The hydrological budget of the three major Asian rivers, namely the Indus, the Ganga and the Brahmaputra, is controlled by the Indian monsoon and Westerlies but their contribution in these basins are highly variable. Widely varying average annual precipitation has been reported within these basins. A poor network of in situ rain gauges, particularly in mountainous regions, inaccessible terrain, high variations in altitude and the significantly large size of basins forces adaption of satellite-based average annual precipitation. We investigate precipitation patterns for these three basins by using satellite-based Tropical Rainfall Measuring Mission (TRMM-3B42) data and compare and validate it with Asian Precipitation Highly Resolved Data Integration Towards Evaluation (APHRODITE) and India Meteorological Department (IMD) interpolated gridded precipitation data. The entire basins as well as basinal areas within the geographic limits of India have been considered. Our study shows that the precipitation broadly follows an east–west and north–south gradient control. The easternmost Brahmaputra Basin has the highest amount of precipitation followed by the Ganga Basin, and the westernmost Indus Basin has the least precipitation; precipitation is highest on the higher elevations than compared to lower elevations of the basins. A seasonal- and elevation-based approach is adapted to estimate snow precipitation and is discussed in terms of overall precipitation.

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Purpose. Microblogging sites are being used by people across the globe to share their opinions and to express sentiments for everything in real time. Through social listening, companies analyse the sentiments to assess the way forward, and the researchers use it to analyse the trend or an event and give forward-looking recommendations. The objective of the paper is to analyse the sentiments of people relating to Paytm IPO which can be used to predict the way forward. Design/methodology/approach. The study attempts sentiment analysis. For this purpose, QSR NVIVO 12, the qualitative analysis tool was used to retrieve the tweets from the Twitter website. NCapture was installed for this purpose. Post data cleaning, stemming, query augmentation and classification, the Twitter data was analysed. Findings. The sentiments around the IPO of Paytm have been negative and sarcastic. The extremely negative tweets were near twice the number of extremely positive tweets. Practical implication. The study can help an investor in evaluating the investment that they might be planning in the given company. For the company, whose IPO is being considered, an analysis of the sentiments around the IPO can help in taking corrective measures, if the sentiment is negative, towards reputation building. Originality/value. The study is an original contribution to the extant literature in the field of sentiment analysis.

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