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.     

Projected changes in flood indices in selected catchments in Poland in the 21st century

The aim of this study is to estimate likely changes in flood indices under a future climate and to assess the uncertainty in these estimates for selected catchments in Poland. Precipitation and temperature time series from climate simulations from the EURO-CORDEX initiative for the periods 1971–2000, 2021–2050 and 2071–2100 following the RCP4.5 and RCP8.5 emission scenarios have been used to produce hydrological simulations based on the HBV hydrological model. As the climate model outputs for Poland are highly biased, post processing in the form of bias correction was first performed so that the climate time series could be applied in hydrological simulations at a catchment-scale. The results indicate that bias correction significantly improves flow simulations and estimated flood indices based on comparisons with simulations from observed climate data for the control period. The estimated changes in the mean annual flood and in flood quantiles under a future climate indicate a large spread in the estimates both within and between the catchments. An ANOVA analysis was used to assess the relative contributions of the 2 emission scenarios, the 7 climate models and the 4 bias correction methods to the total spread in the projected changes in extreme river flow indices for each catchment. The analysis indicates that the differences between climate models generally make the largest contribution to the spread in the ensemble of the three factors considered. The results for bias corrected data show small differences between the four bias correction methods considered, and, in contrast with the results for uncorrected simulations, project increases in flood indices for most catchments under a future climate.     

Spatio-temporal characteristics of extreme precipitation events during 1951–2011 in Shandong,China and possible connection to the large scale atmospheric circulation

Analyses of the spatio-temporal variability of precipitation extremes defined by eleven extreme precipitation indices in Shandong were conducted by utilizing the methods of linear regression, ensemble empirical mode decomposition (EEMD) and Mann–Kendall test. The results revealed that statistically significant decreasing trends existed for almost all extreme precipitation indices except for the consecutive dry days (CDD) and simple daily intensity index. A periodicity of 10–15 years for precipitation extremes is detected by EEMD analysis. Greatest 5-day total rainfall (RX5day), very wet days (R95p) and annual total wet-day precipitation (PRCPTOT) experienced decreasing trends in the region stretching from the southeast coast to the west, while the spatial distribution of the decreasing trends for other indices was more complicated. Moreover, the frequency of occurrence in precipitation extremes at Changdao station, surrounded by the sea in the northeast region, increased in contrast to surrounding stations. This may suggest a possible effect from the local marine environment on extreme precipitation. In addition, the stations with statistically significant positive trends for CDD were mainly located in mid-west Shandong and along the southeast coast, where the extreme precipitation and total rainfall were, on the contrary, characterized by decreasing trends. These results indicate that drought or severe drought events have become more frequent in those regions. Analysis of large-scale atmospheric circulation changes indicates that a strengthening anticyclonic circulation and increasing geopotential height as well as decreasing strength of monsoonal flow in recent decades may have contributed to the variations in extreme precipitation in Shandong.     

Climate change impacts on meteorological drought using SPI and SPEI: case study of Ankara,Turkey

ABSTRACT

Using regionally downscaled and adjusted outputs of three global climate models (GCMs), meteorological drought analysis was accomplished across Ankara, the capital city of Turkey. To this end, standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) were projected under (representative concentration pathway) RCP4.5 and RCP8.5 greenhouse gas scenarios. In general, our results show that Ankara experienced six severe and two extreme drought events during the reference period, 1971–2000. However, the projections indicate fewer drought events for the near-future period of 2016–2040, with no potential extreme drought events. While the RCP4.5 scenario showed that dry spells will be dominant in the second half of the near-future period, the RCP8.5 scenario projected that dry spells will be evenly distributed during the entire near-future period.     

Trends in precipitation extremes over the Yellow River basin in North China: Changing properties and causes

The Mann–Kendall test, composite analysis, and 68 high‐quality meteorological stations were used to explore the spatiotemporal variations and causes of precipitation extremes over the Yellow River basin (YRB) during the period of 1960–2011. Results showed that (a) the YRB is characterized by decreases of most precipitation indices, excluding the simple daily intensity index, which has increasing trends in most locations, suggesting that the intensity of rainfall and the probability of occurrence of droughts have increased during the last decades. (b) Trends of extreme precipitation show mixed patterns in the lower reach of the YRB, where drought–flood disasters have increased. The increases in heavy rainfall and decreases in consecutive wet days in recent years over the northwestern portions of the YRB indicate that the intensity and frequency of above‐normal precipitation have been trending upward in domains. In the central‐south YRB, the maximum 1‐day precipitation (RX1day) and precipitation on extremely wet days (R99p) have significantly increased, whereas the number of consecutive dry days has declined; these trends suggest that the intensity of precipitation extremes has increased in those regions, although the frequency of extreme and total rainfall has decreased. (c) The spatial distributions of seasonal trends in RX1day and maximum 5‐day precipitation (RX5day) exhibited less spatial coherence, and winter is becoming the wettest season regionwide, particularly over the central‐south YRB. (d) There were multiple and overlapping cycles of variability for most precipitation indices, indicating variations of time and frequency. (e) Elevation is intimately correlated with precipitation indices, and a weakening East Asian summer monsoon during 1986–2011 compared to that in 1960–1985 may have played an important role in the declines in most indices over the YRB. Therefore, the combined effects from local and teleconnection forcing factors have collectively influenced the variations in precipitation extremes across the YRB. This study may provide valuable evidence for the effective management of water resources and the conduct of agricultural activities at the basin scale.     

Meteorological drought in the Beijiang River basin,South China: current observations and future projections

It is expected that climate warming will be experienced through increases in the magnitude and frequency of extreme events, including droughts. This paper presents an analysis of observed changes and future projections for meteorological drought for four different time scales (1 month, and 3, 6 and 12 months) in the Beijiang River basin, South China, on the basis of the standardized precipitation evapotranspiration index (SPEI). Observed changes in meteorological drought were analysed at 24 meteorological stations from 1969 to 2011. Future meteorological drought was projected based on the representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5, as projected by the regional climate model RegCM4.0. The statistical significance of the meteorological drought trends was checked with the Mann–Kendall method. The results show that drought has become more intense and more frequent in most parts of the study region during the past 43 years, mainly owing to a decrease in precipitation. Furthermore, long-term dryness is expected to be more pronounced than short-term dryness. Validation of the model simulation indicates that RegCM4.0 provides a good simulation of the characteristic values of SPEIs. During the twenty first century, significant drying trends are projected for most parts of the study region, especially in the southern part of the basin. Furthermore, the drying trends for RCP8.5 (or for long time scales) are more pronounced than for RCP4.5 (or for short time scales). Compared to the baseline period 1971–2000, the frequency of drought for RCP4.5 (RCP8.5) tends to increase (decrease) in 2021–2050 and decrease (increase) in 2051–2080. The results of this paper will be helpful for efficient water resources management in the Beijiang River basin under climate warming.     

Assessment of future precipitation indices in the Shikoku region using a statistical downscaling model

In this study, we used the statistical downscaling model (SDSM) to estimate mean and extreme precipitation indices under present and future climate conditions for Shikoku, Japan. Specifically, we considered the following mean and extreme precipitation indices: mean daily precipitation, R10 (number of days with precipitation >10 mm/day), R5d (annual maximum precipitation accumulated over 5 days), maximum dry-spell length (MaDSL), and maximum wet-spell length (MaWSL). Initially, we calibrated the SDSM model using the National Center for environmental prediction (NCEP) reanalysis dataset and daily time series of precipitation for ten locations in Shikoku which were acquired from the surface weather observation point dataset. Subsequently, we used the validated SDSM, using data from NCEP and outputs form general circulation models (GCM), to predict future precipitation indices. Specifically, the HadCM3 GCM was run under the special report on emissions scenarios (SRES) A2 and B2 scenarios, and the CGCM3 GCM was run under the SRES A2 and A1B scenarios. The results showed that: (1) the SDSM can reasonably be used to simulate mean and extreme precipitation indices in the Shikoku region; (2) the values of annual R10 were predicated to decrease in the future in northern Shikoku under all climate scenarios; conversely, the values of annual R10 were predicted to increase in the future in the range of 0–15 % in southern and western Shikoku. The values of annual MaDSL were predicted to increase in northern Shikoku, and the values of annual MaWSL were predicted to decrease in northeastern Shikoku; (3) the spatial variation of precipitation indices indicated the potential for an increased occurrence of drought across northeastern Shikoku and an increased occurrence of flood events in the southwestern part of Shikoku, especially under the A2 and A1B scenarios; (4) characteristics of future precipitation may differ between the northern and southern sides of the Shikoku Mountains. Regional variations in extreme precipitation indices were not notably evident in the B2 scenario compared to the other scenarios.     

Climate change impacts on surface water resources in the Rheraya catchment (High Atlas,Morocco)

This study aimed to quantify possible climate change impacts on runoff for the Rheraya catchment (225 km²) located in the High Atlas Mountains of Morocco, south of Marrakech city. Two monthly water balance models, including a snow module, were considered to reproduce the monthly surface runoff for the period 1989?2009. Additionally, an ensemble of five regional climate models from the Med-CORDEX initiative was considered to evaluate future changes in precipitation and temperature, according to the two emissions scenarios RCP4.5 and RCP8.5. The future projections for the period 2049?2065 under the two scenarios indicate higher temperatures (+1.4°C to +2.6°C) and a decrease in total precipitation (?22% to ?31%). The hydrological projections under these climate scenarios indicate a significant decrease in surface runoff (?19% to ?63%, depending on the scenario and hydrological model) mainly caused by a significant decline in snow amounts, related to reduced precipitation and increased temperature. Changes in potential evapotranspiration were not considered here, since its estimation over long periods remains a challenge in such data-sparse mountainous catchments. Further work is required to compare the results obtained with different downscaling methods and different hydrological model structures, to better reproduce the hydro-climatic behaviour of the catchment.

EDITOR M.C. Acreman

ASSOCIATE EDITOR R. Hirsch     

Climate extremes in South Western Siberia: past and future

In this study, the temporal and spatial trends of ten climate extreme indices were computed based on observed daily precipitation and on daily maximum and minimum temperatures at 26 weather stations in South Western Siberia during the period 1969–2011 and, based on projected daily maximum and minimum temperatures, during 2021–2050. The Mann–Kendall test was employed to analyze the temporal trend and a combination of multiple linear regressions and semivariogram functions were used to evaluate the regional spatial trends and the local spatial variability of climate extremes, respectively. The results show that the temperature-based climate extremes increase at a 0.05 significance level while none of the precipitation-based climate extremes did. Spatially, dominant gradients are observed along latitude: The northern taiga vegetation zone experiences a colder and wetter climate while the southern forest steppe zone is drier and hotter. Over time, a tendency towards homogenization of the regional climate is observed through a decrease of the spatial variability for most climate extreme indices. In the future, the most intense changes are anticipated for the bio-climate indicators “growing season length” and “growing degree days” in the north, while the warming indicators, “warm day” and “warm night” are expected to be high to the south.     

Changes in daily temperature and precipitation extremes in the Yellow River Basin, China

Spatiotemporal changes in climatic extremes in the Yellow River Basin from 1959 to 2008 were investigated on the basis of a suite of 27 climatic indices derived from daily temperature and precipitation data from 75 meteorological stations with the help of the Mann–Kendall test, linear regression method and GIS technique. Furthermore, the changes in the probability distribution of the extreme indices were examined. The results indicate: (1) The whole basin is dominated by significant increase in the frequency of warm days and warm nights, and dominated by significant decrease in the frequency of cold days and cold nights. Although trends in absolute temperature indices show less spatial coherence compared with that in the percentile-based temperature indices, overall increasing trends can be found in Max Tmax (TXx), Min Tmax (TXn), Max Tmin (TNx) and Min Tmin (TNn). (2) Although the spatial patterns and the number of stations with significant changes for threshold and duration temperature indices are also not identical, general positive trends in warm indices (i.e., summer days (SU25), tropical nights (TR20), warm spell duration indicator and growing season length) and negative trends in cold indices (i.e., frost days, ice days and cold spell duration indicator) can be found in the basin. Annual nighttime temperature has increased at a faster rate than that in daytime temperature, leading to obvious decrease in diurnal temperature range. (3) The changes in precipitation indices are much weaker and less spatially coherent compared with these of temperature indices. For all precipitation indices, only few stations are characterized by significantly change in extreme precipitation, and their spatial patterns are always characterized by irregular and insignificant positive and negative changes. However, generally, changes in precipitation extremes present drying trends, although most of the changes are insignificant. (4) Results at seasonal scale show that warming trends occur for all seasons, particularly in winter. Different from that in other three seasons, general positive trends in max 1-day precipitation (Rx1DAY) and max 5-day precipitation (Rx5DAY) are found in winter. Analysis of changes in probability distributions of indices for 1959–1983 and 1984–2008 indicate a remarkable shift toward warmer condition and a less pronounced tendency toward drier condition during the past decades. The results can provide beneficial reference to water resource and eco-environment management strategies in the Yellow River Basin for associated policymakers and stakeholders.     

Assessment of the impact of climate change on flow regime at multiple temporal scales and potential ecological implications in an alpine river

The source region of Yellow river is an alpine river sensitive to climate changes, but the potential effects of climate change on hydrological regime characteristics and ecological implications are less understood. This study aims to assess the response of the alterations in the flow regimes over the source region of Yellow river to climate change using Soil and Water Integrated Model driven by different Global Circulation Models (GFDL-ESM2M, IPSL-CM5A-LR and MIROC-ESM-CHEM) under three Representative Concentration Pathway emission scenarios (RCP2.6, RCP4.5 and RCP8.5). Indicators of hydrological alteration and River impact index are employed to evaluate streamflow regime alterations at multiple temporal scales. Results show that the magnitude of monthly and annual streamflow except May, the magnitude and duration of the annual extreme, and the number of reversals are projected to increase in the near future period (2020–2049) and far future period (2070–2099) compared to the baseline period (1971–2000). The timing of annual maximum flows is expected to shift backwards. The source region of Yellow river is expected to undergo low change degree as per the scenarios RCP2.6 for both two future periods and under the scenarios RCP4.5 for the near future period, whereas high change degree under RCP4.5 and RCP8.5 in the far period on the daily scale. On the monthly scale, climate changes mainly have effects on river flow magnitude and timing. The basin would suffer an incipient impact alteration in the far period under RCP4.5 and RCP8.5, while low impact in other scenarios. These changes in flow regimes could have several positive impacts on aquatic ecosystems in the near period but more detrimental effects in the far period.

     

Wintertime Seasonal Scale Simulation over Western Himalaya Using RegCM3

The Himalayan region of north India is composed of complex mountain ranges with different altitudes and orientations, causing prevailing weather conditions to be complex. Wintertime eastward moving synoptic weather systems `Western Disturbances' (WDs) yield large amounts of precipitation over this region. Numerous micro/mesoscale circulations become generated along with prevailing weather due to surface heterogeneity and land-use variability of the Himalayan region. WDs along with these circulations may give rise to very adverse weather conditions over the region. Intraseasonal variability of surface climate over the Himalayas is studied using regional climate model (RegCM3) with 60 km resolution. A 6-month (Oct. 1999–Mar. 2000) period, as this period has received an enormous amount of precipitation in the form of snow, is considered to study surface climate variability in terms of temperature, precipitation and snow amount. Model simulations show cold bias over the Himalayan region and warm bias over the northwest India. Average monthly distribution of temperature indicates that a controlled experiment could capture the areas of lowest temperature regime. Precipitation fields could be simulated only up to a certain degree of satisfaction and the influence of topographic elevation and valleys needs to be seen. RegCM3 provides a representation of resolvable atmospheric circulations that results in explaining mean variability during winter.     

Assessing the impact of climate variability and human activities on streamflow from the Wuding River basin in China

Located in the Loess Plateau of China, the Wuding River basin (30 261 km²) contributes significantly to the total sediment yield in the Yellow River. To reduce sediment yield from the catchment, large-scale soil conservation measures have been implemented in the last four decades. These included building terraces and sediment-trapping dams and changing land cover by planting trees and improving pastures. It is important to assess the impact of these measures on the hydrology of the catchment and to provide a scientific basis for future soil conservation planning. The non-parametric Mann–Kendall–Sneyers rank test was employed to detect trends and changes in annual streamflow for the period of 1961 to 1997. Two methods were used to assess the impact of climate variability on mean annual streamflow. The first is based on a framework describing the sensitivity of annual streamflow to precipitation and potential evaporation, and the second relies on relationships between annual streamflow and precipitation. The two methods produced consistent results. A significant downward trend was found for annual streamflow, and an abrupt change occurred in 1972. The reduction in annual streamflow between 1972 and 1997 was 42% compared with the baseline period (1961–1971). Flood-season streamflow showed an even greater reduction of 49%. The streamflow regime of the catchment showed a relative reduction of 31% for most percentile flows, except for low flows, which showed a 57% reduction. The soil conservation measures reduced streamflow variability, leading to more uniform streamflow. It was estimated that the soil conservation measures account for 87% of the total reduction in mean annual streamflow in the period of 1972 to 1997, and the reduction due to changes in precipitation and potential evaporation was 13%. Copyright © 2007 John Wiley & Sons, Ltd.     

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.     

Spatial and temporal variation of extreme precipitation indices in the Yangtze River basin, China

Regional characteristics of extreme precipitation indices (EPI) of precipitation magnitude, intensity and persistence were analyzed based on a daily rainfall dataset of 135 stations during the period of 1961–2010 in the Yangtze River basin, China. The spatial distribution of temporal trends of the selected indices was regionally mapped and investigated by using non-parametric test method. Future projections of EPI changes derived from the output of general circulation model (HadCM3) under the SRES A2 and B2 emission scenarios were downscaled and analyzed. The results show that: (a) there is not a general significant increasing or decreasing trend in EPI for the Yangtze River basin based on historical recorded data; (b) the automated statistical downscaling method-based precipitation captures some spatial distribution of the EPI and the bias correction can improve the simulation results; (c) a mixed pattern of positive and negative changes is observed in most of the nine indices under both scenarios in the first half of twenty-first century, and they increase continuously in the second half of twenty-first century; and (d) the concurrent increase in the heavy rain and drought indices indicates the possibility of the sudden change from drought to water logging in the lower region of Yangtze River basin.     

The spatial and temporal analysis of precipitation concentration and dry spell in Qinghai,northwest China

Understanding precipitation variations from various aspects is important for the assessment of drought risk and the utilization of water resources. The precipitation concentration index (PCI) and the concentration index (CI) were used to investigate/quantify the heterogeneity of the monthly and daily rainfall in Qinghai province that is part of northwestern China, respectively. The precipitation concentration in Qinghai shows a significant irregularity of the monthly rainfall distribution and highly homogeneous distribution of the daily rainfall. It is found that PCI and CI show negative trends at most stations. Meanwhile, the spatial and temporal variation of nine dry spell (DS) indices are analyzed. From the spatial perspective, drought in the northwestern area is much severer than that in other areas of Qinghai. According to the results of temporal analysis by using the Mann–Kendall test, the number of very long DSs, maximum length of DS, mean length of DSs, and the total dry days of extreme DS all decrease. All these results verify that the warm dry climatic pattern in Qinghai can be changed into the warm wet climatic pattern.     

An ensemble approach for the analysis of extreme rainfall under climate change in Naples (Italy)

In the present paper, an ensemble approach is proposed to estimate possible modifications caused by climate changes in the extreme precipitation regime, with the rain gauge Napoli Servizio Idrografico (Naples, Italy) chosen as test case. The proposed research, focused on the analysis of extremes on the basis of climate model simulations and rainfall observations, is structured in several consecutive steps. In the first step, all the dynamically downscaled EURO‐CORDEX simulations at about 12 km horizontal resolution are collected for the current period 1971–2000 and the future period 2071–2100, for the RCP4.5 and the RCP8.5 concentration scenarios. In the second step, the significance of climate change effects on extreme precipitation is statistically tested by comparing current and future simulated data and bias‐correction is performed by means of a novel approach based on a combination of simple delta change and quantile delta mapping, in compliance with the storm index method. In the third step, two different ensemble models are proposed, accounting for the variabilities given by the use of different climate models and for their hindcast performances. Finally, the ensemble models are used to build novel intensity–duration–frequency curves, and their effects on the early warning system thresholds for the area of interest are evaluated.     

Spatio-temporal changes of precipitation and temperature over the Pearl River basin based on CMIP5 multi-model ensemble

Projections of changes in climate are important in assessing the potential impacts of climate change on natural and social systems. However, current knowledge on assembling different GCMs to estimate future climate change over the Pear River basin is still limited so far. This study examined the capability of BMA and arithmetic mean (AM) method in assembling precipitation and temperature from CMIP5 under RCP2.6, RCP4.5 and RCP8.5 scenarios over the Pearl River basin. Results show that the BMA outperforms the traditional AM method. Precipitation tends to increase over the basin under RCP2.6 and RCP4.5 scenarios, whereas decrease under RCP8.5. The most remarkable increase of precipitation is found in the northern region under RCP2.6 scenario. The linear trend of the monthly mean near-surface air temperature increases with the growing CO₂ concentration. The warming trends in four seasons are distinct. The warming rate is prominent in summer and spring than that in other season, meanwhile it is larger in western region than in other parts of the basin. The findings can provide beneficial reference to water resources and agriculture management strategies, as well as the adaptation and mitigation strategies for floods and droughts under the context of global climate change.     

Impacts of climate change and human activities on surface runoff in the Dongjiang River basin of China

Observed rainfall and flow data from the Dongjiang River basin in humid southern China were used to investigate runoff changes during low‐flow and flooding periods and in annual flows over the past 45 years. We first applied the non‐parametric Mann–Kendall rank statistic method to analyze the change trend in precipitation, surface runoff and pan evaporation in those three periods. Findings showed that only the surface runoff in the low‐flow period increased significantly, which was due to a combination of increased precipitation and decreased pan evaporation. The Pettitt–Mann–Whitney statistical test results showed that 1973 and 1978 were the change points for the low‐flow period runoff in the Boluo sub‐catchment and in the Qilinzui sub‐catchment, respectively. Most importantly, we have developed a framework to separate the effects of climate change and human activities on the changes in surface runoff based on the back‐propagation artificial neural network (BP‐ANN) method from this research. Analyses from this study indicated that climate variabilities such as changes in precipitation and evaporation, and human activities such as reservoir operations, each accounted for about 50% of the runoff change in the low‐flow period in the study basin. Copyright © 2010 John Wiley & Sons, Ltd.     

Quantitative assessment of the impact of climate variability and human activities on runoff changes: a case study in four catchments of the Haihe River basin,China

Quantitative evaluation of the effect of climate variability and human activities on runoff is of great importance for water resources planning and management in terms of maintaining the ecosystem integrity and sustaining the society development. In this paper, hydro‐climatic data from four catchments (i.e. Luanhe River catchment, Chaohe River catchment, Hutuo River catchment and Zhanghe River catchment) in the Haihe River basin from 1957 to 2000 were used to quantitatively attribute the hydrological response (i.e. runoff) to climate change and human activities separately. To separate the attributes, the temporal trends of annual precipitation, potential evapotranspiration (PET) and runoff during 1957–2000 were first explored by the Mann–Kendall test. Despite that only Hutuo River catchment was dominated by a significant negative trend in annual precipitation, all four catchments presented significant negative trend in annual runoff varying from ?0.859 (Chaohe River) to ?1.996 mm a^?1 (Zhanghe River). Change points in 1977 and 1979 are detected by precipitation–runoff double cumulative curves method and Pettitt's test for Zhanghe River and the other three rivers, respectively, and are adopted to divide data set into two study periods as the pre‐change period and post‐change period. Three methods including hydrological model method, hydrological sensitivity analysis method and climate elasticity method were calibrated with the hydro‐climatic data during the pre‐change period. Then, hydrological runoff response to climate variability and human activities was quantitatively evaluated with the help of the three methods and based on the assumption that climate and human activities are the only drivers for streamflow and are independent of each other. Similar estimates of anthropogenic and climatic effects on runoff for catchments considered can be obtained from the three methods. We found that human activities were the main driving factors for the decline in annual runoff in Luanhe River catchment, Chaohe River catchment and Zhanghe River catchment, accounting for over 50% of runoff reduction. However, climate variability should be responsible for the decrease in annual runoff in the Hutuo River catchment. Copyright © 2012 John Wiley & Sons, Ltd.