Faculty Publications
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Item Assessment of Changes inWetland Storage in Gurupura River Basin of Karnataka, India, Using Remote Sensing and GIS Techniques(Springer Science+Business Media, 2018) Kundapura, S.; Kommoju, R.; Verma, I.In view of the significant importance of wetlands in the ecosystem and regional economy, an attempt has been made to analyze the impact of land use/land cover dynamics and other contributing factors on spatial status of Gurupura river basin wetland ecosystem located in Karnataka region. The impact assessment has been carried out by analyzing the multi-temporal changes in the storage capacities of wetlands in the watershed, by using remote sensing data of LISS-III. The multi-temporal land use/land cover statistics will reveal the significant changes that have taken place over time in the watershed. The runoff generated can be easily calculated from this information which gives an idea of the total input into the system. In response to these upstream watershed changes, wetland has exhibited changes in spatial extension, structure, and hydrological characteristics. As a consequence of continuously changing land use/land cover characteristics and unpredictability of the monsoon, the wet land ecosystems have exhibited considerable changes in spatial extent and their storage capacities. Overall, there has been degradation in the storage capacities of the wetland ecosystems of the region causing a multitude of adverse effects such as increase in floods and submergence of mainland. © Springer Nature Singapore Pte Ltd. 2019.Item Beyond the data range approach to soft compute the reflection coefficient for emerged perforated semicircular breakwater(Springer, 2019) Kundapura, S.; Hegde, A.V.; Wazerkar, A.V.Prediction of reflection coefficient (Kr) for emerged perforated semicircular breakwater (EPSBW) using artificial neural network (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) is carried out in the present paper. A new approach has been adopted in the present work using ANN and ANFIS models for the prediction of the reflection coefficient (Kr) for the wave periods beyond the range of the dataset used for training the network. The experimental data obtained for a scaled down EPSBW model from regular wave flume experiments at Marine Structure laboratory of National Institute of Technology Karnataka, Surathkal, Mangaluru, India was used. The ensemble was segregated such that certain higher ranges of wave periods were excluded in the training, and possibility of prediction was checked. The independent input parameters (Hi, T, S, D, R, d, hs) that influence the reflection coefficient (Kr) are considered for training as well as testing, where Hi is the incident wave height, T is the wave period, S is the spacing of perforations, D is the diameter of the perforations, R is the radius of the breakwater, d is the depth of the water and hs is the structure height. The accuracy of predictions of reflection coefficient (Kr) is done based on the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The study shows that ANN and ANFIS models may be used for prediction of reflection coefficient Kr of semicircular breakwater for beyond the data range of wave periods used for training. However, ANFIS outperformed ANN model in the prediction of Kr in the case of beyond the data range segregation method. © Springer Nature Singapore Pte Ltd. 2019.Item Experimental Investigation of the Behavior of Tubular T-Joint of Jacket Structures(Springer, 2024) Murugan, N.; Kaliveeran, V.; Kundapura, S.This study deals with a preliminary experimental study to examine the behavior of tubular T-joint of Jacket structures under compressive load, which is helpful for further study of reinforcement in T-joints for strengthening. A specimen of T-joint with geometric dimensions of chord length = 494 mm, chord diameter = 141 mm, chord thickness = 5 mm, and brace length = 237 mm, brace diameter = 90 mm, brace thickness = 4.5 mm was considered for this study. The specimen is subjected to axial compressive load which is applied from the top end of the brace member. The ends of the chord member are in simply supported condition. The experiment is conducted in a 40 T UTM machine. The loads are applied with an interval of 50 kgf starting from zero to the yield load of 9,600 kgf. The experimental setup, specimen details, and the relevant results (load-deformation relationship and failure mechanism) are presented. The findings of the study, i.e., local joint deformation behavior under compressive load, are presented graphically. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Finite Element Modelling and Experimental Validation of Strain Gauge Pasted Over the Surface of a Substrate Subjected to a Transverse Load(Springer, 2024) Raveesh, R.M.; Kaliveeran, V.; Kundapura, S.The strain measurement is important as it directly involves with the deformation of a structure in the field of engineering. Strain is a measure of change in shape that occurs when an external load is applied to an engineering assembly. The evaluation of the strain is used to determine the amount of extension or deformation a structure experiences under different loading conditions. Strain gauges are electrical resistance sensors bonded at critical locations on the surface of structural components to detect surface deformation. Strain gauges are frequently used to continuously check for deformations to avoid accidents that can occur in nuclear power plants, aerospace vehicles, mechanical components, and structures. Strain gauges applied directly to the specimen are partially affected by the bonding material and thickness when tested. Present work intends to study the effect of adhesive thickness on strain values. Adhesives are used to paste strain gauges over the surface of the specimen. Three-Dimensional analysis of the strain gauge model has been carried out with the aid of the Finite element software. Experiments were conducted to study the effect of adhesive thickness by varying the thickness of the adhesive from 0.1 to 1 mm by pasting strain gauge over the surface of the Aluminium specimen of length 230 mm, width of 30 mm, and thickness of 6 mm. The strain values obtained from the finite element analysis were compared with the strain values obtained from the experiments. Finite element analysis results were found to be in good correlation with the experimental results. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Item Hydrologic modelling of flash floods and their effects(Springer Science and Business Media Deutschland GmbH, 2021) Paul, A.R.; Kundapura, S.Flash floods are ranked on top in the number of people that are affected and amount of damages caused. The sudden nature of this disaster gives less time for the victims to prepare, thereby ending up with a disrupted social, economic and political stature. The study aims at analysing the possible peak discharges with the help of a rainfall–runoff model for the flood events that have occurred in the Harangi River basin in the Kodagu district and estimate the economic damage induced. The SCS curve number method is used for simulating the runoff. Fourteen peak events over the months of July and August of two different years are chosen for the validation and calibration of the model. Discharges are simulated using the HEC-HMS extension in WMS software. The effect of variation of rainfall and land-use practices in the runoff volume is studied. It is observed that the changes in land-use practices have more effect on the runoff volume than the rainfall volume. Rapid urbanization and industrialization has increased the intensity of flood damages. The largest flow was recorded when a natural bund of water collected in the upstream was collapsed. © Springer Nature Singapore Pte Ltd 2021.Item Flood inundation mapping of harangi river basin, kodagu, using gis techniques and hec-ras model(Springer Science and Business Media Deutschland GmbH, 2021) Dev Anand, M.R.; Kundapura, S.Flood is the most common hydrologic event frequently experienced in India. The states of Kerala, UP, West Bengal, Karnataka and Assam were the mainly affected by flood in 2018. In Kodagu, the southern district of Karnataka, many people have been affected by heavy rains. Landslides in hilly terrain and flooding have worsened the lives of people and led to the destruction of 800 homes, 240 bridges collapsed, road networks of 2225 km damaged and 65 government buildings affected. The cost of rebuilding road infrastructure and buildings is approximately Rs. 3000 crores. While developing flood mitigation measures, flood inundation maps are an essential component, which will be useful for the planning stage. The mapping is expected to estimate the prone flood zone based on river flood stage without performing additional simulations and quantification of the flood risk with respect to different vulnerability parameters giving a clear picture of the planning stage. These are going to be achieved by both 1D hydrodynamic models and GIS environment. This study gives an insight about how unscientific development activities may increase the negative impacts of natural disasters. It can support the planners to correctly identify the non-vulnerable places while rebuilding the damaged infrastructure. This can help people to resettle permanently in a safer place, so that they will not be affected in the case of future disasters. Depending on the severity of the water levels, we can identify the area for construction of hydraulic structures for flood protection. © Springer Nature Singapore Pte Ltd 2021.Item High-resolution mapping of soil properties using aviris-ng hyperspectral remote sensing data—a case study over lateritic soils in mangalore, india(Springer Science and Business Media Deutschland GmbH, 2021) Chitale, M.M.; Kundapura, S.Quick and accurate mapping of properties of soil is considered to be critical for agriculture and environmental management. Rapid assessment of soil properties is a daunting task in monitoring the environment. The conventional field sampling is a laborious as well as time-consuming job. The conventional methods are restricted to a specific region but there is a need to analyses the soil properties at landscape levels. Hence, this study emphasises on hyperspectral remote sensing which to some extent helps in rapid assessment of the properties. The hyperspectral data used for the study is AVIRIS-NG data. The study explored the potential of AVIRIS-NG hyperspectral data in mapping soil properties which were analysed by in situ laboratory methods and compared with them by geostatistical method of spatial interpolation. Hence, the method adopted for this purpose is the study on spatial variability of soil properties by using Kriging interpolation technique. Also, a review study is carried out on the visible and near-infrared analysis (VNIRA), multiple regression analysis approach and spectral angle mapper supervised classification technique on the high-resolution AVIRIS-NG Hyperspectral data, which will yield as an empirical model for predicting the soil property in question from both wet chemistry and spectral information of a representative set of samples and classifies the data accordingly. © Springer Nature Singapore Pte Ltd 2021.Item A statistical approach for comparison of secondary precipitation products(Springer Science and Business Media Deutschland GmbH, 2021) Kommu, R.; Kundapura, S.; Venkatesh, V.Meteorological data retrieval is the fundamental process for any hydrological research. Precipitation data collection from some constrained territories like high slant geography and inaccessible areas is exceptionally troublesome. Setting the rain gauges is a matter of expense and timely maintenance. To overcome these issues, satellite sensors producing high spatial and temporal resolution datasets can be utilized in the studies involving precipitation component. These satellite products are affected by biases, and hence, there is a need for calibration and verification by using ground observation data based on the statistical coefficients. In this study, the most accessible satellite data products, i.e., CHIRPS, PERSIANN-CDR and TRMM, are employed to check the accuracies against IMD gridded data for the years 2000–2012 using a statistical approach. Selecting the data product having a high coefficient of correlation and low PBIAS is utmost necessary. The current study was performed based on catchment-to-catchment (C-C) method by comparing IMD gridded data with satellite datasets obtained from Google Earth Engine. The results can highlight the data product which can conquer the issue of data inaccessibility in the investigation territory and can be utilized as reference precipitation dataset for different hydrological applications. © Springer Nature Singapore Pte Ltd 2021.Item Relative wave run-up parameter prediction of emerged semicircular breakwater(Springer Science and Business Media Deutschland GmbH, 2021) Kundapura, S.; Rao, S.; Arkal, V.H.Relative wave run-up parameter (Ru/Hi) on breakwaters is a vital component in fixing the elevation of the breakwater crest. In the present study, several soft computing methods has been employed to predict the wave run-up on the emerged seaside perforated semicircular breakwater for the prevailing Arabian sea wave climate, off Mangaluru coast in India. Unlike the mathematical modeling techniques, the soft computing tools have no complexity involved about understanding the nature of underlying process and prediction consumes less time when proper physical model data is available. The soft computing methods like artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS), genetic algorithm based adaptive neuro fuzzy inference system (GA-ANFIS) and particle swarm based adaptive neuro fuzzy inference system (PSO-ANFIS) are the four models employed in the study. The ANN predicted well for the set architecture of (5-7-1). The ANFIS is used to predict the wave run-up on semicircular breakwater models using the hybrid efficiency of fuzzy logic and neural network. An initial FIS is generated for input variables by mapping the input-output data; the training is done using ANN; and the objective of GA and PSO is set to find the best FIS, reducing the root mean square error in the prediction of wave run-up. The most influencing input parameters (Hi/gT2, d/gT2, S/D, hs/d, R/Hi) are taken in non-dimensional form. The data required has been acquired from the physical model experiments conducted in the Marine structures laboratory of National Institute of Technology Karnataka (NITK), Surathkal, India. The GA-ANFIS prediction of wave run-up is found to be better than that of ANFIS prediction in terms of Correlation coefficient (R), Root mean square error (RMSE), Nash sutcliffe efficiency (NSE), Bias and Scatter index (SI). However, among the four models developed the ANN prediction outperformed the other three considered models with a higher R = 0.9467. © Springer Nature Singapore Pte Ltd 2021.Item Hydrological modeling of stream flow over netravathi river basin(Springer Science and Business Media Deutschland GmbH, 2021) Ashish, S.; Kundapura, S.; Kaliveeran, V.Riverine resources which are the basis of life are being transformed through urbanization. This has to be analyzed effectively in order to rejuvenate riverine ecosystems. The effects of land-use dynamics are a factor to be analyzed, and using hydrological modeling which is adopted in this study aids for the same. Soil and Water Assessment Tool (SWAT) is used as an effective tool in modeling the river basin due to its ability to quantify the alternate input data provided to the model. 14-year daily data was simulated in the model provided; the warm-up period for the model is 2 years. Coefficient of determination value of 0.74 and Nash–Sutcliffe efficiency (NSE) to be 0.71 were obtained from the analysis which indicate that the simulated values fall within a good range. The parameters which influence most are found to be curve number, available water capacity in the soil, groundwater delay, Manning’s n and plant uptake compensation. The fitted range was obtained, and this was used to increase the accuracy in SWAT Calibration and Uncertainty Procedures (SWAT-CUP). Sequential Uncertainty Fitting ver.2 (SUFI2) was found to be effective because of its uncertainty consideration criteria, and it accounts for all uncertainties that may occur in the mode. Hydrological modeling of a river basin can help us to assess the impact of alternative input data on the stream flow. © Springer Nature Singapore Pte Ltd 2021.