Techniques for assessing water infrastructure for nonstationary extreme events: a review

Statistical and physically-based methods have been used for designing and assessing water infrastructure such as spillways and stormwater drainage systems. Traditional approaches assume that hydrological processes evolve in an environment where the hydrological cycle is stationary over time. However, in recent years, it has become increasingly evident that in many areas of the world the foregoing assumption may no longer apply, due to the effect of anthropogenic and climatic induced stressors that cause nonstationary conditions. This has attracted the attention of national and international agencies, research institutions, academia, and practicing water specialists, which has led to developing new techniques that may be useful in those cases where there is good evidence and attribution of nonstationarity. We review the various techniques proposed in the field and point out some of the challenges ahead in future developments and applications. Our review emphasizes hydrological design to protect against extreme events such as floods and low flows.     

The influence of dependence in characterizing multi-variable uncertainty for climate change impact assessments

Few approaches exist that explicitly use the uncertainty associated with the spread of climate model simulations in assessing climate change impacts. An approach that does so is second-order approximation (SOA). This incorporates quantification of uncertainty to ascertain its impact on the derived response using a Taylor series expansion of the model. This study uses SOA in a statistical downscaling model of monthly streamflow, with a focus on the influence of dependence in the uncertainty of multiple atmospheric variables. Uncertainty is quantified using the square root error variance concept with a new extension that allows the inter-dependence terms among the atmospheric variable uncertainty to be specified. Applying the model to selected point locations in Australia, it is noted that the downscaling results differ considerably from downscaling that ignores uncertainty. However, when the effects of dependence in uncertainty are incorporated, the results differ according to the regional variations in dependence structure.     

Multi-site bias correction of climate model outputs for hydro-meteorological impact studies: An application over a watershed in China

Bias correction methods remove systematic differences in the distributional properties of climate model outputs with respect to observations, often as a means of pre-processing model outputs for use in hydrological impact studies. Traditionally, bias correction is applied at each weather station individually, neglecting the dependence that exists between different sites, which could negatively affect simulations from a distributed hydrological model. In this study, three multi-variate bias correction (MBC) methods—initially proposed to correct the inter-variable correlation or multi-variate dependence of climate model outputs—are used to correct biases in distributional properties and spatial dependence at multiple weather stations. To reveal the benefits of correcting spatial dependence, two distribution-based single-site bias correction methods are used for comparison. The effects of multi-site correction on hydro-meteorological extremes are assessed by driving a distributed hydrological model and then evaluating the model performance in terms of several meteorological and hydrological extreme indices. The results show that the multi-site bias correction methods perform well in reducing biases in spatial correlation measures of raw global climate model outputs. In addition, the multi-site methods consistently reproduce watershed-averaged meteorological variables better than single-site methods, especially for extreme values. In terms of representing hydrological extremes, the multi-site methods generally perform better than the single-site methods, although the benefits vary according to the hydrological index. However, when applying the multi-site methods, the original temporal sequence of precipitation occurrence may be altered to some extent. Overall, all multi-site bias correction methods are able to reproduce the spatial correlation of observed meteorological variables over multiple stations, which leads to better hydrological simulations, especially for extremes. This study emphasizes the necessity of considering spatial dependence when applying bias correction to ccc outputs and hydrological impact studies.     

A hierarchical Bayesian approach for the analysis of climate change impact on runoff extremes

In this study the impact of climate change on runoff extremes is investigated over the Pacific Northwest (PNW). This paper aims to address the question of how the runoff extremes change in the future compared to the historical time period, investigate the different behaviors of the regional climate models (RCMs) regarding the runoff extremes and assess the seasonal variations of runoff extremes. Hydrologic modeling is performed by the variable infiltration capacity (VIC) model at a 1/8° resolution and the model is driven by climate scenarios provided by the North American Regional Climate Change Assessment Program (NARCCAP) including nine regional climate model (RCM) simulations. Analysis is performed for both the historical (1971–2000) and future (2041–2070) time periods. Downscaling of the climate variables including precipitation, maximum and minimum temperature and wind speed is done using the quantile‐mapping (QM) approach. A spatial hierarchical Bayesian model is then developed to analyse the annual maximum runoff in different seasons for both historical and future time periods. The estimated spatial changes in extreme runoffs over the future period vary depending on the RCM driving the hydrologic model. The hierarchical Bayesian model characterizes the spatial variations in the marginal distributions of the General Extreme Value (GEV) parameters and the corresponding 100‐year return level runoffs. Results show an increase in the 100‐year return level runoffs for most regions in particular over the high elevation areas during winter. The Canadian portions of the study region reflect higher increases during spring. However, reduction of extreme events in several regions is projected during summer. Copyright © 2013 John Wiley & Sons, Ltd.     

Two Approaches for Determining Extreme Years of Global Atmospheric Temperature

Two different groups of indices have been defined to analyze the evolution of global temperature between 1958 and 1998. All the indices were evaluated at three different levels (850, 500 and 200 hPa), and averaged indices were calculated using the whole globe, continental areas and oceanic areas. The first group of indices analyzes the area of the world covered with higher and lower than normal temperatures, detecting a slight cooling in the 200 hPa level. The second group of indices studies the annual frequency of extreme events, and again, it is at 200 hPa where the most intense variation is detected. Finally, an analysis is performed to determine the regions most sensible to variations in the occurrence of extreme events. Tropical areas are mostly responsible of the variations detected in the second group of indices.     

A new analytical solution for assessing climate change impacts on subsurface temperature

Groundwater temperature is an important water quality parameter that affects species distributions in subsurface and surface environments. To investigate the response of subsurface temperature to atmospheric climate change, an analytical solution is derived for a one‐dimensional, transient conduction–advection equation and verified with numerical methods using the finite element code SUTRA. The solution can be directly applied to forward model the impact of future climate change on subsurface temperature profiles or inversely applied to produce a surface temperature history from measured borehole profiles. The initial conditions are represented using superimposed linear and exponential functions, and the boundary condition is expressed as an exponential function. This solution expands on a classic solution in which the initial and boundary conditions were restricted to linear functions. The exponential functions allow more flexibility in matching climate model projections (boundary conditions) and measured temperature–depth profiles (initial conditions). For example, measured borehole temperature data from the Sendai Plain and Tokyo, Japan, were used to demonstrate the improved accuracy of the exponential function for replicating temperature–depth profiles. Also, the improved accuracy of the exponential boundary condition was demonstrated using air temperature anomaly data from the Intergovernmental Panel on Climate Change. These air temperature anomalies were then used to forward model the effect of surficial thermal perturbations in subsurface environments with significant groundwater flow. The simulation results indicate that recharge can accelerate shallow subsurface warming, whereas upward groundwater discharge can enhance deeper subsurface warming. Additionally, the simulation results demonstrate that future groundwater temperatures obtained from the proposed analytical solution can deviate significantly from those produced with the classic solution. Copyright © 2013 John Wiley & Sons, Ltd.     

A two-stage time series model for monthly hydrological projections under climate change in the Lim River basin (southeast Europe)

ABSTRACT

Climate change projections of precipitation and temperature suggest that Serbia could be one of the most affected regions in southeastern Europe. To prepare adaptation measures, the impact of climate changes on water resources needs to be assessed. Pilot research is carried out for the Lim River basin, in southeastern Europe, to predict monthly flows under different climate scenarios. For estimation of future water availability, an alternative approach of developing a deterministic-stochastic time series model is chosen. The proposed two-stage time series model consists of several components: trend, long-term periodicity, seasonality and the stochastic component. The latter is based on a transfer function model with two input variables, precipitation and temperature, as climatic drivers. The Nash-Sutcliffe model efficiency for the observed period 1950–2012 is 0.829. The model is applied for the long-term hydrological prediction under the representative concentration pathway (RCP) emissions scenarios for the future time frame 2013–2070.     

Groundwater depletion in northern India: Impacts of the sub-regional anthropogenic land-use,socio-politics and changing climate

Understanding the key drivers behind intensive use of groundwater resources and subsequent depletion in northern India is important for future food security of India. Although spatio-temporal changes of groundwater storage (GWS) and its depletion in northern India are mapped using the NASA's GRACE (Gravity Recovery and Climate Experiment) records, the sub-regional diverse socio-political and environmental factors contributing to the variability in groundwater withdrawals and renewals are not well documented. Here, we provide new evidence on changes in GWS at different spatial scales using both observations and satellite-based measurements applying both parametric and non-parametric statistical analyses. The substantial loss of GWS has occurred since the beginning of the 21st century, and the decline in GWS is associated with some record-breaking dry and hot climate events. We present how certain state-based policy decisions, such as supplying free electricity for irrigation, prompted farmers to extract groundwater unsustainably and thus led to widespread GWS deletion, which has been also accelerated by frequent dryness and rising temperatures. In the hotspot of Punjab, Haryana and Delhi of northern India, the extracted groundwater during 1985–2013 is equivalent to a metre-high layer if spread uniformly across its geographical domain. We find that the groundwater storage loss in northern India has increased rapidly from 17 km³ to 189 km³ between the pre-2002 and 2002–2013 periods. This loss in northern India is, therefore, an excellent example of rapid surface greening and sub-surface drying—a result of an interplay of socio-political and environmental factors. As groundwater continues to be treated as a common natural resource and no clear definition exists to guide policymaking, this study also illustrates how the administrative district level approach can solve the widespread problem of depletion.     

多区域模式集合的东亚陆地区域的平均和极端降水未来预估

利用东亚区域联合降尺度计划(CORDEX-EA)15个区域模式的模拟结果,集合预估了高排放情景RCP8.5下东亚陆地区域平均和极端降水的未来时空变化,并量化未来预估的不确定性.结果表明：区域模式基本上能够再现东亚及各个区域平均和极端降水的多年平均分布.未来多模式集合预估的平均和极端强降水在东亚各区域多表现为增加,连续无降水日数(CDD)表现为南增北减,且变幅多随时间增大.到21世纪末期,冬季和年平均降水的增幅大值都位于中国西部(WC),冬季降水的变化在WC、蒙古(MG)、中国东北(NE)和中国华北及西北地区东部(NC)的确定性都较高,年降水的变化仅在WC和MG确定性较高.夏季降水增幅大值位于朝鲜半岛和日本(KJ),且仅在这一区域确定性较高.最大5日降水量(Rx5day)和大雨日数(R20)以增加为主且变化的空间分布较为均匀,除去中国江南及华南(SC)和KJ的R20变化,其余区域两个变量的变化确定性都较高.CDD的增幅和减幅大值分别位于SC和MG,其变化在MG、NE和SC确定性较高.

     

Distinguishing streamflow trends caused by changes in climate,forest cover,and permafrost in a large watershed in northeastern China

Understanding how rivers respond to changes in land cover, climate, and subsurface conditions is critical for sustainably managing water resources and ecosystems. In this study, long‐term hydrologic, climate, and satellite data (1973–2012) from the Upper Tahe River watershed (2359 km²) in the Da Hinggan Mountains of northeast China were analysed to quantify the relative hydrologic effects of climate variability (system input) and the combined influences of forest cover change and permafrost thaw (system characteristics) on average annual streamflow (system response) using 2 methods: the sensitivity‐based method and the Kendall–Theil robust line method. The study period was subdivided into a forest harvesting period (1973–1987), a forest stability period (1988–2001), and a forest recovery period (2002–2012). The results indicated that the combined effects of forest harvesting and permafrost thaw on streamflow (+ 47.0 mm) from the forest harvesting period to the forest stability period was approximately twice as large as the effect associated with climate variability (+20.2 mm). Similarly, from the forest stability period to the forest recovery period, the decrease in average annual streamflow attributed to the combined effects of forest recovery and permafrost thaw (?38.0 mm) was much greater than the decrease due to climate variability (?22.2 mm). A simple method was used to separate the distinct impacts of forest cover change and permafrost thaw, but distinguishing these influences is difficult due to changes in surface and subsurface hydrologic connectivity associated with permafrost thaw. The results highlight the need to consider multiple streamflow drivers in future watershed and aquatic ecosystem management. Due to the ecological and hydrological susceptibility to disturbances in the Da Hinggan Mountains, forest harvesting will likely negatively impact ecohydrological processes in this region, and the effects of forest species transition in the forest recovery process should be further investigated.     

CHOSEN: A synthesis of hydrometeorological data from intensively monitored catchments and comparative analysis of hydrologic extremes

Comparative hydrology has been hampered by limited availability of geographically extensive, intercompatible monitoring data on comprehensive water balance stores and fluxes. These limitations have, for example, restricted comprehensive assessment of multiple dimensions of wetting and drying related to climate change and hampered understanding of why widespread changes in precipitation extremes are uncorrelated with changes in streamflow extremes. Here, we address this knowledge gap and underlying data gap by developing a new data synthesis product and using that product to detect trends in the frequencies and magnitudes of a comprehensive set of hydroclimatic and hydrologic extremes. CHOSEN (Comprehensive Hydrologic Observatory Sensor Network) is a database of streamflow, soil moisture, and other hydroclimatic and hydrologic variables from 30 study areas across the United States. An accompanying data pipeline provides a reproducible, semi-automated approach for assimilating data from multiple sources, performing quality assurance and control, gap-filling and writing to a standard format. Based on the analysis of extreme events in the CHOSEN dataset, we detected hotspots, characterized by unusually large proportions of monitored variables exhibiting trends, in the Pacific Northwest, New England, Florida and Alaska. Extreme streamflow wetting and drying trends exhibited regional coherence. Drying trends in the Pacific Northwest and Southeast were often associated with trends in soil moisture and precipitation (Pacific Northwest) and evapotranspiration-related variables (Southeast). In contrast, wetting trends in the upper Midwest and the Rocky Mountains showed few univariate associations with other hydroclimatic extremes, but their latitudes and elevations suggested the importance of changing snowmelt characteristics. On the whole, observed trends are incompatible with a ‘drying-in-dry, wetting-in-wet’ paradigm for climate-induced hydrologic changes over land. Our analysis underscores the need for more extensive, longer-term observational data for soil moisture, snow and evapotranspiration.     

Distributional change of monthly precipitation due to climate change: comprehensive examination of dataset in southeastern United States

A number of watersheds are selected from the Hydro‐Climate Data Network over southeastern United States to examine possible changes in hydrological time series, e.g. precipitation, introduced by changing climate. Possible changes in monthly precipitation are examined by three different methods to detect second order stationarity, abrupt changes in the variance and smooth changes in quantiles of the time series. An analysis of second order stationarity shows that precipitation in eight of the 56 watersheds display nonstationary behaviour. Change‐point analyses reveal that changes in the long‐term variance of monthly precipitation are only detected for a few sites. As a complementary analysis tool, quantile regression aims to detect potential changes of different percentiles of the monthly precipitation over time. Several sites show diverging trends in the quantiles, which implies that the range and thus variance of the data, is increasing. As distinct change‐points are not identified, this suggests that the effect is small and cumulative. Results are analysed in detail, and possible explanations are provided. This type of thorough analysis provides a basis for understanding the possible redistribution of water cycle. It also provides implications for water resources management and hydrological engineering facility design and planning. Copyright © 2013 John Wiley & Sons, Ltd.     

A framework for assessing flow regime alterations resulting from the effects of climate change and human disturbance

Flow regimes have been severely altered by climate change and human activities in recent decades, which has led to ecological degradation in rivers. This study proposes an analogy analysis-based framework, coupled with the Pettitt test, the indicators of hydrological alteration and the range of variation approach, which were used to distinguish the different effects. This framework was applied to the Sha River, a typical river in North China, to test its effectiveness. The results show that: (i) human disturbance had larger effects on pre-flood flow magnitude, the timing, frequency and duration of high and low pulse, and the flow change rate; (ii) climate change mainly influences the magnitude of flood and post-flood flows, and of extreme events; and (iii) the probability of high alteration from the target frequency increased by 69.7% due to the combined impacts. These results can provide valuable references for water resource and aquatic ecosystem management.     

区域气候模式RegCM3对华北地区未来气候变化的数值模拟

采用高水平分辨率区域气候模式进行区域未来气候变化预估,对理解全球增暖对区域气候的潜在影响和科学评估区域气候变化有很好的参考价值.这里对国家气候中心使用25 km高水平分辨率区域气候模式RegCM3单向嵌套全球模式MIROC3.2_hires在观测温室气体(1951—2000)和IPCC A1B温室气体排放情景下(2001—2100)进行的共计150年长时间模拟结果,进行华北地区未来气温、降水和极端气候事件变化的分析.模式检验结果表明:模式对当代(1981—2000)气温以及和气温有关的极端气候事件(霜冻日数、生长季长度)的空间分布和数值模拟较好;对降水及和降水有关的极端气候事件(强降水日期、降水强度、五日最大降水量)能够模拟出它们各自的主要空间分布特征,但在模拟数值上存在偏大、偏强的误差.和全球模式驱动场相比,区域模式模拟的气温、降水和极端气候事件有明显的改进.2010—2100年华北地区随时间区域平均气温升高幅度逐渐增大,随之霜冻日数逐渐减少,生长季长度逐渐增多;同时随温室效应的不断加剧,未来降水呈增加的趋势,强降水日期和五日最大降水量逐渐增多、降水强度逐渐增大.从空间分布看,21世纪末期(2081—2100)气温、降水以及有关的极端气候事件变化比21世纪中期(2041—2060)更加明显.     

区域气候模式RegCM3对华北地区未来气候变化的数值模拟

采用高水平分辨率区域气候模式进行区域未来气候变化预估,对理解全球增暖对区域气候的潜在影响和科学评估区域气候变化有很好的参考价值.这里对国家气候中心使用25 km高水平分辨率区域气候模式RegCM3单向嵌套全球模式MIROC3.2_hires在观测温室气体(1951—2000)和IPCC A1B温室气体排放情景下(2001—2100)进行的共计150年长时间模拟结果,进行华北地区未来气温、降水和极端气候事件变化的分析.模式检验结果表明:模式对当代(1981—2000)气温以及和气温有关的极端气候事件(霜冻日数、生长季长度)的空间分布和数值模拟较好;对降水及和降水有关的极端气候事件(强降水日期、降水强度、五日最大降水量)能够模拟出它们各自的主要空间分布特征,但在模拟数值上存在偏大、偏强的误差.和全球模式驱动场相比,区域模式模拟的气温、降水和极端气候事件有明显的改进.2010—2100年华北地区随时间区域平均气温升高幅度逐渐增大,随之霜冻日数逐渐减少,生长季长度逐渐增多;同时随温室效应的不断加剧,未来降水呈增加的趋势,强降水日期和五日最大降水量逐渐增多、降水强度逐渐增大.从空间分布看,21世纪末期(2081—2100)气温、降水以及有关的极端气候事件变化比21世纪中期(2041—2060)更加明显.     

Simulation of river flow in Britain under climate change: Baseline performance and future seasonal changes

Climate change is likely to manifest in river flow changes across the globe, which could have wide-ranging consequences for society and the natural environment. A number of previous studies used the UK Climate Projections 2009 (UKCP09) to investigate the potential impacts on river flows in Britain, but these projections were recently updated by the release of UKCP18, thus there is a need to update flow studies. Here, the UKCP18 Regional (12 km) projections are applied using a national-scale grid-based hydrological model, to investigate potential future changes in seasonal mean river flows across Great Britain. Analysis of hydrological model performance using baseline climate model data (1980–2010) shows relatively good agreement with use of observation-based data, particularly after application of a monthly precipitation bias-correction. Analysis of seasonal mean flow changes for two future time-slices (2020–2050 and 2050–2080) suggests large decreases in summer flows across the country (median −45% by 2050–2080), but possible increases in winter flows (median 9% by 2050–2080), especially in the north and west. Information on the potential range of flow changes using the latest projections is necessary to develop appropriate adaptation strategies, and comparisons with previous projections can help update existing plans, although such comparisons are often not straightforward.     

Investigation of changes in characteristics of hydrological time series by Bayesian methods

A review of literature reveals the inadequacy of Intervention analysis and spectrum based methods to adequately quantify changes in hydrologic times series. A Bayesian method is used to investigate the statistical significance of observed changes in hydrologic times series and the results are reported herein. The Bayesian method is superior to the previous methods.     

Sensitivity of runoff and soil erosion to climate change in two Mediterranean watersheds. Part II: assessing impacts from changes in storm rainfall,soil moisture and vegetation cover

The impacts of climate change on storm runoff and erosion in Mediterranean watersheds are difficult to assess due to the expected increase in storm frequency coupled with a decrease in total rainfall and soil moisture, added to positive or negative changes to different types of vegetation cover. This report, the second part of a two‐part article, addresses this issue by analysing the sensitivity of runoff and erosion to incremental degrees of change (from ? 20 to + 20%) to storm rainfall, pre‐storm soil moisture, and vegetation cover, in two Mediterranean watersheds, using the MEFIDIS model. The main results point to the high sensitivity of storm runoff and peak runoff rates to changes in storm rainfall (2·2% per 1% change) and, to a lesser degree, to soil water content (?1·2% per 1% change). Catchment sediment yield shows a greater sensitivity than within‐watershed erosion rates to both parameters: 7·8 versus 4·0% per 1% change for storm rainfall, and ? 4·9 versus ? 2·3% per 1% change for soil water content, indicating an increase in sensitivity with spatial scale due to changes to sediment connectivity within the catchment. Runoff and erosion showed a relatively low sensitivity to changes in vegetation cover. Finally, the shallow soils in one of the catchments led to a greater sensitivity to changes in storm rainfall and soil moisture. Overall, the results indicate that decreasing soil moisture levels caused by climate change could be sufficient to offset the impact of greater storm intensity in Mediterranean watersheds. Copyright © 2009 John Wiley & Sons, Ltd.     

On possible drivers of Sun-induced climate changes

We tested the validity of two current hypotheses on the dependence of climate change on solar activity. One of them states that variations in the tropospheric temperature are caused directly by changes of the solar radiance (total or spectral). The other suggests that cosmic ray (CR) fluctuations, caused by the solar/heliospheric modulation, affect the climate via cloud formation. Confronting these hypotheses with seven different sets of the global/hemispheric temperature reconstructions for the last 400 years, we found that the former mechanism is in general more prominent than the latter. Therefore, we can conclude that in so far as the Sun–climate connection is concerned tropospheric temperatures are more likely affected by variations in the UV radiation flux rather than by those in the CR flux.     

More rain,less soil: long‐term changes in rainfall intensity with climate change

This commentary discusses the role of long‐term climate change in driving increases in soil erosion. Assuming that land use and management remain effectively constant, we discuss changes in the ability of rainfall to cause erosion (erosivity), using long daily rainfall data sets from southeast England. An upward trend in mean rainfall per rain day is detected at the century‐plus timescale. Implications for soil erosion and sediment delivery are discussed and evidence from other regions reviewed. We conclude that rates of soil erosion may well increase in a warmer, wetter world. Copyright © 2015 John Wiley & Sons, Ltd.