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 ◽  
...  

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.

2020 ◽  
Vol 9 (2) ◽  
pp. 133 ◽  
Author(s):  
Junnan Xiong ◽  
Quan Pang ◽  
Chunkun Fan ◽  
Weiming Cheng ◽  
Chongchong Ye ◽  
...  

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.


2014 ◽  
Vol 87 ◽  
pp. 96-108 ◽  
Author(s):  
Maria Liste ◽  
Manel Grifoll ◽  
Jaak Monbaliu

2016 ◽  
Vol 64 (4) ◽  
pp. 304-315 ◽  
Author(s):  
Kamila Hlavčová ◽  
Silvia Kohnová ◽  
Marco Borga ◽  
Oliver Horvát ◽  
Pavel Šťastný ◽  
...  

Abstract This work examines the main features of the flash flood regime in Central Europe as revealed by an analysis of flash floods that have occurred in Slovakia. The work is organized into the following two parts: The first part focuses on estimating the rainfall-runoff relationships for 3 major flash flood events, which were among the most severe events since 1998 and caused a loss of lives and a large amount of damage. The selected flash floods occurred on the 20th of July, 1998, in the Malá Svinka and Dubovický Creek basins; the 24th of July, 2001, at Štrbský Creek; and the 19th of June, 2004, at Turniansky Creek. The analysis aims to assess the flash flood peaks and rainfall-runoff properties by combining post-flood surveys and the application of hydrological and hydraulic post-event analyses. Next, a spatially-distributed hydrological model based on the availability of the raster information of the landscape’s topography, soil and vegetation properties, and rainfall data was used to simulate the runoff. The results from the application of the distributed hydrological model were used to analyse the consistency of the surveyed peak discharges with respect to the estimated rainfall properties and drainage basins. In the second part these data were combined with observations from flash flood events which were observed during the last 100 years and are focused on an analysis of the relationship between the flood peaks and the catchment area. The envelope curve was shown to exhibit a more pronounced decrease with the catchment size with respect to other flash flood relationships found in the Mediterranean region. The differences between the two relationships mainly reflect changes in the coverage of the storm sizes and hydrological characteristics between the two regions.


2017 ◽  
Vol 9 (3) ◽  
pp. 621-638 ◽  
Author(s):  
Katerina Papagiannaki ◽  
Vassiliki Kotroni ◽  
Kostas Lagouvardos ◽  
Isabelle Ruin ◽  
Antonis Bezes

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.


2018 ◽  
Vol 13 (4) ◽  
pp. 780-792
Author(s):  
Mohammad Hossain Mahtab ◽  
Miho Ohara ◽  
Mohamed Rasmy ◽  
◽  

The north-eastern part of Bangladesh is very productive for agriculture and fishing, and the region involves several depressed (haor) areas. Flash floods during the pre-monsoon period bring devastating damage to agriculture in the haor region recurrently. To protect crops from flash floods, the Bangladesh Water Development Board constructed several ring-type submersible embankments. In this research, we have investigated the effectiveness of submersible embankments in controlling flash flooding in the Matian and Shanir haors in the Sunamganj district. A two-dimensional rainfall runoff inundation model was applied considering several scenarios for simulating heavy flash flood events in 2004, 2010, and 2016. Without an embankment, the river overflow would have entered the Matian haor 3 days, 22 days, and 9 days earlier in 2004, 2010, and 2016, respectively, whereas it would have been 7 days and 23 days earlier in 2004 and 2010 for the Shanir haor. The event in 2016 was successfully stopped by the Shanir haor embankment. To avoid river overflow entering into the Matian and Shanir haor completely, the embankment height must be elevated further by 1 m and 0.7 m, respectively. Providing proper drainage facilities for the accumulated rain water inside the hoar is still an important issue for protecting the crops effectively.


2018 ◽  
Vol 2 (2) ◽  
pp. 73
Author(s):  
Fara Diva Claudia ◽  
Cecylia Putri Mawarni ◽  
Kadek Krisna Yulianti ◽  
Paulus Agus Winarso

<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>


2019 ◽  
Vol 20 (8) ◽  
pp. 1511-1531 ◽  
Author(s):  
Jessica M. Erlingis ◽  
Jonathan J. Gourley ◽  
Jeffrey B. Basara

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.


2020 ◽  
Author(s):  
Atieh Alipour ◽  
Peyman Abbaszadeh ◽  
Ali Ahmadalipour ◽  
Hamid Moradkhani

&lt;p&gt;Flash floods, as a result of frequent torrential rainfalls caused by tropical storms, thunderstorms,&lt;br&gt;and hurricanes, are a prevalent natural disaster in the southeast U.S. (SEUS), which frequently&lt;br&gt;threaten human lives and properties in the region. According to the U.S. National Weather&lt;br&gt;Service (NWS), flash floods generally initiate within less than six hours of an intense rainfall&lt;br&gt;onset. Therefore, there is a limited chance for effective and timely decision-making. Due to the&lt;br&gt;rapid onset of flash floods, they are costly events, such that only during 1996 to 2017 flash&lt;br&gt;floods imposed 7.5 billion dollars property damage to the SEUS. Therefore, estimating the&lt;br&gt;potential economic damages as a result of flash floods are crucial for flood risk management and&lt;br&gt;financial appraisals for decision makers. A multitude of studies have focused on flood damage&lt;br&gt;modeling, few of which investigated the issue on a large domain. Here, we propose a systematic&lt;br&gt;framework that considers a variety of factors that explain different risk components (i.e., hazard,&lt;br&gt;vulnerability, and exposure) and leverages Machine Learning (ML) for flood damage prediction.&lt;br&gt;Over 14,000 flash flood events during 1996 to 2017 were assessed to analyze their characteristics&lt;br&gt;including frequency, duration, and intensity. Also, different data sources were utilized to derive&lt;br&gt;information related to each event. The most influential features are then selected using a multi&lt;br&gt;criteria variable selection approach. Then, the ML model is implemented for not only binary&lt;br&gt;classification of damage (i.e., whether a flash flood event caused any damage or not), but also for&lt;br&gt;developing a model to predict the financial consequences associated with flash flood events. The&lt;br&gt;results indicate a high accuracy for the classifier, significant correlation and relatively low bias&lt;br&gt;between the predicted and observed property damages showing the effectiveness of proposed&lt;br&gt;methodology for flash flood damage modeling applicable to variety of flood prone regions.&lt;/p&gt;


2017 ◽  
Vol 56 (9) ◽  
pp. 2637-2650 ◽  
Author(s):  
A. Kermanshah ◽  
S. Derrible ◽  
M. Berkelhammer

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.


Author(s):  
Mohamed Saber ◽  
Koray Yilmaz

Abstract. This study investigates the utility of gauge-corrected satellite-based rainfall estimates in simulating flash floods at Karpuz River - a semi-arid basin in Turkey. Global Satellite Mapping of Precipitation (GSMaP) product was evaluated with the rain gauge network at monthly and daily time-scales considering various time periods and rainfall rate thresholds. Statistical analysis indicated that GSMaP shows acceptable linear correlation coefficient with rain gauges however suffers from significant underestimation bias. A rainfall rate threshold of 1 mm/month was the best choice to improve the match between GSMaP and rain gauges implying that appropriate threshold selection is critically important for the bias correction. Multiplicative bias correction was applied to GSMaP data using the bias factors calculated between GSMaP and observed rainfall. Hydrological River Basin Environmental Assessment Model (Hydro-BEAM) was used to simulate flash floods at the hourly time scale driven by the corrected GSMaP rainfall data. The model parameters were calibrated for flash flood events during October-December 2007 and then validated for flash flood events during October-December 2009. The results show that the simulated surface runoff hydrographs reasonably coincide with the observed hydrographs.


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