Projection of glacier runoff in Yarkant River basin and Beida River basin,Western China

Potential changes in glacier area, mass balance and runoff in the Yarkant River Basin (YRB) and Beida River Basin (BRB) are projected for the period from 2011 to 2050 employing the modified monthly degree‐day model forced by climate change projection. Future monthly air temperature and precipitation were derived from the simple average of 17, 16 and 17 General Circulation Model (GCM) projections following the A1B, A2 and B1 scenarios, respectively. These data were downscaled to each station employing the Delta method, which computes differences between current and future GCM simulations and adds these changes to observed time series. Model parameters calibrated with observations or results published in the literature between 1961 and 2006 were kept unchanged. Annual glacier runoff in YRB is projected to increase until 2050, and the total runoff over glacier area in 1970 is projected to increase by about 13%–35% during 2011–2050 relative to the average during 1961–2006. Annual glacier runoff and the total runoff over glacier area in 1970 in BRB is projected to increase initially and then to reach a tipping point during 2011–2030. There are prominent increases in summer, but only small increase in May and October of glacier runoff in YRB, and significant increases during late spring and early summer and significant decreases in July and late summer of glacier runoff in BRB. This study highlights the great differences among basins in their response to future climate warming. The specific runoff from areas exposed after glacier retreat relative to 1970 is projected to general increasing, which must be considered when evaluating the potential change of glacier runoff. Copyright © 2011 John Wiley & Sons, Ltd.     

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.     

Thermal influence of urban groundwater recharge from stormwater infiltration basins

Groundwater warming below cities has become a major environmental issue; but the effect of distinct local anthropogenic sources of heat on urban groundwater temperature distributions is still poorly documented. Our study addressed the local effect of stormwater infiltration on the thermal regime of urban groundwater by examining differences in water temperature beneath stormwater infiltration basins (SIB) and reference sites fed exclusively by direct infiltration of rainwater at the land surface. Stormwater infiltration dramatically increased the thermal amplitude of groundwater at event and season scales. Temperature variation at the scale of rainfall events reached 3 °C and was controlled by the interaction between runoff amount and difference in temperature between stormwater and groundwater. The annual amplitude of groundwater temperature was on average nine times higher below SIB (range: 0·9–8·6 °C) than at reference sites (range: 0–1·2 °C) and increased with catchment area of SIB. Elevated summer temperature of infiltrating stormwater (up to 21 °C) decreased oxygen solubility and stimulated microbial respiration in the soil and vadose zone, thereby lowering dissolved oxygen (DO) concentration in groundwater. The net effect of infiltration on average groundwater temperature depended upon the seasonal distribution of rainfall: groundwater below large SIB warmed up (+0·4 °C) when rainfall occurred predominantly during warm seasons. The thermal effect of stormwater infiltration strongly attenuated with increasing depth below the groundwater table indicating advective heat transport was restricted to the uppermost layers of groundwater. Moreover, excessive groundwater temperature variation at event and season scales can be attenuated by reducing the size of catchment areas drained by SIB and by promoting source control drainage systems. Copyright © 2009 John Wiley & Sons, Ltd.     

Exploring impacts of development and climate change on stormwater runoff

Stormwater runoff is a leading cause of non‐point source pollution in urbanizing areas, and runoff effects will be exacerbated by climate's changing patterns of precipitation. To enhance understanding of impacts of development and climate change on stormwater runoff in small watersheds (< 6500 ha), we developed the Stormwater Runoff Modeling System (SWARM), a simple modeling system based on U.S. Department of Agriculture, Natural Resources Conservation Service curve number and unit hydrograph methods. The objective of this paper is to describe the applications possible with SWARM and to demonstrate its usefulness in exploring the impacts of development and climate change on runoff. Results encompass a range of impact scenarios. One development scenario shows that the amount of rainfall converted to runoff is 27% for an undeveloped area and 67% for a highly developed area. A climate scenario shows that the amount of rainfall converted to runoff in a medium developed area is 25% in drought conditions and 76% in wet conditions. User‐friendly templates make SWARM a good tool for scientific research, for resource management and decision making, and for community science education. The modeling system also supports the investigation of social and economic impacts to communities as they adapt to increased development and climate change. Although we calibrated SWARM specifically to the southeast coastal plain, it can be applied to other regions by recalibrating parameters and modifying calculation templates. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.     

Coupled infiltration and filtration behaviours of concrete porous pavement for stormwater management

Cementitious porous pavement (CPP) is a structural low‐impact development material for rainfall–runoff management. Both infiltration and filtration are critical functions for CPP stormwater quality and quantity control. In this study, three groups of CPP specimens exposed to rainfall–runoff for 4 years and experienced with different maintenance intervals (6, 12 and 48 months, respectively) were used to examine CPP infiltration and filtration performance. Particle mass strained on CPP surface, saturated infiltration rate I_f, temporal infiltration rate I(t), suspended sediment concentration (SSC) and turbidity (τ) were measured to evaluate the process of filtration/infiltration. I(t), SSC and τ were examined less than 50 mg/l of the suspended particle loading. It was found that the CPP surface cleaning methods used in the past 4 years, namely, high pressure wash followed by vacuuming with one atmosphere (100 kPa), were effective, and a 12‐month maintenance interval was verified suitable to maintain the pore structure an acceptable infiltration rate for stormwater management. It was also found that CPP infiltration and filtration process affect each other, and the two properties are coupled in urban stormwater quality and quantity control. On the basis of the experimental measurements, the temporal infiltration rate of the cleaned CPP under a certain particle loading could be simulated by a first‐order nonlinear rational model, and effluent turbidity–SSC relationship was found following a power law. Copyright © 2012 John Wiley & Sons, Ltd.     

Heat release from rooftops during rainstorms in the Minneapolis/St. Paul Metropolitan Area,USA

In the modeling of urban storm water runoff temperatures, the contribution of rooftops to the heating of rainfall runoff is usually neglected or not mentioned in the literature. In this paper we examine the accuracy of this assumption (a) by analyzing temperature data that we recorded on a residential rooftop, a commercial rooftop, and a concrete driveway, and (b) by simulating temperature profiles within rooftops and pavements, and estimating heat transfer amounts from these surfaces to rainfall runoff (‘heat export’). Analysis of both wet‐ and dry‐weather temperature data recorded in the Minneapolis/St. Paul metropolitan area (north‐central USA) over periods of several months leads to the conclusion that (a) a concrete driveway has a far greater capacity for heat storage and release than a shingled residential rooftop, and (b) an insulated commercial rooftop is able to store and release more heat than the residential rooftop. Unexpectedly, the rainfall events with the highest dew point (rainfall) and surface temperatures often occurred during late night or early morning hours, and not during daylight hours. The analysis of three rainfall events showed that the heat export from the commercial rooftop was roughly three times that of the residential rooftop, but only 30%–90% of the heat export from a concrete driveway. Maximum (potential) heat export was significantly higher for the driveway than for either rooftop. In conclusion, the results of the data analysis and heat export simulations support the assumption that residential rooftops contribute very little heating to runoff from rainfall, while commercial rooftops may have a thermal impact on rainfall runoff because of their greater thermal storage capacity. Commercial rooftops, in addition to asphalt and concrete pavements, should be considered when estimating water temperature of rainfall runoff from urbanized areas and the associated impact on the thermal regime of streams and fish habitat. Copyright © 2011 John Wiley & Sons, Ltd.     

Uncertainty analysis of downscaling methods in assessing the influence of climate change on hydrology

Five downscaling techniques, namely the statistical downscaling model, the automated statistical downscaling method, the change factor (CF) method, the advanced CF method, the Weather generator (LarsWG5) method, are applied to the upstream basin of the Huaihe River. Changes in regional climate scenarios and hydrology variables are compared in future periods to investigate the uncertainty associated with the downscaling techniques. Paired-sample T test is applied to evaluation the significant of the difference of the means between the observed data and the downscaled data in the future. The Xinanjiang rainfall–runoff model is employed to simulate the rainfall–runoff relation. The results demonstrate that the downscaling techniques utilized herein predict an increased tendency in the future. The increases range of maximum temperature (T_max) is between 3.7 and 4.7 °C until the time period of 2070–2099 (2080s). While, the increases range of minimum temperature (T_min) is between 2.8 and 4.9 °C until 2080s. The research presented herein determined that there is an increase predicted for the peaks over threshold (discussed in the paper) and a decrease predicted for the peaks below the threshold (discussed in the paper) in the future, which illustrates that the temperature would rise gradually in the future. Precipitation changes are not as obvious as temperatures changes and tend to be influence by the season. Most downscaling techniques predict increases, and others indict decreases. The annual mean precipitation range changes between 3.2 and 53.3 %, and moreover, these changes vary from season to season.     

Assessment of future runoff trends under multiple climate change scenarios in the Willamette River Basin,Oregon, USA

We investigated trends in future seasonal runoff components in the Willamette River Basin (WRB) of Oregon for the twenty‐first century. Statistically downscaled climate projections by Climate Impacts Group (CIG), eight different global climate model (GCM) simulations with two different greenhouse gas (GHG) emission scenarios, (A1B and B1), were used as inputs for the US Geological Survey's Precipitation Runoff Modelling System. Ensemble mean results show negative trends in spring (March, April and May) and summer (June, July and August) runoff and positive trends in fall (September, October and November) and winter (December, January and February) runoff for 2000–2099. This is a result of temperature controls on the snowpack and declining summer and increasing winter precipitation. With temperature increases throughout the basin, snow water equivalent (SWE) is projected to decline consistently for all seasons. The decreases in the centre of timing and 7‐day low flows and increases in the top 5% flow are caused by the earlier snowmelt in spring, decreases in summer runoff and increases in fall and winter runoff, respectively. Winter runoff changes are more pronounced in higher elevations than in low elevations in winter. Seasonal runoff trends are associated with the complex interactions of climatic and topographic variables. While SWE is the most important explanatory variable for spring and winter runoff trends, precipitation has the strongest influence on fall runoff. Spatial error regression models that incorporate spatial dependence better explain the variations of runoff trends than ordinary least‐squares (OLS) multiple regression models. Our results show that long‐term trends of water balance components in the WRB could be highly affected by anthropogenic climate change, but the direction and magnitude of such changes are highly dependent on the interactions between climate change and land surface hydrology. This suggests a need for spatially explicit adaptive water resource management within the WRB under climate change. Copyright © 2010 John Wiley & Sons, Ltd.     

Urban stormwater thermal gene expression models for protection of sensitive receiving streams

Thermal impact of typical high‐density residential, industrial, and commercial land uses is a major concern for the health of aquatic life in urban watersheds, especially in smaller, cold, and cool‐water streams. This is the first study of its kind that provides simple easy‐to‐use equations, developed using gene expression programming (GEP) that can guide the assessment and the design of urban stormwater management systems to protect thermally sensitive receiving streams. We developed 3 GEP models using data collected during 3 years (2009–2011) from 4 urban catchments; the first GEP model predicts event mean temperature at the inlet of the pond; the second model predicts the stormwater temperature at the outlet of the pond; and the third model predicts the temperature of the stormwater after flowing through a cooling trench and before discharging to the receiving stream. The new models have high correlation coefficients of 0.90–0.94 and low prediction uncertainty of less than 4% of the median value of the predicted runoff temperatures. Sensitivity analysis shows that climatic factors have the highest influence on the thermal enrichment followed by the catchment characteristics and the key design variables of the stormwater pond and the cooling trench. The general method presented here is easily transferable to other regions of the world (but not necessarily the exact equations developed here); also through sensitivity and parametric analysis, we gained insight on the key factors and their relative importance in modelling thermal enrichment of urban stromwater runoff.     

A runoff map based on numerically simulated precipitation and a projection of future runoff in Iceland / Une carte d'écoulement basée sur la précipitation numériquement simulée et un scénario du futur écoulement en Islande

Abstract

The runoff of Iceland has been evaluated for the period 1961–1990, and changes in runoff from then to the period 2071–2100 predicted according to a future projection of climate change. The hydrological model WASIM-ETH was used, with meteorological data from the PSU/NCAR MM5 numerical weather model. The evaluation of the effects of climate change on water resources was based on a future climate simulation from the HIRHAM regional climate model with boundary conditions from the HadAM3H global climate model using A2 and B2 emissions scenarios. Future runoff was shown to become much higher in 2071–2100 compared to 1961–1990, predominantly due to increased glacial melt caused by increased temperature. Furthermore, changes in runoff seasonality would be substantial. Thus, according to this projection there could be great changes in hydropower production potential associated with climate change in Iceland.     

Statistical downscaling of extremes of precipitation and temperature and construction of their future scenarios in an elevated and cold zone

Reliable projections of extremes at finer spatial scales are important in assessing the potential impacts of climate change on societal and natural systems, particularly for elevated and cold regions in the Tibetan Plateau. This paper presents future projections of extremes of daily precipitation and temperature, under different future scenarios in the headwater catchment of Yellow River basin over the 21st century, using the statistical downscaling model (SDSM). The results indicate that: (1) although the mean temperature was simulated perfectly, followed by monthly pan evaporation, the skill scores in simulating extreme indices of precipitation are inadequate; (2) The inter-annual variabilities for most extreme indices were underestimated, although the model could reproduce the extreme temperatures well. In fact, the simulation of extreme indices for precipitation and evaporation were not satisfactory in many cases. (3) In future period from 2011 to 2100, increases in the temperature and evaporation indices are projected under a range of climate scenarios, although decreasing mean and maximum precipitation are found in summer during 2020s. The findings of this work will contribute toward a better understanding of future climate changes for this unique region.     

Stormwater pollutant runoff: A stochastic approach

Since stormwater wash-off of pollutants in urban areas is largely affected by environmental variability, it is very difficult to predict the amount of pollutants transported by stormwater runoff during and after individual rainfall events. We investigated the addition of a random component into an exponential wash-off equation of total suspended solids (TSS) and total nitrogen (TN) to model the variability of runoff pollutant concentrations. The model can be analytically solved to describe the probability distributions of TSS and TN concentrations as a function of increasing runoff depths. TSS data from six Australian catchments and TN data from three of these catchments were used to calibrate the model and evaluate its applicability. Using the results of the model, its potential use to determine the appropriate size of stormwater treatment systems is discussed, stressing how probabilistic considerations should be included in the design of such systems. Specifically, stormwater depths retained by a treatment system should result from a compromise between the recurrence of specific runoff depths and the probability to discharge a target pollutant concentration when such a runoff depth is exceeded.     

Effects of land use intensity on stormwater runoff and its temporal occurrence in cold climates

The impacts of land use intensity, here defined as the degree of imperviousness, on stormwater volumes, runoff rates and their temporal occurrence were studied at three urban catchments in a cold region in southern Finland. The catchments with ‘High’ and ‘Intermediate’ land use intensity, located around the city centre, were characterized by 89% and 62% impervious surfaces, respectively. The ‘Low’ catchment was situated in a residential area of 19% imperviousness. During a 2‐year study period with divergent weather conditions, the generation of stormwater correlated positively with catchment imperviousness: The largest annual stormwater volumes and the highest runoff coefficients and number of stormwater runoff events occurred in the High catchment. Land use intensity also altered the seasonality of stormwater runoff: Most stormwater in the High catchment was generated during the warm period of the year, whereas the largest contribution to annual stormwater generation in the Low catchment took place during the cold period. In the two most urbanized catchments, spring snow melt occurred a few weeks earlier than in the Low catchment. The rate of stormwater runoff in the High and Intermediate catchments was higher in summer than during spring snow melt, and summer runoff rates in these more urbanized catchments were several times higher than in the Low catchment. Our study suggests that the effects of land use intensity on stormwater runoff are season dependent in cold climates and that cold seasons diminish the differences between land use intensities. Copyright © 2013 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.     

Daily rainfall projections from general circulation models with a downscaling nonhomogeneous hidden Markov model (NHMM) for south‐eastern Australia

An ensemble of stochastic daily rainfall projections has been generated for 30 stations across south‐eastern Australia using the downscaling nonhomogeneous hidden Markov model, which was driven by atmospheric predictors from four climate models for three IPCC emissions scenarios (A1B, A2, and B1) and for two periods (2046–2065 and 2081–2100). The results indicate that the annual rainfall is projected to decrease for both periods for all scenarios and climate models, with the exception of a few scenarios of no statistically significant changes. However, there is a seasonal difference: two downscaled GCMs consistently project a decline of summer rainfall, and two an increase. In contrast, all four downscaled GCMs show a decrease of winter rainfall. Because winter rainfall accounts for two‐thirds of the annual rainfall and produces the majority of streamflow for this region, this decrease in winter rainfall would cause additional water availability concerns in the southern Murray–Darling basin, given that water shortage is already a critical problem in the region. In addition, the annual maximum daily rainfall is projected to intensify in the future, particularly by the end of the 21st century; the maximum length of consecutive dry days is projected to increase, and correspondingly, the maximum length of consecutive wet days is projected to decrease. These changes in daily sequencing, combined with fewer events of reduced amount, could lead to drier catchment soil profiles and further reduce runoff potential and, hence, also have streamflow and water availability implications. Copyright © 2012 John Wiley & Sons, Ltd.     

Climate change impacts on surface water resources in the Rheraya catchment (High Atlas,Morocco)

This study aimed to quantify possible climate change impacts on runoff for the Rheraya catchment (225 km²) located in the High Atlas Mountains of Morocco, south of Marrakech city. Two monthly water balance models, including a snow module, were considered to reproduce the monthly surface runoff for the period 1989?2009. Additionally, an ensemble of five regional climate models from the Med-CORDEX initiative was considered to evaluate future changes in precipitation and temperature, according to the two emissions scenarios RCP4.5 and RCP8.5. The future projections for the period 2049?2065 under the two scenarios indicate higher temperatures (+1.4°C to +2.6°C) and a decrease in total precipitation (?22% to ?31%). The hydrological projections under these climate scenarios indicate a significant decrease in surface runoff (?19% to ?63%, depending on the scenario and hydrological model) mainly caused by a significant decline in snow amounts, related to reduced precipitation and increased temperature. Changes in potential evapotranspiration were not considered here, since its estimation over long periods remains a challenge in such data-sparse mountainous catchments. Further work is required to compare the results obtained with different downscaling methods and different hydrological model structures, to better reproduce the hydro-climatic behaviour of the catchment.

EDITOR M.C. Acreman

ASSOCIATE EDITOR R. Hirsch     

Impact of climate change on water availability in the Macquarie‐Castlereagh River Basin in Australia

The impact of future climate on runoff generation and the implications of these changes for management of water resources in a river basin are investigated by running these changes through catchment and river system models. Two conceptual daily rainfall‐runoff models are used to simulate runoff across the Macquarie‐Castlereagh region for historical (1895–2006) and future (～2030) climate based on outputs from 15 of the 23 IPCC AR4 GCMs for the A1B global warming scenario. The estimates of future runoff are used as inputs to the river system model. The mean annual historical rainfall averaged across the Macquarie‐Castlereagh region is 544 mm and the simulated runoff is 34 and 30 mm for SIMHYD and Sacramento rainfall‐runoff models, respectively. The mean annual future rainfall and runoff across the region are projected to decrease. The modelling results show a median estimate of a 5% reduction for SIMHYD (50% confidence interval ? 11 to + 7%) and a 7% reduction for Sacramento (50% confidence interval ? 15 to + 8%) in mean annual runoff under a ～2030 climate for the region. The results from the river system modelling indicate that under the ～2030 climate scenario, the median of general security and supplementary diversions are projected to decrease by 4% (50% confidence interval ? 10 to + 5%) and 2% (50% confidence interval ? 5 to + 3%) respectively for the SIMHYD inflows and 8% (50% confidence interval ? 17 to + 6%) and 5% (50% confidence interval ? 11 to + 3%) for the Sacramento inflows. The future annual and seasonal storage volumes for the Burrendong Dam and inflows at all major locations across the region are projected to be lower than the historical records. Copyright © 2011 John Wiley & Sons, Ltd.     

Projecting climate change impacts on stream flow regimes with tracer‐aided runoff models ‐ preliminary assessment of heterogeneity at the mesoscale

The northern mid‐high latitudes form a region that is sensitive to climate change, and many areas already have seen – or are projected to see – marked changes in hydroclimatic drivers on catchment hydrological function. In this paper, we use tracer‐aided conceptual runoff models to investigate such impacts in a mesoscale (749 km²) catchment in northern Scotland. The catchment encompasses both sub‐arctic montane sub‐catchments with high precipitation and significant snow influence and drier, warmer lowland sub‐catchments. We used downscaled HadCM3 General Circulation Model outputs through the UKCP09 stochastic weather generator to project the future climate. This was based on synthetic precipitation and temperature time series generated from three climate change scenarios under low, medium and high greenhouse gas emissions. Within an uncertainty framework, we examined the impact of climate change at the monthly, seasonal and annual scales and projected impacts on flow regimes in upland and lowland sub‐catchments using hydrological models with appropriate process conceptualization for each landscape unit. The results reveal landscape‐specific sensitivity to climate change. In the uplands, higher temperatures result in diminishing snow influence which increases winter flows, with a concomitant decline in spring flows as melt reduces. In the lowlands, increases in air temperatures and re‐distribution of precipitation towards autumn and winter lead to strongly reduced summer flows despite increasing annual precipitation. The integration at the catchment outlet moderates these seasonal extremes expected in the headwaters. This highlights the intimate connection between hydrological dynamics and catchment characteristics which reflect landscape evolution. It also indicates that spatial variability of changes in climatic forcing combined with differential landscape sensitivity in large heterogeneous catchments can lead to higher resilience of the integrated runoff response. Copyright © 2012 John Wiley & Sons, Ltd.     

基于改进U-Net的CMIP5全球气候模式降尺度方法及其在鄱阳湖流域的应用

利用降尺度方法对CMIP5全球气候模式进行空间降尺度并以此研究鄱阳湖流域未来气候时空变化趋势,能够为流域生态环境保护提供数据、技术和理论上的支持.通过简化原始网络结构,在网络首部添加插值层,采用反卷积算法作为上采样算法对传统U-Net网络进行改进,建立基于深度学习的气候模式空间降尺度模型(DLDM).以1965-200...     

Assessment of hydrologic impacts of climate change in Tunga–Bhadra river basin,India with HEC‐HMS and SDSM

Climate change would significantly affect many hydrologic systems, which in turn would affect the water availability, runoff, and the flow in rivers. This study evaluates the impacts of possible future climate change scenarios on the hydrology of the catchment area of the Tunga–Bhadra River, upstream of the Tungabhadra dam. The Hydrologic Engineering Center's Hydrologic Modeling System version 3.4 (HEC‐HMS 3.4) is used for the hydrological modelling of the study area. Linear‐regression‐based Statistical DownScaling Model version 4.2 (SDSM 4.2) is used to downscale the daily maximum and minimum temperature, and daily precipitation in the four sub‐basins of the study area. The large‐scale climate variables for the A2 and B2 scenarios obtained from the Hadley Centre Coupled Model version 3 are used. After model calibration and testing of the downscaling procedure, the hydrological model is run for the three future periods: 2011–2040, 2041–2070, and 2071–2099. The impacts of climate change on the basin hydrology are assessed by comparing the present and future streamflow and the evapotranspiration estimates. Results of the water balance study suggest increasing precipitation and runoff and decreasing actual evapotranspiration losses over the sub‐basins in the study area. Copyright © 2012 John Wiley & Sons, Ltd.