The multi downscaled-scenario products allow us to better assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions (PDFs), of both the climatic variables, might help better understand the interdependence of the two, and thus in-turn help in accessing the future with confidence. In the present study, we have used multi-modelled statistically downscaled ensemble of precipitation and temperature variables. The dataset used is multi-model ensemble of 10 Global Climate Models (GCMs) downscaled product from CMIP5 daily dataset, using the Bias Correction and Spatial Downscaling (BCSD) technique, generated at Portland State University. The multi-model ensemble PDFs of both precipitation and temperature is evaluated for summer (dry) and winter (wet) periods for 10 sub-basins across Columbia River Basin (CRB). Eventually, Copula is applied to establish the joint distribution of two variables on multi-model ensemble data. Results have indicated that the probabilistic distribution helps remove the limitations on marginal distributions of variables in question and helps in better prediction. The joint distribution is then used to estimate the change in trends of said variables in future, along with estimation of the probabilities of the given change. The joint distribution trends are varied, but certainly positive, for summer and winter time scales based on sub-basins. Dry season, generally, is indicating towards higher positive changes in precipitation than temperature (as compared to historical) across sub-basins with wet season inferring otherwise. Probabilities of changes in future, as estimated by the joint precipitation and temperature, also indicates varied degree and forms during dry season whereas the wet season is rather constant across all the sub-basins.

Forested watersheds play a dominant role in the global hydrological cycle. Very few experimental observatories especially in tropical forested regions of India have been undertaken. This study has been initiated for this reason and to gain insights into functioning of the hydrological system in such climatic conditions. This study involves experimental setup of a watershed, it’s monitoring till date, modelling of the hydrological processes observed and the challenges in modelling components of the water balance in this watershed. A Small Experimental Watershed of 4.3 Km2 was set up at Mule Hole, in South India along the Kerala-Karnataka State borders, and is situated inside the Bandipur National park. After an overview of watershed studies, review of literature related to forest watershed studies and processes in the first two chapters, Chapter 3 introduces the study area, Mule Hole Experimental Watershed and explains the methodology used to study this watershed. Model SWAT was used initially to simulate the water balance components. A brief description of the model, methodology adopted and discussion on the results obtained is presented in Chapter 4. The watershed initially modelled as an ungauged watershed using the default parameters in the model, simulated very high groundwater contribution to the runoff. The calibrated model although performed favourably for annual average values and monthly calibration, the daily calibration was unsatisfactory. An auxiliary study on quantification of actual and potential evapotranspiration (ET0) has been carried out in Chapter 5 . Ten methods including Penman-Montieth were compared and evaluated for efficacy of the methods. All methods except for Hargreaves method showed agreement with the Penman-Montieth for annual average values. Priestly-Taylor method was found be the best estimator in comparison with Penman-Montieth method, when used to estimate AET. Adjusted Hargreaves and FAO Blaney -Criddle method were found to be very useful when few or limited climatic data were available for estimation of Potential evapotranspiration. A multidisciplinary approach of estimating recharge consisting of chloride mass balance technique coupled with study of water table fluctuations and groundwater flow analytical modelling has been attempted in Chapter 6. Direct and localized recharge was estimated at 45 mm/yr and indirect recharge 30 mm/yr for the monitored years in the watershed. The low values of recharge rates implied an unexpected very high evapotranspiration rate. It may be inferred that in the absence of groundwater flow to the stream, the recharge joins groundwater flow as outflow of the hydrologic system. An integrated lumped model incorporating the regolith zone and the capability of the tree roots to access this store is presented in Chapter 7. The model was able to simulate the pattern of lag-time between water table rise was observed in shallow piezometers in comparison with hillslope piezometers. The patterns of water table variation among the different hillslope piezometers suggest that they are linked with local processes and not by a regional aquifer dynamics. This study shows that water uptake, combined with the spatial variability of regolith depth, can account for the variable lag time between drainage events and groundwater rise observed for the different piezometers. Chapter 8 discusses the results, conclusions derived from this study and possibility of further scope of studies.

Hydro-climate extreme analysis helps understanding the process of spatio-temporal variation of extreme events due to climate change, and it is an important aspect in designing hydrological structures, forecasting floods and an effective decision making in the field of water resources design and management. The study evaluates extreme precipitation events over the Columbia River Basin (CRB), the fourth largest basin in the U.S., by simulating four CMIP5 global climate models (GCMs) for the historical period (1970-1999) and future period (2041-2070) under RCP85 GHG scenario. We estimated the intensity of extreme and average precipitation for both winter (DJF) and summer (JJA) seasons by using the GEV distribution and multi-model ensemble average over the domain of the Columbia River Basin. The four CMIP5 models performed very well at simulating precipitation extremes in the winter season. The CMIP5 climate models showed heterogeneous spatial pattern of summer extreme precipitation over the CRB for the future period. It was noticed that multi-model ensemble mean outperformed compared to the individual performance of climate models for both seasons. We have found that the multi-model ensemble shows a consistent and significant increase in the extreme precipitation events in the west of the Cascades Range, Coastal Ranges of Oregon and Washington State, the Canadian portion of the basin and over the Rocky Mountains. However, the mean precipitation is projected to decrease in both winter and summer seasons in the future period. The Columbia River is dominated by the glacial snowmelt, so the increase in the intensity of extreme precipitation and decrease in mean precipitation in the future period, as simulated by four CMIP5 models, is expected to aggravate the earlier snowmelt and contribute to the flooding in the low lying areas especially in the west of the Cascades Range. In addition, the climate change shift could have serious implications on transboundary water issues in between the United States and Canada. Therefore, adaptation strategies should be devised to cope the possible adverse effects of the changing the future climate so that it could have minimal influence on hydrology, agriculture, aquatic species, hydro-power generation, human health and other water related infrastructure.