1. Ph.D Theses
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Item Analysis of Influence of Land Use Land Cover and Climate Changes on Streamflow of Netravati Basin, India(National Institute Of Technology Karnataka Surathkal, 2023) Jose, Dinu Maria; G S, DwarakishMassive Land Use/Land Cover (LULC) change is a result of human activities. These changes have, in turn, affected the stationarity of climate, i.e., climate change is beyond the past variability. Studies indicate the effect of LULC change and climate change on the hydrological regime and mark the necessity of its timely detection at watershed/basin scales for efficient water resource management. This study aims to analyse and predict the influence of climate change and LULC change on streamflow of Netravati basin, a tropical river basin on the south-west coast of India. For future climate data, researchers depend on general circulation models (GCMs) outputs. However, significant biases exist in GCM outputs when considered at a regional scale. Hence, six bias correction (BC) methods were used to correct the biases of high-resolution daily maximum and minimum temperature simulations. Considerable reduction in the bias was observed for all the BC methods employed except for the Linear Scaling method. While there are several BC methods, a BC considering frequency, intensity and distribution of rainfall are few. This study used an effective bias correction method which considers these characteristics of rainfall. This study also assessed and ranked the performance of 21 GCMs from the National Aeronautics Space Administration (NASA) Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset and bias-corrected outputs of 13 Coupled Model Inter-comparison Project, Phase 6 (CMIP6) GCMs in reproducing precipitation and temperature in the basin. Four multiple-criteria decision-making (MCDM) methods were used to identify the best GCMs for precipitation and temperature projections. For the CMIP6 dataset, BCC-CSM2-MR was seen as the best GCM for precipitation, while INM-CM5-0 and MPIESM1-2-HR were found to be the best for minimum and maximum temperature in the basin by group ranking procedure. However, the best GCMs for precipitation and temperature projections of the NEX-GDDP dataset were found to be MIROCESM-CHEM and IPSL-CM5A-LR, respectively. Multi-Model Ensembles (MMEs) are used to improve the performance of GCM simulations. This study also evaluates the performance of MMEs of precipitation and temperature developed by six methods, including mean and Machine Learning (ML) techniques.The results of the study reveal that the application of an LSTM model for ensembling performs significantly better than models. In general, all ML approaches performed better than the mean ensemble approach. Analysis and mapping of LULC is essential to improve our understanding of the human-nature interactions and their effects on land-use changes. The effects of topographic information and spectral indices on the accuracy of LULC classification were investigated in this study. Further, a comparison of the performance of Support Vector Machine (SVM) and Random Forest (RF) classifiers was evaluated. The RF classifier outperformed SVM in terms of accuracy. Finally, the classified maps by RF classifier using reflectance values, topographic factors and spectral indices, along with other driving factors are used for making the future projections of LULC in the Land Change Modeler (LCM) module of TerrSet software. The results reveal that the area of built-up is expected to increase in the future. In contrast, a drop in forest and barren land is expected. The SWAT model is used to study the impacts of LULC and climate change on streamflow. The results indicate a reduction in annual streamflow by 2100 due to climate change. While an increase in streamflow of 13.4 % is expected due to LULC change by the year 2100 when compared to the year 2020. The effect of climate change on streamflow is more compared to LULC change. A reduction in change is seen in the streamflow from near to far future.Item Characterization Of Historical and Future Hydrometeorological Droughts in an Indian Tropical River Basin(National Institute of Technology Karnataka, Surathkal, 2020) Pathak, Abhishek A.; Dodamani, B M.Drought is acknowledged as a significant natural disaster which leads to food, fodder, and water shortages along with destruction of vital ecological system. Drought is a transient recurring sinister disaster, which originates from the lack of precipitation and further creeps into different subdivisions of hydrological cycle causing adverse effects on agricultural and its allied sector. Combination of these leads to economic losses and several damage to living organisms. Identifying and quantifying drought characteristics of a region is must to understand the behavior of drought and its profound impacts on society, economy, and environment. Along with the historical knowledge, comprehensive overview of future drought projections is a vital step in ensuring future water and food security. The present study focuses on characterizing different hydrometeorological droughts in the historical and future climate of an agrarian Indian river basin. The specific objectives of the study are 1) To investigate annual and seasonal trends of hydro meteorological variables, over the study area. 2) Assessment and comparison of Meteorological, Hydrological and Agricultural drought characteristics with multiple indices 3) To explore the applicability of copulas theory for joint modeling of drought characteristics 4) Characterization of future hydro-climatic droughts. The study was implemented in the Ghataprabha river basin, being one among the potential lands for agriculture in the basin of river Krishna. Firstly, the basin has been categorized in to humid, sub humid and semiarid region based on Aridity Index. Similarly, groundwater well of the study area are grouped in to different clusters using hierarchical and non-hierarchical clustering methods The annual and seasonal trend analysis of different hydrometeorological variables are carried out using Mann-Kendall trend test and the magnitude of the trend was estimated using the Sen’s Slope Estimator. A non-significant decreasing trends in both rainfall and rainy days was observed in semiarid region during monsoon period. Significant increasing trend in mean temperature was observed for all the stations and for all the seasons with the average magnitude of 0.2⁰ C per decade. Along with the mean temperature, annual andseasonal PET trends were also increasing for all the stations but are significant only in semiarid region with the average increase of 3.5mm per decade. The trends in annual streamflow of the basin are decreasing with magnitude of 574.25 cumecs/year, whereas, no significant trends were observed in the reservoir levels. The trend analysis of the groundwater levels of different clusters, revealed that annual water level in the 81% of the wells of cluster 2 and 47% of the total wells of the study area are significantly declining. The hydrometeorological droughts assessment with different indices portrayed significant number of droughts in the past. The RDI and SPI are behaving similarly in all the stations whereas, significant discrepancies was observed between SPI/RDI and SPEI. The hydrological drought assessed with SDI followed similar pattern with SRSI whereas it showed significant divergence with meteorological droughts. Similarly, Agricultural drought derived through VCI followed similar pattern of SPI-6 in comparison with SPI-3. A teleconnection between meteorological drought and groundwater drought was observed along with the crucial role of underlying hydrogeological characteristics. Joint modelling of hydrometeorological drought characteristics and regional bivariate frequency analysis was carried out by employing Archimedean copula. An attempt has also been made to characterize drought in multivariate perspective by developing Standardized Hydro Meteorological drought Index. From the results of bivariate frequency analysis of meteorological drought, it was observed that, droughts of high severity with prolonged duration are frequent in semiarid region compared to humid and sub-humid regions. The joint probability of hydrological drought conveyed drought of smaller duration or severity are more prominent in the basin whereas joint return periods of groundwater drought is high in the well of cluster 2. The developed SHMI considers combined effects of precipitation and streamflow to picturize a near realistic drought scenario of the basin. The future hydrometeorological drought characteristics were assessed by different RCMs. The different bias correction methods were applied to rainfall and temperature to raw RCMs and observed that CNRM-CM5 with LS bias correction method performed better for correcting the rainfall and VS is proved to be superior for correcting the temperature projections. The trend analysis carried out for the future hydrometeorological variable showed significant decreasing trends in annual and post monsoon season whereas temperature trend is increasing significantly with the rise of 0.150 C per decade. The future hydro-meteorological drought characteristics revealed that the basin will experience more number of droughts compared to the past and it can be attributed to decreasing rainfall trend and significant rise in temperature of the basin. In this study, an attempt has been made to characterize future and historical hydrometeorological droughts comprehensively. The outcome of the study will be helpful to design proactive drought mitigation and preparedness strategies for upcoming drought and it also provides a framework to evaluate the drought risks at other parts of the world.