The Tibetan Plateau (TP) is the headwater of the Yangtze, Yellow, and the transboundary Yarlung Zangbo, Lancang, and Nujiang Rivers, providing essential and pristine freshwater to around 1.6 billion people in Southeast and South Asia. However, the temperature rise TP has experienced is almost three times that of the global warming rate. The rising temperature has resulted in glacier retreat, snow cover reduction, permafrost layer thawing, and so forth. Here we show, based on the longest observed streamflow data available for the region so far, that changing climatic conditions in the TP already had significant impacts on the streamflow in the headwater basins in the area. Our analysis indicated that the annual average temperature in the headwater basins of these five major rivers has been rising on a trend averaging 0.38 °C·decade−1 since 1998, almost triple the rate before 1998, and the change of streamflow has been predominantly impacted by precipitation in these headwater basins. As a result, streamflow in the Yangtze, Yarlung Zangbo, Lancang, and Nujiang River headwater areas is on a decreasing trend with a reduction of flow ranging from 3.0 ×109-5.9 ×109 m3·decade−1 (−9.12% to −16.89% per decade) since 1998. The increased precipitation in the Tangnahai (TNH) and Lanzhou (LZ) Basins contributed to the increase of their streamflows at 8.04% and 14.29% per decade, respectively. Although the increased streamflow in the headwater basins of the Yellow River may ease some of the water resources concerns, the decreasing trend of streamflow in the headwater areas of the southeastern TP region since 1998 could lead to a water crisis in transboundary river basins for billions of people in Southeast and South Asia.
The Tibetan Plateau (TP), also called the Asian Water Tower (AWT), is the headwater for the largest rivers, including the Yangtze, Yellow, Yarlung Zangbo, Lancang/Mekong, Ganges, Indus, and Nujiang Rivers across China and Southeast Asia [1], providing a crucial and reliable source of water for billions of people [2], [3], [4]. However, the climate change that the TP has experienced since the early 1950s is almost three times the global warming rate [5], with the annual average temperature (AAT) increasing by 0.16 °C·decade−1 between 1955 and 1996 and as high as 0.25 °C·decade−1 from 1998 to 2013 [6]. The warming rate of AWT was 0.42 °C per decade during 1980-2018, twice the global average rate [7]. The rising temperature has adversely impacted the cryosphere of the TP, resulting in glacier retreat, snow cover reduction, thawing of permafrost layers, and so on. It has had a far-reaching impact on the water resources in the TP region and its river basins [8]. As these changes continue or even accelerate, they will change the water supply for billions of people [5].
The TP has the third largest group of glaciers on earth, with an estimated total area of 50 657 km2 and a total glacier reserve of 4680 km3. Unfortunately, global warming has accelerated the melting of glaciers in this region. About 82% of the glaciers in the plateau have retreated and shrunk by 15% in volume in the past half-century. The glacier area in the TP was reduced from 48 800 km2 in the 1970s to 44 400 km2 in the early 21st century for a total reduction of 9.05% and an average reduction of about 147 km2 per year. The permafrost in the TP region, which covers an estimated area of approximately 1 480 000 km2 [9], has degraded as well, with the total area shrunk by 16% in the past decade [5], [10], the lower altitudinal limit rose by as much as 80 m [11], and the burial depth below the land surface increased by up to 0.50 m [12].
Studies showed that snow and glacier melt is an essential source of water in the upstream part of the headwater river basins [13], and snow and glacier melt would directly affect the seasonal distribution characteristics of streamflow [14]. The Intergovernmental Panel on Climate Change (IPCC) report [13] showed with medium confidence that the magnitude and seasonality of runoff in snow-dominated and glacier-fed river basins have been affected by snow and glaciers in the high mountain areas; such changes have had impacts on local water resources and agriculture. It also showed with high confidence that summer and annual runoff have increased due to intensified glacier melt in some glacier-fed rivers.
In the TP region, Zhang et al. [15] showed that snowmelt runoff had an increasing trend in the upstream region of the Mekong River but a decreasing trend in the upstream area of the Salween River. The snowmelt runoff in the Upper Mekong River peaked one month earlier for the 1990s and 2000s than in the baseline period of 1964-1990. Zhang et al.’s study [15] indicated that rainfall runoff could be responsible for over 84% of the total runoff in the upstream regions of the Mekong and Salween Rivers. Other studies also showed that snowmelt is a more dominant contributing factor to streamflow [16], especially for those headwater basins with an elevation of 2000 meters above the mean sea level (AMSL) [17], [18]. However, glacier meltwater’s contribution may diminish as glaciers’ coverage reduces. Zhao et al. [19] indicated that glacier runoff might have reached a tipping point as early as the 21st century, with a greater than 20% loss of the glacier area except for the upper stream of the Yangtze River, and projected that glacier runoff might decrease after the 2030s. Observed data has also shown a decreasing trend of meltwater contribution to the streamflow since the later part of the twentieth century [10].
The degradation of permafrost in the TP region has also had a significant impact on hydrologic processes and streamflow. There has been a significant increase in the number of lakes and their respective surface areas in the TP [20]. It was estimated that the contribution to the annual discharge of the Yellow River at Tangnahai was as high as 4.9% from permafrost degradation [21]. Hydrological projections [14], [22] suggest that streamflow in most river source regions would increase along with precipitation and increases in ice/snow melting, and hydrological extremes such as flooding would occur more frequently under future climate change scenarios.
In addition to studies on some individual watersheds [15], [16], there has been great interest in studying the streamflow changes of major river basins in the region. Zhang et al. [12] and Tang et al. [22] both looked at the changes for the entire time series data and found that streamflow for some of the headwater basins in the southeastern part of the TP region has been on an increasing trend. In contrast, the upper stream headwater basins of the Yellow River have been on a decreasing trend. There have also been quite a few publications in Science and Nature addressing the water security concerns due to the impacts of climate change in the TP region [1], [2], [3], [4], [5], [23].
To reveal the change characteristics of headwater streamflow that might have already happened in the source areas of the Yangtze, Yellow, and the transboundary Yarlung Zangbo, Lancang, and Nujiang Rivers, in response to climatic condition change, this study intended to identify the change points of air temperature and precipitation and characterize the change trend and the contributing factors to streamflow change for the corresponding periods. Hopefully, the findings from this study will help to understand if the preparedness for water security in these major river basins is more imminent than the model predictions.
2. Material and methods
2.1. Study region
The Tibetan Plateau is known as the “Roof of the World” and the “Asian Water Tower.” It extends 2800 kilometers from east to west and 300-1500 kilometers from south to north, covering a total area of 2.5 million square kilometers, with an average altitude of more than 4000 meters. TP is the source of many large rivers, including the Yangtze River, the Yellow River, the Nujiang River, the Lancang River, the Yarlung Zangbo River, the Ganges River, the Indus River, and the Tarim River in the East, Southeast, and South Asia. In this study, we were trying to analyze the change characteristics of climate variables of temperature and precipitation and hydrological variable of streamflow in the headwater basins of these eight major rivers for a comprehensive understanding of the long-term historical change and the spatial variation of climatic and hydrological conditions in the region. Unfortunately, the long-term streamflow data were unavailable for the Ganges, the Indus, and the Tarim Rivers. Shown in Fig. 1 are the headwater basins of the Yangtze River, the Yellow River, the Nujiang River, the Lancang River, the Yarlung Zangbo River, and their streamflow gaging stations, and the subbasin characteristics are listed in Table 1. It is worth noting that the ratios of runoff contribution from the headwater subbasin areas for the Yangtze, Langcang, Nujiang, and Yarlung Zangbo Rivers were less than 0.6 and were 1.88-2.14 for the Yellow River.
2.2. Data preparation
This study used the historical temperature, precipitation, and streamflow data available for the region. As shown in Table 2, the observed precipitation and temperature data for the TP region were obtained from the China Meteorological Data Service Center†
of the China Meteorological Administration (CMA) [25], the gauge-based gridded monthly precipitation data were from the Global Precipitation Climatology Centre (GPCC)‡
(Global Historical Climatology Network Copernicus Atmosphere Monitoring Service (GHCN_CAMS)) [24] were downloaded from National Oceanic and Atmospheric Administration (NOAA), USA, and the observed streamflow data were obtained from the Hydrological Yearbook of China published by the Ministry of Water Resources.
We compared the CMA and GPCC precipitation data for all headwater basins (Fig. 2). It can be seen there is a systematic difference between the two. However, both sets of data are well correlated with the correlation coefficient all above 0.9, such a systematic deviation would not affect the statistical analyses for the change point and changing trend. Since the CMA data were only available for the China site of the TP, this study had to use the GPCC data for complete coverage of the entire TP region.
2.3. Statistical analysis methods
This study adopted the non-parametric statistical methods, the Pettitt test [27] to identify the abrupt change points in time sequence data, and the Mann-Kendall test (M-K) [28] to analyze the trend of a time series. The M-K method does not require the data to obey a specific distribution. The test range is wide, which is suitable for trend testing of random and non-normally distributed hydro-meteorological data.
2.3.1. Pettitt test for change-point detection
The Pettitt test is a non-parametric statistical method that can identify the existence of abrupt change points in time sequence data. For time series data with n samples, the statistical value Ut is assessed for all random variables from 1 to n, and Vt is a temporary statistical value. Ut and Vt are calculated as Eqs. (1), (2) in the following:
in which sgn is the sign function, xt and xj are random variables with xt following xj in time. Kt, which has the largest absolute value in Ut, is selected as the most significant change point, and the statistical value P is expressed as Eq. (4) in the following:
in which a P value of 0.05 or less is often considered as a significant change point and 0.01 or less as very significant.
2.3.2. M-K test for change trend
The M-K test is a commonly used non-parametric statistical test method proven to be reliable for analyzing the trend of a time series. This method does not require the data to obey a specific distribution, and the test range is wide. It is suitable for trend testing of random and non-normally distributed hydro-meteorological data.
The M-K test examines the significance of the standardized M-K statistic Z, with α < 0.05 being a significant change and α < 0.01 being a very significant change. Statistic value S for time series is defined as Eq. (5):
in which n is the number of data points, xi and xj are random variables with xj following xi in time. The positive value of the statistic S indicates an upward trend of the time series; otherwise, a negative value means a downward trend. When the data length n is greater than 8, S can be considered to obey the standard normal distribution assumption, and its expectation E(S) and variance Var(S) can be expressed as Eq. (6) and Eq. (7), respectively:
The standardized statistical value ZS is calculated from Eq. (8):
For a random sequence, the critical test value at the given significance level can be found in the normal distribution table, α is the threshold for statistical significance. 1.96 < |ZS| ≤ 2.58 indicates that the sequence has a significant changing trend at the confidence level of 0.05; when |ZS| > 2.58, it indicates that the data series has a significant changing trend at the confidence level of 0.01.
3. Results and discussion
3.1. Change points of climate and streamflow
We have conducted the Pettitt test on the temperature, precipitation, and streamflow annual time series data to identify the change points with statistical significance. The years when changes might have occurred, and their statistical significance are listed in Table 3. It can be seen that the abrupt change of temperature for the majority of the headwater basins occurred in 1998 and was statistically significant; such a change was consistent with the global change of temperature reported by IPCC [13]. For the annual precipitation, only the headwater basin to ZMD had a significant change in 1980; change points detected for all other headwater basins were not statistically significant. The streamflow at the ZMD, PZH, JYQ, and NX gages had a significant change in 1998-1999; JZ, TNH, and LZ had change points around 1987-1990, and CD had an abrupt change in 2008 but not statistically significant.
In the subsequent M-K trend analysis, in addition to the long-term 1961-2018 temperature data, we divided the data into 1961-1998 and 1999-2018 periods based on the change point around 1998 for temperature with significance. The M-K analysis for precipitation and streamflow was also for the 1961-2018, 1961-1998, and 1999-2018 periods to be consistent with the temperature.
3.2. Long-term trends in climate and streamflow
The time series and the linear regression lines of the 1961-2018 (red line), 1961-1998 (blue dashed line), and 1999-2018 (blue dashed line) periods for the eight headwater basins are plotted in Fig. 3. The magnitudes of change trend as the slope of the linear regression lines listed in Table 4 were expressed in the degree of Celsius per ten-year (°C·decade−1) for temperature, in millimeter per ten-year (mm·decade−1) for precipitation, and billion cubic meters per ten-year (× 109 m3ċdecade−1) and the percentage of change per ten-year (%ċ decade−1) for streamflow. Fig. 4 compares the magnitudes of change trends of the annual temperature, annual precipitation, and annual average streamflow for the eight headwater basins. The M-K trend test was also conducted for the monthly temperature, precipitation, and streamflow data that can help understand the changing trend on a monthly base.
3.2.1. Temperature increased at an accelerated pace
For the 1961-2018 period (Table 4), the AAT has consistently increased in all eight headwater basins, with change rates ranging from 0.20 in the Nuxia basin to 0.37 in the Panzhihua basin. However, the change trends for the 1961-1998 and 1999-2018 periods showed an accelerated increase in temperature since 1998. The temperature increase since 1998 was on a trend averaged at 0.38 °C·decade−1 (Fig. 3 and Table 4), higher than the global change [29] and about three times the increase rate of 0.12 °C·decade−1 from 1961 to 1998 in the eight subbasins. This increasing trend was at a pace similar to the predicted change trend for the Shared Socioeconomic Pathway (SSP)2-4.5 scenario [23]. Alarmingly the increasing trend in the Yarlung Zangbo River basin, the dry and warm valley described by the locals, was as high as 0.63 °C·decade−1 (NX), which was at a pace above the predicted 0.56 °C·decade−1 pace for the SSP3-7.0 scenario.
The statistical Z-value of the M-K test for all months of the year for the 1961-2018 period showed that the average monthly temperature (AMT) had had an apparent rise in all months in all eight headwater basins (Fig. 5), although the statistical significance levels are slightly different. The AMT rise was at significant levels in all months of the year in the headwater basins of the Yangtze, Lancang, and Nujiang Rivers and at a significant level for all months except for January, Febuary, and April in the Yarlung Zangbo headwater basin. The AMT in the headwater basins to TNH and LZ significantly increased in all other months except April and May.
To help us understand the seasonal change in temperature, precipitation, and streamflow, we have compared the percent change of the monthly averages between the 1999-2018 and 1961-1998 periods (Fig. 6). Figs. 6(a-i) and (a-ii) showed a consistent increase of AMT for the 1999-2018 period over the 1961-1998 period, and consistent change patterns geographically. In all headwater basins on the east and northeast sides of the TP, including the Yangtze, Yarlung Zangbo, Langcang, and Nujiang Rivers, AMT has had a moderate increase in the summer months and a significant increase in the winter months since 1998. On the north side of the TP for the Yellow River, although the moderate temperature increase was in the summer and a significant increase was in the winter, the largest increase was delayed to February. The substantial rise in December, January, and February could imply less snow-freezing and reduced ice accumulation [17]. The moderate increase in temperature may magnify the thawing of snow, glacier, and permafrost. The combined effect of temperature increases in the summer and winter with paces between the SSP3-4.5 and SSP3-7.0 predictions could accelerate the retreat and even disappearance of glaciers in the TP.
3.2.2. Temporal and spatial changes of precipitation
Unsurprisingly, the change points for precipitation were insignificant except for ZMD. For consistency with the temperature, this study divided the time series data for precipitation into the 1961-1998 and 1999-2018 periods.
Our analysis indicated the annual average precipitation (AAP) was on an increasing trend from 1961 to 2018 in all headwater basins, with change rates ranging from 0.24 to 10.83 mm·decade−1. AAP was also on the increasing trend in all headwater basins for the 1961-1998 period, with change rates of 0.36-8.52 mm·decade−1. However, the change trend of AAP has had major shifts since 1998. The AAP on the east part of the TP, including the headwater basins of the Yangtze, Yarlung Zangbo, Langcang, and Nujiang Rivers, turned to be on decreasing trends with change rates from −7.12 to −72.72 mm·decade−1. On the contrary, in the headwater basins for the Yellow River, the AAP for the 1999-2018 period was higher than the 1961-1998 period and on an increasing trend as high as 89.87-101.26 mm·decade−1 (Table 4).
Climate change in the TP region has also resulted in an apparent interannual variation of precipitation (Fig. 6). The average monthly precipitation (AMP) in the headwater basins for the Yangtze, Yarlung Zangbo, Langcang, and Nujiang Rivers was reduced in November and December but had increased in all other months. In the Yellow River headwater basin, AMP had increased for all months except for July and August.
3.2.3. Change of headwater streamflow and contributing factors
Changes in precipitation had direct impacts on the streamflow and glacier retreat, snow melting, permafrost degradation, and change of land surface conditions subsequently had indirect impacts on streamflow through altered hydrological processes. Statistically, there has been an overall increase of streamflow for all headwater basins on the east part of the TP region except for JZ for the 1961-2018 period, among which the change rate at ZMD, PZH, CD, and JYQ was greater than 2%·decade−1. However, the streamflow of the TNH and LZ headwater basins of the Yellow River had a decreasing trend for the 1961-2018 period with a percent change greater than −2%·decade−1. Such a conclusion is consistent with the findings of Zhang et al. [12]. However, understandably the change characteristics from statistical analysis would be different if we analyze the time series data for different periods. In this study, we were particularly interested in the impact of abrupt temperature since 1998 on streamflow. We found noticeable shifts of change trends of precipitation and streamflow for the periods before and after 1998.
As seen in Table 4, precipitation for all eight subbasins was on an increasing trend for the 1961-1998 period but turned to a decreasing trend on the east part of the TP region and an accelerated increase trend for the Yellow River headwater subbasins from 1999 to 2018. As the results of combined effects of precipitation, glacier and snow melting, and permafrost thawing, streamflow shifted from negative change rates of −4.60%·decade−1 and −5.87%·decade−1 before 1998 to positive rates of 13.03%·decade−1 or 1.74× 109 m3·decade−1 and 17.25%·decade−1 or 2.69 × 109 m3·decade−1 after 1998 at ZMD and CD, although the precipitation was on a decreasing trend after 1998. Such changes in the headwater basins may have been due to the increased snow and glacier melting that compensated for the loss of recharge from precipitation.
However, at PZH, downstream of ZMD, and at JZ, downstream of CD, streamflow had an accelerated pace of reduction with negative rates of −5.88 × 109 m3·decade−1 (−10.43%·decade−1) and −5.08 × 109 m3·decade−1 (−16.89%·decade−1), respectively for the 1999-2018 period, which was more coincide with the changing trend of precipitation in the area. Streamflows at JYQ and NX were also on a decreasing trend with change rates of −3.03 × 109 m3·decade−1 (−12.11%·decade−1) and −5.45 × 109 m3·decade−1 (−9.12%·decade−1) from 1999 to 2018, which were quite significant.
For the Yellow River, the streamflow change trends at the TNH and LZ stations were reversed from decreasing for the 1961-1998 period to increasing since 1998. The increasing rates at both gaging locations were as high as 2.47 × 109 m3·decade−1 (8.04%·decade−1) and 4.39 × 109 m3·decade−1 (14.29%·decade−1), respectively, which positively responded to the increased precipitation of as much as 101.26 and 89.87 mm·decade−1 in the TNH and LZ subbasins.
It is apparent that there were significant differences in the change characteristics of precipitation and streamflow for analysis based on the 1961-2018 period and when the data were divided into the 1961-1998 and 1999-2018 according to the abrupt change point for temperature. The comparative analysis in this study showed dividing the time series data based on the change point would be more informative and also imperative for trend analysis.
We have also conducted the correlation analysis between precipitation and streamflow to understand how significantly the precipitation would have impacted the streamflow for the 1961-2018, 1961-1998, and 1999-2018 periods (Table 5). Correlation coefficients indicated that streamflow in the headwater basins of the Yangtze, Yarlung Zangbo, Langcang, and Nujiang Rivers correlated well with precipitation (Table 5), with correlation coefficients ranging from 0.66-0.85 for the 1961-1998 period and 0.60-0.76 for the 1999-2018 period. The slightly reduced correlation with precipitation could imply that snow and glacier melting played an increasing role in the streamflow due to accelerated warming in the region. For the Yellow River, streamflow at TNH was negatively correlated with precipitation. In contrast, at LZ, the correlation coefficient for the 1961-1998 period was 0.68 but dropped to 0.18 for 1999-2018 due to human activities such as water withdrawal and damming for hydropower. Although the melting glaciers in the TP are predicted to cause a reduced water supply in the coming decades [4], [17], [30], [31], in the headwater basins for the Yangtze, Yarlung Zangbo, Langcang, and Nujiang Rivers, rainfall and snowmelt contribute to more than 88% of the streamflow, less than 11.60% of the streamflow was from glacier melt (Table 6) [32].
4. Conclusions
In conclusion, our analysis indicated that the AAT in the headwater basins of these five major rivers has been increasing on a trend averaging 0.38 °C·decade−1 since 1998, more than triple the increasing rate for the 1961-1998 period; such a change is at a pace similar to the SSP2-4.5 scenario. The increase in the Yarlung Zangbo River basin was alarmingly as high as 0.63 °C·decade−1, even above the predicted 0.56 °C·decade−1 for the SSP3-7.0 scenario.
Precipitation in the headwater basins for the Yangtze, Yarlung Zangbo, Langcang, and Nujiang Rivers had an apparent reduction since 1998, with a change rate of −7.12 to −72.72 mm·decade−1. In contrast, precipitation in the headwater basins of the Yellow River had a significant increase since 1998, with a trend as high as 89.87-101.26 mm·decade−1.
Although glacier retreat has had and will have a profound impact on river runoff, the change in precipitation has had a significant impact on the change in streamflow characteristics. The increased precipitation in the TNH and LZ basins contributed to the increase of streamflow at rates of 2.47 × 109 m3·decade−1 (8.04%·decade−1) and 4.39 × 109 m3·decade−1 (14.29%·decade−1), respectively. On the other hand, as a result of the reduced precipitation, streamflow in the headwater basins for the Yangtze, Yarlung Zangbo, Lancang, and Nujiang River basins has been dropping, with flow reduction rates ranging from −9.12%·decade−1 to −16.89%·decade−1. Such change trends caused by climate change in the TP region may lead to a water crisis in China and Southeast and South Asia.
Seasonally, the significant increase in temperature in the winter and moderate growth in the summer could change the freezing condition of snow and glacier and the thawing of permafrost in the region. The AMP in the southeastern TP areas was reduced in November and December, possibly due to reduced snowfall, but increased from April to June. In the Yellow River headwater basin, AMP was reduced in July and August but increased for all other months. The streamflow had an apparent increase from November to March of next year but a decrease in streamflow around the summer, particularly in August, in all headwater basins.
Such changes reflected the altered seasonal hydrological characteristics in these river basins due to the impact of global warming on temperature and the subsequent glacier retreat, reduction of snow cover and depth, degradation of permafrost, changes in precipitation, and so forth. The comparative analysis in this study showed dividing the time series data based on the change point would be more informative and also imperative for trend analysis.
Acknowledgments
This research was funded by the Second Tibetan Plateau Scientific Expedition and Research Program (2019QZKK0203) and the National Key Research and Development Programs of China (2021YFC3201100).
Compliance with ethics guidelines
Zhenxin Bao, Jianyun Zhang, Yanqing Lian Guoqing Wang, Junliang Jin, Zhongrui Ning, Jiapeng Zhang, Yanli Liu, and Xiaojun Wang declare that they have no conflicts of interest or financial conflicts to disclose.
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