Evaluating sources of uncertainty in Australian runoff projections

Generating estimates of the future impacts of climate change on human and natural systems is confounded by cascading uncertainties which propagate through the impact assessment. Here, a simple stochastic rainfall–runoff model representing 238 river basins on the Australian continent was used to assess the sensitivity of the risk of runoff changes to various sources of uncertainty. Uncertainties included global mean temperature change, greenhouse gas stabilisation targets, catchment sensitivities to climatic change, and the seasonality of runoff, rainfall, and evaporation. Model simulations provided estimates of the first-order risk of climate change to Australian catchments, with several regions having high likelihoods of experiencing significant reductions in future runoff. Climate uncertainty (at global and regional scales) was identified as the dominant driving force in hydrological risk assessments. Uncertainties in catchment sensitivities to climatic changes also influenced risk, provided they were sufficiently large, whereas structural assumptions of the model were generally negligible. Collectively, these results indicate that rigorous assessment of climate risk to water resources over relatively long time-scales is largely a function of adequately exploring the uncertainty space of future climate changes.     

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.     

The role of urban growth,climate change,and their interplay in altering runoff extremes

Changes in climate and urban growth are the most influential factors affecting hydrological characteristics in urban and extra‐urban contexts. The assessment of the impacts of these changes on the extreme rainfall–runoff events may have important implications on urban and extra‐urban management policies against severe events, such as floods, and on the design of hydraulic infrastructures. Understanding the effects of the interaction between climate change and urban growth on the generation of runoff extremes is the main aim of this paper. We carried out a synthetic experiment on a river catchment of 64 km² to generate hourly runoff time series under different hypothetical scenarios. We imposed a growth of the percentage of urban coverage within the basin (from 1.5% to 25%), a rise in mean temperature of 2.6 °C, and an alternatively increase/decrease in mean annual precipitation of 25%; changes in mean annual precipitation were imposed following different schemes, either changing rainstorm frequency or rainstorm intensity. The modelling framework consists of a physically based distributed hydrological model, which simulates fast and slow mechanisms of runoff generation directly connected with the impervious areas, a land‐use change model, and a weather generator. The results indicate that the peaks over threshold and the hourly annual peaks, used as hydrological indicators, are very sensitive to the rainstorm intensity. Moreover, the effects of climate changes dominate on those of urban growth determining an exacerbation of the fast runoff component in extreme events and a reduction of the slow and deep runoff component, thus limiting changes in the overall runoff.     

Simulating the impacts of land-use and climate change on water resource availability for a large south Indian catchment

Abstract

A monthly rainfall-runoff model was calibrated for a large tropical catchment in southern India. Various land-use and climatic change scenarios were tested to assess their effects on mean annual runoff and assured water yield at the Bhavanisagar Reservoir in Tamil Nadu, India. The largest increase in runoff (19%) came from converting forest and savanna (the indigenous control scenario) to agriculture. Mean annual runoff decreased by 35% after conversion to commercial forest and 6% after partial conversion to tea plantations. The predicted climate scenarios of reduced dry season rainfall decreased the annual runoff by 5% while enhanced annual rainfall caused a 17% increase in runoff. Even if land-use and climate changes had relatively large effects on runoff, the changes in reservoir yield which can be assured every year, were often less severe. This was probably due to the buffering effect of the reservoir and variation in the mean annual runoff.     

The effects of possible future climate change on evaporation losses from four contrasting UK water catchment areas

Evaporation losses from four water catchment areas under different land uses and climatic conditions were calculated using formulations developed from small plot studies. These formulations, dependent on rainfall inputs, potential evaporation and air temperature, were extrapolated to the catchment scale using land classifications based on analysing remotely sensed imagery. The approach adopted was verified by comparing the estimated annual evaporation losses with catchment water use, given by the difference between rainfall inputs and stream flow outputs, allowing for changes in soil moisture. This procedure was repeated using modified values of rainfall, potential evaporation and air temperature, as given by a climate change scenario. The computed evaporation losses were used in annual water balances to calculate stream flow losses under the climate change scenario. It was found that, in general, stream flow from areas receiving high rainfall would increase as a result of climate change. For low rainfall areas, a decrease in stream flow was predicted. The largest actual changes in stream flow were predicted to occur during the winter months, although the largest percentage changes will occur during the summer months. The implications of these changes on potable water supply are discussed. © 1998 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.     

Quantitative assessment of the impact of climate variability and human activities on runoff changes: a case study in four catchments of the Haihe River basin,China

Quantitative evaluation of the effect of climate variability and human activities on runoff is of great importance for water resources planning and management in terms of maintaining the ecosystem integrity and sustaining the society development. In this paper, hydro‐climatic data from four catchments (i.e. Luanhe River catchment, Chaohe River catchment, Hutuo River catchment and Zhanghe River catchment) in the Haihe River basin from 1957 to 2000 were used to quantitatively attribute the hydrological response (i.e. runoff) to climate change and human activities separately. To separate the attributes, the temporal trends of annual precipitation, potential evapotranspiration (PET) and runoff during 1957–2000 were first explored by the Mann–Kendall test. Despite that only Hutuo River catchment was dominated by a significant negative trend in annual precipitation, all four catchments presented significant negative trend in annual runoff varying from ?0.859 (Chaohe River) to ?1.996 mm a^?1 (Zhanghe River). Change points in 1977 and 1979 are detected by precipitation–runoff double cumulative curves method and Pettitt's test for Zhanghe River and the other three rivers, respectively, and are adopted to divide data set into two study periods as the pre‐change period and post‐change period. Three methods including hydrological model method, hydrological sensitivity analysis method and climate elasticity method were calibrated with the hydro‐climatic data during the pre‐change period. Then, hydrological runoff response to climate variability and human activities was quantitatively evaluated with the help of the three methods and based on the assumption that climate and human activities are the only drivers for streamflow and are independent of each other. Similar estimates of anthropogenic and climatic effects on runoff for catchments considered can be obtained from the three methods. We found that human activities were the main driving factors for the decline in annual runoff in Luanhe River catchment, Chaohe River catchment and Zhanghe River catchment, accounting for over 50% of runoff reduction. However, climate variability should be responsible for the decrease in annual runoff in the Hutuo River catchment. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

Impacts of climate change and human activities on surface runoff in the Dongjiang River basin of China

Observed rainfall and flow data from the Dongjiang River basin in humid southern China were used to investigate runoff changes during low‐flow and flooding periods and in annual flows over the past 45 years. We first applied the non‐parametric Mann–Kendall rank statistic method to analyze the change trend in precipitation, surface runoff and pan evaporation in those three periods. Findings showed that only the surface runoff in the low‐flow period increased significantly, which was due to a combination of increased precipitation and decreased pan evaporation. The Pettitt–Mann–Whitney statistical test results showed that 1973 and 1978 were the change points for the low‐flow period runoff in the Boluo sub‐catchment and in the Qilinzui sub‐catchment, respectively. Most importantly, we have developed a framework to separate the effects of climate change and human activities on the changes in surface runoff based on the back‐propagation artificial neural network (BP‐ANN) method from this research. Analyses from this study indicated that climate variabilities such as changes in precipitation and evaporation, and human activities such as reservoir operations, each accounted for about 50% of the runoff change in the low‐flow period in the study basin. Copyright © 2010 John Wiley & Sons, Ltd.     

The impact of climate change on runoff in the Yarlung Tsangpo River basin in the Tibetan Plateau

The Tibetan Plateau (TP) is the “water tower of Asia” and it plays a key role on both hydrology and climate for southern and eastern Asia. It is critical to explore the impact of climate change on runoff for better water resources management in the TP. However, few studies pay attention to the runoff response to climate change in large river systems on the TP, especially in data-sparse upstream area. To complement the current body of work, this study uses two rainfall-runoff models (SIMHYD and GR4J) to simulate the monthly and annual runoff in the upstream catchments of the Yarlung Tsangpo River basin (YTR) under historical (1962–2002) and future (2046–2065 A1B scenario) climate conditions. The future climate series are downscaled from a global climate model (MIROC3.2_hires) by a high resolution regional climate model (RegCM3). The two rainfall-runoff models successfully simulate the historical runoff for the eight catchments in the YTR basin, with median monthly runoff Nash–Sutcliffe Efficiency of 0.86 for SIMHYD and 0.83 for GR4J. The mean annual future temperature in eight catchments show significant increase with the median of +3.8 °C. However, the mean annual future precipitation shows decrease with the median of ?5.8 % except in Lhatse (+2.0 %). The two models show similar modeling results that the mean annual future runoff in most of catchments (seven in eight) shows decrease with the median of ?13.9 % from SIMHYD and ?15.2 % from GR4J. The results achieved in this study are not only helpful for local water resources management, but also for future water utilization planning in the lower reaches region of the Brahmaputra.     

Hydrological response of a medium-sized mountainous catchment to climate changes

Abstract

The long term hydrological response of a medium-sized mountainous catchment to climate changes has been examined, The climate changes were represented by a set of hypothetical scenarios of temperature increases coupled with precipitation and potential evapotranspiration changes. Snow accumulation and ablation, plus runoff from the study catchment (the Mesochora catchment in central Greece) were simulated under present (historical) and altered climate conditions using the US National Weather Service snowmelt and soil moisture accounting models. The results of this research obtained through alternative scenarios suggest strongly that all the hypothetical climate change scenarios would cause major decreases in winter snow accumulation and hence increases in winter runoff, as well as decreases in spring and summer runoff. The simulated changes in annual runoff were minor compared with the changes in the monthly distribution of runoff. Attendant changes in the monthly distribution of soil moisture and actual evapotranspiration would also occur. Such hydrological results would have significant implications on future water resources design and management.     

Parameter uncertainty of the AWBM model when applied to an ungauged catchment

In this study, a quantitative assessment of uncertainty was made in connection with the calibration of Australian Water Balance Model (AWBM) for both gauged and ungauged catchment cases. For the gauged catchment, five different rainfall data sets, 23 different calibration data lengths and eight different optimization techniques were adopted. For the ungauged catchment case, the optimum parameter sets obtained from the nearest gauged catchment were transposed to the ungauged catchments, and two regional prediction equations were used to estimate runoff. Uncertainties were ascertained by comparing the observed and modelled runoffs by the AWBM on the basis of different combinations of methods, model parameters and input data. The main finding from this study was that the uncertainties in the AWBM modelling outputs could vary from ?1.3% to 70% owing to different input rainfall data, ?5.7% to 11% owing to different calibration data lengths and ?6% to 0.2% owing to different optimization techniques adopted in the calibration of the AWBM. The performance of the AWBM model was found to be dominated mainly by the selection of appropriate rainfall data followed by the selection of an appropriate calibration data length and optimization algorithm. Use of relatively short data length (e.g. 3 to 6 years) in the calibration was found to generate relatively poor results. Effects of different optimization techniques on the calibration were found to be minimal. The uncertainties reported here in relation to the calibration and runoff estimation by the AWBM model are relevant to the selected study catchments, which are likely to differ for other catchments. The methodology presented in this paper can be applied to other catchments in Australia and other countries using AWBM and similar rainfall–runoff models. Copyright © 2014 John Wiley & Sons, Ltd.     

Estimation of rainfall elasticity of streamflow in Australia

Abstract

Estimates of rainfall elasticity of streamflow in 219 catchments across Australia are presented. The rainfall elasticity of streamflow is defined here as the proportional change in mean annual streamflow divided by the proportional change in mean annual rainfall. The elasticity is therefore a simple estimate of the sensitivity of long-term streamflow to changes in long-term rainfall, and is particularly useful as an initial estimate of climate change impact in land and water resources projects. The rainfall elasticity of streamflow is estimated here using a hydrological modelling approach and a nonparametric estimator. The results indicate that the rainfall elasticity of streamflow (? _P ) in Australia is about 2.0–3.5 (observed in about 70% of the catchments), that is, a 1% change in mean annual rainfall results in a 2.0–3.5% change in mean annual streamflow. The rainfall elasticity of streamflow is strongly correlated to runoff coefficient and mean annual rainfall and streamflow, where streamflow is more sensitive to rainfall in drier catchments, and those with low runoff coefficients. There is a clear relation-ship between the ? _P values estimated using the hydrological modelling approach and those estimated using the nonparametric estimator for the 219 catchments, although the values estimated by the hydrological modelling approach are, on average, slightly higher. The modelling approach is useful where a detailed study is required and where there are sufficient data to reliably develop and calibrate a hydrological model. The nonparametric estimator is useful where consistent estimates of the sensitivity of long-term streamflow to climate are required, because it is simple to use and estimates the elasticity directly from the historical data. The nonparametric method, being model independent, can also be easily applied in comparative studies to data sets from many catchments across large regions.     

The impact of climate change on groundwater recharge and runoff in a humid,equatorial catchment: sensitivity of projections to rainfall intensity

Abstract

Projected warming in equatorial Africa, accompanied by greater evaporation and more frequent heavy precipitation events, may have substantial but uncertain impacts on terrestrial hydrology. Quantitative analyses of climate change impacts on catchment hydrology require high-resolution (<50 km) climate data provided by regional climate models (RCMs). We apply validated precipitation and temperature data from the RCM PRECIS (Providing Regional Climates for Impact Studies) to a semi-distributed soil moisture balance model (SMBM) in order to quantify the impacts of climate change on groundwater recharge and runoff in a medium-sized catchment (2098 km²) in the humid tropics of southwestern Uganda. The SMBM explicitly accounts for changes in soil moisture, and partitions effective precipitation into groundwater recharge and runoff. Under the A2 emissions scenario (2070–2100), climate projections from PRECIS feature not only rises in catchment precipitation and modelled potential evapotranspiration by 14% and 53%, respectively, but also increases in rainfall intensity. We show that the common application of the historical rainfall distribution using delta factors to the SMBM grossly underestimates groundwater recharge (i.e. 55% decrease relative to the baseline period of 1961–1990). By transforming the rainfall distribution to account for changes in rainfall intensity, we project increases in recharge and runoff of 53% and 137%, respectively, relative to the baseline period.     

Hydrological impacts of climate change predicted for an inland lake catchment in Ontario by using monthly water balance analyses

Potential hydrological impacts of climate change on long‐term water balances were analysed for Harp Lake and its catchment. Harp Lake is located in the boreal ecozone of Ontario, Canada. Two climate change scenarios were used. One was based on extrapolation of long‐term trends of monthly temperature and precipitation from a 129‐year data record, and another was based on a Canadian general circulation model (GCM) predictions. A monthly water balance model was calibrated using 26 years of hydrological and meteorological data, and the model was used to calculate hydrological impact under two climate change scenarios. The first scenario with a warmer and wetter climate predicted a smaller magnitude of change than the second scenario. The first scenario showed an increase in evaporation each month, an increase in catchment runoff in summer, fall and winter, but a decrease in spring, resulting in a slight increase in lake level. Annual runoff and lake level would increase because the precipitation change overrides evaporation change. The second scenario with a warmer, drier climate predicted a greater change, and indicated that evaporation would increase each month, runoff would increase in many months, but would decrease in spring, causing the lake level to decrease slightly. Annual runoff and lake level would decrease because evaporation change overrides precipitation change. In both scenarios, the water balance changes in winter and spring are pronounced. Copyright © 2009 John Wiley & Sons, Ltd.     

GCM-related uncertainty in river flow projections at the threshold for “dangerous” climate change: the Kalu Ganga river,Sri Lanka

The Kalu Ganga catchment is one of the largest in Sri Lanka, and is home to 5% of the national population. A first assessment is provided here of the sensitivity of Kalu Ganga runoff to a 2°C increase in global mean temperature – the supposed threshold for “dangerous” climate change. Runoff is simulated using the HBV-Light hydrological model and scenario data from seven general circulation models (GCMs). Precipitation is the strongest cause of change in runoff. Substantial inter-GCM differences in scenario precipitation lead to uncertainty in the direction of change in mean annual runoff from the baseline (range ?25% to +19%). Scenario monthly runoff ranges from ?41% to +124% of the baseline values at its most extreme (March); June is the only month with a consistent direction of change (range ?17% to ?65%) – thus indicating that climate change may lead to a substantially different hydrological regime in the Kalu Ganga catchment.     

Variations in runoff,sediment load,and their relationship for a major sediment source area of the Jialing River basin,southern China

Investigation of the variations in runoff, sediment load, and their dynamic relation is conducive to understanding hydrological regime changes and supporting channel regulation and fluvial management. This study is undertaken in the Xihanshui catchment, which is known for its high sediment-laden in the Jialing River of the Yangtze River basin, southern China, to evaluate the change characteristics of runoff, sediment load, and their relationship at multi-temporal scales from 1966 to 2016. The results showed that runoff changed significantly for more months, whereas the significant changes in monthly sediment load occurred from April to September. The contributions of runoff in summer and autumn and sediment load in summer to their annual value changes were greater. Annual runoff and sediment load in the Xihanshui catchment both exhibited significant decreasing trends (p < 0.05) with a significant mutation in 1993 (p < 0.05). The average annual runoff in the change period (1994–2016) decreased by 49.58% and annual sediment load displayed a substantial decline with a reduction of 77.77% in comparison with the reference period (1966–1993) due to climate change and intensive human activity. The power functions were satisfactory to describe annual and extreme monthly runoff–sediment relationships, whereas the monthly runoff–sediment relationship and extreme monthly sediment-runoff relationship were changeable. Spatially, annual runoff–sediment relationship alteration could be partly attributed to sediment load changes in the upstream area and runoff variations in the downstream region. Three quantitative methods revealed that the main driver for significant reductions of annual runoff and sediment load is the human activity dominated by soil and water conservation measures, while climate change only contributed 22.73%–38.99% (mean 32.07%) to the total runoff reduction and 3.39%–35.56% (mean 17.32%) to the total decrease in sediment load.     

Hydrological response of a humid agroforestry catchment at different time scales

Using data collected at the Mero catchment during three hydrological years (2005/06–2007/08), an analysis of rainfall–runoff relationships was performed at annual, seasonal, monthly, and event scales. At annual scale, the catchment showed low runoff coefficients (23–35%), due to high water storage capacity soils as well as high runoff inter‐annual variability. Rainfall variability was the main responsible for the differences in the inter‐annual runoff. At seasonal and monthly scales, there was no simple relationship between rainfall and runoff. Seasonal dynamics of rainfall and potential evapotranspiration in conjunction with different rainfall distribution during the study years could be the key factors explaining the complex relationship between rainfall and runoff at monthly and seasonal scale. At the event scale, the results revealed that the hydrological response was highly dependent on initial conditions and, to a lesser extent, on rainfall amount. The shapes of the different hydrographs, regardless of the magnitude, presented similar characteristics: a moderate rise and a prolonged recession, suggesting that subsurface flow was the dominant process in direct runoff. Moreover, all rainfall–runoff events had a higher proportion of baseflow than of direct runoff. A cluster‐type analysis discriminated three types of events differentiated mainly by rainfall amount and antecedent rainfall conditions. The study highlights the role of the antecedent rainfall and the need for caution in extrapolating relationships between rainfall amount and hydrological response of the catchment. Copyright © 2013 John Wiley & Sons, Ltd.     

Runoff reduction due to environmental changes in the Sanchuanhe river basin

Recently, runoff in many river basins in China has been decreasing. Therefore, the role that climate change and human activities are playing in this decrease is currently of interest. In this study, we evaluated an assessment method that was designed to quantitatively separate the effects of climate change and human activities on runoff in river basins. Specifically, we calibrated the SIMHYD rainfall runoff model using naturally recorded hydro-meteorologic data pertaining to the Sanchuanhe River basin and then determined the effects of climate change and human activities on runoff by comparing the estimated natural runoff that occurred during the period in which humans disturbed the basin to the runoff that occurred during the period prior to disturbance by humans. The results of this study revealed that the S1MHYD rainfall runoff model performs well for estimating monthly discharge. In addition, we found that absolute runoff reductions have increased in response to human activities and climate change, with average reductions of 70.1% and 29.9% in total runoff being caused by human activities and climate change, respectively. Taken together, the results of this study indicate that human activities are the primary cause of runoff reduction in the Sanchuanhe River basin.     

Changes in potential evapotranspiration and surface runoff in 1981–2010 and the driving factors in Upper Heihe River Basin in Northwest China

Changes in potential evapotranspiration and surface runoff can have profound implications for hydrological processes in arid and semiarid regions. In this study, we investigated the response of hydrological processes to climate change in Upper Heihe River Basin in Northwest China for the period from 1981 to 2010. We used agronomic, climatic and hydrological data to drive the Soil and Water Assessment Tool model for changes in potential evapotranspiration (ET₀) and surface runoff and the driving factors in the study area. The results showed that increasing autumn temperature increased snow melt, resulting in increased surface runoff, especially in September and October. The spatial distribution of annual runoff was different from that of seasonal runoff, with the highest runoff in Yeniugou River, followed by Babaohe River and then the tributaries in the northern of the basin. There was no evaporation paradox at annual and seasonal time scales, and annual ET₀ was driven mainly by wind speed. ET₀ was driven by relative humidity in spring, sunshine hour duration in autumn and both sunshine hour duration and relative humility in summer. Surface runoff was controlled by temperature in spring and winter and by precipitation in summer (flood season). Although surface runoff increased in autumn with increasing temperature, it depended on rainfall in September and on temperature in October and November. Copyright © 2016 John Wiley & Sons, Ltd.