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The first part of this paper demonstrated the existence of bias in GCM-derived precipitation series, downscaled using either a statistical technique (here the Statistical Downscaling Model) or dynamical method (here high resolution Regional Climate Model HadRM3) propagating to river flow estimated by a lumped hydrological model. This paper uses the same models and methods for a future time horizon (2080s) and analyses how significant these projected changes are compared to baseline natural variability in four British catchments. The UKCIP02 scenarios, which are widely used in the UK for climate change impact, are also considered. Results show that GCMs are the largest source of uncertainty in future flows. Uncertainties from downscaling techniques and emission scenarios are of similar magnitude, and generally smaller than GCM uncertainty. For catchments where hydrological modelling uncertainty is smaller than GCM variability for baseline flow, this uncertainty can be ignored for future projections, but might be significant otherwise. Predicted changes are not always significant compared to baseline variability, less than 50% of projections suggesting a significant change in monthly flow. Insignificant changes could occur due to climate variability alone and thus cannot be attributed to climate change, but are often ignored in climate change studies and could lead to misleading conclusions. Existing systematic bias in reproducing current climate does impact future projections and must, therefore, be considered when interpreting results. Changes in river flow variability, important for water management planning, can be easily assessed from simple resampling techniques applied to both baseline and future time horizons. Assessing future climate and its potential implication for river flows is a key challenge facing water resource planners. This two-part paper demonstrates that uncertainty due to hydrological and climate modelling must and can be accounted for to provide sound, scientifically-based advice to decision makers. [ABSTRACT FROM AUTHOR]

In this paper we combined a multimodel ensemble based on 15 regional climate models with a multicatchment approach to explore the hydrologic sensitivity of 14 neighboring and rather similar catchments to changing climate conditions. Current (1982-2010) and future (2062-2090) streamflow was simulated with the HBV model. A diagnostic approach was used, which considered major behavioral catchment functions by using hydrologically relevant signatures related to overall water balance, flow duration curves and hydrograph attributes. Projected increases in temperature and precipitation resulted in increased total available streamflow, with lower spring and summer flows, but substantially higher winter streamflow. Furthermore, significant changes in flow durations with lower chances of both high and low flows can be expected in boreal Sweden in the future. This overall trend in projected streamflow pattern changes was comparable among the analyzed catchments but the magnitude of change differed considerably. This suggests that catchments belonging to the same region can show distinctly different degrees of hydrological responses to the same external climate change signal. We reason that differences in spatially distributed physical catchment properties within catchments are not only of great importance for current streamflow behavior, but also play a major role in the sensitivity of catchments to changing climate conditions. [ABSTRACT FROM AUTHOR]

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Land use/cover (LULC) and climate change are two main factors affecting watershed hydrology. In this paper, individual and combined impacts of LULC and climate change on hydrologic processes were analysed applying the model Soil and Water Assessment Tool in a coastal Alabama watershed in USA. Temporally and spatially downscaled Global Circulation Model outputs predict a slight increase in precipitation in the study area, which is also projected to experience substantial urban growth in the future. Changes in flow frequency and volume in the 2030s (2016-2040) compared to a baseline period (1984-2008) at daily, monthly and annual time scales were explored. A redistribution of daily streamflow is projected when either climate or LULC change was considered. High flows are predicted to increase, while low flows are expected to decrease. Combined change effect results in a more noticeable and uneven distribution of daily streamflow. Monthly average streamflow and surface runoff are projected to increase in spring and winter, but especially in fall. LULC change does not have a significant effect on monthly average streamflow, but the change affects partitioning of streamflow, causing higher surface runoff and lower baseflow. The combined effect leads to a dramatic increase in monthly average streamflow with a stronger increasing trend in surface runoff and decreasing trend in baseflow. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In an earlier global climate-change study, air temperature and precipitation data for the entire twenty-first century simulated from five general circulation models were used as input to precalibrated watershed models for 14 selected basins across the United States. Simulated daily streamflow and energy output from the watershed models were used to compute a range of statistics. With a side-by-side comparison of the statistical analyses for the 14 basins, regional climatic and hydrologic trends over the twenty-first century could be qualitatively identified. Low-flow statistics (95%% exceedance, 7-day mean annual minimum, and summer mean monthly streamflow) decreased for almost all basins. Annual maximum daily streamflow also decreased in all the basins, except for all four basins in California and the Pacific Northwest. An analysis of the supply of available energy and water for the basins indicated that ratios of evaporation to precipitation and potential evapotranspiration to precipitation for most of the basins will increase. Probability density functions (PDFs) were developed to assess the uncertainty and multimodality in the impact of climate change on mean annual streamflow variability. Kolmogorov--Smirnov tests showed significant differences between the beginning and ending twenty-first-century PDFs for most of the basins, with the exception of four basins that are located in the western United States. Almost none of the basin PDFs were normally distributed, and two basins in the upper Midwest had PDFs that were extremely dispersed and skewed. [ABSTRACT FROM AUTHOR]

It is now common knowledge that many water resources stresses relate to access to water within a basin. Yi River Basin, a typical river basin characterized by intensive agricultural processes, significant population growth, and water management, has been undergoing grave water problems. In this paper, the long-term trend of precipitation and streamflow in Yi River Basin, from 1964 to 2010, was investigated via Mann-Kendall test. The change point occurred in the year 1965 dividing the long-term series into two periods. Climate elasticity method and linear regression method were implemented to quantify the impact of precipitation and human activities on runoff and presented basically consistent results of the percentage change in an annual runoff for the postchange period. The results reveal that the decline of annual runoff in postchange period is mainly attributed to precipitation variability of 53.66–58.25% and human activities of 46.34–41.74%, as estimated by climate elasticity method and linear regression method, respectively. This study detected the changes in the precipitation-streamflow relationship and investigated the possible causes in the Yi River, which will be helpful for providing a reference for the management of regional water resources. [ABSTRACT FROM AUTHOR]

Summary This paper presents an assessment of the effects of climate change on river flow regimes in representative English catchments, using the UKCP09 climate projections. These comprise a set of 10,000 coherent climate scenarios, used here (i) to evaluate the distribution of potential changes in hydrological behaviour and (ii) to construct relationships between indicators of climate change and hydrological change. The study uses six catchments, and focuses on change in average flow, high flow (Q5) and low flow (Q95). There is a large range in hydrological change in each catchment between the plausible UKCP09 climate projections, with differences between catchments largely due to differences in catchment geology and baseline water balance. The range in change between the UKCP09 projections is in most catchments smaller than the range between changes with scenarios based on the CMIP3 ensemble of climate models (although the shape of the distribution of changes is different), and earlier UK scenarios produce changes that tend towards the lower (drier) end of the UKCP09 range. The difference between emissions scenarios is small compared to the range across the 10,000 scenarios. Changes in high flows are largely driven by changes in winter precipitation, whilst changes in low flows are determined by changes in summer precipitation and temperature. [ABSTRACT FROM AUTHOR]

Summary Spatial variability of climate can negatively affect catchment streamflow predictions if it is not explicitly accounted for in hydrologic models. In this paper, we examine the changes in streamflow predictability when a hydrologic model is run with spatially variable (distributed) meteorological inputs instead of spatially uniform (lumped) meteorological inputs. Both lumped and distributed versions of the EXP-HYDRO model are implemented at 41 meso-scale (500–5000 km 2 ) catchments in the Pacific Northwest region of USA. We use two complementary metrics of long-term spatial climate variability, moisture homogeneity index ( I M ) and temperature variability index ( I TV ), to analyze the performance improvement with distributed model. Results show that the distributed model performs better than the lumped model in 38 out of 41 catchments, and noticeably better (>10% improvement) in 13 catchments. Furthermore, spatial variability of moisture distribution alone is insufficient to explain the observed patterns of model performance improvement. For catchments with low moisture homogeneity ( I M < 80%), I M is a better predictor of model performance improvement than I TV ; whereas for catchments with high moisture homogeneity ( I M > 80%), I TV is a better predictor of performance improvement than I M . Based on the results, we conclude that: (1) catchments that have low homogeneity of moisture distribution are the obvious candidates for using spatially distributed meteorological inputs, and (2) catchments with a homogeneous moisture distribution benefit from spatially distributed meteorological inputs if they also have high spatial variability of precipitation phase (rain vs. snow). [ABSTRACT FROM AUTHOR]

Projecting future changes of streamflow in the Jinsha River Basin (JRB) is important for the planning and management of the west route of South-to-North Water Transfer Project (SNWTP). This paper presented an analysis of the implications of CMIP5 climate models on the future streamflow in the JRB, using SWAT model. Results show that: (1) In the JRB, a 10% precipitation decrease might result in a streamflow increase of 15 to 18% and a 1 °C increase in temperature might results in a 2 to 5% decrease in streamflow; (2) GFDL-ESM2M and NORESM1-M showed considerable skill in representing the observed precipitation and temperature, which can be chosen to analyze the changes in streamflow in the future; (3) The precipitation and temperature were projected to increase by 0.8 to 5.0% and 1.31 to 1.87 °C. The streamflow was projected to decrease by 4.1 to 14.3% in the upper JRB. It was excepted to change by −4.6 to 8.1% in the middle and lower JRB (MLJRB). The changes of low streamflow in the MLJRB were −5.8 to 7.4%. Therefore, the potential impact of climate on streamflow will have little effect on the planning and management of the west route of SNWTP. [ABSTRACT FROM AUTHOR]

Hydrological processes depend directly on climate conditions [e.g., precipitation, potential evapotranspiration ( PE)] based on the water balance. This paper examines streamflow datasets at four hydrological stations and meteorological observations at 79 weather stations to reveal the streamflow changes and underlying drivers in four typical watersheds (Meigang, Saitang, Gaosha, and Xiashan) within Poyang Lake Basin from 1961 to 2000. Most of the less than 90th percentile of daily streamflow in each watershed increases significantly at different rates. As an important indicator of the seasonal changes in the streamflow, CT (the timing of the mass center of the streamflow) in each watershed shows a negligible change. The annual streamflow in each watershed increases at different rates, with a statistically significant trend (at the 5 % level) of 9.87 and 7.72 mm year, respectively, in Meigang and Gaosha watersheds. Given the existence of interactions between precipitation and PE, the original climate elasticity of streamflow can not reflect the relationship of streamflow with precipitation and PE effectively. We modify this method and find the modified climate elasticity to be more accurate and reasonable using the correlation analysis. The analyses from the modified climate elasticity in the four watersheds show that a 10 % increase (decrease) in precipitation will increase (decrease) the annual streamflow by 14.1-16.3 %, while a 10 % increase (decrease) in PE will decrease (increase) the annual streamflow by −10.2 to −2.1 %. In addition, the modified climate elasticity is applied to estimate the contribution of annual precipitation and PE to the increasing annual streamflow in each watershed over the past 40 years. Our result suggests that the percentage attribution of the increasing precipitation is more than 59 % and the decreasing in PE is less than 41 %, indicating that the increasing precipitation is the major driving factor for the annual streamflow increase for each watershed. [ABSTRACT FROM AUTHOR]

Summary: In this paper we proposed: (1) an algorithm of glacier melt, sublimation/evaporation, accumulation, mass balance and retreat; (2) a dynamic Hydrological Response Unit approach for incorporating the algorithm into the Soil and Water Assessment Tool (SWAT) model; and (3) simulated the transient glacier retreat and its impacts on streamflow at basin scale. Application of the enhanced SWAT model in the Manas River Basin (MRB) in the Tianshan Mountains in northwest China, shows that the approach is viable as evidenced by a Nash–Sutcliff efficiency of 0.65 and a percent bias of −3.7% for daily streamflow and water balance, respectively. The results indicate that the glacier area decreased by 11% during the simulation period from 1961 to 1999, which is within the range of records from other glaciers. On average, glacier melt contributed 25% to streamflow, although glacier area accounts for only 14% of the catchment drainage area in the MRB. Glacier melt was positively correlated to temperature change (R 2 =0.70, statistical significance P <0.001) and negatively correlated to precipitation (R 2 =0.20, statistical significance P <0.005). The results indicate that glacier melt was more sensitive to temperature change than to precipitation change, implying that modeling the effects of climate change with increasing temperatures and decreasing precipitation should be further studied. [ABSTRACT FROM AUTHOR]

Abstract: Global climate change has tremendously altered the spatial and temporal distributions of precipitation. The Streamflow of the Yellow River decreased in the past decades, both because of human consumption and climate variations. This paper analyzed the trends of natural and observed streamflow of the Lijin hydrological station, as well as the precipitation and air temperature of the whole Yellow River Basin. There was an obvious change in the natural streamflow in 1991 when analyzed by the Mann-Kendall (M-K) method. Precipitation decreased in the whole Yellow River Basin. 22 Meteorological stations have slight increases, while the other 67 stations measured declines, in which 47 of the Meteorological stations’ decrements were over 5%. There was a descent of temperature for only 2 stations, while the temperature rose for the other 87 stations. The average temperature increment was 0.82°C and the highest was 1.91°C in Tsinghai Center station. The quantitative Streamflow-precipitation-temperature relations plot was drawn by Geostatistical Analyst module of ArcGIS 9.3. The streamflow have various responses to the different extents of precipitation and air temperature. In the past four decades, precipitation elasticity to streamflow was 1.95, and the elasticity index may give a general relationship between precipitation and streamflow. However, it varies with different scenarios. [Copyright &y& Elsevier]

Both climate change and human activities are known to have induced changes to hydrology. Consequently, quantifying the net impact of human contribution to the streamfiow change is a challenge. In this paper, a decomposition method based on the Budyko hypothesis is used to quantify the climate (i.e., precipitation and potential evaporation change) and direct human impact on mean annual streamflow (MAS) for 413 watersheds in the contiguous United States. The data for annual precipitation, runoff, and potential evaporation are obtained from the international Model Parameter Estimation Experiment (MOPEX), which is often assumed to only include gauges unaffected by human interferences. The data are split into two periods (1948-1970 and 1971-2003) to quantify the change over time. Although climate is found to affect MAS more than direct human impact, the results show that assuming the MOPEX data set to be unaffected by human activities is far from realistic. Climate change causes increasing MAS in most watersheds, while the direct human-induced change is spatially heterogeneous in the contiguous United States, with strong regional patterns, e.g., human activities causing increased MAS in the Midwest and significantly decreased MAS in the High Plains. The climate- and human-induced changes are found to be more severe in arid regions, where water is limited. Comparing the results to a collection of independent data sets indicates that the estimated direct human impacts on MAS in this largely nonurban set of watersheds might be attributed to several human activities, such as cropland expansion, irrigation, and the construction of reservoirs. [ABSTRACT FROM AUTHOR]

It is unambiguous that climate change alters the intensity and frequency of precipitation and temperature distribution at the global and local levels. The rate of change in temperature in the northern latitudes is higher than the worldwide average. The annual distribution of precipitation over the Himalayas in the northern latitudes shows substantial spatial and temporal heterogeneity. Precipitation and temperature are the major driving factors that impact the streamflow and water availability in the basin, illustrating the importance of research on the impact of climate change on streamflow by varying the precipitation and temperature in the Thuli Bheri River Basin (TBRB). Multiple climate models were used to project and evaluate the precipitation and temperature distribution changes in temporal and spatial domains. To analyze the potential impact of climate change on the streamflow in the basin, the Soil and Water Assessment Tool (SWAT) hydrological model was used. The climate projection was carried out in three future time windows. The result shows that the precipitation fluctuates between approximately +12% and +50%, the maximum temperature varies between [ABSTRACT FROM AUTHOR]

In this study, the Providing Regional Climates for Impacts Studies (PRECIS) and the Regional Climate Model (RegCM) system as well as the Variable Infiltration Capacity (VIC) macroscale hydrologic model were integrated into a general framework to investigate impacts of future climates on the hydrologic regime of the Athabasca River basin. Regional climate models (RCMs) including PRECIS and RegCM were used to develop ensemble high-resolution climate projections for 1979–2099. RCMs were driven by the boundary conditions from the Hadley Centre Global Environment Model, version 2 with Earth system configurations (HadGEM2-ES); the Second Generation Canadian Earth System Model (CanESM2); and the Geophysical Fluid Dynamics Laboratory Earth System Model with MOM (GFDL-ESM2M) under the representative concentration pathways (RCPs). The ensemble climate simulations were validated through comparison with observations for 1984–2003. The RCMs project increases in temperature, precipitation, and wind speed under RCPs across most of the Athabasca River basin. Meanwhile, VIC was calibrated using the University of Arizona Shuffled Complex Evolution method (SCE-UA). The performance of the VIC model in replicating the characteristics of the observed streamflow was validated for 1994–2003. Changes in runoff and streamflow under RCPs were then simulated by the validated VIC model. The validation results demonstrate that the ensemble-RCM-driven VIC model can effectively reproduce historical climatological and hydrological patterns in the Athabasca River basin. The ensemble-RCM-driven VIC model shows that monthly streamflow is projected to increase in the 2050s and 2080s under RCPs, with notably higher flows expected in the spring for the 2080s. This will have substantial impacts on water balance on the Athabasca River basin, thus affecting the surrounding industry and ecosystems. The developed framework can be applied to other regions for exploration of hydrologic impacts under climate change. [ABSTRACT FROM AUTHOR]

As climate change is projected to alter both temperature and precipitation, snow-controlled mid-latitude catchments are expected to experience substantial shifts in their seasonal regime, which will have direct implications for water management. In order to provide authoritative projections of climate change impacts, the uncertainty inherent to all components of the modelling chain needs to be accounted for. This study assesses the uncertainty in potential impacts of climate change on the hydro-climate of a headwater sub-catchment of New Zealand's largest catchment (the Clutha River) using a fully distributed hydrological model (WaSiM) and unique ensemble encompassing different uncertainty sources: general circulation model (GCM), emission scenario, bias correction and snow model. The inclusion of snow models is particularly important, given that (1) they are a rarely considered aspect of uncertainty in hydrological modelling studies, and (2) snow has a considerable influence on seasonal patterns of river flow in alpine catchments such as the Clutha. Projected changes in river flow for the 2050s and 2090s encompass substantial increases in stream-flow from May to October, and a decline between December and March. The dominant drivers are changes in the seasonal distribution of precipitation (for the 2090s C29 to C84% in winter) and substantial decreases in the seasonal snow storage due to temperature increase. A quantitative comparison of uncertainty identified GCM structure as the dominant contributor in the seasonal streamflow signal (44-57 %) followed by emission scenario (16-49 %), bias correction (4-22 %) and snow model (3-10 %). While these findings suggest that the role of the snow model is comparatively small, its contribution to the overall uncertainty was still found to be noticeable for winter and summer. [ABSTRACT FROM AUTHOR]

A slight variation in the magnitude of stream flow can have a substantial influence on the development of water resources. The Songhua River Basin (SRB) serves as a major grain commodity basin and is located in the northeastern region of China. Recent studies have identified a gradual decrease in stream flows, which presents a serious risk to water resources of the region. It is therefore necessary to assess the variation in stream flow and to predict the future of stream flows and droughts to make a comprehensive plan for agricultural irrigation. The simulation of monthly stream flows and the investigation of the influence of climate on the stream flow in the SRB were performed by utilizing the Integrated Water Evaluation and Planning (WEAP) tool coupled with observed precipitation data, as well as the Asian Precipitation-Highly-Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE’s Water Resources) precipitation product. The Nash-Sutcliffe coefficient (NSC) was used to assess the WEAP efficiency. During the time of calibration, NSC was obtained as 0.90 and 0.67 using observed and APHRODITE precipitation data, respectively. The results indicate that WEAP can be used effectively in the SRB. The application of the model suggested a maximum decline in stream flow, reaching 24% until the end of 21st century under future climate change scenarios. The drought indices (standardized drought index and percent of normal index) demonstrated that chances of severe to extreme drought events are highest in 2059, 2060 and 2085, while in the remaining time period mild to moderate drought events may occur in the entire study area. The drought duration, severity and intensity for the period of 2011-2099 under all scenarios, [(A1B: 12, − 1.55, − 0.12), (A2: 12, − 1.41, − 0.09), (max. wetting and warming conditions: 12, − 1.37, − 0.11) and (min. wetting and warming conditions: 12, − 1.69, − 0.19)], respectively. [ABSTRACT FROM AUTHOR]

Climate change has become an important issue for scientific community, for its numerous impacts, especially on agriculture and environment. To shed light on this phenomenon, long data-sets of meteorological data as well as temperature and rainfall extreme events are needed, since they are important climate variability indicators. In a small semi-agricultural catchment of the Italian Apennines, drained by the Centonara Stream, weather data have been monitored for 30 years (1986-2015). Here, their trend was identified with Mann-Kendall test, and the temperature and precipitation extremes were characterized by means of specific indices. Data were analyzed at event, daily, seasonal, and annual bases. In addition, to understand implications of rainfall patterns on catchment hydrological response, a total of 388 rainfall-streamflow events (recorded during 1994-2009) were analyzed. Results showed a significant increase of temperature (minimum (Tn), mean (Tm), and maximum (Tx)), both at annual and seasonal base, except for Winter, with an annual mean increase of 0.08, 0.09, and 0.13 °C year for Tn, Tm, and Tx, respectively. Annual rainfall data showed a positive trend for the number of wet days, but not in the quantity. In Winter, the rainfall amount and the number of wet days increased. The annual number of rainfall extreme events ( P > 20.2 mm and D > 18.3 h) significantly increased, especially in spring and autumn. The rainfall-streamflow relationship suggested that the flow response of the Centonara Stream depends mainly on the rainfall amount. So, since the number of extreme events ( P > 20.2 mm) is increasing in spring and autumn, an increase of events with high streamflow in these seasons may occur. [ABSTRACT FROM AUTHOR]

Snowmelt run-off model (SRM) based on degree-day approach has been employed to evaluate the change in snow-cover depletion and corresponding streamflow under different projected climatic scenarios for an eastern Himalayan catchment in India. Nuranang catchment located at Tawang district of Arunachal Pradesh with an area of 52 km is selected for the present study with an elevation range of 3143-4946 m above mean sea level. Satellite images from October to June of the selected hydrological year 2006-2007 were procured from National Remote Sensing Centre, Hyderabad. Snow cover mapping is done using NDSI method. Based on long term meteorological data, temperature and precipitation data of selected hydrological year are normalized to represent present climatic condition. The projected temperature and precipitation data are downloaded from NCAR's GIS data portal for different emission scenarios (SRES), viz., A1B, A2, B1; and IPCC commitment (non-SRES) scenario for different future years (2020, 2030, 2040 and 2050). Projected temperature and precipitation data are obtained at desired location by spatially interpolating the gridded data and then by statistical downscaling using linear regression. Snow depletion curves for all projected scenarios are generated for the study area and compared with conventional depletion curve for present climatic condition. Changes in cumulative snowmelt depth for different future years are highest under A1B and lowest under IPCC commitment, whereas A2 and B1 values are in-between A1B and IPCC commitment. Percentage increase in streamflow for different future years follows almost the same trend as change in precipitation from present climate under all projected climatic scenarios. Hence, it was concluded that for small catchments having seasonal snow cover, the total streamflow under projected climatic scenarios in future years will be primarily governed by the change in precipitation and not by change in snowmelt depth. Advancing of depletion curves for different future years are highest under A1B and lowest under IPCC commitment. A2 and B1 values are in-between A1B and IPCC commitment. [ABSTRACT FROM AUTHOR]

Six global climate models (GCMs) from Coupled Model Intercomparison Project Phase 5 under three Respectively Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5) were used to assess the impact of climate change on streamflow for the Huangnizhuang catchment (HNZ) in China. Change factor method was used for bias correction between GCM outputs and observations and the SWAT model was used to simulate the hydrological processes. The results indicated that the SWAT model performed well in the study catchment with a monthly Nash-Sutcliffe efficiency (NS) of 0.93 and 0.91 and daily NS of 0.63 and 0.68 for calibration and validation periods respectively. Their corresponding relative errors were −2.2 and 8.9, and −2.6 and 8.5 % respectively. The ensemble of multi-GCMs projected an increase of precipitation in the middle and end of twenty-first century over the HNZ, ranging from −2.4 to 9 %. However, streamflow is likely to decline in the future, ranging −6.9 to 0.8 %, mainly due to an increase of evapotranspiration in a warming world, as air temperature shows steadily increases for all the GCMs and RCPs. Average monthly streamflow from six GCMs are likely to increase in August and September but decline from October to June. The associated uncertainties of the reported results were also discussed. It includes, but is not limit to, different GCMs, emissions scenarios, downscaling techniques as well as hydrological simulations. The results of this study can inform planning of long-term basin water management strategies taking into account global change scenarios. [ABSTRACT FROM AUTHOR]

Evaluation of water balance at the watershed scale is a fundamental step for estimating streamflow in watersheds. Mean annual water balance of 17 watersheds across Michigan were evaluated by comparing observed streamflow with simulated streamflow estimated using Fu's Equation, which is based on the Budyko Hypothesis. The Budyko Hypothesis describes mean annual water balance as a function of available water and energy. Impact of long-term climatic controls (e.g., precipitation, potential evapotranspiration (ETP)) on mean annual water balance was also investigated with Fu's Equation. Results indicated that observed streamflow ranged from 237 to 529 mm per year, with an average of 363 mm per year in the study watersheds during 1967-2011. On average, 40% of long-term precipitation in the study watersheds was converted into surface runoff. The performance of Fu's Equation in estimating mean annual streamflow resulted in Root Mean Square Error (RMSE) value of 64.1 mm/year. Mean annual streamflow was sensitive to changes in mean annual precipitation, and less sensitive to changes in mean annual ETp in the watersheds. With the increase of baseflow index (BFI), mean annual streamflow was less sensitive to climate change. Overall, different contributions of baseflow to streamflow modified the impact of climate controls on mean annual water balance in the baseflow-dominated watersheds. [ABSTRACT FROM AUTHOR]

Individual impacts of climate change, land use/coverage change, the regulation of water reservoir and water use to intra-annual distribution of streamflow of the Dongjiang River basin, South China, are quantitatively separated. Data on precipitation, streamflow, regulation of water reservoirs, and water use are used in the analysis. Changes in the concentration degree and non-uniformity coefficient of intra-annual distribution of streamflow over time scales from daily to monthly are evaluated. Trend and change point analyses are applied to determine characteristics of intra-annual distribution of streamflow. By comparison with the difference among region precipitation, naturalized streamflow and observed streamflow, the contribution of main impact factors to the intra-annual distribution of streamflow are quantified. Results demonstrate the non-uniformity coefficient decreases with a negative logarithmic linear function of the time scale. Change points of the concentration degree and non-uniformity coefficient occurred in 1973 exhibited a significant downward trend. In the period posterior to the change point the former and the latter decrease approximately by 15-34 % and by 29-40 %, respectively. The decrease in concentration degree and non-uniformity coefficient is due to the regulation of water reservoirs and land use/cover change; while the increase is the result of water use and climate change. The individual contributions to the impact on the intra-annual distribution of streamflow from regulation of water reservoirs, land use/cover change, water use, and climate change are approximately −33.5, −9.0, 4.5 and 1.0 %. It is observed that the impacts of the regulations of the Xinfengjiang, Fengshuba, and Baipenzhu reservoirs account for −21, −10, and −2 %, respectively. There is an increasing tendency in the impacts of land use/cover change and water use in the past 30 years. [ABSTRACT FROM AUTHOR]

Warming will affect snowline elevation, potentially altering the timing and magnitude of streamflow from mountain landscapes. Presently, the assessment of potential elevation-dependent responses is difficult because many gauged watersheds integrate drainage areas that are both snow and rain dominated. To predict the impact of snowline rise on streamflow, we mapped the current snowline (1980 m) for the Salmon River watershed (Idaho, USA) and projected its elevation after 3 °C warming (2440 m). This increase results in a 40% reduction in snow-covered area during winter months. We expand this analysis by collecting streamflow records from a new, elevation-stratified gauging network of watersheds contained within high (2250-3800 m), mid (1500-2250 m) and low (300-1500 m) elevations that isolate snow, mixed and rain-dominated precipitation regimes. Results indicate that lags between percentiles of precipitation and streamflow are much shorter in low elevations than in mid- and high-elevation watersheds. Low elevation annual percentiles (Q25 and Q75) of streamflow occur 30-50 days earlier than in higher elevation watersheds. Extreme events in low elevations are dominated by low- and no-flow events whereas mid- and high-elevation extreme events are primarily large magnitude floods. Only mid- and high-elevation watersheds are strongly cross correlated with catchment-wide flow of the Salmon River, suggesting that changes in contributions from low-elevation catchments may be poorly represented using mainstem gauges. As snowline rises, mid-elevation watersheds will likely exhibit behaviours currently observed only at lower elevations. Streamflow monitoring networks designed for operational decision making or change detection may require modification to capture elevation-dependent responses of streamflow to warming. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We present an assessment of climate change impacts on the hydrologic regime of the 600,000 km Upper Paraguay River basin, located in central South America based on predictions of 20 Atmospheric/Ocean General Circulation Models (AOGCMs). We considered two climate change scenarios from the Intergovernmental Panel on Climate Change (IPCC) and two 30-years time intervals centered at 2030 and 2070. Projected temperature and precipitation anomalies estimated by the AOGCMs for the study site are spatially downscaled. Time series of projected temperature and precipitation were estimated using the delta change approach. These time series were used as input to a detailed coupled hydrologic-hydraulic model aiming to estimate projected streamflow in climate change scenarios at several control points in the basin. Results show that impacts on streamflow are highly dependent on the AOGCM used to obtain the climate predictions. Patterns of temperature increase persist over the entire year for almost all AOGCMs resulting in an increase in the evapotranspiration rate of the hydrological model. The precipitation anomalies show large dispersion, being projected as either an increase or decrease in precipitation rates. Based on these inputs, results from the coupled hydrologic-hydraulic model show nearly one half of projections as increasing river discharge, and other half as decreasing river discharge. If the mean or median of the predictions is considered, no discernible change in river discharge should be expected, despite the dispersion among results of the AOGCMs that reached +/−10 % in the short horizon and +/− 20 % in the long horizon, at several control points. [ABSTRACT FROM AUTHOR]

Climate change, particularly the projected changes to precipitation patterns, is likely to affect runoff both regionally and temporally. Extreme rainfall events are expected to become more intense in the future in arid urban areas and this will likely lead to higher streamflow. Through hydrological modeling, this article simulates an urban basin response to the most intense storm under anthropogenic climate change conditions. This study performs an event-based simulation for shorter duration storms in the Flamingo Tropicana (FT) watershed in Las Vegas, Nevada. An extreme storm, defined as a 100-year return period storm, is selected from historical records and perturbed to future climatic conditions with respect to multimodel multiscenario (A1B, A2, B1) bias corrected and spatially disaggregated data from the World Climate Research Programme's (WCRP's) database. The cumulative annual precipitation for each 30-year period shows a continuous decrease from 2011 to 2099; however, the summer convective storms, which are considered as extreme storms for the study area, are expected to be more intense in future. Extreme storm events show larger changes in streamflow under different climate scenarios and time periods. The simulated peak streamflow and total runoff volume shows an increase from 40% to more than 150% (during 2041-2099) for different climate scenarios. This type of analysis can help evaluate the vulnerability of existing flood control system and flood control policies. [ABSTRACT FROM AUTHOR]

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Hydrological modeling for climate-change impact assessment implies using meteorological variables simulated by global climate models (GCMs). Due to mismatching scales, coarse-resolution GCM output cannot be used directly for hydrological impact studies but rather needs to be downscaled. In this study, we investigated the variability of seasonal streamflow and flood-peak projections caused by the use of three statistical approaches to downscale precipitation from two GCMs for a meso-scale catchment in southeastern Sweden: (1) an analog method (AM), (2) a multi-objective fuzzy-rule-based classification (MOFRBC) and (3) the Statistical DownScaling Model (SDSM). The obtained higher-resolution precipitation values were then used to simulate daily streamflow for a control period (1961-1990) and for two future emission scenarios (2071-2100) with the precipitation-streamflow model HBV. The choice of downscaled precipitation time series had a major impact on the streamflow simulations, which was directly related to the ability of the downscaling approaches to reproduce observed precipitation. Although SDSM was considered to be most suitable for downscaling precipitation in the studied river basin, we highlighted the importance of an ensemble approach. The climate and streamflow change signals indicated that the current flow regime with a snowmelt-driven spring flood in April will likely change to a flow regime that is rather dominated by large winter streamflows. Spring flood events are expected to decrease considerably and occur earlier, whereas autumn flood peaks are projected to increase slightly. The simulations demonstrated that projections of future streamflow regimes are highly variable and can even partly point towards different directions. [ABSTRACT FROM AUTHOR]

This study investigates the low-frequency components of observed monthly river flow from a large number of small catchments in Europe. The low-frequency components, defined as fluctuations on time scales longer than one year, were analysed both with respect to their dominant space-time patterns as well as their contribution to the variance of monthly runoff. The analysis of observed streamflow and corresponding time series of precipitation and temperature, showed that the fraction of low-frequency variance of runoff is on average larger than, and not correlated to, the fraction of lowfrequency variance of precipitation and temperature. However, it is correlated with mean climatic conditions and is on average lowest in catchments with significant influence of snow. Furthermore, it increases (decreases) under drier (wetter) conditions -- indicating that the average degree of catchment wetness may be a primary control of low-frequency runoff dynamics. The fraction of low-frequency variance of runoff is consistently lower in responsive catchments, with a high variability of daily runoff. The dominant space-time patterns of low-frequency runoff in Europe, identified using nonlinear dimension reduction, revealed that low-frequency runoff can be described with three modes, explaining together 80.6% of the variance. The dominant mode has opposing centres of simultaneous variations in northern and southern Europe. The secondary mode features a west-east pattern and the third mode has its centre of influence in central Europe. All modes are closely related to the space-time patterns extracted from time series of precipitation and temperature. In summary, it is shown that the dynamics of low-frequency runoff follows well known continental-scale atmospheric features, whereas the proportion of variance attributed to low-frequency fluctuations is controlled by catchment processes and varies with mean climatic conditions. The results may have implications for interpreting the impact of changes in temperature and precipitation on river-flow dynamics. [ABSTRACT FROM AUTHOR]

Under the background of global climate change, hydrological responses to climate change were investigated in Northeastern China. This study analyses the trends of annual and seasonal temperature, precipitation and streamflow series in Nenjiang River Basin. Correlations between streamflow and meteorological variables were investigated, while parametric method and nonparametric tests were applied to determine the trends and correlations. Data collected from a series of monitoring stations showed significant increasing trends of annual and seasonal mean temperature versus time, whereas during the whole period the annual and seasonal precipitation in the basin did not exhibit similar trends although temporal and spatial variations were detected. Affected by the precipitation and temperature changes, significant trends of decreasing annual, spring and autumn streamflow were demonstrated; the decrease concentrating mainly on the mainstream and tributaries of the left bank. Correlation analyses revealed strong relationships between the streamflow and meteorological variables in Nenjiang River Basin, and the impacts of climate change on streamflow were complicated. Results from this study will help water resource managers for decision makings that address the consequences of climate change. [ABSTRACT FROM AUTHOR]

Extreme hydro-meteorological events have become the focus of more and more studies in the last decade. Due to the complexity of the spatial pattern of changes in precipitation processes, it is still hard to establish a clear view of how precipitation has changed and how it will change in the future. In the present study, changes in extreme precipitation and streamflow processes in the Dongjiang River Basin in southern China are investigated with several nonparametric methods, including one method (Mann-Kendall test) for detecting trend, and three methods (Kolmogorov-Smirnov test, Levene's test and quantile test) for detecting changes in probability distribution. It was shown that little change is observed in annual extreme precipitation in terms of various indices, but some significant changes are found in the precipitation processes on a monthly basis, which indicates that when detecting climate changes, besides annual indices, seasonal variations in extreme events should be considered as well. Despite of little change in annual extreme precipitation series, significant changes are detected in several annual extreme flood flow and low-flow series, mainly at the stations along the main channel of Dongjiang River, which are affected significantly by the operation of several major reservoirs. To assess the reliability of the results, the power of three non-parametric methods are assessed by Monte Carlo simulation. The simulation results show that, while all three methods work well for detecting changes in two groups of data with large sample size (e.g., over 200 points in each group) and large differences in distribution parameters (e.g., over 100% increase of scale parameter in Gamma distribution), none of them are powerful enough for small data sets (e.g., less than 100 points) and small distribution parameter difference (e.g., 50% increase of scale parameter in Gamma distribution). The result of the present study raises the concern of the robustness of statistical change-detection methods, shows the necessity of combined use of different methods including both exploratory and quantitative statistical methods, and emphasizes the need of physically sound explanation when applying statistical test methods for detecting changes. [ABSTRACT FROM AUTHOR]

This study develops and implements a methodology to estimate the impacts of global climate change on regional hydrological regimes using ArcGIS Geostatistical Analyst. The model is easily used and can be expanded to different watersheds. The ArcGIS Geostatistical Analyst interface provides a comprehensive set of tools for creating surfaces from measured sample points compared with the previous method of using adjustable tension continuous curvature surface gridding. As a result, users can rapidly compare different interpolation techniques in order to obtain the best solution. Model results can subsequently be used in GIS models for visualization and analyses. The methodology was applied to the Spokane River Watershed. Results indicate that a 30% precipitation increase causes a 50% increase of streamflow when the temperature is normal compared to only a 20–30% increase in streamflow if the average annual air temperature is 1.5°C higher than normal. Conversely, a 20% precipitation decrease results in approximately 25–30% less streamflow when the temperature is normal but a 45% decrease in streamflow if the temperature is 1.5°C higher than normal. These research results can be used as reference conditions for long-term watershed water management strategies under global warming scenarios. The precipitation elasticity of runoff is also investigated. The precipitation elasticity was found to be 1.67 although it varied with precipitation and temperature. [ABSTRACT FROM AUTHOR]

The soil and water assessment tool (SWAT) model was applied for the first time in Cuba to assess the potential impacts of climate change on water availability in the Cauto River basin. The model was calibrated (and validated) for the 2001–2006 (2007–2010) period at a monthly timescale in two subbasins La Fuente and Las Coloradas, representative of middle and upper sections of the Cauto basin; the calibrated models showed good performance. The output available for the regional climate Model RegCM4.3 was used to force the calibrated SWAT models to simulate a baseline (1970–2000) period and near-future (2015–2039) hydrologic regimes under the representative concentration pathway (RCP) 8.5 emission scenario. The future projections suggest regional increases of 1.5 °C in mean annual temperature and a 38% decrease in mean annual precipitation in the subbasins. These changes translate to possible reductions in the annual streamflow of up to 61% with respect to the baseline period, whereas the aquifer recharge in the basin is expected to decrease up to 58%, with a consequent reduction of groundwater flow, especially during the boreal summer wet season. These projection scenarios should be of interest to water resources managers in tropical regions. [ABSTRACT FROM AUTHOR]