Derivation of climate elasticity of runoff to assess the effects of climate change on annual runoff

2011 ◽  
Vol 47 (7) ◽  
Author(s):  
Hanbo Yang ◽  
Dawen Yang
Keyword(s):  
Climate Change ◽  
Annual Runoff ◽  
Climate Elasticity

scholarly journals Integrated assessment of climate and human contributions to variations in streamflow in the Ten Great Gullies Basin of the Upper Yellow River, China

2020 ◽  
Vol 68 (3) ◽  
pp. 249-259
Author(s):  
Tong Liu ◽  
He Qing Huang ◽  
Ming an Shao ◽  
Jiong Cheng ◽  
Xiang Dong Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Hydrological Model ◽  
Yellow River ◽  
Annual Runoff ◽  
Integrated Method ◽  
Climate Elasticity ◽  
Relative Contribution ◽  
Pettitt Test ◽  
Monthly Runoff

AbstractClimate change and human activity are two linked factors that alter the spatiotemporal distribution of the available water. Assessing the relative contribution of the two factors on runoff changes can help the planners and managers to better formulate strategies and policies regarding regional water resources. In this work, using two typical sub-basins of the Yellow River as the study area, we first detected the trend and the breakpoint in the annual streamflow data with the Pettitt test during the period 1964–2011. Next, a Budyko-based climate elasticity model and a monthly hydrological model were employed as an integrated method to distinguish the relative contributions of climate change and human activities to the long-term changes in runoff. The results showed that a significant decline in the annual runoff occurred in the two sub-basins during the study period, and the abrupt change point in the annual runoff at the two sub-basins both occurred in 1997. The conceptual hydrological model performed well in reproducing monthly runoff time series at the two sub-basins. The Nash-Sutcliffe efficiency (NSE) between observed and simulated runoff during the validation period exceeds 0.83 for the two sub-basins. Climate elasticity method and hydrological model give consistent attribution results: human activities are the major drivers responsible for the decreased annual runoff in the Ten Great Gullies Basin. The relative contributions of climate change and human activities to the changes in the annual runoff were 22–32% and 68–78%, respectively.

scholarly journals Uncertainty in runoff based on Global Climate Model precipitation and temperature data – Part 2: Estimation and uncertainty of annual runoff and reservoir yield

2014 ◽  
Vol 11 (5) ◽  
pp. 4579-4638 ◽  
Author(s):  
M. C. Peel ◽  
R. Srikanthan ◽  
T. A. McMahon ◽  
D. J. Karoly
Keyword(s):  
Climate Change ◽  
Standard Deviation ◽  
Climate Change Impact ◽  
Global Climate ◽  
Annual Runoff ◽  
Monthly Precipitation ◽  
Change Impact ◽  
The Impact ◽  
Reservoir Yield ◽  
Precipitation And Temperature

Abstract. Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between Global Climate Models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) datasets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to approximate within-GCM uncertainty of monthly precipitation and temperature projections and assess its impact on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. To-date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2014) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from CMIP3 for use in this paper. Here we present within- and between-GCM uncertainty results in mean annual precipitation (MAP), temperature (MAT) and runoff (MAR), the standard deviation of annual precipitation (SDP) and runoff (SDR) and reservoir yield for five CMIP3 GCMs at 17 world-wide catchments. Based on 100 stochastic replicates of each GCM run at each catchment, within-GCM uncertainty was assessed in relative form as the standard deviation expressed as a percentage of the mean of the 100 replicate values of each variable. The average relative within-GCM uncertainty from the 17 catchments and 5 GCMs for 2015–2044 (A1B) were: MAP 4.2%, SDP 14.2%, MAT 0.7%, MAR 10.1% and SDR 17.6%. The Gould–Dincer Gamma procedure was applied to each annual runoff time-series for hypothetical reservoir capacities of 1× MAR and 3× MAR and the average uncertainty in reservoir yield due to within-GCM uncertainty from the 17 catchments and 5 GCMs were: 25.1% (1× MAR) and 11.9% (3× MAR). Our approximation of within-GCM uncertainty is expected to be an underestimate due to not replicating the GCM trend. However, our results indicate that within-GCM uncertainty is important when interpreting climate change impact assessments. Approximately 95% of values of MAP, SDP, MAT, MAR, SDR and reservoir yield from 1× MAR or 3× MAR capacity reservoirs are expected to fall within twice their respective relative uncertainty (standard deviation/mean). Within-GCM uncertainty has significant implications for interpreting climate change impact assessments that report future changes within our range of uncertainty for a given variable – these projected changes may be due solely to within-GCM uncertainty. Since within-GCM variability is amplified from precipitation to runoff and then to reservoir yield, climate change impact assessments that do not take into account within-GCM uncertainty risk providing water resources management decision makers with a sense of certainty that is unjustified.

scholarly journals An evaluation of the effect of future climate on runoff in the Dongjiang River basin, South China

2015 ◽  
Vol 368 ◽  
pp. 257-262
Author(s):  
K. Lin ◽  
W. Zhai ◽  
S. Huang ◽  
Z. Liu
Keyword(s):  
Climate Change ◽  
River Basin ◽  
South China ◽  
Annual Runoff ◽  
Future Climate ◽  
Weather Data ◽  
Future Climate Change ◽  
Dongjiang River ◽  
The Future ◽  
The Impact

Abstract. The impact of future climate change on the runoff for the Dongjiang River basin, South China, has been investigated with the Soil and Water Assessment Tool (SWAT). First, the SWAT model was applied in the three sub-basins of the Dongjiang River basin, and calibrated for the period of 1970–1975, and validated for the period of 1976–1985. Then the hydrological response under climate change and land use scenario in the next 40 years (2011–2050) was studied. The future weather data was generated by using the weather generators of SWAT, based on the trend of the observed data series (1966–2005). The results showed that under the future climate change and LUCC scenario, the annual runoff of the three sub-basins all decreased. Its impacts on annual runoff were –6.87%, –6.54%, and –18.16% for the Shuntian, Lantang, and Yuecheng sub-basins respectively, compared with the baseline period 1966–2005. The results of this study could be a reference for regional water resources management since Dongjiang River provides crucial water supplies to Guangdong Province and the District of Hong Kong in China.

The «rainfall-runoff» system and its long-term fluctuations in the Siverskyi Donets River Basin (Ukraine)

2021 ◽  
Author(s):  
Hanna Bolbot ◽  
Vasyl Grebin
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
River Basin ◽  
Air Temperature ◽  
River Runoff ◽  
Annual Runoff ◽  
Annual Precipitation ◽  
Spring Flood ◽  
Current Period

<p>The current patterns estimation of the water regime under climate change is one of the most urgent tasks in Ukraine and the world. Such changes are determined by fluctuations in the main climatic characteristics - precipitation and air temperature, which are defined the value of evaporation. These parameters influence on the annual runoff distribution and long-term runoff fluctuations. In particular, the annual precipitation redistribution is reflected in the corresponding changes in the river runoff.<br>The assessment of the current state and nature of changes in precipitation and river runoff of the Siverskyi Donets River Basin was made by comparing the current period (1991-2018) with the period of the climatological normal (1961-1990).<br>In general, for this area, it was defined the close relationship between the amount of precipitation and the annual runoff. Against the background of insignificant (about 1%) increase of annual precipitation in recent decades, it was revealed their redistribution by seasons and separate months. There is a decrease in precipitation in the cold period (November-February). This causes (along with other factors) a decrease in the amount of snow and, accordingly, the spring flood runoff. There are frequent cases of unexpressed spring floods of the Siverskyi Donets River Basin. The runoff during March-April (the period of spring flood within the Ukrainian part of the basin) decreased by almost a third.<br>The increase of precipitation during May-June causes a corresponding (insignificant) increase in runoff in these months. The shift of the maximum monthly amount of precipitation from May (for the period 1961-1990) to June (in the current period) is observed.<br>There is a certain threat to water supply in the region due to the shift in the minimum monthly amount of precipitation in the warm period from October to August. Compared with October, there is a higher air temperature and, accordingly, higher evaporation in August, which reduces the runoff. Such a situation is solved by rational water resources management of the basin. The possibility of replenishing water resources in the basin through the transfer runoff from the Dnieper (Dnieper-Siverskyi Donets channel) and the annual runoff redistribution in the reservoir system causes some increase in the river runoff of summer months in recent decades. This is also contributed by the activities of the river basin management structures, which control the maintenance water users' of minimum ecological flow downstream the water intakes and hydraulic structures in the rivers of the basin.<br>Therefore, in the period of current climate change, the annual runoff distribution of the Siverskyi Donets River Basin has undergone significant changes, which is related to the annual precipitation redistribution and anthropogenic load on the basin.</p>

scholarly journals SWAT-Based Runoff Simulation and Runoff Responses to Climate Change in the Headwaters of the Yellow River, China

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 509
Author(s):  
Jingwen Wu ◽  
Haiyan Zheng ◽  
Yang Xi
Keyword(s):  
Climate Change ◽  
Assessment Tool ◽  
Water Cycle ◽  
Yellow River ◽  
Annual Runoff ◽  
The Yellow River ◽  
Runoff Simulation ◽  
Alpine Regions ◽  
Slight Upward Trend ◽  
The Impact

Runoff in snowy alpine regions is sensitive to climate change in the context of global warming. Exploring the impact of climate change on the runoff in these regions is critical to understand the dynamics of the water cycle and for the improvement of water resources management. In this study, we analyzed the long-term variations in annual runoff in the headwaters region of the Yellow River (HRYR) (a typical snowy mountain region) during the period of 1956–2012. The Soil and Water Assessment Tool (SWAT) with different elevation bands was employed to assess the performance of monthly runoff simulations, and then to evaluate the impacts of climate change on runoff. The results show that the observed runoff for the hydrological stations at lower relative elevations (i.e., Maqu and Tangnaihai stations) had a downward trend, with rates of 1.91 and 1.55 mm/10 years, while a slight upward trend with a rate of 0.26 mm/10 years was observed for the hydrological station at higher elevation (i.e., Huangheyan station). We also found that the inclusion of five elevation bands could lead to more accurate runoff estimates as compared to simulation without elevation bands at monthly time steps. In addition, the dominant cause of the runoff decline across the whole HRYR was precipitation (which explained 64.2% of the decrease), rather than temperature (25.93%).

Impact of Climate Change on Water Resources in the Shiyang River Basin and the Adaptive Measures for Energy Conservation and Emission Reduction

2013 ◽  
Vol 405-408 ◽  
pp. 2167-2171 ◽  
Author(s):  
Zhou Li ◽  
Xiao Yan Li ◽  
Juan Sun
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Water Resources ◽  
Energy Conservation ◽  
Climate Change Impacts ◽  
Warming Trend ◽  
Annual Runoff ◽  
Climate Scenarios ◽  
Surface Water Resources ◽  
Precipitation And Temperature

Climate is an important factor which formed and affected surface water resources. Through sensitivity analysis of natural runoff towards climate change, assuming the main factors effect runoff are precipitation and temperature, then according to the possible tendency of climate changes in the future, set climate scenarios, and use the hydrological model simulate the changes trend of runoff under different climate scenarios, thereby analyze the climate change impacts on surface water resources. The results show that annual runoff will be increased with the increasing annual precipitation, and it will be reduced with rise of annual temperature, the sensitivity that annual runoff towards the change of precipitation and temperature are equally notable, both of them are two major factors impact on the change of runoff and the precipitation change impacts on annual runoff will be even more obvious in flood season. Last, with the global warming trend, put forward the corresponding adaptive measures of energy conservation and emissions reduction。

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