The study of precipitation trends is critically important for a country like India whose food security and economy are dependent on the timely availability of water. In this work, monthly, seasonal and annual trends of rainfall have been studied using monthly data series of 135 years (1871–2005) for 30 sub-divisions (sub-regions) in India. Half of the sub-divisions showed an increasing trend in annual rainfall, but for only three (Haryana, Punjab and Coastal Karnataka), this trend was statistically significant. Similarly, only one sub-division (Chattisgarh) indicated a significant decreasing trend out of the 15 sub-divisions showing decreasing trend in annual rainfall. In India, the monsoon months of June to September account for more than 80% of the annual rainfall. During June and July, the number of sub-divisions showing increasing rainfall is almost equal to those showing decreasing rainfall. In August, the number of sub-divisions showing an increasing trend exceeds those showing a decreasing trend, whereas in September, the situation is the opposite. The majority of sub-divisions showed very little change in rainfall in non-monsoon months. The five main regions of India showed no significant trend in annual, seasonal and monthly rainfall in most of the months. For the whole of India, no significant trend was detected for annual, seasonal, or monthly rainfall. Annual and monsoon rainfall decreased, while pre-monsoon, post-monsoon and winter rainfall increased at the national scale. Rainfall in June, July and September decreased, whereas in August it increased, at the national scale. Citation Kumar, V., Jain, S. K. & Singh, Y. (2010) Analysis of long-term rainfall trends in India. Hydrol. Sci. J. 55(4), 484–496.

The northeast region (NER) of India covers an area of 0.26 million km². This region is one of the highest rainfall‐receiving regions on the planet. Consequently, it has huge water and hydropower potential and analysis of rainfall and temperature trends would be of interest to water and energy planners. Trends in monthly, seasonal, and annual rainfall and temperature on the subdivision and regional scale for the NER were examined in this study. Trend analysis of rainfall data series for 1871–2008 did not show any clear trend for the region as a whole, although there are seasonal trends for some seasons and for some hydro‐meteorological subdivisions. Similar analysis for temperature data showed that all the four temperature variables (maximum, minimum, and mean temperatures and temperature range) had rising trend. Notably for the post‐monsoon season, the Sen's estimator of slope ( °C/year) was 0.019, 0.011, and 0.015 for the maximum, minimum, and mean temperature, respectively. Copyright © 2012 Royal Meteorological Society

Flood forecasting (FF) is one the most challenging and difficult problems in hydrology. However, it is also one of the most important problems in hydrology due to its critical contribution in reducing economic and life losses. In many regions of the world, flood forecasting is one among the few feasible options to manage floods. Reliability of forecasts has increased in the recent years due to the integration of meteorological and hydrological modelling capabilities, improvements in data collection through satellite observations, and advancements in knowledge and algorithms for analysis and communication of uncertainties. The present paper reviews different aspects of flood forecasting, including the models being used, emerging techniques of collecting inputs and displaying results, uncertainties, and warnings. In the end, future directions for research and development are identified.

Quantitative assessments of the degree to which the modeled behavior of a system matches with the observations provide an evaluation of the model’s predictive abilities. In this context, the Nash–Sutcliffe efficiency index is widely used in water resources sector to assess the performance of a hydrologic model. Through a series of results, this technical note demonstrates that this index alone is not adequate in describing the performance of a model. It is shown that relatively poor models can give a high value of the index and vice-versa. Thus, it is advisable to employ the other statistical measures before arriving at a definite conclusion about the performance of a hydrologic model.

This study aims to determine trends in annual and seasonal rainfall and rainy days over different river basins across India. The data used consists of daily gridded rainfall at 1° × 1° resolution for the period 1951–2004. Sen's non-parametric estimator of slope was used to estimate the magnitude of trend whose statistical significance was assessed by the Mann–Kendall test. Among 22 basins studied, 15 showed a decreasing trend in annual rainfall; only one basin showed a significant decreasing trend at 95% confidence level. Of the 6 basins showing an increasing trend, 1 basin showed a significant positive trend. The monsoon rainfall increased over 6 basins, decreased over 16 basins and a decreasing trend for 2 basins was found statistical significant. With the exception of Ganga, Brahmaputra and EFR4, all river basins experienced the same direction of trend in monsoon and annual rainfall. Four river basins experienced increasing (non-significant) trend in annual rainy days; three basins did not show any change in annual rainy days whereas 15 basins have shown a decreasing trend in annual rainy days. The decreasing trend in three basins was statistically significant. Most of the basins have shown the same direction of trend in rainfall and rainy days at the annual and seasonal scale.