scholarly journals Streamflow into Beijing and Its Response to Climate Change and Human Activities over the Period 1956–2016

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 622 ◽  
Author(s):  
Xing Mu ◽  
Hao Wang ◽  
Yong Zhao ◽  
Huan Liu ◽  
Guohua He ◽  
...  
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Potential Evapotranspiration ◽  
Spatial Scales ◽  
Meteorological Data ◽  
Kendall Test ◽  
Spatial And Temporal Variability ◽  
Annual Streamflow ◽  
Significant Downward Trend ◽  
Human Effects

Streamflow is likely affected by climate change and human activities. In this study, hydro-meteorological data from six rivers upstream of Beijing, namely, the Yongdinghe, Baihe, Heihe, Chaohe, Juhe, and Jumahe Rivers, were analyzed to quantify the spatial and temporal variability of streamflow and their responses to climate change and human activities over the period of 1956–2016. The Mann–Kendall test and moving t-test were used to detect trends and changing points of the annual streamflow. Results showed that the streamflow into Beijing experienced a statistically significant downward trend (p < 0.05), abruptly changing after the early 1980s, owing to climate and human effects. The climate elasticities of the streamflow showed that a 10% decrease in precipitation would result in a 24.5% decrease in total streamflow, whereas a 10% decrease in potential evapotranspiration would induce a 37.7% increase in total streamflow. Human activities accounted for 87% of the reduction in total streamflow, whereas 13% was attributed to climate change. Lastly, recommendations are provided for adaptive management of water resources at different spatial scales.

scholarly journals Impacts of Climate and Anthropogenic Activities on Streamflow Regimes in the Beiluo River, China

Water ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 2892
Author(s):  
Zhibo Xie ◽  
Xingmin Mu ◽  
Peng Gao ◽  
Changxue Wu ◽  
Dexun Qiu
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Human Activities ◽  
Potential Evapotranspiration ◽  
Anthropogenic Activities ◽  
Annual Streamflow ◽  
Impact Of Climate Change ◽  
Daily Streamflow ◽  
Significant Downward Trend ◽  
The Impact

Quantitatively assessing the characteristics of river streamflow variation and conducting research on attribution identification are the basis for formulating climate-change response strategies and rational use of water resources. Based on the daily streamflow data of the Zhuangtou Hydrological Station in 1970–2018, this paper analyzes the streamflow changes in the Beiluo River Basin and studies the impact of climate change and anthropogenic activities on the streamflow in this basin. A non-parametric Mann–Kendall test and Pettitt’s test were used to determine the trend and detect abrupt changes of streamflow and baseflow. The method based on precipitation and potential evapotranspiration, as well as the double-mass curve of precipitation–streamflow, was established to evaluate the impact of climate change and non-climate factors on annual streamflow. The results reveal a statistically significant downward trend (p = 0.01) in both annual streamflow and baseflow, with the abrupt point year in 1994 and 1988, respectively. When comparing to a modest declining trend in annual average precipitation, we see that the temperature showed a significant upward trend (p = 0.01), whose abrupt point year was 1996. Under the policy of returning farmland to forest, land-use analysis shows that the area of farmland had decreased by 222.4 km2, of which 31.4% was mainly converted into the forestland. By the end of 2015, the area of forestland had increased by 123.4 km2, which has largely caused streamflow decrease. For the method based on precipitation and potential evapotranspiration, climate change contributed 43.7% of the annual streamflow change, and human activities (mainly refers to LUCC) contributed 56.3%. For the DMC of precipitation–streamflow, the precipitation contributed 9.4%, and non-precipitation factors (mainly refers to human activities) contributed 90.6%, and human activities played a more vital part in driving streamflow reduction in different decades, with a contribution rate of more than 70%. This study is of great practical significance to the planning, management, development and utilization of water resources in basins.

scholarly journals Decomposition and Attribution Analysis of Runoff Alteration of the Dongting Lake in China

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2729
Author(s):  
Yuyun Huang ◽  
Minghui Yu ◽  
Haoyong Tian ◽  
Yujiao Liu
Keyword(s):  
Climate Change ◽  
Sensitivity Analysis ◽  
Human Activities ◽  
Potential Evapotranspiration ◽  
Dominant Role ◽  
Meteorological Data ◽  
Dongting Lake ◽  
Change Points ◽  
Runoff Change ◽  
Runoff Depth

The runoff process in the Dongting Lake has been influenced by climate change and human activities in recent decades. To manage the Dongting Lake efficiently and exploit water resources properly under the background of water shortage, it is desired to detect the factors of runoff change in the Dongting Lake. Hydro-meteorological data from 1961 to 2019 are analyzed to reveal the climate change and runoff alteration of the Dongting Lake comprehensively. Mutation test is used to detect the change points of runoff depth series, finding that 1984 and 2005 are change points and therefore 1961–1983, 1984–2004, and 2005–2019 are regarded as baseline period (BP), period 1 (P1), and period 2 (P2), respectively. Eight methods are used to quantitatively assess the relative contribution of human activities and climate change on runoff variation. It reveals that climate change especially precipitation change plays the dominant role (climate change makes runoff depth increase 70.14–121.51 mm, human activities make runoff depth decrease 51.98–103.35 mm) in runoff alteration in P1 while human activities play a prime role (account for 88.47–93.17%) in P2. Human activities such as reservoir construction, water consumption, and land-use (land-cover) change may be the main factors that influence the runoff in the Dongting Lake in P2. According to the sensitivity analysis, runoff in the Dongting Lake is more sensitive to climate change in P2 compared with that in P1, and no matter in P1 or P2, runoff is more sensitive to change in precipitation than the change in potential evapotranspiration. Combined with climate forecast, the results of sensitivity analysis can be used to estimate runoff change caused by climate change in the future.

scholarly journals The Characteristics of Runoff Process Structure Changes under the Influence of Climate Change and Human Activities and the Decomposition of Contribution Rate of Impact Factors

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiaoyuan Song ◽  
Zhongyuan Zhu ◽  
XiaoKang Xi ◽  
Guibin Zhang ◽  
Hailong Wang
Keyword(s):  
Climate Change ◽  
Distribution Coefficient ◽  
River Basin ◽  
Human Activities ◽  
Potential Evapotranspiration ◽  
Meteorological Data ◽  
Uneven Distribution ◽  
Impact Factors ◽  
Adjustment Coefficient ◽  
Contribution Rate

The research of the runoff structure and its influencing factors in the Xilinhe River Basin not only provides indispensable basic data for the economic development, but also has long-term significance for the protection of grasslands. Based on the runoff data of Xilinhot Hydrological Station from 1960 to 2010 and the daily meteorological data of three surrounding weather stations from 1960 to 2010, the paper calculated the potential evapotranspiration with Penman’s formula and used the combination of Mann-Kendall and Pettitt to diagnose the variation points of characteristic value of runoff distribution during the year. The cumulant slope change rate method is used to quantitatively analyze the contribution rate of climate change and human activities to the uneven distribution coefficient and the complete adjustment coefficient of runoff during the year. The results show that (1) the monthly distribution of runoff in the Xilinhe River Basin is obviously “bimodal” during the year, and the uneven coefficient, complete adjustment coefficient, and concentration in the 2000s are significantly higher than those of 60s-90s. (2) In 1998, the coefficient of uneven distribution of runoff in the Xilinhe River Basin and the coefficient of complete adjustment both showed abrupt changes. (3) Climate change and human activities contributed 11.48% and 88.52% and 9.35% and 90.65% to the uneven distribution coefficient and the complete adjustment coefficient, respectively, of the runoff in the Xilinhe River Basin. Human activities are the main driving factors for changes in the distribution of runoff in the Xilinhe River Basin during the year.

scholarly journals Response of LUCC on Runoff Generation Process in Middle Yellow River Basin: The Gushanchuan Basin

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1237 ◽  
Author(s):  
Caihong Hu ◽  
Li Zhang ◽  
Qiang Wu ◽  
Shan-e-hyder Soomro ◽  
Shengqi Jian
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Yellow River ◽  
Trend Test ◽  
Generation Process ◽  
Runoff Generation ◽  
Contribution Rate ◽  
Runoff Reduction ◽  
Runoff Change ◽  
Significant Downward Trend

Runoff reduction in most river basins in China has become a hotpot in recent years. The Gushanchuan river, a primary tributary of the middle Yellow river, Northern China, showed a significant downward trend in the last century. Little is known regarding the relative contributions of changing environment to the observed hydrological trends and response on the runoff generation process in its watershed. On the basis of observed hydrological and meteorological data from 1965–2010, the Mann-Kendall trend test and climate elasticity method were used to distinguish the effects of climate change and human activities on runoff in the Gushanchuan basin. The results indicate that the runoff in the Gushanchuan Basin has experienced significant declines as large as 77% from 1965 to 2010, and a mutation point occurred around 1997; the contribution rate of climate change to runoff change is 12.9–15.1%, and the contribution rate of human activities to runoff change is 84.9–87.1%. Then we divided long-term data sequence into two stages around the mutation point, and analyzed runoff generation mechanisms based on land use and cover changes (LUCC). We found that the floods in the Gushanchuan Basin were still dominated by Excess-infiltration runoff, but the proportion in 1965–1997 and 1998–2010 decreased gradually (68.46% and 45.83% in turn). The proportion of Excess-storage runoff and Mixed runoff has increased, which means that the runoff is made up of more runoff components. The variation law of the LUCC indicates that the forest area increased by 49.61%, the confluence time increased by 50.42%, and the water storage capacity of the watershed increased by 30.35%.

scholarly journals Quantifying the Impacts of Climate Change, Coal Mining and Soil and Water Conservation on Streamflow in a Coal Mining Concentrated Watershed on the Loess Plateau, China

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1054 ◽  
Author(s):  
Qiaoling Guo ◽  
Yaoyao Han ◽  
Yunsong Yang ◽  
Guobin Fu ◽  
Jianlin Li
Keyword(s):  
Climate Change ◽  
Coal Mining ◽  
Loess Plateau ◽  
Water Conservation ◽  
Soil And Water Conservation ◽  
The Loess Plateau ◽  
Annual Streamflow ◽  
Significant Downward Trend ◽  
The Impact ◽  
Soil And Water

The streamflow has declined significantly in the coal mining concentrated watershed of the Loess Plateau, China, since the 1970s. Quantifying the impact of climate change, coal mining and soil and water conservation (SWC), which are mainly human activities, on streamflow is essential not only for understanding the mechanism of hydrological response, but also for water resource management in the catchment. In this study, the trend of annual streamflow series by Mann-Kendall test has been analyzed, and years showing abrupt changes have been detected using the cumulative anomaly curves and Pettitt test. The contribution of climate change, coal mining and SWC on streamflow has been separated with the monthly water-balance model (MWBM) and field investigation. The results showed: (1) The streamflow had an statistically significant downward trend during 1955–2013; (2) The two break points were in 1979 and 1996; (3) Relative to the baseline period, i.e., 1955–1978, the mean annual streamflow reduction in 1979–1996 was mainly affected by climate change, which was responsible for a decreased annual streamflow of 12.70 mm, for 70.95%, while coal mining and SWC resulted in a runoff reduction of 2.15 mm, 12.01% and 3.05mm, 17.04%, respectively; (4) In a recent period, i.e., 1997–2013, the impact of coal mining on streamflow reduction was dominant, reaching 29.88 mm, 54.24%. At the same time, the declining mean annual streamflow induced through climate change and SWC were 13.01 mm, 23.62% and 12.20 mm, 22.14%, respectively.

scholarly journals Tropical rainfall trend and stationarity analysis

2020 ◽  
Vol 20 (7) ◽  
pp. 2471-2483
Author(s):  
Chun Kang Ng ◽  
Jing Lin Ng ◽  
Yuk Feng Huang ◽  
Yi Xun Tan ◽  
Majid Mirzaei
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
River Basin ◽  
Spatial Scales ◽  
Kendall Test ◽  
Temporal Analysis ◽  
Northern Region ◽  
Rainfall Series ◽  
Kelantan River Basin ◽  
Temporal And Spatial

Abstract Climate change is most likely to cause changes to the temporal and spatial variability of rainfall. A trend analysis to investigate the rainfall pattern can detect changes over temporal and spatial scales for a rainfall series. In this study, trend analysis using the Mann–Kendall test and Sen's slope estimator was conducted in the Kelantan River Basin, Malaysia. The Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test was applied to evaluate the stationarity of the rainfall series. This basin annually faces onslaughts of varying year-end flooding conditions. The trend analysis was applied for monthly, seasonal and yearly rainfall series between 1989 and 2018. The temporal analysis results showed that both increasing and decreasing trends were detected for all rainfall series. The spatial analysis results indicated that the northern region of the Kelantan River Basin showed an increasing trend, whilst the southwest region showed a decreasing trend. It was found that almost all the rainfall series were stationary except at two rainfall stations during the Inter Monsoon 1, Inter Monsoon 2 and yearly rainfall series. Results obtained from this study can be used as reference for water resources planning and climate change assessment.

Hydrological Cycles Change in the Yellow River Basin during the Last Half of the Twentieth Century

2008 ◽  
Vol 21 (8) ◽  
pp. 1790-1806 ◽  
Author(s):  
Qiuhong Tang ◽  
Taikan Oki ◽  
Shinjiro Kanae ◽  
Heping Hu
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Human Activities ◽  
River Discharge ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Linear Component ◽  
Annual Streamflow ◽  
The Yellow River Basin

Abstract A distributed biosphere hydrological (DBH) model system was used to explore the internal relations among the climate system, human society, and the hydrological system in the Yellow River basin, and to interpret possible mechanisms for observed changes in Yellow River streamflow from 1960 to 2000. Several scenarios were evaluated to elucidate the hydrological response to climate system, land cover, and irrigation. The results show that climate change is the dominant cause of annual streamflow changes in the upper and middle reaches, but human activities dominate annual streamflow changes in the lower reaches of the Yellow River basin. The annual river discharge at the mouth is affected by climate change and by human activities in nearly equal proportion. The linear component of climate change contributes to the observed annual streamflow decrease, but changes in the climate temporal pattern have a larger impact on annual river discharge than does the linear component of climate change. Low flow is more significantly affected by irrigation withdrawals than by climate change. Reservoirs induce more diversions for irrigation, while at the same time the results demonstrate that the reservoirs may help to maintain environmental flows and counter what otherwise would be more serious reductions in low flows.

Spanish coast resilience face to storm and beach renourishment monitored from space. 

2021 ◽  
Author(s):  
Anne-Laure Beck ◽  
Jara Martinez Sanchez
Keyword(s):  
Climate Change ◽  
Change Detection ◽  
Human Activities ◽  
Spatial Scales ◽  
Sandy Beaches ◽  
Band Ratio ◽  
Coastal Dynamics ◽  
Earth Observations ◽  
Spatial Coverage ◽  
The Impact

&lt;p&gt;The increasing storm frequency and strength due to climate change, coupled with human activities along the coast unbalance the coastal dynamics. A constant monitoring is necessary to better understand and mitigate the effect on Spanish coastal environments. Spain has around 8 000 Km of coastal areas along the Iberian Peninsula, the Balearic and Canary island. These coasts have a high coastal geomorphology variability, from rocky coasts with large estuaries on the Atlantic face in the northwest of the Iberian Penisula, to long sandy beaches with dunes systems and large wetlands in the southwest. On the Mediterranean coast, low rocky cliffs and sandy beaches with a wide variety of coastal infrastructures and deltas. Although in-situ measurements are highly efficient on capturing coastal parameters and features at a given time, the cost of continuous acquisition campaigns for the whole coast is dissuasive. Earth Observations provide wide spatial coverage over a large temporal scale allowing us to develop a methodology adapted to all coastal morphologies and dynamics to follow the impact of climate change and human activities on Spain&amp;#8217;s top touristic attraction, it&amp;#8217;s coasts.&lt;/p&gt;&lt;p&gt;Our developed methodology uses the instantaneous boundary between land and sea on satellite images extracted using an algorithm based on the Liu &amp; Jezek methodology. The use of the Canny edge detection is improved by a local adaptive threshold applied on a band ratio image. NDVI, BNDVI, GNDVI or others are applied depending on coastal features and natures to extract with high precision the land/ sea interface. Is then applied to the obtained waterlines waves, slope and tide correction to obtain inter-comparable lines to build some time-series product at different time scale. The spatial scale of the changes due to coastal dynamics within the coastal environment is a challenge for change detection due to the shifts between earth observations. The application of a geo-location method helps with the spatial accuracy constraint and ensure an accurate change detection by monitoring real movements and therefore allow us to capture coastal change at different temporal and spatial scales.&lt;/p&gt;

scholarly journals Impact of Climate Change and Human Activities on Streamflow Variations Based on the Budyko Framework

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2001 ◽  
Author(s):  
Lee ◽  
Yeh
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Human Activities ◽  
Potential Evapotranspiration ◽  
Land Use Changes ◽  
Dominant Factor ◽  
Climate Factors ◽  
The Sustainable Development ◽  
Precipitation Changes ◽  
Northern Taiwan

In recent years, the influence of climate change and human activity on the global environment have become a concern. It is essential to better understand the hydrologic environment to evaluate water availability and related issues. In this study, we perform a trend and breakpoint analysis on streamflow time series in the Lanyang, Keelung, Dahan, Fengshan, Youluo and Shangping River Basins in northern Taiwan. Furthermore, we apply the Budyko–Fu equation and the Budyko–Mezentsev–Choudhury–Yang equation to evaluate the elasticity of streamflow with respect to climate factors and the catchment characteristics parameter. We discuss the sensitivity of streamflow to climate factors (precipitation and potential evapotranspiration), as well as sensitivity to human activities such as land use changes. We detected breakpoints in the streamflow time series for the Lanyang and Keelung rivers in in 1993 and 1990, respectively. The streamflow of Lanyang River increased by 32.50% during the variation period (1993–2017), with 109.00% of the variation caused by non-climate factors. The Keelung River’s streamflow was reduced by 18.11% during the variation period (1990–2017), and the dominant factor was climate change, accounting for 71.53% of the reduction. Sensitivity analysis showed that precipitation changes were the most sensitive factor of streamflow variation. For every 1% increase in precipitation, the streamflow would increase by 1.05% to 1.37%. These results could serve as a reference for the sustainable development of water resources and territorial policies in northern Taiwan.

scholarly journals Differing Responses to Rainfall Suggest More Than One Functional Type of Grassland in South Africa

2018 ◽  
Vol 10 (12) ◽  
pp. 2055 ◽  
Author(s):  
Catherine Van den Hoof ◽  
Michel Verstraete ◽  
Robert Scholes
Keyword(s):  
Climate Change ◽  
South Africa ◽  
Spatial Scales ◽  
Annual Rainfall ◽  
Mean Annual Precipitation ◽  
Spatial And Temporal Variability ◽  
Arid Zones ◽  
Monthly Precipitation ◽  
Good Tool ◽  
Grassland Productivity

Grasslands, which represent around 40% of the terrestrial area, are mostly located in arid and semi-arid zones. Semiarid ecosystems in Africa have been identified as being particularly vulnerable to the impacts of increased human pressure on land, as well as enhanced climate variability. Grasslands are indeed very responsive to variations in precipitation. This study evaluates the sensitivity of the grassland ecosystem to precipitation variability in space and time, by identifying the factors controlling this response, based on monthly precipitation data from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) data from the Multi-angle Imaging SpectroRadiometer-High Resolution (MISR-HR) datasets, used as proxy for productivity, at 60 grassland sites in South Africa. Our results show that MISR-HR products adequately capture the spatial and temporal variability in productivity at scales that are relevant to this study, and they are therefore a good tool to study climate change impacts on ecosystem at small spatial scales over large spatial and temporal domains. We show that combining several determinants and accounting for legacies improves our ability to understand patterns, identify areas of vulnerability, and predict the future of grassland productivity. Mean annual precipitation is a good predictor of mean grassland productivity. The grasslands with a mean annual rainfall above about 530 mm have a different functional response to those receiving less than that amount of rain, on average. On the more arid and less fertile soils, large inter-annual variability reduces productivity. Our study suggests that grasslands on the more marginal soils are the most vulnerable to climate change.

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