Changes in rainfall affect drinking water, river and surface runoff, soil moisture, groundwater reserve, electricity generation, agriculture production and ultimately the economy of a country. Trends in rainfall, therefore, are important for examining the impact of climate change on water resources for its planning and management. Here, as analysed from 119 years of rainfall measurements at 16 different rain gauge stations across northeast India, a significant change in the rainfall pattern is evident after the year 1973, with a decreasing trend in rainfall of about 0.42 ± 0.024 mm dec−1. The wettest place of the world has shifted from Cherrapunji (CHE) to Mawsynram (MAW) (separated by 15 km) in recent decades, consistent with long-term rainfall changes in the region. The annual mean accumulated rainfall was about 12 550 mm at MAW and 11 963 mm at CHE for the period 1989–2010, as deduced from the available measurements at MAW. The changes in the Indian Ocean temperature have a profound effect on the rainfall in the region, and the contribution from the Arabian Sea temperature and moisture is remarkable in this respect, as analysed with a multivariate regression procedure for the period 1973–2019. The changes in land cover are another important aspect of this shift in rainfall pattern, as we find a noticeable reduction in vegetation area in northeast India in the past two decades, implying the human influence on recent climate change.

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The estimate of changes in hydrological fluxes from a climate change perspective is inevitable for assessing the sustainability of watersheds and conserving water resources. Here, we quantify and assess the changes in different hydrological flux components for the Manu-Deo River Basin (MDRB) of northeast India using Soil and Water Assessment Tool (SWAT) simulations and multi-temporal data at various resolutions. Sequential Uncertainty Fitting (SUFI-2) optimization is used to calibrate and validate the simulations for the periods 1984–2006 and 2007–2016 and for the four future representative concentration pathway (RCP) scenarios. The model performed reasonably well for calibration and validation for daily data, in accordance with the Nash–Sutcliffe efficiency and coefficient of determination (0.54/0.55 and 0.52/0.72, respectively). The analysis for the period 1985–2013 reveals a decreasing trend in streamflow, which indicates increasing trends of drought there. Furthermore, it shows an increasing trend in evapotranspiration (ET) and decreasing trend for baseflow (BF), suggesting an adverse impact on agricultural production during lean periods. In addition, the RCP 2.6 and 6.0 scenarios for the monsoon season in future time scales are expected to cause a reduction in different flow components, although RCP 8.5 shows increased water availability there. The sub-basin-scale quantification and multi-temporal analysis of water availability under the present and future climate scenarios, as presented here, can assist water managers in formulating a suitable operational policy to implement a better decision-making framework for river and waterbody management. This is particularly important for mountainous regions, where input data are sparse and modelling of hydrological fluxes is challenging.

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