Abstract This study uses GIS-based multi-criteria decision analysis integrated with statistical techniques to investigate groundwater potential zones (GWPZs) in Chennai, Kancheepuram, and Tiruvallur districts. The study emphasizes regional-specific assessments, identifying the coastal plain regions of Kancheepuram and Tiruvallur as areas with high groundwater potential. Lithology was identified as the most critical factor influencing groundwater availability, followed by soil and drainage density. The variability of rainfall patterns further highlighted the significance of traditional weightage methods combined with modern GIS-based modelling for accurate assessments. This integrated approach provides a robust sustainable water resource management framework, especially in urban and peri-urban areas. Future research directions include applying machine learning, enhanced geospatial techniques, and utilizing diverse datasets such as remote sensing and geophysical surveys for improved GWPZ mapping. Graphical Abstract
Water supply for domestic and industrial purposes, Environmental sciences
Precipitation—or a lack thereof—can be both cause and consequence of heatwaves. Whereas most heatwave-precipitation research has emphasized summer heatwaves and extreme precipitation, heatwaves outside of summer are relatively more important for driving streamflow. Further, there is increasing recognition of how heatwaves impact river basin hydrology via their influence on the cryosphere, but fewer studies have considered the hydrological impacts of heatwaves via precipitation. Here, we aim to link and address these knowledge gaps by offering an analysis of a set of seasonally- and spatially-varying precipitation characteristics of heatwaves. We consider: (1) how the frequency of heatwave precipitation varies by precipitation intensity; (2) how the frequency and magnitude of precipitation differs between heatwave and non-heatwave periods; (3) how the frequency and magnitude of precipitation varies throughout a heatwave; and (4) how precipitation varies between periods before, during, and after heatwaves. We assess these characteristics for 14 425 basins across North America for winter, spring, summer, and autumn heatwaves. We find that there is a high degree of spatial and seasonal variability in all characteristics assessed. Overall, heatwaves are wetter in autumn and winter but are drier in spring and summer. We find that there are drier conditions overall in the continental interior and wetter conditions overall along the northwest and east coasts. Precipitation is generally greater and more frequent on the final day of heatwaves relative to other days, except for the west and east coast regions in winter. For those cases, heatwaves are generally wetter than periods that occur immediately before and after, indicating strong links between precipitation and relative warmth. These findings have implications for the processes that drive streamflow during heatwaves, and offer insights into the role that extreme temperature events play in modifying river basin hydrology.
Water supply for domestic and industrial purposes, Technology
Humaira Yasmin, Rawan Bossly, Fuad S. Alduais
et al.
Abstract This study discusses numerically the gyrating flow of a hybrid nanofluid comprising carbon nanotube nanoparticles on a stretched sheet employing a porous medium. To create a hybrid nanofluid mixture, single-walled and multi-walled carbon nanotube nanoparticles are mixed with water. The sheet’s surface is subject to velocity slip and convective conditions. The effects of Joule heating, Brownian motion, thermophoresis, and viscous dissipation have been used. The model is shown as PDEs, which are subsequently rehabilitated to ODEs using similarity variables. As the outcome of this study, a greater magnetic factor escalates the velocity panel along the secondary direction and heat profile while decreasing the primary velocity. Higher nanoparticle volume fractions improve the thermal profile while declining the velocity profiles along the primary and secondary directions. Both the primary and secondary velocity distributions decrease in response to the increased rotation and velocity slip factors. The temperature distribution is enhanced with the heat source factor, thermal radiation factor, Eckert, and thermal Biot numbers. The Schmidt number has reduced the concentration panels, whereas the concentration Biot number improved the concentration distribution.
Seyed Mohammad Enayati, Mohsen Najarchi, Osman Mohammadpour
et al.
Abstract This study aimed to forecast dam inflows and subsequently predict its capability in producing HEPP using machine learning and evolutionary optimization techniques. Mahabad Dam, located in the northwest of Iran and recognized as one of the nation’s key dams, served as a case study. First, artificial neural networks (ANN) and support vector regression (SVR) were employed to predict dam inflows, with optimization of parameters achieved through Harris hawks optimization (HHO), a robust optimization technique. The data of temperature, precipitation, and dam inflow over a 24-year period on a monthly basis, incorporating various lag times, were used to train these machines. Then, HEPP from the dam was predicted using temperature, precipitation, dam inflow, and dam evaporation as input variables. The models were applied to data covering the years 2000 to 2020. The results of the first part indicated both hybrid models (HHO-ANFIS and HHO-SVR) improved the prediction performance compared to the single models. Based on the results of Taylor’s diagram and the error evaluation criteria, the HHO-ANFIS hybrid model (RMSE, MAE, and NSE of 3.90, 2.41, and 0.86, respectively) exerted better performance than HHO-SVR (RMSE, MAE, and NSE of 4.39, 2.70, and 0.86, respectively). The results of the second part showed that using the HHO algorithm to optimize single models (RMSE, MAE, and NSE of 0.2, 10, and 0.90, respectively) predicted HEPP better than single models (RMSE, MAE, and NSE of 0.2, 10, and 0.90, respectively). The results of Taylor’s diagram also showed that the HHO-ANFIS model exerted better performance. The findings of this study indicated the promising performance of machine learning models optimized by metaheuristic algorithms in the simultaneous prediction of dam inflows and HEPP in multi-purpose dams for better management and allocation of surface water resources.
Desmond Rowland Eteh, Francis Emeka Egobueze, Moses Paaru
et al.
Abstract This study explored how dam operation and rainfall patterns interact to influence flooding in the Niger Delta, Nigeria. This study utilizes Sentinel-1 Synthetic Aperture Radar (SAR) data to analyze the flood events from 2018 to 2022, focusing on key locations such as Obiafu (downstream), Kainji/Jebba, and Lagdo dams (upstream). Analyzed Sentinel-1 satellite data [European Space Agency (ESA), 2018–2022], shuttle Radar Topography Mission, alongside rainfall data [Center for Hydrometeorology and Remote Sensing (CHRS), 2018–2022] and surface water level to assess flood variations between 2018 and 2022. The flood extent was differentiated from that of permanent water bodies using Sentinel-1 images with an RGB band (Snap 7.0), and the rainfall patterns were examined via inverse distance weighting (IDW) interpolation (ArcGIS 10.5). The findings reveal that the intensity and timing of flooding vary significantly across these regions. Obiafu experienced high flooding in October 2020 and 2022, while Kainji/Jebba and Lagdo dams had contrasting flood severities during these periods. Additionally, a comparative analysis of hydrograph data from these locations shows a delayed downstream response, highlighting the need for coordinated water release strategies to mitigate flood risks. The results also indicate that upstream dam operations, particularly water releases, contribute to downstream flooding, although local rainfall patterns remain a crucial factor. By aligning SAR data with real-time water levels, this study emphasizes the importance of integrating satellite-based monitoring with hydrological models to improve flood prediction accuracy and minimize socio-economic impacts in the Niger Delta. The study concludes that enhanced flood management strategies, incorporating both rainfall forecasting and dam operation schedules, are critical for reducing flood-related vulnerabilities in the region.
Water supply for domestic and industrial purposes, Environmental sciences
Abstract Stormwater drainage networks are designed to reduce the risk of rainwater damage to the served area. The purpose of optimizing a stormwater drainage system is to reduce overall construction costs and to meet hydraulic design requirements. Currently, designs that rely on software or manual calculations are limited by the available time and the designer’s capabilities. In fact, manual optimization for large networks consumes a lot of time and effort, and there is no guarantee that the optimal design is reached, also it is subject to human errors. In recent years, several researchers have focused on creating optimization design algorithms specifically for sewer and storm networks, such as genetic algorithm (GA), linear programming (LP), heuristic programming (HP),…etc. However, these studies were limited to covering one or two design parameters and constraints. Additionally, in some studies, the hydraulic performance of the designed network was not treated in a proper way, especially the water surface profile effects. So, the main objective of the study is to develop an effective hydraulic-based optimization algorithm (HBOA) that can dynamically get the optimal design with minimum total cost for a given storm network layout and meet all hydraulic requirements. To achieve this, a MATLAB code is created and coupled with SewerGEMS software that automatically simulates all expected optimization scenarios based on network hydraulic performance. The HBOA is validated economically and hydraulically using two benchmark examples from the literature. According to the economic validation, the total network cost generated by HBOA was the lowest when compared to the optimization methods found in the literature. During the hydraulic evaluation, it was observed that the optimization algorithm (GA-HP) used in the literature for the benchmark examples does not meet the hydraulic requirements where the networks are flooded, whereas HBOA meets the hydraulic requirements with minimal overall network cost. Also, the HBOA is applied to four real stormwater drainage networks that were already designed, constructed, and optimized manually. The four redesigned real cases using HBOA revealed a cost reduction of about 15% compared to the original designs, while consuming a few hours for the design and optimization processes. Finally, the developed HBOA is a robust, time-efficient, and cost-effective optimization and hydraulic design tool which could be used in the design of stormwater drainage networks with different design constraints with minimal human interference.
Zaid S. Alotaibi, Khalid N. Alharbi, Yaseen Alharbi
et al.
Abstract A semi-industrial demineralization facility was used in six CDI cells to desalinate in two steps. A desalination cycle lowered the feedwater salinity from 1 to 0.5 g/L and produced 200 l/h of demineralized water. This process may be repeated to increase efficiency. Initially, feedwater commenced at 1 g/L. Monitoring both voltage and current during the salt ion removal indicated that CDI cells may recover 30% of the energy utilized. Furthermore, V–Q curves using charge and voltage measurements increased energy recovery by 30%. By cutting off the CDI cells' power source, the electrodes' operating voltage was recorded between 0.85 and 0.9 V, much lower than the external contacts' 1.2 V. The desalination system's efficiency could rise if the electrode voltage was measured and adjusted. In conclusion, storage tanks can provide desalinated water while minimizing water waste; hence, they should be installed. This study examined the physical–technical parameters of a CDI desalination system through experiments and several operational modes. Moreover, it revealed CDI desalination system improvements.
Abstract Constructed wetlands (CWs) are engineered environments designed to utilise natural processes to treat urban or industrial wastewater, with the core driver of the bioremediation process provided by the microorganisms present within. This study isolated 32 bacterial strains from sediment across the Sardar Bherry CW to find candidates with remediation properties and to understand how the physiochemical gradient from wastewater input influences the functional properties of the bacteria present. Bacterial isolates recovered closer to the wastewater effluence were more likely to be pathogenic, with increased haemolytic activity, causing high rates of fish mortality. In contrast, isolates recovered further from the wastewater source were observed to be non-pathogenic and have increased inhibitory effect against pathogenic strains. Extracellular proteins extracted from non-pathogenic isolates also appeared to be effective at inhibiting the growth of pathogenic bacteria, including multidrug resistant strains. Non-pathogenic isolates recovered across all sampling sites displayed the ability to reduce high levels of ammonia in solution during laboratory testing. Antibiogram assays of the recovered isolates showed a relatively high rate of multidrug resistant or marginally resistant bacteria across all sampling sites, highlighting a potential limitation within the CW bioremediation process in mitigating antibiotic resistant strains. This isolate based study provided an avenue to understand the influence of spatial succession from wastewater effluence on bacterial characteristics, as well as obtain candidates that can be further investigated for optimisation in bioremediation efforts. The cultured isolates can supplement future environmental sequencing studies by providing wet lab specimens to compare (meta)genomic information discovered within the CW ecosystem.
Musaab A. A. Mohammed, Abdelrhim Eltijani, Norbert P. Szabó
et al.
Abstract This research employed the groundwater quality index (GWQI), multivariate statistical methods, and human health risk assessment model to investigate the suitability of groundwater for domestic uses in northern Khartoum state, Sudan. The groundwater samples were analyzed for eleven physiochemical parameters, including pH, EC, TDS, TH, Cl−, SO4 2−, NO3 −, Ca2+, Mg2+, Na+, HCO3 − and the primary investigation indicated the deviation of these parameters from World Health Organization (WHO) standards. The hydrochemical analysis revealed different groundwater facies with the dominance of Ca–Mg–HCO3 water type. Consequently, the groundwater samples were classified, based on GWQI, into three categories as 76.4% of the samples fall in the excellent water class, 17.6% are projected in the good water class, and 5.9% of groundwater samples are considered unsuitable for human consumption. The multivariate statistical methods were applied, including Pearson’s correlation analysis, principal component analyses (PCA), and hierarchical cluster analysis (HCA). Three principal components (PCs) explaining 86.07% of total variances are extracted. These PCs indicated that rock-water interactions and agricultural practices influence groundwater quality in the study area. Additionally, HCA is used to categorize groundwater samples based on the concentration of the physiochemical parameters. Consequently, three types of groundwater were identified as low, medium, and highly mineralized. In the final stage, the non-carcinogenic human health risk was assessed based on the concentration of NO3 − using the United States Environmental Protection Agency (USEPA) models. The obtained hazard quotient for children indicated that 64.7% of groundwater samples are beyond the permissible limit (1 <), and the use of these samples may result in health consequences. Therefore, remedial measures are suggested for the sustainable use of groundwater.
Water supply for domestic and industrial purposes, Environmental sciences
Abstract A total of seventy irrigation water samples were collected from Leh, Ladakh, India, to determine their hydrochemistry profile and water quality for irrigation purposes. Water quality indices such as total hardness (TH), residual sodium carbonate (RSC), potential salinity (PS), permeability index (PI), Kelly's ratio (KR), sodium absorption ratio (SAR), corrosivity ratio (CR), and chloroalkaline indices (CAI) were measured. The Piper diagram, Durov's diagram, and United States Salinity Laboratory (USSL) diagram were drawn to determine the water types, ion exchange processes, and rock–soil–water interaction. The findings indicated that the hydrochemical characteristics of irrigation water are naturally alkaline. Furthermore, water quality parameters revealed that the study area’s surface water is suitable for irrigation purposes, despite relatively high TH and MH levels. The level of CR indicated that water should not be transported using metal pipes. The CAI and Durov's plot indicated direct ionic exchange processes controlling water chemistry. Additionally, this irrigation water is mainly dominated by the Ca2+–Cl−–SO4 2−, Na+–K+–CaCO3 + HCO3 −, and Na+–K+–Cl− type, which indicates silicate rock weathering along with some anthropogenic input. The USSL salinity diagram indicated a medium salinity and low Na hazard. Hence, it is concluded that the rock weathering cycle is the natural source of all the cations and anions, and these ions pass directly from water to rock and vis-à-vis, along with some input of anthropogenic activity.
Majid Smaeili, Hamid Madani, Bahram Majd Nassiri
et al.
Abstract This study was aimed to investigate the effect of drought stress on some ecophysiological characteristics of sunflower cultivars. This study was conducted in the form of split plots in a randomized complete block design with three replications in the Braun area of Isfahan province for the year 2020. Drought stress at three irrigation levels after evaporation of 90, 120, and 150 mm from Class A evaporation pan as non-stress, mild, and severe stress, respectively, in the main plots and five cultivars of sunflower Chiara, Oscar, Fantasia, Hisun 33, and Shams was placed in the subplots. Drought stress affected achene yield, harvest index, and drought tolerance of sunflower cultivars. The highest biophysical water productivity (WPb) was obtained from 90 and then 120-mm irrigation and among sunflower cultivars from Fantasia and Hisun 33 cultivars. The highest economic water productivity (WPe) was obtained with 90-mm irrigation and Fantasia and Hisun 33 cultivars. The highest HI belonged to 90 and then 120-mm irrigation. The highest HI was related to Fantasia, Oscar, and Hisun 33 cultivars, and the lowest HI was related to Shams and Chiara cultivars. The highest and the lowest grain yield were obtained in 90 (control) and 150 mm of evaporation, respectively. The highest grain yield was obtained in Fantasia, Shams, and Oscar cultivars, and the lowest yield was observed in Hisun 33 and Chiara cultivars. In general, drought stress affected yield, HI, crop water productivity (WPc), and drought tolerance of sunflower cultivars.
In this paper, an attempt has been made to use the double-acting reciprocating hydraulic pump to get increased water supply. For water supply output a mathematical calculation has been done. Dual side double-acting reciprocating water pump setup using the scotch yoke mechanism consists of two reciprocating pumps in which a plunger is provided for the pumping action. Here a cam plate is used to guide the plunger to move in a reciprocating motion and a specified motor is separately operated to run the cam plate. Due to this motion of the plunger, high pressure is attained inside the pump, and water is pumped out. Here, the reciprocating motion of the plunger is the key function for the operation of the pump and as a result of this repeated action, thrust is developed inside the pump. Due to this thrust, the delivery of the water from the cylinder is carried out. The delivery action takes place by the movement of the plunger as the flow of water is constant. So the water delivered will be at high pressure. With our setup, this happens to both the pumps simultaneously. Hence we achieve double the discharge rate of water with a single input from the motor. This setup can be applied to various applications in agriculture, domestic use, and industrial purposes.
Abstract Streams draining to Gilgel Gibe catchment cross agricultural and urban land uses receiving a different pollutant that challenges water quality. A total of 21 sampling sites were selected from seven streams of agricultural (n = 3), urban (n = 3) and forest (n = 1) land-use types. Composite samples were collected from upstream, middle and downstream of all land-use types. Twenty-three physicochemical parameters were measured from each sampling site. Temperature, DO, pH, EC, turbidity, width, depth, current velocity and discharge were measured onsite. Two milliliters of unfiltered water samples was collected from every site for laboratory analysis. Mean of NO3-N was highest in agricultural streams than forested and urban streams. In contrast, mean of SRP, NH4-N and COD and BOD5 concentration was greater in urban streams followed by agricultural streams, whereas forest streams are lowest. Concentrations of nutrients, EC and turbidity were recorded in increasing manner across land-use gradient from forested to agricultural and urban streams. The analysis of one-way ANOVA showed that all physicochemical parameters were significantly different among all sites with different land-use types (P < 0.05), except for water temperature (one-way ANOVA: F = 0.987, P = 0.494). NMDS and cluster analyses have discriminated the sites into three groups of land-use types. Then, we conclude that water quality of urban stream is highly impaired than agricultural streams, whereas forested streams have better water quality. Therefore, stream restoration projects, reforestation, conservation of riparian vegetation appropriate waste disposal need to be encouraged in the study area for sustainable management of freshwater resources.
Norzaura Abd Rahman, Nur Shazwani Muhammad, Jazuri Abdullah
et al.
Aging pipes in the domestic water distribution network have the potential to decrease the quality and quantity of the treated water supplied to the consumers. Therefore, a calibrated water distribution model is helpful to monitor and understand the behaviour of a real water distribution network. However, a comprehensive performance indicator and an integrated method to assess the efficiency of model performance have not been well established in the literature. This study developed a methodology for a model calibration exercise, with consideration of two uncertainty parameters, i.e., Hazen–Williams roughness coefficient of the pipes and Non-Revenue Water (NRW) in each nodal demand. Following this, a statistical color-coded performance indicator was established, based on the Nash–Sutcliffe Efficiency Coefficient (NSEC), the coefficient of determination (R2), the correlation coefficient (r), and the Mean Absolute Error (MAE). The accuracy of the calibrated model was measured by Discrepancy Ratio (DR) analysis. This study concluded that the model performed well when NRW was added to the nodal demand in zone(s) with suspected water loss activities. The suggested Hazen–Williams roughness coefficient for PVC pipes was between 130 and 140 for pipes aged more than 20 years. The threshold error value to determine the accuracy of the simulated model was proposed to be between –0.05 and 0.05.
Quality assessment of the groundwater resources is one of the most important issues in water resources development. The main purpose of this study is to model the nitrate pollution, to recognize the spatial and temporal variations of nitrate concentration and to predict the nitrate movement under hydrological gradient. Thus, collecting and organizing the field data, formulation of hydrodynamic characteristics and transmission phenomena was conducted for the aquifer system in Varamin plain, Iran. In this study, a quantitative model of GMS software was prepared using MODELFLOW code and the qualitative data was imported to the model. The MT3D was used for modeling. According to the modeling results, it is predicted that during a 10-year period water from some zones of the aquifer will become non-potable. The most important factor in degrading the water quality in downstream of cities is the nitrate pollution from absorbent wells in residential areas in addition to the nitrate pollution from the agricultural areas in upstream. Due to the existence of an impermeable layer, confined aquifer is less affected by nitrate pollution in Varamin plain. According to the quality standards for drinking water, this aquifer is in an appropriate condition. It is suggested that drinking water be supplied from the wells recharged by the confined aquifer..
Technology, Water supply for domestic and industrial purposes
Nowadays, low impact development (LID) and best management practice (BMP) are being used to reduce the impact of urban development on the runoff quantity. Regarding to this and according to Tehran position and its development, this research was conducted using SWMM model to study the effect of LID-BMP methods on runoff in district 22 of Tehran city, Iran, with area of 54000 ha. This study included five scenarios: current situation, green roof, permeable pavement, vegetative swale and green roof-permeable pavement-vegetative swale. The study was conducted for rainfall in 5 return periods (i.e. 2, 5, 10, 50 and 100 year) in 19 sub-basins. Results: The results showed that the effectiveness of all methods to reduce runoff was increased up to the return period of 50-yr and then reduced for the 100-yr return period. Green roof and vegetative swale had the most and the least effect on runoff, respectively. In addition, comparison of peak flow of these methods with the results from the Tehran Runoff Management Master Plan revealed that green roof was most effective on the peak flow reduction.
Technology, Water supply for domestic and industrial purposes
Mohammad Ebadi, Mohammad Mozdianfard, Majid Aliabadi
Considering the challenges faced and emphases being put in the last two decades on the water consumption at Esfahan Oil Refining Company (EORC), substantial efforts were made on its optimization and recovery of effluent from various unit operations. The effluent re-use from the Reverse Osmosis (RO) unit, collected at the evaporating pools was considered in this research, using membrane distillation, as a modern desalination approach to recover water. In this study, RSM modelling was employed for optimization and prediction of membrane distillation operating conditions on the brackish effluent output from the RO unit at EORC. Tests were carried out on a flat module with 80cm<sup>2</sup> effective surface area using micro porous commercial PTFE membranes based on PP. Effects of three parameters of feed temperature, and flow rate as well as permeate temperature on the permeate flux were investigated using the Design Expert software. Software modelling results indicated that feed temperature had the largest influence in increasing the permeate flux (almost twice the effect of permeate temperature and feed flow rate). The maximum optimized permeate flux in the test range investigated was 59.67 L/m<sup>2</sup>h with 0.9570 desirability at feed temperature of 70°C, permeate temperature of 15°C and feed flow rate of 2L/min. This research showed that direct contact membrane distillation (DCMD) could successfully be employed for water recovery from the RO outlet effluent at EORC. Optimization of operating condition at Esfahan climatic condition can be achieved using software modelling.
Technology, Water supply for domestic and industrial purposes