Impacts of multiple climate factors and vegetation changes on evapotranspiration in Southwest China from 1982 to 2018

Uncovering the impact of climate and vegetation changes on runoff in karstic regions of southwest China

Abstract. Hydrological processes are widely understood to be sensitive to changes in climate, but the effects of concomitant changes in vegetation and soils have seldom been considered in snow-dominated mountain basins. The response of mountain hydrology to vegetation/soil changes in the present and a future climate was modeled in three snowmelt-dominated mountain basins in the North American Cordillera. The models developed for each basin using the Cold Regions Hydrological Modeling platform employed current and expected changes to vegetation and soil parameters and were driven with recent and perturbed high-altitude meteorological observations. Monthly perturbations were calculated using the differences in outputs between the present- and a future-climate scenario from 11 regional climate models. In the three basins, future climate change alone decreased the modeled peak snow water equivalent (SWE) by 11 %–47 % and increased the modeled evapotranspiration by 14 %–20 %. However, including future changes in vegetation and soil for each basin changed or reversed these climate change outcomes. In Wolf Creek in the Yukon Territory, Canada, a statistically insignificant increase in SWE due to vegetation increase in the alpine zone was found to offset the statistically significant decrease in SWE due to climate change. In Marmot Creek in the Canadian Rockies, the increase in annual runoff due to the combined effect of soil and climate change was statistically significant, whereas their individual effects were not. In the relatively warmer Reynolds Mountain in Idaho, USA, vegetation change alone decreased the annual runoff volume by 8 %, but changes in soil, climate, or both did not affect runoff. At high elevations in Wolf and Marmot creeks, the model results indicated that vegetation/soil changes moderated the impact of climate change on peak SWE, the timing of peak SWE, evapotranspiration, and the annual runoff volume. However, at medium elevations, these changes intensified the impact of climate change, further decreasing peak SWE and sublimation. The hydrological impacts of changes in climate, vegetation, and soil in mountain environments were similar in magnitude but not consistent in direction for all biomes; in some combinations, this resulted in enhanced impacts at lower elevations and latitudes and moderated impacts at higher elevations and latitudes.

Vegetation and climate evolution during the Last Glaciation at Tengchong in Yunnan Province, Southwest China

The rapidly warming Arctic is experiencing permafrost degradation and shrub expansion. Future climate projections show a clear increase in mean annual temperature and increasing precipitation in the Arctic; however, the impact of these changes on hydrological cycling in Arctic headwater basins is poorly understood. This study investigates the impact of climate change, as represented by simulations using a high-resolution atmospheric model under a pseudo-global-warming configuration, and projected changes in vegetation, using a spatially distributed and physically based Arctic hydrological model, on a small headwater basin at the tundra–taiga transition in northwestern Canada. Climate projections under the RCP8.5 emission scenario show a 6.1°C warming, a 38% increase in annual precipitation, and a 19 W m−2 increase in all-wave annual irradiance over the twenty-first century. Hydrological modeling results suggest a shift in hydrological processes with maximum peak snow accumulation increasing by 70%, snow-cover duration shortening by 26 days, active layer deepening by 0.25 m, evapotranspiration increasing by 18%, and sublimation decreasing by 9%. This results in an intensification of the hydrological regime by doubling discharge volume, a 130% increase in spring runoff, and earlier and larger peak streamflow. Most hydrological changes were found to be driven by climate change; however, increasing vegetation cover and density reduced blowing snow redistribution and sublimation, and increased evaporation from intercepted rainfall. This study provides the first detailed investigation of projected changes in climate and vegetation on the hydrology of an Arctic headwater basin, and so it is expected to help inform larger-scale climate impact studies in the Arctic.

Due to the special nature of karst landforms, quantification of their vegetation dynamics and their underlying driving factors remains a formidable challenge. Based on the NDVI dataset, this study uses principal component analysis to extract comprehensive factors and utilizes an optimized parameter-based geographical detector and geographically weighted regression models to assess the explanatory capacity of comprehensive factors concerning the spatial differentiation of vegetation change. The results of this study revealed the following: (1) In terms of temporal and spatial vegetation changes, the Asian karst concentrated distribution area (AKC) displayed overall stability and an increasing trend between 2000 and 2020. Notably, the northern (Southwest China) karst region experienced the most substantial vegetation increase, with increased areas exceeding 70%, primarily concentrated in the provinces of Guizhou and Guangxi. In contrast, the southern (Indochina Peninsula) karst region, particularly in Cambodia, Laos, and Vietnam (CLV), exhibited a significant decreasing trend, with decreased areas exceeding 30%. (2) By analyzing the driving factors affecting vegetation change, vegetation changes exhibited distinct spatial differentiations, along with positive and negative effects. Human factors, including human activity intensity, urban economic development, and agricultural economic development (explanatory power and local R2 were both greater than 0.2), exerted a more significant impact on vegetation change in the AKC than natural factors such as thermal conditions, water conditions, and soil conditions. This impact was positive in Southwest China but inhibited in the Indochina Peninsula, particularly within the CLV karst area. Notably, the interaction between natural and human factors greatly enhanced their impacts on vegetation changes. These results provide valuable insights into vegetation changes and their driving mechanisms, which are crucial for preserving the stability of delicate karst ecosystems and facilitating vegetation recovery.

Vegetation is an essential component of terrestrial ecosystems, influenced by climate change and human activities. Quantifying the relative contributions of climate change and human activities to vegetation dynamics is crucial for addressing global climate change. Sichuan Province is one of the essential ecological functional areas in the upper reaches of the Yangtze River, and its vegetation change is of great significance to the environmental function and ecological security of the Yangtze River Basin and southwest China. In this paper, the modified Carnegie-Ames-Stanford Approach(CASA) model was used to estimate the monthly NPP (Net Primary Productivity) of vegetation in Sichuan Province from 2000 to 2018, and the univariate linear regression analysis was used to analyze the temporal and spatial variation of vegetation NPP in Sichuan Province from 2000 to 2018. In addition, taking vegetation NPP as an index, Pearson correlation analysis, partial correlation analysis, and second-order partial correlation analysis were carried out to quantitatively analyze the contribution of climate change and human activities to vegetation NPP. Finally, the Hurst index and nonparametric Man-Kendall significance test were used to predict the future change trend of vegetation NPP in Sichuan Province. The results show that (1) from 2000 to 2018, the NPP of vegetation in Sichuan Province has a significant increasing trend (Slope = 6.09gC·m-2·a-1), with a multi-year average of 438.72 gC·m-2·a-1, showing a trend of low in the east and high in the middle. The response of vegetation NPP to altitude is different at different elevations; (2) the contribution rates of climate change and human activities to vegetation NPP change are 4.12gC·m-2·a-1 and 1.97gC·m-2·a-1, respectively. In contrast, the impact of human activities on NPP is more significant than climate change. Human activities are the main factors affecting vegetation restoration and degradation in Sichuan Province. However, the positive contribution to NPP change is less than climate change; (3) the future vegetation NPP change trend in Sichuan Province is mainly rising, and the same direction change trend is much larger than the reverse change trend. The areas with an increasing trend in the future account for 89.187% of the total area. This research helps understand the impact of climate change and human activities on vegetation change in Sichuan Province. It offers scientific bases for vegetation restoration and ecosystem management in Sichuan and the surrounding areas.

Vegetation and climate changes since the Last Glacial Maximum inferred from high-resolution pollen records from the Sichuan Basin, southwest China

Identifying vegetation changes and the associated driving forces provides a valuable reference for developing ecological restoration strategies. However, it remains a challenge to disentangle the impacts of climate, vegetation, and human interference impacts on vegetation changes. In this study, the temporal variations of the Normalized Difference Vegetation Index (NDVI) during 2000 ~ 2015 in space were used to identify the greening (restoration) and browning (degradation) areas in southwest China. The Random Forest (RF) approach was applied to distinguish the main driving forces of the greening and browning areas. Results showed that the RF approach can be effectively used to learn the complex non–linear interactions between vegetation change, local climate, and human interferences. Vegetation greening was prominent in 85.90% of the study area, while 5.59% of the area still experienced significant vegetation degradation. Population pressure was an important factor to alter the sign of long-term vegetation trends. The greening trends are mainly observed in the high elevation areas with low population density (e.g., population density lower than 180 people/km2 and altitudeabove 1000m), which are attributed to both artificial reforestation measures and climate warming. In contrast, the browning trend was concentrated in the low elevation areas with high and temporally intensified population density due to urbanization with a high population density (over 1000 people/km2) and an increased rate (over 20 people/km2 per year). The results of this study strengthen our understanding of the complex convolutions among climate, human activities, and vegetation in southwest China.

The use of random forest to identify climate and human interference on vegetation coverage changes in southwest China

Impacts on watershed-scale runoff and sediment yield resulting from synergetic changes in climate and vegetation

Coverage-dependent amplifiers of vegetation change on global water cycle dynamics

A greater negative impact of future climate change on vegetation in Central Asia: Evidence from trajectory/pattern analysis

Land‐cover/climate changes and their impacts on hydrological processes are of widespread concern and a great challenge to researchers and policy makers. Kejie Watershed in the Salween River Basin in Yunnan, south‐west China, has been reforested extensively during the past two decades. In terms of climate change, there has been a marked increase in temperature. The impact of these changes on hydrological processes required investigation: hence, this paper assesses aspects of changes in land cover and climate. The response of hydrological processes to land‐cover/climate changes was examined using the Soil and Water Assessment Tool (SWAT) and impacts of single factor, land‐use/climate change on hydrological processes were differentiated. Land‐cover maps revealed extensive reforestation at the expense of grassland, cropland, and barren land. A significant monotonic trend and noticeable changes had occurred in annual temperature over the long term. Long‐term changes in annual rainfall and streamflow were weak; and changes in monthly rainfall (May, June, July, and September) were apparent. Hydrological simulations showed that the impact of climate change on surface water, baseflow, and streamflow was offset by the impact of land‐cover change. Seasonal variation in streamflow was influenced by seasonal variation in rainfall. The earlier onset of monsoon and the variability of rainfall resulted in extreme monthly streamflow. Land‐cover change played a dominant role in mean annual values; seasonal variation in surface water and streamflow was influenced mainly by seasonal variation in rainfall; and land‐cover change played a regulating role in this. Surface water is more sensitive to land‐cover change and climate change: an increase in surface water in September and May due to increased rainfall was offset by a decrease in surface water due to land‐cover change. A decrease in baseflow caused by changes in rainfall and temperature was offset by an increase in baseflow due to land‐cover change. Copyright © 2009 John Wiley & Sons, Ltd.

The impact of climate change on maize potential productivity and the potential productivity gap in Southwest China (SWC) are investigated in this paper. We analyze the impact of climate change on the photosynthetic, light-temperature, and climatic potential productivity of maize and their gaps in SWC, by using a crop growth dynamics statistical method. During the maize growing season from 1961 to 2010, minimum temperature increased by 0.20°C per decade (p < 0.01) across SWC. The largest increases in average and minimum temperatures were observed mostly in areas of Yunnan Province. Growing season average sunshine hours decreased by 0.2 h day−1 per decade (p < 0.01) and total precipitation showed an insignificant decreasing trend across SWC. Photosynthetic potential productivity decreased by 298 kg ha-1 per decade (p < 0.05). Both light-temperature and climatic potential productivity decreased (p < 0.05) in the northeast of SWC, whereas they increased (p < 0.05) in the southwest of SWC. The gap between light-temperature and climatic potential productivity varied from 12 to 2729 kg ha−1, with the high value areas centered in northern and southwestern SWC. Climatic productivity of these areas reached only 10%–24% of the light-temperature potential productivity, suggesting that there is great potential to increase the maize potential yield by improving water management in these areas. In particular, the gap has become larger in the most recent 10 years. Sensitivity analysis shows that the climatic potential productivity of maize is most sensitive to changes in temperature in SWC. The findings of this study are helpful for quantification of irrigation water requirements so as to achieve maximum yield potentials in SWC.

Trends in vegetation change and their relationships with terrain conditions are significant to understand and evaluate the efficiency of ecological engineering implemented in karst regions, Southwest China. This study aimed to identify vegetation change trends in Hechi, Guangxi, China using time-series of SPOT-VGT NDVI data (1999-2010) and DEM. Linear trend analysis was applied to examine NDVI change trends. The results indicated that most of NDVI values had increased during this time period. There were spatial variations in NDVI change trends, which could be partiallly explained by different karst terrain conditions. The areas of most obviously positive trends in NDVI change were found at the elevation of 500-1000m and the relief amplitude between 200 and 500 m. Negative trends in NDVI change were appeared on slopes of south (sunlit) and we st (semi-sunlit) aspect and at the elevation of 200 - 500 m, where were mainly due to human activities. Keywords: vegetation change, remote sensing, SPOT-V GT NDVI, Karst regions, terrain conditions