Future trend analysis of precipitation in the Haihe River basin based on a method combining wavelet and rescaled range analyses

Climate change has become an increasingly dominant environmental issue which has been attracting more and more attention in recent years. It is necessary to determine the cycle and trend of annual precipitation in the Haihe River Basin in the context of climate change because it is the largest river system in northern China. A combined method of rescaled range analysis and wavelet analysis is applied to identify the cycle and trend in annual precipitation based on data from 12 weather stations in the Haihe River Basin. The results of wavelet analysis show that the 12 weather stations all have the long main cycles of 35-38 years and the medium-length cycles of 22-25 years. Datong, Yuanping, Shijiazhuang, Taiyuan, Anyang, and Huimin stations have the short-length cycles of 9-11 years. The results of rescaled range analysis show that all of the Hurst exponents are greater than 0.5, which indicates that the future trend of annual precipitation will very likely follow the historical trend. Therefore, nine stations will have the downward trends, and other stations will have the upward trends in the future, according to the analysis of the historical trends by the method of wavelet analysis.

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Long-term variation of water vapor content and precipitation in the Haihe river basin

Journal of Water and Climate Change ◽

10.2166/wcc.2014.155 ◽

2014 ◽

Vol 6 (2) ◽

pp. 341-351 ◽

Cited By ~ 1

Author(s):

Chun Chang ◽

Ping Feng ◽

Fawen Li ◽

Yunming Gao

Keyword(s):

Water Vapor ◽

River Basin ◽

Reanalysis Data ◽

Water Vapor Content ◽

Haihe River Basin ◽

Haihe River ◽

Annual Water ◽

Environmental Prediction ◽

High Consistency ◽

The Haihe River Basin

Based on the Haihe river basin National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data from 1948 to 2010 and the precipitation data of 53 hydrological stations during 1957–2010, this study analyzed the variation of water vapor content and precipitation, and investigated the correlation between them using several statistical methods. The results showed that the annual water vapor content decreased drastically from 1948 to 2010. It was comparatively high from the late 1940s to the late 1960s and depreciated from the early 1970s. From the southeast to the northwest of the Haihe river basin, there was a decrease in water vapor content. For vertical distribution, water vapor content from the ground to 700 hPa pressure level accounted for 72.9% of the whole atmospheric layer, which indicated that the water vapor of the Haihe river basin was mainly in the air close to the ground. The precipitation in the Haihe river basin during 1957–2010 decreased very slightly. According to the correlation analysis, the precipitation and water vapor content changes showed statistically positive correlation, in addition, their break points were both in the 1970s. Furthermore, the high consistency between the precipitation efficiency and precipitation demonstrates that water vapor content is one of the important factors in the formation of precipitation.

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Spatial and Temporal Variation Characteristics of Snowfall in the Haihe River Basin from 1960 to 2016

Water ◽

10.3390/w13131798 ◽

2021 ◽

Vol 13 (13) ◽

pp. 1798

Author(s):

Xu Wu ◽

Su Li ◽

Bin Liu ◽

Dan Xu

Keyword(s):

Temporal Variation ◽

River Basin ◽

Spatial And Temporal Variation ◽

Haihe River Basin ◽

Temperature Threshold ◽

Threshold Method ◽

Exponential Equation ◽

Haihe River ◽

The Haihe River Basin ◽

Different Levels

The spatio-temporal variation of precipitation under global warming had been a research hotspot. Snowfall is an important part of precipitation, and its variabilities and trends in different regions have received great attention. In this paper, the Haihe River Basin is used as a case, and we employ the K-means clustering method to divide the basin into four sub-regions. The double temperature threshold method in the form of the exponential equation is used in this study to identify precipitation phase states, based on daily temperature, snowfall, and precipitation data from 43 meteorological stations in and around the Haihe River Basin from 1960 to 1979. Then, daily snowfall data from 1960 to 2016 are established, and the spatial and temporal variation of snowfall in the Haihe River Basin are analyzed according to the snowfall levels as determined by the national meteorological department. The results evalueted in four different zones show that (1) the snowfall at each meteorological station can be effectively estimated at an annual scale through the exponential equation, for which the correlation coefficient of each division is above 0.95, and the relative error is within 5%. (2) Except for the average snowfall and light snowfall, the snowfall and snowfall days of moderate snow, heavy snow, and snowstorm in each division are in the order of Zones III > IV > I > II. (3) The snowfall and the number of snowfall days at different levels both show a decreasing trend, except for the increasing trend of snowfall in Zone I. (4) The interannual variation trend in the snowfall at the different levels are not obvious, except for Zone III, which shows a significant decreasing trend.

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