气候变化对淮河蒙洼蓄滞洪区启用风险影响评估

基于RCP情景下47个IPCC CMIP5气候模式模拟数据和大尺度水文模型VIC,预估了未来（2021-2050年）气候变化对淮河蒙洼蓄滞洪区启用的可能影响。结果表明：与基准期（1971-2000年）相比,多模式预估淮河上游未来多年平均气温一致呈增加趋势,平均增幅范围0.2～1.7℃。不同模式对降水预估差异较大,但有超过70%的模式预估降水呈增加趋势,平均增幅为3.4%～4.1%。未来气候情景下,王家坝断面洪水总体呈增加趋势,20年一遇的洪水强度平均增幅19%,洪水频率将增大,蒙洼蓄滞洪区启用可能更加频繁,启用的风险加大。     

The impacts of climate change on river flood risk at the global scale

This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5?×?0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km² of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km² of cropland, and the change in risk varies between ?9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application.     

Snowpack and runoff response to climate change in Owens Valley and Mono Lake watersheds

Precipitation from the Eastern Sierra Nevada watersheds of Owens Lake and Mono Lake is one of the main water sources for Los Angeles’ over 4 million people, and plays a major role in the ecology of Mono Lake and of these watersheds. We use the Variable Infiltration Capacity (VIC) hydrologic model at daily time scale, forced by climate projections from 16 global climate models under greenhouse gas emissions scenarios B1 and A2, to evaluate likely hydrologic responses in these watersheds for 1950–2099. Comparing climate in the latter half of the 20th Century to projections for 2070–2099, we find that all projections indicate continued temperature increases, by 2–5 °C, but differ on precipitation changes, ranging from ?24 % to +56 %. As a result, the fraction of precipitation falling as rain is projected to increase, from a historical 0.19 to a range of 0.26–0.52 (depending on the GCM and emission scenario), leading to earlier timing of the annual hydrograph’s center, by a range of 9–37 days. Snowpack accumulation depends on temperature and even more strongly on precipitation due to the high elevation of these watersheds (reaching 4,000 m), and projected changes for April 1 snow water equivalent range from ?67 % to +9 %. We characterize the watershed’s hydrologic response using variables integrated in space over the entire simulated area and aggregated in time over 30-year periods. We show that from the complex dynamics acting at fine time scales (seasonal and sub-seasonal) simple dynamics emerge at this multi-year time scale. Of particular interest are the dynamic effects of temperature. Warming anticipates hydrograph timing, by raising the fraction of precipitation falling as rain, reducing the volume of snowmelt, and initiating snowmelt earlier. This timing shift results in the depletion of soil moisture in summer, when potential evapotranspiration is highest. Summer evapotranspiration losses are limited by soil moisture availability, and as a result the watershed’s water balance at the annual and longer scales is insensitive to warming. Mean annual runoff changes at base-of-mountain stations are thus strongly determined by precipitation changes.     

气候变化对水文季节性迁移的影响：以水库汛期分期和极值降水为例

气候变化影响下水利工程的可靠设计和安全运行是广大决策者、研究者和公众共同关注的热点问题。以清江流域为研究对象,首先采用模糊集合分析法对不同温室气体排放情景(A2、A1B和B1)下的逐日降水资料进行汛期分期,再通过广义极值分布(GEV)函数对各分期的极值降水序列进行频率分析。结果表明,降水季节性迁移直接影响汛期分期;3种排放情景下未来各时段(2011—2030年、2046—2065年和2080—2099年)的主汛期较基准期均推迟且有缩短趋势。对于极值降水量级,未来情景下明显小于基准期,且这种差距随着重现期的增大而增大;主汛期明显大于前汛期和后汛期,且在时段之间的差异明显大于排放情景之间的差异。     

Creating regional climate change scenarios over southern South America for the 2020’s and 2050’s using the pattern scaling technique: validity and limitations

Dynamical downscaling of global climate simulations is the most adequate tool to generate regional projections of climate change. This technique involves at least a present climate simulation and a simulation of a future scenario, usually at the end of the twenty first century. However, regional projections for a variety of scenarios and periods, the 2020s or the 2050s, are often required by the impact community. The pattern scaling technique is used to estimate information on climate change for periods and scenarios not simulated by the regional model. We based our study on regional simulations performed over southern South America for present climate conditions and two emission scenarios at the end of the twenty first century. We used the pattern scaling technique to estimate mean seasonal changes of temperature and precipitation for the 2020s and the 2050s. The validity of the scalability assumptions underlying the pattern scaling technique for estimating near future regional climate change scenarios over southern South America is assessed. The results show that the pattern scaling works well for estimating mean temperature changes for which the regional changes are linearly related to the global mean temperature changes. For precipitation changes, the validity of the scalability assumption is weaker. The errors of estimating precipitation changes are comparable to those inherent to the regional model and to the projected changes themselves.     

淮河流域水文极值预测模型研究

为探索气候变化影响下水文极值的非平稳性和预测方法,建立了水文极值非平稳广义极值（GEV）分布的统计预测模型。利用1952-2010年淮河上游流域累计面雨量和流量年最大值资料、同期500 hPa环流特征量资料以及17个CMIP5模式对环流特征量的模拟结果,筛选出对水文极值影响显著的年平均北半球极涡强度指数作为GEV分布参数的预测因子。分析了在RCP2.6、RCP4.5和RCP8.5情景下2006-2050年淮河上游流域水文极值对气候变化的响应。结果表明,10年以下与10年以上重现期的水文极值在非平稳过程中呈现前者下降而后者上升的相反变化趋势;多模型预测的集合平均在未来情景中均呈现上升趋势,情景排放量越大增幅越大,重现期越长增幅也越大。与极值的常态相比,极值的极端态更易受气候变化影响。     

全球增暖背景下2050年前长江流域气候趋势预估

根据ECHAM5/ MPI-OM模式对长江流域21世纪前半叶气候变化的预估数据,分析了全流域、上游地区和中下游地区未来气候变化趋势。结果表明,长江流域气温将持续升高,尤其7-8月升温趋势明显,年平均温度升高最大幅度为2.60℃;全流域7月降水将增加,8月降水有减少趋势,未来夏季降水更加集中,不仅会增加洪涝灾害的发生机率,也有可能导致旱灾的发生。     

A copula-based multivariate analysis of Canadian RCM projected changes to flood characteristics for northeastern Canada

In the present work, climate change impacts on three spring (March–June) flood characteristics, i.e. peak, volume and duration, for 21 northeast Canadian basins are evaluated, based on Canadian regional climate model (CRCM) simulations. Conventional univariate frequency analysis for each flood characteristic and copula based bivariate frequency analysis for mutually correlated pairs of flood characteristics (i.e. peak–volume, peak–duration and volume–duration) are carried out. While univariate analysis is focused on return levels of selected return periods (5-, 20- and 50-year), the bivariate analysis is focused on the joint occurrence probabilities P1 and P2 of the three pairs of flood characteristics, where P1 is the probability of any one characteristic in a pair exceeding its threshold and P2 is the probability of both characteristics in a pair exceeding their respective thresholds at the same time. The performance of CRCM is assessed by comparing ERA40 (the European Centre for Medium-Range Weather Forecasts 40-year reanalysis) driven CRCM simulated flood statistics and univariate and bivariate frequency analysis results for the current 1970–1999 period with those observed at selected 16 gauging stations for the same time period. The Generalized Extreme Value distribution is selected as the marginal distribution for flood characteristics and the Clayton copula for developing bivariate distribution functions. The CRCM performs well in simulating mean, standard deviation, and 5-, 20- and 50-year return levels of flood characteristics. The joint occurrence probabilities are also simulated well by the CRCM. A five-member ensemble of the CRCM simulated streamflow for the current (1970–1999) and future (2041–2070) periods, driven by five different members of a Canadian Global Climate Model ensemble, are used in the assessment of projected changes, where future simulations correspond to A2 scenario. The results of projected changes, in general, indicate increases in the marginal values, i.e. return levels of flood characteristics, and the joint occurrence probabilities P1 and P2. It is found that the future marginal values of flood characteristics and P1 and P2 values corresponding to longer return periods will be affected more by anthropogenic climate change than those corresponding to shorter return periods but the former ones are subjected to higher uncertainties.     

Projections of climate change impacts on river flood conditions in Germany by combining three different RCMs with a regional eco-hydrological model

A general increase in precipitation has been observed in Germany in the last century, and potential changes in flood generation and intensity are now at the focus of interest. The aim of the paper is twofold: a) to project the future flood conditions in Germany accounting for various river regimes (from pluvial to nival-pluvial regimes) and under different climate scenarios (the high, A2, low, B1, and medium, A1B, emission scenarios) and b) to investigate sources of uncertainty generated by climate input data and regional climate models. Data of two dynamical Regional Climate Models (RCMs), REMO (REgional Model) and CCLM (Cosmo-Climate Local Model), and one statistical-empirical RCM, Wettreg (Wetterlagenbasierte Regionalisierungsmethode: weather-type based regionalization method), were applied to drive the eco-hydrological model SWIM (Soil and Water Integrated Model), which was previously validated for 15 gauges in Germany. At most of the gauges, the 95 and 99 percentiles of the simulated discharge using SWIM with observed climate data had a good agreement with the observed discharge for 1961–2000 (deviation within ±10 %). However, the simulated discharge had a bias when using RCM climate as input for the same period. Generalized Extreme Value (GEV) distributions were fitted to the annual maximum series of river runoff for each realization for the control and scenario periods, and the changes in flood generation over the whole simulation time were analyzed. The 50-year flood values estimated for two scenario periods (2021–2060, 2061–2100) were compared to the ones derived from the control period using the same climate models. The results driven by the statistical-empirical model show a declining trend in the flood level for most rivers, and under all climate scenarios. The simulations driven by dynamical models give various change directions depending on region, scenario and time period. The uncertainty in estimating high flows and, in particular, extreme floods remains high, due to differences in regional climate models, emission scenarios and multi-realizations generated by RCMs.     

A megacity in a changing climate: the case of Kolkata

Projections by the Intergovernmental Panel on Climate Change suggest that there will be an increase in the frequency and intensity of climate extremes in the 21st century. Kolkata, a megacity in India, has been singled out as one of the urban centers vulnerable to climate risks. Modest flooding during monsoons at high tide in the Hooghly River is a recurring hazard in Kolkata. More intense rainfall, riverine flooding, sea level rise, and coastal storm surges in a changing climate can lead to widespread and severe flooding and bring the city to a standstill for several days. Using rainfall data, high and low emissions scenarios, and sea level rise of 27 cm by 2050, this paper assesses the vulnerability of Kolkata to increasingly intense precipitation events for return periods of 30, 50, and 100 years. It makes location-specific inundation depth and duration projections using hydrological, hydraulic, and urban storm models with geographic overlays. High resolution spatial analysis provides a roadmap for designing adaptation schemes to minimize the impacts of climate change. The modeling results show that de-silting of the main sewers would reduce vulnerable population estimates by at least 5 %.     

Precipitation extremes and the impacts of climate change on stormwater infrastructure in Washington State

The design of stormwater infrastructure is based on an underlying assumption that the probability distribution of precipitation extremes is statistically stationary. This assumption is called into question by climate change, resulting in uncertainty about the future performance of systems constructed under this paradigm. We therefore examined both historical precipitation records and simulations of future rainfall to evaluate past and prospective changes in the probability distributions of precipitation extremes across Washington State. Our historical analyses were based on hourly precipitation records for the time period 1949–2007 from weather stations in and near the state’s three major metropolitan areas: the Puget Sound region, Vancouver (WA), and Spokane. Changes in future precipitation were evaluated using two runs of the Weather Research and Forecast (WRF) regional climate model (RCM) for the time periods 1970–2000 and 2020–2050, dynamically downscaled from the ECHAM5 and CCSM3 global climate models. Bias-corrected and statistically downscaled hourly precipitation sequences were then used as input to the HSPF hydrologic model to simulate streamflow in two urban watersheds in central Puget Sound. Few statistically significant changes were observed in the historical records, with the possible exception of the Puget Sound region. Although RCM simulations generally predict increases in extreme rainfall magnitudes, the range of these projections is too large at present to provide a basis for engineering design, and can only be narrowed through consideration of a larger sample of simulated climate data. Nonetheless, the evidence suggests that drainage infrastructure designed using mid-20th century rainfall records may be subject to a future rainfall regime that differs from current design standards.     

FUTURE CHANGE OF PRECIPITATION EXTREMES OVER THE PEARL RIVER BASIN FROM REGIONAL CLIMATE MODELS

Based on RegCM4, a climate model system, we simulated the distribution of the present climate (1961-1990) and the future climate (2010-2099), under emission scenarios of RCPs over the whole Pearl River Basin. From the climate parameters, a set of mean precipitation, wet day frequency, and mean wet day intensity and several precipitation percentiles are used to assess the expected changes in daily precipitation characteristics for the 21st century. Meanwhile the return values of precipitation intensity with an average return of 5, 10, 20, and 50 years are also used to assess the expected changes in precipitation extremes events in this study. The structure of the change across the precipitation distribution is very coherent between RCP4.5 and RCP8.5. The annual, spring and winter average precipitation decreases while the summer and autumn average precipitation increases. The basic diagnostics of precipitation show that the frequency of precipitation is projected to decrease but the intensity is projected to increase. The wet day percentiles (q90 and q95) also increase, indicating that precipitation extremes intensity will increase in the future. Meanwhile, the 5-year return value tends to increase by 30%-45% in the basins of Liujiang River, Red Water River, Guihe River and Pearl River Delta region, where the 5-year return value of future climate corresponds to the 8- to 10-year return value of the present climate, and the 50-year return value corresponds to the 100-year return value of the present climate over the Pearl River Delta region in the 2080s under RCP8.5, which indicates that the warming environment will give rise to changes in the intensity and frequency of extreme precipitation events.     

21世纪珠江流域水文过程对气候变化的响应

应用HBV-D水文模型和多个气候模式预估了不同温室气体排放情景下珠江主干流西江的径流过程,分析了21世纪水资源量和洪水频率的变化。结果表明：2050年后年降水量和年径流量较基准期（1961—1990年）明显增加;流域平均的月降水量和径流量在5—10月间均呈增加趋势,12月至次年2月呈减少趋势;年最大1 d和7 d洪量逐渐增加,重现期逐渐缩短。2030年前枯水期径流增加有望缓解枯水期用水压力,而2050年之后丰水期径流量以及洪水强度、发生频率的增加将给珠江流域防汛抗洪带来更大压力,在制订气候变化对流域水资源影响适应性对策时应考虑这两方面的影响。     

Application of downscaled precipitation for hydrological climate-change impact assessment in the upper Ping River Basin of Thailand

This paper assesses the impacts of climate change on water resources in the upper Ping River Basin of Thailand. A rainfall-runoff model is used to estimate future runoff based on the bias corrected and downscaled ECHAM4/OPYC general circulation model (GCM) precipitation scenarios for three future 5-year periods; the 2023–2027 (2025s), the 2048–2052 (2050s) and 2093–2097 (2095s). Bias-correction and spatial disaggregation techniques are applied to improve the characteristics of raw ECHAM4/OPYC precipitation. Results of future simulations suggest a decrease of 13–19 % in annual streamflow compared to the base period (1998–2002). Results also indicate that there will be a shift in seasonal streamflow pattern. Peak flows in future periods will occur in October–November rather than September as observed in the base period. There will be a significant increase in the streamflow in April with overall decrease in streamflow during the rainy season (May–October) and an increase during the dry season (November–April) for all future time periods considered in the study.     

Implications of 21st century climate change for the hydrology of Washington State

Pacific Northwest (PNW) hydrology is particularly sensitive to changes in climate because snowmelt dominates seasonal runoff, and temperature changes impact the rain/snow balance. Based on results from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4), we updated previous studies of implications of climate change on PNW hydrology. PNW 21st century hydrology was simulated using 20 Global Climate Models (GCMs) and 2 greenhouse gas emissions scenarios over Washington and the greater Columbia River watershed, with additional focus on the Yakima River watershed and the Puget Sound which are particularly sensitive to climate change. We evaluated projected changes in snow water equivalent (SWE), soil moisture, runoff, and streamflow for A1B and B1 emissions scenarios for the 2020s, 2040s, and 2080s. April 1 SWE is projected to decrease by approximately 38–46% by the 2040s (compared with the mean over water years 1917–2006), based on composite scenarios of B1 and A1B, respectively, which represent average effects of all climate models. In three relatively warm transient watersheds west of the Cascade crest, April 1 SWE is projected to almost completely disappear by the 2080s. By the 2080s, seasonal streamflow timing will shift significantly in both snowmelt dominant and rain–snow mixed watersheds. Annual runoff across the State is projected to increase by 2–3% by the 2040s; these changes are mainly driven by projected increases in winter precipitation.     

MULTIPLE TIME SCALE ANALYSIS OF CLIMATE VARIATION IN MACAU DURING THE LAST 100 YEARS

The multiple time scale climate changes are studied and calculated with statistical analysis and wavelet transformation on the basis of daily series of observed data over the period 1901-2007 in Macau.The result shows that statistically significant oscillations with 2 to 5 years of period generally exist in the series of climate variables(e.g.annual mean surface air temperature and precipitation as well as evaporation etc.),but with obvious locality in time domain.The variation of annual mean surface air temperature has a quasi 60-year period.The phases of the 60-year variation approximately and consistently match that of Atlantic Multidecadal Oscillation(AMO).The oscillations of seasonal mean surface air temperature in summer and winter have the periods of quasi 30-year and quasi 60-year,respectively.These two periods of oscillations have statistically significant correlation with Pacific decadal oscillation(PDO) and AMO,individually.The multidecadal variations of the precipitation of the annually first flood period and annual evaporation are dominated by periods of quasi 30-year and quasi 50-year,respectively.     

Changes in future climate indices using Statistical Downscaling Model in the upper Baro basin of Ethiopia

Climate indices are the diagnostic tools used to define the state of climate system. The main objective of this study was to investigate the climate index change in future time periods in the upper Baro basin of Ethiopia. The daily precipitation and maximum and minimum temperature data were downscaled using Statistical Downscaling Model (SDSM). The precipitation and temperature data were estimated according to UK Hadley Centre Coupled Model version 3 (HadCM3) global circulation model with medium-high (A2) and medium-low emission (B2) scenarios in three future time interval periods. The De Martonne Aridity Index and Pinna Combinative Index change of the future time periods centered at 2020s, 2050s, and 2080s was computed. The analysis was based on percentage change between the baseline and three future time periods. The monthly De Martonne Aridity Index result showed that there are months in the dry season classified as semi-dry with value of less than 20 and the land needs irrigation in these months. The Pinna Combinative Index value also showed the same trend like that of the De Martonne Aridity Index and a high correlation coefficient was noticed, verifying similar trend of the two indices for the three future time period changes. Overall, humidity is expected to decrease in most of the months in the three future time periods for both A2 and B2 emission scenarios because of the increment of temperature in the future.     

Ensemble flood risk assessment in Europe under high end climate scenarios

At the current rate of global warming, the target of limiting it within 2 degrees by the end of the century seems more and more unrealistic. Policymakers, businesses and organizations leading international negotiations urge the scientific community to provide realistic and accurate assessments of the possible consequences of so called “high end” climate scenarios.This study illustrates a novel procedure to assess the future flood risk in Europe under high levels of warming. It combines ensemble projections of extreme streamflow for the current century based on EURO-CORDEX RCP 8.5 climate scenarios with recent advances in European flood hazard mapping. Further novelties include a threshold-based evaluation of extreme event magnitude and frequency, an alternative method to removing bias in climate projections, the latest pan-European exposure maps, and an improved flood vulnerability estimation.Estimates of population affected and direct flood damages indicate that by the end of the century the socio-economic impact of river floods in Europe is projected to increase by an average 220% due to climate change only. When coherent socio-economic development pathways are included in the assessment, central estimates of population annually affected by floods range between 500,000 and 640,000 in 2050, and between 540,000 and 950,000 in 2080, as compared to 216,000 in the current climate. A larger range is foreseen in the annual flood damage, currently of 5.3 B€, which is projected to rise at 20–40 B€ in 2050 and 30–100 B€ in 2080, depending on the future economic growth.     

Risk assessment of precipitation extremes in northern Xinjiang,China

This study was conducted using daily precipitation records gathered at 37 meteorological stations in northern Xinjiang, China, from 1961 to 2010. We used the extreme value theory model, generalized extreme value (GEV) and generalized Pareto distribution (GPD), statistical distribution function to fit outputs of precipitation extremes with different return periods to estimate risks of precipitation extremes and diagnose aridity–humidity environmental variation and corresponding spatial patterns in northern Xinjiang. Spatiotemporal patterns of daily maximum precipitation showed that aridity–humidity conditions of northern Xinjiang could be well represented by the return periods of the precipitation data. Indices of daily maximum precipitation were effective in the prediction of floods in the study area. By analyzing future projections of daily maximum precipitation (2, 5, 10, 30, 50, and 100 years), we conclude that the flood risk will gradually increase in northern Xinjiang. GEV extreme value modeling yielded the best results, proving to be extremely valuable. Through example analysis for extreme precipitation models, the GEV statistical model was superior in terms of favorable analog extreme precipitation. The GPD model calculation results reflect annual precipitation. For most of the estimated sites’ 2 and 5-year T for precipitation levels, GPD results were slightly greater than GEV results. The study found that extreme precipitation reaching a certain limit value level will cause a flood disaster. Therefore, predicting future extreme precipitation may aid warnings of flood disaster. A suitable policy concerning effective water resource management is thus urgently required.     

Regional impact assessment of flooding under future climate and socio-economic scenarios for East Anglia and North West England

Interactive tools developed within the RegIS project for assessing the impacts of flooding provide information to support flood management policies and analyse the performance of possible adaptation activities to climate change. This paper describes the methodologies used in the development of these tools including tidal and fluvial flooding processes with different levels of climate pressures, represented by changes in sea level and peak river flows. Potential impacts of climate change for East Anglia and North West England are explored to the 2050s using four socio-economic scenarios to represent plausible futures. This includes changes in urban land use as well as adaptive responses to flooding comprising dike upgrade and realignment options. The results indicate that future climate will increase flood risk in both regions. East Anglia is more vulnerable to climate change than North West England at the present level of protection, especially in the extensive coastal lowlands of the Fens and Broads because of the combined effects of sea-level rise and increased fluvial flows. Although the present adaptive policy of upgrading defences in East Anglia will reduce the impacts of flooding, this policy is not effective in the case of the more extreme climate change scenarios by 2050s. In this case, more extensive adaptation would be required.