The spatiotemporal variations and propagation of droughts in Plateau Mountains of China

Yang, Fan; Duan, Xingwu; Guo, Qiankun; Lu, Shaojuan; Hsü, K.

doi:10.1016/j.scitotenv.2021.150257

Cited by 43 publications

(19 citation statements)

References 46 publications

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“…An interesting phenomenon is that Nanling Mountain serves as the dividing line between Clusters 1 and 2, which further proves the influence of topographical factors on drought [14]. Yang et al [55] reported that in plateaus and mountainous areas with complex terrain, the order of drought spread varies with altitude. Agricultural droughts in high-altitude areas evolve into hydrological droughts.…”

Section: Discussionmentioning

confidence: 81%

Framework for Monitoring the Spatiotemporal Distribution and Clustering of Drought Characteristics in Hunan Province

Huang

Baig

et al. 2021

Applied Sciences

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Drought is a widespread phenomenon in the context of global climate change. Owing to the geographical location of Hunan Province in the middle reaches of Yangtze River and the abundance of forests area in this region with a large population, there is a need to focus on the impacts of drought for devising policies. The spatiotemporal distribution scheme of a given area must be determined to plan water management and protect ecosystems effectively. This study proposes a framework for exploring the spatiotemporal distribution model of drought using comprehensive surveys of historical meteorological stations, which consists of two parts, namely the characteristics of drought extraction in the spatiotemporal distribution and drought models discovered by the clustering method. Firstly, we utilized the run theory to extract drought characteristics, such as drought duration, drought severity, and drought intensity. Secondly, the K-means clustering method was adopted to explore the distribution patterns on the basis of the drought characteristics. Lastly, the method was applied to Hunan Province. Results show that historical drought conditions can be monitored with their characteristics of spatiotemporal variability. Three drought distribution clusters exist in this region. Cluster 1 in western Hunan tends to be a long-term, low-intensity drought, cluster 2 in the southern part tends to be a short-term, high-intensity drought, and cluster 3 in the central part is prone to severe drought. The proposed framework is flexible as it allows parameters to be adjusted and extraction methods to achieve reasonable results for a given area.

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Section: Discussionmentioning

confidence: 81%

Framework for Monitoring the Spatiotemporal Distribution and Clustering of Drought Characteristics in Hunan Province

Huang

Baig

et al. 2021

Applied Sciences

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“…In addition to climatic factors, other environmental factors (e.g., elevation, slope and aspect) can influence the drought patterns in a region ( Kumari et al., 2020 ). Because elevation is a direct control factor affecting temperature, slope orientation affects solar exposure time and solar radiation (P. Zhang et al., 2022 ), both of which are important factors affecting vegetation drought ( Yang et al., 2022 ). The only highly significant correlation (r = -0.52519) found in our study was between elevation and the probability of meadow decline to the 30th percentile of the land during severe drought, with a smaller effect of slope and slope orientation on meadow drought ( Figure 15 ).…”

Section: Discussionmentioning

confidence: 99%

Probabilistic assessment of drought stress vulnerability in grasslands of Xinjiang, China

et al. 2023

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In the process of climate warming, drought has increased the vulnerability of ecosystems. Due to the extreme sensitivity of grasslands to drought, grassland drought stress vulnerability assessment has become a current issue to be addressed. First, correlation analysis was used to determine the characteristics of the normalized precipitation evapotranspiration index (SPEI) response of the grassland normalized difference vegetation index (NDVI) to multiscale drought stress (SPEI-1 ~ SPEI-24) in the study area. Then, the response of grassland vegetation to drought stress at different growth periods was modeled using conjugate function analysis. Conditional probabilities were used to explore the probability of NDVI decline to the lower percentile in grasslands under different levels of drought stress (moderate, severe and extreme drought) and to further analyze the differences in drought vulnerability across climate zones and grassland types. Finally, the main influencing factors of drought stress in grassland at different periods were identified. The results of the study showed that the spatial pattern of drought response time of grassland in Xinjiang had obvious seasonality, with an increasing trend from January to March and November to December in the nongrowing season and a decreasing trend from June to October in the growing season. August was the most vulnerable period for grassland drought stress, with the highest probability of grassland loss. When the grasslands experience a certain degree of loss, they develop strategies to mitigate the effects of drought stress, thereby decreasing the probability of falling into the lower percentile. Among them, the highest probability of drought vulnerability was found in semiarid grasslands, as well as in plains grasslands and alpine subalpine grasslands. In addition, the primary drivers of April and August were temperature, whereas for September, the most significant influencing factor was evapotranspiration. The results of the study will not only deepen our understanding of the dynamics of drought stress in grasslands under climate change but also provide a scientific basis for the management of grassland ecosystems in response to drought and the allocation of water in the future.

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“…Precipitation and temperature are important factors that affect drought variation, and these two factors determine the spatial distribution of drought grade and drought frequency in the region [51]. Geomorphic factors lead to regional differentiation of drought, among which elevation plays a critical role in the spatial-temporal differentiation of drought spread in plateau mountains [52]. Human activities such as the increase in domestic water supplies and the expansion of urban areas can accelerate the spread of drought [53].…”

Section: Driving Factorsmentioning

confidence: 99%

Spatial-Temporal Evolution and Driving Forces of Drying Trends on the Qinghai-Tibet Plateau Based on Geomorphological Division

Liu

Zhao

et al. 2022

IJERPH

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The Qinghai–Tibet Plateau (QTP) is a sensor of global climate change and regional human activities, and drought monitoring will help to achieve its ecological protection and sustainable development. In order to effectively control the geospatial scale effect, we divided the study area into eight geomorphological sub-regions, and calculated the Temperature-Vegetation Drought Index (TVDI) of each geomorphological sub-region based on MODIS Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) data, and synthesized the TVDI of the whole region. We employed partial and multiple correlation analyses to identify the relationship between TVDI and temperature and precipitation. The random forest model was further used to study the driving mechanism of TVDI in each geomorphological division. The results of the study were as follows: (1) From 2000 to 2019, the QTP showed a drought trend, with the most significant drought trend in the central region. The spatial pattern of TVDI changes of QTP was consistent with the gradient changes of precipitation and temperature, both showing a gradual trend from southeast to northwest. (2) There was a risk of drought in the four seasons of the QTP, and the seasonal variation of TVDI was significant, which was characterized by being relatively dry in spring and summer and relatively humid in autumn and winter. (3) Drought in the QTP was mainly driven by natural factors, supplemented by human factors. The driving effect of temperature and precipitation factors on TVDI was stable and significant, which mainly determined the spatial distribution and variation of TVDI of the QTP. Geomorphological factors led to regional intensification and local differentiation effects of drought, especially in high mountains, flat slopes, sunny slopes and other places, which had a more significant impact on TVDI. Human activities had local point-like and linear impacts, and grass-land and cultivated land that were closely related to the relatively high impacts on TVDI of human grazing and farming activities. In view of the spatial-temporal patterns of change in TVDI in the study area, it is important to strengthen the monitoring and early warning of changes in natural factors, optimize the spatial distribution of human activities, and scientifically promote ecological protection and restoration.

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The spatiotemporal variations and propagation of droughts in Plateau Mountains of China

Cited by 43 publications

References 46 publications

Framework for Monitoring the Spatiotemporal Distribution and Clustering of Drought Characteristics in Hunan Province

Framework for Monitoring the Spatiotemporal Distribution and Clustering of Drought Characteristics in Hunan Province

Probabilistic assessment of drought stress vulnerability in grasslands of Xinjiang, China

Spatial-Temporal Evolution and Driving Forces of Drying Trends on the Qinghai-Tibet Plateau Based on Geomorphological Division

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