High resolution climate change scenarios: implications for British runoff

Nationwide changes in spatially well‐resolved patterns of British runoff were investigated under two climate change scenarios derived from general circulation model (GCM) output. A physical process‐based hydrological model (HYSIM) was used to simulate effective runoff across a 10 km×10 km British grid under baseline and future climate conditions. A gridded baseline climatology for precipitation and the Penman variables was used to validate HYSIM across Britain using grid cell‐specific parameters derived from land use and soil type. The climate change scenarios were constructed from the Hadley Centre's high resolution equilibrium GCM (UKHI) for 2050 and transient GCM (UKTR) for 2065. Future effective runoff was simulated under both scenarios by applying changes in precipitation and the Penman variables to the baseline climatology. Annual effective runoff is shown to increase throughout most of Britain under the UKHI scenario for 2050, whilst it decreases over much of England and Wales under the UKTR scenario for 2065. Both scenarios show an increasing gradient in runoff between a wetter northern Britain and a drier south‐eastern Britain. This gradient is more pronounced under the UKTR scenario. Changes in effective runoff for winter and summer show an increase in seasonality under both scenarios. Winter runoff is shown to increase most in northern Britain under both scenarios, whilst summer runoff is shown to experience major reductions over much of England and Wales under the UKTR scenario. If these simulations are realized, Britain may expect an accentuated north to south‐east imbalance in available water resources. If this is combined with a temporal imbalance suggested by the increased seasonality, there could be problems for the future management of British water resources. Copyright © 1999 John Wiley & Sons, Ltd.     

气候变化对长江流域汉江和赣江径流的影响

近几年来,国家气候中心己经建立了中国主要四大流域气候对水资源影响评估的模式框架.本文拟进一步证明其中之一的两参数分布式月水量平衡水文模式对长江之上汉江和赣江两子流域径流的模拟能力,结果表明该水文模式对目前气候条件下径流模拟效果较好,运行稳定,可用于实时业务运行.在此基础上,利用ECHAM4和HadCM2两GCM(General Circulation Model)未来气候情景模拟结果及目前实测气候情况,对汉江和赣江两子流域的径流对未来气候变化的敏感性进行评估.经检验,两GCM对未来气候,特别是降水情景模拟存在一定差异,因此,造成径流对气候变化的响应不同,这充分反映了全球模式模拟结果不确定性在气候变化影响研究中的重要性.     

Future climate and runoff projections across New South Wales,Australia: results and practical applications

This paper describes the rainfall–runoff modelling for New South Wales (NSW) and Australian Capital Territory (ACT) under historical climate and the likely changes to runoff around the year 2030 for the Intergovernmental Panel on Climate Change (IPCC) SRES A1B global warming scenario. Results show that the mean annual historical rainfall and runoff, averaged over the entire region, are 516 and 55 mm, respectively. There is considerable uncertainty in the global climate modelling (GCM) of rainfall response in the region to global warming. The majority of GCMs show a decrease in the mean annual rainfall and the median estimate indicates that future mean annual runoff in the region in ～2030 relative to ～1990 will be lower by 0–20% in the southern parts, no change to a slight reduction in the eastern parts and higher by 0–20% in the northwest corner. Averaged across the entire region, the median estimate is a 5% decrease in the mean annual runoff and the extreme estimates range from a 14% decrease to a 10% increase in mean annual runoff. This is the first comprehensive study on the hydrological impacts of climate change done in NSW that covers the entire state. Outputs from this study are being used to underpin the hydrology for a number of major climate change impact studies that are presently underway across NSW. The results and output datasets from this study will be available through a web interface and they can be used by all state government agencies and industries in NSW to plan for and adapt to the impacts of climate change. Copyright © 2010 John Wiley & Sons, Ltd.     

Macroscale hydrological modelling approach for study of large scale hydrologic impacts under climate change in Indian river basins

In climate‐change studies, a macroscale hydrologic model (MHM) operating over large scales can be an important tool in developing consistent hydrological variability estimates over large basins. MHMs, which can operate at coarse grid resolutions of about 1° latitude by longitude, have been used previously to study climate change impacts on the hydrology of continental scale or global river basins. They can provide a connection between global atmospheric models and water resource systems on large spatial scales and long timescales. In this study, the variable infiltration capacity (VIC) MHM is used to study large scale hydrologic impacts of climate change for Indian river basins. Large‐scale changes in runoff, evapotranspiration and soil moisture for India, as well as station‐scale changes in discharges for three major river basins with distinct climatic and geographic characteristics are examined in this study. Climate model projections for meteorological variables (precipitation, temperature and wind speed) from three general circulation models (GCMs) and three emissions scenarios are used to drive the VIC MHM. GCM projections are first interpolated to a 1° by 1° hydrologic model grid and then bias‐corrected using a quantile–quantile mapping. The VIC model is able to reproduce observed statistics for discharges in the Ganga, Narmada and Krishna basins reasonably well, even at the coarse grid resolution employed using a calibration period for years 1965–1970 and testing period from 1971–1973/1974. An increasing trend is projected for summer monsoon surface runoff, evapotranspiration and soil moisture in most central Indian river basins, whereas a decrease in runoff and soil moisture is projected for some regions in southern India, with important differences arising from GCM and scenario variability. Discharge statistics show increases in mid‐flow and low flow at Farakka station on Ganga River, increased high flows at Jamtara station upstream of Narmada, and increased high, mid‐flow and low flow for Vijayawada station on Krishna River in the future. Copyright © 2013 John Wiley & Sons, Ltd.     

Estimation of catchment yield and associated uncertainties due to climate change in a mountainous catchment in Australia

This paper examines the impacts of climate change on future water yield with associated uncertainties in a mountainous catchment in Australia using a multi‐model approach based on four global climate models (GCMs), 200 realisations (50 realisations from each GCM) of downscaled rainfalls, 2 hydrological models and 6 sets of model parameters. The ensemble projections by the GCMs showed that the mean annual rainfall is likely to reduce in the future decades by 2–5% in comparison with the current climate (1987–2012). The results of ensemble runoff projections indicated that the mean annual runoff would reduce in future decades by 35%. However, considerable uncertainty in the runoff estimates was found as the ensemble results project changes of the 5^th (dry scenario) and 95^th (wet scenario) percentiles by ?73% to +27%, ?73% to +12%, ?77% to +21% and ?80% to +24% in the decades of 2021–2030, 2031–2040, 2061–2070 and 2071–2080, respectively. Results of uncertainty estimation demonstrated that the choice of GCMs dominates overall uncertainty. Realisation uncertainty (arising from repetitive simulations for a given time step during downscaling of the GCM data to catchment scale) of the downscaled rainfall data was also found to be remarkably high. Uncertainty linked to the choice of hydrological models was found to be quite small in comparison with the GCM and realisation uncertainty. The hydrological model parameter uncertainty was found to be lowest among the sources of uncertainties considered in this study. Copyright © 2015 John Wiley & Sons, Ltd.     

Review of field observations of runoff generation in the tropics

Over the last thirty years, French hydrologists have observed flow characteristics at the outlets of small tropical watersheds, characteristics which vary between arid zones, humid zones and equatorial rainforest zones. The main physical phenomena related to the various types of runoff generation have been observed and analysed. The generation of runoff and subsurface runoff following tropical rainstorms depends on soil surface formations, texture and structure as well as vegetation cover, geological substrata, weathered material and climate.

Analysis is also made of experimental rainfall-runoff relationships, the shape of flood hydrographs and the conditions necessary for the occurrence of steady base flow. Scale effects between experimental plot and watershed have been studied to identify any effect this may have upon runoff generation and flow. Tables detail watershed characteristics and relationships between these and rainfall and runoff.     

A nonstationary runoff frequency analysis for future climate change and its uncertainties

With the intensification of climate change, its impact on runoff variations cannot be ignored. The main purpose of this study is to analyse the nonstationarity of runoff frequency adjusted for future climate change in the Luanhe River basin, China, and quantify the different sources of uncertainties in nonstationary runoff frequency analysis. The advantage of our method is the combination of generalized additive models in location, scale, and shape (GAMLSS) and downscaling models. The nonstationary GAMLSS models were established for the nonstationary frequency analysis of runoff (1961–2010) by using the observed precipitation as a covariate, which is closely related to runoff and contributes significantly to its nonstationarity. To consider the nonstationary effects of future climate change on future runoff variations, the downscaled precipitation series in the future (2011–2080) from the general circulation models (GCMs) were substituted into the selected nonstationary model to calculate the statistical parameters and runoff frequency in the future. A variance decomposition method was applied to quantify the impacts of different sources of uncertainty on the nonstationary runoff frequency analysis. The results show that the impacts of uncertainty in the GCMs, scenarios, and statistical parameters of the GAMLSS model increase with increasing runoff magnitude. In addition, GCMs and GAMLSS model parameters have the main impacts on runoff uncertainty, accounting for 14% and 83% of the total uncertainty sources, respectively. Conversely, the interactions and scenarios make limited contributions, accounting for 2% and 1%, respectively. Further analysis shows that the sources of uncertainty in the statistical parameters of the nonstationary model mainly result from the fluctuations in the precipitation sequence. This result indicates the necessity of considering the precipitation sequence as a covariate for runoff frequency analysis in the future.     

A new surface runoff parameterization with subgrid-scale soil heterogeneity for land surface models

Soil heterogeneity plays an important role in determining surface runoff generation mechanisms. At the spatial scales represented by land surface models used in regional climate model and/or global general circulation models (GCMs) for numerical weather prediction and climate studies, both infiltration excess (Horton) and saturation excess (Dunne) runoff may be present within a studied area or a model grid cell. Proper modeling of surface runoff is essential to a reasonable representation of feedbacks in the land–atmosphere system. In this paper, a new surface runoff parameterization that dynamically represents both Horton and Dunne runoff generation mechanisms within a model grid cell is presented. The new parameterization takes into account of effects of soil heterogeneity on Horton and Dunne runoff. A series of numerical experiments are conducted to study the effects of soil heterogeneity on Horton and Dunne runoff and on soil moisture storage under different soil and precipitation conditions. The new parameterization is implemented into the current version of the hydrologically based variable infiltration capacity (VIC) land surface model and tested over three watersheds in Pennsylvania. Results show that the new parameterization plays a very important role in partitioning the water budget between surface runoff and soil moisture in the atmosphere–land coupling system. Significant underestimation of the surface runoff and overestimation of subsurface runoff and soil moisture could be resulted if the Horton runoff mechanism were not taken into account. Also, the results show that the Horton runoff mechanism should be considered within the context of subgrid-scale spatial variability of soil properties and precipitation. An assumption of time-invariant spatial distribution of potential infiltration rate may result in large errors in surface runoff and soil moisture. In addition, the total surface runoff from the new parameterization is less sensitive to the choice of the soil moisture shape parameter of the distribution.     

Storm‐event rainfall–runoff modelling approach for ungauged sites in Taiwan

This work develops a top‐down modelling approach for storm‐event rainfall–runoff model calibration at unmeasured sites in Taiwan. Twenty‐six storm events occurring in seven sub‐catchments in the Kao‐Ping River provided the analytical data set. Regional formulas for three important features of a streamflow hydrograph, i.e. time to peak, peak flow, and total runoff volume, were developed via the characteristics of storm event and catchment using multivariate regression analysis. Validation of the regional formulas demonstrates that they reasonably predict the three features of a streamflow hydrograph at ungauged sites. All of the sub‐catchments in the study area were then adopted as ungauged areas, and the three streamflow hydrograph features were calculated by the regional formulas and substituted into the fuzzy multi‐objective function for rainfall–runoff model calibration. Calibration results show that the proposed approach can effectively simulate the streamflow hydrographs at the ungauged sites. The simulated hydrographs more closely resemble observed hydrographs than hydrographs synthesized using the Soil Conservation Service (SCS) dimensionless unit hydrograph method, a conventional method for hydrograph estimation at ungauged sites in Taiwan. Copyright © 2008 John Wiley & Sons, Ltd.     

Propagation of uncertainties in interpolated rainfields to runoff errors

Conditional daily rainfields were generated using collocated raingauge radar data by a kriging interpolation method, and disaggregated into hourly rainfields using variants of the method of fragments. A geographic information system (GIS)-based distributed rainfall–runoff model was used to convert the hourly rainfields into hydrographs. Using the complete radar rainfall as input, the rainfall–runoff model was calibrated based on storm events taken from nested catchments. Performance statistics were estimated by comparing the observed and the complete radar rainfall simulated hydrographs. Degradation in the hydrograph performance statistics by the simulated hourly rainfields was used to identify runoff error propagation. Uncertainty in daily rainfall amounts alone caused higher errors in runoff (depth, peak, and time to peak) than those caused by uncertainties in the hourly proportions alone. However, the degradation, which reduced with runoff depth, caused by the combined uncertainties was not significantly different from that caused by the uncertainty of amounts alone.     

Improving WRF-Hydro runoff simulations of heavy floods through the sea surface temperature fields with higher spatio-temporal resolution

This study investigates the impact of the spatio-temporal accuracy of four different sea surface temperature (SST) datasets on the accuracy of the Weather Research and Forecasting (WRF)-Hydro system to simulate hydrological response during two catastrophic flood events over the Eastern Black Sea (EBS) and the Mediterranean (MED) regions of Turkey. Three time-variant and high spatial resolution external SST products (GHRSST, Medspiration and NCEP-SST) and one coarse-resolution and time-invariant SST product (ERA5- and GFS-SST for EBS and MED regions, respectively) already embedded in the initial and the boundary conditions datasets of WRF model are used in deriving near-surface atmospheric variables through WRF. After the proper event-based calibration is performed to the WRF-Hydro system using hourly and daily streamflow data in both regions, uncoupled model simulations for independent SST events are conducted to assess the impact of SST-triggered precipitation on simulated extreme runoff. Some localized and temporal differences in the occurrence of the flood events with respect to observations depending on the SST representation are noticeable. SST products represented with higher cross-correlations (GHRSST and Medspiration) revealed significant improvement in flood hydrographs for both regions. The GHRSST dataset shows a substantial improvement in NSE (~70%), RMSE reduction up to 20%, and an increase in correlation from 0.3 to 0.8 with respect to the invariable SST (ERA5) in simulated runoffs over the EBS region. The use of both GHRSST and Medspiration SST data characterized with high spatio-temporal correlation resulted in runoff simulations exactly matching the observed runoff peak of 300 m³/s by reducing the overestimation seen in invariable SST (GFS) in the MED region. Improved precipitation simulation skills of the WRF model with the detailed SST representation show that the hydrographs of GHRSST and Medspiration simulations show better performance compared to the simulated hydrographs by observed precipitation.     

Assessment of GCM simulations of annual and seasonal rainfall and daily rainfall distribution across south‐east Australia

Global warming can potentially lead to changes in future rainfall and runoff and can significantly impact the regional hydrology and future availability of water resources. All the large‐scale climate impact studies use the future climate projections from global climate models (GCMs) to estimate the impact on future water availability. This paper presents results from a detailed assessment to investigate the capability of 15 GCMs to reproduce the observed historical annual and seasonal mean rainfalls, the observed annual rainfall series and the observed daily rainfall distribution across south‐east Australia. The assessment shows that the GCMs can generally reproduce the spatial patterns of mean seasonal and annual rainfalls. However, there can be considerable differences between the mean rainfalls simulated by the GCMs and the observed rainfall. The results clearly show that none of the GCMs can simulate the actual annual rainfall time series or the trend in the annual rainfall. The GCMs can also generally reproduce the observed daily (ranked) rainfall distribution at the GCM scale. The GCMs are ranked against their abilities to reproduce the observed historical mean annual rainfall and daily rainfall distribution, and, based on the combined score, the better GCMs include MPI‐ECHAM5, MIUB, CCCMA_T47, INMCM, CSIRO‐MK3·0, CNRM, CCCMA_T63 and GFDL 2·0 and those with poorer performances are MRI, IPSL, GISS‐AOM, MIROC‐M, NCAR‐PCM1, IAP and NCAR‐CCSM. However, the reduction in the combined score as we move from the best‐ to the worst‐performing GCMs is gradual, and there is no evident cut‐off point or threshold to remove GCMs from climate impact studies. There is some agreement between the results here and many similar studies comparing the performance of GCMs in Australia, but the results are not always consistent and do significantly disagree with several of the studies. Copyright © 2010 John Wiley & Sons, Ltd.     

Regional regression models for hydro‐climate change impact assessment

Hydro‐climatic impacts in water resources systems are typically assessed by forcing a hydrologic model with outputs from general circulation models (GCMs) or regional climate models. The challenges of this approach include maintaining a consistent energy budget between climate and hydrologic models and also properly calibrating and verifying the hydrologic models. Subjective choices of loss, flow routing, snowmelt and evapotranspiration computation methods also increase watershed modelling uncertainty and thus complicate impact assessment. An alternative approach, particularly appealing for ungauged basins or locations where record lengths are short, is to predict selected streamflow quantiles directly from meteorological variable output from climate models using regional regression models that also include physical basin characteristics. In this study, regional regression models are developed for the western Great Lakes states using ordinary least squares and weighted least squares techniques applied to selected Great Lakes watersheds. Model inputs include readily available downscaled GCM outputs from the Coupled Model Intercomparison Project Phase 3. The model results provide insights to potential model weaknesses, including comparatively low runoff predictions from continuous simulation models that estimate potential evapotranspiration using temperature proxy information and comparatively high runoff projections from regression models that do not include temperature as an explanatory variable. Copyright © 2014 John Wiley & Sons, Ltd.     

Assessing the effect of climate change on mean annual runoff in the Songhua River basin,China

Influences of climatic change on the components of global hydrological cycle, including runoff and evapotranspiration are significant in the mid‐ and high‐latitude basins. In this paper, the effect of climatic change on annual runoff is evaluated in a large basin—Songhua River basin which is located in the northeast of China. A method based on Budyko‐type equation is applied to separate the contributions of climatic factors to changes in annual runoff from 1960 to 2008, which are computed by multiplying their partial derivatives by the slopes of trends in climate factors. Furthermore, annual runoff changes are predicted under IPCC SRES A2 and B2 scenarios with projections from five GCMs. The results showed that contribution of annual precipitation to annual runoff change was more significant than that of annual potential evapotranspiration in the Songhua River basin; and the factors contributing to annual potential evapotranspiration change were ranked as temperature, wind speed, vapour pressure, and sunshine duration. In the 2020s, 2050s, and 2080s, changes in annual runoff estimated with the GCM projections exhibited noticeable difference and ranged from ? 8·4 to ? 16·8 mm a^?1 (?5·77 to ? 11·53% of mean annual runoff). Copyright © 2011 John Wiley & Sons, Ltd.     

Modeling the effects of climate change projections on streamflow in the Nooksack River basin,Northwest Washington

The Nooksack River has its headwaters in the North Cascade Mountains and drains an approximately 2000 km² watershed in northwestern Washington State. The timing and magnitude of streamflow in a snowpack‐dominated drainage basin such as the Nooksack River basin are strongly influenced by temperature and precipitation. Projections of future climate made by general circulation models (GCMs) indicate increases in temperature and variable changes in precipitation for the Nooksack River basin. Understanding the response of the river to climate change is crucial for regional water resources planning because municipalities, tribes, and industry depend on the river for water use and for fish habitat. We combine three different climate scenarios downscaled from GCMs and the Distributed‐Hydrology‐Soil‐Vegetation Model to simulate future changes to timing and magnitude of streamflow in the higher elevations of the Nooksack River. Simulations of future streamflow and snowpack in the basin project a range of magnitudes, which reflects the variable meteorological changes indicated by the three GCM scenarios and the local natural variability employed in the modeling. Simulation results project increased winter flows, decreased summer flows, decreased snowpack, and a shift in timing of the spring melt peak and maximum snow water equivalent. These results are consistent with previous regional studies, but the magnitude of increased winter flows and total annual runoff is higher. Increases in temperature dominate snowpack declines and changes to spring and summer streamflow, whereas a combination of increases in temperature and precipitation control increased winter streamflow. Copyright © 2013 John Wiley & Sons, Ltd.     

The effect of rainstorm movement on urban drainage network runoff hydrographs

This article explores the relations between network properties and the effect from moving rainstorms in terms of the peak response and time to centroid of hydrographs. A simple conceptual rectangular catchment is introduced with different configurations of drainage network simulated by the Gibbs stochastic model. The efficiency of the urban pipe networks varies widely compared with natural river networks; hence, the Gibbs model can be an appropriate approach to represent the network properties in urban drainage system. Simple cases of rainstorms moving with upstream and downstream directions and different speeds are considered to investigate the effect of rainstorm movement on urban drainage network runoff hydrographs. The results indicate that the effect of the direction and speed of the rainstorm movement varies significantly depending on the network properties. The relationship between storm speed and direction and the change in the peak runoff is dependent on the network configuration and network efficiency. In contrast to previous studies, this study indicates that the speed and direction of the rainfall movement that produces the maximum peak discharge changes depending on the network configuration. Copyright © 2011 John Wiley & Sons, Ltd.     

Comparing three land surface schemes used in general circulation models

Land-surface processes are part of the lower boundary conditions for the atmosphere. The schemes used in general circulation models (GCM) to represent this forcing are relatively simple but they play an important role in the simulation of climate. This paper compares three different land-surface schemes used in GCM. All were run with the same imposed atmospheric conditions in order to analyse the differences in the hydrological cycle. The intercomparison showed that simulated evaporation, runoff and soil moisture were different in all three cases. In order to get a better understanding of the mechanisms at work in the models, features from two of the schemes were included in the other scheme. With these modifications we were able to reduce the wide range between model results. We showed that the surface resistance and field capacity were essential parameters in determining the annual cycle of evaporation and that a representation of subgrid-scale variability of soil moisture had an important impact on runoff.     

Climatic control on river discharge simulations,Zackenberg River drainage basin,northeast Greenland

A spatially distributed, physically based, hydrologic modeling system (MIKE SHE) was applied to quantify intra‐ and inter‐annual discharge from the snow and glacierized Zackenberg River drainage basin (512 km²; 20% glacier cover) in northeast Greenland. Evolution of snow accumulation, distribution by wind‐blown snow, blowing‐snow sublimation, and snow and ice surface melt were simulated by a spatially distributed, physically based, snow‐evolution modelling system (SnowModel) and used as input to MIKE SHE. Discharge simulations were performed for three periods 1997–2001 (calibration period), 2001–2005 (validation period), and 2071–2100 (scenario period). The combination of SnowModel and MIKE SHE shows promising results; the timing and magnitude of simulated discharge were generally in accordance with observations (R² = 0·58); however, discrepancies between simulated and observed discharge hydrographs do occur (maximum daily difference up to 44·6 m³ s^?1 and up to 9% difference between observed and simulated cumulative discharge). The model does not perform well when a sudden outburst of glacial dammed water occurs, like the 2005 extreme flood event. The modelling study showed that soil processes related to yearly change in active layer depth and glacial processes (such as changes in yearly glacier area, seasonal changes in the internal glacier drainage system, and the sudden release of glacial bulk water storage) need to be determined, for example, from field studies and incorporated in the models before basin runoff can be quantified more precisely. The SnowModel and MIKE SHE model only include first‐order effects of climate change. For the period 2071–2100, future IPCC A2 and B2 climate scenarios based on the HIRHAM regional climate model and HadCM3 atmosphere–ocean general circulation model simulations indicated a mean annual Zackenberg runoff about 1·5 orders of magnitude greater (around 650 mmWE year^?1) than from today 1997–2005 (around 430 mmWE year^?1), mainly based on changes in negative glacier net mass balance. Copyright © 2007 John Wiley & Sons, Ltd.     

Assessment on the function of reservoirs for flood control during typhoon seasons based on a distributed hydrological model

A grid‐based distributed hydrological model, PDTank model, is used to simulate hydrological processes in the upper Tone River catchment. The Tone River catchment often suffers from heavy rainfall events during the typhoon seasons. The reservoirs located in the catchment play an important role in flood regulation. Through the coupling of the PDTank model and a reservoir module that combines the storage function and operation function, the PDTank model is used for flood forecasting in this study. By comparing the hydrographs simulated using gauging and radar rainfall data, it is found that the spatial variability of rainfall is an important factor for flood simulation and the accuracy of the hydrographs simulated using radar rainfall data is slightly improved. The simulation of the typhoon flood event numbered No. 9 shows that the reservoirs in the catchment attenuate the peak flood discharge by 423·3 m³/s and validates the potential applicability of the distributed hydrological model on the assessment of function of reservoirs for flood control during typhoon seasons. Copyright © 2011 John Wiley & Sons, Ltd.     

Uncertainty in hydrologic modelling for estimating hydrologic response due to climate change (Santiam River,Oregon)

This paper explores the predicted hydrologic responses associated with the compounded error of cascading global circulation model (GCM) uncertainty through hydrologic model uncertainty due to climate change. A coupled groundwater and surface water flow model (GSFLOW) was used within the differential evolution adaptive metropolis (DREAM) uncertainty approach and combined with eight GCMs to investigate uncertainties in hydrologic predictions for three subbasins of varying hydrogeology within the Santiam River basin in Oregon, USA. Predictions of future hydrology in the Santiam River include increases in runoff in the fall and winter months and decreases in runoff for the spring and summer months. One‐year peak flows were predicted to increase whereas 100‐year peak flows were predicted to slightly decrease. The predicted 10‐year 7‐day low flow decreased in two subbasins with little groundwater influences but increased in another subbasin with substantial groundwater influences. Uncertainty in GCMs represented the majority of uncertainty in the analysis, accounting for an average deviation from the median of 66%. The uncertainty associated with use of GSFLOW produced only an 8% increase in the overall uncertainty of predicted responses compared to GCM uncertainty. This analysis demonstrates the value and limitations of cascading uncertainty from GCM use through uncertainty in the hydrologic model, offers insight into the interpretation and use of uncertainty estimates in water resources analysis, and illustrates the need for a fully nonstationary approach with respect to calibrating hydrologic models and transferring parameters across basins and time for climate change analyses. Copyright © 2012 John Wiley & Sons, Ltd.