International Journal of Hydrology Science and Technology (41 papers in press)

Regular Issues

• Geostatistical analyses empowered with gradient boosting and extra trees classifier algorithms in the prediction of groundwater quality and geology-lithology attributes over YSR district, India  
  by Mogaraju Jagadish Kumar 
  Abstract: Machine learning classifiers are integrated with the geostatistical analyses through interpolation techniques to predict groundwater quality and geology-lithology. Ordinary kriging is used to obtain the optimal interpolation model using RMSSE values. The data extracted from the surface maps were passed onto ML algorithms, resulting in prediction accuracies of 99% for groundwater quality and 96% in predicting the geology-lithology features. There was certain overfitting in the prediction and it was probably due to several classes of geology-lithology variables and limited data available for analysis. The interpolation methods might affect the model performance by producing overfiting and underfitting results. It is to report that the gradient boosting classifier yielded relatively high prediction accuracies in predicting groundwater quality when two classes were used. The extra trees classifier returned better results in predicting geology-lithology features when multiple classes were used in this study.
  Keywords: machine learning; geostatistics; groundwater quality; gradient boosting classifier; extra trees classifier; India.
  DOI: 10.1504/IJHST.2022.10050042
   
  
• Comparison features importance for temporal and spatial-temporal approaches in GRACE and GRACE-FO signal re-construction based on GLDAS data  
  by Viktor Szabó 
  Abstract: Machine learning algorithms can effectively learn the complex relationships between various input variables from the global land data assimilation system (GLDAS) and the total water storage (TWS) observed by gravity recovery and climate experiment (GRACE) and GRACE-FO (follow-on) missions. As the TWS depends on various features, a serious question arises about the importance of used variables for reconstruction. Furthermore, will the variables used for the reconstruction be equally significant for grid-based and basin-based analyses? This work examined the importance of individual predictors for the temporal and spatial-temporal approach over 254 river basins using GRACE and GRACE-FO data as target and GLDAS data as predictors. The extreme gradient boosting (XGBoost) algorithm was used to reconstruct TWS. Results were evaluated with root-mean-square error, normalised root-mean-square error, Pearson correlation coefficient, Nash-Sutcliffe efficiency, and Kolmogorov-Smirnow-test metrics. Model output influence was checked by the model-agnostic version of the feature importance and by Shapley additive explanations (SHAP).
  Keywords: total water storage; TWS; global land data assimilation system; GRACE; GRACE-FO; features importance; extreme gradient boosting; XGBoost; Shapley additive explanations; SHAP.
  DOI: 10.1504/IJHST.2022.10048532
   
  
• Long term trend analysis on precipitation in Ajmer district of Rajasthan State, India  
  by Jinal H. Pastagia, Darshan J. Mehta 
  Abstract: The research focuses on long-term patterns of climatic variability, such as precipitation. Rainfall trends in the Ajmer region were assessed using the Mann-Kendall (MK) test, Sens slope estimator, and the innovative trend analysis (ITA) technique on various time scales. Monthly precipitation data were used for the period of 121 years, i.e., 1901-2021. Trends (1901-2021) was assessed at the 5% significant level using a statistical trend analysis method called the MannKendall test. Mann-Kendall trend analysis result reveals an insignificant increase in the region of Ajmer district. At any time, series across the Ajmer district, there is no clear increase or decrease trend. According to the results of the ITA test, all four seasons and annual trends indicate decreasing. Almost all the significant trends identified using the M-K method were excellently recognised by the ITA method. The finding of the study will be useful to understand the risks and vulnerabilities of seasonal and annual precipitation under climate change scenarios in the region.
  Keywords: climate change; innovative trend analysis; ITA; Mann-Kendall test; precipitation; Sen's slope estimator.
  DOI: 10.1504/IJHST.2022.10048587
   
  
• Artificial neural network for modelling the sediments accumulation in Es-Saada reservoir (North-Western Algeria)  
  by Mustapha Sidi Adda, Djilali Yebdri, Djilali Baghdadi, Sarita Gajbhiye Meshram 
  Abstract: Sediment deposition represents an important aspect of dam reservoir exploitation and management, as it relates to several operational and environmental problems. This study aimed to model the spatiotemporal evolution of the sediment accumulation in the Es-Saada reservoir (North-Western Algeria) using an artificial neural network (ANN) under low data conditions. The ANN model calibration was applied to the chronological period between the bathymetric surveys in 1986 and 2000, and the model verification was performed using data from a third survey conducted in 2003. The simulation of the reservoir bed presented acceptable results compared to the measured data (mean error of 7.76%). The model can provide predictive capacity curve for an average gap of 0.068 to the real curve, with a signification of 93.2%. It would be concluded that using determinist models for predicting sediment accumulation in reservoirs is complicated and needs all system details, while the application of ANN presents an adequate and uncomplicated method for predicting sediment distribution in dam reservoirs and also reservoir volume reduction in an approximate way.
  Keywords: sediments accumulation; artificial neural network; ANN; sedimentation modelling; Es-Saada reservoir; sediment discharge; Algeria.
  DOI: 10.1504/IJHST.2022.10048616
   
  
• Developing rainfall intensity-duration-frequency curves for Dodola catchment to estimate peak discharge using frequency analysis  
  by Takele Sambeto Bibi 
  Abstract: The development of intensity-duration-frequency (IDF) curves is one of the most common and useful tools to estimate peak discharge. The purpose of this study was to develop the IDF curves for five selected stations in the Dodola catchment. The Ethiopian Road Authority (ERA) reduction empirical formula was used to estimate the short-duration rainfall intensity from daily rainfall data. The L-moment ratio diagram and three goodness-of-fit tests were used to identify the best-fit probability distribution. The IDF curves that were constructed using regionalised distribution were compared with at-site IDF curves. The difference between the two sets of IDF curves small differences, also, shows the same trend for all selected return periods. These IDF curves will help in the estimation of peak discharge in the catchment.
  Keywords: probability distribution; IDF curves; peak discharge; Dodola catchment.
  DOI: 10.1504/IJHST.2022.10048737
   
  
• Understanding efficient seawater intrusion assessment in coastal region of India: a methodological review  
  by Zalak Bhavsar, Jayeshkumar Patel 
  Abstract: India is fortunate to have a long length of coastline. In addition to the numerous villages and industrial communities, many of the country’s metropolitan centres are situated along the coastline. Saltwater intrusion is the migration of salty water into freshwater coastal aquifers, resulting in groundwater quality degradation. Land-use changes, climate change, and sea-level rise are the most significant contributing causes to saltwater intrusion in coastal aquifers. Coastal saline water intrusion has a broad range of impacts on the community and financial systems, in addition to the area’s overall ecosystem, prompting many studies. According to the research, saline soils cover around 70 thousand square kilometres in India, including about 21,000 square kilometres in coastal regions. It is imperative to understand the extent of seawater intrusion in order to plan and manage mitigation measures towards sustainable development. The objective of this paper is to derive an insightful review of the methods, i.e., hydrogeochemical assessment, geophysical assessment and numerical modelling; used to tackle the pertaining issue of seawater intrusion.
  Keywords: coastal aquifer; geophysical method; geophysical method; hydrogeochemical method; seawater intrusion; India.
  DOI: 10.1504/IJHST.2022.10048738
   
  
• A framework for the evaluation of MRP complex precipitation in a CORDEX-SA regional climate applied to REMO  
  by Shashikant Verma, A.D. Prasad, Mani Kant Verma 
  Abstract: In this study, rainfall patterns are depicted using 16 regional climate models of seasonal monsoon across the Mahanadi Reservoir Project (MRP) Complex region from 1980 to 2005. Bias correction and different statistical analyses were used to evaluate the model's degree of uncertainty and model performance with the relevant observations, respectively. The purpose of this study is to: 1) compare the capability of regional climate models (RCMs) in reproducing seasonal monsoons; 2) climate change impact in the near future (2021-2046), mid-future (2047-2072), and far-future (2073-2098) over the study area. The seasonal monsoon rainfall under two different RCPs (RCP 4.5 and 8.5) was used to test the experiments and data's ability. Among 16 Coordinated Regional Climatic Downscaling Experiment (CORDEX) models, the REgional MOdel (REMO 2009) has a higher R2(i.e., 0.610). Therefore, such studies assist to analyse the impact of monsoon rainfall on different sectors and responding to climate change.
  Keywords: CORDEX-South Asia; MRP complex; regional climate model; RCM; bias correction; statistical analysis.
  DOI: 10.1504/IJHST.2022.10049165
   
  
• Probabilistic flood risk assessment using coupled hydrologic and 2-D-hydraulic model in the Jhelum River, Northwest Himalayas  
  by Saika Manzoor, Manzoor Ahmad Ahangar 
  Abstract: Keeping in mind the susceptibility to flooding-related disasters in the past, the need was identified for flood risk assessment using recent modelling techniques in the data-scarce River Jhelum, India. This study conducted a preliminary rainfall frequency analysis to find the best fit statistical model for calculating peak flow rates for multiple return periods. A framework was followed for the spatio-temporal delineation of flood-prone areas by integrating the watershed modelling system (WMS), Hydrologic Engineering Center-Hydrologic Modelling system (HEC-HMS), and two-dimensional Hydrologic Engineering Center-River Analysis System (2-D HEC-RAS) for different return period design floods. The 2-D unsteady state flood modelling in HEC-RAS showed the river overflowing its flow path for all the return periods, with 55% of the Srinagar city inundated in the 100-year event. The simulated flood depths and velocity maps for every design flood scenario are shown. The 2-D simulations yielded encouraging results compared to the most recent flood event.
  Keywords: hydrologic modelling; 2D hydraulic modelling; floodplain delineation; 2D HEC-RAS; River Jhelum.
  DOI: 10.1504/IJHST.2022.10050494
   
  
• Application of deep learning algorithm in hydrometry  
  by Mohammad Zakwan, Shaik A. Qadeer, Mohammed Yousuf Khan 
  Abstract: Estimation of discharge in a river is an integral part of water resource engineering. In this regard various artificial intelligence (AI) techniques have been employed to model the discharge ratings. The present work compares the performance of two neural network namely back propagation neural network (BPNN) and radial basis neural network (RBNN) to model the discharge rating. The estimated discharge was also compared with the discharge estimated using conventional method. Published data of two gauging station was used for the comparative analysis. It was observed that application of neural networks greatly improved the estimates of discharge as compared to conventional method. Application of artificial neural network (ANN) reduced the sum of square of error (SSE) by about 90% on an average. Maximum absolute error reduced from 51.36 and 141.21 to 5.04 and 7.68 respectively for the two stations for RBNN when compared to conventional method during validation. Calibration results reveal that among the BPNN and RBNN, RBNN could model the ratings at both the stations, better than BPNN.
  Keywords: hydrometry; discharge; river; ratings; neural networks; back propagation neural network; BPNN; radial basis neural network; RBNN; artificial neural network; ANN; sum of square of error; SSE.
  DOI: 10.1504/IJHST.2022.10050564
   
  
• A software for water pollution treatment technology evaluation by supporting customisable indicator systems for specific scenarios  
  by Bo Song, Chen Chen, Rongrong Kou 
  Abstract: Determining the best water pollution treatment technology (WPTT) is one of the biggest challenges in water pollution management. We proposed the point of specific evaluations for specific scenarios to select appropriate technologies that can improve the efficiency of water pollution treatment. This point refers to establishing specific indicator systems for water pollution treatment technology evaluation (WPTTE) for specific scenarios. A software was developed to achieve specific evaluations for specific scenarios by supporting the rapid construction of customised indicator systems. The functions of this software include data management, indicator system matching, visualising construction of indicator systems, comprehensive evaluation and graphic display. In addition, the software was demonstrated by an example of ammonia nitrogen wastewater treatment technology selection. The software can meet the demands of multi-scene and multi-role evaluation and make the establishment of indicator systems more straightforward and effective. The study provides a solid foundation for specific evaluations for specific scenarios.
  Keywords: water pollution; treatment technology; technology evaluation; specific evaluations for specific scenarios; indicator system; analytic hierarchy process; AHP; evaluation software.
  DOI: 10.1504/IJHST.2022.10050837
   
  
• River discharge estimation in the Punatshangchu River Basin, Bhutan using an integrated flood analysis system  
  by Damudar Dahal, Parmanand Kumar, Ramesh Chhetri, Rocky Talchabhadel, Chandra Man Rai 
  Abstract: Predicting river discharge is essential for managing water resources, contributing to the economy, and minimising associated hydrologic risks. Despite the manifold importance of a sound understanding of river discharge, the rugged geography of Bhutan makes installing sophisticated water discharge measuring equipment challenging. Using an integrated flood analysis system - a non-structural method - is used to calculate the river discharge of the Punatshangchu River Basin. The two tank configuration hydrologic model was applied through parameterisation, calibration, and validation and was forced using rainfall data. The maximum observed discharge was 1,532 m3/s and the minimum was 58 m3/s. The validated simulation model showed a maximum discharge of 1,522 m3/s and a minimum discharge of 138 m3/s, respectively. The simulated result overestimates the low flow and underestimates the high flow. A Nash-Sutcliffe efficiency of 0.7626 was achieved, indicating a satisfactory level of estimation. The study found that the IFAS model can predict river discharge in a data-scarce environment.
  Keywords: integrated flood analysis system; IFAS; model calibration; Punatshangchu River Basin; PRB; river discharge; simulation; Bhutan.
  DOI: 10.1504/IJHST.2022.10051274
   
  
• Long-term spatial and temporal trend analysis of stream flow and suspended sediment transport of Godavari River Basin, India  
  by Madhura C. Aher, S.M. Yadav 
  Abstract: Long-term spatial and temporal variations of stream flow and suspended sediment discharge of rivers are important for effective planning of available water resources and soil conservation measures. In present study the gradual and abrupt change in stream flow and suspended sediment discharge at 21 stream gauging stations which are located on the Godavari River were analysed for the period of 1969 to 2015 (46 years). The Mann-Kendall (MK) trend test and Pettitt test is used to detect the gradual and abrupt change respectively. The results of MK test indicates that 76% stations shows decreasing trend in stream flow, whereas 90% stations shows decreasing trend in suspended sediment discharge. The Abrupt change is reported in the early and middle period of 1990 to 2000. The significant decreasing trend in stream flow and sediment discharge is due to the construction of extensive dams, land use change and rainfall pattern.
  Keywords: Godavari Basin; stream flow; suspended sediment discharge; trend; change point.
  DOI: 10.1504/IJHST.2022.10051376
   
  
• Developing rainfall intensity-duration-frequency curves at the western flank of Mt. Merapi, Indonesia  
  by F. Tata Yunita, Indratmo Soekarno, Joko Nugroho, Untung Budi Santosa 
  Abstract: The intensity and frequency of extreme events are continuously increasing due to climate change, leading to a rise in flood probability. Considering flood discharge by connecting the recent rainfall data is critical. This research aims to provide temporal characteristics of rainfall intensity in the western flank of Mt. Merapi. The 10-, 20-, 30-, 40-, 50-, 60-, 120-, 180-, 360-, and 720-minutes annual maximum rainfall data from 5 stations were used to develop the intensity-duration-frequency (IDF) curves by using Logarithmic and power equations. Distribution frequency analysis was carried out using extreme value type-I, normal, lognormal, Pearson type-III, and log Pearson type-III methods. The results showed that the proposed model is satisfying for short-duration rainfall of less than 360-minutes with R-values of more than 90%. These alternative IDF curves based on short-duration rainfall data significantly improve the accuracy of lahar flood mitigation measures in Mt. Merapi.
  Keywords: short-duration rainfall; IDF curve; mountainous region; lahar flood.
  DOI: 10.1504/IJHST.2022.10051623
   
  
• Univariate streamflow forecasting using deep learning networks  
  by R. Yamini Priya, Manjula R 
  Abstract: Streamflow plays a vital role when deciding on water resource planning and management. According to data resources and their availability, streamflow prediction for different regions has been made so far using distinctive models, such as physically-based hydrologic models, statistical models and machine learning algorithms. This article describes the applications of recently generated deep learning N-BEATs algorithm by modifying the basic structure with nonlinear predictor coefficient and long short-term memory (LSTM) for univariate streamflow forecasting in the Ponnaiyar River Basin. To develop the model, the model utilised the data of three streamflow stations that contain 40 years of Villipuram discharge and 36 years of Gummanur and Vazhavachanur discharge. The experimental analysis is performed to analyse the performances of the proposed model. From the results, both models performed well during the training and validation period. Similarly, the accuracy estimation of validation conducted by N-BEATs and LSTM Nash-Sutcliff efficiency for upstream (0.827 and 0.792) and midstream (0.9407 and 0.865) have revealed that the modified N-BEATs accomplished superior outcomes than LSTM, respectively. It is concluded that the proposed N-BEATs model can be applied for univariate streamflow forecasting which simplifies the data complexity for model establishment.
  Keywords: deep learning networks; streamflow; water resource planning; annual rainfall; forecasting; root mean square error; RMSE.
  DOI: 10.1504/IJHST.2022.10051827
   
  
• Numerical modelling of groundwater flow in Nambiyar river basin  
  by S.P. Rajaveni, R.V. Archana, B. Saranya, P. Shakthi Priyadharshini 
  Abstract: Coastal aquifers are groundwater resources that connect land and sea. Coastal aquifers supply freshwater to almost one billion people who live near the coast and interact with coastal risks as well as coastal ecosystems. On a regional and global scale, coastal groundwater runoffs should pay more attention to the balance between water and solutes. The objective of this paper is to simulate the dynamics of groundwater discharge along the Nambiyar river basin coastal shoreline. A three-dimensional groundwater flow equation was used to estimate the groundwater discharge along the shoreline from December 2010 to December 2018. By adjusting aquifer parameters within the permitted range, steady state calibration was performed to match the observed and simulated groundwater heads. The study results show that the quantity of groundwater discharge is high during the month of August compared to the month of April.
  Keywords: groundwater discharge; groundwater model; Nambiyar river basin; finite element model.
  DOI: 10.1504/IJHST.2022.10052059
   
  
• Study rainfall intensity duration frequency relationships under climate change for design of efficient urban stormwater drainage systems in Dodola town, Ethiopia  
  by Takele Sambeto Bibi, Nebiyu Waliyi Tekesa 
  Abstract: The variability in rainfall intensity caused by climate change has an impact on the efficiency of urban stormwater drainage systems. Therefore, this study presents the relationships between rainfall intensity and climate change using the global climate models MIROC-ESM, HadGEM2-ES, and CanESM2 under two representative concentration pathway scenarios (RCP4.5 and RCP8.5). The future projected daily rainfall was extracted and bias-corrected using the python scripts. The results show that the highest intensity of rainfall for a 100-year recurrence period in a 5-minute duration is 201.2 mm/hr. The relative difference between the RCP4.5 climate change scenario and historic rainfall ranges between 25.1% and 36.3% for the 2030s, 3.0% and 81.4% for 2050s, and 1.5% and 58.6% for 2080s, respectively. Similarly, the difference between the climate change scenario and historic rainfall for the 2030s ranged from 13.9% to 49.8%, with an average value of around 25.1% in the case of RCP8.5. As a result, the investigation of rainfall intensity relationships due to climate change will be used to design efficient drainage systems.
  Keywords: climate change; CanESM2; rainfall intensity; relative difference.
  DOI: 10.1504/IJHST.2022.10052154
   
  
• Optimal operation of the multi-reservoir system: a comparative study of robust metaheuristic algorithms  
  by Shashikant Verma, A.D. Prasad, Mani Kant Verma 
  Abstract: In a multi-reservoir system, the functioning of one reservoir affects the other reservoirs. A multi-reservoir system must be managed as a single entity for sustainable water management. Thus, assessing a multi-reservoir system’s existing operating policy is crucial for integrated operation. In this study, the recently introduced grey wolf optimisation (GWO) was compared to the robust metaheuristic algorithm the whale optimisation algorithm (WOA). First, the performance of these algorithms was evaluated and compared for multi-reservoir system operation optimisation. The statistical indices coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), mean square error (MSE), normalise mean square error (NMSE), and mean absolute percentage error (MAPE) were used to compare the algorithms’ performance. According to the test findings, among the ten algorithms evaluated. GWO was shown to be the most effective, and it is suggested as a reliable and promising technique for optimising multi-reservoir systems.
  Keywords: metaheuristic algorithm; multi-reservoir system; Mahanadi reservoir project; grey wolf optimisation; GWO; whale optimisation algorithm; WOA.
  DOI: 10.1504/IJHST.2022.10052274
   
  
• Groundwater quality evaluation in Enugu Metropolis, Southeastern Nigeria: a medical hydrogeological approach  
  by Michael Emeka Okechukwu, Ikenna Onyekwelu, Emeka Leonard Ndulue, Emmanuel Amagu Echiegu, Felix Uzochukwu Asoiro, Vintus Ogwo, Uche Jenice Chiwetalu 
  Abstract: Groundwater has proven to be a valuable resource for the local population of developing countries. Medical hydrogeology, a concept that primarily studies the positive and negative health effects of minerals in water has rarely been studied in Nigeria. Hence, we quantified the percentage of recommended daily intake (RDI) of calcium (Ca), magnesium (Mg), and chloride (Cl-) in connection with groundwater physicochemical parameters occurring in groundwater wells found in Enugu Metropolis, Nigeria. The results showed that groundwater wells in the metropolis are deficient in Ca, Mg, and Cl- minerals. Even though the groundwater physicochemical parameters were within the WHO limits, lead (Pb) and acidic pH concentrations exceeding the WHO limits were observed in over 80% of sampled locations. Consequently, we conclude that groundwater in the metropolis is not a good source of Ca, Mg, and Cl- intake and harbours noxious Pb and pH levels.
  Keywords: medical hydrogeology; groundwater; toxicants; minerals; calcium; magnesium; chloride; health.
  DOI: 10.1504/IJHST.2023.10053225
   
  
• Climate change and its impact on streamflow in the upper Blue Nile River Basin, Ethiopia  
  by Gizachew Kassa, Ayenew Desalegn, Anirudh Bhowmick 
  Abstract: To reduce uncertainty in climate projection and accompanied stream flow prediction, three CMIP5 climate models ensemble mean outputs of baseline and scenarios (RCP4.5 and 8.5) combined with HEC-HMS4.2 hydrological modelling of three large sub-basins were applied to estimate impact of climate change on streamflow of upper Blue Nile River Basin, Ethiopia. Mean annual, seasonal climate and streamflow changes were assessed for each sub-basin. Rainy season (June to September) precipitation becomes enhanced, while it becomes reduced during other seasons, hence mean annual decreased relative to historical. Average wet and dry season runoff change ranges from +67% to -52.16% and +62.6% to -59% under RCP4.5 and RCP8.5 during the mid-term (2050s), while during long-term (2080s) changes from +61.3% to -57% and +78.3% to -53.6% across three sub-basins. The projected mean annual streamflow showed a decrement of 10.6% for Kesse and Belles sub-basins and an increment of up to 25% for Didessa sub-basin.
  Keywords: climate change; streamflow; water resource; Blue Nile River Basin.
  DOI: 10.1504/IJHST.2023.10053425
   
  
• Groundwater drought assessment in Southwestern Bangladesh  
  by Noor- E-Ashmaul Husna, Sheikh Hefzul Bari, G.M. Tarekul Islam, A.K.M. Saiful Islam 
  Abstract: Globally, groundwater level depletion (groundwater drought) is a major issue. This issue is spreading throughout Bangladesh and poses an ongoing threat to safe water access. To comprehend the groundwater drought scenario in Bangladesh’s salinity-prone southwestern coastal region, we employed a threshold level technique. The drought scales are determined using three threshold levels (170%, 190%, and 195% of mean water level). Findings indicate that the region has experienced moderate to severe drought in the past. Moderate drought periods often last two to three months. It is anticipated that occurrences of groundwater drought would advance the current salinity front further upstream.
  Keywords: groundwater; drought; Bangladesh; coastal Bangladesh; groundwater drought index; threshold level; water deficit.
  DOI: 10.1504/IJHST.2023.10053456
   
  
• Effects of the 2018 and 2019 floods in Kerala, India on the existing multivariate statistical models  
  by P. G. Dileep Kumar, Narayanan Viswanath, Sobha Cyrus, Benny Mathews Abraham 
  Abstract: The state of Kerala, India, experienced severe flood events during August 2018 and 2019. The aim of this paper was to study the post-flood relevance of the multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) models formed before floods, for Kozhikode city, Kerala, India. For this, water samples were collected from 49 different locations in the above city, in September 2019. Both the existing MLR and ANFIS models were found to be less effective on post-flood data. Hence, new MLR, structural equation (SE) and ANFIS models were formed separately for severely and less severely flood-affected samples by performing bootstrapping to address the problems caused by the small datasets. The root mean square error (RMSE) and Lorenz curve were used to analyse the performance of the models. It was observed that ANFIS models performed better than MLR models.
  Keywords: flood events; statistical modelling; multiple linear regression; adaptive neuro-fuzzy inference system; structural equation modelling.
  DOI: 10.1504/IJHST.2023.10053898
   
  
• Inventory and status of glaciers in the Pir Panjal Range Kashmir basin between 1980 and 2020  
  by Mohmad Ashraf Ganaie, Syed Kaiser Bukhari 
  Abstract: The study aims to investigate watershed-wise glacier inventory, their observational changes and topographic influence on the glaciers in the Pir Panjal Range of the Kashmir basin from 1980 to 2020. In total, 122 glaciers (0.01 km2-0.96 km2) were mapped from 2020 image with a mean size of 0.13 km2. The glaciers have shrunk from 25.74 km2 in 1980 to 15.91 km2 in 2020, with an area loss of 9.83 km2. The Vishaw watershed hosts the maximum number of glaciers (55) and observed the highest glacier loss (6.1 km2) during the period. The results revealed that there is a strong topographic influence on the recession of the glaciers. Smaller glaciers (?0.5 km2) have receded more (~38.89%) as compared to the larger glaciers (>0.5 km2). South facing glaciers observed higher glacier loss as compared to North facing glaciers. Furthermore, high-altitude glaciers (<3800 m amsl and 3800-4000 m amsl) have witnessed higher recession than low-altitude glaciers. Glaciers having steep slopes of (> 20) experienced lower recession compared to glaciers having gentle slopes (< 20).
  Keywords: Google earth engine; GEE; remote sensing; glacier recession; topographic parameters; Pir Panjal Range.
  DOI: 10.1504/IJHST.2023.10054107
   
  
• Performance assessment of two semi-distributed and lumped hydrological models in the Peruvian Andes  
  by Víctor Oscar Rendón Dávila, Albert Johan Mamani Larico, Gabriel Fabricio Mejia Medina, Ángela Milagros Figueroa Tapia, Deysi Ivani Yana Quispe, Lady Nathaly Constancio Vilca, Vanessa Rossa Hilario Coaguila, Sebastián Adolfo Zúñiga Medina 
  Abstract: The high demand for water resources in the Peruvian Andes requires simple and available tools for decision-making. In our study, the lumped Temez model and soil and water assessment tool (SWAT) model were used in the El Pane Basin. The performance of both the models was reasonably good. The SWAT model showed less uncertainty, whereas the Temez model showed a better percent bias. Using the Penman-Monteith actual evapotranspiration model from SWAT, the evapotranspiration/precipitation ratio showed an increase in variability in the last decade and a decreasing trend during drought periods. The soil water content was well-represented by the normalised difference vegetation index and the land surface temperature index owing to the high correlations between them. The Temez model was appropriate for studying limited data of the El Pane Basin, while the SWAT model allowed more detailed studies. Both the models were found to be useful tools for water management.
  Keywords: soil and water assessment tool; SWAT; Témez; soil water; evapotranspiration; normalised difference vegetation index; NDVI; land surface temperature; LST.
  DOI: 10.1504/IJHST.2023.10054441
   
  
• Estimation of storage capacity of the proposed rainwater harvesting structures (check dam) using geospatial technique: a case study in Tripura, India  
  by Bajitborlang L. Chyne, Ranjit Das, Naveen Ramachandran, Shanbor Kurbah 
  Abstract: The state of Tripura receives 2,380 mm rainfall annually. Due to the topography, most of the surface runoff drains off. Rainwater harvesting is a straightforward technique that collects and stores runoff from open spaces for future use. Check dam is one of the structures for harvesting rainwater. For preparing a proper water management scheme, estimation of the storage capacity of the reservoir is essential. Remote sensing and geographic information system is effectively utilised for estimation the storage capacity of the reservoirs. The inundated areas of the dams were estimated using digital elevation model in GIS environment and used finite difference method to develop the depth area curve and then elevation-area-capacity curve. The storage capacities of the proposed structures were estimated to be 3.19 and 0.35 million m3 at Buri Gang and Ghoramara Cherra respectively. This study provides a methodology to estimate the storage volume of reservoirs using geospatial technique.
  Keywords: reservoir; capacity; geographic information system; GIS; digital elevation model; DEM; topography; India.
  DOI: 10.1504/IJHST.2023.10054787
   
  
• Precipitation prediction in Bangladesh using machine learning approaches  
  by Md. Ariful Islam, Mosa. Tania Alim Shampa 
  Abstract: In the assessment of different hydrological activities, the prediction of rainfall is essential. As agriculture is critical to survival in Bangladesh, rainfall or precipitation is most important. This study shows how a machine learning approach can be used to make a reliable model for predicting rain. This way, people can know when rain is coming and take the steps they need to protect their crops. Many techniques have been applied so far to predict rainfall. But machine learning algorithms can provide more accuracy in this case. Nine machine learning algorithms have been used to find a good model that can be used to predict rain in Bangladesh. The prediction models were evaluated by dint of evaluation metrics such as coefficient of determination (R 2 ), root mean squared error (RMSE), and mean absolute error (MAE). Among nine algorithms and eight models, the model H including all meteorological exogenous inputs with gradient boosting regressor algorithm led to the best predictions (R 2 = 0.78, RMSE = 134, MAE = 92) for Sylhet division. The model G excluding wind speed with gradient boosting regressor algorithm shows the best predictions (R 2 = 0.76, RMSE = 147, MAE = 89) for both Chittagong and Rangpur divisions.
  Keywords: rainfall; machine learning algorithms; precipitation; gradient boosting regressor; GBR; Bangladesh.
  DOI: 10.1504/IJHST.2023.10055268
   
  
• Groundwater recharge and its response to land use - land cover dynamics in Biji catchment of Marodi-Jeeh, Somaliland  
  by Ridwan Ahmed Abdirahman, Dagnachew Daniel Molla, Tarun Kumar Lohani 
  Abstract: The land cover dynamics in Biji catchment of Somaliland was undertaken to evaluate groundwater (GW) recharge response to LULC change using integrated geospatial and distributed modelling approach. Satellite imagery (Land sat TM and ETM+ 30 m) classification of 1986, 2005 and 2019 using Arc GIS software image processing techniques were employed. Land use change of agriculture over the last 33 years was assessed as 16.8%-24.8%, bare land 15.8%-14.9%, shrub 67.3%-59.7%, and built-up 0.06%-0.5%. The water balance indicates evapotranspiration loss of 61.1%, runoff 4.7%, and GW-recharge 34.2%. GW recharge response of land use dynamics in the last three periods was about 135.8, 142.5, and 137.7 mm, respectively which is predominantly due to agricultural expansion and urbanisation. During the same period, WetSpass model was used to estimate total flow with a correlation coefficient of 0.82 and 0.88 respectively at a statistically significant level.
  Keywords: Biji catchment; Somaliland; groundwater recharge; LULC; WetSpass model.
  DOI: 10.1504/IJHST.2023.10055362
   
  
• The effect of reactor H/D ratios on the cultivation of aerobic granular sludge  
  by Fengli Zhao, Shenjie Zhou 
  Abstract: Height to diameter ratios (H/D ratios) of the sequencing batch reactors (SBRs) are of great significance in the cultivation of the aerobic granular sludge (AGS). In this study, the gas-liquid two-phase flow patterns in the reactors with two different H/D ratios of 5 and 3 were simulated based on computational fluid dynamics (CFD). The results showed that higher H/D ratios of the reactors provided smaller liquid velocity and shear rate but more small vortices and longer circulations compare with the lower H/D ratio reactor. Moreover, the cultivation of AGS in the two H/D ratio reactors was further investigated. It was found that reactors with higher H/D ratios can accelerate sludge granulation and retain more sludge than reactors with lower H/D ratios. However, the two reactors achieved the similar pollutant removal efficiency during the stable period, demonstrating that a high H/D ratio can enhance granulation but is not necessary for practical applications, which can reduce construction difficulties.
  Keywords: aerobic granular sludge; AGS; H/D ratios; computational fluid dynamics; CFD; flow patterns; granular performance.
  DOI: 10.1504/IJHST.2023.10055671
   
  
• Grouting - an effective method for reducing the permeability of sandy soils  
  by A.C. Sekhar, Benny Mathews Abraham, T.G. Santhosh Kumar, A. Sridharan 
  Abstract: Grouting is normally undertaken to reduce the permeability of rock or soil formations and this process is used extensively in the construction of hydraulic structures such as dams, tunnels and in a wide variety of special cases. Even though the application of the grouting technique to reduce the permeability of rock formations has been reported in literature, no serious attempts are reported about the effective use of this technique to reduce the permeability of soil formations. In this paper, an attempt has been made to study the effectiveness of grouting in reducing the permeability of the granular medium. Constant head permeability tests were carried out on the sand medium treated with different grouting materials such as cement, bentonite, lime, locally available clay and different combinations of the above materials. By grouting with different grout materials (e.g., in the case of cement - bentonite grout) the permeability of the medium sand got reduced from 10-4 m/s to 10-9 m/s. The present study undoubtedly proves the effectiveness of using grouting as an efficient technique in reducing the permeability of sandy soils.
  Keywords: ground improvement; ground water management; grouting; soil permeability; sub-surface barriers.
  DOI: 10.1504/IJHST.2023.10055876
   
  
• Identifying the optimum location of the dewatering pumping wells around excavations using numerical FEFLOW model: a theoretical study  
  by Hayder H. Kareem 
  Abstract: A theoretical study has been explored the dewatering process in an excavation pit has dimensions (600 x 600) m2 and depth 6m in an area (4,000 x 4,000) m2 with a total depth 30 m using FEFLOW programme. A mathematical model is created to reduce the water table at least 1 m below the bottom level of the excavation. The model is run in the steady state (one year) and transient flow (45 days, 60 days, 90 days and 120 days) conditions. Pumping wells are installed at distances of 50 m, 100 m, 150 m, 300 m, 450 m and 600 m away from the excavation. The total tested scenarios are 27: 15 (steady state) and 12 (transient state). Only 13 scenarios succeeded in achieving the required condition: 4 (steady state) and 9 (transient state). Economically, over the succeeded scenarios, scenario (S16) is considered the best dewatering one with the lowest extraction rate (157,500 m3/45 days) and minimal distance away from the excavation (50 m).
  Keywords: construction excavation pit; dewatering; FEFLOW; optimum location; mathematical modelling.
  DOI: 10.1504/IJHST.2023.10056098
   
  
• Urban expansion based on remote sensing extraction of impervious surface information  
  by Weifeng Kang, Dayong Chen 
  Abstract: Impervious surface is an important evaluation factor for the study of urban regional expansion and its social and environmental effects using remote sensing technology and the city has expanded rapidly, which is obviously reflected in the great changes in the impervious surface. Relying on 3S technology to study the classification method of urban impervious surface in this area and to explore the dynamic change law of urban impervious surface and its driving force has dual value of scientific research and social economy. This paper explores the computer automatic extraction method of impervious surface in my country in the past 20 years by using the time series Landsat TM images and object-based image analysis and processing technology and laws to explore the changes and internal causes of urban expansion. Moreover, this method can be utilised for hydrological modelling, flood mapping and monitoring, water quality monitoring, and urban heat island analysis.
  Keywords: impervious surface; improved normalised difference impervious surface index; object-based image analysis; OBIA; image segmentation.
  DOI: 10.1504/IJHST.2023.10056161
   
  
• Bias correction of regional climate model simulation for hydrological climate change over Bouregrag watershed in Morocco  
  by F. Gadouali, T. Benabdelouahab, A. Boudhar, R. Hadria, N. Semane, A. Fadil, K. Elrhaz 
  Abstract: General and regional climate models (GCMs/RCMs) exhibit many systematic biases, which affects the simulation accuracy of the real precipitation patterns and consequently the associated hydrological changes. The common approach used to reduce errors in the climate model output is to apply bias correction methods (BCMs) which attempt to adjust the climate simulation by its observation counterpart. In this study, we applied BCM on simulated rainfall over the Bouregrag basin (Morocco) from CanRCM4 CORDEX RCM using linear SCALING method (SCALING), gamma quantile mapping (GQM) and empirical quantile mapping (EQM). Owing to its high performance compared to the others, we applied the EQM method on climate projections under the RCP4.5 scenario. Results showed a decrease up to -50% in the monthly rainfall for the period 20412060 with the exception of August and December exhibiting an increase between +20% and +78%. This study supports the need to bias correct climate data before their use in hydrological models where the bias could be irreversible.
  Keywords: regional climate model; RCM; bias correction methods; BCMs; hydrological models; quantile mapping; Morocco.
  DOI: 10.1504/IJHST.2023.10056362
   
  
• Dam break analysis using hydrodynamic modelling and geospatial techniques: a case of Damanganga reservoir, Gujarat, India  
  by Kishanlal Darji, Uttamkumar Vyas, Dhruvesh Patel 
  Abstract: Flooding is a recurring phenomenon which can reduce certain extent by storing the water in large dam. However, dam operation is the most challenging part of flood resilience in recent climatic uncertainty and extremes. Furthermore, old dams have the potential to fail due to extreme rainfall, earthquakes, and structural failure. Recently, dam break analysis for prior threat detection has been used to strengthen resilience and improve decision-making by guiding emergency action plans (EAP) preparation. This paper describes the analysis of overtopping and piping failure of the earthen part of the Damanganga reservoir, Gujarat, India using geospatial techniques and 2D hydrodynamic inundation modelling. The Froehlich’s guideline is utilised for dam breach analysis. Water surface elevation, Water depth, water velocity, arrival time, and water inundation map were developed using 2D HEC-RAS based hydrodynamic modelling. The generated maps will utilise for flood decision making activity to reinforce the EAP for large dam.
  Keywords: dam break analysis; hydrodynamic modelling; Dam Rehabilitation and Improvement Program; DRIP; geospatial techniques; emergency action plans; EAP; digital elevation model; DEM; India.
  DOI: 10.1504/IJHST.2023.10056492
   
  
• Impact of large dam reservoirs on slight local season shifting (case study: Three Gorges Dam)  
  by Yongzhen Deji, Jihui Fan, Majid Galoie, Artemis Motamedi 
  Abstract: The monthly data (19802018) from 54 stations, which were classified into three altitude levels, were extracted. The analysis showed TGD had a minor effect on the variation of the precipitation data. Also, due to the variation in dominant wind direction and speed, the spatial distribution of rainfall was altered significantly. The Standardised Precipitation Evapotranspiration Index (SPEI) analysis in 1, 3, and 12 months showed degradation in the positive drought index downstream of the dam after impounding. The data analysis showed that TGD had a strong impact on the increase in monthly temperature and relative humidity both upstream and downstream of the dam such that for the regions with altitudes of higher than 400 m.a.s.l., the month with the maximum monthly RH and temperature was shifted from December to June and from July to June, respectively. This shifting in lower altitude regions was not seen.
  Keywords: Three Gorges Dam; TGD; meteorological data analysis; season shifting; local climate change.
  DOI: 10.1504/IJHST.2023.10056527
   
  
• Anomalous behaviour of Indian summer monsoon rainfall due to the change in some of the monsoon semi-permanent features in surplus and deficit years  
  by Ghulam G. Zahid, Nuzhat Fatima, Aparna Sinha, Ajhar Hussain, Firoz Ahmad 
  Abstract: The purpose of this research is to better understand the Indian summer monsoons insufficient rainfall in 2002 and excess rainfall in 2007, as well as their relationship with large-scale circulation features and land-sea heating contrast. Zonal and Meridional wind at 850 Hpa and mean sea level pressure and monthly mean rainfall are the parameters used to describe the semi-permanent features and anomalous behaviour of ISMR. Over extensive portions of the Indian Ocean, Arabian Sea, and much of India, significant mean sea level pressure and rainfall anomalies are present. Negative rainfall anomalies prevailed over some parts in the centre of the monsoon core zone (MCZ). By evaluating the Somali jet, the Mascarene high and ISMR observed that heavy rainfall occurs in the MCZ. Mascarene high show stronger anticlockwise circulation in deficit year but due to the effects of El Nino wind and moisture transferred towards the East-Pacific region.
  Keywords: Indian summer monsoon rainfall; ISMR; monsoon semi-permanent features; ENSO; convection; cross-equatorial low-level jet; monsoon core zone; MCZ.
  DOI: 10.1504/IJHST.2023.10056541
   
  
• Rainfall trend analysis in Gujarat’s semi-arid zone: a modified approach with autocorrelation consideration  
  by Ramiz F. Tasiya, Naveena K. Kannegowda, Shilpesh C. Rana 
  Abstract: Precise identification of rainfall movement is very essential during climate change scenarios for better water resources management. Erratic and violent monsoon rainfall movements are observed in the coastal region of Maharashtra, Gujarat, and Kerala within a very short period. The aim of the research is to identify the changes that occurred in the South-West monsoon rainfall trend using advance statistical package of R-software, for the semi-arid region of Gujarat. From the Wallis and Moore phase-frequency test, it is found that 6 out of 29 stations are having significant auto-correlation. Modified Mann-Kendall and Sen’s slope tests are used to carry out rainfall trend analysis. Spatial representation of mean SW-monsoon rainfall and Sen’s slope shows lower magnitude near coastal region and higher magnitude at higher elevation range. As a result, it is concluded that in monsoon two stations (7%) and particularly during June month seven (24%) stations are showing a significantly decreasing trend.
  Keywords: R-software; Sen’s Slope test; Wallis and Moore phase-frequency test (Z- test); modified Mann-Kendall test.
  DOI: 10.1504/IJHST.2023.10056997
   
  
• Determining the most suitable Sentinel-2 indices for turbidity and chlorophyll-a concentration for an oligotrophic to mesotrophic reservoir in Brazil  
  by Fernanda Mara Coelho Pizani, Camila Costa De Amorim, Philippe Maillard 
  Abstract: Water quality is a major issue for agencies responsible for the management and maintenance of reservoirs. In this article, Sentinel-2 (S-2) data is tested to produce reliable estimates of turbidity and chlorophyll-a concentrations in an oligotrophic to mesotrophic reservoir in Brazil. The spectral bands were all tested individually and jointly to determine the best and most stable features. Many indices are also tested. In situ data was acquired over a period of three years with synchronous S-2 data. The models were evaluated on their robustness and stability using a bundle of in situ dataset (all field campaigns). The results show that no model can be directly applied to other reservoirs or different dates without calibration. Conversely, calibrating the S-2 indices with two in situ measurementsa greatly reduces the errors. Average root mean square errors of 0.518 FNU and 1.1 _g/l were obtained for turbidity and chlorophyll-a concentrations respectively.
  Keywords: chlorophyll-a; turbidity; empirical models; Sentinel-2; reservoir.
  DOI: 10.1504/IJHST.2023.10057236
   
  
• Effect of hydrological model selection in climate change impact assessment in the Dano tropical catchment (Burkina-Faso)  
  by Yacouba Yira, Aymar Y. Bossa, Ngague Hisseine Ganda, Djigbo F. Badou, Kpade O. Laurentin Hounkpatin, Jean Hounkpè, Luc Ollivier Sintondji 
  Abstract: Applying a validated hydrological model is a common approach in climate change impact studies. The current study used an ensemble of five regional climate models and two hydrological simulation models (HBV-light and GR4J). Both models were successfully calibrated and validated with coefficients of determination-R 2 and Nash and Sutcliffe efficiencies-NSE ranging between 0.64 and 0.88. Compared to the reference period (1976-2005), the projected temperature shows an increase for the future periods 2021-2100, whereas for the projected precipitation change, a mixed trend is expected. The projected discharge change is very similar to the precipitation signal. The results further indicate for some climate datasets that, the climate-induced discharge change is lower than 50 mm per year for both HBV-light and GR4J, while the inter-comparison of discharges between the two hydrological models indicates differences exceeding 100 mm per year. Therefore, the choice of the hydrological model overscores the impact of the projected climate change.
  Keywords: climate change; CORDEX; discharge; HBV-light; GR4J; hydrological model selection; climate change impact; tropical catchment; Burkina Faso.
  DOI: 10.1504/IJHST.2023.10057775
   
  
• Integrated rainfall-runoff modelling using fuzzy logic considering soil moisture: case study of Damanganga Basin  
  by Vrushti C. Kantharia, Darshan J. Mehta 
  Abstract: The present study aims to develop integrated rainfall-runoff modelling considering soil moisture at three different depths (5 cm, 100 cm, and bedrock) for the Damanganga basin. To simulate the daily discharge Mamdani fuzzy-logic model and adaptive neuro-fuzzy inference system (ANFIS) are used. The analysis is carried out for the South-West Monsoon season, i.e., (June, July, August, and September) for 39 years, i.e., 1983-2022. Mamdanis fuzzy-logic and adaptive neuro-fuzzy inference system (ANFIS) model uses soil moisture and rainfall data as the input variables to simulate daily discharge. The model application result reveals that soil moisture at bedrock gives more precise results as compared to soil moisture at 5 and 100 cm. Comparison between both the models is also carried out on the basis of regression and the results demonstrate that the adaptive neuro-fuzzy inference system (ANFIS) model gives a more precise value of daily discharge as compared to the Mamdani fuzzy model. This study can be helpful to future research scholars and to hydrological scientists in selecting appropriate rainfall-runoff models.
  Keywords: ANFIS; Damanganga; discharge; fuzzy logic; Mamdani; rainfall; soil moisture.
  DOI: 10.1504/IJHST.2023.10058036
   
  
• Infiltration characteristics and hydraulic properties of soil as affected by tillage practices and biochar-poultry manure application.  
  by Chukwuebuka Vincent Azuka 
  Abstract: The study investigated the effect of biochar and poultry manure (PM) applications on infiltration characteristics and hydraulic properties of degraded Ultisols in Nsukka under two tillage practices. The treatments were tillage practices (conventional tillage; zero-tillage) and organic amendments (10 t/ha biochar, 10 t/ha PM, 10 t/ha biochar + 200 kg/ha NPK and 400 kg/ha NPK). The results showed significant (p < 0.05) higher values of cumulative and steady-state infiltration, saturated hydraulic conductivity (Ksat), microporosity and total porosity (TP) in tilled soils (1,266 mm, 0.772 cm/min, 25.88 cm/hr, 40.53% and 49.23% respectively) than in no-tilled soils (799 mm, 0.502 cm/min, 20.05 cm/hr, 36.88% and 45.81% respectively). Organic amendments had a significant (p < 0.05) effect on BD, cumulative and steady-state infiltration, Ksat and available water capacity (AWC). The highest values of cumulative and steady-state infiltration, Ksat and AWC (1,302 mm, 0.800 cm/min, 25.23 cm/hr and 0.290 respectively) and lowest values of BD (1.49 g/cm3) were obtained in biochar-amended soil.
  Keywords: organic amendment; soil degradation; soil quality; biochar; soil productivity.
  DOI: 10.1504/IJHST.2023.10058434
   
  
• Extreme value modelling using the peaks over threshold method, an inverse cumulative uniform distribution approach  
  by Justin Chirima 
  Abstract: This paper proposes an inverse continuous uniform distribution approach for selecting the threshold when performing the peaks over threshold (POT) method to data with outliers. Applying results from the mean residual life plot (MRLP) and the threshold stability plot (TSP), the threshold is assumed to follow a continuous uniform distribution between values a and b. An inverse uniform distribution algorithm for threshold selection is developed and applied to hypothetical data and Zimbabwean precipitation data. The proposed method is capable of determining optimal thresholds which give reasonable fits for historical data.
  Keywords: uniform distribution; threshold; generalised Pareto distribution; GPD; peaks over threshold; POT.
  DOI: 10.1504/IJHST.2023.10058520
   
  
• Estimation of rainfall-runoff potential using SCS-CN and geospatial approach for Loktak Lake watershed, India  
  by Ranu Jajo Laishram, Wazir Alam 
  Abstract: Rainfall and runoff are important hydrologic variables that determine the spatio-temporal availability and distribution of water resources. The Loktak Lake watershed is an important ungauged catchment of Manipur, India, where the runoff behaviour has not been well documented due to constraints involved in its direct estimation. Therefore, the present study uses the soil conservation service curve number (SCS-CN) method by integrating geoinformatics tools to estimate the potential runoff from Loktak watershed. The assessed land use/land cover changes of the catchment area during 2000 to 2020 illustrate significant increase in urbanisation/built-up area (10.67% to 19.95%) and decrease in forest cover (25.86% to 24.49%). The estimated total potential runoff depths during the study period ranged from 118.21 mm to 996.88 mm, with highest runoff observed in 2017. Average annual proportion of rainfall converted to runoff was around 25.9%, and highest average monthly runoff was observed during June and lowest in January.
  Keywords: runoff; watershed; SCS-CN; land use/land cover; LULC; geographic information system; GIS; remote sensing; India.