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   总被引：2，自引：0，他引：2  

Weiguang Wang  Quanxi Shao  Tao Yang  Shizhang Peng  Wanqiu Xing  Fengchao Sun  Yufeng Luo 《水文研究》2013,27(8):1158-1174

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.  相似文献   

Long‐term discharge prediction for the Turnu Severin station (the Danube) using a linear autoregressive model     

Pavla Pekarova  Jan Pekar 《水文研究》2006,20(5):1217-1228

The long‐term trends of yearly discharge time series and runoff variability at seven stations along the River Danube are identified. The results of statistical analysis of discharge time series indicate the period around the year 1860 was the driest decade in central and eastern Europe since 1840. In these years, the mean annual air temperature in central Europe was lower by about 1 °C compared with the 1990s. It is important to notice that the two driest decades (around 1860s and 1990s) of the instrumental era occurred in very different temperature conditions. The 28–31 years; 20–21 years; 14 years, as well as 4·2, 3·6, and 2·4 years fluctuations of annual discharge in the River Danube were found. Also, the long‐term streamflow prediction based on stochastic modelling methods is treated. Harmonic models and the Box–Jenkins methods were used. The predictions of yearly River Danube discharge time series were made for two decades ahead. From the stochastic models it follows that the annual discharge in the Danube at Turnu Severin station should reach its local maximum within the years 2004–06. The period 2015–19 should be dry. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

Determining the relative contributions of climate change and multiple human activities to variations of sediment regime in the Minjiang River,China   总被引：1，自引：0，他引：1  

Qiang Tang  Xiubin He  Yuhai Bao  Xinbao Zhang  Feng Guo  Hongwei Zhu 《水文研究》2013,27(25):3547-3559

In‐stream sediment transport plays an important role in delivery of sediment‐associated terrestrial elements. Investigating the history of fluvial sediment regime responding to changes in natural and anthropogenic driving forces provides a theoretical basis for establishment of optimal strategies on catchment management. The present study aims to systematically detect the patterns of change in sediment load at two key hydrological stations (Pengshan and Gaochang) in the Minjiang River and quantitatively evaluate the relative contributions of regional precipitation change and multiple local human activities to the observed sediment variations. Abrupt change in annual sediment load was detected in 1990 at Pengshan and in 1968, 1980 and 1992 at Gaochang. Compared with the baseline period of 1957–1990, precipitation decline and human activities had respectively contributed to 5 × 10⁶ t and 2 × 10⁶ t of reduction in mean annual sediment load at Pengshan during 1991–2007. For the entire Minjiang basin, taking 1956–1968 as the baseline period, precipitation decline and human activities had relatively contributed to 10 × 10⁶ t and 18 × 10⁶ t of reduction in mean annual sediment load at Gaochang during 1969–1980. During 1981–1992, precipitation decline had relatively contributed to 5 × 10⁶ t of reduction in mean annual sediment load, but human activities had led to 3 × 10⁶ t of increase in mean annual sediment load. During 1993–2009, 13 × 10⁶ t and 17 × 10⁶ t of reduction in mean annual sediment load may be attributed to precipitation decline and human activities, respectively. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

Effect of modelling scale on the assessment of climate change impact on river runoff     

Mikołaj Piniewski  Frank Voss  Ilona Bärlund  Tomasz Okruszko  Zbigniew W. Kundzewicz 《水文科学杂志》2013,58(4):737-754

Abstract

The effect of using two distributed hydrological models with different degrees of spatial aggregation on the assessment of climate change impact on river runoff was investigated. Analyses were conducted in the Narew River basin situated in northeast Poland using a global hydrological model (WaterGAP) and a catchment-scale hydrological model (SWAT). Climate change was represented in both models by projected changes in monthly temperature and precipitation between the period 2040–2069 and the baseline period, resulting from two general circulation models: IPSL-CM4 and MIROC3.2, both coupled with the SRES A2 emissions scenario. The degree of consistency between the global and the catchment model was very high for mean annual runoff, and medium for indicators of high and low runoff. It was observed that SWAT generally suggests changes of larger magnitude than WaterGAP for both climate models, but SWAT and WaterGAP were consistent as regards the direction of change in monthly runoff. The results indicate that a global model can be used in Central and Eastern European lowlands to identify hot-spots where a catchment-scale model should be applied to evaluate, e.g. the effectiveness of management options.

Editor D. Koutsoyiannis; Associate editor F.F. Hattermann

Citation Piniewski, M., Voss, F., Bärlund, I., Okruszko, T., and Kundzewicz. Z.W., 2013. Effect of modelling scale on the assessment of climate change impact on river runoff. Hydrological Sciences Journal, 58 (4), 737–754.  相似文献   

Standard normal homogeneity test as a tool to detect change points in climate-related river discharge variation: case study of the Kupa River Basin     

《水文科学杂志》2012,57(2):227-241

ABSTRACT

The study addresses homogeneity testing of annual discharge time series for eight hydrological stations and five annual climate time series for one weather station in the Kupa River Basin, between Slovenia and Croatia, and global annual average surface temperature time series for the period 1961–2010. The standard normal homogeneity test (SNHT) was used to detect both abrupt and gradual linear trend homogeneity breaks. The results reveal natural change points at the beginning of the 1980s. Absolute homogeneity testing of average annual weather station-level air pressure, annual precipitation, differences between precipitation totals and potential evapotranspiration and surface runoff from the independent observation time series confirmed an abrupt shift, also at the beginning of the 1980s. The trend of local air temperature for 1985–2000, which partly coincides with global surface temperature trend for 1974–2005, strengthened the river discharge regime shift since the beginning of the 1980s. These results could improve climate variation monitoring and estimation of the impact of climate variation on the environment in the area. Generally, an indication of climate regime change points and an assessment of their duration could provide significant benefits for the society.  相似文献   

Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization     

Evdokia Tapoglou  Ioannis C. Trichakis  Zoi Dokou  Ioannis K. Nikolos 《水文科学杂志》2013,58(6):1225-1239

Abstract

Artificial neural networks (ANNs) have recently been used to predict the hydraulic head in well locations. In the present work, the particle swarm optimization (PSO) algorithm was used to train a feed-forward multi-layer ANN for the simulation of hydraulic head change at an observation well in the region of Agia, Chania, Greece. Three variants of the PSO algorithm were considered, the classic one with inertia weight improvement, PSO with time varying acceleration coefficients (PSO-TVAC) and global best PSO (GLBest-PSO). The best performance was achieved by GLBest-PSO when implemented using field data from the region of interest, providing improved training results compared to the back-propagation training algorithm. The trained ANN was subsequently used for mid-term prediction of the hydraulic head, as well as for the study of three climate change scenarios. Data time series were created using a stochastic weather generator, and the scenarios were examined for the period 2010–2020.