The extreme rainfall event during June 2013 in the Western Himalayas caused widespread flash floods, which triggered landslides, a lake-outburst, and debris flow. For the hydrological study of such an unexpected extreme event, it is essential to have reliable and accurate rainfall predictions based on satellite observations. The mountainous state of Uttarakhand is covered by complex topography, and this state has few, unevenly distributed, rain gauge networks. This unique study was conducted to evaluate three satellite based rainfall products (i.e., TMPA-3B42, Global Satellite Mapping of Precipitation (GSMaP), and NOAA CPC Morphing Technique (CMORPH)) against the observed rain gauge-based India Meteorological Department (IMD) gridded dataset for this rainfall episode. The results from this comprehensive study confirmed that the magnitude of precipitation and peak rainfall intensity were underestimated in TMPA-3B42 and CMORPH against gauge-based IMD data, while GSMaP showed dual trends with under- and over-predictions. From the results of the statistical approach on the determination of error statistic metrics (MAE (mean absolute error), NRMSE (normalized root mean square error), PBIAS (percent bias), and NSE (Nash-Sutcliffe efficiency)) of respective satellite products, it was revealed that TMPA-3B42 predictions were more relevant and accurate compared to predictions from the other two satellite products for this major event. The TMPA-3B42-based rainfall was negatively biased by 18%. Despite these caveats, this study concludes that TMPA-3B42 rainfall was useful for monitoring extreme rainfall event in the region, where rain-gauges are sparse.

In this study, an atmospheric dispersion model along with a systematic emission inventory was used to explore the possible control strategy to reduce ambient levels of nitrogen oxides (NO_x) in Kanpur city, India. A GIS based emission inventory of NO_x was developed for the base, 5th and 10th years. It was observed that the 5th and 10th years will experience increased emissions by factors of 1.7 and 2.5 of the base year if no control policy is implemented. Seventeen control options (i.e. introduction of Euro 6 to vehicles, banning of 15-year old private vehicles etc.) were considered for evaluation through the dispersion modelling. A control scenario comprising the following control options (1) implementation of Euro 6 for vehicles, (2) compressed natural gas (CNG) for commercial and public vehicles, etc. was found to be most effective in reducing the ambient NO_x levels and attaining a 24-hour average air quality standard.