Well-Observed Time Series Does Speak for Itself!

Our research focus on extracting the inherent characteristics of hydro-climatologic system from the time-series itself. This is particularly significant considering the complexity of the hydro-climate system and the inadequate information of system sub-components. Lack of holistic knowledge about such complex hydro-climatic systems steered us to hypothesise that "A well-observed time-series does speak for itself!" Concepts of chaos theory and phase-space re-construction are applied to unveil the nonlinear physical linkages between global-climatic causative factors and hydrologic-extreme episodes. Novel algorithms are developed to reduce predictive uncertainty by minimizing the infamous butterfly-effect and improving the model perfection. Further, we also focus on mapping and enhancing the predictability of different hydro-climatic variables to improve the hydrological predictions.

Climate Change Impact Assessment and Regional Downscaling

Water resources is inextricably linked with climate. Globally, the negative impacts of future climate change on freshwater systems are expected to outweigh the benefits. Climate change affects the function and operation of existing water infrastructure - including hydropower, structural flood defences, drainage and irrigation systems - as well as water management practices (IPCC, 2008). The primary concerns regarding climate projections while incorporating it in hydroclimatology field are the following: (i) Reliability of future projections and associated uncertainties (ii) Suitable downscaling model which replicates the regional scale hydro-climatic system (iii) Non-stationarity of hydrologic variables and inter-relationship etc. Our group work on developing methodologies to improve the reliability by reducing the uncertainties in future projections.

Regional Hydrolgic Modeling and Land-Use Land-Cover Changes

The linkages between water resources and climate is captured through hydrological modeling at a regional or watershed scale. Hydrological modeling helps to attain a good insight into the hydrological processes required for an efficient water resources management. Our research emphasize on parameter estimation on hydrological models and also to assess the climate change impacts in river basins through hydrological models such Variable Infiltration Capacity (VIC), Soil Water Assessment Tool (SWAT) etc. Implications of climate change in hydrologic extremes and water availability in the basin, spatial and temporal scale effects, land-use land-cover changes are essential to be explored.

Hydrolgical Hazards and Extreme Events Modeling

Extreme events though occur rarely, have adverse impact on water resources management. Rarity often limits the application and efficiency of models in simulating these events. Recent revelation of rapid climate change further aggravates this issue. We are particualrly interested in exploring the evolution of extremes, the intensity-duration-frequency characteristics and the effect of non-stationarity and interdependency in extreme event modeling. Effect of dominant teleconnections in extremes, flood and drought prone areas and the associated spatio-temporal severity are topics worth exploring.

Land Surface Processes Modeling

In regional climate modeling, one of the major drivers of climate variability is the natural and human induced land-use land-cover (LULC) changes. Undoubtedly, any potential changes in land-use have impacts on water resources. However, quantifying these impacts and incorporating these processes in any climate model remains a challenging problem in studies on climate change impact on water resources. Regional climate modeling with land surface schemes and dynamic vegetation need to be emphasized especially in tropical regions with heterogeneous land surface, dynamic vegetation growth and spatio-temporally varying irrigation. The rising population and interference of human influences make the problem even more complex. We emphasize on selecting and parametrizing specific land surface schemes which can model and replicate a region's atmosphere-land feedbacks accounting the vegetation heterogeneity.