Faculty Publications
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Item Variability of streambed hydraulic conductivity in an intermittent stream reach regulated by Vented Dams: A case study(Elsevier B.V., 2018) Naganna, S.R.; Deka, P.C.The hydro-geological properties of streambed together with the hydraulic gradients determine the fluxes of water, energy and solutes between the stream and underlying aquifer system. Dam induced sedimentation affects hyporheic processes and alters substrate pore space geometries in the course of progressive stabilization of the sediment layers. Uncertainty in stream-aquifer interactions arises from the inherent complex-nested flow paths and spatio-temporal variability of streambed hydraulic properties. A detailed field investigation of streambed hydraulic conductivity (Ks) using Guelph Permeameter was carried out in an intermittent stream reach of the Pavanje river basin located in the mountainous, forested tract of western ghats of India. The present study reports the spatial and temporal variability of streambed hydraulic conductivity along the stream reach obstructed by two Vented Dams in sequence. Statistical tests such as Levene's and Welch's t-tests were employed to check for various variability measures. The strength of spatial dependence and the presence of spatial autocorrelation among the streambed Ks samples were tested by using Moran's I statistic. The measures of central tendency and dispersion pointed out reasonable spatial variability in Ks distribution throughout the study reach during two consecutive years 2016 and 2017. The streambed was heterogeneous with regard to hydraulic conductivity distribution with high-Ks zones near the backwater areas of the vented dam and low-Ks zones particularly at the tail water section of vented dams. Dam operational strategies were responsible for seasonal fluctuations in sedimentation and modifications to streambed substrate characteristics (such as porosity, grain size, packing etc.), resulting in heterogeneous streambed Ks profiles. The channel downstream of vented dams contained significantly more cohesive deposits of fine sediment due to the overflow of surplus suspended sediment-laden water at low velocity and pressure head. The statistical test results accept the hypothesis of significant spatial variability of streambed Ks but refuse to accept the temporal variations. The deterministic and geo-statistical approaches of spatial interpolation provided virtuous surface maps of streambed Ks distribution. © 2018 Elsevier B.V.Item Acetaminophen micropollutant: Historical and current occurrences, toxicity, removal strategies and transformation pathways in different environments(Elsevier Ltd, 2019) Vo, H.N.; Le, G.K.; Nguyen, T.M.; Bui, X.-T.; Nguyen, K.H.; Rene, E.R.; Vo, T.D.H.; Cao Ngoc, N.-D.; Mohan, R.Acetaminophen (ACT) is commonly used as a counter painkiller and nowadays, it is increasingly present in the natural water environment. Although its concentrations are usually at the ppt to ppm levels, ACT can transform into various intermediates depending on the environmental conditions. Due to the complexity of the ACT degradation products and the intermediates, it poses a major challenge for monitoring, detection and to propose adequate treatment technologies. The main objectives of this review study were to assess (i) the occurrences and toxicities, (2) the removal technologies and (3) the transformation pathways and intermediates of ACT in four environmental compartments namely wastewater, surface water, ground water, and soil/sediments. Based on the review, it was observed that the ACT concentrations in wastewater can reach up to several hundreds of ppb. Amongst the different countries, China and the USA showed the highest ACT concentration in wastewater (?300 ?g/L), with a very high detection frequency (81–100%). Concerning surface water, the ACT concentrations were found to be at the ppt level. Some regions in France, Spain, Germany, Korea, USA, and UK comply with the recommended ACT concentration for drinking water (71 ng/L). Notably, ACT can transform and degrade into various metabolites such as aromatic derivatives or organic acids. Some of them (e.g., hydroquinone and benzoquinone) are toxic to human and other life forms. Thus, in water and wastewater treatment plants, tertiary treatment systems such as advanced oxidation, membrane separation, and hybrid processes should be used to remove the toxic metabolites of ACT. © 2019 Elsevier LtdItem Fractal-based supervised approach for dimensionality reduction of hyperspectral images(Elsevier Ltd, 2024) Gupta, V.; Gupta, S.K.; Shetty, A.Dimensionality reduction is one of the most challenging and crucial issues apart from data mining, security, and scalability, which have retained much traction due to the ever-growing need to analyze the large volumes of data generated daily. Fractal Dimension (FD) has been successfully used to characterize data sets and has found relevant applications in dimension reduction. This paper presents an application of the FD Reduction (FDR) Algorithm on geospatial hyperspectral data, examining its usefulness for data sets with a relatively high embedding dimension. We examine the algorithm at two levels. First is the conventional FDR approach (unsupervised) at the image level. Alternatively, we propose a pixel-level supervised approach for band reduction based on time-series complexity analysis. Techniques for determining an optimal intrinsic dimension for the dataset using these two techniques are examined. We also develop a parallel GPU-based implementation for the unsupervised image-level FDR algorithm, reducing the run-time by nearly 10 times. Furthermore, both approaches use a support vector machine classifier to compare the classification performance of the original and reduced image obtained. © 2024 Elsevier LtdItem Unravelling flood complexity: statistical and neural network approaches for Cauvery River Basin, India(Springer Science and Business Media B.V., 2024) Sahu, M.K.; Shwetha, H.R.; Dwarakish, G.S.Floods are widespread natural calamities with substantial socio-economic effects that demand adequate management measures and forecasts. In this study, the most popular traditional statistical distribution techniques, Gumbel, Log Pearson-III (LP-III), Log-Normal (LN) and three soft computing techniques such as Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Adaptive Neuro-Fuzzy Inference System-Firefly Algorithm (ANFIS-FFA) were examined for their potential to predict floods. These approaches were employed for modelling yearly maximum discharge at M.H. Halli, T. Narasipur, Kollegal, Biligundulu, Urachikottai, Kodumudi, and Musiri gauging stations of the Cauvery River using 40 years (1980 to 2019) data. Two statistical constraints, the wilton index (WI) and the root mean square error (RMSE), are employed to determine the performance of the proposed hybrid model. The results showed that, for M.H. Halli, Biligundulu, Urachikottai, Kodumudi, and Musiri gauging stations, ANFIS-FFA gave the highest WI values as 0.9141, 0.9636, 0.9205, 0.9373, and 0.8939, whereas and for T. Narasipur, and Kollegal gauging stations the ANN gave the highest WI value 0.8524 and 0.9440, respectively, during the testing phase. Futhermore, the coefficient of determination (R2) for ANFIS-FFA at M.H. Halli, Biligundulu, Urachikottai, Kodumudi, and Musiri gauging stations were 0.9140, 0.9636, 0.9205, 0.9378, and 0.8999, respectively and for ANN at T. Narasipur, Kollegal gauging stations were of R2 as 0.8574 and 0.9440, respectively. Based on these results, it can be concluded that the soft computing techniques (ANFIS-FFA and ANN) outperformed the statistical techniques. © The Author(s), under exclusive licence to Springer Nature B.V. 2024.