Balaji Narasimhan

Indian Institute of Technology Madras | IIT Madras · Department of Civil Engineering

Departures in precipitation from the normal are the cause of the onset of agricultural drought. In this study, we aim to identify extreme precipitation deficits using an index called Percent Normal (PN). We applied the proposed PN index to the agriculturally productive Mekong River Basin (MRB) to evaluate the propagation of precipitation deficits i...

The southern peninsular India is characterized by unique climatology with rainfall processes throughout the year from land-ocean contrasts. In addition, the complex terrain induces localized effects causing huge spatial and temporal variability in the observed precipitation. This study aims at evaluating the sensitivity of the high-resolution Weath...

Extreme events like floods and droughts are of concern for any country in the context of the damage caused to life as well as property. This situation calls for adequate management measures such as flood plain mapping, in order to minimize the extent of damage. ASTER(Advance Space Borne Thermal Emission and Reflection Radiometer) DEM(Digital Elevat...

Discrete groundwater level datasets are interpolated often using kriging group of models to produce a spatially continuous groundwater level map. There is always some level of uncertainty associated with different interpolation methods. Therefore, we developed a new trend function with the mean groundwater level as a drift variable in the regressio...

Richards equation is solved for soil water flow modeling in the unsaturated zone continuum. Interblock hydraulic conductivities, while solving for Richards equation, are estimated by some sort of averaging process based on upstream and downstream nodes hydraulic conductivity values. The accuracy of the interblock hydraulic conductivity estimation m...

Kerala state (India) experienced a devastating flood event during the month of August 2018. While an extreme rainfall event (ERE) was the primary reason for this flood, there was criticism at various levels that the authorities failed to manage the flood effectively through reservoir operations. One of the worst affected basins, Periyar River Basin...

Groundwater level prediction and forecasting using univariate time series models are useful for effective groundwater management under data limiting conditions. The seasonal autoregressive integrated moving average (SARIMA) models are widely used for modeling groundwater level data as the groundwater level signals possess the seasonality pattern. A...

Study region Upper Blue Nile, Ethiopia Study focus The recent availability of high-resolution soil data offers a better representation of spatially varying hydrologic parameters and could help in building accurate models. Despite the release of the AfSIS 250 m resolution soil data in 2015, its benefits in improving streamflow prediction accuracy i...

Land use and land cover maps can support our understanding of coupled human-environment systems and provide important information for environmental modeling and water resource management. Satellite data are a valuable source for land use and land cover mapping. However, cloud-free or weather independent data are necessary to map cloud-prone regions...

Energy loss in a steep open channel due to randomly spaced spherically shaped macroroughness elements such as boulders was investigated using a three-dimensional fluid dynamics solver. First, a relationship for energy loss at large Froude numbers due to a single boulder was derived as a function of flow rate, flow depth, and boulder diameter. Nondi...