International Journal of Hydrology Science and Technology (34 papers in press)

Regular Issues

• Long-range forecasting of daily rainfall using machine learning techniques  
  by Syamantak Bhunia, Ujjwal Saha 
  Abstract: Around the world, awareness of the value of rainfall forecasting and its social and economic advantages is rapidly growing. Nation like India, where agriculture is one of the main economic drivers, accurate rainfall forecasting is essential for managing water resources and reducing hydrological extremes. To predict daily rainfall for a year in the drought-prone Kangsabati river basin, long short-term memory (LSTM) and random forest (RF) techniques were utilised using the data of 52 years (1969 to 2020). Finding the right associated variable and a substantial lag in the time series that allows for future value prediction is essential when developing time series forecasting models. The partial auto correlation function and Pearson correlation technique were applied in this context. Furthermore, comparisons were made between the suggested models and the well-known statistical model, the seasonal auto-regressive integrative moving average (SARIMA). The study shows that for this region, the proposed LSTM model and SARIMA model had higher accuracy than the RF model. Additionally, this research suggests that machine learning algorithms may be used to analyse daily rainfall for a particular catchment or station and, to a certain extent, forecast extreme hydrological events.
  Keywords: hyperparameter; long short-term memory; LSTM; machine learning; rainfall forecasting; RF; SARIMA.
  DOI: 10.1504/IJHST.2024.10061937
   
  
• Modeling of scour depth in the existing bridge piers with and without an adjacent parallel bridge  
  by Biswajit Dalal, Subhrajyoti Deb 
  Abstract: This paper presents a hydraulic simulation conducted to assess the stability of the Netaji Subhas Bridge on the Gomti River in Tripura. The simulation takes into account different scour profiles and numerous flood events. The calculation of local scour at various piers takes into account four different flow profiles: PF1 (1,495 m3 /s), PF2 (1,147 m3 /s), PF3 (711 m3 /s) and PF4 (475 m3 /s). The analysis of the HEC-RAS model reveals that the scour depth (Ys) and the Froudes number (Fr) exhibit a decrease for all flow profiles when a parallel bridge is constructed upstream of the existing bridge. But, if the new bridge is constructed on the downstream side then Ys and Fr are increased for PF2, PF3 and PF4 but in the case of PF1, only the Ys decreased. Therefore, the safer and more serviceable option is to construct the parallel bridge on the upstream side of the existing bridge.
  Keywords: Gomti River; parallel bridges; HEC-RAS; modelling; scour depth.
  DOI: 10.1504/IJHST.2024.10062372
   
  
• Performance evaluation of commonly used infiltration models  
  by Redahegn Sileshi, Robert Pitt, Shirley Clark 
  Abstract: Soil infiltration rate is a critical parameter in the design and evaluation of stormwater control facilities. The aim of this research was to evaluate selected infiltration models (Horton’s, Kostiakov’s, and Green-Ampt’s) used to estimate final soil infiltration rate. Parameters of the models were estimated. The goodness of fit of the three equations for infiltration was tested using the root mean squared error (RMSE). Comparison of the field and predicted infiltration rate evaluated at each time interval indicated that the infiltration rate predicted by the Green-Ampt’s and Horton’s models were much closer to the measured data.
  Keywords: infiltration rate; stormwater; infiltration models; model parameter; root mean squared error; RMSE.
  DOI: 10.1504/IJHST.2024.10063206
   
  
• Minimising greenhouse gas emissions from small and medium-sized wastewater treatment plants  
  by Jerzy Mikosz 
  Abstract: Municipal wastewater treatment plants often use the activated sludge process in single-stage reactors with nitrification or in two-stage reactors with nitrification and denitrification. Both processes, if operated under unfavourable environmental conditions, can lead to excessive production of nitrous oxide (N2O), a gas with a high global warming potential (GWP) of about 300). In turn, the decomposition of organic pollutants leads to the release of CO2 and CH4 into the atmosphere. When analysing greenhouse gas emissions from wastewater treatment, it is also necessary to consider indirect emissions, mainly related to the use of energy from external sources. Estimating the magnitude of these emissions based on actual measurements is difficult. This article presents the results of simulation studies on the potential for reducing greenhouse gas emissions from small and medium-sized wastewater treatment plants with aerobic sludge digestion (AD) through operational optimisation of existing plants or the application of new technologies.
  Keywords: wastewater treatment plant; WWTP; activated sludge; multiphase reactors; nitrification; enitrification; aerobic digestion; greenhouse gases; GHG; GHG emission; nitrous oxide; N2O; computer simulation.
  DOI: 10.1504/IJHST.2024.10063324
   
  
• Using artificial neural network with clustering techniques to predict the suspended sediment load  
  by Abdelghafour Dellal, Abdelouahab Lefkir, Yamina Elmeddahi, Samir Bengherifa 
  Abstract: Rivers are natural water channels that are influenced by a variety of factors, including erosion and sedimentation, which have a detrimental impact on the ecosystem’s health and water quality. Recently, researchers resorted to using an artificial neural network (ANN) to model the suspended sediment load. This study addressed the application of a multi-layer ANN model. Feed-forward with a backpropagation algorithm based on five different collection methods for the input data. To model the daily suspended sediment load in the Sacramento River, California, USA, current and delayed Ql flow discharge data and solid flow Qs data were used. The accuracy of the five methods was compared in 10 different input groups based on proficiency criteria: standard deviation ratio RSR, coefficient of determination R2, percentage bias (PBIAS), and Nash-Sutcliffe efficacy (NSE). The ANN model with the k-mean clustering technique provides the best results. The RSR values varied between 0.30 to 0.42, and the R2 values ranged from 0.82 to 0.91. While the range of NSE values was from 0.79 to 0.90.
  Keywords: artificial neural network; ANN; clustering technique; flow discharge; suspended sediment.
  DOI: 10.1504/IJHST.2024.10063467
   
  
• Site selection and hydropower potential assessment in Upper Sutlej River Basin: a case study of Indian and Tibetan regions using RS-GIS, SWAT and T-F models  
  by Nikki Chanda, Madhusudana Rao Chintalacheruvu, Anil Kumar Choudhary 
  Abstract: This research explores the untapped hydropower potential in India and Tibets Upper Sutlej River Basin (USRB). By leveraging remote sensing and GIS methods, the study identifies 901 new sites in India and 95 sites in Tibet for potential hydropower generation. The present study estimates that the Indian sites have 2,923 megawatt (MW), 1,830 MW and 1,274 MW, while the Tibetan sites have 289 MW, 178 MW and 98 MW hydropower potential at 50%, 75% and 90% dependability flows, respectively for medium or high-head in the USRB. The future hydropower generation potential is also assessed at the Bhakra dam site, a significant project in the USRB region, utilising historical streamflow data (19932013) and projected streamflows (20142053) through calibrated SWAT and T-F models results. This research offers valuable insights for sustainable development and highlights the immense hydroelectric power possibilities in the USRB region.
  Keywords: hydropower; Upper Sutlej River Basin; USRB; RS-GIS; soil water assessment tool; SWAT; Thomas-Fiering model; T-F model.
  DOI: 10.1504/IJHST.2024.10063572
   
  
• Application of CE-QUAL-W2 model for optimal selective withdrawal of reservoir concerning water quality (case study: Shahr Bijar Dam Reservoir, Iran)  
  by Seyed Abolfazl Ebrahimi 
  Abstract: Reservoirs, essential for human water supply, experience thermal stratification affecting water quality. Utilising the CE-QUAL-W2 model, this study simulates thermal stratification and water quality in Shahr Bijar Reservoir, Iran, spanning September 2019 to 2020. Simulations identify the optimal intake gate for selective withdrawal, considering parameters such as dissolved oxygen, phosphate, ammonium, and total dissolved solids. Calibration and validation demonstrate a reasonable correlation between simulated and observed data. Thermal stratification leads to variable water quality at different intake gate levels. Three seasonal management scenarios determine the optimal outlet for selective withdrawal. Results indicate that the third intake gates, with IRWQISC indices of 83.1, 85.5, and 79.8 in fall, spring, and summer, deliver superior-quality water. In winter, all three intake gates, each with an index of 87, exhibit identical quality. This study introduces an innovative approach to reservoir withdrawal optimisation, emphasising seasonal variations and practical implications for water resource management.
  Keywords: water quality modelling; CE-QUAL-W2; selective withdrawal; dam operation; reservoir management.
  DOI: 10.1504/IJHST.2024.10063982
   
  
• Predictive hydraulic conductivity modeling of wide gradation spectrum sandy soils using stepwise multiple linear and LASSO regression  
  by Mohammad Aasif Khaja, Shagoofta Rasool Shah, Ramakar Jha 
  Abstract: Accurate estimation of soil hydraulic conductivity (K) is crucial in groundwater hydrology and geo-environmental engineering applications. This study introduces novel K predictive modelling for wide gradation spectrum sandy soils, employing stepwise multiple linear regression (SMLR) and least absolute shrinkage and selection operator (LASSO) techniques. Using an 81-sample dataset with key variables, including particle sizes, gradation parameters, porosity, and dry density, this study addresses limitations in existing K prediction methods. Correlation analysis reveals variable associations and multicollinearity issues, necessitating feature selection and the development of SMLR and LASSO regression models. While both models perform well on the training dataset, LASSO excels in mitigating overfitting, achieving a high coefficient of determination (R2) of 0.82 and 0.87 on the training and testing datasets. Comparative analyses with existing models in the literature underscored LASSO’s superiority in approximating laboratory-measured K-values, establishing it as the preferred choice for hydraulic conductivity estimation.
  Keywords: hydraulic conductivity; sandy soils; predictive modelling; stepwise multiple linear regression; SMLR; LASSO regression.
  DOI: 10.1504/IJHST.2024.10064217
   
  
• Accessing the accuracy of modified Schlumberger (Hummel) array of vertical electrical sounding: a pivotal to groundwater exploration  
  by Abayomi Adesola Olaojo, Prekibina Tamunoimama Oti, Kehinde David Oyeyemi 
  Abstract: Space constraints encountered in areas with well-developed housing layouts impede geophysical exploration for groundwater. The study aims to evaluate the effectiveness of the modified Hummel array in groundwater exploration. 32 vertical electrical sounding (VES) data were obtained using both the full and half Hummel and Schlumberger arrays on a migmatite gneiss, revealing its applicability in a complex geology. The data were processed by curve matching and computer iteration. The curve types (H, KH, and QH) and geoelectric sequences inferred from the arrays showed similar layer distributions. The correlated raw data and geoelectric parameters generated moderate to strong coefficients (0.5224-0.9999), indicating a high degree of similarity. The T-values (>2) confirmed the reliability of the coefficients used as predictors. The closeness of data around 1:1 line revealed half Hummel to be a better substitute for Schlumberger, especially in built-up areas where mirror electrode spread is not achievable due to space constraints.
  Keywords: Hummel; Schlumberger; sounding; geoelectric; groundwater; resistivity; correlation; exploration; gneiss; curve-type.
  DOI: 10.1504/IJHST.2024.10064540
   
  
• Analysis of groundwater resources in the Majene coastal aquifer - Indonesia based on a hydrogeological conceptual model  
  by Muhammad Ramli, Aryanti Virtanti Anas 
  Abstract: Many cities do not have sufficient groundwater availability information. As a result, meeting the communitys water needs can become a problem, as in Majene City - Indonesia. Therefore, it is necessary to gain an understanding of groundwater through a hydrogeological conceptual model. The conceptual model was developed based on rock resistivity, hydro-chemical, and climatological data. The rocks that make up this area form an unconfined aquifer which receives a recharge of 277 mm/year. The resistivity data characterises the rock layer/aquifer as being relatively uniform down to a depth of 150 metres. The hydro-chemical groundwater data in the aquifer was indicated to have been contaminated with seawater intrusion. An interpretive model of 2D areal simulation using the developed conceptual model to figure out the current condition based on estimated model parameters and boundary conditions. The numerical results could provide groundwater flow patterns according to the field observations and indicate significant river influence on seawater intrusion into the aquifer.
  Keywords: groundwater; hydro-chemical; seawater intrusion; salinity; aquifer; resistivity; numerical model; recharge; water balance; Indonesia.
  DOI: 10.1504/IJHST.2024.10064608
   
  
• Comparative assessment of LSTM approaches for enhanced prediction of rainfall climatology with minimum uncertainty  
  by Akshay Kumar, Saumitra Rai, Gaurav Kumar, Rajiv Gupta 
  Abstract: Forecasting precipitation is highly challenging for scientific modellers due to the complexity and uncertainty of atmospheric data and weather prediction models. To investigate the hydrological alternations such as rising sea levels, increasing floods and evaporation, and changes in snowpack caused by climate change, it is essential to accurately predict precipitation, a function of several interrelated climatic variables. This study presents a unique approach to predicting precipitation with minimum uncertainty by performing a comparative assessment of long-short-term memory (LSTM) approaches. The LSTM prediction models were run using quarterly, semi-annual, annual, and biannual precipitation data and other data such as temperature, vapour pressure, cloud cover, rainy days, and potential evaporation. Bivariate models using potential evaporation and temperature produced equivalent results to the multivariate model as the mean absolute error (MAE) was found to be 23.89% and 26.35%, respectively, compared to the univariate model (MAE 76.29%).
  Keywords: precipitation prediction; machine learning; LSTM; climate change.
  DOI: 10.1504/IJHST.2024.10064994
   
  
• Economic and hydraulic outcomes in storm water collection networks - application of momentum equation  
  by Masih Zolghadr, Farzan Jahanbakhsh, Hector Martin, Mohammad Rafie Rafiee, Hazi Md. Azamathulla 
  Abstract: The efficacy of existing stormwater collection systems and the costs associated with safely transmitting floodwater remain uncertain due to climate change. A case study employing one-dimensional hydraulic flood routing with a five-year return period was conducted in Qader Abad, Iran. The study compared the hydraulic characteristics, dimensions and construction cost of stormwater collection systems using dynamic, diffusive, kinematic, and constant flow techniques. The findings of the study emphasised that ignoring the inertia and pressure terms could lead to an overestimation of the flow depth and conduit diameter. In particular, the dynamic wave method demonstrated a lower average maximal discharge than other methods. Despite their higher computational costs, the dynamic and diffusive wave methods had significantly lower construction costs than the kinematic and constant flow methods.These findings highlight the importance of incorporating inertia and pressure terms into the momentum equation when estimating the construction costs of urban drainage projects.
  Keywords: urban drainage system; numerical simulation; rainfall-runoff model; SWMM software; stormwater; climate change.
  DOI: 10.1504/IJHST.2024.10065598
   
  
• Effect of different discharges and type of soils on scour under bridge piers by using statistical analysis  
  by Basima Abbas Jabir Al-Humairi, Fatima Asaad Tayeb, Noor S. Mahdi 
  Abstract: The effect of different water discharges on soil scour bridge piers was investigated in this study, which used cylindrical shape piers and experiments on sand soil and river sand soil, with different water discharges and conducted on rectangular laboratory channel with length 12 m and width 0.5 m.The results were statistically treated by using DataFit software package depending on parameters like the flow velocity, depth of water, area of water section, diameter of pier, medium particle size, Froude number, discharge of water, intensity of flow. Several parameters such as coefficient of determination (R2 ), standard estimated error (SEE), root mean squared error (RMSE), mean absolute error (MAE) and relative error (RE) were determined using the strength of the relationship between estimated and observed values of scour depth under bridge pier and used to verify the generated model.
  Keywords: soil scour; bridge pier; velocity of water; statistical analysis; type of soil; scour; statistical analysis; soils; velocity; piers.
  DOI: 10.1504/IJHST.2024.10065828
   
  
• Machine learning-based approach coupled to SWAT model to dynamically quantify the natural groundwater recharge  
  by Khaoula Khemiri, Anis Chkirbene, Constantinos F. Panagiotou, Catalin Stefan 
  Abstract: Limited understanding of aquifers’ responses to global warming and human activities challenges scientists and water professionals. This study, an early attempt to simulate natural groundwater recharge in the Chiba watershed, assesses the impact of human activities and climate change using Google Earth Engine and machine learning. With a Kappa coefficient of about 90%, the study produced reliable results. From 1985 to 2021, the SWAT model effectively replicated hydrological dynamics. Findings show that a 12% increase in agricultural land and a 2% decrease in precipitation result in a 16% rise in evapotranspiration and a 33% decline in natural recharge. Hydrological processes are sensitive to precipitation and land use changes. Spatial distribution of annual recharge indicates low groundwater recharge with upstream-downstream variance. Landsat images and machine learning enhance land use/land cover classification in Tunisia’s semiarid context. This research calls for deeper investigations into groundwater levels for comprehensive groundwater resource management and sustainability.
  Keywords: climate change; groundwater; natural recharge; human activities; random forest; soil and water assessment tool; SWAT; modelling.
  DOI: 10.1504/IJHST.2024.10065829
   
  
• Sustainable solutions for brackish water desalination: a comprehensive investigation into reverse osmosis efficiency enhancement  
  by Moumni Mohammed, Massour El Aoud Mohamed 
  Abstract: Desalination of brackish and saltwater is one of the most important freshwater resources in water stressed regions. The reverse osmosis process is an efficient and successful water desalination technology that requires a significant amount of electrical power and accordingly, it prevents the diffusion of this technology worldwide. The objective of this study is to reduce energy consumption in a Moroccan brackish water reverse osmosis desalination plant. Currently, this plant operates without energy recovery and the production rate reaches 1,017 m3 /h with a maximum SEC of 3.2 kWh/m3 . The organisation plans to increase production rates by adding more reverse osmosis trains which has a direct impact on the SEC. This study aims to optimise SEC through this plant in its future design. Both configurations with and without ERD were simulated to analyse the variation of SEC using a range of feed water parameter fluctuations, particularly its temperature and salinity. The results showed that the implementation of ERD in the future design will reduce the SEC by 30%.
  Keywords: desalination; brackish water; reverse osmosis; energy recovery.
  
  
• Free surface flow assessment through a homogeneous earth-fill dam using a feed-forward neural network model  
  by Mohamed Khorchani, Noureddine Rhayma, Sandra Pereira, Pierre Breul 
  Abstract: Seepage flow through the body of an earth-fill dam adversely affects dam’s stability. Therefore, a better understanding of the seepage phenomenon is required to detect early signs of abnormal behaviour and to plan intervention strategies when needed. In this study, a feed-forward neural network model is used to evaluate the free surface flow through a homogenous earth-fill dam. Data collected from the monitoring system were first analysed using principal component analysis (PCA) to identify the relationships between the selected variables. The model inputs were then pre-processed using Min-Max scaling transformation, and a trial-and-error approach has been used in order to achieve the best neural network architecture. As a next step, the delayed effects of reservoir water level fluctuations on the seepage phenomenon were investigated. Additionally, the effect of the dataset size on the prediction capabilities of the neural network model has also been explored. According to the selected performance criteria, the proposed neural network model was shown to be a powerful tool for predicting piezometric levels in dam’s body. Such a result can be used for a continuous simulation of earth dam’s behaviour when coupled with a numerical model.
  Keywords: earth-fill dam; neural networks; free surface flow; delayed effects.
  DOI: 10.1504/IJHST.2024.10066191
   
  
• Energy dissipation downstream multi opening sluice gate  
  by Mohammad Y. Hamid, Ahmed Y. Mohammed 
  Abstract: Sluice gates are structures, which are used to regulate the water level in open channels. Many studies examined the hydraulic properties of these gates to reach the best performance, but studies that dealt with multi-opening sluice gates are still few and need more investigations, this study focuses on gate operating scenarios and the effect on energy dissipation. The energy dissipation equation for a multi-opening sluice gate is predicted and compared with actual data, with maximum error not exceed 15%. The results showed that the maximum E/E1 values reached 70.18% for the same gate openings, and this value reached 68.46% when the summation of intermediate openings is greater than that for side operating. These values decrease to 44.1% in the opposite operation, so this operating system must be avoided.
  Keywords: sluice gate; open channel flow; energy dissipation; multi-opening gate; operating scenarios.
  DOI: 10.1504/IJHST.2024.10066353
   
  
• Enhancing bridge pier resilience against scouring during extreme flood condition using vegetation as a countermeasure-experimental approach  
  by Sajjad Hussain, Nadir Murtaza, Zaka Ullah Khan, Naeem Ejaz, Inzimam Ul Haq, Diyar Khan 
  Abstract: In the current investigation, scour mitigation around the bridge pier has been explored using vegetation of different densities (G/d) and aspect ratios (A/R) under various flow conditions. Initially, scour depth around the bridge pier was measured without vegetation elements, and afterwards vegetation elements were installed on the upstream side of the bridge pier to investigate maximum scour reduction. The result demonstrates that denser vegetation elements with a lower A/R value reduce scour depth significantly because of greater resistance to the flow. However, scour depth decreased by decreasing the G/d and A/R values from 2.85 to 0.71 and 18.5 to 7.45, respectively. A maximum scour reduction of 71.7% was observed by placing denser vegetation with A/R = 7.46 on the upstream side of the pier. The findings of the present research help to provide an eco-friendly solution for bridge pier scour mitigation.
  Keywords: bridge pier; scour; vegetation; aspect ratio; climate change.
  DOI: 10.1504/IJHST.2024.10066354
   
  
• In-situ bathymetry and discharge-based modelling for potential GLOF assessment of Gepang Gath Lake, Lahaul Himalaya, India  
  by Parmod Kumar, Swati Sharma, I.M. Bahuguna, Sanjay Deswal, Partibha, Jogender Singh 
  Abstract: The present study covers a vulnerable glacial lake known as Gepang Gath Lake in the Lahaul area of Himachal Pradesh, India. The field investigation was carried out to measure depth and discharge rate for analysing the probability of lake outburst hazard. The lake depth ranges between a minimum of 2m to a maximum of 48 m with an average depth of 19 m with a standard deviation of 13 as per the field surveys. The stream discharge of 10 m/s was measured near Sissu village valley lying downslope from the Gepang Gath Lake on 21 June 2021 in the afternoon. Snowmelt discharge from the temperature index model was compared with the stream discharge on a clear weather day plus the rainfall data of monsoon months (when the possibility for discharge is higher) was analysed and modelled in HEC-HMS software for peak precipitation discharge based on rainfall data of July and August. 1D flood modelling using glacial lake volume in HEC-RAS software was performed and finally, the resultant discharge (a combination of all three discharges from snowmelt, precipitation and lake volume) is 3,696 m3 /s. This resultant discharge is considered huge enough to affect the downstream and valley area with a high-intensity flood that can reach up to the Tandi village area.
  Keywords: Gepang Gath Lake; snowmelt; lake depth; discharge rate; HEC-HMS; HEC-RAS; India.
  DOI: 10.1504/IJHST.2024.10066536
   
  
• Evaluating the sensitivity of hydrological response to changes in vegetation classification: a case study of St. Charles Bay, Texas, USA  
  by Kaniz Farzana, Cade Coldren, Catherine Simpson, Theodore G. Cleveland, Joseph Young 
  Abstract: Hydrological modelling is dependent on accurate vegetation classification. We tested the sensitivity of hydrological predictions to classification errors by using the EDYS ecological model developed for St. Charles Bay watershed, Texas, USA. Three image-based computer classification methods (object-based, supervised, and unsupervised) were assessed against a detailed field-based survey by using global sensitivity analysis and RMSE. The objective was to evaluate relative impacts of each classification method on a range of hydrological variables and across rainfall extremes. Hydrological outputs of EDYS were strongly influenced by different classification methods and rainfall patterns, but no consistent patterns or trends emerged. Thus, no single classification method was universally superior, suggesting a complex interrelation between classification, hydrological variables, and climatic conditions. This research underscores the importance of method selection in hydrological modelling, and so care should be taken when choosing vegetation classification methods to properly address specific research or management objectives.
  Keywords: sensitivity analysis; hydrological processes; vegetation classification; object-based; supervised classification; unsupervised classification; ecological dynamics simulation; EDYS; coastal marsh; Aransas National Wildlife Refuge; ANWR; USA.
  DOI: 10.1504/IJHST.2024.10066620
   
  
• Evaluation of the effect of Hydrophobic Leca and Hydrophobic Perlite coating on the water evaporation reduction  
  by Roza Ghahramani Jajin, Mohammad Ghorbanpour 
  Abstract: The purpose of current research is to investigate the effect of hydrophobic Leca and hydrophobic Perlite coatings on reducing water evaporation. To achieve this goal, Pearlite and Leca were hydrophobicised with stearic acid. The properties of the prepared samples were analysed using BET (Brunauer Emmett Teller), FT-IR (Fourier-transform infrared spectroscopy), and thermo gravimetric analysis (TGA). The contact angle of hydrophobic Perlite and Leca was around 115 and 131, respectively. According to TGA results, the specific surface area of parent Leca and Perlite has decreased after hydrophobisation. FT-IR and TGA showed the presence of stearic acid on Pearlite and Leca, as well as the interaction between them. The synthesised hydrophobic coatings were stable for more than 100 days and remained floating on the water surface. The evaporation efficiency of hydrophobic coatings was investigated at different temperatures and in the presence of sunlight and wind. Hexadecanol, hydrophobic Leca, and Perlite prevent water evaporation by 31, 25, and 24%.
  Keywords: hydrophobic stones; evaporation reduction; reservoirs; Perlite; hexadecanol; Leca.
  DOI: 10.1504/IJHST.2025.10066668
   
  
• Rainfall prediction using soft computing techniques: a case study of Purna River Basin  
  by Darshan J. Mehta, Nisarg Nanavati, Sanjaykumar M. Yadav 
  Abstract: Rainfall is the most significant climate element affecting the livelihood and well-being. For a country like India whose economy depends on agriculture, accurate rainfall data is important. The main challenge is to build a model on a long-term rainfall prediction. The Purna River is main source of water for agriculture as well as domestic in Navsari District. The objective of the study is to predict rainfall with the help of soft computing technique. The studies are carried out using specifically artificial neural network (ANN). The first step in water resource management is the correct forecasting of rainfall. Accuracy was evaluated using mean square error method, and results showed that the artificial neural network (ANN) based prediction model showed an acceptable level of accuracy performance. To achieve these models are developed with the different input parameters namely humidity, temperature and wind speed. For the analysis, the dataset of 21 years periods (1999-2020) is used for training and testing. Model performance is evaluated using statical metrics such as mean square error (MSE). These findings hold the key to revolutionising water resources planning, flood preparedness and risk assessment in the region with potential applicability to similar regions worldwide.
  Keywords: rainfall prediction; water resources management; soft computing; Purna River Basin; artificial neural network; ANN.
  DOI: 10.1504/IJHST.2024.10066670
   
  
• Mitigation of local scour around a trapezoidal bridge abutment using sacrificial piles  
  by Sheraz Hussain, Ghufran Ahmed Pasha, Muhammad Ali Afridi, Nadir Murtaza, Khawaja Atif Naseem, Abdul Shakoor, Usman Ghani, Afzal Ahmed, Khaled Mohamed Khedher 
  Abstract: Scour poses a significant threat to the stability of bridge piers and abutments. This study investigates the effectiveness of sacrificial piles as a countermeasure to reduce scour around bridge abutments through laboratory experiments. The abutment was modelled in a trapezoidal shape, common in Pakistan, with circular sacrificial piles positioned upstream. The aspect ratio (AR) of the pile group varied between 0.75, 1.00, and 1.70, with the spacing between cylinders (G/d) set at 1.5, 2.14, and 2.84. Optimal scour reduction (40.26%) was achieved when the distance between piles and the abutment was increased up to six times the abutment width. The highest scour reduction (70.13%) occurred with a dense pile configuration (G/d = 1.5) and an AR of 0.75. The study also proposes a regression-based predictive equation and sensitivity analysis to estimate scour depth around bridge abutments in open flume conditions.
  Keywords: scour depth; bridge abutment; sacrificial piles; clear water condition; sensitivity analysis.
  DOI: 10.1504/IJHST.2024.10066826
   
  
• Assessment of flood controlling ability of hypothetical flood control dams by HEC-HMS model in catchment area of Koyna Dam in India  
  by Sanjay Doiphode 
  Abstract: Floods are major disasters that occur on a global scale. The construction of flood control dam (FCD) is considered sustainable, eco-friendly and effective flood control method due to its ability to quickly mitigate flood effects. HEC-HMS software has been successfully used by various researchers to simulate the rainfall-runoff correlation. The Koyna Dam in India is a conservation dam that was not designed for flood control. Due to the geographical nature and urbanisation of the area, it is difficult to implement traditional flood mitigation measures in Patan, Karad and Sangli City and its nearby area which is prone to flooding on downstream side of the Koyna Dam. Hence different approaches of implementing FCD in the watershed area of the Koyna Dam have been proposed to reduce the risk of flooding. In the Koyna watershed using spatial data and GIS software, 30 hypothetical FCD sites were identified and evaluated via HEC-HMS modelling. To quantify the effect of the provision of FCD, the flood attenuation ratio (FAR) and flood storage ratio (FSR) were used. The simulation results showed that the Koyna Dam watershed is conducive to the implementation of flood control dams. During heavy rainfall FCD will retain approximately 3.20 thousand million cubic feet (TMC) water, with an 11% reduction in flood volume approaching the dam and a 41% reduction in the peak inflow at the Koyna Dam.
  Keywords: HEC-HMS; flood control dam; FCD; Koyna dam; design storm; intensity duration frequency; IDF; morphometric analysis.
  DOI: 10.1504/IJHST.2024.10066827
   
  
• A systematic evaluation of time of concentration models in a predominantly agrarian catchment of Southeastern Nigeria  
  by Chidozie Charles Nnaji, Tochukwu Raphael Siwobi 
  Abstract: In order to accurately estimate peak discharge and subsequently determine the size of hydraulic structures, the time of concentration (TC) of the catchment must be accurately determined. This study was aimed at comparing the applicability of 15 carefully selected Tc equations to Ifite Ogwari catchment in Anambra State, Nigeria. The calculated values of TC were subjected to exploratory statistical analysis and sensitivity analysis. The Temez, Haktanir and Sezen and Chow equations gave the most representative values of TC of the sub-catchments with 100% of all TC values falling within the inclusion criteria of median +- 0.5 SD while returning the median TC three times each out of eleven catchments. The Pasini and Sheridan models were the worst performing with all the TC values calculated falling outside median
  Keywords: time of concentration; TC; runoff; catchment; QSWAT; Ifite-Ogwari.
  DOI: 10.1504/IJHST.2024.10066860
   
  
• Characterisation and dispersion simulation of brine discharge: case study of Al Hoceima Desalination Plant, Morocco  
  by Soukaina El Khalki, Abdellatif Lemhamdi, Mohamed Ghalit, Rachida Elbarghmi, Abdelhadi Makan 
  Abstract: The escalating water scarcity crisis in arid and semi-arid regions has led to the widespread adoption of desalination plants, offering a solution to meet the increasing demand for freshwater. In Morocco, the establishment of seawater desalination facilities, including the Al Hoceima plant, addresses the pressing need for potable water. However, the generation of brine as a by-product necessitates an in-depth examination of its impact on marine environments. This study focuses on analysing the physicochemical characteristics of brine discharged by the Al Hoceima Desalination Plant and simulating its dispersion in the marine environment using CORMIX software. The brine exhibited distinct differences from seawater, presenting elevated salinity, metallic elements, and slight variations in pH and turbidity. These disparities could potentially affect marine ecosystems, underscoring the importance of monitoring and mitigating brine discharge effects. Simulation modelling revealed specific patterns in brine dispersion, delineating the near-field and far-field zones with differing spatial and temporal characteristics. Understanding these dynamics aids in implementing discharge strategies to minimise ecological impacts. Various factors influencing brine dilution, such as discharge angle, water depth, and current velocity, were identified as crucial elements in determining brine behaviour in the marine environment.
  Keywords: desalination; brine discharge; marine environment; physicochemical analysis; environmental impact; CORMIX simulation.
  DOI: 10.1504/IJHST.2024.10066861
   
  
• Hydrology and sediment yield response to changes in land-use and climate in the Upper Blue Nile Basin, Ethiopia  
  by Lewoye Tsegaye, Rishikesh Bharti 
  Abstract: Environmental components substantially affected by climate and environmental disruptions are watershed-scale hydrology and soil erosion. This research assessed the effects of scenario-based climate and land use land cover (LULC) changes on sediment and hydrology using dynamic conversion of land-uses and its effects (Dyna-CLUE) and soil and water assessment tool (SWAT) in Gumara watershed of Ethiopia. Climate change was analysed using GCM-RCMs outputs under SRES A1B and representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5) from 20252099. Runoff, groundwater flow, lateral flow, and water yield decreased, whereas, evapotranspiration (ET) and sediment yield increased in both scenarios. Compared to LULC, climate change has a greater impact on reducing runoff (1933.6%, 1.737.9%) and water yield (15.133.6%, 7.241.4%) in A1B and RCPs respectively. Rapid LULC conversion resulted in a significant increase in sediment yield up to 71.9% in A1B and 84.3% in RCPs.
  Keywords: climate prediction; LULC change scenario; RCPs; sediment output; surface runoff; water balance.
  
  
• Water balance analysis of a typical temporary pond in the Flooding Pampa (Argentina) during a dry period  
  by Ninoska Briceño, Ilda Entraigas, Carlos Scioli, Martin Blanco 
  Abstract: Knowledge of wetlands water balance constitutes a tool that allows quantitative evaluation of water dynamics. The Flooding Pampa (Argentina) is characterised by scarce topographic slopes and significant development of temporary ponds. A water balance was performed for analysing the dynamics of a Pampasic pond. During the analysed period, water inputs into the pond originated primarily from surface runoff from the surrounding areas and, secondarily, from direct precipitation; while the outputs were mainly due to runoff through the outlet channel and evapotranspiration, since the underground flow was almost insignificant. The latter parameter also had the particularity that it was expressed only unidirectionally (from the pond to the aquifer). Vertical processes (precipitation, evapotranspiration and infiltration) contributed to 38% of the balance, compared to horizontal processes (surface runoff) that represented 62%. The results serve as a basis for facing the study of the response of these systems in different scenarios.
  Keywords: water balance; temporary pond; Flooding Pampa; wetland; plain; Argentina; hydrology; dry period; water dynamics; aquifer.
  DOI: 10.1504/IJHST.2025.10067534
   
  
• Analysis of flood severity using intelligent deep networks and sentinel image for the Kerala region  
  by Supriya Kamoji, Mukesh Kalla 
  Abstract: Accurate flood prediction and the classification of severity levels are vital for assessing the impact of floods and ensuring the safety of affected populations. Despite introducing numerous systems, many existing models require significant time to generate prediction results. Intelligent techniques like neural networks have been proposed to enhance prediction accuracy to address this. However, the complexity of data sources, such as satellite or sentinel data, poses challenges due to their unstructured nature and noisy attributes. This study introduces a pioneering approach known as the virtual bee-based recurrent model (VBRM) for flood prediction and severity classification. Specifically, the model categorises floods into low, medium, and high severity levels. The initial step involves gathering sentinel data related to the floods in Ernakulum, Kerala. This data is then used to train the VBRM, followed by a pre-processing stage that effectively filters out irrelevant features and noise. Subsequently, the refined data is fed into the classification layer, where the model extracts pertinent features and determines the severity level of floods. The ultimate objective is to achieve high prediction accuracy with minimal errors. Various performance metrics are employed and a comparative analysis is conducted against other existing models to evaluate the model's performance.
  Keywords: deep networks; feature extraction; flood severity classification; optimisation; sentinel data; virtual bee-based recurrent model; VBRM.
  DOI: 10.1504/IJHST.2025.10067872
   
  
• Investigating the effect of watershed management on land use, groundwater recharge, and irrigation potential in Tigray region, northern Ethiopia  
  by Tsige Yenalem, Yilma Kidanie, Ahmed Mohammed Degu, Teame Yisfa 
  Abstract: This study was conducted to investigate the effect of watershed management on groundwater recharge and irrigation expansion in northern Ethiopia. The GIS-based water and energy transfer between soil, plants, and atmosphere under the quasi-steady state (WetSpass) hydrological model was implemented. Two scenarios, before watershed management (1997-2007) and after watershed management (2008-2018), were investigated. After watershed management, groundwater recharge increased from 9.7, 44.4, and 54.15 mm for dry, rainy, and annual conditions, respectively, to 9.9, 96.2, and 106.13 mm for these conditions. The relationship between calculated and observed groundwater depths results in a coefficient of determination of 0.81. After watershed management, the water balance system had evapotranspiration, surface runoff, and groundwater recharge of 83.7%, 3.0%, and 13.3%, respectively, of total precipitation. Excess groundwater recharge of 6.51% resulted in extending the irrigation area by 12.7 hectares. Results show that WetSpass is effective in estimating groundwater recharge and irrigation area expansion.
  Keywords: groundwater recharge; hydrology; water balance; watershed management; WetSpass; Ethiopia.
  DOI: 10.1504/IJHST.2025.10067873
   
  
• Solute transport with decay type input source in one-dimensional heterogeneous groundwater: analytical solution  
  by Premlata Singh, Gulrana, Arun Dubey, Dilip Kumar Jaiswal 
  Abstract: The process of aquifer remediation extends with the growing dependence on groundwater. Mathematical model of solute transport in porous media is important tool used to characterise the extent of approximating the shape, size and position of a contaminant. In the present study, an unsteady solute transport model advection-diffusion equation (ADE) is taken and analytical solutions were obtained by using Laplace integral transformation technique (LITT). The concentration is predicted in presence and absence of source, i.e., firstly initially medium (aquifer/air) is not supposed to be solute free, i.e., initially domain is already polluted/contaminated and secondly the medium is clean, taking decay type exponential input at origin. The dependence of velocity on space variable is of linear non-homogeneous nature due to heterogeneity of the semi-infinite horizontal dispersion medium. The dispersivity is considered square of the velocity which represents the seasonal variation of the year in tropical regions.
  Keywords: advection-dispersion equation; groundwater; heterogeneity; pollution; semi-infinite medium.
  DOI: 10.1504/IJHST.2025.10067891
   
  
• Analysing of rainfall-runoff modelling using a hybrid DNN-SGD optimisation in Sub Basin of Brahmaputra River, India  
  by Subha Sinha 
  Abstract: The main objective of this research is to improve the accuracy of runoff prediction and assess the effectiveness of the proposed DNN-SGD model. The performance of the DNN-SGD model is evaluated using standard metrics, including the coefficient of determination (R²), mean squared error (MSE), and root mean squared error (RMSE). The significance of findings demonstrating the superior performance of the proposed DNN-SGD model compared to other widely used methods, including ANN, DNN, ANN-PSO, and ANN-SGD. The results indicate that the DNN-SGD model achieved a remarkably high R² of 0.99998, indicating its ability to capture a large proportion of the variability in the observed data. Moreover, it obtained the lowest RMSE value of 0.002252 and MSE value of 0.000507, further confirming its superior accuracy and predictive capabilities. Overall, this study providing an advanced rainfall-runoff modelling approach for water resource management in the Brahmaputra River Sub Basin and other similar regions.
  Keywords: rainfall; runoff; flood; deep neural network; DNN; stochastic gradient decent; SGD; Brahmaputra River; ANN PSO; water management; India.
  DOI: 10.1504/IJHST.2025.10067892
   
  
• Estimation of groundwater recharge in Southern Ghana  
  by Delaiah Antwi Nyarko, Larry Pax Chegbeleh, Elikplim Abla Dzikunoo, Edward Kofi Ackom, Sandow Mark Yidana 
  Abstract: The rainfall infiltration breakthrough (RIB) model has been applied to estimate groundwater recharge over parts of the saprolite aquifer unit in Southern Ghana. This method relies on rainfall and groundwater level data monitored simultaneously over a period, and properties of the aquifer material. The water table fluctuations (WTF) technique was applied independently to validate the results of RIB technique. Both methods were executed based on specific yield (Sy) values in the range of 1%-5%. The results suggest a wide range of variations in groundwater recharge rates over the terrain. Groundwater recharge rates fall in the range of 0.58%-21.36% of annual precipitation based on the RIB. The results indicate that the lag period between rainfall and eventual groundwater recharge ranges between 0 and 9 months, depending on the thickness and content of the unsaturated zone. Estimates of groundwater recharge suggest variably good fortunes for groundwater.
  Keywords: RIB model; WTF method; groundwater level fluctuation; groundwater recharge; shallow unconfined aquifer; saprolite aquifer system; lag time; lag length.
  DOI: 10.1504/IJHST.2024.10062601
   
  
• Evaluation of mesoscale physical habitats in sediment and water quality improvement - a mesocosm study for urban canals  
  by Sanjana De Zoysa, Kurugama A.T. Chandeep, Pathirathne H.D.R. Pathirathne, Pattiyage I.A. Gomes 
  Abstract: This study investigated the applicability of different types of attenuation processes (i.e., aeration and stirring) with and without dilution in nutrients (nitrogen and phosphorous) and sulphide-polluted sediment cleanup via laboratory mesocosms. Attenuation refers to the decline in contaminant concentration, a phenomenon driven by processes like dilution, mixing, and dispersion. Dilution, a remedial method involving the blending of contaminated water with uncontaminated often happens with uncontaminated runoff or a tributary. Regardless of the seasons, aeration, stirring, combined aeration and stirring, and dilution generally resulted in better removal efficiency of pollutants. Aeration combined with stirring showed notable improvements across multiple water quality parameters, and parameters seemed to be treatment type dependent, but without any significant differences. Dilution reduced electrical conductivity and increased dissolved oxygen but did not influence ammoniacal nitrogen and phosphate. The energy consumption for a unit percentage improvement via aeration and stirring was 0.04-0.25 USD and 0.03-0.15 USD, respectively. Therefore, relying solely on attenuation processes without dilution is deemed economically infeasible in real or prototype applications. This research sheds light on potential applications including pros and cons, emphasising the need for a balanced approach, and setting the stage for future studies.
  Keywords: aeration; dilution; energy; mesocosms; mesoscale physical habitats; sediment; stirring; water quality.
  DOI: 10.1504/IJHST.2025.10067874