Faculty Publications
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Item Assessment of hydropower potential in Nethravathi river basin using SWAT model(CAFET INNOVA Technical Society cafetinnova@gmail.com 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda, Hyderabad 500029, 2015) Babar, S.; Shobhita, M.P.; Ramesh, H.Hydropower plants have the advantage of producing renewable and clean power, the renewable and reliable energy source that serves national environmental and energy policy objectives. Therefore, the development of hydropower plant and improvements of water management have essential in contributing to sustainable growth and energy production in developing countries like India. The present study is concerned with the development of methodology and assessment of hydropower potential in the Nethravathi River basin with the help of Remote Sensing and GIS. The drainage area covers about 3190 km2 at Bantwal gauging point, and most of the land cover of the basin is dominated by forest. The basin was divided into six sub-basins based on hydrology and topography using GIS tools. The climate over the basin is coastal humid tropical and receives an average annual rainfall of about 4000 mm. sub-basin discharges were estimated using the Soil Conservation Services (SCS) curve number method. To ensure the total discharge from six sub-basins computed from SCS curve number method, the flows were routed and simulated at the gauging location using Soil and Water Assessment Tool (SWAT). SWAT model was calibrated for monthly time steps from 1998–2001, and validated for 2002–2003. Flow-duration curves (FDC) were generated for each sub-basin to assess the dependable yield. The results have shown a good agreement between observed and the simulated flows. The available discharge at 75%, 80% and 90% of time for each sub-basin were extracted from the FDC. This result were used to calculate the hydropower potential in all the six sub-basins at Q75, Q80 and Q90, by integrating thematic layers using ArcSWAT. © 2015 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.Item Analysis of climate trend and effect of land use land cover change on Harangi streamflow, South India: a case study(Springer Science and Business Media Deutschland GmbH, 2017) Anil, A.P.; Ramesh, H.Land use land cover (LULC) and climate change are considered to be driving factors contributing to the alteration of the hydrological regime. Therefore, an attempt has been made to study climate trend and the effect of LULC on streamflow in a basin covered predominantly by forest. The Harangi river basin is one of such basins located in the western ghats of South India. The LULC trend was carried out by considering temporal multispectral data for the years 1990, 2002 and 2008 obtained from Landsat-5TM and IRS 1C (Indian Remote Sensing Satellites). Climate parameters such as rainfall and temperatures were considered for the trend analysis in this study. The rainfall trend was studied using Man-Kendall and Sen’s slope method to understand the spatio-temporal variability. Rainfall shows the decrease trend at Suntikoppa rain gauge station in January and June months. Harangi and Madapura rain gauge stations also show a decrease of rainfall trend for only January month. Temperature trend show increase in maximum temperature for the month of April, May and November whereas increase in minimum temperature was observed in the month of November and December. Spatial extent of LULC found that 52.4% (220.014 km2) of the study area was covered with forest in 1990 which has considerably decreased to 43.9% (184.53 km2) in 2008. There was a rise in total area of plantation crops from 106.27 km2 (25.32%) to 138.20 km2 (32.9%) during this period. Soil and Water Assessment Tool (SWAT) was used to study the effect of LULC on streamflow. SWAT model was calibrated and validated using observed daily streamflow data. The coefficient of correlation (r2) was found to be 0.87 and 0.86 for calibration and validation, respectively. The results found the annual streamflow to increase by 0.77% from 1990 to 2008 whereas the mean monthly streamflow has increased by 9.46% during this period. This was mainly due to the reduction in forest area observed in LULC maps. © 2017, Springer International Publishing Switzerland.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 An ANN supported mathematical morphology based algorithm for lakes extraction from satellite images(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2018) Rishikeshan, C.A.; Ramesh, H.With advances in remote sensing (RS) technology and platforms, more and more high-quality and fine spatial resolution satellite images are available. Manual method of feature extraction from remote sensing imagery is a tedious and time-consuming process. Thus automated and replicable technique plays vital role in updating lake database to evaluate the spatial and temporal evolution of lakes and ponds especially for vastly growing urban areas. This research work presents an artificial neural network (ANN) computed threshold value-based mathematical morphology (MM)-driven approach for extraction of lakes from satellite imageries with better accuracy. Accuracy of developed methodology has been assessed with the ground truths of the study area revealing better performance with different data-sets compared to existing methods. On an average scale for all data-sets used, the proposed algorithm is able to extract lakes with 99.47% accuracy and 0.9397 correlation coefficient (MCC). The existing classification method exhibited an accuracy of 98.75% and correlation coefficient of 0.89049. Similarly, the existing threshold-driven method has 99.31% accuracy and 0.90374 correlation coefficient. Maintenance of actual size and shape of the lakes, run-time control over structuring elements, semi-automation, faster processing, and single band adaptability are features of this work. © 2017 Indian Society for Hydraulics.Item The impact of spatiotemporal patterns of land use land cover and land surface temperature on an urban cool island: a case study of Bengaluru(Springer International Publishing, 2019) Govind, N.R.; Ramesh, H.In most of the developing countries, man-made developments in the environment have led to the growing demand to contextualize the land use land cover (LULC) changes and land surface temperature (LST) variations. Due to the modification in the surface properties of the cities, a difference in energy balance between the cities and its nonurban surroundings is observed. The aim of this study is to analyze the spatial and temporal patterns of LULC and LST and its interrelationship in Bengaluru urban district, India, during the period from 1989 to 2017 using remote sensing data. Intensity analysis was performed for the interval to analyze the LULC change and identify the driving forces. The impact of LULC change on LST was assessed using hot spot analysis (Getis–Ord Gi* statistics). The results of this study show that (a) dominant LULC change experienced is the increase in urban area (approximately 40%) and the rate of land use change was faster in the time period 1989–2001 than 2001–2017; (b) the major transition witnessed is from barren and agricultural land to urban; (c) over the period of 28 years, LST patterns for different land use classes exhibit an increasing trend with an overall increase of approximately 6 °C and the mean LST of urban area increased by about 8 °C; (d) LST pattern change can be effectively analyzed using hot spot analysis; and (e) as the urban expansion occurs, the cold spots have increased, and it is mainly clustered in the urban area. It confirms the presence of an urban cool island effect in Bengaluru urban district. The findings of this work can be used as a scientific basis for the sustainable development and land use planning of the region in the future. © 2019, Springer Nature Switzerland AG.