Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
7 results
Search Results
Item Analysis of variability and trends in rainfall over northern Ethiopia(Springer Verlag service@springer.de, 2016) Kiros, G.; Shetty, A.; Nandagiri, L.Rainfall is a key component of the hydrological cycle, and its spatiotemporal variability is essential from the both scientific and practical perspectives. This study is focused on analysis of temporal variability and trends in historical rainfall records for stations in the Geba River basin. The Geba catchment is surrounded by the Danakil basin in the east, by the Tekeze River basin in the south, and the Werie River basin in the west which is located in the northern Ethiopia regional state of Tigray between 38° 38? E and 39° 48? E and 13° 18? N and 14° 15? N. The climate over the basin is semi-arid and has large elevation differences varying from 926 to 3301 m above mean sea level. Daily rainfall data of 43 years measured at seven stations in the basin for the period of 1971 to 2013 for annual and seasonal rainfall trends have been processed and used for the analysis. The non-parametric Mann–Kendall test and the Sen’s slope estimator have been used to identify the existence of trends and slope magnitude in rainfall. Results revealed that although there was a mix of positive and negative trends, they were no statistically significant except at one station which showed an increasing trend in annual rainfall. Considering rainfall in different seasons, an increase in rainfall was observed in two stations in the wet season which, however, was not statistically significant. For the remaining stations, a weak decline in wet season rainfall (not statistically significant at 95 % confidence level) for four stations and absence of trend for one station were noticed. Furthermore, no statistically significant trend (positive or negative) was evident for the dry season rainfall. Results of this study may prove useful in the preparation of climate change mitigation and adaptation strategies in rainfed agricultural and water supply systems in the region. © 2016, Saudi Society for Geosciences.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 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 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 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 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.