Li Wang

Soil erosion is one of the global threats to the environment. Further, climate and vegetation changes have pronounced effects on soil erosion in high-mountain areas. In this study, the revised universal soil loss equation (RUSLE) was improved by developing a method for calculating snowmelt runoff erosivity based on a simulated snowmelt runoff and the observed sediment load, using which the soil erosion rate in the upper Heihe River Basin (UHRB) was calculated. The proposed approach provides an effective method for estimating the soil erosion rate and identifying the causes for its change in high-mountain areas. The normalized difference vegetation index (NDVI) was significantly and positively correlated with both precipitation and temperature in the region and exhibited a significant increasing trend. The increase in NDVI led to a decrease in the soil erosion rate (for the annual, rainfall, and snowmelt periods), although erosive rainfall and snowmelt runoff showed increasing trends, indicating the dominating impact of vegetation cover on soil erosion. The average soil erosion rate of UHRB was 806.2 t km⁻² a⁻¹ from 1982 to 2015. On average, soil erosion during rainfall and snowmelt periods contributed to 90.67% and 9.33% of annual soil erosion, respectively. However, the resultant soil erosion rate caused by 1 mm of snowmelt runoff was about 1.9 times that caused by 1 mm erosive rainfall. Soil erosion during the snowmelt period was particularly sensitive to temperature and showed consistent responses to climate and vegetation changes in UHRB and its two tributaries. An increasing NDVI promoted by climate change and anthropogenic factors played a major role in alleviating soil erosion, and the warming exerted intense impacts on soil erosion during the snowmelt period. These findings would be helpful for proposing effective measures for soil conservation in high-mountain areas under climate and vegetation changes.

Water resources and the water cycle in high mountain areas are significantly impacted by climate change. In this study, the midstream section of the Yarlung Tsangpo River basin, situated in the southern part of the Tibetan Plateau, was chosen as the target area, and the Soil Water Assessment Tool (SWAT) was used to assess how climate change may affect hydrological processes. The SWAT model proved effective for runoff and snow cover area simulation. Surface runoff, interflow, and groundwater accounted for 47.2%, 24.4%, and 28.4% of the total runoff, respectively. The spatial distribution of runoff was mainly influenced by precipitation and glacier distribution, whereas the spatial distributions of individual runoff components were mainly influenced by soil properties. Overall, the total runoff as well as its components (surface runoff, interflow, and groundwater) increased at a rate of 0.03–0.83%/10 yr (p > 0.05) in the study area during 1983–2017, which could be attributed to the increase in precipitation. Surface runoff peaked earlier (August) than interflow and groundwater (September), owing to the longer convergence time of interflow and groundwater. Future predictions showed a warming and wetting trend (p < 0.05) in the study area from 2020 to 2100 under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios. The total runoff was projected to increase at a rate of 0.92–3.56%/10 yr, and the change of total runoff mainly came from the increase of surface runoff.

Alpine lakes on the Tibetan Plateau have significantly changed under a changing climate over past decades. However, the changing patterns of the inflow sources of the lakes, i.e., rainfall and the melt water of snow and glaciers, and their response to climate change remain uncertain because obtaining accurate precipitation and melt water discharge is difficult due to the complex topography, spatial variability, and scarce stations of the alpine area. A distributed hydrological model, J2000, was employed in this study to simulate runoff component variations of the Yamzho Yumco Lake glaciated basin during 1974–2019. Except for observed daily runoff from two tributaries, a High Asia Refined (HAR) high-resolution reanalysis of precipitation data was combined with field precipitation gradient observation and snow cover area validation, all performed simultaneously to reduce the uncertainty of inflow components in the model. Results showed that the average runoff into the lake during 1974–2019 was 5.5 ± 1.4 × 10⁸ m³/10a, whereas rainfall runoff, glacier melt runoff, snowmelt runoff, and baseflow contributed to 54.6%, 10.8%, 1.8%, and 32.7% of total runoff in mean, respectively. Seasonal runoff in spring, summer, autumn, and winter accounted for 6.7%, 60.6%, 23.9% and 8.8% of annual total runoff, respectively. In glacial areas, the reduction in total runoff after removing the precipitation trend was 1.4 times than that of temperature, and in non-glacial areas, the reduction in total runoff after removing the precipitation trend was 1.6 times than the increase in total runoff after removing the temperature trend. The proportion of rainfall runoff increased at a rate of 1.0%/10a, whereas the proportion of melt runoff decreased at a rate of 0.07%/10a during the study period.

Climate change has a wide range of impacts on Pakistan’s water resources system, followed by increased magnitude, frequency and intensity of extreme events. Therefore, investigating the variations in extreme climatic events is vital in planning and developing agriculture and water conservation projects. Hence, the present study investigated the spatiotemporal variability of extreme precipitation indices (EPIs) over the Jhelum River basin (JRB) using the Mann-Kendall (MK) and innovative trend analysis (ITA) methods. In addition, variations in the event-based extreme precipitation (EEPs) and time distribution patterns (TDPs) were analyzed because EPIs considered the daily precipitation values only and the combined effect of the extreme events that last for more than 1 day were often neglected. The results show that the fixed and station-related EPIs, i.e., R10, R20, R25, CWD, Prcpt and R95p, exhibited significant decreasing trends at 06, 05, 04, 04, 07 and 05 stations, whereas an increasing trend was evident for consecutive dry days (CDD) at nine stations with a magnitude of 0.33 days/year, indicating a rise in the drought events compared to floods. Moreover, precipitation events with an amount of 40–290 mm, duration of 4–7 days and concentration ratio of 0.7–0.95 were found to be dominant across JRB. Therefore, an increase in the CDD and a decrease in the consecutive wet days (CWD) may change the magnitude, intensity and frequency of extreme precipitation events and consequently pressure the availability of water resources. Therefore, the findings of this study may help understand the precipitation variability over JRB and play a pivotal role in future development projects.

The impact of climate change on soil erosion is pronounced in high mountain area. In this study, the revised universal soil loss equation (RUSLE) model was improved for better calculation of soil erosion during snowmelt period by integrating a distributed hydrological model in upper Heihe river basin (UHRB). The results showed that the annual average soil erosion rate from 1982 to 2015 in the study area was 8.1 t ha-1 yr-1, belonging to the light grade. To evaluate the influence of climate change on soil erosion, detrended analysis of precipitation, temperature and NDVI was conducted. It was found that in detrended analysis of precipitation and temperature, the soil erosion of UHRB would decrease 26.5% and 3.0%, respectively. While in detrended analysis of NDVI, soil erosion would increase 9.9%. Compared with precipitation, the effect of temperature on total soil erosion was not significant, but the detrended analysis of temperature showed that the effect of temperature on soil erosion during snowmelt period can reach 70%. These finding were helpful for better understanding of the impact of climate change on soil erosion and provide a scientific basis for soil management in high mountain area under climate change in the future.

The glacier ratio influences both the contribution of meltwater runoff and the response of the basin's hydrological processes to climate change. In this study, the Karuxung, the Tuotuo and the Babao river basins with glaciers accounting for 20.7%, 2.1% and 0.38% respectively, were selected to study their hydrological processes under the climate change. Based on the daily runoff data of 30 years and MODIS snow cover products, the J2000 model was applied to quantify the contribution of meltwater and rainfall runoff, analyze the temporal and spatial variation characteristics of runoff and clarify the influence of climate change on these three basin. The main findings are as follows: (1) The contribution of glacier and snow melt runoff for the Karuxung, Tuotuo and Babao river basin was 60.7%, 25.3% and 19.9%, respectively. The contribution of rainfall runoff for the three basins was 39.3%, 74.7% and 81.1%, respectively. (2) The peak of glacier and snow melt runoff converted from summer to spring with the glacier ratio decreasing. (3) The runoff supplies in the Karuxung, Tuotuo and Babao river basin were from the 5500m-6500m, 4500m-5500m zone, and 3500m-4500m elevation zone, respectively. (4) The runoff and its components in the Karuxung and Tuotuo river basins showed significant increasing trends while the Babao river basin showed no significant change trends. (5) In the Karuxung river basin with large glacier ratio, the increase in temperature mainly caused the increase of meltwater and runoff, showing a positive impact on runoff. For the Tuotuo and Babao river basin with small glacier ratios, the increase in temperature mainly caused increased evaporation and reduced runoff, showing a negative impact on runoff.