Climate Change in the Urals,Russia, Inferred from Borehole Temperature Data

Borehole temperatures in the central and south Urals were analysed for the past ground surface temperature (GST) signal. 31 highquality temperature logs were selected for this purpose and inverted with algorithms based on the generalised least squares theory. The signal to noise ratio was improved by averaging the results of individual borehole inversions. No distinct regional trends were found in the studied region except for some indications of more pronounced warming in the south. The mean GST history (GSTH) was characterised by cooling down to –0.6 °C in the 18th century and subsequent warming to 0.5 °C above the longterm mean at the beginning of this century, and to 1 – 1.5 °C by 1980. The stability of the mean GSTH was tested in dependence on the number of holes used for the averaging. It showed that any subset of 15 holes yielded a GSTH similar to that obtained from the whole set. A surface air temperature (SAT) time series comprising the period 1832 – 1989 was combined from 17 meteorological records. Its least squares warming rate of 1.1 °C per 100 years is somewhat higher than that of the GST (0.7 – 0.8°C/100 years) in the same period.     

气候变化对沅江流域径流影响研究

温室气体排放量增加造成气候变化,对全球资源环境产生重要影响.本文在水量平衡基础上,建立考虑气象要素和地形变化的月水文模型,利用实测径流资料对模型在时空尺度上进行验证.利用全球气候模型(GCMs)预测的未来气候变化情形,对处于湿润区的沅江流域径流过程进行预测.分析结果表明,该区域径流过程对降雨和气温变化十分敏感.根据英国Hadcm2模型对本世纪中叶气候变化预测结果,沅江流域未来年降雨量减少0.43%气温升高1.55℃,丰水期降雨增加,而枯水期将有较大幅度减少.年径流量相应减少6.8%,丰水期径流量增大11%,枯水期径流减少47%,不利于防洪和水资源开发利用.     

Climate change impacts on extreme precipitation of water supply area in Istanbul: use of ensemble climate modelling and geo-statistical downscaling

ABSTRACT

Numerous statistical downscaling models have been applied to impact studies, but none clearly recommended the most appropriate one for a particular application. This study uses the geographically weighted regression (GWR) method, based on local implications from physical geographical variables, to downscale climate change impacts to a small-scale catchment. The ensembles of daily precipitation time series from 15 different regional climate models (RCMs) driven by five different general circulation models (GCMs), obtained through the European Union (EU)-ENSEMBLES project for reference (1960–1990) and future (2071–2100) scenarios are generated for the Omerli catchment, in the east of Istanbul city, Turkey, under scenario A1B climate change projections. Special focus is given to changes in extreme precipitation, since such information is needed to assess the changes in the frequency and intensity of flooding for future climate. The mean daily precipitation from all RCMs is under-represented in the summer, autumn and early winter, but it is overestimated in late winter and spring. The results point to an increase in extreme precipitation in winter, spring and summer, and a decrease in autumn in the future, compared to the current period. The GWR method provides significant modifications (up to 35%) to these changes and agrees on the direction of change from RCMs. The GWR method improves the representation of mean and extreme precipitation compared to RCM outputs and this is more significant, particularly for extreme cases of each season. The return period of extreme events decreases in the future, resulting in higher precipitation depths for a given return period from most of the RCMs. This feature is more significant with downscaling. According to the analysis presented, a new adaption for regulating excessive water under climate change in the Omerli basin may be recommended.     

Ground Surface Warming History in Northern Canada Inferred from Inversions of Temperature Logs and Comparison with Other Proxy Climate Reconstructions

— Well temperature logs from 61 sites located in discontinuous and continuous permafrost regions of northern Canada are analyzed. The method of functional space inversion (FSI) is applied to the set of precise temperature logs from wells located between 60 ° and 82 °N. There is strong evidence of extensive ground surface temperature (GST) warming beginning in the late 18^th century and lasting until the 20^th century. This was preceded by a lengthy period of cooling. The approximate average increase of the surface temperature of Canadian Arctic, based on all individual GST histories, is > 1.3 °C for the last 200 years. Simultaneous inversion of all well temperature data suggests an even higher warming (approximately 2 °C). There has been no strong south-to-north gradient in the ground warming magnitude when northern Canadian data are compared with eastern and central Canadian data south of 60 °N which also shows warming close to 2 °C. In Alaska, warming of some 2 °C has been restricted mainly to the 20^th century. In general, however, a high warming magnitude is common for most of Canada and Alaska for the previous century. The averaged GST history (GSTH) for the Canadian Arctic is calibrated with and compares visually with a variety of recently published regional and hemispheric proxy climate reconstructions. These show that GST warming derived from well temperature logs is generally higher than one shown by other proxy (mainly tree-ring reconstructions).Received April, 2003     

Climate impacts on extreme ice-jam events in Canadian rivers

Abstract

River ice jams can produce extreme flood events with major social, economic and ecological impacts throughout Canada. Ice breakup and jamming processes are briefly reviewed and shown to be governed by the flow hydrograph, the thickness and strength of the winter ice cover, and the stream morphology. These factors are directly or indirectly influenced by weather conditions which implies potential impacts of climate change and variability on the severity of ice-jamming. Relevant work has to date focused on simple measures of climatic effects, such as the timing of freeze-up and breakup, and indicates trends that are consistent with concomitant changes in air temperature. More recently, it has been found that increased incidence of mid-winter breakup events and higher freshet flows in certain parts of Canada could enhance the frequency and severity of ice jams. Possible future trends under climate warming scenarios are discussed and associated impacts identified in a general manner.     

全球变暖对长江洪水的可能影响及其前景预测

要长江流域近150a间发生的1870、1931、1935、1954与1998年特大洪水灾害损失严重;长江洪水是我国的心腹之患.1990年以来,长江大洪水高频发生,达6次.长江洪水的发生,除湖泊蓄洪功能减弱等因素外,与全球变暖有关.20世纪90年代为近千年中全球最暖的年代,水循环加快,长江中下游夏季降水量为近120a最多的十年,高出1961-1990平均值112mm;而降雨集中和大暴雨降水事件的增加是洪水增加的主要原因.区域气候模式模拟在CO₂倍增时,长江流域温度升高2.2℃,夏季降水增加10%-20%,气溶胶的增加可能使此值降低一些.考虑气候变暖可能促进潜在蒸发增加9%-15%的假定情景,计算在降水增加10%,蒸发增加9%条件下,最大洪峰流量在大通站将会达到8.4×10⁴ m³/s左右,己超过1998年洪峰流量;汉口站7.9×10⁴ m³/s,超过有记录以来所有的洪峰流量;而在宜昌站高达6.94×10⁴ m³/s,超过自有实测记录以来的除1896年和1981年以外所有的洪峰流量.假定情景的最高值出现在降水增加20%,蒸发增加15%时,大通站流量将达到9.45×10⁴ m³/s,超过该站近百年最大值,1954年的9.26×10⁴ m³/s;宜昌站将出现7.82×10⁴ m³/s流量,超过1882年以来所有实测记录值,但比1870年据洪痕推算的10.5×10⁴ m³/s仍有逊色.未来气候若继续变暖,降水量增加将给长江洪水防御带来巨大的压力.但上述估算是粗糙的,有一定的不确定性,需在以后的研究中进一步改进.     

Climate change impacts on bedload transport in alpine drainage basins with hydropower exploitation

Sediment transport is known to have a significant impact on hydropower infrastructures and changes in sediment transport rates are important for sediment management measures and hydroelectricity production. In this study, we present how climate change may affect bedload transport in 66 high alpine catchments used by hydropower companies in the Valais, Switzerland. Future sediment yield is estimated with a runoff‐based sediment transport model for the two future 30 year time periods 2021–2050 and 2070–2099. The analysis is integrated into a modelling chain in which error‐corrected and downscaled climate scenarios generated in the framework of the ENSEMBLES project are coupled to the hydrological model PREVAH, glacier retreat and bedload transport. To calibrate the sediment transport model, we used the observed sediment volumes in water intakes and reservoirs if such data were available. The results obtained show on average a decrease of sediment yield due to the reduced runoff generation during summer, especially for the scenario period 2070–2099. A shift of the seasonal sediment transport regime with a current maximum during July and August to earlier months in the year is predicted. Projections of future sediment yield rely on the accuracy of the individual modeling chain elements. The different sources of uncertainty are discussed qualitatively. Copyright © 2015 John Wiley & Sons, Ltd.     

Steric Sea-Level Change and its Impact on the Gravity Field caused by Global Climate Change

It is sometimes assumed that steric sea-level variations do not produce a gravity signal as no net mass change, thus no change of ocean bottom pressure is associated with it. Analyzing the output of two CO₂ emission scenarios over a period of 2000 years in terms of steric sea-level changes, we try to quantify the gravitational effect of steric sea-level variations. The first scenario, computed with version 2.6 of the Earth System Climate Model developed at the University of Victoria, Canada (UVic ESCM), is implemented with a linear CO₂ increase of 1% of the initial concentration of 365 ppm and shows a globally averaged steric effect of 5.2 m after 2000 years. In the second scenario, computed with UVic ESCM version 2.7, the CO₂ concentration increases quasi-exponentially to a level of 3011 ppm and is hold fixed afterwards. The corresponding globally averaged steric effect in the first 2000 years is 2.3 m. We show, due to the (vertical) redistribution of ocean water masses (expansion or contraction), the steric effect results also in a small change in the Earth’s gravity field compared to usually larger changes associated with net mass changes. Maximum effects for computation points located on the initial ocean surface can be found in scenario 1, with the effect on gravitational attraction and potential ranging from 0.0 to −0.7·10⁻⁵ m s⁻² and −3·10⁻³ to 6·10⁻³ m² s⁻², respectively. As expected, the effect is not zero but negligible for practical applications.     

Climate change impact on the hydrological budget of a large Mediterranean island

ABSTRACT

Crete is a Mediterranean, karst-dominated island, characterized by long drought periods. The Karst-SWAT model, combined with 11 climate change scenarios, was run to assess climate change impacts on the island under two set-ups, both using the auto-irrigation function of the model: (1) with water drawn from the shallow or deep aquifer, and (2) with irrigated water derived from an unlimited outside source. The first set-up provided insight into the fluctuation of future irrigation needs, and when compared to the second set-up, enabled quantification of the future water deficit. The Water Exploitation Index was used to describe the spatial variability of future water stress on Crete. A decrease in both surface and karstic spring flows is foreseen, especially after 2060 (24.2 and 16.5%, respectively). Simulated irrigation water demand and water deficit show continuous increase throughout the projection period (2020–2098).     

The implications of bias correction methods and climate model ensembles on soil erosion projections under climate change

Climate change will most likely cause an increase in extreme precipitation and consequently an increase in soil erosion in many locations worldwide. In most cases, climate model output is used to assess the impact of climate change on soil erosion; however, there is little knowledge of the implications of bias correction methods and climate model ensembles on projected soil erosion rates. Using a soil erosion model, we evaluated the implications of three bias correction methods (delta change, quantile mapping and scaled distribution mapping) and climate model selection on regional soil erosion projections in two contrasting Mediterranean catchments. Depending on the bias correction method, soil erosion is projected to decrease or increase. Scaled distribution mapping best projects the changes in extreme precipitation. While an increase in extreme precipitation does not always result in increased soil loss, it is an important soil erosion indicator. We suggest first establishing the deviation of the bias-corrected climate signal with respect to the raw climate signal, in particular for extreme precipitation. Furthermore, individual climate models may project opposite changes with respect to the ensemble average; hence climate model ensembles are essential in soil erosion impact assessments to account for climate model uncertainty. We conclude that the impact of climate change on soil erosion can only accurately be assessed with a bias correction method that best reproduces the projected climate change signal, in combination with a representative ensemble of climate models. © 2018 John Wiley & Sons, Ltd.     

The effects of climate change on potential groundwater recharge in Great Britain

The predicted increase in mean global temperature due to climate change is expected to affect water availability and, in turn, cause both environmental and societal impacts. To understand the potential impact of climate change on future sustainable water resources, this paper outlines a methodology to quantify the effects of climate change on potential groundwater recharge (or hydrological excess water) for three locations in the north and south of Great Britain. Using results from a stochastic weather generator, actual evapotranspiration and potential groundwater recharge time‐series for the historic baseline 1961–1990 and for a future ‘high’ greenhouse gas emissions scenario for the 2020s, 2050s and 2080s time periods were simulated for Coltishall in East Anglia, Gatwick in southeast England and Paisley in west Scotland. Under the ‘high’ gas emissions scenario, results showed a decrease of 20% in potential groundwater recharge for Coltishall, 40% for Gatwick and 7% for Paisley by the end of this century. The persistence of dry periods is shown to increase for the three sites during the 2050s and 2080s. Gatwick presents the driest conditions, Coltishall the largest variability of wet and dry periods and Paisley little variability. For Paisley, the main effect of climate change is evident during the dry season (April–September), when the potential amount of hydrological excess water decreases by 88% during the 2080s. Overall, it is concluded that future climate may present a decrease in potential groundwater recharge that will increase stress on local and regional groundwater resources that are already under ecosystem and water supply pressures. Copyright © 2007 John Wiley & Sons, Ltd.     

The impact of climate change on extreme precipitation in Sicily,Italy

Increasing precipitation extremes are one of the possible consequences of a warmer climate. These may exceed the capacity of urban drainage systems, and thus impact the urban environment. Because short‐duration precipitation events are primarily responsible for flooding in urban systems, it is important to assess the response of extreme precipitation at hourly (or sub‐hourly) scales to a warming climate. This study aims to evaluate the projected changes in extreme rainfall events across the region of Sicily (Italy) and, for two urban areas, to assess possible changes in Depth‐Duration‐Frequency (DDF) curves. We used Regional Climate Model outputs from Coordinated Regional Climate Downscaling Experiment for Europe area ensemble simulations at a ~12 km spatial resolution, for the current period and 2 future horizons under the Representative Concentration Pathways 8.5 scenario. Extreme events at the daily scale were first investigated by comparing the quantiles estimated from rain gauge observations and Regional Climate Model outputs. Second, we implemented a temporal downscaling approach to estimate rainfall for sub‐daily durations from the modelled daily precipitation, and, lastly, we analysed future projections at daily and sub‐daily scales. A frequency distribution was fitted to annual maxima time series for the sub‐daily durations to derive the DDF curves for 2 future time horizons and the 2 urban areas. The overall results showed a raising of the growth curves for the future horizons, indicating an increase in the intensity of extreme precipitation, especially for the shortest durations. The DDF curves highlight a general increase of extreme quantiles for the 2 urban areas, thus underlining the risk of failure of the existing urban drainage systems under more severe events.     

Climate changes and their impacts on water resources in semiarid regions: a case study of the Wei River basin,China

Understanding the impacts of climate change and human activity on the hydrological processes in river basins is important for maintaining ecosystem integrity and sustaining local economic development. The objective of this study was to evaluate the impact of climate variability and human activity on mean annual flow in the Wei River, the largest tributary of the Yellow River. The nonparametric Mann–Kendall test and wavelet transform were applied to detect the variations of hydrometeorological variables in the semiarid Wei River basin in the northwestern China. The identifications were based on streamflow records from 1958 to 2008 at four hydrological stations as well as precipitation and potential evapotranspiration (PET) data from 21 climate stations. A simple method based on Budyko curve was used to evaluate potential impacts of climate change and human activities on mean annual flow. The results show that annual streamflow decreased because of the reduced precipitation and increased PET at most stations. Both annual and seasonal precipitation and PET demonstrated mixed trends of decreasing and increasing, although significant trends (P < 0.05) were consistently detected in spring and autumn at most stations. Significant periodicities of 0.5 and 1 year (P < 0.05) were examined in all the time series. The spectrum of streamflow at the Huaxian station shows insignificant annual cycle during 1971–1975, 1986–1993 and 1996–2008, which is probably resulted from human activities. Climate variability greatly affected water resources in the Beiluo River, whereas human activities (including soil and water conservation, irrigation, reservoirs construction, etc.) accounted more for the changes of streamflow in the area near the Huaxian station during different periods. The results from this article can be used as a reference for water resources planning and management in the semiarid Wei River basin. Copyright © 2012 John Wiley & Sons, Ltd.     

Impact of human activities on stream flow in the Biliu River basin,China

The obvious decline in stream flow to the Biliu River reservoir over the period 1990–2005 has raised increasing concerns. Climate change and human activities, which mainly include land use changes, hydraulic constructions and artificial water consumption, are considered to be the most likely reasons for the decline in stream flow. This study centres on a detailed analysis of the runoff response to changes in human activities. Using a distributed hydrological model, (Soil and Water Assessment Tool), we simulated runoffs under different human activity and climate scenarios to understand how each scenario impacts stream flow. The results show that artificial water consumption correlates with the precipitation (wet, normal and dry) of the year in question and is responsible for most of the decrease in runoff during each period and for each different wetness year. A Fuzzy Inference Model is also used to find the relationship between the precipitation and artificial water consumption for different years, as well as to make inferences regarding the future average impact on runoff. Land use changes in the past have increased the runoff by only a small amount, while another middle reservoir (Yunshi) has been responsible for a decrease in runoff since operation began in 2001. We generalized the characteristics of the human activities to predict future runoff using climate change scenarios. The future annual flow will increase by approximately 10% from 2011 to 2030 under normal human activities and future climate change scenarios, as indicated by climate scenarios with a particularly wet year in the next 20 years. This study could serve as a framework to analyse and predict the potential impacts of changes both in the climate and human activities on runoff, which can be used to inform the decision making on the river basin planning and management. Copyright © 2012 John Wiley & Sons, Ltd.     

Climate impacts on global irrigation requirements under 19 GCMs,simulated with a vegetation and hydrology model

Abstract

This study quantifies global changes in irrigation requirements for areas presently equipped for irrigation of major crop types, using climate projections from 19 GCMs up to the 2080s. Analysis is based on results from the global eco-hydrological model LPJmL that simulates the complex and dynamic interplay of direct and indirect climate change effects upon irrigation requirements. We find a decrease in global irrigation demand by ～17% in the ensemble median, due to a combination of beneficial CO₂ effects on plants, shorter growing periods and regional precipitation increases. In contrast, increases of >20% are projected with a high likelihood (i.e. in more than two thirds of the climate change scenarios) for some regions, including southern Europe, and, with a lower likelihood, for parts of Asia and North America as well. If CO₂ effects were not accounted for, however, global irrigation demand would hardly change, and increases would prevail in most regions except for southern Asia (where higher precipitation is projected). We stress that the CO₂ effects may not be realized everywhere, that irrigation requirements will probably increase further due to growing global food demand (not considered here), and that a significant amount of water to meet future irrigation requirements will have to be taken from fossil groundwater, environmental flow reserves or diverted rivers.

Editor D. Koutsoyiannis; Associate editor A. Montanari

Citation Konzmann, M., Gerten, D., and Heinke, J., 2013. Climate impacts on global irrigation requirements under 19 GCMs, simulated with a vegetation and hydrology model. Hydrological Sciences Journal, 58 (1), 1–18.     

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.     

Impact of the spatial variability of daily precipitation on hydrological projections: A comparison of GCM‐ and RCM‐driven cases in the Han River basin,Korea

In this study, we investigate the impact of the spatial variability of daily precipitation on hydrological projections based on a comparative assessment of streamflow simulations driven by a global climate model (GCM) and two regional climate models (RCMs). A total of 12 different climate input datasets, that is, the raw and bias‐corrected GCM and raw and bias‐corrected two RCMs for the reference and future periods, are fed to a semidistributed hydrological model to assess whether the bias correction using quantile mapping and dynamical downscaling using RCMs can improve streamflow simulation in the Han River basin, Korea. A statistical analysis of the daily precipitation demonstrates that the precipitation simulated by the GCM fails to capture the large variability of the observed daily precipitation, in which the spatial autocorrelation decreases sharply within a relatively short distance. However, the spatial variability of precipitation simulated by the two RCMs shows better agreement with the observations. After applying bias correction to the raw GCM and raw RCMs outputs, only a slight change is observed in the spatial variability, whereas an improvement is observed in the precipitation intensity. Intensified precipitation but with the same spatial variability of the raw output from the bias‐corrected GCM does not improve the heterogeneous runoff distributions, which in turn regulate unrealistically high peak downstream streamflow. GCM‐simulated precipitation with a large bias correction that is necessary to compensate for the poor performance in present climate simulation appears to distort streamflow patterns in the future projection, which leads to misleading projections of climate change impacts on hydrological extremes.     

Impact of climate change on 24‐h design rainfall depth estimation in Qiantang River Basin,East China

The frequency and magnitude of extreme meteorological or hydrological events such as floods and droughts in China have been influenced by global climate change. The water problem due to increasing frequency and magnitude of extreme events in the humid areas has gained great attention in recent years. However, the main challenge in the evaluation of climate change impact on extreme events is that large uncertainty could exist. Therefore, this paper first aims to model possible impacts of climate change on regional extreme precipitation (indicated by 24‐h design rainfall depth) at seven rainfall gauge stations in the Qiantang River Basin, East China. The Long Ashton Research Station‐Weather Generator is adopted to downscale the global projections obtained from general circulation models (GCMs) to regional climate data at site scale. The weather generator is also checked for its performance through three approaches, namely Kolmogorov–Smirnov test, comparison of L‐moment statistics and 24‐h design rainfall depths. Future 24‐h design rainfall depths at seven stations are estimated using Pearson Type III distribution and L‐moment approach. Second, uncertainty caused by three GCMs under various greenhouse gas emission scenarios for the future periods 2020s (2011–2030), 2055s (2046–2065) and 2090s (2080–2099) is investigated. The final results show that 24‐h design rainfall depth increases in most stations under the three GCMs and emission scenarios. However, there are large uncertainties involved in the estimations of 24‐h design rainfall depths at seven stations because of GCM, emission scenario and other uncertainty sources. At Hangzhou Station, a relative change of ?16% to 113% can be observed in 100y design rainfall depths. Copyright © 2012 John Wiley & Sons, Ltd.     

Comparative Study on Two Methods for Measuring Wave Velocity Change of Crustal Medium Based on Large Volume Airgun Excitation Data

This paper proposes the application of dynamic programming method to calculate the relative change of wave velocities and compares its similarities and differences with the cross-correlation delay estimation method based on interference. The results show that:①the trend of wave velocities obtained by cross-correlation method and dynamic programming method are consistent. Besides,it is considered that the calculated result using cross-correlation delay method is reliable.② Compared with the cross-correlation delay method,the calculated result of the dynamic programming method has a magnifying effect and is more sensitive to small disturbances.③ Under ideal conditions,the wave velocity change trend calculated by P-wave and S-wave phase should be consistent. In addition,the cross-correlation delay method is used to calculate the wave velocity change.Under appropriate conditions,the process of recovering from the suspected wave velocity before the M_L1. 1 earthquake near the airgun source can be observed.