during 2009–2019. (3) Cropping patterns are an important factor affecting the coupling coordination development of the WEC system. Strengthening connections among various sectors and improving energy utilization efficiency are critical actions to promote the low-carbon transition of crop production. This study provides the latest reference for realizing the coordinated development of the WEC system in the TRB.

Modeling and Forecasting of nanoFeCu Treated Sewage Quality Using Recurrent Neural Network (RNN)

Rapid industrialization and population growth cause severe water pollution and increased water demand. The use of FeCu nanoparticles (nanoFeCu) in treating sewage has been proven to be a space-efficient method. The objective of this work is to develop a recurrent neural network (RNN) model to estimate the performance of immobilized nanoFeCu in sewage treatment, thereby easing the monitoring and forecasting of sewage quality. In this work, sewage data was collected from a local sewage treatment plant. pH, nitrate, nitrite, and ammonia were used as the inputs. One-to-one and three-to-three RNN architectures were developed, optimized, and analyzed. The result showed that the one-to-one model predicted all four inputs with good accuracy, where R2 was found within a range of 0.87 to 0.98. However, the stability of the one-to-one model was not as good as the three-to-three model, as the inputs were chemically and statistically correlated in the later model. The best three-to-three model was developed by a single layer with 10 neurons and an average R2 of 0.91. In conclusion, this research provides data support for designing the neural network prediction model for sewage and provides positive significance for the exploration of smart sewage treatment plants.

Collective dynamics analysis based on the multiplex network method to unravel the backbone of fluctuations in groundwater level data

Collective behavior of groundwater level (GWL) in the Tabriz plain, northwest Iran, was modeled in the framework of complex networks. The GWL is considerably influenced by the lack of recharge due to drought in recent years and the increasing water demand of the industrial city of Tabriz. In this order, convergent cross-mapping (CCM) method was utilized to infer the causal relations by adopting a robust statistical approach based on hypothesis testing. Reconstructing structure is a challenge in network-based approaches to capture the dynamical variability of the measurements.This study aims to construct functional connectivity for a better understanding of informational flows among the wells. Multiplex network (MUX) was used as a set of coupled networks through interconnected layers to structure the information obtained from collective dynamics and time-reversal. The proposed procedure was evaluated by performing a systematic analysis of random network (RN) as a well-known model to consider the topological characteristics. The influence of connectivity reconstruction on network topology was also investigated by the generated experiments for different numbers of the dynamical units and lengths of the simulations at each unit. The MUX was constructed from the GWL for monthly observations over 15 years (2001–2017). Afterwards, the time-series was divided into three categories to infer the network connections in different time periods for various sets of the monitoring wells.The analysis indicates that unphysical connections are reduced by increasing the number of the coupling units as a desirable feature for detecting the underlying connectivity. The MUX is employed with the proposed statistical approach to quantitatively unravel the backbone of fluctuations in the GWL whose indirect causal relations form the skeleton. The MUX dynamics efficiently determines the underlying processes and identifies spatio-temporal patterns of the GWL fluctuations in two layers of the constructed networks.

Recent innovation and impacts of nano-based technologies for wastewater treatment on humans: a review

Sustainable wastewater management requires environment-friendly, efficient, and cost-effective methods of water treatment. The ever-growing list of emerging contaminants in municipal wastewater requires advanced, efficient, and cost-effective techniques for its treatment to combat the increasing water demand. The nano-based technologies hold great potential in improving water treatment efficiency and augmenting the water supply. However, the environmental effects of these technologies are still questionable among the public and scientific community. The present review discusses risks to human health due to the use of nano-based technology for the removal of emerging contaminants in water. The discussion will be about the impacts of these technologies on humans. Recommendations about safe and environmentally friendly options for nano-based technology for water treatment have been included. Safest options of nano-based technologies for water treatment and steps to minimize the risk associated with them have also been incorporated in this article. Since all biological systems are different, separate risk analyses should be performed at the environmentally relevant concentration for different durations. There is little/no information on the quantitative impact on humans and requires more understanding. The quantitative measurement of the cellular uptake of nanoparticles is usually difficult. We hope this article will serve its purpose for water researchers, medical researchers, environmentalists, policymakers, and the government.

Determination of Environmental Flows in Data-Poor Estuaries—Wami River Estuary in Saadani National Park, Tanzania

Land use changes and mounting water demands reduce freshwater inflows into estuaries, impairing estuarine ecosystems and accelerating coastal seawater intrusion. However, determining minimum river inflows for management guidelines is hampered by a lack of ecosystem-flow link data. This study describes the development of freshwater inflow guidelines for the Wami Estuary, combining scarce river flow data, hydrological modeling, inferring natural salinity regime from vegetation zonation and investigating freshwater requirements of people/wildlife. By adopting the Building Blocks Methodology, a detailed Environmental Flows Assessment was performed to know the minimum water depth/quality seasonal requirements for vegetation, terrestrial/aquatic wildlife and human communities. Water depth requirements were assessed for drought and normal rainfall years; corresponding discharges were obtained by a hydrological model (HEC-RAS) developed for the river channel upstream of estuary. Recommended flows were well within historically occurring flows. However, given the rapidly increasing water demand coupled with reduction in basin water storage due to deforestation/wetland loss, it is critical to ensure these minimum flows are present, without which essential ecosystem services (fisheries, water quality, mangrove forest resources and wildlife/tourism) will be jeopardized. The EFA process is described in painstaking detail to provide a reference for undertaking similar studies in data-poor regions worldwide.

Controls and rates of evaporation from a water supply reservoir in the Colorado Front Range

Evaporation can be a major component of a reservoir’s water balance in arid, populated regions such as the western United States, yet accurate measurements are scarce. In an effort to fill this observation gap, direct measurements of evaporation from Standley Lake, a water supply reservoir in the Colorado Front Range, were collected via the eddy covariance method from March 1, 2020 through February 28, 2021. Evaporation followed a seasonal pattern, with the spring, summer, and early fall experiencing daily cycles that peaked just after midday, with measurable evaporation occurring each day for approximately 4–6 h. In the late fall and winter, the daily cycles decayed and episodic enhancements in evaporation were common, most often lasting between 18 and 36 h, some longer. Evaporation peaked in June, aligning with peak net radiation, and summertime evaporation was predominantly driven by diurnal variations in wind speed and the vapor pressure gradient. Interestingly, fall and winter saw multiple periods of negative (downward) sensible heat transfer which helped drive wintertime evaporation. The study period evaporation totaled 1377 mm, with 35 % of that occurring in summer, 27 % in fall, 21 % in spring, and 17 % in winter. This study shows that evaporation is a significant part of the energy balance of Standley Lake, and with continued observations, enables a better understanding of the impacts a changing climate and increased water demands have on water resources.

Collaborative Watershed Modeling as Stakeholder Engagement Tool for Science-Based Water Policy Assessment in São Paulo, Brazil

This study describes a collaborative modeling process deployed at the Cantareira Water Supply System (CWSS) in São Paulo City Metropolitan Area, Brazil. The CWSS faces challenges for meeting the increasing water demand, while land-use and climate change and their combined effect on its water cycle and balance have created a complex water resources management problem. Through a stakeholder engagement process—involving scientists and policymakers, the water utility company, and state administration—environmental simulation models were developed to elicit and represent multiple environmental, economic, and policy perspectives, developing a mutual language to communicate and establish common goals of water resources management. Study outputs include estimation of biophysical and economic benefits associated with prioritized native vegetation restoration activities in the source watersheds. These outputs are deployed in support of landscape planning and the decision process integrating multiple stakeholder perspectives in São Paulo state administration, the water utility company, and municipalities.

Groundwater Investigation Using Electrical Resistivity Method at New Borg El-Arab City, Alexandria, Egypt

New Borg El-Arab is a city located on the northwestern coast of Egypt, where the increasing anthropogenic activities have led to an increase in water demand. Groundwater is the main source of water in this area, but it is seriously affected by the Mediterranean saltwater intrusion. This causes a substantial impact on the water quality of the coastal aquifer. In this study, the electrical resistivity method was applied to delineate the shallow groundwater aquifer and its quality. Twenty vertical electrical soundings (VES) distributed along 6 profiles were measured. To observe the seasonal groundwater variations, 14 VES points were measured at the end of the rainy season, while the measurements of 6 VES points were repeated at the end of the dry season. The results revealed 4 geoelectrical layers; the first layer is a surface dry zone with variable resistivity values, followed by a water-bearing layer; while the third is a limestone layer, followed by a clay deposits zone. In comparison to the winter season, the water-bearing layer records lower resistivity values at the end of summer. Optimal locations to drill new groundwater wells have also been determined with a depth varying from 1.8 m north to about 30 m south.

Water Scarcity Risk Index: A Tool for Strategic Drought Risk Management

Drought events have affected many regions of the world, having negative economic, environmental and social impacts. When accompanied by increasing water demands, these events can lead to water scarcity. Since droughts can significantly vary in each geographic area, several indices have been developed around the world. Hazard indexes are commonly used to predict meteorological, agricultural and hydrological droughts. These indexes intend to predict hazards, but they do not provide information on when and where deficits can have negative consequences. This study presents a new planning and decision-support tool for monitoring water scarcity situations in a given region. This tool, called the Water Scarcity Risk Index (W-ScaRI), is formed by two subindices, which are proposed to describe a hazard and its consequences. Each subindex was constructed using a group of indicators and indices selected from the technical literature or originally proposed in this work. The W-ScaRI was applied to the Rio de Janeiro Metropolitan Region (RJMR), supplied with water by the Guandu/Lajes/Acari system. The RJMR is one of the most densely populated regions in Brazil, located in an area that has no natural water bodies capable of meeting its supply needs. Therefore, the Guandu River, which, in fact, is formed by two discharge transpositions from the Paraíba do Sul River, is the main drinking water supply source for this region. The RJMR suffered the consequences of unexpected, prolonged droughts in the Southeast region in 2003 and 2014–2015, leading the local authorities to implement temporary emergency measures in the management system of Paraíba do Sul and Guandu Basins, avoiding water shortage but showing the urgent need for planning and management support tools to anticipate possible future problems. The results of the study show that the formulation of the W-ScaRI can represent the water scarcity risk in a relatively simple way and, at the same time, with adequate conceptual and methodological consistency.

APPLYING THE QUALITY AND POLLUTION INDICES FOR EVALUATING THE WASTEWATER EFFLUENT QUALITY OF KUFRANJA WASTEWATER TREATMENT PLANT, JORDAN

In Jordan, reclaimed wastewater has become a significant component of water resources due to acute water scarcity and increased water demand for different purposes. The vast majority of the reclaimed wastewater is used for restricted and unrestricted agriculture, with agriculture being one of the main economic activities in the country. The purpose of this study is to assess the quality of the wastewater effluent from the Kufranja Wastewater Treatment Plant (WWTP) and its suitability for irrigation and discharge into streams, wadis, or water bodies using the water quality index (WQI) and the water pollution index (WPI). The WQI and WPI were calculated using 15 physiochemical and biological parameters in total. The results of WQI and WPI based on the Jordanian standards for the reuse of reclaimed wastewater showed that the wastewater effluent of Kufranja WWTP falls within the category of "good quality" for the irrigation of industrial crops, field crops, and forest trees, while it falls within the category of "unsuitable quality or highly polluted water" for other irrigation uses. Moreover, the Kufranja WWTP effluent is of "unsuitable quality or highly polluted water" for discharging into streams, wadis, or water bodies. The findings from this study show that the Kufranja WWTP performed well during the year of study, where the average removal efficiency (EFF%) for BOD5, COD, and TSS was 95.1%, 95.6%, and 96.0%, respectively. The WQI results in this study revealed that E. coli has the greatest contribution to the WQI values, followed by PO43-, pH, and SAR, implying that the previous parameters are to blame for the deterioration of the effluent quality of the Kufranja WWTP and its inappropriateness for most uses. Therefore, further advanced treatments are required to reduce the loading of these parameters.

Evaluation of the quality indicators of collector-drainage water for reusing purposes: a study from Sirdarya province, Uzbekistan

Currently, in the countries of the Aral Sea basin, due to the negative effects of climate change and the unreasonable use of water resources, the reduction and pollution of existing water resources, the increase in demand for water and its protection are required. Due to the increase in the amount of mineralization due to the discharge of the mineralized collector-drainage waters formed in the irrigated areas to the rivers, their use is limited due to the pollution of the upper and lower streams of the river basins. Researches revealed that the mineralization of Central Mirzachol drainage water has increased by 3.5 times, the total hardness has increased by 4 times, the amount of cation and anion and heavy metals is also high. It was found that the quality of the water of the Central Mirzachol drainage is the worst, and the water of the Boyovut well has a relatively good quality indicator. As a result of the discharge of collector-drainage waters to the Syr Darya River, the main water source of the province, the total hardness of the river reaches 2.0 times, the mineralization is 1.2 times, the amount of cations potassium, sodium, calcium and magnesium, the amount of sulfates and chlorides from anions, heavy metals: manganese, caused the amount of zinc, tin, copper to exceed the permitted standards.

Monitoring and modelling of water quality parameters using artificial intelligence

Rapid population growth leads to an increase in demand for water and spikes levels of water pollution. In this study, a low cost and innovative internet of things (IoT) device was used in the monitoring of water quality parameters. The monitoring system implemented used consists of maker-UNO as the core controller, SIM7600-GSM module as the Wi-Fi module and the water quality parameters sensors (total dissolved solids (TDS), oxidation reduction potential (ORP), temperature and turbidity). This study applied five different artificial intelligence (AI) techniques models to predict the water quality parameters. The data were collected from phytoremediation treatment system and modelled by using artificial neural network (ANN), regression trees, support vector machine (SVM), ensemble trees and the Gaussian process regression (GPR). A satisfying prediction models were achieved indicating that early prevention of contamination in the treatment system can be achieved through the application of monitoring and artificial intelligence modelling tools.

Spatio-Temporal Analysis on Groundwater - Case Study for Thiruvallur District

Thiruvallur District in Tamil Nadu is one such district, with groundwater levels reaching depths of 50m to 60m below the surface. Growing populations, variations in land use patterns, reduction in rainfall depth, and other factors all contributed to an increase in water demand and a decrease in water potential. This affects the quality of groundwater as well. In this study, the variation of both Groundwater potential and Groundwater Quality is analyzed. The collected data has undergone thorough processing to ensure its accuracy and relevance for the area to be studied. (Thiruvallur District). The base map for the place to be analyzed and the well-map are created in the QGIS software with the data. The processed data is imported into the QGIS to create a database. With the database, the spatial variation between the stations is mapped. The temporal variation of the stations is carried out. The spatial map is done for the groundwater level and Groundwater quality parameters like pH, TDS, Cl, etc. The temporal variation is shown in the graph for the GW level and GW quality parameters with respect to the well-points.

Application of advanced computer technologies in determination of irrigation regimes for cotton in water scarcity areas

Agriculture is one of climate change's most sensitive economic sectors. In Uzbekistan, 95% of agricultural products come from irrigated lands. Because the agricultural sector of Uzbekistan meets the population's demand for food and industrial raw materials, ensuring national food security. Different climatic and soil-hydrogeological variations are countrywide significant to assess the possible increase in crop water demand and to determine the water consumption and irrigation regime in the irrigated lands. Therefore, this research aimed to create the hydrological module-zoning (HMZ) map of irrigated lands using geoinformation systems (GIS) technologies by employing spatial soil-hydrogeological data and determining water consumption and irrigation regimes for cotton according to FAO methodology. The area of investigation was the irrigated agricultural lands of the northern regions of the Republic of Karakalpakstan, located in Uzbekistan, which has undergone significant climate change over the last 30 years due to the Aral Sea tragedy and is faced with water scarcity. HMZ map of the study area has been figured out by ArcGIS 10.8 program based on Bespalov's methodology. Determining water demand of cotton developed by developed HMZs based on the CropWat 8.0 program using meteorological parameters. The study showed that identified areas of HMZ and the irrigation regime for cotton by Bespolov in the 80s of the last century have significantly changed because of climate change.

Assessment of Water Distribution for the Effectiveness of Water Allocation Modeling

This research intends to conduct the assessment of water distributing performance for supporting the performance index assessment of water allocation modeling. The main aim is intending to solve the conflict of water interest, so there is necessary to be carried out the water allocation so water user society will get the water regarding to their right fairly, efficiently, and sustainably. Along with the increasing of population number and the social and economy conditions of society, there will all be increasing water demand for various uses. However, the quality tends to decrease because it has potency to increase the local conflict becoming a conflict between the regency and city that is unwanted. The water preparation and allocation are activities in operating the water resource infrastructure, whose aim is to optimize the usage of water resource infrastructure. This research was conducted in the watersheds of Manjuto, Slagan, Dikit, Teraman, Muar, Padang Guci, Bangkenang, Manna, Kelam, Nasal, and Luas. The methodology consists of collecting data on each watershed that are water availability and water demand; then, water balance and distribution (allocation) are analyzed. The result of water allocation analysis shows the water availability due to the dependable discharge as the reference such as Q 80 or discharge with the probability of 80%; still several watersheds experience the water deficit in fulfilling the irrigation water requirement, household-city-industry (RKI), plantation, fishery, husbandry, and river flow maintenance needs. A new research is needed for the index assessment of water allocation in the watersheds that experience the water deficit to obtain the plan value of water demand fulfilling allocation in the water deficit condition, whether non-critical, lightly critical, moderately critical, and heavily critical. Keywords : water availability, water demand, water balance, water allocation. https://doi.org/10.55463/issn.1674-2974.50.3.7

Modified Particle Swarm Optimization for the Optimum Use of Multi-Reservoir Systems: MRP Complex, Chhattisgarh

The effective operation of reservoirs has been a key concern among the water resources management authorities as a consequence of global water shortages and decreased surface water runoff owing to increasing water demand and the effect of climate change. Water shortages, economic constraints, and environmental concerns have all contributed to the optimization of operations becoming increasingly replaced by new technologies. Optimization operation of water resources system is a challenging issue because of its nonlinearity, multiple constraints, and several dimensions. To address the challenges associated with the operation of the multipurpose Mahanadi reservoir in Chhattisgarh, India. The present study utilizes the application of modified particle swarm optimization (MPSO). The present study was conducted to evaluate the performance of the particle swarm optimization (PSO) model in comparison to the current operating reservoir system, to minimize the sum of squared deviations in downstream release and demand. The average percentage changes in reliability (100.31%), resilience (85.02%), sustainability (24.54%), as well as vulnerability reduced up to 69.54%. The model also had the lowest error parameters in the system such as (RMSE = 1.3892, MAPE = 0.1003, NMSE = 0.1025, MAE = 38.6689, and MSE = 1.9299), despite having the highest R2, i.e., 0.8974. When applied to the Ravishankar Sagar reservoir, MPSO yields optimal, worst, average, and standard deviation (SD) values of 0.45, 0.56, 0.51, and 0.038, respectively. In terms of optimizing the release and storage rates, MPSO performed consistently better than the PSO and other metaheuristics reviewed from the literature during the study. Therefore, MPSO is advantageous in the search for the optimal reservoir operation policy because it is easy to implement, requires less functional evaluations, and quickly tracks global optimum. Hence this study provides significant evidence that MPSO can be used to effectively solve real optimization challenges.