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Summary: This paper presents an assessment of the impacts of climate change on a series of indicators of hydrological regimes across the global domain, using a global hydrological model run with climate scenarios constructed using pattern-scaling from 21 CMIP3 (Coupled Model Intercomparison Project Phase 3) climate models. Changes are compared with natural variability, with a significant change being defined as greater than the standard deviation of the hydrological indicator in the absence of climate change. Under an SRES (Special Report on Emissions Scenarios) A1b emissions scenario, substantial proportions of the land surface (excluding Greenland and Antarctica) would experience significant changes in hydrological behaviour by 2050; under one climate model scenario (Hadley Centre HadCM3), average annual runoff increases significantly over 47% of the land surface and decreases over 36%; only 17% therefore sees no significant change. There is considerable variability between regions, depending largely on projected changes in precipitation. Uncertainty in projected river flow regimes is dominated by variation in the spatial patterns of climate change between climate models (hydrological model uncertainty is not included). There is, however, a strong degree of consistency in the overall magnitude and direction of change. More than two-thirds of climate models project a significant increase in average annual runoff across almost a quarter of the land surface, and a significant decrease over 14%, with considerably higher degrees of consistency in some regions. Most climate models project increases in runoff in Canada and high-latitude eastern Europe and Siberia, and decreases in runoff in central Europe, around the Mediterranean, the Mashriq, central America and Brasil. There is some evidence that project change in runoff at the regional scale is not linear with change in global average temperature change. The effects of uncertainty in the rate of future emissions is relatively small. [Copyright &y& Elsevier]

Summary: Despite the increasing use of regional climate model (RCM) simulations in hydrological climate-change impact studies, their application is challenging due to the risk of considerable biases. To deal with these biases, several bias correction methods have been developed recently, ranging from simple scaling to rather sophisticated approaches. This paper provides a review of available bias correction methods and demonstrates how they can be used to correct for deviations in an ensemble of 11 different RCM-simulated temperature and precipitation series. The performance of all methods was assessed in several ways: At first, differently corrected RCM data was compared to observed climate data. The second evaluation was based on the combined influence of corrected RCM-simulated temperature and precipitation on hydrological simulations of monthly mean streamflow as well as spring and autumn flood peaks for five catchments in Sweden under current (1961–1990) climate conditions. Finally, the impact on hydrological simulations based on projected future (2021–2050) climate conditions was compared for the different bias correction methods. Improvement of uncorrected RCM climate variables was achieved with all bias correction approaches. While all methods were able to correct the mean values, there were clear differences in their ability to correct other statistical properties such as standard deviation or percentiles. Simulated streamflow characteristics were sensitive to the quality of driving input data: Simulations driven with bias-corrected RCM variables fitted observed values better than simulations forced with uncorrected RCM climate variables and had more narrow variability bounds. [ABSTRACT FROM AUTHOR]

Summary: This paper introduces an approach to route discharge with a variable river flow velocity based on the Manning–Strickler formula within large scale hydrological models. The approach has been developed for the global scale hydrological model WaterGAP and model results have been analyzed focusing on Europe. The goal was to find a method that is simple enough to derive the required parameters from globally available data while being sophisticated enough to deliver realistic flow velocity estimates for a large variety of environmental conditions. The river bed roughness (Manning’s n) is approximated in a spatially explicit way based on topography, the location of urban population, and river sinuosity. The hydraulic radius is estimated from actual river discharge, and river bed slope is derived by combining a high resolution DEM, a 5arc min drainage direction map, and river sinuosity. The modeled river flow velocity has been validated against data of US gauging stations. The representation of lateral transport has clearly been improved compared to the constant flow velocity applied in older model versions. The effect of incorporating variable flow velocities as compared to a constant flow velocity is largest on flood discharge, which generally increases in large rivers. The impact on monthly discharge hydrographs is marginal only. WaterGAP has been driven by three climate change projections for the 2050s to assess climate change impacts on flow velocity, and on the residence time of water in the European river system. Results indicate a decrease in residence times for Northern Europe and an increase for parts of the Mediterranean. [Copyright &y& Elsevier]

Summary: Water companies in the United Kingdom have considered climate change in their water resources plans for more than a decade through studies funded by UK Water Industry Research (UKWIR). This paper presents an initial assessment of the impact of the UK Climate Projections 2009 (UKCP09) on river flows at a national scale for the 2020s under the A1B scenario and the implications for water resource planning. A daily hydrological modelling framework based on two conceptual model structures and the Generalized Likelihood Uncertainty Estimation (GLUE) methodology has been applied to 70 catchments across the UK. A Latin Hypercube Sampling approach was adopted to handle the probabilistic nature of UKCP09. Results show a decrease in mean annual flow over most of the UK, with negative median values of all monthly changes except in winter over the western and northern mountainous areas. Furthermore the results indicate a high likelihood of a significant decline in summer flows. An analysis of variance shows that the main uncertainty in river flow changes comes from the spread in climate projections. Finally results are found to be consistent with a previous UKWIR assessment based on individual projections from 6 Global Climate Models (GCMs) under the A2 scenario. The reduction in summer low-flows, critical for water resources, appears however more limited with UKCP09. Although most expected changes are within natural variability, the drier conditions overall and the greater spread of results with respect to previous assessments indicates a need for testing the robustness of water resource plans. [Copyright &y& Elsevier]

Summary: Most of the plantation impact studies reported in literature normally use either one of the sensitivity-based approach or a hydrological model with few actually comparing the impact results from these different approaches. This paper investigates the impacts of increase or decrease in plantations and climate variability on streamflow using two approaches: the sensitivity-based approach (including a non-parametric model and six Budyko framework based models) and the hydrological modelling approach (using Xinanjiang and SIMHYD models) for three medium sized catchments in Australia. The results from the nine methods show that both plantation expansion/reduction and climatic differences can have major effects on catchment streamflow. There is a small variability in the reduction or increase in streamflow estimated by the nine methods. The results from this study show that the estimates of plantation impacts from the dynamic hydrological models are similar to those from the commonly used sensitivity-based approaches. The sensitivity-based approaches are only applicable where long term datasets are available and they only provide results at a mean annual time scale. The hydrological models simulate plantation impacted streamflow time series and so they can be used to estimate the relative contributions of land cover changes and climate change/variability at a daily, monthly or annual time-step. The outputs from the hydrological models can also be used to investigate the impacts of plantation expansion or reduction and climate change/variability on different runoff characteristics. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an analysis on the hydrological regimes from several rivers flowing from the western slope of the Andes Cordillera. We compiled a database of 40 unimpaired average monthly streamflow records located in central and southern Chile, spanning the region between latitudes 30°S and 40°S and the period between years 1961 and 2006. River categories encompass snowmelt, mixed and rainfall dominated watersheds. The water year hydrograph center of timing (CT) is used as an indicator of flow regime and as a proxy for streamflow distribution throughout the year. The CT for each river is correlated to local climatic variables such as seasonal temperature and precipitation, and to large-scale circulation indexes. We assess CT trends using the Mann–Kendall test for varying time windows within the study period. Overall results for the 1961–2006 period show a significant (95% confidence level) negative trend (CT date shifting towards earlier in the year) for 23 out of the 40 analyzed series. However, when studying time windows within the entire period there seems to be a break in the trend during the late 1970s, with positive or null changes for the latter half of the study period for most of the stations analyzed. We found that even though the CT is significantly correlated (r >0.5) to temperature indexes in the snowfed watersheds, there has been no significant change in CT timing for most of these watersheds despite documented warming on the region. CT for all types of watersheds present clear correlation to precipitation indexes (r >0.8), and we observed high and significant correlation between CT and ONI, SOI and MEI indexes for all the study region: higher (lower) precipitation amounts during El Niño (La Niña), rather than temperature variations, seem to be the most important factor controlling CT timing during these episodes. In order of importance, the CT showed higher correlation with annual precipitation amounts and timing, MEI, ONI and SOI, mean winter and spring temperature, and finally PDO. The detected trends are consistent only with trends in precipitation, as rivers that showed high correlation to temperature do not show any trend. These conclusions suggest that rivers on the region show a different response to temperature changes when compared to rivers of similar regime in the northern hemisphere, and that precipitation amount and timing are the source of most of the variability in streamflow timing for both snowmelt and rainfall dominated watersheds. Temperature induced variability in streamflow timing should be studied with more precise hydrological models, as the CT has a complex behavior due to multiple climatical dependencies. Studying such behavior using only historical data might be insufficient for drawing more precise conclusions. [Copyright &y& Elsevier]

Summary: The distribution-free Mann–Kendall test is widely used for the assessment of significance of trends in many hydrologic and climatic time series. Previous studies have suggested both exact and approximate formulas for the calculation of the variance of the test statistic when the data are serially correlated. This paper outlines a procedure for the calculation of the exact distribution of the Mann–Kendall trend test statistic for persistent data with an arbitrary correlation structure. The particular cases of the AR(1) (first order autoregressive) model and the Fractional Gaussian Noise (FGN) model are presented for sample sizes between 3 and 9. While it has been previously shown that the Normal distribution gives a reasonable approximation to the exact distribution for large values of sample size n, a more accurate approximation based on the Beta distribution is proposed for moderate values of n. The application of the test to small samples is illustrated by testing the significance of recent trends starting in 1990 in 58 world river flow time series. The results confirm the effect of scaling in small samples and the benefits of using the Beta distribution as an approximation. [Copyright &y& Elsevier]