Faculty Publications
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Item Parameter estimation and vulnerability assessment of coastal unconfined aquifer to saltwater intrusion(2012) Mahesha, A.; Vyshali; Lathashri, U.A.; Ramesh, H.The focus of the present work is to characterize a tropical, coastal aquifer and to carry out its vulnerability to saltwater intrusion using hydrogeological parameters. The characterization of the aquifer involves pumping tests, vertical electrical sounding, and water quality analysis carried out at 41 monitoring wells. The area under investigation lies between two tropical, seasonal, tidal rivers, i.e., Pavanje and Gurpur rivers, joining the Arabian on the west coast of India. The aquifer is predominantly shallow and unconfined, having moderate to good groundwater potential with transimissivity and specific yield ranging from 49.2 to 461:4 m2/day and 0.00058 to 0.2805, respectively. The electrical resistivity tests indicated that the thickness of the aquifer ranges from 18 to 30 m. The study also investigates the saltwater affected areas in the region the vertical electrical sounding and water quality analysis. The resistivity results revealed several probable isolated saltwater intruded pockets in the region with resistivity less than 70 Om. From the salinity analysis of water, the locations that are affected during February to May (summer) and throughout the year are identified. The wells that are located close to the coast (< 350 m) and at lower elevations (well bottom < +1 m) were found to be saline throughout the year. Also, wells along the banks of the river show considerable salinity (> 200 ppm) during the summer period from tidal inflow along the rivers. The water samples were also analyzed for chloride to bicarbonate ratios during December to May at all the monitoring wells and were found to be exceeding the allowable limit at several locations. The saltwater vulnerability maps are derived for the area by the index-based method using the hydrogeological parameters. The method was found to be effective while compared to the field observations. The results from the analysis indicate that the aquifer is medium to highly vulnerable to saltwater intrusion at majority of the locations. The impact of projected sea level rise by 0.25 and 0.50 m from the climate change is also assessed on the vulnerability of the region to saltwater intrusion. © 2012 American Society of Civil Engineers.Item Ground water potential assessment of Haladi River basin in Westernghat of Udupi district, Karnataka, India(2013) Mahadeve Gowda, S.K.; Nagaraj, M.K.For a sustainable development of water resources, it is imperative to make a quantitative estimation of the available water resources. It is necessary to maintain the groundwater reservoir in a state of Dynamic equilibrium over a period of time and the water level fluctuations have to be kept within a particular range over the monsoon and non-monsoon seasons. Groundwater is a dynamic system. The total annual replenishable resource is around 43 M ha-m. The development and over-exploitation of groundwater resources have raised the concern and need for judicious and scientific resource management and conservation. Among the two major water resources, surface and ground water, it is the ground water resource, which needs to be managed carefully, especially in drought prone areas. To assess the groundwater potential, a suitable and accurate technique is required for a meaningful and objective analysis. A critical study is carried out on the different methods of estimating the groundwater potential and compared to arrive the most suitable technique for practical utility. In this work, five methods of estimating groundwater recharge were studied viz., 1. Yearly water level fluctuation 2. Ten year average water level fluctuation 3. Fluctuation between the lowest and highest water levels over ten years 4. Relationship between rainfall and recharge Method. The results of this study helps in accurate prediction of groundwater availability, which in turn may avoid groundwater over exploitation and help to restore the eco-systems. © 2013 CAFET-INNOVA TECHNICAL SOCIETY.Item Evaluating uncertainty of the soil and water assessment tool (SWAT) model in the upper cauvery basin, Karnataka, India(CAFET INNOVA Technical Society 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda, Hyderabad 500029, 2015) Kumar Raju, B.C.; Nandagiri, L.Quantification of uncertainties associated with hydrological models are essential for accurate assessment of water balance components and optimal planning and management of water and land resources at basin-scale. The present study was taken up to evaluate the uncertainties associated with the Soil and Water Assessment Tool (SWAT) model using for two different techniques: i) Generalized Likelihood Uncertainty Estimation (GLUE) and ii) Sequential Uncertainty Fitting (SUFI-2) techniques. The study was carried out in the Upper Cauvery River basin (36,682 km2) located in the humid to sub-humid region of Karnataka State, India. The calibration of the model was carried out using the Nash – Sutcliffe (NS) coefficient as the objective function for both GLUE and SUFI-2 techniques. The P-factor was 67% and 71% of observed streamflow data bracketed by the 95% prediction uncertainty (95PPU) for GLUE and SUFI-2 respectively during calibration period and corresponding values of 54% and 61% during validation period. Overall results indicate the applicability of SWAT model with moderate levels of uncertainty in large basins located in the humid tropics. The calibrated SWAT model can be used for assessment of water balance components and land use management scenarios in the Upper Cauvery Basin. © 2015 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.Item Comparison of Oceansat-2 scatterometer- to buoy-recorded winds and spatial distribution over the Arabian Sea during the monsoon period(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2015) Gadad, S.; Deka, P.C.For this wind resource assessment (WRA) study, wind speed and direction are the fundamental inputs. Also, these studies are data driven and require large historical wind speed data sets available on the site. This work explores the application of space-based scatterometer winds for assimilation into WRA studies towards the development of offshore wind energy. This article focuses on estimating the performance of Oceansat-2 scatterometer (OSCAT)-derived wind vector using in situ data from buoys at different locations in the Arabian Sea. A comparative study between three methods for estimating the equivalent neutral winds (ENW) for buoys is carried out. OSCAT winds were closest to ENW estimated by the Liu–Katsaros–Businger (LKB) method. The spatial and temporal windows for comparison were 0.5° and ±60 minutes, respectively. The monsoon months (June–September) of 2011 were selected for study. The root mean square deviation for wind speed is less than 2.5 m s?1 and wind direction is less than 20°, and a small positive bias is observed in the OSCAT wind values. From the analysis, the OSCAT wind values are consistent with in situ-observed values. Furthermore, wind atlas maps were developed with OSCAT winds, representing the spatial distribution of winds at a height of 10 m over the Arabian Sea. © 2015 Taylor & Francis.Item Assessment of soil moisture uptake under different salinity levels for paddy crop(American Society of Civil Engineers (ASCE) onlinejls@asce.org, 2016) Devatha, C.P.; Shankar, V.; Ojha, C.S.P.The core of salinity problems starts from the fact that irrigation waters contain some amount of dissolved salts. Soil moisture salinity is dependent on soil type, climate, water use, and irrigation. The root water-uptake pattern for paddies is studied for saline as well as nonsaline conditions in the present study using a nonlinear root water uptake model. Field crop experiments are carried out using irrigation water with two different levels of salinity (4 and 6.25 dS=m) and fresh water. The effect of salinity on soil moisture uptake is studied by two approaches, i.e., effect on crop coefficient and effect on hydraulic conductivity. Based upon the experimental observations for lowsaline (4 dS=m), high-saline (6.25 dS=m), and freshwater conditions, an exponential form of an equation is established for the hydraulic conductivity. The results obtained for soil moisture depletion in the crop root zone show significant improvement in prediction of soil moisture uptake for saline cases with the use of the obtained nonlinearity parameter. © 2016 American Society of Civil Engineers.Item Assessment of soil erosion by RUSLE model using remote sensing and GIS - A case study of Nethravathi Basin(Elsevier B.V., 2016) Ganasri, B.P.; Ramesh, H.Soil erosion is a serious problem arising from agricultural intensification, land degradation and other anthropogenic activities. Assessment of soil erosion is useful in planning and conservation works in a watershed or basin. Modelling can provide a quantitative and consistent approach to estimate soil erosion and sediment yield under a wide range of conditions. In the present study, the soil loss model, Revised Universal Soil Loss Equation (RUSLE) integrated with GIS has been used to estimate soil loss in the Nethravathi Basin located in the southwestern part of India. The Nethravathi Basin is a tropical coastal humid area having a drainage area of 3128 km2 up to the gauging station. The parameters of RUSLE model were estimated using remote sensing data and the erosion probability zones were determined using GIS. The estimated rainfall erosivity, soil erodibility, topographic and crop management factors range from 2948.16 to 4711.4 MJ/mm·ha? 1hr? 1/year, 0.10 to 0.44 t ha? 1·MJ? 1·mm? 1, 0 to 92,774 and 0 to 0.63 respectively. The results indicate that the estimated total annual potential soil loss of about 473,339 t/yr is comparable with the measured sediment of 441,870 t/yr during the water year 2002–2003. The predicted soil erosion rate due to increase in agricultural area is about 14,673.5 t/yr. The probability zone map has been derived by the weighted overlay index method indicate that the major portion of the study area comes under low probability zone and only a small portion comes under high and very high probability zone. The results can certainly aid in implementation of soil management and conservation practices to reduce the soil erosion in the Nethravathi Basin. © 2015 China University of Geosciences (Beijing) and Peking UniversityItem EXhype: A tool for mineral classification using hyperspectral data(Elsevier B.V., 2017) Adep, R.N.; Shetty, A.; Ramesh, H.Various supervised classification algorithms have been developed to classify earth surface features using hyperspectral data. Each algorithm is modelled based on different human expertises. However, the performance of conventional algorithms is not satisfactory to map especially the minerals in view of their typical spectral responses. This study introduces a new expert system named ‘EXhype (Expert system for hyperspectral data classification)’ to map minerals. The system incorporates human expertise at several stages of it's implementation: (i) to deal with intra-class variation; (ii) to identify absorption features; (iii) to discriminate spectra by considering absorption features, non-absorption features and by full spectra comparison; and (iv) finally takes a decision based on learning and by emphasizing most important features. It is developed using a knowledge base consisting of an Optimal Spectral Library, Segmented Upper Hull method, Spectral Angle Mapper (SAM) and Artificial Neural Network. The performance of the EXhype is compared with a traditional, most commonly used SAM algorithm using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data acquired over Cuprite, Nevada, USA. A virtual verification method is used to collect samples information for accuracy assessment. Further, a modified accuracy assessment method is used to get a real users accuracies in cases where only limited or desired classes are considered for classification. With the modified accuracy assessment method, SAM and EXhype yields an overall accuracy of 60.35% and 90.75% and the kappa coefficient of 0.51 and 0.89 respectively. It was also found that the virtual verification method allows to use most desired stratified random sampling method and eliminates all the difficulties associated with it. The experimental results show that EXhype is not only producing better accuracy compared to traditional SAM but, can also rightly classify the minerals. It is proficient in avoiding misclassification between target classes when applied on minerals. © 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)Item A novel mathematical morphology based algorithm for shoreline extraction from satellite images(Taylor and Francis Ltd., 2017) Rishikeshan, C.A.; Ramesh, H.Shoreline extraction is fundamental and inevitable for several studies. Ascertaining the precise spatial location of the shoreline is crucial. Recently, the need for using remote sensing data to accomplish the complex task of automatic extraction of features, such as shoreline, has considerably increased. Automated feature extraction can drastically minimize the time and cost of data acquisition and database updating. Effective and fast approaches are essential to monitor coastline retreat and update shoreline maps. Here, we present a flexible mathematical morphology-driven approach for shoreline extraction algorithm from satellite imageries. The salient features of this work are the preservation of actual size and shape of the shorelines, run-time structuring element definition, semi-automation, faster processing, and single band adaptability. The proposed approach is tested with various sensor-driven images with low to high resolutions. Accuracy of the developed methodology has been assessed with manually prepared ground truths of the study area and compared with an existing shoreline classification approach. The proposed approach is found successful in shoreline extraction from the wide variety of satellite images based on the results drawn from visual and quantitative assessments. © 2017 Wuhan University. Published by Informa UK Limited, trading as Taylor & Francis Group.Item Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques(Springer Verlag, 2018) Gulgundi, M.S.; Shetty, A.Groundwater quality deterioration due to anthropogenic activities has become a subject of prime concern. The objective of the study was to assess the spatial and temporal variations in groundwater quality and to identify the sources in the western half of the Bengaluru city using multivariate statistical techniques. Water quality index rating was calculated for pre and post monsoon seasons to quantify overall water quality for human consumption. The post-monsoon samples show signs of poor quality in drinking purpose compared to pre-monsoon. Cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA) were applied to the groundwater quality data measured on 14 parameters from 67 sites distributed across the city. Hierarchical cluster analysis (CA) grouped the 67 sampling stations into two groups, cluster 1 having high pollution and cluster 2 having lesser pollution. Discriminant analysis (DA) was applied to delineate the most meaningful parameters accounting for temporal and spatial variations in groundwater quality of the study area. Temporal DA identified pH as the most important parameter, which discriminates between water quality in the pre-monsoon and post-monsoon seasons and accounts for 72% seasonal assignation of cases. Spatial DA identified Mg, Cl and NO3 as the three most important parameters discriminating between two clusters and accounting for 89% spatial assignation of cases. Principal component analysis was applied to the dataset obtained from the two clusters, which evolved three factors in each cluster, explaining 85.4 and 84% of the total variance, respectively. Varifactors obtained from principal component analysis showed that groundwater quality variation is mainly explained by dissolution of minerals from rock water interactions in the aquifer, effect of anthropogenic activities and ion exchange processes in water. © 2018, The Author(s).Item Hierarchical clustering approaches for flood assessment using multi-sensor satellite images(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2019) Senthilnath, J.; Shreyas, P.B.; Rajendra, R.; Sundaram, S.; Kulkarni, S.; Benediktsson, J.A.In this paper, hierarchical clustering methods are used on synthetic aperture radar (SAR) (during the flood) and LISS-III (before the flood) data to analyse damage caused by floods. The flooded and non-flooded regions are extracted from the SAR image while different land cover regions are extracted from the LISS-III image. Initially, the Bayesian information criterion (BIC) is implemented to obtain the constraints for the number of clusters. The optimal cluster centres are then computed using hierarchical clustering approach (i.e. cluster splitting and merging techniques). The cluster splitting techniques such as Iterative Self-Organising Data Technique (ISODATA), Mean Shift Clustering (MSC), Niche Genetic Algorithm (NGA) and Niche Particle Swarm Optimisation (NPSO) were applied on SAR and LISS-III data. The cluster centres obtained from these algorithms are used to group similar data points by using merging method into their respective classes. Further, the results obtained for each method are overlaid to analyse the individual land cover region that is affected by floods. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.