Quantitative evaluation of the impact of climate change and human activities on Jialing river runoff changes in the past 60 years, China

The natural fluctuation of runoff maintains the shape of the river basin, biodiversity, and biological habitat conditions, thus ensuring the stability of the ecosystem (Cloern et al. 2016). With the enhancement of human activities and climate change, the natural runoff process in the basin has been affected to varying degrees, which in turn has changed the regional water cycle conditions. Therefore, assessing the degree of alteration in runoff and quantifying the impact of human activities and climate change is an important way to clarify the changing mechanism of the watershed's hydrological regime and the law of its response.

Attribution analysis of runoff changes at home and abroad usually uses the elastic coefficient method and hydrological model to quantify the impact of human activities and climate change on runoff. Schaake (1990) was the first to describe the sensitivity of runoff to changes in precipitation through the elastic coefficient method. After the improvement, the elastic coefficient method has been extended to a variety of climatic factors, for example, temperature (Fu et al. 2007), potential evapotranspiration (Liu et al. 2013), relative humidity (Dooge et al. 1999), wind speed and solar radiation (Yang & Yang 2011), and quantify the elastic coefficient by the nonparametric method (Sankarasubramanian et al. 2001; Ma et al. 2010) or Budyko formula (Arora 2002; Xu et al. 2014). Hydrological models can be implemented at different scales and have certain mechanistic explanations, but the data requirements are stricter, and there are uncertainties in parameter estimation. Lotfirad used the IHACRES rainfall-runoff model for river flow simulation to assess the impact of climate change on runoff and hydrological drought in the Hablehroud river basin in central Iran (Lotfirad et al. 2021). Xin et al. (2019) used the abcd model to quantify the effects of climate and human activities on seasonal-scale runoff changes in the Huifa River basin. On the time scale, it is still difficult to replace the hydrological model on the seasonal and daily scales, while on the annual scale, such as the water–heat balance theory based on the Budyko hypothesis, the calculation is relatively simple, and the parameters are easy to obtain, which has certain advantages in dealing with related problems. Follow-up researchers proposed the elastic coefficient method based on the Budyko hypothesis, which was used to separate the impact of climate change on runoff and quantify the contribution of the unit climate factor change, which has been widely used.

As the largest tributary in the Yangtze River basin, the Jialing River is the main source of runoff in the upper reaches of the Yangtze River. The change of its runoff directly affects the runoff change of the mainstream of the Yangtze River. In recent years, with the intensification of climate change (rainfall, evapotranspiration) and human activities (reservoir construction and operation, land use, etc.), the spatial and temporal patterns of the water cycle in the basin have changed accordingly, altering the exploitation and natural distribution of water resources and gradually expanding the impact on the ecological environment of the basin (Wu et al. 2018). Relevant scholars have done a lot of research on the hydrological situation of the Jialing River. Li et al. (2020) studied the long-term change pattern of Jialing River runoff and found that the influence of climate change on runoff showed a weakening trend, and the influence of human activities gradually increased and dominated. Richter et al. (1996) was the first to develop the ecological hydrological index variation range method IHA. After continuous improvement by later scholars, this method has been widely used in hydrological changes and ecological effects (Richter et al. 1998; Bin Ashraf et al. 2016; Gao et al. 2018; Huang et al. 2019; Yang et al. 2020). Ding et al. (2008) applied mathematical models to reveal the causes of annual runoff and sand transport changes in the Jialing River basin, and investigated the relationship between precipitation and sand transport, and human activities and sand transport. Zhou et al. (2020) quantitatively evaluated the contribution of climate change and human activities to runoff changes in the Jialing River using an improved double mass curve, attributing the main factors to human activities such as the construction of large reservoirs and land use after 1985, and concluded that the multi-year scale annual average runoff in the Jialing River basin showed a decreasing trend, and the contribution of human activities to runoff changes in the basin reached 65%. Meanwhile, for the attribution analysis of runoff changes in the Jialing River, although some scholars have quantitatively assessed the contributions of different factors, the influence of river evapotranspiration, and the response between runoff changes and each element have rarely been considered. Analyzing the degree of contribution of multiple influencing factors to runoff changes in the basin is beneficial to promote ecological restoration and sustainable development of the Yangtze River basin. Therefore, further research is needed.

The purpose of this study is to quantify the contribution rates of climate change and human activities to the runoff changes in the Jialing River basins over a long time series. Taking 1985 as the abrupt year, a series of ecological indicators were used to evaluate the runoff of the Jialing River. Combined with the ecological response mechanism under the change of the hydrological regime in the Jialing River basin, the response law of the runoff regime before and after the abrupt period was deduced. The hydrothermal coupling theory based on the Budyko elastic coefficient method and the method of the slope change rate of cumulants were used for comparative analysis to separate and quantitatively evaluate the influence of climatic factors (rainfall, potential evapotranspiration) and human activities to runoff change. The Jialing River Basin is divided into three sub-basins for specific analysis, and the differences in the impact of human activities and climate change on runoff changes are distinguished in time and space, which fills the gap of this research basin, achieves understanding and protects the health status of the basin, and realizes the realization of water resources in the basin. For sustainable regulation, the research results have important guiding significance for the restoration of watershed habitats.

In this study, we selected daily flow data from 1957 to 2017 at Beibei hydrological station in the Jialing River basin, and annual flow data from Xiaoheba, Wusheng, and Luoduxi hydrological stations, with mean values of 2,097.82, 437.54, 783.1, and 680.55 m³/s, respectively. The above data are from the ‘‘Hydrological Yearbook of Yangtze River Basin’’. The meteorological data were obtained from 12 meteorological stations in the Jialing River basin, including precipitation, maximum temperature, minimum temperature, air pressure, relative humidity, etc. The average values in the basin were obtained through Tyson polygons as 962.62 mm, 21.41°C, 13.82°C, 972.24 hpa, and 78.97%. These data were obtained from the China Meteorological Data Network (http://data.cma.cn/). Based on gridded data from 1998 to 2020 with a 1 km resolution, the Normalized Difference Vegetation Index (NDVI) employed in this study first calculates the monthly NDVI using the maximum approach and then means the monthly NDVI to calculate the yearly NDVI. NDVI data for each period are obtained from the Resource and Environment Science and Data Center of the Chinese Academy of Sciences (https://www.resdc.cn/data.aspx), and the data production is based on the Landsat TM/ETM remote sensing images of each period as the main data source and generated by manual visual interpretation.

Since the Mann–Kendall nonparametric test method is not affected by outliers when analyzing hydrological data, it has been widely used in the hydrological analysis. In this study, the M-K method is used to identify the evolution law of Jialing River runoff, and to determine the year of the sudden change in the hydrological conditions of the basin (Burn & Elnur 2002; Kahya & Kalaycı 2004). The mean difference T-test method was used to verify the runoff mutation year obtained by the M-K nonparametric test method. The specific calculation principle of the method is shown in Huntington (2006).

In this formula, ‘W’ is the wavelet transform coefficient; ‘’ is a signal or square-integrable function; ‘a’ is the scale factor, reflecting the period length of the wavelet; ‘b’ is the translation factor, reflecting the translation in time ‘’ is the complex conjugate for ‘’.

In this formula, ‘D_i’ represents the change degree of the ith index; ‘D_o’ represents the overall flow change degree; ‘N_oi’ represents the number of years that the ith disturbed flow index falls within the RVA threshold; ‘N_e’ represents the expectation that the runoff index is expected to fall within the RVA threshold after disturbance Years; ‘r’ represents the proportion of the runoff index falling within the RVA threshold before disturbance, taking 50%; ‘n’ represents the number of indicators. The scale of change is specified: 0–33% is low change (L); 33–67% is moderate change (M); 67–100% is high change (H).

In the formula, ‘ET₀’ is the potential evapotranspiration (mm); ‘Δ’ is the slope of saturated vapor pressure curve (kPa/°C); ‘R_n’ is net radiation MJ/(m²·d); ‘G’ is soil heat flux MJ/(m²·d); ‘’ is the wet and dry constant (kPa/°C); ‘T’ is the average temperature (°C); ‘u₂’ is the wind speed at 2 m above the ground (m/s); ‘e_s’ is the saturated vapor pressure (kPa); ‘e_a’ is the actual water vapor pressure (kPa). In the formula, the ‘ ΔR_n’, ‘G’, ‘’, ‘e_s’, and ‘e_a ’ can be obtained from meteorological data such as the average temperature, average maximum, minimum temperature, relative humidity, sunshine hours, and so on of each site.

In the formula, ‘ΔQ’ is the change of flow before and after the abrupt period; ΔQ_C and ΔQ_H are the runoff changes caused by climate change and human activities, respectively; ‘η_C’ and ‘η_H’ are the contribution rates of climate change and human activities to the runoff change, respectively.

In the formula, ‘ΔE₀’ and ‘ΔP’ are the changes in potential evapotranspiration and precipitation before and after the mutation period, respectively; ‘’ and ‘’ are the elastic coefficients of runoff to rainfall and potential evapotranspiration, respectively; The ‘’ and ‘’ in the formula is detailed in Table 2.

Table 2

Formula details

Number .	.	.	Literature Resources .
1			Zhang et al. (2001)
2			Fu (1981)
3			Schreiber (1904)
4			Budyko (1948)
5			Pike (1964)
6			Ol'dekop (1911)

Number .	.	.	Literature Resources .
1			Zhang et al. (2001)
2			Fu (1981)
3			Schreiber (1904)
4			Budyko (1948)
5			Pike (1964)
6			Ol'dekop (1911)

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Since there may be mutation points with low mutation reliability in the testing process of this method, considering that there are multiple mutation years that pass the 90% significance test, the mean difference T-test (Table 3) is used to verify the double mutation of the results. The study finally attributed the sudden change in the hydrological evolution of the Jialing River Basin to 1985.

Table 3

Results of Mann–Kendall analysis of the runoff discharge variation trend at the main hydrologic stations in the Jialing River

Hydrometric station .	Beibei .	Xiaoheba .	Wusheng .	Luoduxi .
ZC	−2.69	−3.29	−2.44	−0.86
Inspection criterion
Tendency	Significant reduction	Significant reduction	Significant reduction	Insignificant reduction

Hydrometric station .	Beibei .	Xiaoheba .	Wusheng .	Luoduxi .
ZC	−2.69	−3.29	−2.44	−0.86
Inspection criterion
Tendency	Significant reduction	Significant reduction	Significant reduction	Insignificant reduction

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In this study, the daily flow data of Beibei Station from 1957 to 2017 were used to analyze the flow change of the entire Jialing River basin before the abrupt change. The natural state range of 32 hydrological indicators was defined with the daily flow data before the mutation, and the number of years when the 32 parameters of the daily flow fell within the target range after the mutation was calculated to measure the degree of alteration of the parameters of runoff change. Usually, the average value of each index parameter of the natural state flow series plus or minus the standard deviation or 33–67% of the frequency of each index is the upper and lower thresholds.

According to Figure 12(b), it is seen that the potential evapotranspiration and the runoff depth change in opposite trends, and the potential evapotranspiration and the runoff depth show a negative correlation change. Before and after the mutation, the change rate of potential evapotranspiration with runoff depth decreased from 0.285 to 0.167, indicating that the effect of potential evapotranspiration was weak. Similarly, the correlation coefficient decreased from 0.367 to 0.07, indicating that the potential evapotranspiration was affected by the impact of runoff changes gradually weakening.

To sum up, rainfall dominates the climatic factors in the Jialing River Basin, which is the key factor leading to the change in runoff. This is consistent with the research results of Guo et al. (2015) and others. It shows that the potential evapotranspiration in the Jialing River Basin has a certain degree of influence on the runoff change and can be ignored. The extent can be ignored. However, with the gradual increase of human activities, the impact of climate on runoff has been relatively diluted, and human activities have gradually played a leading role in the change of runoff (Hayashi et al. 2015).

Since the 1980s, the land-use situation in the Jialing River Basin has also changed accordingly. Wang et al. (2019) used the SWAT model to quantitatively analyze the land-use change in the Jialing River Basin from 1985 to 2005 by constructing a variety of scenarios. The study found that the forest land in the basin decreased by about 399 km², the urban construction land increased by about 57 km², the cultivated land, grassland, and industrial land showed different changes in different regions. The cultivated land in the upstream area increased by 71 km², the middle and lower reaches decreased by about 174 km², the grassland in the upper reaches decreased by about 7 km², while the grassland and industrial land increased by about 307 and 26 km² in the middle and lower reaches, respectively.

To sum up, the effects of human activities on runoff change are presented in different aspects. Among the underlying surface factors, the common influence of various soil and water conservation work, farmland irrigation, the joint operation of cascade reservoirs, and land use (Hu et al. 2016) should also be considered.

Changes in runoff patterns under natural conditions can be used as important indicators to evaluate the level of ecological diversity and the vulnerability of the ecological environment in the basin. Ecological environment vulnerability refers to the description of the ecosystem's ability to resist external disturbances and self-repair after damage (Zhang et al. 2009) and is affected by both climatic factors and human activities. Under the influence of strong external disturbance, fragile ecosystems may have irreversible effects on the health, stability, balance, and evolution of the ecosystem.

The Jialing River Basin is rich in fish diversity, with many endemic fish species, currently occupying one third of the entire Yangtze River Basin (Wei et al. 2012). With the construction of a series of cascade hydropower stations, the expansion of the catchment area of the reservoir area and the slowing of the flow rate, the original water ecological environment of the river has been changed, and the growth and reproduction of fish with migratory characteristics, suitable for rapids habitat characteristics, and drifting egg-producing characteristics have been hindered. Waters suitable for fish growth and reproduction are affected (Liu et al. 2021). However, with the increase of the catchment area of the reservoir area, the fishery production potential of the reservoir area has increased. Some still-water-loving fish may increase with the increase of plankton in the reservoir area, such as carp, crucian carp, and some cucurbits, which can promote the increase of fishery production in some reservoir areas (Yu et al. 2014).

Taking the southern section of the middle reaches of Jialing River as an example, there are about 28 species of waterfowl observed at present, among which the spotted duck, red-billed gull, and cormorant account for 50.87% of the total number of birds in this area (Guo-fu & Xue-fu 2008). In recent years, the survey found that the number of waterfowl has gradually decreased. The reason is that the ‘canalization’ of the Jialing River and the construction of cascade reservoirs have led to the flooding of large-scale river floodplains, central bar, and other suitable places for waterfowl to live in the basin. The surrounding ecological environment has been changed so that it is difficult to form new suitable habitats through natural restoration in the short term (Fang & Hui-Ling 1998). Therefore, the reduction of suitable habitats for waterfowl in the watershed is the direct cause of the decline.

To determine the impact of climate change and human activities on runoff patterns in the Jialing River Basin. This study comprehensively assessed the hydrological regime from the aspects of interannual and intraannual variation characteristics, abrupt changes, and periodic fluctuations, and quantified the degree of alteration in runoff processes under changing environments with the help of IHA-RVA. Then, this study constructs Budyko model based on the principle of water balance, quantitatively separates the effects of climate change and human activities, and tests the results with the help of SCRAQ method. The results can be summarized as follows:

• (1)

  According to the test results of the Mann-Kendall nonparametric test method and the mean difference T-test method, the runoff of the four hydrological stations on the Jialing River from 1957 to 2017 showed a downward trend, and all passed the 95% significance test, and finally determined that the 1985 year is the mutation year.

• (2)

  The Joint Reservoir Group has an obvious peak-shaving effect on the average annual runoff in the Jialing River Basin. After the mutation period, the monthly median flow rate of Beibei Station showed a downward trend in March and an upward trend in September, and both reached a high degree of alteration. The duration of the extreme flow at Beibei Station showed a downward trend, and the number of low-flow pulses increased and reached a high degree of alteration. The overall flow change in the Jialing River Basin is 50.87%, which is a moderate change.

• (3)

  Human activities are an important factor in the runoff change of the Jialing River. The contribution rates to the runoff changes in the Fu River Basin, the Qu River Basin, the Jialing River Main Stream, and the Bailong River Basin are 64.57, 74.14, and 66.31% respectively. The sensitivity of runoff to rainfall and potential evapotranspiration is the same, the contribution rate of rainfall to it is 27.10, 29.90, and 23.10%, respectively; the contribution rate of potential evapotranspiration to runoff change is about 5%.

The results of the study help to understand the characteristics and driving mechanisms of the evolution of the hydrological situation in the Jialing River basin under the changing environment, and provide a reference for policy-makers to develop water management countermeasures to accommodate climate change and intensified human activities. The next research should focus on building a comprehensive framework based on the existing results, combining hydrological models to restore natural flows while distinguishing the effects of different types of human activities (land-use change, reservoir scheduling, and human water withdrawal) on the changes of basin runoff, which will analyze the basin water resources system from a more comprehensive perspective and provide valuable information for adjusting different types of human activity responses.

H.W. conducted funding acquisition, administered the project, brought resources, conducted an investigation, and supervised the work. Y.M. conceptualized the whole article, conducted data curation, formal analysis, investigation, developed the methodology, brought resources, developed the software, validated and visualized the article, wrote the original draft, and wrote the review and edited the article. H.Y. conducted an investigation and a formal analysis, developed the methodology, and validated and visualized the article. F.H. visualized the article and conducted investigation and formal analysis. W.G. conducted funding acquisition and administered the project.

This study was supported by the National Natural Science Fund of China (51779094); The 2016 Henan University Science and Technology Innovation Talent Support Plan (16HASTIT024); The Guizhou Provincial Water Resources Department 2020 Water Conservancy Science and Technology Project (KT202008).

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.