A quantitative framework for estimating water resources in India

While issues related to water attract considerable attention in all spheres of life in India, very little quantitative information is available on the water budget of the country. There are primarily two reasons for this lacuna: first, the dearth of information on the variables associated with hydrology, and second, the absence of an easily accessible quantitative framework to put these variables in perspective. In this article, we discuss a framework that has been assembled to address both these issues. At the core of the framework is a hydrological routing model (HYDRA) that has been used to study the water balance of basins on various scales, ranging from a few square kilometres to continents. The basic data needed for implementing the framework are a suitable digital elevation model (DEM) and data on precipitation and evapotranspiration. Available discharge data can be used to validate the performance of the model. We demonstrate the viability of the framework by applying it to the hydrology of the Mandovi river on the western slopes of the Sahyadris; it is typical of the rivers along the Indian west coast. Most of the catchment area of the river is in Goa, but parts of the river also flow through Karnataka and Maharashtra. We use a 30" -resolution (∼ 1 km) DEM (GLOBE) and HYDRA to show that the model output mimics the observed discharge well, providing indirect validation for the surface run-off and sub-surface drainage values on which no data are available

A GPU-based integrated approach to simulation for deformable surface meshes

Surgical techniques have evolved from direct hands-on maneuvers to indirect minimally-invasive procedures, learning which involves using virtual simulation environments with standardized exercises typically comprising scene representation, collision-detection, force feedback, and rendering. Key challenges are the need to improve speed and realism of the simulation while being run on consumer-grade computing platforms. This thesis aims at overcoming these challenges by developing an algorithm to utilize the Graphics Processing Unit (GPU) as a parallel processor. The approach presented consists of three phases: Off-line surface wrapping, implicit integration algorithm for deformation, and tactile feedback. A prototype implementation using the NVIDIA GeForce 7600GS is presented. Interactive surface wrapping models a cloth-like surface into a closed mesh while the deformation phase is a GPU-based parallelized Implicit Euler method. Point-based haptic interaction with virtual coupling provides tactile feedback. The results show significant speedups, a maximum of 6.5 times, for the GPU-based simulation over its CPU counterpart