temperature increased by 0.85 °C between 1988 and 2012, at a rate of 0.064 °C per decade according to

Intergovernmental Panel on Climate Change's Fifth Report, such an increase in global temperature would suffice

to influence regional hydrological cycles, including changes in the spatial and temporal distribution of

precipitation [2]. Global warming could aggravate the unequal distribution of precipitation, resulting in more

rain in wet places and less rain in dry ones [3,4]. While, the concept of "arid areas becoming drier and humid

areas increasing wetter" does not apply to all places, only about 11% of worldwide precipitation over land has

been "drier and wetter" since 1948 [5], and extreme precipitation events are anticipated to become more intense

and frequent in specific sections of the mid-latitudes and humid tropics [2].

China's average climate, as well as the features of extreme weather and climate events, has changed as a result

of global warming [6]. Since 1960, China's average temperature has increased by 1.2 °C [7]. The extreme

seven largest river basins with the worst water scarcity, and found that precipitation in this river basin was on

the declining trend[11,12]. Annual precipitation in the Haihe River basin decreased with an average slope of

areas of the Haihe river basin was higher than that in mountainous and hilly areas [14]. Yu et al presented

pertinent findings on the evolution of precipitation in the Haihe River basin, reporting a gradual decline from

east to west and south to north[15].

The Yongding River is the largest branch of the Haihe River basin and is also called Beijing's mother river [16],

and has suffered from many disasters. According to historical records, in the 800 years before the founding of

the 1960s, 361 days in the 1980s, and the whole year in the 1990s. The river completely dried up with the river

bed exposed, and the groundwater level in the surrounding area continued to decline. At the same time, the rapid

economic and social development leads to the over-exploitation of water resources in the basin and the water

quality in most reaches of the river has been deteriorating for a long time. For example, the Guanting reservoir,

situated in the Yongding River, is the first large reservoir built after the founding of new China and was once of

Beijing's main water supply sources. As the reservoir's water quality deteriorated, it was forced to withdraw from

the city's drinking water system in 1997 [17].

Since 2000, the State Council of China has approved and implemented the Plan for Sustainable Utilization of

Water Resources in the Capital in the early twenty-first century and the Plan for Water Allocation in the main

stream of the Yongding River to alleviate the scarcity of water resources in Beijing, rationally allocate water

Bridge dried up all year round, which could not guarantee the water demand of the ecological environment and

caused serious ecological degradation in the water-scarce area associated with the Yongding River [19,20]. It

has seriously harmed the river's ecological function and hampered the long-term economic and social

development of the coordinated development zone of Beijing, Tianjin, and Hebei [21].

The response of hydrological processes to precipitation changes and climate variabilities, as well as the resulting

changes in regional water conservation capacity, are critical for the sustainable use of water resources. Due to

the fact that a detailed analysis of the climate variability of all seasons, including temperature and precipitation,

as well as their interrelationship, has not been performed for the Yongding River basin, this study aims (i) to

investigate seasonal and annual variabilities in precipitation and temperature in the basin; and (ii) to detect

climate jumps and precipitation periodicities over a 62-year climatological period from 1959 to 2020. It allows

The Yongding River basin covers an area of 47,053 km

, of which the mountain area covers 45,100 km

,

accounting for 95.8%, and the plain area covers 1,953 km

, accounting for 4.2% [22].

Yongding River, one of the four major national flood control channels in China, flows through Inner Mongolia

autonomous regions, Shanxi province, Hebei province, Beijing, and Tianjin City, and belongs to the northern

system of the Haihe River basin, as shown in Fig. 1. Yongding River upstream consists of two tributaries, Yanhe

River from the Inner Mongolia Plateau and Sanggan River from the Shanxi Plateau. The two rivers flow through

alternate ravines valleys, and basins and merge at Huailai Zhuguantun, and after the confluence, they are called

sea at Beitang, Tianjin City. Among the rivers, the Sanggan River is the main source of the Yongding River, 390

km long, the Yanghe River is 101 km long, the Yongding River is 307 km long, the Yongding New River is 62

km long, and a total length of the Yongding River is 761 km.

The Yongding River basin is a temperate continental monsoon climate, which is a climate transition zone

between semi-humid and semi-arid. The spring dries early with some sandstorms, summer is hot with heavy

days in the mountainous area, and the frozen period is more than 4 months. The average annual precipitation in

the Yongding river basin ranges from 360 mm to 650 mm, and there is a large difference in precipitation in

annual runoff was 4.67.

Economy and society

The administrative division of the Yongding River Basin includes parts of Beijing, Tianjin, Hebei, Shanxi, and

Inner Mongolia with 51 cities, counties, and districts, among which Hebei province involves three prefecture-

level cities of Zhangjiakou, Baoding, Langfang, and Shanxi Province involves three prefecture-level cities of

Xinzhou, Shuozhou, and Datong[20].

From 2017 to 2020, the resident population of 8 major cities or districts (Shuozhou and Datong in Shanxi,

Zhangjiakou, and Langfang in Hebei, Yanqing District, Mentougou District, Fangshan District and Daxing

District in Beijing) in the Yongding River Basin has increased from about 17.81 million in 2017 to 18.33 million

of the eight cities (districts) in the basin increased from 45,900 yuan in 2017 to 51,700 yuan in 2019, up

12.6%[21].

scientific, technological innovation, research and development base. It will be the future shipping and logistics

centre of northern China and an important economic development belt of the Beijing-Tianjin-Hebei region[22].

Furthermore, we utilized the Kriging interpolation method to create spatial distribution maps depicting

significant changes and jumps in temperature and precipitation, as well as correlations between temperature and

Then, remove the auto-correlation from the original time series:

(4)

Where

Spearman’s Correlation Analysis

variables. This method, which does not require data distribution information and can better reflect the correlation

between precipitation and temperature, uses a monotone equation to evaluate the correlation between two

statistical variables [22].

It is calculated as:

(9)

= the difference between the ranks of corresponding

variables, and n = the number of observations.

and its degree classification standards are shown in Table 1 [30].

Moving t-Test

The moving t-test (MTT) detects climate jumps in a series by comparing the significant differences between the

averages of two groups of samples. In China, this strategy is commonly utilized to detect climatic jump

occurrences [31,32]. The subsequence X

samples was acquired before the datum point with an average

was defined by all locations satisfying |t| > t

after the statistic was calculated, and climate leaps may occur in

, of 5% for this study.

The test statistic S

is defined as follows:

and the statistic index UF

at all stations (Figure 2a). Specifically, the most intense increase in temperature is observed in the eastern

regions including Zhangjiakou, Beijing, and Langfang, and the gentlest in Datong city, which showed a spatial

most area of Datong City, all other areas showed an increasing trend.

Figure 2. Spatial distribution of the significance of annual and seasonal mean temperatures (a) annual; (b)

spring; (c) summer; (d) autumn, and (e) winter.

The temperature jumps in the Yongding River Basin from 1959-2020 are presented in Table 4.

in 1979 to 2020. There was a significant increase observed from 2007 to 2020, while summer mean precipitation

decreased from 1959 to 1968. It then experienced an increase from 1969 to 1982, followed by another decrease

from 1983 to 2020. . There was a significant decrease noted from 2009 to 2020. Autumn mean precipitation

exhibited a decrease from 1962 to 2007, followed by an increase from 2008 to 2020, with no significant overall

trend. Winter mean precipitation decreased from 1962 to 1969 and increased from 1970 to 2020. Notably,

significant increases were observed in 2016 and 2019.

The results of the MTT and MK tests for the seasonal precipitation in the Yongding River Basin from 1959 to

2020 were shown in Fig. 9. The Yongding River Basin seasonal precipitation MTT and MK test results from the

study period of 1959 to 2020 revealed that the jump timings were not nearly consistent between the two these

two methods MTT and MK. In the Yongding River Basin from 1959 to 2020, precipitation jumps were identified

In this study, the climate jump was considered in two parts: temperature and precipitation.

When examining the spatial distribution of temperature jumps, it is evident that multiple temperature jumps

occurred in most areas of the Yongding River Basin (Figure 11).

temperature jumps, two jumps occurred in Datong City and some areas in the northern part of Zhangjiakou City,

while one jump occurred in the upper reaches of the Yongding River watershed, excluding these areas. In winter,

Yongding River Basin, while jumps occurred once in 71.07% of the area, and no jumps occurred in 16.03% of

the area.

The spatial distribution of annual mean temperature jumps reveals three jumps in the central part of the study

area (eastern part of Datong City) and one jump in the remaining area, except for some areas in the eastern and

central parts where no jumps occurred.

Table 6. Area percentage according to the number of jumps of the annual and seasonal temperature.

The precipitation jump is relatively complicated as compared to the temperature jump as shown in (Fig. 12). The

spatial distribution of spring mean precipitation jumps is diverse, with three jumps occurring in the northern part

or two jumps occurred in other areas.

Figure 12. Spatial distribution of precipitation jumps throughout Yongding River basin between 1959 and 2020

(a) annual (b) spring (c) summer (d) autumn and (e) winter

The areas where climate jumps did not occur in spring and winter account for 8.92% and 29.96% of the total

Yongding River Basin, respectively. However, the impact on the total precipitation jumps is not as significant

since the precipitation is relatively low during these seasons. In summer and autumn, more than one precipitation

jump occurred in all areas.

Table 7. Area percentage according to the number of jumps of the annual and seasonal precipitation

the eastern part of the study area had two jumps. In the annual series, the area where the average annual

precipitation jump occurred once accounted for 73.87% of the total watershed area, and the area where the jump

occurred twice accounted for 26.13%, with no area experiencing no jump. This indicates that the main cause of

the annual precipitation jump is the change in precipitation during summer and autumn, which exhibits high

variability and severity in this basin.

other hand, this is a characteristic that many people have, and multi-time scale characteristics can be found in

both seasonal and annual precipitation. The results vary depending on the area characteristics and the time period

of selected historical data; some are obvious while others are not.

In accordance with the results of the Mann-Kendall test, which used annual average temperature data from 1959

to 2020, the average annual temperature at 53 stations (i.e., 100% of the total number of stations) shows an

upward trend, with the trend toward growth being significant at every station. No station, however, displays a