http://localhost:8081/jspui/handle/123456789/11 Wed, 22 Apr 2026 13:10:08 GMT 2026-04-22T13:10:08Z http://localhost:8081/jspui/handle/123456789/20363 Title: SPATIOTEMPORAL ANALYSIS OF SOIL MOISTURE AND PRECIPITATION DEPENDENCE OVER INDIA AND EUROPE Authors: J, Ashish Manoj Abstract: Anthropogenic climate change has impacted almost all phases of the global water cycle. Growing consensus asserts that extreme precipitation events will only rise in the years to come. However, an increase in extreme precipitation events does not necessarily correspond to higher flood risk. Much onus lies on the antecedent conditions before the storm events. Despite the importance of Soil Moisture (SM) – Precipitation (P) dependence in runoff generation, relatively few studies have unraveled the SM – P dependence. Previous studies were constrained by the direct trivial relationship existing between SM and P, and hence there is a need to understand direction and dynamical interdependency. We employed Event Coincidence Analysis (ECA) to identify and quantify the preconditioning of P extremes by soil moisture (SM) anomalies. In this work, we first disentangled the SM-P dependence patterns for the major river basins of India. High precursor coincidence rate (>45%) was obtained for traditional flash flood-prone areas over India - Ganga river basin, West-flowing rivers of Kutch and Saurashtra including Luni, inland drainage of Rajasthan and Narmada river basin, indicating the robustness of the approach. The trigger coincidence rate reveals strong SM-P coupling over central India. Our results indicate the applicability of ECA in characterizing the spatiotemporal patterns of SM-P dependence over India. The SM-P covariation relationships are established for the major climatic regions covering Europe in the second part of the thesis work. Our results indicate strong seasonal variations in such SM-P preconditioning over Europe. A significant shift in the magnitude and spatial extent of SM-P coupling is seen within the seasons for the various regions. In winter, strong coincidence is seen in western and central Europe, and the coincidence weakens in summer. We further used the timings of annual maximum discharge (Peak flood values) at a catchment scale from a European flood database to investigate how the seasonal and spatial variations in the timings of floods could be interpreted from the SM-P preconditioning perspective. Our results will strengthen existing flood risk assessment initiatives while providing new avenues and implications for a better understanding and proper representation of preconditioned compound flooding events worldwide. Fri, 01 Apr 2022 00:00:00 GMT http://localhost:8081/jspui/handle/123456789/20363 2022-04-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/20362 Title: UNDERSTANDING THE ROLE OF LAND USE-LAND COVER IN RUNOFF GENERATION IN THE UPPER KOSI RIVER CATCHMENT USING SWAT MODEL Authors: Kumar, Vivek Abstract: The land use-land covers (LULCs) alterations in the Himalayan regions are leading to different environmental issues such as change in the hydrological behaviour of the small catchments. The LULC changes in the regions are caused by different factors such as continuous deforestation, changes in climatic patterns, and anthropogenic activities such as the conversion of the forest area into agricultural land and agricultural area into pastureland. This study analysed the role of different LULCs on the water yield in different sub-basins of a Himalayan River, Upper Kosi, using a semi-distributed hydrological model, namely Soil and Water Assessment Tool (SWAT). The area of the Upper Kosi River catchment is 1469 km2 and the catchment was divided into 21 sub-basins and 75 Hydrological Response Units (HRUs) for modelling purposes. The SWAT model was calibrated and validated using SWAT-Calibration and Uncertainty Program (CUP) based Sequential Uncertainty Fitting (SUFI-2) algorithm. Out of the limited four years of data, the first two years (2014-15) were used for model calibration, and the next two years (2016-17) were used for model validation. A parameter sensitivity test was performed, and the most sensitive parameters were identified as GW_DELAY.gw, CH_N1.sub, GWQMN.gw, and RCHRG_DP.gw. The performance of the model was evaluated using standard metrics, namely, Nash Sutcliffe Efficiency (NSE), Coefficient of Determination (R2), and Percent-bias (PBIAS). For the calibration period, the performance metrics were 0.45 (NSE), 0.37 (R2), and 2.9 (PBIAS), and during the validation period, performance metrics were 0.60 (NSE), 0.75 (R2), and 2.07 (PBIAS). Despite the limited training model, the model performance was reasonably good during the calibration and validation periods, as indicated by performance metrics. The sub-basin scale analysis has shown that the upper Kosi River catchment receives a higher water yield contribution from the downstream sub-basins compared to the midstream and upstream sub-basins. Further, the water yield was analysed for the relative contribution of individual land covers to the watershed. It was found that urban areas have the highest contribution to surface runoff, followed by agricultural and forest lands, respectively. The contribution of mixed and evergreen forests to surface runoff was found to be approximately the same. Sun, 01 May 2022 00:00:00 GMT http://localhost:8081/jspui/handle/123456789/20362 2022-05-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/20361 Title: HYDROGRAPH SEPARATION AND SNOWMELT MODELLING OF RIVER BHAGIRATHI AT HARSHIL Authors: Sharma, Shrishti Abstract: Snowbound and glacier-bound catchments of the Himalayas are the prime water source for a wide range of the population. The population downstream relies on the streamflow from such catchments to fulfil their domestic, industrial, and agricultural water demands. Water from snow and glacier melt is a significant component of the annual streamflow apart from direct runoff and baseflow. With increasing global warming, there has been a significant loss in glacier and snow cover, which will increase river flow due to the increase of glacier melt and snowmelt. This brings a change in the runoff pattern and the contribution of different sources in runoff in the basin in both space and time. However, over time, due to the excessive retreat of glaciers, the snowmelt contribution would reduce, and the river discharge would reduce, causing a reduction in water availability downstream. Therefore, it becomes essential that the study for quantifying the contribution of different sources to the streamflow and modelling is done to understand the streamflow dynamics in a much better way. The current study aims to model the discharge on the snowmelt runoff model (2016 -2021) and also to quantify end members' contributions to the river Bhagirathi at Harshil for the winter and spring seasons (1 December 2021- to -9 April 2022). The hydrograph separation is done by application of isotope hydrology. A three-component mixing model is applied using EC and δ 18O as tracers. The average percentage of contribution of surface runoff, groundwater, and ice melt is 13.07 %, 44.66% and 42%, respectively. The groundwater was the major contributor before the ablation started, with an average percentage contribution of around 46.46 %. The ablation starts in second week of march, and ice melt contribution starts rising and peaks at 61.20 % at the end of the study period. For the snowmelt runoff modelling, the snow cover area and hydroclimatic data are used to model the discharge at Harshil. The model is calibrated from July 2016 to Dec 2018 and validated from 2019 to December 2021. The average Dv and NSE are -2.20% & 0.92 during calibration and -6.27 % & 0.89 during validation, respectively. Fri, 01 Apr 2022 00:00:00 GMT http://localhost:8081/jspui/handle/123456789/20361 2022-04-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/20360 Title: DROUGHT CHARACTERIZATION AND PROPAGATION OVER INDIAN SUB-CONTINENT: A COMPLEX NETWORK APPROACH Authors: Rawat, Shivam Abstract: Drought is a natural disaster that affects water resources, agriculture, and social and economic development due to its long-term and frequent occurrence. However, spatiotemporal assessment of drought characteristics over India at the sub-basin scale based on terrestrial water storage is unexplored. In the first part of this study, the terrestrial water storage anomalies (TWSA) obtained from a Gravity Recovery and Climate Experiment and precipitation data are used to compute Combined Climatological Deviation Index (CCDI) and GRACE-Drought Severity Index (GRACE-DSI). The trend characteristics of GRACE-DSI and CCDI are investigated using the non-parametric Mann-Kendall test, and its slope is estimated using the Theil-Sen slope estimator. Our results showed that GRACE-DSI exhibits significant negative trends over most of the Indian sub-basins compared to CCDI, indicating that most of the drought events are due to depletion of TWS. The sub-basin showing significant negative GRACE-DSI trends and significant positive CCDI trends conclude that precipitation is available, preventing TWS from depletion. The number of sub-basins showing significant negative trends for GRACE-DSI is more than that for CCDI. Hence TWS is depleting for most of the subbasins in India. The maximum drought duration obtained by GRACE-DSI and CCDI is 26months (2002-2004) and 17 months (2013-2015), respectively. The maximum drought severity computed by GRACE-DSI and CCDI is -44.2835 and -13.4392, respectively. In the second part of this study, we have utilized a complex network technique to study the drought propagation over the Indian subcontinent. In Methodology, we first computed drought event series based on GRACE-DSI. Then by the event synchronization method, we computed the strength matrix. By applying the threshold value, we have converted the strength matrix into an adjacency matrix and then constructed the network. After network construction, we have computed network matrices like degree, indegree, outdegree, betweenness centrality, and closeness centrality. Out results show that Krishna upper, Krishna middle, Manjra, the Godavari lower, and Mahanadi lower subbasins are more critical subbasins because they have high degree values between 33 to 42. The Godavari lower, Krishna upper, and Mahanadi lower subbasins are more important pathways for drought propagation because they have a high value of betweenness centrality. Fri, 01 Apr 2022 00:00:00 GMT http://localhost:8081/jspui/handle/123456789/20360 2022-04-01T00:00:00Z