Faculty Publications
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Item Spatial variation in drainage characteristics and geomorphic instantaneous unit hydrograph (GIUH); implications for watershed management-A case study of the Varada River basin, Northern Karnataka(2011) Bhagwat, T.N.; Shetty, A.; Hegde, V.S.Geomorphological characteristics can be treated as signatures of hydrological responses. Geomorphologic instantaneous unit hydrograph (GIUH) is of utmost use in planning watershed management programs on a broad scale in absence of hydrologic data. Fifth order basins from different agroclimatic zones in the Varada River basin were selected to understand the spatial variation in drainage characteristics. These sub-basins show significant differences in their morphometric properties such as basin area, drainage density, bifurcation ratio, circularity ratio, constant of channel maintenance etc. These differences reflect variation in the hydrological process and geomorphologic instantaneous unit hydrograph (GIUH) of different sub-basins and can be used to understand watershed management aspects. Fifth order sub-basin in the Southern Transition agroclimatic zone is potential for artificial recharge programs. Sub-basins in the Hilly non-forest zone on the north are ideal for surface water storage like tank development program while Forested Hilly zone on the north are environmentally sensitive and prone to erosion. © 2011 Elsevier B.V.Item Land use scenario analysis and prediction of runoff using SCS-CN method: A case study from the Gudgudi tank, Haveri district, Karnataka, India(2011) Bhagwat, N.B.; Shetty, A.; Hegde, V.S.Runoff from the Gudgudi tank catchment (209 ha) near Hangal in the Northern Karnataka is estimated employing Soil Conservation Services(SCS) model based on the hydrological data and land use/ land cover data. Rainfall measured for 2006 using a tipping bucket indicated annual rainfall of 887.7mm in the tank catchment. Textural characteristics of the soil indicate sandy-clayey type which corresponds to hydrological soil group "C and D". Average Soil infiltration rate of 0.18 cm/hour for the forest-land and 0.21 cm/hour for agriculture land has been observed. Weighted curve number is arrived based on the antecedent moisture conditions, and runoff is estimated for the existing land-use. Areastorage curve is constructed using the tank bed contours. Considering the hypothetical changes in the agriculture and forest area coverage, optimum conditions for maximizing the runoff and storage in the tank is arrived. The analysis suggests land use pattern of 15% of forest cover and 85% of agriculture land coverage in this region provide maximum runoff and storage in the tank for sustainable development. © 2011 CAFET-INNOVA TECHNICAL SOCIETY.Item Identification and Apportionment of Pollution Sources to Groundwater Quality(Springer Basel info@birkhauser-science.com, 2016) Gulgundi, M.S.; Shetty, A.Characterizing groundwater quality and apportionment of pollution sources to groundwater pollution is important for managing water resources effectively. Owing to rapid industrialization and population growth in Bengaluru city, the groundwater quality is getting deteriorated. Receptor modeling by Multi-Linear Regression of the Absolute Principal Component Scores (APCS-MLR) has been used to evaluate the source apportionment of groundwater pollution in order to recognize and quantify the pollution sources. Groundwater quality data measured for pre-monsoon and post-monsoon in the year 2014, comprising 14 physico-chemical parameters from 68 sites distributed across the study area, have been used. Principal component analysis identified four factors explaining 79.2 % of the total variance. Receptor modeling using APCS-MLR provided apportionment of different sources responsible for the groundwater quality along with percentage contribution of the recognized sources to each parameter. Results revealed that most of the variables were primarily affected by rock water interactions, seepage of sewage and industrial effluent. It was also found that few parameters gained significant contribution from the unidentified sources. Finally, the model performance was evaluated based on the ratio of estimated mean to measured mean (E/M). It was found that except for Fe with (E/M) ratio as high as 7.1, the model showed moderate strength with (E/M) values ranging from 0.51 to 2.83 of all the other parameters. © 2016, Springer International Publishing Switzerland.Item Age-based classification of arecanut crops: a case study of Channagiri, Karnataka, India(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2016) Bhojaraja, B.E.; Shetty, A.; Nagaraj, M.K.; Manju, P.Arecanut is one of the predominant plantation crop grown in India. Yield of this crop depends upon age of the crop and there is no information on the spectral behaviour of arecanut crops across its ages. In this study popular supervised classification algorithms were utilized for age discrimination of arecanut crops using Hyperion imagery. Arecanut plantations selected for the study are located in Channagiri Taluk, Davanagere district of Karnataka state, India. Ground truth information collected involves: (i) GPS coordinates of selected plots, (ii) spectral reflectance of arecanut crops with age ranging from 1 to 50 years, using handheld spectroradiometer with 1 nm spectral resolution. These spectral measurements were made close in time to the acquisition of Hyperion imagery to build age-based spectral library. It is observed from the analysis that crops of ages below 3, 3–7, 8–15 and above 15 years were showing distinct spectral behaviour. Accordingly, crops age ranging from 1 to 50 were grouped into four classes. Classification of arecanut crops based on age groups was performed using methods like spectral angle mapper, support vector machine and minimum distance classifier, and were compared to find the most suitable method. Among the classification methods adopted, support vector machine with linear kernel function resulted in most accurate classification method with overall accuracy of 72% for within class seperability. Individual age group classification producer’s accuracy varied minimum of 12.5% for 3–7 years age group and maximum of 86.25% for above 15 years age group. It may be concluded that, not only age- based arecanut crop classification is possible, but also it is possible to develop age-based spectral library for plantation crop like arecanut. © 2015 Taylor & Francis.Item Modelling the land use system process for a pre-industrial landscape in India(Springer Science and Business Media Deutschland GmbH, 2017) Ghosh, S.; Shetty, A.Land in India is changing in a rapid pace since the green revolution during 1960 and industrial policy reforms during 1990. Certainly land cover land use (LCLU) changes have huge impacts on countries overall ecological balance and climate change. The most intriguing fact is LCLU change is an interconnected phenomenon like a system. The understanding of local level LCLU dynamics are yet to get a momentum in India. The present study is an attempt: (1) to examine the land use change drivers active at the studied landscape of coastal Karnataka in India and (2) to model the LCLU changes in pre-industrialized period using Dyna-CLUE model. Binary logistic regression was used to categorize land change drivers and to estimate the probability of changes. Odd ratio from logistic regression indicates that the biophysical drivers are most prominent in determining location of LCLU. They being slope, relative relief, drainage density and availability of ground water are the most influential drivers for most of the land classes. The Dyna-CLUE model is successful to simulate the LCLU change at aggregate level but the spatial allocation needs improvement. © 2017, Springer International Publishing Switzerland.Item Spatio-temporal precipitation variability over Western Ghats and Coastal region of Karnataka, envisaged using high resolution observed gridded data(Springer Science and Business Media Deutschland GmbH, 2017) Doranalu Chandrashekar, V.; Shetty, A.; Singh, B.B.; Sharma, S.Climatic changes in the recent decades have led to large variations in precipitation over the different geographical regions of the globe. Changes in precipitation pattern over the space and time can severely affect the country like India, which has a large spatio-temporal variability in the precipitation. Any shift in the mean precipitation pattern pose a challenge to economy, agricultural farming and the ecosystem of these regions. In the present study, we analyze the seasonal spatio-temporal variation in trends of long term (1901–2013) observed high resolution (0.25° × 0.25°) gridded daily precipitation data of the Indian Meteorological Department over Western Ghats and coastal region of Karnataka, vulnerable to the risks of climate change. Our analysis shows increasing trend in seasonal ratio of precipitation over the Southern coastal plains and the adjacent Western Ghats region during pre-monsoon (MAM) while the southern coastal plains show decreasing trend in monsoon period (JJAS). Daily intensity index of precipitation during monsoon shows increasing trend in northern plains with decreasing trend in the medium precipitation events. Our study finds that different topographic regions of Karnataka have different responses in the trends of precipitation, particularly the response of plains is quite different to that of the higher elevated Ghat region. © 2017, Springer International Publishing AG, part of Springer Nature.Item The role of atmospheric correction algorithms in the prediction of soil organic carbon from hyperion data(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2017) Minu, S.; Shetty, A.; Minasny, B.; Gomez, C.In this study, the role of atmospheric correction algorithm in the prediction of soil organic carbon (SOC) from spaceborne hyperspectral sensor (Hyperion) visible near-infrared (vis-NIR, 400–2500 nm) data was analysed in fields located in two different geographical settings, viz. Karnataka in India and Narrabri in Australia. Atmospheric correction algorithms, (1) ATmospheric CORection (ATCOR), (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), (3) 6S, and (4) QUick Atmospheric Correction (QUAC), were employed for retrieving spectral reflectance from radiance image. The results showed that ATCOR corrected spectra coupled with partial least square regression prediction model, produced the best SOC prediction performances, irrespective of the study area. Comparing the results across study areas, Karnataka region gave lower prediction accuracy than Narrabri region. This may be explained due to difference in spatial arrangement of field conditions. A spectral similarity comparison of atmospherically corrected Hyperion spectra of soil samples with field-measured vis-NIR spectra was performed. Among the atmospheric correction algorithms, ATCOR corrected spectra found to capture the pattern in soil reflectance curve near 2200 nm. ATCOR’s finer spectral sampling distance in shortwave infrared wavelength region compared to other models may be the main reason for its better performance. This work would open up a great scope for accurate SOC mapping when future hyperspectral missions are realized. © 2017 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 Trends in extreme rainfall over ecologically sensitive Western Ghats and coastal regions of Karnataka: an observational assessment(Springer Verlag service@springer.de, 2018) Chandrashekar, V.D.; Shetty, A.Rainfall is one of the pivotal climatic variables, which influence spatio-temporal patterns of water availability. In this study, we have attempted to understand the interannual long-term trend analysis of the daily rainfall events of ? 2.5 mm and rainfall events of extreme threshold, over the Western Ghats and coastal region of Karnataka. High spatial resolution (0.25° × 0.25°) daily gridded rainfall data set of Indian Meteorological Department was used for this study. Thirty-eight grid points in the study area was selected to analyze the daily precipitation for 113 years (1901–2013). Grid points were divided into two zones: low land (exposed to the sea and low elevated area/coastal region) and high land (interior from the sea and high elevated area/Western Ghats). The indices were selected from the list of climate change indices recommended by ETCCDI and are based on annual rainfall total (RR), yearly 1-day maximum rainfall, consecutive wet days (? 2.5 mm), Simple Daily Intensity Index (SDII), annual frequency of very heavy rainfall (? 100 mm), frequency of very heavy rainfall (? 65–100 mm), moderate rainfall (? 2.5–65 mm), frequency of medium rainfall (? 40–65 mm), and frequency of low rainfall (? 20–40 mm). Mann-Kendall test was applied to the nine rainfall indices, and Theil-Sen estimator perceived the nature and the magnitude of slope in rainfall indices. The results show contrasting trends in the extreme rainfall indices in low land and high land regions. The changes in daily rainfall events in the low land region primarily indicate statistically significant positive trends in the annual total rainfall, yearly 1-day maximum rainfall, SDII, frequency of very heavy rainfall, and heavy rainfall as well as medium rainfall events. Furthermore, the overall annual rainfall strongly correlated with all the rainfall indices in both regions, especially with indices that represent heavy rainfall events which is responsible for the total increase of rainfall. © 2018, Saudi Society for Geosciences.Item Application of remote sensing and GIS for identification of potential ground water recharge sites in Semi-arid regions of Hard-rock terrain, in north Karnataka, South India(Springer Science and Business Media Deutschland GmbH, 2018) Bhagwat, T.N.; Hegde, V.S.; Shetty, A.Hydro-geomorphological characteristics, together with soil, slope, lineament density and Land use Land cover are signatures of potential ground water recharge areas, and are vital for water harvesting. In the present paper, Fifth order sub-basins in Semi-arid regions of the Varada River basin in South India is studied for selection of suitable area for recharge and prioritize the sub-basins using Indian Remote Sensing satellite (IRS) P6; Linear Imaging Self Scanning Sensor (LISS III) and ArcGIS 9.2. The Fifth order sub-basins of the Varada River spread in Hard-rock terrain and of different agro-climatic zones. The study shows that there are significant spatial variations in the fifth order basins with respect to their morphometric characteristics such as the basin area, drainage density, bifurcation ratio, and circularity ratio, constant of channel maintenance and slope of the basin. These variations reflect the differences in the hydrological process in the different Sub-basins. Based on the variations in the linear, aerial, relief as well as the slope, lineament density, and precipitation pattern rankings are assigned for each parameter with respect to ground water recharge within the Subbasins. Weighted sum overlay for precipitation, Land use, soil and Water table fluctuation are used to select the suitable areas of recharge within the sub-basins. Buffers created for lineaments and drainage networks were intersected with the suitable area of recharge for the probable tank's locations for recharge. The tank locations identified after intersection and having higher stream orders are further filtered for the identification of potential sites for ground water recharge. In the prioritized sub-basins SB-8, SB-10, SB-11 locations have been selected for recharge. © 2018, Springer International Publishing AG, part of Springer Nature.
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