Projected 21st century climate change on snow conditions over Shasta Dam watershed by means of dynamical downscaling

Snow is an important component of the Earth's climate system and is particularly vulnerable to global warming. It has been suggested that warmer temperatures may cause significant declines in snow water content and snow cover duration. In this study, snowfall and snowmelt were projected by means of a regional climate model that was coupled to a physically based snow model over Shasta Dam watershed to assess changes in snow water content and snow cover duration during the 21st century. This physically based snow model requires both physical data and future climate projections. These physical data include topography, soils, vegetation, and land use/land cover, which were collected from associated organizations. The future climate projections were dynamically downscaled by means of the regional climate model under 4 emission scenarios simulated by 2 general circulation models (fifth‐generation of the ECHAM general circulation model and the third‐generation atmospheric general circulation model). The downscaled future projections were bias corrected before projecting snowfall and snowmelt processes over Shasta Dam watershed during 2010–2099. This study's results agree with those of previous studies that projected snow water equivalent is decreasing by 50–80% whereas the fraction of precipitation falling as snowfall is decreasing by 15% to 20%. The obtained projection results show that future snow water content will change in both time and space. Furthermore, the results confirm that physical data such as topography, land cover, and atmospheric–hydrologic data are instrumental in the studies on the impact of climate change on the water resources of a region.     

Impact of climate change on diffuse pollutant fluxes at the watershed scale

This study aims to assess watershed‐scale impacts of changing climate on sediment, phosphorus, nitrogen and pesticide (atrazine) fluxes over the 21st century at the watershed scale. In particular, changes in dissolved and particulate forms of water quality constituents in response to climate change are investigated. The hydrologic model Soil and Water Assessment Tool was calibrated and evaluated in a primarily agricultural watershed in the Midwestern United States to simulate hydrologic and water quality processes on a daily basis over the 2015–2099 time horizon. The model was then driven with 112 distinct statistically downscaled climate projections representing Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) low, moderate and high greenhouse gas emission scenarios. Projected hydrologic and water quality responses were categorized according to the three IPCC SRES emission scenarios for summarizing and synthesizing results over early‐century (2015–2034), mid‐century (2045–2064) and late‐century (2080–2099) assessment. Results revealed clear warming trends in the study area, whereas small increases in precipitation were predicted. Streamflow, sediment and total nutrient loads did not differ noticeably between assessment periods. However, the proportion of dissolved to total nutrients increased significantly from early‐century to late‐century periods. With the exception of total atrazine in the mid‐century period, predicted pollutant loads for a given assessment period did not differ between emission pathways for a given assessment period. Changes in pollutant fluxes showed pronounced monthly variability. The projected increase in readily available forms of nutrients has important implications for the ecological health of water systems and management of drinking water supplies. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

Extreme value modelling of daily areal rainfall over Mediterranean catchments in a changing climate

Heavy rainfall events during the fall season are causing extended damages in Mediterranean catchments. A peaks‐over‐threshold model is developed for the extreme daily areal rainfall occurrence and magnitude in fall over six catchments in Southern France. The main driver of the heavy rainfall events observed in this region is the humidity flux (FHUM) from the Mediterranean Sea. Reanalysis data are used to compute the daily FHUM during the period 1958–2008, to be included as a covariate in the model parameters. Results indicate that the introduction of FHUM as a covariate can improve the modelling of extreme areal precipitation. The seasonal average of FHUM can improve the modelling of the seasonal occurrences of heavy rainfall events, whereas daily FHUM values can improve the modelling of the events magnitudes. In addition, an ensemble of simulations produced by five different general circulation models are considered to compute FHUM in future climate with the emission scenario A1B and hence to evaluate the effect of climate change on the heavy rainfall distribution in the selected catchments. This ensemble of climate models allows the evaluation of the uncertainties in climate projections. By comparison to the reference period 1960–1990, all models project an amplification of the mean seasonal FHUM from the Mediterranean Sea for the projection period 2070–2099, on average by +22%. This increase in FHUM leads to an increase in the number of heavy rainfall events, from an average of 2.55 events during the fall season in present climate to 3.57 events projected for the period 2070–2099. However, the projected changes have limited effects on the magnitude of extreme events, with only a 5% increase in the median of the 100‐year quantiles. Copyright © 2011 John Wiley & Sons, Ltd.     

Changes in Projected Spatial and Seasonal Groundwater Recharge in the Upper Colorado River Basin

The Colorado River is an important source of water in the western United States, supplying the needs of more than 38 million people in the United States and Mexico. Groundwater discharge to streams has been shown to be a critical component of streamflow in the Upper Colorado River Basin (UCRB), particularly during low‐flow periods. Understanding impacts on groundwater in the basin from projected climate change will assist water managers in the region in planning for potential changes in the river and groundwater system. A previous study on changes in basin‐wide groundwater recharge in the UCRB under projected climate change found substantial increases in temperature, moderate increases in precipitation, and mostly periods of stable or slight increases in simulated groundwater recharge through 2099. This study quantifies projected spatial and seasonal changes in groundwater recharge within the UCRB from recent historical (1950 to 2015) through future (2016 to 2099) time periods, using a distributed‐parameter groundwater recharge model with downscaled climate data from 97 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate projections. Simulation results indicate that projected increases in basin‐wide recharge of up to 15% are not distributed uniformly within the basin or throughout the year. Northernmost subregions within the UCRB are projected an increase in groundwater recharge, while recharge in other mainly southern subregions will decline. Seasonal changes in recharge also are projected within the UCRB, with decreases of 50% or more in summer months and increases of 50% or more in winter months for all subregions, and increases of 10% or more in spring months for many subregions.     

Effects of mid‐twenty‐first century climate and land cover change on the hydrology of the Puget Sound basin,Washington

The distributed hydrology–soil–vegetation model (DHSVM) was used to study the potential impacts of projected future land cover and climate change on the hydrology of the Puget Sound basin, Washington, in the mid‐twenty‐first century. A 60‐year climate model output, archived for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), was statistically downscaled and used as input to DHSVM. From the DHSVM output, we extracted multi‐decadal averages of seasonal streamflow, annual maximum flow, snow water equivalent (SWE), and evapotranspiration centred around 2030 and 2050. Future land cover was represented by a 2027 projection, which was extended to 2050, and DHSVM was run (with current climate) for these future land cover projections. In general, the climate change signal alone on sub‐basin streamflow was evidenced primarily through changes in the timing of winter and spring runoff, and slight increases in the annual runoff. Runoff changes in the uplands were attributable both to climate (increased winter precipitation, less snow) and land cover change (mostly reduced vegetation maturity). The most climatically sensitive parts of the uplands were in areas where the current winter precipitation is in the rain–snow transition zone. Changes in land cover were generally more important than climate change in the lowlands, where a substantial change to more urbanized land use and increased runoff was predicted. Both the annual total and seasonal distribution of freshwater flux to Puget Sound are more sensitive to climate change impacts than to land cover change, primarily because most of the runoff originates in the uplands. Both climate and land cover change slightly increase the annual freshwater flux to Puget Sound. Changes in the seasonal distribution of freshwater flux are mostly related to climate change, and consist of double‐digit increases in winter flows and decreases in summer and fall flows. Copyright © 2010 John Wiley & Sons, Ltd.     

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.     

Climate variability,snow, and physiographic controls on storm hydrographs in small forested basins,western Cascades,Oregon

Large floods are often attributed to the melting of snow during a rain event. This study tested how climate variability, snowpack presence, and basin physiography were related to storm hydrograph shape in three small (<1 km²) basins with old‐growth forest in western Oregon. Relationships between hydrograph characteristics and precipitation were tested for approximately 800 storms over a nearly 30‐year period. Analyses controlled for (1) snowpack presence/absence, (2) antecedent soil moisture, and (3) hillslope length and gradient. For small storms (<150 mm precipitation), controlling for precipitation, the presence of a snowpack on near‐saturated soil increased the threshold of precipitation before hydrograph rise, extended the start lag, centroid lag, and duration of storm hydrographs, and increased the peak discharge. The presence of a snowpack on near‐saturated soil sped up and steepened storm hydrographs in a basin with short steep slopes, but delayed storm hydrographs in basins with longer or more gentle slopes. Hydrographs of the largest events, which were extreme regional rain and rain‐on‐snow floods, were not sensitive to landform characteristics or snowpack presence/absence. Although the presence of a snowpack did not increase peak discharge in small, forested basins during large storms, it had contrasting effects on storm timing in small basins, potentially synchronizing small basin contributions to the larger basin hydrograph during large rain‐on‐snow events. By altering the relative timing of hydrographs, snowpack melting could produce extreme floods from precipitation events whose size is not extreme. Further work is needed to examine effects of canopy openings, snowpack, and climate warming on extreme rain‐on‐snow floods at the large basin scale. Copyright © 2008 John Wiley & Sons, Ltd.     

Potentially modified hydropower production under climate change in the Italian Alps

We present an assessment of the potential impacts of climate change on hydropower production within a paradigmatic, very highly exploited cryospheric area of upper Valtellina valley in the Italian Alps. Based on dependable and unique hydrological measures from our high‐altitude hydrometric network Idrostelvio during 2006–2015, we set up the Poly‐Hydro model to mimic the cryospheric processes driving hydrological flow formation in this high‐altitude area. We then set up an optimization tool, which we call Poly‐Power, to maximize the revenue of the plant manager under given hydrological regimes, namely, by proper operation of the hydroelectric production scheme (reservoirs, pipelines, and power plants) of the area. We then pursue hydrological projections until 2100, feeding Poly‐Hydro with the downscaled outputs of three general circulation models from the Intergovernmental Panel on Climate Change Fifth Assessment Report, under the scenarios Representative Concentration Pathway (RCP) 2.6, RCP 4.5, and RCP 8.5. We assess hydrological flows in two reference decades, that is, at half century (2040–2049), and end of century (2090–2099). We then feed the so obtained hydrological scenarios as inputs to Poly‐Power, and we project future production of hydroelectric power, with and without reoperation of the system. The average annual stream flows for hydropower production decreases along the century under our scenarios (?21 to +7%, on average ? 5% at half century; ?17 to ?2%, average ? 8%, end of century), with ice cover melting unable to offset such decrease. Reduction in snowfall and increase in liquid rainfall are the main factors affecting the modified hydrological regime. Energy production (and revenues) at half century may increase under our scenarios (?9 to +15%, +3% on average). At the end of century in spite of a projected increase on average (?7 to +6%, +1% on average), under the warmest scenario RCP 8.5 decrease of energy production is consistently projected (?4% on average). Our results provide an array of potential scenarios of modified hydropower production under future climate change and may be used for brain storming of adaptation strategies.     

Climate change analysis on historical watershed‐scale precipitation by means of long‐term dynamical downscaling

A methodology based on long‐term dynamical downscaling to analyse climate change effects on watershed‐scale precipitation during a historical period is proposed in this study. The reliability and applicability of the methodology were investigated based on the long‐term dynamical downscaling results. For an application of the proposed methodology, two study watersheds in Northern California were selected: the Upper Feather River watershed and the Yuba River watershed. Then, precipitation was reconstructed at 3‐km spatial resolution and hourly intervals over the study watersheds for 141 water years from 1 October 1871 to 30 September 2012 by dynamically downscaling a long‐term atmospheric reanalysis dataset, 20th century global reanalysis version 2 by means of a regional climate model. The reconstructed precipitation was compared against observed precipitation, in order to assess the applicability of the proposed methodology for the reconstruction of watershed‐scale precipitation and to validate this methodology. The validation shows that the reconstructed precipitation is in good agreement with observation data. Moreover, the differences between the reconstructed precipitation and the corresponding observations do not significantly change through the historical period. After the validation, climate change analysis was conducted based on the reconstructed precipitation. Through this analysis, it was found that basin‐average precipitation has increased significantly over both of the study watersheds during the historical period. An upward trend in monthly basin‐average precipitation is not significant in wet months except February while it is significant in dry months of the year. Furthermore, peak values of basin‐average precipitation are also on an upward trend over the study watersheds. The upward trend in peak basin‐average precipitation is more significant during a shorter duration. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

Extreme precipitation time trends in Ontario, 1960–2010

The impact of climate change on the behaviour of intensity–duration–frequency curves is critical to the estimation of design storms, and thus to the safe design of drainage infrastructure. The present study develops a regional time trend methodology that detects the impact of climate change on extreme precipitation from 1960 to 2010. The regional time trend linear regression method is fitted to different durations of annual maximum precipitation intensities derived from multiple sites in Ontario, Canada. The results show the relationship between climate change and increased extreme precipitation in this province. The regional trend analysis demonstrates, under nonstationary conditions arising from climate change, that the intensity of extreme precipitation increased decennially between 1.25% for the 30‐min storm and 1.82% for the 24‐h storm. A comparison of the results with a regional Mann–Kendall test validates the found regional time‐trend results. The results are employed to extrapolate the intensity–duration–frequency curves temporally and spatially for future decades across the province. The results of the regional time trend assessment help with the establishment of new safety margins for infrastructure design in Ontario. Copyright © 2016 John Wiley & Sons, Ltd.     

Identifying threshold storm events and quantifying potential impacts of climate change on sediment yield in a small upland agricultural watershed of Ontario

Agricultural zones are significant sediment sources, but it is crucial to identify critical source areas (CSAs) of sediment yield within these zones where best management practices (BMPs) can be applied to the best effect in reducing sediment delivery to receiving water bodies rather than the economically nonviable alternative of randomly or sweepingly implementing BMPs. A storm event of a specific magnitude and hyetograph profile may, at different times, generate a greater or lesser sediment yield. The widely used agricultural nonpoint source (AGNPS) model was used to identify CSAs for sediment losses in Southwestern Ontario's agriculture‐dominated 374‐ha Holtby watershed. A storm threshold approach was adopted to identify critical periods for higher sediment losses. An AGNPS model for the Holtby watershed was set up, calibrated, and validated for run‐off volume, peak flow rate, and sediment yield for several storms. The calibrated and validated model was run for storms of increasing return periods to identify threshold storm events that would generate sediment yield greater than an acceptable value for early and late spring, summer, and fall seasons. Finally, to evaluate the potential impacts of climate change, we shifted shorter duration summer storms into spring conditions and quantified the changes in sediment yield dynamics. A 6‐hr, 7.5‐year early spring storm would generate sediment losses exceeding the acceptable limit of 0.34 t ha^?1 for the season. However, summer storms (2 hr, up to 100 years) tended to generate sediment yields below those of an identifiable threshold storm. If such shorter duration summer storms occurred in spring, the sediment yield would increase by more than fivefold. A 5‐year future storm would generate an equivalent effect of a 100‐year current spring event. The high sediment delivery to be expected will have significant implications regarding the future management of water quality of receiving waters. Appropriate placement of BMPs at CSAs will thus be needed to reduce such high sediment delivery to receiving waters.     

Impacts of climate change in three hydrologic regimes in British Columbia,Canada

Hydrologic modelling has been applied to assess the impacts of projected climate change within three study areas in the Peace, Campbell and Columbia River watersheds of British Columbia, Canada. These study areas include interior nival (two sites) and coastal hybrid nival–pluvial (one site) hydro‐climatic regimes. Projections were based on a suite of eight global climate models driven by three emission scenarios to project potential climate responses for the 2050s period (2041–2070). Climate projections were statistically downscaled and used to drive a macro‐scale hydrology model at high spatial resolution. This methodology covers a large range of potential future climates for British Columbia and explicitly addresses both emissions and global climate model uncertainty in the final hydrologic projections. Snow water equivalent is projected to decline throughout the Peace and Campbell and at low elevations within the Columbia. At high elevations within the Columbia, snow water equivalent is projected to increase with increased winter precipitation. Streamflow projections indicate timing shifts in all three watersheds, predominantly because of changes in the dynamics of snow accumulation and melt. The coastal hybrid site shows the largest sensitivity, shifting to more rainfall‐dominated system by mid‐century. The two interior sites are projected to retain the characteristics of a nival regime by mid‐century, although streamflow‐timing shifts result from increased mid‐winter rainfall and snowmelt, and earlier freshet onset. Copyright © 2012 John Wiley & Sons, Ltd.     

Statistical downscaling of extreme daily precipitation,evaporation, and temperature and construction of future scenarios

Generally, the statistical downscaling approaches work less perfectly in reproducing precipitation than temperatures, particularly for the extreme precipitation. This article aimed to testify the capability in downscaling the extreme temperature, evaporation, and precipitation in South China using the statistical downscaling method. Meanwhile, the linkages between the underlying driving forces and the incompetent skills in downscaling precipitation extremes over South China need to be extensively addressed. Toward this end, a statistical downscaling model (SDSM) was built up to construct future scenarios of extreme daily temperature, pan evaporation, and precipitation. The model was thereafter applied to project climate extremes in the Dongjiang River basin in the 21st century from the HadCM3 (Hadley Centre Coupled Model version 3) model under A2 and B2 emission scenarios. The results showed that: (1) The SDSM generally performed fairly well in reproducing the extreme temperature. For the extreme precipitation, the performance of the model was less satisfactory than temperature and evaporation. (2) Both A2 and B2 scenarios projected increases in temperature extremes in all seasons; however, the projections of change in precipitation and evaporation extremes were not consistent with temperature extremes. (3) Skills of SDSM to reproduce the extreme precipitation were very limited. This was partly due to the high randomicity and nonlinearity dominated in extreme precipitation process over the Dongjiang River basin. In pre‐flood seasons (April to June), the mixing of the dry and cold air originated from northern China and the moist warm air releases excessive rainstorms to this basin, while in post‐flood seasons (July to October), the intensive rainstorms are triggered by the tropical system dominated in South China. These unique characteristics collectively account for the incompetent skills of SDSM in reproducing precipitation extremes in South China. Copyright © 2011 John Wiley & Sons, Ltd.     

Climate change and North Sea storm surge extremes: an ensemble study of storm surge extremes expected in a changed climate projected by four different regional climate models

The coastal zones are facing the prospect of changing storm surge statistics due to anthropogenic climate change. In the present study, we examine these prospects for the North Sea based on numerical modelling. The main tool is the barotropic tide-surge model TRIMGEO (Tidal Residual and Intertidal Mudflat Model) to derive storm surge climate and extremes from atmospheric conditions. The analysis is carried out by using an ensemble of four 30-year atmospheric regional simulations under present-day and possible future-enhanced greenhouse gas conditions. The atmospheric regional simulations were prepared within the EU project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). The research strategy of PRUDENCE is to compare simulations of different regional models driven by the same global control and climate change simulations. These global conditions, representative for 1961–1990 and 2071–2100 were prepared by the Hadley Center based on the IPCC A2 SRES scenario. The results suggest that under future climatic conditions, storm surge extremes may increase along the North Sea coast towards the end of this century. Based on a comparison between the results of the different ensemble members as well as on the variability estimated from a high-resolution storm surge reconstruction of the recent decades it is found that this increase is significantly different from zero at the 95% confidence level for most of the North Sea coast. An exception represents the East coast of the UK which is not affected by this increase of storm surge extremes.     

Assessment of climate change impacts on the hydrology of the Peruvian Amazon–Andes basin

In this article, we propose an investigation of the modifications of the hydrological response of two Peruvian Amazonas–Andes basins in relationship with the modifications of the precipitation and evapotranspiration rates inferred by the IPCC. These two basins integrate around 10% of the total area of the Amazonian basin. These estimations are based on the application of two monthly hydrological models, GR2M and MWB3, and the climatic projections come from BCM2, CSMK3 and MIHR models for A1B and B1 emission scenarios (SCE A1B and SCE B1). Projections are approximated by two simple scenarios (anomalies and horizon) and annual rainfall rates, evapotranspiration rates and discharge were estimated for the 2020s (2008–2040), 2050s (2041–2070) and 2080s (2071–2099). Annual discharge shows increasing trend over Requena basin (Ucayali river), Puerto Inca basin (Pachitea river), Tambo basin (Tambo river) and Mejorada basin (Mantaro river) while discharge shows decreasing trend over the Chazuta basin (Huallaga river), the Maldonadillo basin (Urubamba river) and the Pisac basin (Vilcanota river). Monthly discharge at the outlet of Puerto Inca, Tambo and Mejorada basins shows increasing trends for all seasons. Trends to decrease are estimated in autumn discharge over the Requena basin and spring discharge over Pisac basin as well as summer and autumn discharges over both the Chazuta and the Maldonadillo basins. Copyright © 2011 John Wiley & Sons, Ltd.     

Impact of projected climate change on the hydrology in the headwaters of the Yellow River basin

Located in the northeast of the Tibetan Plateau, the headwaters of the Yellow River basin (HYRB) are very vulnerable to climate change. In this study, we used the Soil and Water Assessment Tool (SWAT) model to assess the impact of future climate change on this region's hydrological components for the near future period of 2013–2042 under three emission scenarios A1B, A2 and B1. The uncertainty in this evaluation was considered by employing Bayesian model averaging approach on global climate model (GCM) multimodel ensemble projections. First, we evaluated the capability of the SWAT model for streamflow simulation in this basin. Second, the GCMs' monthly ensemble projections were downscaled to daily climate data using the bias‐correction and spatial‐disaggregation method and then were utilized as input into the SWAT model. The results indicate the following: (1) The SWAT model exhibits a good performance for both calibration and validation periods after adjusting parameters in snowmelt module and establishing elevation bands in sub‐basins. (2) The projected precipitation suggests a general increase under all three scenarios, with a larger extent in both A1B and B1 and a slight variation for A2. With regard to temperature, all scenarios show pronounced warming trends, of which A2 displays the largest amplitude. (3) In the terms of total runoff from the whole basin, there is an increasing trend in the future streamflow at Tangnaihai gauge under A1B and B1, while the A2 scenario is characterized by a declining trend. Spatially, A1B and B1 scenarios demonstrate increasing trends across most of the region. Groundwater and surface runoffs indicate similar trends with total runoff, whereas all three scenarios exhibit an increase in actual evapotranspiration. Generally, both A1B and B1 scenarios suggest a warmer and wetter tendency over the HYRB in the forthcoming decades, while the case for A2 indicates a warmer and drier trend. Findings from this study can provide beneficial reference to water resource and eco‐environment management strategies for governmental policymakers. Copyright © 2015 John Wiley & Sons, Ltd.     

Robust inferences on climate change patterns of precipitation extremes in the Iberian Peninsula

This work presents a methodology to make statistical significant and robust inferences on climate change from an ensemble of model simulations. This methodology is used to assess climate change projections of the Iberian daily-total precipitation for a near-future (2021–2050) and a distant-future (2069–2098) climates, relatively to a reference past climate (1961–1990).Climate changes of precipitation spatial patterns are estimated for annual and seasonal values of: (i) total amount of precipitation (PRCTOT), (ii) maximum number of consecutive dry days (CDD), (iii) maximum of total amount of 5-consecutive wet days (Rx5day), and (iv) percentage of total precipitation occurred in days with precipitation above the 95th percentile of the reference climate (R95T). Daily-total data were obtained from the multi-model ensemble of fifteen Regional Climate Model simulations provided by the European project ENSEMBLES. These regional models were driven by boundary conditions imposed by Global Climate Models that ran under the 20C3M conditions from 1961 to 2000, and under the A1B scenario, from 2001 to 2100, defined by the Special Report on Emission Scenarios of the Intergovernmental Panel on Climate Change.Non-parametric statistical methods are used for significant climate change detection: linear trends for the entire period (1961–2098) estimated by the Theil-Sen method with a statistical significance given by the Mann-Kendall test, and climate-median differences between the two future climates and the past climate with a statistical significance given by the Mann-Whitney test. Significant inferences of climate change spatial patterns are made after these non-parametric statistics of the multi-model ensemble median, while the associated uncertainties are quantified by the spread of these statistics across the multi-model ensemble. Significant and robust climate change inferences of the spatial patterns are then obtained by building the climate change patterns using only the grid points where a significant climate change is found with a predefined low uncertainty.Results highlight the importance of taking into account the spread across an ensemble of climate simulations when making inferences on climate change from the ensemble-mean or ensemble-median. This is specially true for climate projections of extreme indices such CDD and R95T. For PRCTOT, a decrease in annual precipitation over the entire peninsula is projected, specially in the north and northwest where it can decrease down to 400 mm by the middle of the 21st century. This decrease is expected to occur throughout the year except in winter. Annual CDD is projected to increase till the middle of the 21st century overall the peninsula, reaching more than three weeks in the southwest. This increase is projected to occur in summer and spring. For Rx5day, a decrease is projected to occur during spring and autumn in the major part of the peninsula, and during summer in northern Iberia. Finally, R95T is projected to decrease around 20% in northern Iberia in summer, and around 15% in the south-southwest in autumn.     

Estimation of future precipitation change in the Yangtze River basin by using statistical downscaling method

In this study, the applicability of the statistical downscaling model (SDSM) in downscaling precipitation in the Yangtze River basin, China was investigated. The investigation includes the calibration of the SDSM model by using large-scale atmospheric variables encompassing NCEP/NCAR reanalysis data, the validation of the model using independent period of the NCEP/NCAR reanalysis data and the general circulation model (GCM) outputs of scenarios A2 and B2 of the HadCM3 model, and the prediction of the future regional precipitation scenarios. Selected as climate variables for downscaling were measured daily precipitation data (1961–2000) from 136 weather stations in the Yangtze River basin. The results showed that: (1) there existed good relationship between the observed and simulated precipitation during the calibration period of 1961–1990 as well as the validation period of 1991–2000. And the results of simulated monthly and seasonal precipitation were better than that of daily. The average R ² values between the simulated and observed monthly and seasonal precipitation for the validation period were 0.78 and 0.91 respectively for the whole basin, which showed that the SDSM had a good applicability on simulating precipitation in the Yangtze River basin. (2) Under both scenarios A2 and B2, during the prediction period of 2010–2099, the change of annual mean precipitation in the Yangtze River basin would present a trend of deficit precipitation in 2020s; insignificant changes in the 2050s; and a surplus of precipitation in the 2080s as compared to the mean values of the base period. The annual mean precipitation would increase by about 15.29% under scenario A2 and increase by about 5.33% under scenario B2 in the 2080s. The winter and autumn might be the more distinct seasons with more predicted changes of precipitation than in other seasons. And (3) there would be distinctive spatial distribution differences for the change of annual mean precipitation in the river basin, but the most of Yangtze River basin would be dominated by the increasing trend.