Changes in groundwater runoff under the effect of climate and anthropogenic impact

Quantitative relationships between groundwater runoff and other water balance components are obtained. These relationships enable the prediction of changes in groundwater nourishment in different natural-geographic zones on the Earth because of global climatic changes and intense anthropogenic impact on the water regime of different areas. Groundwater runoff values (natural groundwater resources) in individual river basins are estimated. Digital maps (grid-models) of the space and time distribution of water balance elements (based on GIS-technology) are constructed for major river basins in European Russia, and river runoff is calculated in each grid node in river basins with a step of 0.1° in geographic coordinates. The values of major water balance components, thus related with one another, serve as the basis for their spatial and temporal analysis and cartographic representation. The proposed method was tested against data on Volga basin where long-term observational data on water balance elements are available in a number of hydrometric sections.     

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.     

Assessment of possible anthropogenic changes in the runoff of the Syr Darya River on the basis of a mathematical model

The development of a simulation model of water and salt balance for river basins with the predominance of irrigated agriculture is considered. The results of a simulation experiment for the assessment of possible anthropogenic changes in Syr Darya River runoff for some scenarios of the implementation of a set of resource-saving and environment protection measures are given.     

气候变化和人类活动对鄱阳湖流域赣江径流影响的定量分析

气候变化和人类活动对流域径流影响的定量研究是当前研究的热点,赣江作为鄱阳湖流域最大的子流域,径流变化对鄱阳湖湿地水生态系统具有重要的影响.利用Mann-Kendall突变检验分析了赣江流域径流1955—2010年间演变趋势,再分别应用统计方法和IHACRES集总式模型分析气候要素和人类活动对径流的影响.研究表明IHACRES能够较好地模拟赣江流域径流,适用于中亚热带湿润季风气候区.Mann-Kendall突变检验表明赣江流域径流在1979年发生突变,可划分为1955—1979年和1980—2010年两个时段.降水是影响赣江流域径流年际变化的主要因素,而土地利用等人类活动的影响并不明显.水库建设显著影响赣江径流的季节分配,1980—2010年间人类活动影响更加显著,其中45%的年份秋季径流增加50%以上,26%的年份秋季径流增加超过100%,其中1989年的秋季径流增加幅度达到320%.     

Assessment on variability of extreme climate events for the Upper Thames River basin in Canada

Climate change may affect magnitude and frequency of regional extreme events with possibility of serious impacts on the existing infrastructure systems. This study investigates how the current spatial and temporal variations of extreme events are affected by climate change in the Upper Thames River basin, Ontario, Canada. A weather generator model is implemented to obtain daily time series of three climate variables for two future climate scenarios. The daily time series are disaggregated into hourly to capture characteristics of intense and rapidly changing storms. The maximum annual precipitation events for five short durations, 6‐, 12‐, 24‐, 48‐, and 72‐h durations, at each station are extracted from the generated hourly data. The frequency and seasonality analyses are conducted to investigate the temporal and spatial variability of extreme precipitation events corresponding to each duration. In addition, this study investigates the impacts of increase in temperature using reliability, resilience, and vulnerability. The results indicate that the extreme precipitation events under climate change will occur earlier than in the past. In addition, episodes of extremely high temperature may last longer up to 19·7% than under the no‐change climate scenario. This study points out that the revision of the design storms (e.g. 100‐ or 250‐year return period) is warranted for the west and the south east region of the basin. Copyright © 2011 John Wiley & Sons, Ltd.     

Quantitative assessment of the impact of climate variability and human activities on runoff changes for the upper reaches of Weihe River

In the wake of global and regional climate change and heightened human activities, runoff from some rivers in the world, especially in the arid and semi-arid regions, has significantly decreased. To reveal the varying characteristics leading to the change in runoff, detecting the influencing factors has been important in recent scientific discussions for water resources management in drainage basins. In this paper, an investigation into attributing the runoff response to climate change and human activities were conducted in two catchments (Wushan and Shetang), situated in the upper reaches of Weihe River in China. Prior to the identification of the factors that influenced runoff changes, the Mann–Kendall test was adopted to identify the trends in hydro-climate series. Also, change-points in the annual runoff were detected through Pettitt’s test and the precipitation–runoff double cumulative curve method. It is found that both catchments presented significant negative trend in annual runoff and the detected change-point in runoff occurs in 1993. Hence, the pre-change period and post-change period are defined before and after 1993, respectively. Then, runoff response to climate change and human activities was quantitatively evaluated on the basis of hydrologic sensitivity analysis and hydrologic model simulation. They provided similar estimates of the percentage change in mean annual runoff for the post-change period over the considered catchments. It is found that the decline in annual runoff over both catchments can be mainly attributed to the human activities, the reduction percentages due to human activities range from 59 to 77 %. The results of this study can provide a reference for the development, utilization and management of the regional water resources and ecological environment protection.     

Impacts of climate variability on stream-flow in the Yellow River

This paper examines the impacts of climate variability upon the regional hydrological regimes of the Yellow River in China. Results indicate that the average annual precipitation is 494·8 mm in La Niña years and only 408·8 mm in El Niño years. The difference is 86·0 mm, or 18·8% over the long-term average. The stream-flows in the La Niña years are higher than that in El Niño years: 9·2% at the Lan-Zhou station, 9·5% for Tou-Dao-Guai station, 11·8% for Long-Men, 17·6% for San-Men-Xia, 19·2% at the Hua-Yuan-Hou station, and 22·0% at the Li-Jin station. Both precipitation and stream-flow responses show temporal and spatial patterns. The relationship among the stream-flow, precipitation, and temperature, which was obtained by ArcGIS Geostatistical Analyst based on observed data, indicates stream-flow is sensitive to both precipitation and temperature. For small precipitation increases (less than 13%), the stream-flow percentage change is less than the precipitation change for the Yellow River. The results of this paper can be used as a reference for watershed water resources planning and management to maintain the healthy life and proper function of the river. Copyright © 2007 John Wiley & Sons, Ltd.     

Attributing runoff changes to climate variability and human activities: uncertainty analysis using four monthly water balance models

Hydrological simulations to delineate the impacts of climate variability and human activities are subjected to uncertainties related to both parameter and structure of the hydrological models. To analyze the impact of these uncertainties on the model performance and to yield more reliable simulation results, a global calibration and multimodel combination method that integrates the Shuffled Complex Evolution Metropolis (SCEM) and Bayesian Model Averaging of four monthly water balance models was proposed. The method was applied to the Weihe River Basin, the largest tributary of the Yellow River, to determine the contribution of climate variability and human activities to runoff changes. The change point, which was used to determine the baseline period (1956–1990) and human-impacted period (1991–2009), was derived using both cumulative curve and Pettitt’s test. Results show that the combination method from SCEM provides more skillful deterministic predictions than the best calibrated individual model, resulting in the smallest uncertainty interval of runoff changes attributed to climate variability and human activities. This combination methodology provides a practical and flexible tool for attribution of runoff changes to climate variability and human activities by hydrological models.     

Assessment of the statistical significance of global changes in the annual river runoff in XXI century due to possible anthropogenic warming of climate

A number of uncertainties of forecasts of changes in the annual runoff depths at global scale, obtained using information on results of integration of 21 IPCC climate models is studied. Following possible errors of these forecasts are calculated: errors of models; differences between main (IPCC) scenarios of emission of greenhouse gases in the atmosphere and resultant changes of global temperatures; mistakes in estimates of average long-term observed values of the runoff depths for the “control” period. Global maps of a “significance index” of forecasted changes in the runoff depths (estimations of changes in the annual runoff depths divided by mean square root values of errors of these estimations) for 2025, 2050, 2075 and 2100 are presented. It is shown that the most significant global changes of the runoff depths (growth in the north of Eastern Siberia, of the Russian Far East, of North America, falling in the “Greater Mediterranean Region”) are predicted for the second quarter of 21st century. Further changes of the runoff amplify only in the Amazon basin (reduction, by 2075). Almost everywhere else (including almost all European territory of Russia, Western Siberia, south of Eastern Siberia and of the Far East) the significance of changes in the runoff depths during 21st century is negligible.     

The role of climate change and human interventions in affecting watershed runoff responses

Identifying the role of the two main driving factors—climate change and human interventions—in influencing runoff processes is essential for sustainable water resources management. For this purpose, runoff regime change detection methods were used to divide the available hydroclimatic variables into a baseline and a disturbed period. We applied hydrological modelling and the climate elasticity of runoff method to determine the contribution of climate change and human interventions to changes in runoff. The hydrological model, SWAT, was calibrated during the baseline period and used to simulate the naturalized runoff pattern for the disturbed period. Significant changes in runoff in the study watershed were detected from 1982, suggesting that human interventions play a dominant role in influencing runoff. The combined effects of climate change and human interventions resulted in a 41.3 mm (23.9%) decrease in runoff during the disturbed period, contributing about 40% and 60% to the total runoff change, respectively. Furthermore, analysis of changes in land cover dynamics in the watershed over the past four decades supported these changes in runoff. Contrary to other decades, the discrepancy between naturalized and observed runoff was small in the 2010s, likely due to increased baseflow as a result of storage and/or release of excess water during the dry season. This study contributes to our understanding of how climate change and human interventions affect hydrological responses of watersheds, which is important for future sustainable water management and drought adaptation.     

Assessment of future runoff trends under multiple climate change scenarios in the Willamette River Basin,Oregon, USA

We investigated trends in future seasonal runoff components in the Willamette River Basin (WRB) of Oregon for the twenty‐first century. Statistically downscaled climate projections by Climate Impacts Group (CIG), eight different global climate model (GCM) simulations with two different greenhouse gas (GHG) emission scenarios, (A1B and B1), were used as inputs for the US Geological Survey's Precipitation Runoff Modelling System. Ensemble mean results show negative trends in spring (March, April and May) and summer (June, July and August) runoff and positive trends in fall (September, October and November) and winter (December, January and February) runoff for 2000–2099. This is a result of temperature controls on the snowpack and declining summer and increasing winter precipitation. With temperature increases throughout the basin, snow water equivalent (SWE) is projected to decline consistently for all seasons. The decreases in the centre of timing and 7‐day low flows and increases in the top 5% flow are caused by the earlier snowmelt in spring, decreases in summer runoff and increases in fall and winter runoff, respectively. Winter runoff changes are more pronounced in higher elevations than in low elevations in winter. Seasonal runoff trends are associated with the complex interactions of climatic and topographic variables. While SWE is the most important explanatory variable for spring and winter runoff trends, precipitation has the strongest influence on fall runoff. Spatial error regression models that incorporate spatial dependence better explain the variations of runoff trends than ordinary least‐squares (OLS) multiple regression models. Our results show that long‐term trends of water balance components in the WRB could be highly affected by anthropogenic climate change, but the direction and magnitude of such changes are highly dependent on the interactions between climate change and land surface hydrology. This suggests a need for spatially explicit adaptive water resource management within the WRB under climate change. Copyright © 2010 John Wiley & Sons, Ltd.     

Assessment of the total and anthropogenic organic matter runoff from the territory of the Commonwealth of Independent States

This article provides an assessment of river runoff of organic matter into seas from the territory of the Commonwealth of Independent States, its anthropogenic component and tendencies in their changes over certain periods from 1936 to 2000. The distribution within a year, modules, runoff ratio of organic matter and major ions are discussed.     

Long-term variability of nitrate and nitrite nitrogen runoff in the Amur River near Khabarovsk

The long-term dynamics of the runoff of mineral oxidized forms of nitrogen in the Amur River near Khabarovsk City is discussed. An increase in nitrate nitrogen runoff by a factor of 2.1 is recorded as compared to the period of 1981–2000. It is shown that the Sungari River is now responsible for the formation of the anthropogenic component of the runoff of mineral nitrogen forms.     

Impacts of climate change and hydraulic structures on runoff and sediment discharge in the middle Yellow River

Due to climate change and its aggravation by human activities (e.g. hydraulic structures) over the past several decades, the hydrological conditions in the middle Yellow River have markedly changed, leading to a sharp decrease in runoff and sediment discharge. This paper focused on the impacts of climate change and hydraulic structures on runoff and sediment discharge, and the study area was located in the 3246 km² Huangfuchuan (HFC) River basin. Changes in annual runoff and sediment discharge were initially analysed by using the Mann–Kendall trend test and Pettitt change point test methods. Subsequently, periods of natural and disturbed states were defined. The results showed that both the annual runoff and sediment discharge presented statistically significant decreasing trends. However, compared with the less remarkable decline in annual rainfall, it was inferred that hydraulic structures might be another important cause for the sharp decrease in runoff and sediment discharge in this region. Consequently, sediment‐trapping dams (STDs, a type of large‐sized check dam used to prevent sediment from entering the Yellow River main stem) were considered in this study. Through evaluating the impacts of the variation in rainfall patterns (i.e. amount and intensity) and the STD construction, a positive correlation between rainfall intensity and current STD construction was found. This paper revealed that future soil and water conservation measures should focus on areas with higher average annual rainfall and more rainstorm hours. Copyright © 2015 John Wiley & Sons, Ltd.     

Response of runoff to climate change in the Wei River basin,China

Abstract

Climate change will likely have severe effects on water shortages, flood disasters and the deterioration of aquatic systems. In this study, the hydrological response to climate change was assessed in the Wei River basin (WRB), China. The statistical downscaling method (SDSM) was used to downscale regional climate change scenarios on the basis of the outputs of three general circulation models (GCMs) and two emissions scenarios. Driven by these scenarios, the Soil and Water Assessment Tool (SWAT) was set up, calibrated and validated to assess the impact of climate change on hydrological processes of the WRB. The results showed that the average annual runoff in the periods 2046–2065 and 2081–2100 would increase by 12.4% and 45%, respectively, relative to the baseline period 1961–2008. Low flows would be much lower, while high flows would be much higher, which means there would be more extreme events of droughts and floods. The results exhibited consistency in the spatial distribution of runoff change under most scenarios, with decreased runoff in the upstream regions, and increases in the mid- and lower reaches of the WRB.

Editor Z.W. Kundzewicz; Associate editor D. Yang     

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.     

Assessment of alternative adsorption models and global sensitivity analysis to characterize hexavalent chromium loss from soil to surface runoff

We investigate our ability to assess transfer of hexavalent chromium, Cr(VI), from the soil to surface runoff by considering the effect of coupling diverse adsorption models with a two‐layer solute transfer model. Our analyses are grounded on a set of two experiments associated with soils characterized by diverse particle size distributions. Our study is motivated by the observation that Cr(VI) is receiving much attention for the assessment of environmental risks due to its high solubility, mobility, and toxicological significance. Adsorption of Cr(VI) is considered to be at equilibrium in the mixing layer under our experimental conditions. Four adsorption models, that is, the Langmuir, Freundlich, Temkin, and linear models, constitute our set of alternative (competing) mathematical formulations. Experimental results reveal that the soil samples characterized by the finest grain sizes are associated with the highest release of Cr(VI) to runoff. We compare the relative abilities of the four models to interpret experimental results through maximum likelihood model calibration and four model identification criteria (i.e., the Akaike information criteria [AIC and AIC_C] and the Bayesian and Kashyap information criteria). Our study results enable us to rank the tested models on the basis of a set of posterior weights assigned to each of them. A classical variance‐based global sensitivity analysis is then performed to assess the relative importance of the uncertain parameters associated with each of the models considered, within subregions of the parameter space. In this context, the modelling strategy resulting from coupling the Langmuir isotherm with a two‐layer solute transfer model is then evaluated as the most skilful for the overall interpretation of both sets of experiments. Our results document that (a) the depth of the mixing layer is the most influential factor for all models tested, with the exception of the Freundlich isotherm, and (b) the total sensitivity of the adsorption parameters varies in time, with a trend to increase as time progresses for all of the models. These results suggest that adsorption has a significant effect on the uncertainty associated with the release of Cr(VI) from the soil to the surface runoff component.     

Estimating the sensitivity of mean annual runoff to climate change using selected hydrological models

Hydrological model sensitivity to climate change can be defined as the response of a particular hydrological model to a known quantum of climate change. This paper estimates the hydrological sensitivity, measured as the percentage change in mean annual runoff, of two lumped parameter rainfall-runoff models, SIMHYD and AWBM and an empirical model, Zhang01, to changes in rainfall and potential evaporation. These changes are estimated for 22 Australian catchments covering a range of climates, from cool temperate to tropical and moist to arid. The results show that the models display different sensitivities to both rainfall and potential evaporation changes. The SIMHYD, AWBM and Zhang01 models show mean sensitivities of 2.4%, 2.5% and 2.1% change in mean annual flow for every 1% change in mean annual rainfall, respectively. All rainfall sensitivities have a lower limit of 1.8% and show upper limits of 4.1%, 3.4% and 2.5%, respectively. The results for potential evaporation change are −0.5%, −0.8% and −1.0% for every 1% increase in mean annual potential evaporation, respectively, with changes rainfall being approximately 3–5 times more sensitive than changes in potential evaporation for each 1% change in climate. Despite these differences, the results show similar correlations for several catchment characteristics. The most significant relationship is between percent change in annual rainfall and potential evaporation to the catchment runoff coefficient. The sensitivity of both A and B factors decreases with an increasing runoff coefficient, as does the uncertainty in this relationship. The results suggest that a first-order relationship can be used to give a rough estimate of changes in runoff using estimates of change in rainfall and potential evaporation representing small to modest changes in climate. Further work will develop these methods further, by investigating other regions and changes on the subannual scale.     

Assessing the effect of climate change on mean annual runoff in the Songhua River basin,China

Influences of climatic change on the components of global hydrological cycle, including runoff and evapotranspiration are significant in the mid‐ and high‐latitude basins. In this paper, the effect of climatic change on annual runoff is evaluated in a large basin—Songhua River basin which is located in the northeast of China. A method based on Budyko‐type equation is applied to separate the contributions of climatic factors to changes in annual runoff from 1960 to 2008, which are computed by multiplying their partial derivatives by the slopes of trends in climate factors. Furthermore, annual runoff changes are predicted under IPCC SRES A2 and B2 scenarios with projections from five GCMs. The results showed that contribution of annual precipitation to annual runoff change was more significant than that of annual potential evapotranspiration in the Songhua River basin; and the factors contributing to annual potential evapotranspiration change were ranked as temperature, wind speed, vapour pressure, and sunshine duration. In the 2020s, 2050s, and 2080s, changes in annual runoff estimated with the GCM projections exhibited noticeable difference and ranged from ? 8·4 to ? 16·8 mm a^?1 (?5·77 to ? 11·53% of mean annual runoff). Copyright © 2011 John Wiley & Sons, Ltd.     

The impact of climate change on runoff in the Yarlung Tsangpo River basin in the Tibetan Plateau

The Tibetan Plateau (TP) is the “water tower of Asia” and it plays a key role on both hydrology and climate for southern and eastern Asia. It is critical to explore the impact of climate change on runoff for better water resources management in the TP. However, few studies pay attention to the runoff response to climate change in large river systems on the TP, especially in data-sparse upstream area. To complement the current body of work, this study uses two rainfall-runoff models (SIMHYD and GR4J) to simulate the monthly and annual runoff in the upstream catchments of the Yarlung Tsangpo River basin (YTR) under historical (1962–2002) and future (2046–2065 A1B scenario) climate conditions. The future climate series are downscaled from a global climate model (MIROC3.2_hires) by a high resolution regional climate model (RegCM3). The two rainfall-runoff models successfully simulate the historical runoff for the eight catchments in the YTR basin, with median monthly runoff Nash–Sutcliffe Efficiency of 0.86 for SIMHYD and 0.83 for GR4J. The mean annual future temperature in eight catchments show significant increase with the median of +3.8 °C. However, the mean annual future precipitation shows decrease with the median of ?5.8 % except in Lhatse (+2.0 %). The two models show similar modeling results that the mean annual future runoff in most of catchments (seven in eight) shows decrease with the median of ?13.9 % from SIMHYD and ?15.2 % from GR4J. The results achieved in this study are not only helpful for local water resources management, but also for future water utilization planning in the lower reaches region of the Brahmaputra.