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The Eastern Indian Gangetic Plains are characterized by a primarily nature-dependent region blessed with an enormous supply of mineral resources. The region is witnessing a rapid transition in its demographic structure because of rapid industrialization. The region provides a classic example of an area which shows a trend reverse to that observed globally, as far as the frequency of extreme precipitation events is concerned. This paper provides a risk characterization of the entire region, based on the empirical behavior shown by data available so far, in addition to predictions based on theory of extreme values. The long-term behavior prediction is made with an aim to provide policy makers ample time and direction to develop suitable disaster prevention measures. The focus is primarily on extremely high rainfall events, their frequency, trend and estimated long-term behavior. The study corroborates the stability assumption behind the Indian monsoon, and also provides an indication of the expected long-term as well as short-term threats. This study provides a unique application of the extreme value theory to help in developing a threat map for a region whose population is known to be highly impacted by any significant deviations from a normal monsoon. [ABSTRACT FROM AUTHOR]

Snow- and glacier melt are important contributors to river discharge in high-elevated areas of the Himalayan region. Thus, it is important that the key processes controlling snow and glacier accumulation and melting, are well represented in hydrological models. In this study, the sensitivity of modelled discharge to different snowmelt parameterizations was evaluated. A distributed hydrological model that operated on a 1 × 1 km2 grid at a daily time resolution was applied to a high-elevated mountainous basin, the Upper Beas basin in Indian Himalaya, including several sub-basins with a varying degree of glacier covered areas. The snowmelt was calculated using (i) a temperature-index method, (ii) an enhanced temperature-index method including a shortwave radiation term, and (iii) an energy balance method. All model configurations showed similar performance at daily, seasonal, and annual timescales and a lower performance for the validation period than for the calibration period; a main reason being the failure to capture the observed negative trend in annual discharge in the validation period. The results suggest that model performance is more sensitive to the precipitation input, i.e. interpolation method than to the choice of snowmelt routine. The paper highlights the challenges related to the lack of high quality data sets in mountainous regions, which are those areas globally with most water resources. [ABSTRACT FROM AUTHOR]

This special edition is a compilation of papers delivered orally at the workshop on regionalization of models for operational purposes in developing countries held during the joint International Association of Hydrological Sciences (IAHS) and International Association of Hydrogeologists (IAH) International Convention in Hyderabad, India during September 2009. The overall theme of the convention was 'Water: A vital resource under stress -- how can science help?' How science can help solve practical water resources management problems and regionalization of models have been recurring themes in hydrological science over the last few decades. If anything, however, the gap between scientific developments and their application in practice has widened, notably in developing countries where financial and institutional constraints continue to be difficult to overcome. While data scarcity remains a major problem, a combination of developments in models, availability of remotely sensed data and an understanding of the treatment of uncertainty implies that we can overcome many of the data deficiency issues. Unfortunately, this does not seem to be the case in practice, and effective and sustainable technology transfer remains elusive in many developing countries. [ABSTRACT FROM AUTHOR]