s u m m a r y Sensitivity analysis (SA) aims to identify the key parameters that affect model performance and it plays important roles in model parameterization, calibration, optimization, and uncertainty quantification. However, the increasing complexity of hydrological models means that a large number of parameters need to be estimated. To better understand how these complex models work, efficient SA methods should be applied before the application of hydrological modeling. This study provides a comprehensive review of global SA methods in the field of hydrological modeling. The common definitions of SA and the typical categories of SA methods are described. A wide variety of global SA methods have been introduced to provide a more efficient evaluation framework for hydrological modeling. We review, analyze, and categorize research into global SA methods and their applications, with an emphasis on the research accomplished in the hydrological modeling field. The advantages and disadvantages are also discussed and summarized. An application framework and the typical practical steps involved in SA for hydrological modeling are outlined. Further discussions cover several important and often overlooked topics, including the relationship between parameter identification, uncertainty analysis, and optimization in hydrological modeling, how to deal with correlated parameters, and time-varying SA. Finally, some conclusions and guidance recommendations on SA in hydrological modeling are provided, as well as a list of important future research directions that may facilitate more robust analyses when assessing hydrological modeling performance.

This study investigates changes in temporal trends and spatial patterns of precipitation in Beijing over the last six decades. These changes are discussed in the context of rapid urbanization and the growing imbalance between water supply and demand in Beijing. We observed significant decreases in precipitation amounts from 1950 to 2012, with the annual precipitation decreasing by 32% at a decadal rate of 28.5 mm. In particular, precipitation decrease is more pronounced in the summer and warm seasons when water use is at its seasonal peak. We further analyzed hourly precipitation data from 43 rain gauges between 1980 and 2012 to examine the spatiotemporal characteristics of both precipitation amount and intensity across six distinct subregions in Beijing. No significant spatial variations in precipitation changes were identified, but slightly greater amounts of precipitation were noted in the urban areas (plains) than in the surrounding suburbs (mountains), due to the effect of urbanization and topography. Precipitation intensity has increased substantially, especially at the hourly duration, as evidenced by the more frequent occurrence of extreme storms. The observed decreased water availability and the increase in extreme weather events require more integrated water management, particularly given the expectation of a warmer and more variable climate, the continued rapid growth of the Beijing metropolis, and the intensifying conflict between water supply and demand.

This study investigates the spatial and temporal variation of meteorological droughts in the Upper Blue Nile (UBN) basin in Ethiopia using longer historical records (1953 to 2009) of 14 meteorological stations, and 23 other stations with relatively shorter records (1975 to 2009). The influence of using varying record length on drought category was studied by comparing the Standard Precipitation Index (SPI) results from the 14 stations with long record length, by taking out incrementally one year record from 1953 to 1975.These analyses show that the record length from 1953 to 1975 has limited effect on changing the drought category and hence the record length from 1975 to 2009 could be used for drought analysis in the UBN basin. The spatio-temporal analyses of the SPI values show that throughout the UBN basin seasonal or annual meteorological drought episodes

A critical discussion of recent studies that analysed the effects of climate change on the water resources of the River Nile Basin (RNB) is presented. First, current water-related issues on the RNB showing the particular vulnerability to environmental changes of this large territory are described. Second, observed trends in hydrological data (such as temperature, precipitation, river discharge) as described in the recent literature are presented. Third, recent modelling exercises to quantify the effects of climate changes on the RNB are critically analysed. The many sources of uncertainty affecting the entire modelling chain, including climate modelling, spatial and temporal downscaling, hydrological modelling and impact assessment are also discussed. In particular, two contrasting issues are discussed: the need to better recognize and characterize the uncertainty of climate change impacts on the hydrology of the RNB, and the necessity to effectively support decision-makers and propose suitable adaptation strategies and measures. The principles of a code of good practice in climate change impact studies based on the explicit handling of various sources of uncertainty are outlined. Hydrologie et climat futurs dans le bassin du Nil: une revueRésumé Une discussion critique des études récentes qui ont analysé les effets du changement climatique sur les ressources en eau du bassin du Nil (RNB) est présentée. Premièrement, les problèmes actuels liés à l'eau dans le RNB montrant la vulnérabilité particulière de ce vaste territoire aux changements environnementaux sont décrits. Deuxièmement, les tendances observées dans les données hydrologiques (comme la température, les précipitations, le débit des rivières) sont présentées, telles qu'elles sont décrites dans la littérature récente. Troisièmement, les exercices récents de modélisation quantitative des effets des changements climatiques dans le RNB sont analysés de manière critique. Les nombreuses sources d'incertitude qui affectent toute la chaîne de modélisation, incluant la modélisation du climat, la descente d'échelles spatiale et temporelle, la modélisation hydrologique, et l'évaluation des impacts sont également discutées. En particulier, deux questions contrastées sont discutées: la nécessité de mieux identifier et caractériser l'incertitude des impacts du changement climatique sur l'hydrologie du RNB, et la nécessité de soutenir efficacement les décideurs et de proposer des stratégies d'adaptation et des mesures appropriées. Les principes d'un code de bonnes pratiques dans les études d'impact du changement climatique sont décrits, qui reposent sur le traitement explicite des diverses sources d'incertitude.

Abstract. Advances in mesoscale numerical weather predication make it possible to provide rainfall forecasts along with many other data fields at increasingly higher spatial resolutions. It is currently possible to incorporate highresolution NWPs directly into flood forecasting systems in order to obtain an extended lead time. It is recognised, however, that direct application of rainfall outputs from the NWP model can contribute considerable uncertainty to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be magnified by the scaling process. As the ensemble weather forecast has become operationally available, it is of particular interest to the hydrologist to investigate both the potential and implication of ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. In this paper, we employ a distributed hydrological model to analyse the performance of the ensemble flow forecasts based on the ensemble rainfall inputs from a shortrange high-resolution mesoscale weather model. The results show that: (1) The hydrological model driven by QPF can produce forecasts comparable with those from a raingaugedriven one; (2) The ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematic biases are sometimes significant and, as such, extra effort needs to be made to improve the quality of such a system.