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Springer (part of Springer Nature), Stochastic Environmental Research and Risk Assessment, 2(25), p. 223-233

DOI: 10.1007/s00477-010-0433-9

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An integrated statistical approach to identify the nonlinear trend of runoff in the Hotan River and its relation with climatic factors

Journal article published in 2010 by Jianhua Xu ORCID, Yaning Chen, Weihong Li, Yang Yang, Yulian Hong
This paper is available in a repository.
This paper is available in a repository.

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Abstract

A number of studies have indicated a transition from warm-dry to warm-wet climate in Northwest China after the 1980s. This transition was characterized by an increase in temperature and precipitation, added river runoff volume, increased lake water surface elevation and area, and elevated groundwater table. However, some literatures showed that the Hotan River has presented a contrary situation, i.e. the runoff decreased, whereas temperature and precipitation increased. In order to discover the nonlinear runoff trend and its causes in the Hotan River, based on the related data from hydrological stations, ground and air sounding meteorological stations, this study applied a comprehensive method combing correlation analysis, wavelet analysis and regression analysis to investigate the runoff change in the Hotan River with its relevant climatic factors over the past decades. The main findings are: (a) the hydrological process of the Hotan River is a nonlinear system, with a periodicity of 24 year cycle, and it shows different nonlinear trends at different time scales; (b) the data from the ground meteorological stations in the Hotan area shows a false appearance that there is almost no correlation between runoff and temperature, and a little negative correlation between runoff and precipitation; (c) but the data from air sounding meteorological stations shows the truth that there is a close relation between the runoff in the Hotan River and the 0°C level height in summer on the north slope of Kunlun Mountains. The two variables present a same periodicity, i.e. 24-year cycle, having similar nonlinear trends and significant correlations at different time scales.