Sensitivity of hydrological variables to climate change in the Haihe River basin,China

Using the defined sensitivity index, the sensitivity of streamflow, evapotranspiration and soil moisture to climate change was investigated in four catchments in the Haihe River basin. Climate change contained three parts: annual precipitation and temperature change and the change of the percentage of precipitation in the flood season (P_f). With satisfying monthly streamflow simulation using the variable infiltration capacity model, the sensitivity was estimated by the change of simulated hydrological variables with hypothetical climatic scenarios and observed climatic data. The results indicated that (i) the sensitivity of streamflow would increase as precipitation or P_f increased but would decrease as temperature increased; (ii) the sensitivity of evapotranspiration and soil moisture would decrease as precipitation or temperature increased, but it to P_f varied in different catchments; and (iii) hydrological variables were more sensitive to precipitation, followed by P_f, and then temperature. The nonlinear response of streamflow, evapotranspiration and soil moisture to climate change could provide a reference for water resources planning and management under future climate change scenarios in the Haihe River basin. Copyright © 2011 John Wiley & Sons, Ltd.     

Sequential assimilation of soil moisture and streamflow data in a conceptual rainfall–runoff model

Soil moisture is a key hydrological variable in flood forecasting: it largely influences the partition of rain between runoff and infiltration and thus controls the flow at the outlet of a catchment. The methodology developed in this paper aims at improving the commonly used hydrological tools in an operational forecasting context by introducing soil moisture data into streamflow modelling. A sequential assimilation procedure, based on an extended Kalman filter, is developed and coupled with a lumped conceptual rainfall–runoff model. It updates the internal states of the model (soil and routing reservoirs) by assimilating daily soil moisture and streamflow data in order to better fit these external observations. We present in this paper the results obtained on the Serein, a Seine sub-catchment (France), during a period of about 2 years and using Time Domain Reflectivity probe soil moisture measurements from 0–10 to 0–100 cm and stream gauged data. Streamflow prediction is improved by assimilation of both soil moisture and streamflow individually and by coupled assimilation. Assimilation of soil moisture data is particularly effective during flood events while assimilation of streamflow data is more effective for low flows. Combined assimilation is therefore more adequate on the entire forecasting period. Finally, we discuss the adequacy of this methodology coupled with Remote Sensing data.     

Grid parameterization of a conceptual distributed hydrological model through integration of a sub-grid topographic index: necessity and practicability

Abstract

Grid-based distributed models have become popular for describing spatial hydrological processes. However, the influence of non-homogeneity within a grid on streamflow simulation was not adequately addressed in the literature. In this study, we investigated how the statistical characteristics of soil moisture storage within a grid impacts on streamflow simulations. The spatial variation of the topographic index, TI, within a grid was used to determine parameter B of the statistical curve of soil moisture storage in the Xinanjiang model. For comparison of influences of the non-homogeneity within a grid on streamflow simulation, two parameterization schemes of soil moisture storage capacity were developed: a grid-parameterization scheme for a distributed model and a catchment-averaged scheme for a semi-distributed model. The practicability and usefulness of the grid-parameterization method were evaluated through model comparisons. The two models were applied in Jiangwan experimental catchment Zhejiang Province, China. Streamflow discharge data at the catchment outlet from 1971 to 1986 at different temporal resolutions, e.g. 15 min and daily time step, were used for model calibration and validation. Statistical results for different grid scales demonstrated that the mean and variation of TI and B decline significantly as the grid scale increases. The simulated streamflow discharges of the two models were similar and the semi-distributed model outperformed the distributed model slightly when the streamflow at the outlet of the catchment was used as the only basis for comparison. In addition, a relatively larger bias in the predicted discharges between these two models was observed along with an abrupt increase of soil moisture saturation ratio. A further analysis of the simulated soil moisture content distribution revealed that the distributed model can provide a reasonable representation of the variable source area concept, which was justified to some extent by the field experiment data.

Editor D. Koutsoyiannis

Citation Liu, J.T., Chen, X., Wu, J.C., Zhang, X.N., Feng, D.Z. and Xu, C.-Y., 2012. Grid parameterization of a conceptual, distributed hydrological model through integration of a sub-grid topographic index: necessity and practicability. Hydrological Sciences Journal, 57 (2), 282–297.     

A multi-objective calibration approach using in-situ soil moisture data for improved hydrological simulation of the Prairies

ABSTRACT

Traditionally, hydrological models are only calibrated to reproduce streamflow regime without considering other hydrological state variables, such as soil moisture and evapotranspiration. Limited studies have been performed on constraining the model parameters, despite the fact that the presence of a large number of parameters may provide large degree of freedom, resulting in equifinality and poor model performance. In this study, a multi-objective optimization approach is adopted, and both streamflow and soil moisture data are calibrated simultaneously for an experimental study basin in the Saskatchewan Prairies in western Canada. The results of this study show that the multi-objective calibration improves model fidelity compared to the single objective calibration. Moreover, the study demonstrates that single objective calibration performed against only streamflow can fairly mimic the streamflow hydrograph but does not yield realistic estimation of other fluxes such as evapotranspiration and soil moisture (especially in deeper soil layers).     

Variability of particulate (SS,POC) and dissolved (DOC,NO3) matter during storm events in the Alegria agricultural watershed

The temporal variability of suspended sediment, nitrates (NO₃) and dissolved (DOC) and particulate organic carbon concentrations was analysed in the Alegria agricultural watershed over a 2‐year period. Nine storm events were studied, including an exhaustive analysis of hydrometeorological conditions, quantification of fluxes, and concentration‐discharge hysteresis loop characterization. The overall aim was to study the variability in these components during storm events and determine the mechanisms (flow paths) affecting the trajectories, from the source to the stream. The forms, rotational patterns and trends of hysteretic loops were investigated, and relationships between hysteresis features and hydrological parameters were studied. The results revealed clear differences between particulate (suspended sediment, particulate organic carbon) and dissolved (DOC, NO₃) matter transport responses. Movement of the particulate matter was attributed to surface water, as reflected in clockwise hysteresis loops, whereas dissolved matter showed, in general, counterclockwise hysteresis loops, indicating a time delay in the arrival of solutes to the stream. This could be related to subsurface flow paths for DOC and a groundwater source for NO₃. Copyright © 2013 John Wiley & Sons, Ltd.     

Role of time variant and invariant terms on soil moisture spatio-temporal variability in a subhumid coastal wetland

The knowledge of soil moisture spatio-temporal variability is highly relevant for water resources management. This paper reports an analysis of the spatial–temporal variability of soil moisture data for a small to medium-scale soil-sensors network in a coastal wetland of southwestern Spain. Measurements were taken from five sites located in the Doñana National Park over the time-period of one hydrological year from September 2017 to September 2018. The total area of the soil-sensors network shows an extension about 25 × 3 km. Soil moisture data was separated into time invariant (the temporal mean of the whole period at each site) and time-variant terms (the deviations of soil moisture from the mean, or anomalies). The time-invariant component was generally the main contributor to the total spatial variance of soil moisture and it was mostly controlled by the groundwater levels in the area. Nevertheless, the time variant terms have a huge effect on soil moisture variability in very dry states. Characteristic convex time-dependent patterns for this field site were found between spatially averaged soil moisture and its variability. This information could be used for the up and downscaling of soil moisture from satellite data. Those patterns of relation between spatial mean and variability of soil moisture were only affected by heavy rainfalls giving rise to hysteretic behaviour. This study shows that even though groundwater level is a time-variant variable, it significantly affects soil moisture's time-variant but also time-invariant terms due to the different average groundwater level depths at the different sites.     

Passive microwave remote sensing contribution to hydrological variables

Physical principles governing passive microwave remote sensing of hydrological variables are outlined and illustrated by actual observations by ground-based, air-borne and space-borne microwave radiometers operating at different frequencies. Specific hydrological variables addressed in this paper are soil moisture, seasonal inundation of rivers and swamps, vegetation, snow, and rainfall. Passive remote sensing provides measurements of electromagnetic radiation emitted by the land-atmosphere system, which can be related more directly to the radiative characteristics of the system than to physical or physiological characteristics. Estimation of hydrological variables from microwave observations necessarily involves models relating the radiative to the physical characteristics, and in general more than one physical characteristics determine the microwave observations. This non-uniqueness in the relationship between microwave observations to a particular hydrological variable leads to uncertainties in the estimation of the variable. Notwithstanding this limitation, the principles and the examples given in this paper illustrate the value of passive microwave observations to regional and global hydrology at a temporal resolution of days aggregated to a decade.     

Quantifying contributions of snowmelt water to streamflow using graphical and chemical hydrograph separation

In this study, we characterize the snowmelt hydrological response of nine headwater watersheds in southeast Wyoming by separating streamflow into three components using a combination of tracer and graphical approaches. First, continuous 15-min records of specific conductance (SC) from 2016 to 2018 were used to separate streamflow into annual contributions, representing water that contributes to streamflow in a given year that entered the watershed in the same year being considered, and perennial contributions, representing water that contributes to streamflow in a given year that entered the watershed in previous years. Then, diurnal streamflow cycles occurring during the snowmelt season were used to graphically separate annual contributions into rapid diurnal snowmelt contributions, representing water with the relatively fastest hydrological response and shortest residence time, and delayed annual contributions, representing water with relatively longer residence time in the watershed before becoming streamflow. On average, mean annual total streamflow was comprised of between 22% and 46% perennial contributions, 7% and 14% rapid diurnal snowmelt contributions, and 46% and 55% delayed annual contributions across the watersheds. A hysteresis index describing SC-discharge patterns indicated that, annually, most watersheds showed negative, concave, anti-clockwise hysteretic direction suggesting faster flow pathways dominate streamflow on the rising limb of the annual hydrograph relative to the falling limb. At the daily timescale during snowmelt-induced diurnal streamflow cycles, hysteresis was negative, but with a clockwise direction, implying that rapid diurnal snowmelt contributions generated from the concurrent daily snowmelt, with lower SC, arrived after delayed annual contribution peaks and preferentially contributed on the falling limb of diurnal cycles. South-facing watersheds were more susceptible to early season snowmelt at slower rates, resulting in less annual and more perennial contributions. Conversely, north-facing watersheds had longer snow persistence and larger proportions of annual contributions and rapid diurnal snowmelt contributions. Watersheds with surficial geology dominated by glacial deposits had a lower proportion of rapid diurnal snowmelt contributions compared to watersheds with large percentages of bedrock surficial geology.     

Influence of soil moisture hysteresis on the functioning of capillary barriers

Previous experimental studies of capillary barriers have identified highly hysteretic soil moisture retention characteristics in the materials used. In this study, numerical modelling is used to analyse the role of soil moisture hysteresis in capillary barrier functioning. Comparisons between published experimental results and model simulations indicate that soil moisture hysteresis was a necessary inclusion in the modelling approach to adequately reproduce pore water pressure distributions and the timing of breakthrough occurrences. Under hypothetical intermittent infiltration and evaporation conditions, the predicted volumetric water content in the moisture retention layer was significantly different for hysteretic and non‐hysteretic models. The hysteresis effect was found to be dependent on the nature of infiltration–evaporation cycling, although the predicted volume of flow through the hysteretic barrier was lower than that of the non‐hysteretic case, regardless of the nature of the cyclic upper boundary conditions. For practical engineering designs, where the water leakage through the barrier is the primary concern, the inclusion of soil moisture hysteresis in numerical modelling is needed. Copyright © 2009 John Wiley & Sons, Ltd.     

Seasonal patterns of suspended sediment transport in an abandoned farmland catchment in the Central Spanish Pyrenees

The suspended sediment response of a small catchment subjected to farmland abandonment and subsequent plant recolonization was studied in relation to its hydrological functioning. The analysis of data over a seven‐year period demonstrated that suspended sediment yield was greatly influenced by the occurrence of intense, low‐frequency events. Greater amounts of suspended sediment were exported during spring, when the catchment was hydrologically more active. Rainfall intensity and baseflow at the start of a flood event had a strong influence on the sediment response, suggesting that several hydrological processes were active within the catchment. SSC (suspended sediment concentration)‐Q hysteretic loop analysis at the event scale aided understanding of the sedimentological and hydrological behaviour of the catchment. During the study period the SSC‐Q loops showed a high degree of seasonality and two main patterns strongly related to catchment wetness were distinguished. When the catchment was dry (mainly during summer and the beginning of autumn) the predominant process was infiltration excess runoff over sparsely vegetated areas close to the main channel. Under these conditions, floods exhibited a counter‐clockwise hysteretic loop and were characterized by a small streamflow response, short duration and high SSC. Under wet conditions (mainly during winter and spring), saturation excess runoff was increasingly dominant over vegetated areas. Under these conditions, floods exhibited a clockwise hysteretic loop, and were characterized by a larger streamflow response, longer duration and higher suspended sediment yield. The lower SSC during the falling stage of the hydrograph is likely to be due to dilution effects related to the contribution of clean water resulting from enlargement of the saturated areas, together with an increase in the baseflow discharge. Copyright © 2009 John Wiley & Sons, Ltd.     

Multi‐variable and multi‐site calibration and validation of SWAT in a large mountainous catchment with high spatial variability

Many methods developed for calibration and validation of physically based distributed hydrological models are time consuming and computationally intensive. Only a small set of input parameters can be optimized, and the optimization often results in unrealistic values. In this study we adopted a multi‐variable and multi‐site approach to calibration and validation of the Soil Water Assessment Tool (SWAT) model for the Motueka catchment, making use of extensive field measurements. Not only were a number of hydrological processes (model components) in a catchment evaluated, but also a number of subcatchments were used in the calibration. The internal variables used were PET, annual water yield, daily streamflow, baseflow, and soil moisture. The study was conducted using an 11‐year historical flow record (1990–2000); 1990–94 was used for calibration and 1995–2000 for validation. SWAT generally predicted well the PET, water yield and daily streamflow. The predicted daily streamflow matched the observed values, with a Nash–Sutcliffe coefficient of 0·78 during calibration and 0·72 during validation. However, values for subcatchments ranged from 0·31 to 0·67 during calibration, and 0·36 to 0·52 during validation. The predicted soil moisture remained wet compared with the measurement. About 50% of the extra soil water storage predicted by the model can be ascribed to overprediction of precipitation; the remaining 50% discrepancy was likely to be a result of poor representation of soil properties. Hydrological compensations in the modelling results are derived from water balances in the various pathways and storage (evaporation, streamflow, surface runoff, soil moisture and groundwater) and the contributions to streamflow from different geographic areas (hill slopes, variable source areas, sub‐basins, and subcatchments). The use of an integrated multi‐variable and multi‐site method improved the model calibration and validation and highlighted the areas and hydrological processes requiring greater calibration effort. Copyright © 2005 John Wiley & Sons, Ltd.     

Climate Variability in NW Spain and its Relationship with Water Balance and Streamflow in a Small Headwater Catchment: Preliminary Results

This paper presents preliminary results from an analysis of hydrological variability of a catchment located in Galicia (NW Spain), with particular focus on the effects of climate variability (temperature and precipitation), using daily streamflow data for the period October 2004 to September 2009. The climate variability has been studied by means of data obtained in a meteorological station on the area. The analysis is based on the examination of statistical parameters, flow duration characteristics, baseflow separation and the relationship between measured streamflow and precipitation. The results show that daily, monthly and annual streamflow are highly variable in this catchment. At seasonal scale about 65% of the water flows in winter (33%) and spring (32%) months, although with significant differences between years. This seasonality essentially relates to distribution and characteristics of precipitation episodes. However, there is not a narrow relationship between precipitation and streamflow, because soil moisture conditions have an important role in the hydrological behaviour of the catchment. The baseflow contribution to total streamflow is quite high, with baseflow index values above 0.69, which is consistent with the characteristics of the study area, such as geology (dominated by schist), soils (Umbrisols and Cambisols), vegetation cover (over 65% forest area) and precipitation characteristics (heavy, long duration and low intensity). The flow duration analysis also reveals that the flow regime is dominated by baseflow, recording high flow peaks during a limited period of the year. The study reveals that the major cause of streamflow variability in this catchment is related to precipitation distribution and soil moisture conditions. The results suggest that the Corbeira stream undergoes a reduction in low streamflows and an increase in the frequency of high flows, hence producing an increase in the risks associated with these changes.     

On the importance of soil moisture in calibration of rainfall–runoff models: two case studies

Streamflow modelling results from the GR4H and PDM hydrological models were evaluated in two Australian sub-catchments, using (1) calibration to streamflow and (2) joint-calibration to streamflow and soil moisture. Soil moisture storage in the models was evaluated against soil moisture observations from field measurements. The PDM had the best performance in terms of both streamflow and soil moisture estimations during the calibration period, but was outperformed by GR4H during validation. It was also shown that the soil moisture estimation was improved significantly by joint-calibration for the case where streamflow and soil moisture estimations were poor. In other cases, addition of the soil moisture constraint did not degrade the results. Consequently, it is recommended that GR4H be used, in preference to the PDM, in the foothills of the Murrumbidgee catchment or other Australian catchments with semi-arid to sub-humid climate, and that soil moisture data be used in the calibration process.     

Regional assimilation of in situ observed soil moisture into the VIC model considering spatial variability

ABSTRACT

In order to improve the soil moisture (SM) modelling capacity, a regional SM assimilation scheme based on an empirical approach considering spatial variability was constructed to assimilate in situ observed SM data into a hydrological model. The daily variable infiltration capacity (VIC) model was built to simulate SM in the Upper Huai River Basin, China, with a resolution of 5 km × 5 km. Through synthetic assimilation experiments and validations, the assimilated SM was evaluated, and the assimilation feedback on evapotranspiration (ET) and streamflow are analysed and discussed. The results show that the assimilation scheme improved the SM modelling capacity, both spatially and temporally. Moreover, the simulated ET was continually affected by changes in SM simulation, and the streamflow predictions were improved after applying the SM assimilation scheme. This study demonstrates the potential value of in situ observations in SM assimilation, and provides valuable ways for improving hydrological simulations.     

Comparison of daily and sub-daily SWAT models for daily streamflow simulation in the Upper Huai River Basin of China

Despite the significant role of precipitation in the hydrological cycle, few studies have been conducted to evaluate the impacts of the temporal resolution of rainfall inputs on the performance of SWAT (soil and water assessment tool) models in large-sized river basins. In this study, both daily and hourly rainfall observations at 28 rainfall stations were used as inputs to SWAT for daily streamflow simulation in the Upper Huai River Basin. Study results have demonstrated that the SWAT model with hourly rainfall inputs performed better than the model with daily rainfall inputs in daily streamflow simulation, primarily due to its better capability of simulating peak flows during the flood season. The sub-daily SWAT model estimated that 58 % of streamflow was contributed by baseflow compared to 34 % estimated by the daily model. Using the future daily and 3-h precipitation projections under the RCP (Representative Concentration Pathways) 4.5 scenario as inputs, the sub-daily SWAT model predicted a larger amount of monthly maximum daily flow during the wet years than the daily model. The differences between the daily and sub-daily SWAT model simulation results indicated that temporal rainfall resolution could have much impact on the simulation of hydrological process, streamflow, and consequently pollutant transport by SWAT models. There is an imperative need for more studies to examine the effects of temporal rainfall resolution on the simulation of hydrological and water pollutant transport processes by SWAT in river basins of different environmental conditions.     

Seasonal changes in runoff generation in a small forested mountain catchment

This study aimed to investigate the seasonal variability of runoff generation processes, the sources of stream water, and the controls on the contribution of event water to streamflow for a small forested catchment in the Italian pre‐Alps. Hydrometric, isotopic, and electrical conductivity data collected between August 2012 and August 2013 revealed a marked seasonal variability in runoff responses. Noticeable differences in runoff coefficients and hydrological dynamics between summer and fall/spring rainfall events were related to antecedent moisture conditions and event size. Two‐component and three‐component hydrograph separation and end‐member mixing analysis showed an increase in event water contributions to streamflow with event size and average rainfall intensity. Event water fractions were larger during dry conditions in the summer, suggesting that stormflow generation in the summer consisted predominantly of direct channel precipitation and some saturated overland flow from the riparian zone. On the contrary, groundwater and hillslope soil water contributions dominated the streamflow response during wet conditions in fall. Seasonal differences were also noted between event water fractions computed based on isotopic and electrical conductivity data, likely because of the dilution effect during the wetter months. Copyright © 2014 John Wiley & Sons, Ltd.     

Evolutionary assimilation of streamflow in distributed hydrologic modeling using in-situ soil moisture data

This study has applied evolutionary algorithm to address the data assimilation problem in a distributed hydrological model. The evolutionary data assimilation (EDA) method uses multi-objective evolutionary strategy to continuously evolve ensemble of model states and parameter sets where it adaptively determines the model error and the penalty function for different assimilation time steps. The assimilation was determined by applying the penalty function to merge background information (i.e., model forecast) with perturbed observation data. The assimilation was based on updated estimates of the model state and its parameterizations, and was complemented by a continuous evolution of competitive solutions.The EDA was illustrated in an integrated assimilation approach to estimate model state using soil moisture, which in turn was incorporated into the soil and water assessment tool (SWAT) to assimilate streamflow. Soil moisture was independently assimilated to allow estimation of its model error, where the estimated model state was integrated into SWAT to determine background streamflow information before they are merged with perturbed observation data. Application of the EDA in Spencer Creek watershed in southern Ontario, Canada generates a time series of soil moisture and streamflow. Evaluation of soil moisture and streamflow assimilation results demonstrates the capability of the EDA to simultaneously estimate model state and parameterizations for real-time forecasting operations. The results show improvement in both streamflow and soil moisture estimates when compared to open-loop simulation, and a close matching between the background and the assimilation illustrates the forecasting performance of the EDA approach.     

The value of remotely sensed surface soil moisture for model calibration using SWAT

Remotely sensed (RS) data can add value to a hydrological model calibration. Among this, RS soil moisture (SM) data have mostly been assimilated into conceptual hydrological models using various transformed variable or indices. In this study, raw RS surface SM is used as a calibration variable in the Soil and Water Assessment Tool model. This means the SM values were not transformed into another variable (e.g., soil water index and root zone SM index). Using a nested catchment, calibration based only on RS SM and optimizing model parameters sensitive to SM using particle swarm optimization improved variations in streamflow predictions at some of the gauging stations compared to the uncalibrated model. This highlighted part of the catchments where the SM signal directly influenced the flow distribution. Additionally, highlighted high and low flow signals were mostly influenced. The seasonal breakdown indicates that the SM signal is more useful for calibrating in wetter seasons and in areas with higher variations in elevation. The results identified that calibration only on RS SM improved the general rainfall–runoff response simulation by introducing delays but cannot correct the overall routing effect. Furthermore, catchment characteristics (e.g., land use, elevation, soil types, and precipitation) regulating SM variation in different seasons highlighted by the model calibration are identified. This provides further opportunities to improve model parameterization.     

Error distribution modelling of satellite soil moisture measurements for hydrological applications

Satellite‐based soil moisture data accuracies are of important concerns by hydrologists because they could significantly influence hydrological modelling uncertainty. Without proper quantification of their uncertainties, it is difficult to optimize the hydrological modelling system and make robust decisions. Currently, the satellite soil moisture data uncertainty has been limited to summary statistics with the validations mainly from the in situ measurements. This study attempts to build the first error distribution model with additional higher‐order uncertainty modelling for satellite soil moisture observations. The methodology is demonstrated by a case study using the Soil Moisture and Ocean Salinity satellite soil moisture observations. The validation is based on soil moisture estimates from hydrological modelling, which is more relevant to the intended data use than the in situ measurements. Four probability distributions have been explored to find suitable error distribution curves using the statistical tests and bootstrapping resampling technique. General extreme value is identified as the most suitable one among all the curves. The error distribution model is still in its infant stage, which ignores spatial and temporal correlations, and nonstationarity. Further improvements should be carried out by the hydrological community by expanding the methodology to a wide range of satellite soil moisture data using different hydrological models. Copyright © 2016 John Wiley & Sons, Ltd.     

Response of hydrology to climate change in the southern Appalachian Mountains using Bayesian inference

Predicting long‐term consequences of climate change on hydrologic processes has been limited due to the needs to accommodate the uncertainties in hydrological measurements for calibration, and to account for the uncertainties in the models that would ingest those calibrations and uncertainties in climate predictions as basis for hydrological predictions. We implemented a hierarchical Bayesian (HB) analysis to coherently admit multiple data sources and uncertainties including data inputs, parameters, and model structures to identify the potential consequences of climate change on soil moisture and streamflow at the head watersheds ranging from low to high elevations in the southern Appalachian region of the United States. We have considered climate change scenarios based on three greenhouse gas emission scenarios of the Interovernmental Panel on Climate Change: A2, A1B, and B1 emission scenarios. Full predictive distributions based on HB models are capable of providing rich information and facilitating the summarization of prediction uncertainties. With predictive uncertainties taken into account, the most pronounced change in soil moisture and streamflow would occur under the A2 scenario at both low and high elevations, followed by the A1B scenario and then by the B1 scenario. Uncertainty in the change of soil moisture is less than that of streamflow for each season, especially at high elevations. A reduction of soil moisture in summer and fall, a reduction or slight increase of streamflow in summer, and an increase of streamflow in winter are predicted for all three scenarios at both low and high elevations. The hydrological predictions with quantified uncertainties from a HB model could aid more‐informed water resource management in developing mitigation plans and dealing with water security under climate change. Copyright © 2012 John Wiley & Sons, Ltd.