A comprehensive approach to characterization of the nonlinearity of runoff in the headwaters of the Tarim River, western China

Abstract

Abstract:Nonlinear characteristics of the runoff processes in the headwaters of the Tarim River were identified and evaluated using several selected methods, including wavelet analysis, correlation dimension, and R/S analysis. Time-series of annual data describing runoff, average temperature, and precipitation from 1957 to 2005 were used to construct and test empirical models. The primary findings of this study were as follows: (1) The annual runoff of the headwaters are complex and nonlinear in nature, and they each presented periodic, nonlinear trends at the chosen time scales, chaotic dynamics, and long-memory characteristics. (2) These nonlinear trends appeared to have resulted from the regional climatic changes that occurred during the study period. The periodicity of changes in runoff occurred on an approximately 25-year cycle, which appeared to be correlated with temperature and precipitation cycles. In addition, the annual runoff exhibited a significant, positive correlation with the temperature and precipitation factors at the 4-, 8-, 16-, and 32-year temporal scales. (3) The correlation dimensions of the attractor derived from the runoff time series for the Hotan, Yarkand, and Aksu rivers were all greater than 3Ð0 and non-integral, implying that all three rivers are dynamic chaotic systems that are sensitive to initial conditions, and that the dynamic modelling of their annual runoff requires at least four independent variables. (4) The computed Hurst exponents indicate that a long-term memory characteristic exists in the annual runoff processes. However, there were some differences observed, with the Aksu and Yarkand rivers demonstrating a persistent trait, and the Hotan River exhibiting an anti-persistent feature.

Changes in Stream Flow and Their Relationships with Climatic Variations and Anthropogenic Activities in the Poyang Lake Basin, China

“…Sun et al [42] found that pan evaporation in the Poyang Lake Basin increased from 2002, and it would attribute to the temperature increases. This was different from the snowmelt-dominated basins in China, such as Tarim River, western China [43] and Yarlung Zangbo River on the Tibetan Plateau [44], where elevated temperature produced higher stream flow because of enhanced snowmelt. However, as a whole, stream flow was more sensitive to precipitation than evaporation in the Poyang Lake Basin [45].…”

Study on the Variation of Terrestrial Water Storage and the Identification of Its Relationship with Hydrological Cycle Factors in the Tarim River Basin, China

“…The 114 rivers in the TRB connected with the mainstream reduced throughout history to just 3 rivers in the present day [33]. The mean annual runoff of 3.989 × 10 10 m 3 is exhibited in the TRB, where the water component from ice and snow and precipitation in the mountains accounts for 48.2% [33,34]. The three largest headstreams, Aksu River, Hotan River, and Yarkand River, account for 73.2%, 23.2%, and 3.6% of the total runoff, respectively [35].…”

“…Additionally, Advances in Meteorology 3 the annual air temperature in the TRB exhibits intra-annual variations [33]. The barren and sparsely vegetated land plays major role in the land use in the TRB, which accounts for 56.2% [34].…”

Nonlinear Response of Streamflow to Climate Change in High-Latitude Regions: A Case Study in Headwaters of Nenjiang River Basin in China’s Far Northeast

“…These studies employed methods designed under the hypothesis that the time series of hydroclimatic variables are stationary and therefore can be considered as a linear system (such as moving average or polynomial, linear regression, empirical or spline function fitting) [11]. However, studies also found that hydroclimatic processes are complex and hydroclimatic variables, including runoff, precipitation, temperature and evapotranspiration, often behave nonlinearly and nonstationarily [12,13]. Therefore, traditional (i.e., linear interpretation) methods cannot satisfy for capturing nonlinear, nonstationary response patterns of streamflow to climatic variability.…”