The Spatiotemporal Characteristics of Wildfires across Australia and Their Connections to Extreme Climate Based on a Combined Hydrological Drought Index

Cui, Lilu; Zhu, Chengkang; Zou, Zhengbo; Yao, Chaolong; Zhang, Cheng; Li, Yu

doi:10.3390/fire6020042

Cited by 5 publications

(4 citation statements)

References 70 publications

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“…The long-term trend change in TWSC is mainly caused by human activities, so we detrended TWSC to better reflect the impact of climate change on TWSC. The expression of time series decomposition is as follows [48,49]:…”

Section: Detrend Approachmentioning

confidence: 99%

Spatiotemporal Evolution Characteristics of 2022 Pakistan Severe Flood Event Based on Multi-Source Satellite Gravity Observations

Cui,

Meng,

et al. 2024

Remote Sensing

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In the summer of 2022, Pakistan experienced a severe flood event that brought great destruction to the local people and ecosystem. However, there is no comprehensive study on the process, spread and causes of this flood. Therefore, we combined multiple satellite gravity data, meteorological data, hydrological data, and satellite remote sensing data to conduct a thorough investigation and study of this flood. The results show that a 20-year time series of the terrestrial water storage change based multiple gravity data has the high accuracy and reliability, which is used for detecting the flood. The flood propagated through meteorological system (three months), agricultural system (six months) and terrestrial ecosystems (five months), respectively, and the two southern provinces (Balochistan and Sindh) are the most affected by the flood, whose flood severity is 6.955 and 9.557, respectively. The center of the severe flood is located at the border region between the above two province. The severe flood is attributed primarily to the global extreme climate events (La Niña and negative Indian Ocean Dipole events) that altered the transport path of water vapor in the Indian Ocean, causing large amounts of water vapor to converge over Pakistan, resulting in heavy precipitation, and secondarily to the melting of extensive glacier in the mountainous of northern Pakistan as a result of the high temperature in March-May 2022. The above results contribute to the understanding of the mechanism of the impact of extreme climate events on the regional climate, and provide some references for the study of severe floods.

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Section: Detrend Approachmentioning

confidence: 99%

Spatiotemporal Evolution Characteristics of 2022 Pakistan Severe Flood Event Based on Multi-Source Satellite Gravity Observations

Cui,

Meng,

et al. 2024

Remote Sensing

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“…Assuming x 1 and x 2 are the two independent observation time series, their correlation coefficient is expressed as [58]:…”

Section: Correlation Coefficient and Delay Monthsmentioning

confidence: 99%

Spatiotemporal Evaluation of the Flood Potential Index and Its Driving Factors across the Volga River Basin Based on Combined Satellite Gravity Observations

Zou,

Li,

Cui

et al. 2023

Remote Sensing

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Floods have always threatened the survival and development of human beings. To reduce the adverse effects of floods, it is very important to understand the influencing factors of floods and their formation mechanisms. In our study, we integrated the Gravity Recovery and Climate Experiment and its Follow-On and Swarm solutions to estimate an uninterrupted 19-year flood potential index (FPI) time series, discussed the spatiotemporal distribution characteristics of the FPI and monitored major floods in the Volga River basin (VRB) from 2003 to 2021. Finally, we analyzed the relationship between the FPI and hydrometeorological factors to comprehend the flood formation mechanism. The results show that data fusion has reduced the uncertainty of terrestrial water storage change (TWSC), and the TWSC from the combined satellite gravity observations has a good consistency with that from the Global Land Data Assimilation System model (correlation coefficient = 0.92). During the study period, two major floods (June 2005 and May 2018) occurred in the VRB. The FPI has a significant seasonal change characteristic, and shows a high flood risk in spring and a low one in autumn. With regards to spatial distribution, the flood risk is increasing in the north (increasing rate = 0.1) and decreasing in the south (decreasing rate = 0.39). Snow water equivalent (SWE, correlation coefficient = 0.75) has a stronger correlation with the FPI than precipitation (PPT, correlation coefficient = 0.46), which is attributed to the recharge of SWE on water resources greater than that of PPT. The rising surface temperature (ST) speeds up snow melt, resulting in excessive groundwater and soil moisture, and the flood risk greatly increases at this time. The process lasts about three months. Therefore, except for PPT, ST is also a climatic factor leading to the floods in the VRB. Our study provides a reference for flood research in high-latitude regions.

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“…Suppose the two independent time series are x 1 and x 2 , the correlation coefficient between the above time series is expressed as [60]:…”

Section: Correlation Coefficient and Delay Monthsmentioning

confidence: 99%

Spatiotemporal Variation Characteristics of Droughts and Their Connection to Climate Variability and Human Activity in the Pearl River Basin, South China

Cui

Chen

et al. 2023

Water

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Droughts have damaging impacts on human society and ecological environments. Therefore, studying the impacts of climate variability and human activity on droughts has very important scientific value and social significance in order to understand drought warnings and weaken the adverse impacts of droughts. In this study, we used a combined drought index based on five Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On solutions to characterize droughts in the Pearl River basin (PRB) and its sub-basins during 2003 and 2020. Then, we accurately quantified the impact of climate variability and human activity on droughts in the PRB and seven sub-basins by combining the hydrometeorological climate index and in situ human activity data. The results show that 14 droughts were identified in the PRB, particularly the North River basin with the most drought months (52.78%). The El Niño-Southern Oscillation and the Indian Ocean Dipole were found to have important impacts on droughts in the PRB. They affect the operation of the atmospheric circulation, as well as the East Asia summer monsoon, resulting in a decrease in precipitation in the PRB. This impact shows a significant east–west difference on the spatial scale. The middle and upper reaches of the PRB were found to be dominated by SM, while the lower reaches were found to be dominated by GW. Human activity was found to mainly exacerbate droughts in the PRB, but also plays a significant role in reducing peak magnitude. The sub-basins with a higher proportion of total water consumption experienced more droughts (more than 11), and vice versa. The Pearl River Delta showed the highest drought intensification. Reservoir storage significantly reduces the drought peak and severity, but the impact effect depends on its application and balance with the total water consumption. Our study provides a reference for analyzing the drought characteristics, causes, and impacts of sub-basins on a global scale.

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The Spatiotemporal Characteristics of Wildfires across Australia and Their Connections to Extreme Climate Based on a Combined Hydrological Drought Index

Cited by 5 publications

References 70 publications

Spatiotemporal Evolution Characteristics of 2022 Pakistan Severe Flood Event Based on Multi-Source Satellite Gravity Observations

Spatiotemporal Evolution Characteristics of 2022 Pakistan Severe Flood Event Based on Multi-Source Satellite Gravity Observations

Spatiotemporal Evaluation of the Flood Potential Index and Its Driving Factors across the Volga River Basin Based on Combined Satellite Gravity Observations

Spatiotemporal Variation Characteristics of Droughts and Their Connection to Climate Variability and Human Activity in the Pearl River Basin, South China

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