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

Abstract

Abstract:Located in the Loess Plateau of China, the Wuding River basin (30 261 km 2 ) 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)(1962)(1963)(1964)(1965)(1966)(1967)(1968)(1969)(1970)(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%.

Drivers of drying on the Yongding River in Beijing

“…However the most probable change-points in the streamflow time-series at all stations match the start years of Beijing's most recent drought (Table 5). From 1980 to 2010, Beijing suffered two official droughts (defined as significant reduction in precipitation from the mean long-term value of 585 mm) in: (1) the 1980s and (2) 1999-2007(Probe, 2010. Mean annual precipitation at the three stations from 1980 to 2010 were 36.8% (Guanting Reservoir), 24.3% (Yanchi), and 5.6% (Sanjiadian) lower than the long-term mean annual precipitation in Beijing.…”

“…The separation and quantification of climate variation and human impacts on streamflow can be challenging due to the complex interactions between climate, human activities, and hydrological processes. A range of statistical and modeling techniques have been developed to estimate streamflow changes from climate change and human activities (Li et al, 2007;Barnett et al, 2008;Yang and Tian, 2009;Gautam et al, 2010;Ma et al, 2010;Gao et al, 2011). The impacts of climate variability on hydrologic time-series can be estimated using trend analysis (Lettenmaier et al, 1994;Whitfield and Cannon, 2000).…”

Quantifying the effects of climate change and human activities on runoff in the water source area of Beijing, China

“…Hence, it is important to detect and separate the effects of climate change and human activities and to determine the dominant factors which lead to runoff changes. Although several studies have recently been conducted on this topic (Lane et al 2005, Tuteja et al 2007, Li et al 2007, Wang et al 2009, Wei and Zhang, 2010, Zeng et al 2013, separating the effects of climate change and human activities in hydrology is still a challenge, and the impacts of the two factors on the water cycle still need further investigation at the local scale (Wang et al 2012).…”

Modelling stream flow with a discrete rainfall–runoff model and 37 GHz PDBT microwave observations: the Xiangjiang River basin case study

“…The regional water storage capacity is estimated from physically based model parameters, such as the topography-soil index in TOPMODEL (Sivapalan et al, 1987) or the infiltration factor in VIC (Liang et al, 1994;Wood et al, 1992). These parameters determine the saturated soil 25 area when a storm occurs.…”