Spatiotemporal Evolution of Droughts and Their Teleconnections with Large-Scale Climate Indices over Guizhou Province in Southwest China

Xiao, Liangang; Chen, Xi; Zhang, Runrun; Zhang, Zhicai

doi:10.3390/w11102104

Cited by 8 publications

(9 citation statements)

References 41 publications

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“…The analysis of meteorological drought and hydrological drought indicates that Southwest China is experiencing a drought trend, and the drought trend in autumn is most obvious for all seasonal periods, which is in accordance with Wang et al [27]. Previous studies have made detailed summaries of drought trends in Guizhou, Sichuan and Yunnan with different drought indices [27][28][29][30][31][32][33]. In the 21st century, on the one hand, severe drought events in 2006 and 2009/2010 in Southwest China have also been extensively reported [34][35][36].…”

Section: Discussionsupporting

confidence: 71%

Analysis of Characteristics of Hydrological and Meteorological Drought Evolution in Southwest China

Tang

Wen

Shi

et al. 2021

Water

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Based on the data of 82 meteorological stations and six representative hydrological stations in four provinces in Southwest China (Guizhou, Sichuan, Yunnan, Chongqing), this paper uses standardized precipitation evapotranspiration index (SPEI) and standardized runoff index (SRI) to analyze the spatial and temporal evolution characteristics of drought in the study area from 1968 to 2018. Combined with the Southwest monsoon index and historical drought data, the correlation of drought and the applicability of different drought indices were verified. The results show that: (1) SPEI-12 in Southwest China shows a downward trend from 1968 to 2018, with a linear trend rate of −0.074/10a, and SPEI-3 has a downward trend in four seasons, the maximum linear trend rate being −0.106/10a in autumn;(2) The change in SRI-12 and SRI-24 value directly reflected the decrease in SRI value, indicating that drought events are increasing in recent times, especially in the 21st century (3). Severe drought occurred in the south of Southwest China, as indicated by the increase of drought frequency in this area. The main reason for the variations in the frequency distribution of drought in Southwest China is the combined effect of the change of precipitation and evapotranspiration. (4) The correlation between hydrological drought index and disaster areas is stronger than the correlation between meteorological drought and disaster areas.

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Section: Discussionsupporting

confidence: 71%

Analysis of Characteristics of Hydrological and Meteorological Drought Evolution in Southwest China

Tang

Wen

Shi

et al. 2021

Water

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“…Himayoun and Roshni (2019) investigated that the drought characteristics are significantly influenced by ENSO4.0 events throughout the Jhelum basin of India. Moreover, a consistently weaker phase of positive IOD and PDO patterns during the recent severe drought in 2000–2002 deviates from the previous drought, which tends to be linked with large‐scale connections (Xiao et al ., 2019; Ain et al ., 2020; Liu et al ., 2020). In terms of large‐scale inter‐connection perspective, the 2000–2005 droughts are changed from previous droughts of southern Pakistan, confirming our findings based on dynamic association with the large‐scale climate indices droughts over Pakistan.…”

Section: Discussionmentioning

confidence: 99%

Observed changes in seasonal drought characteristics and their possible potential drivers over Pakistan

Ullah

Yin

et al. 2021

Intl Journal of Climatology

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Long‐term drought monitoring and its assessment are of great importance for meteorological disaster risk management. The recurrent spells of heat waves and droughts have severely affected the environmental conditions worldwide, including Pakistan. The present work sought to investigate the spatiotemporal changes in drought characteristics over Pakistan during Rabi and Kharif cropping seasons. The role of large‐scale circulation and interannual mode of climate variability is further explored to identify the physical mechanisms associated with droughts in the region. Monthly precipitation and temperature data (1983–2019) from 53 meteorological stations were used to study drought characteristics, using the standardized precipitation evapotranspiration index (SPEI). The nonparametric Mann–Kendall, Sen's Slope, and Sequential Mann–Kendall tests were applied on the drought index to determine the statistical significance and magnitude of the historical trend. The state‐of‐the‐art Bayesian Dynamic Linear model was further used to analyse large‐scale climate drivers of droughts, revealed an increase in drought severity, mostly over arid to semiarid regions for both cropping seasons. While temperature played a significant role in defining droughts over dry and hot seasons, rainfall is influential over the western disturbances influenced region. The analysis of atmospheric circulation patterns revealed that large‐scale changes in wind speed, air temperature, relative humidity, and geopotential height anomalies are the likely drivers of droughts in the region. We found that Niño4, sea surface temperature, and multivariate El Niño‐Southern Oscillation (ENSO4.0) Index are the most influential factors for seasonal droughts across Pakistan. Overall, the findings provide a better understanding of drought‐prone areas in the region, and this information is of potential use for mitigating and managing drought risks.

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“…As it is located in the karst plateau area of Southwest China and belongs to the humid subtropical plateau monsoon climate, the study area has poor light conditions, heavy rainfall, and cloud cover all year round. These factors lead to a serious lack of optical remote sensing image data, especially high-resolution data, and there is an urgent need for high-spatiotemporal-resolution images in daily production and scientific research activities [35][36][37].…”

Section: Study Areamentioning

confidence: 99%

Applicability Analysis of GF-2PMS and PLANETSCOPE Data for Ground Object Recognition in Karst Region

Shen

Zhou

Yang

et al. 2022

Land

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Remote sensing image with high spatial and temporal resolution is very important for rational planning and scientific management of land resources. However, due to the influence of satellite resolution, revisit period, and cloud pollution, it is difficult to obtain high spatial and temporal resolution images. In order to effectively solve the “space–time contradiction” problem in remote sensing application, based on GF-2PMS (GF-2) and PlanetSope (PS) data, this paper compares and analyzes the applicability of FSDAF (flexible spatiotemporal data fusion), STDFA (the spatial temporal data fusion approach), and Fit_FC (regression model fitting, spatial filtering, and residual compensation) in different terrain conditions in karst area. The results show the following. (1) For the boundary area of water and land, the FSDAF model has the best fusion effect in land boundary recognition, and provides rich ground object information. The Fit_FC model is less effective, and the image is blurry. (2) For areas such as mountains, with large changes in vegetation coverage, the spatial resolution of the images fused by the three models is significantly improved. Among them, the STDFA model has the clearest and richest spatial structure information. The fused image of the Fit_FC model has the highest similarity with the verification image, which can better restore the coverage changes of crops and other vegetation, but the actual spatial resolution of the fused image is relatively poor, the image quality is fuzzy, and the land boundary area cannot be clearly identified. (3) For areas with dense buildings, such as cities, the fusion image of the FSDAF and STDFA models is clearer and the Fit_FC model can better reflect the changes in land use. In summary, compared with the Fit_FC model, the FSDAF model and the STDFA model have higher image prediction accuracy, especially in the recognition of building contours and other surface features, but they are not suitable for the dynamic monitoring of vegetation such as crops. At the same time, the image resolution of the Fit_FC model after fusion is slightly lower than that of the other two models. In particular, in the water–land boundary area, the fusion accuracy is poor, but the model of Fit_FC has unique advantages in vegetation dynamic monitoring. In this paper, three spatiotemporal fusion models are used to fuse GF-2 and PS images, which improves the recognition accuracy of surface objects and provides a new idea for fine classification of land use in karst areas.

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Spatiotemporal Evolution of Droughts and Their Teleconnections with Large-Scale Climate Indices over Guizhou Province in Southwest China

Cited by 8 publications

References 41 publications

Analysis of Characteristics of Hydrological and Meteorological Drought Evolution in Southwest China

Analysis of Characteristics of Hydrological and Meteorological Drought Evolution in Southwest China

Observed changes in seasonal drought characteristics and their possible potential drivers over Pakistan

Applicability Analysis of GF-2PMS and PLANETSCOPE Data for Ground Object Recognition in Karst Region

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