Faculty Publications
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Publications by NITK Faculty
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Item Future transition in climate extremes over Western Ghats of India based on CMIP6 models(Springer Science and Business Media Deutschland GmbH, 2023) Shetty, S.; Umesh, P.; Shetty, A.The effect of climate change on the tropical river catchments in the Western Ghats of India is studied using the Coupled Model Intercomparison Project-6 data (CMIP-6). Multi-model ensembles of rainfall and temperature are constructed using the Random Forest ensemble technique for bias-corrected GCMs in the near future (2014–2050) and far future (2051–2100) horizons. For the two catchments each in the southern, central, and northern Ghats, the trend in minimum and maximum temperatures, precipitation, and other indices are calculated. By 2100, dry sub-humid and humid catchments will see a higher increase in mean annual temperature than per-humid central catchments. In future decades, the warm days and nights increase by 45–50% and 40–70%, respectively, with twofold warming in the winter season. Under a climate change scenario, annual rainfall increases in Vamanapuram, Ulhas, and Purna, while Chaliyar, Netravati, and Aghanashini catchments experience a decrease in rainfall in the far future with an increase in pre-monsoon rainfall. The southern catchments are anticipated to have contrasting variations in the rainfall extremes; northern catchments face a substantial increase in very wet to extremely wet days and medium to heavy rainfall. In all catchments (excluding Vamanapuram), cumulative wet days increase with a decrease in cumulative dry days. After the mid-twenty-first century, humid to per-humid catchments encompass an increase in cool nights, whereas it disappears in dry sub-humid catchments of the Ghat. Interestingly, warming tendencies begin to slow down after 2050. This investigation can assist in comprehending the regional climate extremes in the Western Ghats to formulate better climate risk planning and adaptation strategies. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.Item Quantification of change in land cover and rainfall variability impact on flood hydrology using a hydrological model in the Ethiopian river basin(Springer Science and Business Media Deutschland GmbH, 2023) Tola, S.Y.; Shetty, A.Changes in land cover and climate are the dominant factors that significantly impact the hydrological process. However, the impact on flood response behaviour varies spatiotemporally. This study quantitatively assessed the effects of individual and coupled changes in land cover and climate on peak and high flows in the upstream and downstream parts of the Upper Awash River basin. Two time periods were chosen for comparison: baseline (1988–2001) and evaluation (2002–2015). The Soil Water and Assessment Tool (SWAT) was used to estimate the impact of these changes. The model satisfactorily simulated daily and extreme flows. The evaluation of annual maximal discharge variability between 1985 and 2015 at upstream and downstream stations showed significant positive and insignificant negative trends, respectively. However, the sub-basin’s annual wet day rainfall (PRCPTOT) showed a downward trend. The annual maximal discharge–PRCPTOT relationship was significant during the baseline but later had no significance. The SWAT model showed that the main factor that affected the changes in upstream flow was the land cover change, increasing peak and high flow by 38.69% and 11.95%, respectively, compared to the baseline period. However, combined changes resulted in downstream peak and high flow reductions of 19.55% and 50.33%, respectively. As a result, changes in flood characteristics are strong functions of land cover, especially in the upstream sub-basin and land cover and climate in the downstream sub-basin. Overall, the impact of changes in the cropland-dominated basin was noticeably different. The study assists water resource managers in understanding the causes of hydrological dynamics and developing mitigation strategies. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.Item The effectiveness of machine learning-based multi-model ensemble predictions of CMIP6 in Western Ghats of India(John Wiley and Sons Ltd, 2023) Shetty, S.; Umesh, P.; Shetty, A.The popularity of cutting-edge machine learning ensemble approaches has solved many climate change research and prediction issues. The six top-performing GCMs obtained from Technique for Order Preference by Similarity to an Ideal Solution were ensembled using seven machine learning ensemble methods such as Random Forest Regressor (RFR), Support Vector Regressor (SVR), Linear Regression (LR), Adaptive Boosting Regressor (AdaBoost), Extreme Gradient Boosting Regressor (XGBR), Extra Tree Regressor (ETR), Multi-Layer Perceptron neural network (MLP) and simple Arithmetic Mean (AM) over the diverse geo-climatic basins. Precipitation is best simulated by EC-Earth3 and BCC-CSM2-MR. Maximum temperature by MPI-ESM1-2-HR, EC-Earth3-Veg, INM-CM5-0 and MPI-ESM1-2-LR. Minimum temperature by INM-CM5-0 and MPI-ESM1-2-LR model. The MME of XGBR and RFR stand out for their superior performance across all six basins, with exceptional performance over the per-humid basins, while AdaBoost, SVR and the AM underperform. Examining the interseasonal variability of the simulated MMEs over the basins highlights the reliability of these MME models. The anticipated change in maximum and minimum temperature in the SSP245 and SSP585 in the future horizon corroborates the undeniable rise in temperature by all the MMEs with a dramatic change in future temperature in AM and AdaBoost in precipitation with a factor of two rises in the far future over the recent past. Though climate change is expected to increase precipitation, atmospheric stabilization over the Ghats will affect the spatiotemporal distribution of precipitation. We recommend a comprehensive testing and validation approach to generate ensembles in regional investigations involving complicated and diverse precipitation mechanisms. © 2023 Royal Meteorological Society.Item Flood hazard map of the Becho floodplain, Ethiopia, using nonstationary frequency model(Springer Science and Business Media Deutschland GmbH, 2024) Tola, S.Y.; Shetty, A.Flood estimates based on stationary flood frequency models are commonly used as inputs to flood hazard mapping. However, changing flood characteristics caused by climate change necessitate more accurate assessments of the probabilities of rare flood events. This study aims to develop a flood hazard map based on the nonstationary flood frequency using a generalized extreme value distribution model for the Becho floodplain in the upper Awash River basin. The distributional location parameter was modeled as a function of rainfall amount of different durations, annual total precipitation from wet days, yearly mean maximum temperature and time as covariates. The one-dimensional Hydrological Engineering Center River Analysis System (HEC-RAS) hydraulic model with steady flow analysis was used to generate flood hazard map input, depth and velocity, and inundation extent for different return periods. The result indicated that the model as a function of rainfall, such as monthly rainfall (August) and annual wet day precipitation, provided the best fit to the observed hydrological data. Rainfall as a covariate can explain the variation in the peak flood series. The developed hazard map based on depth alone and the combination of depth and velocity thresholds resulted in more than 70% of the floodplain area being classified as a high hazard zone under 2, 25, 50, and 100-years return periods. The current study assists water resource managers in considering changing environmental factors and an alternative flood frequency model for developing flood hazard management and mitigation strategies. © The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2023.Item Multiscenario Analysis of Hydrological Responses to Climate Change over River Basins of the Western Ghats of India(American Society of Civil Engineers (ASCE), 2024) Shetty, S.; Umesh, P.; Shetty, A.In the face of rising greenhouse gas concentrations, our study investigates the intricate regional dynamics of hydrological responses across three vital river basins of the Western Ghats of India. Employing advanced eXtreme Gradient Boosting (XGBoost) ensemble models based on Coupled Model Intercomparison Project (CMIP6) data, the article explores the anticipated changes in the climate variables under two future scenarios. The findings reveal a compelling narrative of temperature fluctuations, with increased warming in future decades from November to June ushering in warmer winters and extended summer seasons. These climatic shifts carry profound implications for rainfall patterns, potentially disrupting rainfall during the pivotal months of June and July up to the decade 2030s, with a more pronounced increase in the Purna River Basin (PRB) after the decade 2050s. The projected future climate scenarios indicate that the Vamanapuram River Basin (VRB) and PRB will experience contrasting patterns of dry and wet events, with the VRB facing severe to extreme dry and the PRB witnessing increased moderate to extreme wet events under high-emission scenarios. Additionally, the PRB may experience the paradox of increasing wetness and aridity. These insights provide crucial guidance for policy formulation and adaptation measures to safeguard agriculture and other vital sectors in the face of evolving climate conditions. © 2024 American Society of Civil Engineers.