Relationship between sand-dust weather and water dynamics of desert areas in the middle reaches of Heihe River

作     者：Yun Niu XianDe Liu Xin Li YanQiang Wei Hu Zhang XiaoYan Li 

作者机构：Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences Lanzhou Gansu 730000 China Academy of Ecology Science of Zhangye Gansu Science and Technology Innovation Service Platform of Ecology in Qilian Mountains Gansu Province Zhangye Gansu 734000 China Academy of Water Resource Conservation Forests of Qilian Mountains in Gansu Province Test Station of Desertification Control in Hongshawo Zhangye Gansu 734000 China 

出 版 物：《Research in Cold and Arid Regions》 (寒旱区科学（英文版）)

年 卷 期：2016年第8卷第6期

页      面：516-523页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0705[理学-地理学] 0706[理学-大气科学] 

基　　金：supported by the Science and Technology Innovation Service Platform of Qilian mountains in Gansu Province (No. 144JTCG254) the Innovation Groups of Basic Research of Gansu Province (No. 145RJIG337) the National Natural Science Foundation of China (No. 41461004) 

主　　题：sand-dust weather water dynamics regression model middle reaches of the Heihe River 

摘      要：Sand-dust weather has become an international social-environmental issue of common concern, and constitutes a serious threat to human lives and economic development. In order to explore the responses of natural desert sand and dust to the dynamics of water in desertification, we extracted long-term monitoring data related to precipitation, soil water, groundwater, and sand-dust weather. These data originated from the test stations for desertification control in desert areas of the middle reaches of the Heihe River. We used an algorithm of characteristic parameters, correlations, and multiple regression analysis to establish a regression model for the duration of sand-dust weather. The response char-acteristics of the natural desert sand and dust and changes of the water inter-annual and annual variance were also examined. Our results showed： （1） From 2006 to 2014 the frequency, duration, and volatility trends of sand-dust weather obviously increased, but the change amplitudes of precipitation, soil water, and groundwater level grew smaller. （2） In the vegetative growth seasons from March to November, the annual variance rates of the soil moisture content in each of four studied layers of soil samples were similar, and the changes in the frequency and duration of sand-dust weather were similar. （3） Our new regression equation for the duration of sand-dust weather passed the R test, F test, and t test. By this regression model we could predict the duration of sand-dust weather with an accuracy of 42.9%. This study can thus provide technological support and reference data for water resource management and re-search regarding sand-dust weather mechanisms.