scholarly journals Spatiotemporal Characteristics and Driving Force Analysis of Flash Floods in Fujian Province

2020 ◽  
Vol 9 (2) ◽  
pp. 133 ◽  
Author(s):  
Junnan Xiong ◽  
Quan Pang ◽  
Chunkun Fan ◽  
Weiming Cheng ◽  
Chongchong Ye ◽  
...  
Keyword(s):  
Driving Forces ◽  
Flash Flood ◽  
Principal Component ◽  
Flash Floods ◽  
Fujian Province ◽  
Spatiotemporal Characteristics ◽  
Middle Mountains ◽  
Driving Force Analysis ◽  
Economic Development Model ◽  
The Impact

Flash floods are one of the most destructive natural disasters. The comprehensive identification of the spatiotemporal characteristics and driving factors of a flash flood is the basis for the scientific understanding of the formation mechanism and the distribution characteristics of flash floods. In this study, we explored the spatiotemporal patterns of flash floods in Fujian Province from 1951 to 2015. Then, we analyzed the driving forces of flash floods in geomorphic regions with three different grades based on three methods, namely, geographical detector, principal component analysis, and multiple linear regression. Finally, the sensitivity of flash floods to the gross domestic product, village point density, annual maximum one-day precipitation (Rx1day), and annual total precipitation from days > 95th percentile (R95p) was analyzed. The analytical results indicated that (1) The counts of flash floods rose sharply from 1988, and the spatial distribution of flash floods mainly extended from the coastal low mountains, hills, and plain regions of Fujian (IIA2) to the low-middle mountains, hills, and valley regions in the Wuyi mountains (IIA4) from 1951 to 2015. (2) From IIA2 to IIA4, the impact of human activities on flash floods was gradually weakened, while the contribution of precipitation indicators gradually strengthened. (3) The sensitivity analysis results revealed that the hazard factors of flash floods in different periods and regions had significant differences in Fujian Province. Based on the above results, it is necessary to accurately forecast extreme precipitation and improve the economic development model of the IIA2 region.

scholarly journals Flash Flood Susceptibility Assessment Based on Geodetector, Certainty Factor, and Logistic Regression Analyses in Fujian Province, China

2020 ◽  
Vol 9 (12) ◽  
pp. 748
Author(s):  
Yifan Cao ◽  
Hongliang Jia ◽  
Junnan Xiong ◽  
Weiming Cheng ◽  
Kun Li ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Flash Flood ◽  
Pearson Correlation ◽  
Flash Floods ◽  
Ensemble Model ◽  
Susceptibility Assessment ◽  
Certainty Factor ◽  
Fujian Province ◽  
Flood Susceptibility ◽  
Susceptibility Maps

Flash floods are one of the most frequent natural disasters in Fujian Province, China, and they seriously threaten the safety of infrastructure, natural ecosystems, and human life. Thus, recognition of possible flash flood locations and exploitation of more precise flash flood susceptibility maps are crucial to appropriate flash flood management in Fujian. Based on this objective, in this study, we developed a new method of flash flood susceptibility assessment. First, we utilized double standards, including the Pearson correlation coefficient (PCC) and Geodetector to screen the assessment indicator. Second, in order to consider the weight of each classification of indicator and the weights of the indicators simultaneously, we used the ensemble model of the certainty factor (CF) and logistic regression (LR) to establish a frame for the flash flood susceptibility assessment. Ultimately, we used this ensemble model (CF-LR), the standalone CF model, and the standalone LR model to prepare flash flood susceptibility maps for Fujian Province and compared their prediction performance. The results revealed the following. (1) Land use, topographic relief, and 24 h precipitation (H24_100) within a 100-year return period were the three main factors causing flash floods in Fujian Province. (2) The area under the curve (AUC) results showed that the CF-LR model had the best precision in terms of both the success rate (0.860) and the prediction rate (0.882). (3) The assessment results of all three models showed that between 22.27% and 29.35% of the study area have high and very high susceptibility levels, and these areas are mainly located in the east, south, and southeast coastal areas, and the north and west low mountain areas. The results of this study provide a scientific basis and support for flash flood prevention in Fujian Province. The proposed susceptibility assessment framework may also be helpful for other natural disaster susceptibility analyses.

Urban Area Response to Flash Flood–Triggering Rainfall, Featuring Human Behavioral Factors: The Case of 22 October 2015 in Attica, Greece

2017 ◽  
Vol 9 (3) ◽  
pp. 621-638 ◽  
Author(s):  
Katerina Papagiannaki ◽  
Vassiliki Kotroni ◽  
Kostas Lagouvardos ◽  
Isabelle Ruin ◽  
Antonis Bezes
Keyword(s):  
Risk Perception ◽  
Flash Flood ◽  
Time Correlation ◽  
Flash Floods ◽  
Space Time ◽  
Coping Responses ◽  
Accumulated Rainfall ◽  
Flood Impact ◽  
And Coping ◽  
The Impact

Abstract Over the past several decades, flash floods that occurred in Attica, Greece, caused serious property and infrastructure damages, disruptions in economic and social activities, and human fatalities. This paper investigated the link between rainfall and flash flood impact during the catastrophic event that affected Attica on 22 October 2015, while also addressing human risk perception and behavior as a response to flash floods. The methodology included the analysis of the space–time correlation of rainfall with the citizens’ calls to the emergency fire services for help, and the statistical analysis of people’s responses to an online behavioral survey. The results designated critical rainfall thresholds associated with flash flood impact in the four most affected subareas of the Attica region. The impact magnitude was found to be associated with the localized accumulated rainfall. Vulnerability factors, namely, population density, geographical, and environmental features, may have contributed to the differences in the impact magnitudes between the examined subareas. The analysis of the survey’s behavioral responses provided insights into peoples’ risk perception and coping responses relative to the space–time distribution of rainfall. The findings of this study were in agreement with the hypothesis that the more severe the rainfall, the higher peoples’ severity assessment and the intensity of emotional response. Deeper feelings of fear and worry were found to be related to more adjustments to the scheduled activities and travels. Additionally, being alert to the upcoming rainfall risk was found to be related to decreased worry and fear and to fewer changes in scheduled activities.

scholarly journals Utilization of estimated rainfall as an early warning system before flash flood event

2018 ◽  
Vol 2 (2) ◽  
pp. 73
Author(s):  
Fara Diva Claudia ◽  
Cecylia Putri Mawarni ◽  
Kadek Krisna Yulianti ◽  
Paulus Agus Winarso
Keyword(s):  
Flash Flood ◽  
Remote Sensing Data ◽  
Heavy Rain ◽  
Flash Floods ◽  
Extreme Weather ◽  
Atmospheric Dynamics ◽  
Observation Data ◽  
Rainfall Estimation ◽  
Wrf Modeling ◽  
The Impact

<p class="Abstract">On October 10, 2018 there has been extreme weather in the form of heavy rain accompanied by lightning in Tanah Datar District, West Sumatra. This extreme weather caused flash floods and landslides that killed many people. Therefore, by using remote sensing data in the form of radar and satellite as well as WRF modeling (Weather Research and Forecasting) the authors conducted analysis of heavy rainfall events to determine the estimated rainfall and atmospheric dynamics during the occurrence of flash floods and landslides. WRF modeling is used to determine the condition of atmospheric lability. For the calculation of rainfall estimation, the method used is the Convective Stratiform Technique (CST) method that utilizes satellite data and the Z-R relation selection method that utilizes radar data. Then the calculation results from each method are verified using observation data. Relative bias shows the CST method and the selection of Z-R relations tend to be overestimate, but has a very high correlation value with observation data. Information on rainfall estimation and atmospheric dynamics is expected to be used to provide early warnings aimed at minimizing losses from the impact of disasters.</p>

scholarly journals Impact of Flash Flood Events on the Coastal Waters Around Madeira Island: The “Land Mass Effect”

2022 ◽  
Vol 8 ◽  
Author(s):  
Alexandra Rosa ◽  
Cláudio Cardoso ◽  
Rui Vieira ◽  
Ricardo Faria ◽  
Ana R. Oliveira ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Coastal Waters ◽  
Flash Flood ◽  
Mass Effect ◽  
Flash Floods ◽  
River Plume ◽  
Flood Events ◽  
Madeira Island ◽  
The Impact ◽  
Land Runoff

The Island Mass Effect has been primarily attributed to nutrient enhancement of waters surrounding oceanic islands due to physical processes, whereas the role of land runoff has seldom been considered. Land runoff can be particularly relevant in mountainous islands, highly susceptible to torrential rainfall that rapidly leads to flash floods. Madeira Island, located in the Northeast Atlantic Ocean, is historically known for its flash flood events, when steep streams transport high volumes of water and terrigenous material downstream. A 22-year analysis of satellite data revealed that a recent catastrophic flash flood (20 February 2010) was responsible for the most significant concentration of non-algal Suspended Particulate Matter (SPM) and Chlorophyll-a at the coast. In this context, our study aims to understand the impact of the February 2010 flash flood events on coastal waters, by assessing the impact of spatial and temporal variability of wind, precipitation, and river discharges. Two specific flash floods events are investigated in detail (2 and 20 February 2010), which coincided with northeasterly and southwesterly winds, respectively. Given the lack of in situ data documenting these events, a coupled air-sea-land numerical framework was used, including hydrological modeling. The dynamics of the modeled river plumes induced by flash floods were strongly influenced by the wind regimes subsequently affecting coastal circulation, which may help to explain the differences between observed SPM and Chlorophyll-a distributions. Model simulations showed that during northeasterly winds, coastal confinement of the buoyant river plume persisted on the island’s north coast, preventing offshore transport of SPM. This mechanism may have contributed to favorable conditions for phytoplankton growth, as captured by satellite-derived Chlorophyll-a in the northeastern coastal waters. On the island’s south coast, strong ocean currents generated in the eastern island flank promoted strong vertical shear, contributing to vertical mixing. During southwesterly winds, coastal confinement of the plume with strong vertical density gradient was observed on the south side. The switch to eastward winds spread the south river plume offshore, forming a filament of high Chlorophyll-a extending 70 km offshore. Our framework demonstrates a novel methodology to investigate ocean productivity around remote islands with sparse or absent field observations.

scholarly journals Diagnosing Moisture Sources for Flash Floods in the United States. Part II: Terrestrial and Oceanic Sources of Moisture

2019 ◽  
Vol 20 (8) ◽  
pp. 1511-1531 ◽  
Author(s):  
Jessica M. Erlingis ◽  
Jonathan J. Gourley ◽  
Jeffrey B. Basara
Keyword(s):  
United States ◽  
Boundary Layer ◽  
Land Surface ◽  
Flash Flood ◽  
The United States ◽  
Flash Floods ◽  
Heat Fluxes ◽  
Surface Model ◽  
Positive Anomaly ◽  
The Impact

Abstract Backward trajectories were derived from North American Regional Reanalysis data for 19 253 flash flood reports published by the National Weather Service to determine the along-path contribution of the land surface to the moisture budget for flash flood events in the conterminous United States. The impact of land surface interactions was evaluated seasonally and for six regions: the West Coast, Arizona, the Front Range, Flash Flood Alley, the Missouri Valley, and the Appalachians. Parcels were released from locations that were impacted by flash floods and traced backward in time for 120 h. The boundary layer height was used to determine whether moisture increases occurred within the boundary layer or above it. Moisture increases occurring within the boundary layer were attributed to evapotranspiration from the land surface, and surface properties were recorded from an offline run of the Noah land surface model. In general, moisture increases attributed to the land surface were associated with anomalously high surface latent heat fluxes and anomalously low sensible heat fluxes (resulting in a positive anomaly of evaporative fraction) as well as positive anomalies in top-layer soil moisture. Over the ocean, uptakes were associated with positive anomalies in sea surface temperatures, the magnitude of which varies both regionally and seasonally. Major oceanic surface-based source regions of moisture for flash floods in the United States include the Gulf of Mexico and the Gulf of California, while boundary layer moisture increases in the southern plains are attributable in part to interactions between the land surface and the atmosphere.

scholarly journals The Spatiotemporal Distribution of Flash Floods and Analysis of Partition Driving Forces in Yunnan Province

2019 ◽  
Vol 11 (10) ◽  
pp. 2926 ◽  
Author(s):  
Junnan Xiong ◽  
Chongchong Ye ◽  
Weiming Cheng ◽  
Liang Guo ◽  
Chenghu Zhou ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Economic Development ◽  
Return Period ◽  
Driving Forces ◽  
Flash Flood ◽  
Temporal Distribution ◽  
Heavy Precipitation ◽  
Spatiotemporal Analysis ◽  
Flash Floods

Flash floods are one of the most serious natural disasters, and have a significant impact on economic development. In this study, we employed the spatiotemporal analysis method to measure the spatial–temporal distribution of flash floods and examined the relationship between flash floods and driving factors in different subregions of landcover. Furthermore, we analyzed the response of flash floods on the economic development by sensitivity analysis. The results indicated that the number of flash floods occurring annually increased gradually from 1949 to 2015, and regions with a high quantity of flash floods were concentrated in Zhaotong, Qujing, Kunming, Yuxi, Chuxiong, Dali, and Baoshan. Specifically, precipitation and elevation had a more significant effect on flash floods in the settlement than in other subregions, with a high r (Pearson’s correlation coefficient) value of 0.675, 0.674, 0.593, 0.519, and 0.395 for the 10 min precipitation in 20-year return period, elevation, 60 min precipitation in 20-year return period, 24 h precipitation in 20-year return period, and 6 h precipitation in 20-year return period, respectively. The sensitivity analysis showed that the Kunming had the highest sensitivity (S = 21.86) during 2000–2005. Based on the research results, we should focus on heavy precipitation events for flash flood prevention and forecasting in the short term; but human activities and ecosystem vulnerability should be controlled over the long term.

Using Climate Models to Estimate Urban Vulnerability to Flash Floods

2017 ◽  
Vol 56 (9) ◽  
pp. 2637-2650 ◽  
Author(s):  
A. Kermanshah ◽  
S. Derrible ◽  
M. Berkelhammer
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Travel Demand ◽  
Flash Flood ◽  
Flash Floods ◽  
Flood Frequency ◽  
Geographical Information ◽  
Climate System Model ◽  
Infrastructure Networks ◽  
The Impact

Abstract Climate change will impact urban infrastructure networks by changing precipitation patterns in a region. This study presents a novel vulnerability assessment framework for infrastructure networks against extreme rainfall-induced flash floods, with a specific application to transportation. The framework combines climate models, network science, geographical information systems (GIS), and stochastic modeling to compile a vulnerability surface (VS). Daily precipitation simulations for 2006–2100 from the Community Climate System Model, version 4 (CCSM4), are used to produce a stochastic simulation of extreme flash flood events in five U.S. cities—that is, Boston, Massachusetts; Houston, Texas; Miami, Florida; Oklahoma City, Oklahoma; and Philadelphia, Pennsylvania—under two different climate scenarios (RCP4.5 and RCP8.5). To assess the impact of these events, percentage drops in static (i.e., overall properties and robustness topological indicators) and dynamic (i.e., GIS accessibility and travel demand metrics) network properties are measured before and after simulated extreme events. The results of these metrics are inputs on a radar diagram to form a VS. Overall, the results show that changes in flash flood frequency due to climate change can have a significant impact on road networks, as was demonstrated recently in Houston, Texas. The magnitude of these impacts is chiefly associated with the geographic location of the cities and the size of the networks. The proposed framework can be reproduced in any city around the world, and researchers can use the results as guidelines for infrastructure design and planning purposes. Moreover, sensitivity analysis to varying greenhouse gas concentration trajectories can help local and national authorities to prioritize strategies for adaptation to climate change in more vulnerable regions.

scholarly journals Spatial–temporal characteristics and driving factors of flash floods in Shaanxi Province considering regional differentiation

2021 ◽  
Author(s):  
Han Zhang ◽  
Jungang Luo ◽  
Jingyan Wu ◽  
Mengjie Yu
Keyword(s):  
Driving Forces ◽  
Flash Flood ◽  
Temporal Distribution ◽  
Flash Floods ◽  
Shaanxi Province ◽  
Regional Differentiation ◽  
Effective Prevention ◽  
Temporal Characteristics ◽  
Northern Shaanxi ◽  
And Control

Abstract Flash floods show strong regional differentiation in spatial–temporal distribution and driving forces, thereby hindering their effective prevention and control. This study analyzed the spatiotemporal characteristics of flash floods in Shaanxi Province, China, differentiated among the northern Shaanxi (NS), Guanzhong (GZ), and southern Shaanxi (SS) regions based on the Mann–Kendall, Theil–Sen Median, and standard deviation ellipse methods. The main factors driving disasters and their interactions in each region were then identified within the three categories of precipitation factor (PPF), surface environment factor, and human activity factor (HAF) based on a geographical detector. Finally, the differences in flash flood characteristics among the NS, GZ, and SS regions were analyzed. The results showed that flash floods in Shaanxi Province are greatly affected by the PPF and the HAF, although the spatial–temporal characteristics and disaster-causing factors were significantly different in each region. The regions were ranked according to the number and growth trends of flash floods as follows: SS &gt; GZ &gt; NS. Furthermore, flash floods were affected by multiple factors, with the interaction between factors acting as a driving force of flash floods. The results of this study can provide a reference for the management of flash floods under regional differentiation.

Study of Urban Land-Use Structure Situation on the Ground of Information Entropy

2011 ◽  
Vol 50-51 ◽  
pp. 1008-1012
Author(s):  
Cui Lan Mi ◽  
Ying Li Liu
Keyword(s):  
Principal Component Analysis ◽  
Land Use ◽  
Information Entropy ◽  
Markov Models ◽  
Driving Forces ◽  
Principal Component ◽  
Urban Land Use ◽  
Equilibrium Degree ◽  
Land Use Structure ◽  
The Impact

In order to reveal the change law of land structure in recent years and the future land use structure in urban Tangshan, an analysis of the rules is conducted by applying such information theory as information entropy, equilibrium degree and dominance degree to nine types of land in urban Tangshan from 1998 to 2007. Then principal component analysis and SPSS are used to analyze the driving forces and the impact of various factors on land use structure. Finally, land use structure in 2012 and 2017 is predicted through Markov models.

scholarly journals Flash-Floods Influence Macroinvertebrate Communities Distribution in Lotic Ecosystems

2019 ◽  
Vol 21 (1) ◽  
pp. 45-56
Author(s):  
Octavian Pacioglu ◽  
Alina Satmari ◽  
Milca Petrovici ◽  
Mălina Pîrvu ◽  
Mirela Cîmpean ◽  
...  
Keyword(s):  
Flash Flood ◽  
Flash Floods ◽  
Macroinvertebrate Communities ◽  
Lotic Ecosystems ◽  
Average Slope ◽  
The Impact ◽  
Upstream Catchment

Abstract Stream dwelling invertebrate populations are facing an ample array of stressors including the habitat imbalance caused by important floods. In this research we used a novel way to estimate the impact of floods upon the substrate, by utilising a remote variable named “flash-flood potential” (FFP), which accounts for the site slope and the average slope of the upstream catchment. The results showed that certain groups are sensitive to the influence of the FFP whereas other are not. We propose this remote variable as a surrogate for assessing stress imposed by floods and sediment scouring for lotic macroinvertebrates.

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