Faculty Publications
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Item Analysis of extreme rainfall events over Nethravathi basin(Taylor and Francis Ltd., 2014) Babar, S.; Ramesh, H.India gets three fourths of its annual rainfall during the south-west monsoon season (June-September). The study of extreme events is significant in the stochastic behaviour of rainfall pattern. The aim of the present work is to compare different methods; and find a suitable method to study extreme rainfall trend analysis. In this study, frequency distribution method, generalized extreme value (GEV) distribution, Mann-Kendall and Sens slope estimator are used for rainfall trend analysis over the Nethravathi basin located in the southern part of India. The rainfall data during the monsoon months (June-September) were analysed for a period of 1971-2010. The comparison of all the methods had been carried out and it has been observed that there is an increasing trend of frequency in class-1 and decreasing trend in class-2 and class-3, respectively. The interpretation of the results is carried by using the GEV distribution and non-parametric trend analysis (Mann-Kendall and Sens slope estimator test). It turns out the best results to identify the extreme rainfall trend are obtained by the statistical techniques - Block Maxima (GEV) distribution, Mann-Kendall and Sens slope estimator test as compared to frequency-based method. The above results which help to study climate change will contribute towards sustainable development of the Nethravathi River basin. © 2013 © 2013 Indian Society for Hydraulics.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 Integrated assessment of bias correction techniques, CMIP6 model rankings, and multi-model ensemble optimisation across diverse temporal scales for regional climate projection in Kerala, Southwestern India(Springer Science and Business Media Deutschland GmbH, 2025) Athithottam, S.M.; Ramesh, H.In the context of climate change, CMIP6 (Coupled model intercomparison project phase 6) General Circulation Models (GCMs) are indispensable for projecting global and regional climate impacts, including temperature rise, precipitation variability, and extreme weather events. These models serve as the basis for Intergovernmental Panel on Climate Change (IPCC) assessments and are crucial for informing mitigation and adaptation strategies. However, their coarse resolution and systematic biases limit their direct application in local-scale climate impact studies. This motivates the present study, which aims to enhance the reliability of CMIP6 precipitation projections over Kerala, a monsoon-dominated, topographically complex region susceptible to rainfall variability. This study employs the CRITIC–TOPSIS (Criteria Importance through intercriteria correlation and technique for order of preference by similarity to ideal solution) framework to comprehensively evaluate bias correction methods, GCM performance, and multi-model ensembling (MME) techniques across multiple temporal scales. Observed daily rainfall data from the India Meteorological Department (IMD) serve as the reference for model evaluation. This integrated, data-driven approach enables robust ranking and selection of optimal models and techniques for regional application. The findings reveal considerable variability in model performance across time scales. ACCESS-ESM1-5 performs consistently well, while MRI-ESM2-0 and HadGEM3-GC31-LL are more suited to long-term projections. IITM-ESM and CMCC-CM2-SR5 show strength in short- to medium-term applications. Advanced ensemble methods, such as Support Vector Machines, Gradient Boosting Machines, Random Forests, and LightGBM, outperform simpler methods in capturing rainfall variability. The study’s results provide practical guidance for selecting climate models and designing ensemble strategies, particularly for hydrological forecasting, infrastructure planning, and climate risk assessment in Kerala and similar monsoon-prone regions. Overall, this research contributes to advancing regional climate modelling practices and supports informed, climate-resilient decision-making at policy and planning levels. © The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences 2025.