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Summary: In this study a rigorous evaluation and comparison of the difference in water balance simulations resulted from using different downscaling techniques, GCMs and hydrological models is performed in upper Hanjiang basin in China. The study consists of the following steps: (1) the NCEP/NCAR reanalysis data for the period 1961–2000 are used to calibrate and validate the statistical downscaling techniques, i.e. SSVM (Smooth Support Vector Machine) and SDSM (Statistical Downscaling Model); (2) the A2 emission scenarios from CGCM3 and HadCM3 for the same period are used as input to the statistical downscaling models; and (3) the downscaled local scale climate scenarios are then used as the input to the Xin-anjiang and HBV hydrological models. The results show that: (1) for the same GCM, the simulated runoffs vary greatly when using rainfall provided by different statistical downscaling techniques as the input to the hydrological models; (2) although most widely used statistics in the literature for evaluation of statistical downscaling methods show SDSM has better performance than SSVM in downscaling rainfall except the Nash–Sutcliffe efficiency (NSC) and root mean square error-observations standard deviation ratio (RSR), the runoff simulation efficiency driven by SDSM rainfall is far lower than by SSVM; and (3) by comparing different statistics in rainfall and runoff simulation, it can be concluded that NSC and RSR between simulated and observed rainfall can be used as key statistics to evaluate the statistical downscaling models’ performance when downscaled precipitation scenarios are used as input for hydrological models. [Copyright &y& Elsevier]

• A framework was provided for analyzing change causes of runoff and sediment load. • Runoff change attribution analysis was incorporated in quantifying sediment change. • Dam construction obviously disturbed the evolution characteristics of sediment load. Under the background of climate variability and anthropogenic stresses, changes of the runoff and sediment processes have drawn increasing concerns during the past decades. Analyzing the evolution characteristics and causes of runoff and sediment load is critical for the sustainable development of water resource and terrestrial ecosystems of river basins. This study presents an integrated approach for analyzing the evolution characteristics of the annual runoff and sediment load, including the trend, periodicity, change point and their correlations in the Wujiang River basin (WRB) –a typical mountainous river system in southwest China, based on the observed data during the period 1970–2016. On this basis, the contributions of climate variability and human activities on runoff change were first distinguished by using a widely applied Budyko-based hydrological sensitivity method, and then the quantified result was further applied in the attribution analysis of river sediment load change. Research results revealed that the change patterns of runoff and sediment processes, such as the trend, periodicity and potential change point, as well as the relationships of precipitation-runoff and runoff-sediment load are quite different in the WRB. Quantitative assessment revealed that climate variability contributes to 71.5%–85.6% changes of mean annual runoff in 1985–1994, 1995–2004 and 2005–2016 with reference to the baseline period of 1970–1984. In contrary, human activities dominate the reduction of sediment load in the river, and the contribution rate ranged in 67.2%–107.5%. Variations of annual runoff in the WRB was the direct result of climate variability, while land use change played a secondary role. The construction of cascade hydropower reservoirs, particularly in the upper and middle reaches of the Wujiang River is fundamentally responsible for the significant decreasing and the weakened periodicity of sediment load as well as the changed runoff-sediment load correlation at Wulong station in recent years. However, this influence was not big enough to modify the regime of annual runoff. [ABSTRACT FROM AUTHOR]

Highlights • The study shows the transferability of regionalization methods with changing climate. • The study compares the uncertainty from climate models and regionalization methods. • The difference between the regionalization methods tends to increase in the future. • In larger precipitation regions, climate models dominate the uncertainty. • Physical similarity method with parameter option produced the most robust result. Abstract Regionalization methods have been extensively discussed as the solution for runoff predictions in ungauged basins (PUB), especially during the PUB decade (2003–2012). At the same time, research topics relevant to climate change appear to be an essential and attractive field for hydrologists in recent decades, because the availability and quality of water resources are strongly affected by climate change. However, it is still unknown whether regionalization methods can be used to predict hydrological impacts of climate change for ungauged catchments or how much uncertainty of future predictions may result from the use of regionalization methods. Therefore, in this study, we investigate the transferability of regionalization methods (i.e. spatial proximity and physical similarity methods, regression method) under changing climate conditions and compare the uncertainty resulting from regionalization methods with that from using climate models. The investigation is based on 108 catchments in Norway, with large variability in climate conditions and geographic characteristics. The study applies a lumped conceptual rainfall-runoff model (WASMOD) with simple structure and six model parameters. Our result shows that (a) the differences in the predictions by the regionalization methods tend to increase in the future, (b) the physical similarity method with parameter option (i.e. the model parameters from the physically-similar donor catchments are first averaged and then used to run the model for the target catchment) shows higher transferability than other methods, (c) the uncertainty contributions from climate models and regionalization methods to future runoff prediction are basin dependent, and (d) the uncertainty of future runoff prediction due to regionalization methods can be higher than that from climate models in low precipitation areas. This study provides insight to the choice of regionalization methods under changing climate conditions and the role of regionalization methods to the uncertainty contributions in future runoff predictions. [ABSTRACT FROM AUTHOR]

Summary This study aims to provide model estimates of changes in hydrological elements, such as EvapoTranspiration (ET) and runoff, in Southern Africa in the near future until 2029. The climate change scenarios are projected by a high-resolution Regional Climate Model (RCM), RegCM4, which is the latest version of this model developed by the Abdus Salam International Centre for Theoretical Physics (ICTP). The hydrological projections are performed by using a large-scale hydrological model (WASMOD-D), which has been tested and customized on this region prior to this study. The results reveal that (1) the projected temperature shows an increasing tendency over Southern Africa in the near future, especially eastward of 25°E, while the precipitation changes are varying between different months and sub-regions; (2) an increase in runoff (and ET) was found in eastern part of Southern Africa, i.e. Southern Mozambique and Malawi, while a decrease was estimated across the driest region in a wide area encompassing Kalahari Desert, Namibia, southwest of South Africa and Angola; (3) the strongest climate change signals are found over humid tropical areas, i.e. north of Angola and Malawi and south of Dem Rep of Congo; and (4) large spatial and temporal variability of climate change signals is found in the near future over Southern Africa. This study presents the main results of work-package 2 (WP2) of the ‘Socioeconomic Consequences of Climate Change in Sub-equatorial Africa (SoCoCA)’ project, which is funded by the Research Council of Norway. [ABSTRACT FROM AUTHOR]

Summary The Budyko-type equations have begun to be widely adopted to separate the contributions of climate change and human activities to the variation of runoff over long-term periods by using the multi-year averages of hydrological variables. In this study, a two-step framework based on four single-parameter Budyko-type equations is proposed to separate the impacts of climate change and human activities on runoff. First, the relationship of the parameter w in each Budyko-type equation with climatic and human factors is built to reveal the time-variation process of w by using an 11-year moving window. Second, the impacts of climate change and human activities on runoff are separated by using both the decomposition method and the sensitivity method. This separating framework is applied to analyze the variation of the runoff during 1960–2009 in the Weihe River. It is found that the parameter w in each Budyko-type equation is significantly related to both factors of climate and human activities. The results from both the decomposition method and the sensitivity method show that climate change is the main driving factor to the decline in runoff of the Weihe River, while human activities are another important factor. In general, climate change affects runoff not only by changing the hydrological inputs (precipitation and potential evaporation) but also by altering the watershed characteristics as represented by the parameter w ; while the impacts of human activities on runoff are exerted mainly through the alteration of the watershed characteristics. [ABSTRACT FROM AUTHOR]

• An improved Budyko complementary relationship (IBCR) is developed. • The IBCR incorporates effects of both climate change and human activities on basin characteristics. • The IBCR is more flexible than the original relation in separating runoff change. Numerous efforts have been made to separate effects of climate change and human activities on long-term runoff change, including a commonly used method based on the Budyko complementary relationship (BCR) to deal with the non-closure problems often encountered in separating the observed runoff change into its contributed components. The BCR was derived by assuming the change of the Budyko parameter reflecting basin characteristics is related to human activities alone. However, some studies show that basin characteristics are related to both climate change and human activities in certain basins, where applying the BCR method could lead to wrong results. In the study, a more flexible form of the BCR, the improved Budyko complementary relationship (IBCR), is developed under the situation that basin characteristics may relate to climate change. A separation method based on the IBCR is also developed. In this IBCR method, the relationship of the basin characteristics parameter to climate and/or human factors is estimated by using a multi-year moving window. To identify the flexibility of the IBCR method relative to the BCR method, both methods were applied to the Weihe basin of China, whose basin characteristics have been found to be affected by both climate change and human activities. Compared with the IBCR method, the BCR method overestimates the climate effect, while underestimates the human effect on the runoff change in the Weihe basin. It is found that whether or not to incorporate the climate effect into the basin characteristics parameter has a significant impact on the runoff change separation results in Weihe basin. Overall, the IBCR method is more reasonable and flexible for separating the long-term runoff change into different components. [ABSTRACT FROM AUTHOR]