scholarly journals Flood reconstruction using botanical evidence in Rapentosa catchment, in Marathon, Greece.

2016 ◽  
Vol 47 (3) ◽  
pp. 1388 ◽  
Author(s):  
N. Diakakis
Keyword(s):  
Flash Flood ◽  
Flood Plain ◽  
Hydraulic Modeling ◽  
Documentary Evidence ◽  
Flood Events ◽  
Instrumental Data ◽  
The Past ◽  
Increment Borer ◽  
Water Stage ◽  
Flood Analysis

Botanical evidence has been used in the past  for flash flood analysis, especially when instrumental data were scarce. This work focuses on the use of such evidence as a tool to study flash flood phenomena in Rapentosa torrent, in Marathon, Greece. To this aim, impact scars induced during past flood events    on trees along the torrent  , were  considered water stage indicators and were used   to determine discharge magnitude of these flow episodes. Samples extracted from the scarred specimens with the aid  of an increment borer, were used to date these impacts wounds. 1-D h y-draulic  modeling  was  used  to  provide  a  reconstruction  of  the  highest-discharge event, while results were cross-examined with    historical damages to verify the out-come of the analysis. Analysis showed a total of 22 impact wounds along the torrent indicating discharge values between 17.1 m3/s and 84.9 m3/s during past flow episodes. Three flash flood events were identified in 1996, 1998 and 2001. Hydraulic modeling of the 2001 event, which presented the highest flow values, illustrated its extent    and water depth across    the  flood  plain, presenting good correlation with the available documentary evidence.

scholarly journals Use of Artificial Intelligence to Improve Resilience and Preparedness Against Adverse Flood Events

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 973 ◽  
Author(s):  
Sara Saravi ◽  
Roy Kalawsky ◽  
Demetrios Joannou ◽  
Monica Rivas Casado ◽  
Guangtao Fu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
Flash Flood ◽  
Weather Forecast ◽  
Specific Pattern ◽  
The Novel ◽  
Flood Events ◽  
Ice Melt ◽  
The Past ◽  
Different Types

The main focus of this paper is the novel use of Artificial Intelligence (AI) in natural disaster, more specifically flooding, to improve flood resilience and preparedness. Different types of flood have varying consequences and are followed by a specific pattern. For example, a flash flood can be a result of snow or ice melt and can occur in specific geographic places and certain season. The motivation behind this research has been raised from the Building Resilience into Risk Management (BRIM) project, looking at resilience in water systems. This research uses the application of the state-of-the-art techniques i.e., AI, more specifically Machin Learning (ML) approaches on big data, collected from previous flood events to learn from the past to extract patterns and information and understand flood behaviours in order to improve resilience, prevent damage, and save lives. In this paper, various ML models have been developed and evaluated for classifying floods, i.e., flash flood, lakeshore flood, etc. using current information i.e., weather forecast in different locations. The analytical results show that the Random Forest technique provides the highest accuracy of classification, followed by J48 decision tree and Lazy methods. The classification results can lead to better decision-making on what measures can be taken for prevention and preparedness and thus improve flood resilience.

Effects of 2017 Early Flash Flooding on Agriculture in Haor Areas of Sunamganj

2021 ◽  
Vol 12 (1-2) ◽  
pp. 117-125
Author(s):  
S Mondal ◽  
L Akter ◽  
HJ Hiya ◽  
MA Farukh
Keyword(s):  
Agricultural Production ◽  
Flash Flood ◽  
Eastern Region ◽  
Fish Production ◽  
Flood Events ◽  
Flash Flooding ◽  
The North ◽  
North Eastern ◽  
Boro Rice

The Sunamganj district is covered by major Haor systems in the north-eastern region of Bangladesh. Flash flood is the most commonly occurring water related disaster in the Haor areas. During the flash flood it is very common that people lost their primary agricultural productions which are the only source of their livelihood. The present study focuses on the effects of 2017 early flash flooding on rice and fish production of Sunamganj Haor areas. The flood caused enormous damage to agriculture such as rice especially Boro rice and fish production on which the Haor dwellers rely upon for their livelihood. The total affected land of Boro rice cultivation in Haors of Sunamganj was 149,224 hectare and the total amount of damaged rice was 393,855 metric ton (MT). The total number of affected farmers was 315,084. The early flash flood also affects the quality of Haor water which caused the death of fishes. The total amount of damaged fish was 49.75 MT and the loss was 158.70 lakh taka. The total number of affected fishermen was 44,445. This findings could be very useful for the environmental scientists to predict the probable future effects on agricultural production due to early flash flood events in Sunamganj Haors areas. Environ. Sci. & Natural Resources, 12(1&2): 117-125, 2019

Representative flash flood events in Romania Case studies

2008 ◽  
pp. 1587-1596
Author(s):  
G Stancalie ◽  
B Antonescu ◽  
C Oprea ◽  
A Irimescu ◽  
S Catana ◽  
...  
Keyword(s):  
Case Studies ◽  
Flash Flood ◽  
Flood Events

Methodology for risk assessment of flash flood events due to climate and land use changes

2012 ◽  
Author(s):  
M Velasco ◽  
A Cabello ◽  
I Escaler ◽  
J Barredo ◽  
A Barrera-Escoda
Keyword(s):  
Risk Assessment ◽  
Land Use ◽  
Flash Flood ◽  
Land Use Changes ◽  
Flood Events

scholarly journals MobRISK: a model for assessing the exposure of road users to flash flood events

2017 ◽  
Vol 17 (9) ◽  
pp. 1631-1651 ◽  
Author(s):  
Saif Shabou ◽  
Isabelle Ruin ◽  
Céline Lutoff ◽  
Samuel Debionne ◽  
Sandrine Anquetin ◽  
...  
Keyword(s):  
Exposure Assessment ◽  
Flash Flood ◽  
Activity Patterns ◽  
Traffic Load ◽  
Road User ◽  
Population Exposure ◽  
Flood Events ◽  
Population Mobility ◽  
Road Users ◽  
Adverse Weather

Abstract. Recent flash flood impact studies highlight that road networks are often disrupted due to adverse weather and flash flood events. Road users are thus particularly exposed to road flooding during their daily mobility. Previous exposure studies, however, do not take into consideration population mobility. Recent advances in transportation research provide an appropriate framework for simulating individual travel-activity patterns using an activity-based approach. These activity-based mobility models enable the prediction of the sequence of activities performed by individuals and locating them with a high spatial–temporal resolution. This paper describes the development of the MobRISK microsimulation system: a model for assessing the exposure of road users to extreme hydrometeorological events. MobRISK aims at providing an accurate spatiotemporal exposure assessment by integrating travel-activity behaviors and mobility adaptation with respect to weather disruptions. The model is applied in a flash-flood-prone area in southern France to assess motorists' exposure to the September 2002 flash flood event. The results show that risk of flooding mainly occurs in principal road links with considerable traffic load. However, a lag time between the timing of the road submersion and persons crossing these roads contributes to reducing the potential vehicle-related fatal accidents. It is also found that sociodemographic variables have a significant effect on individual exposure. Thus, the proposed model demonstrates the benefits of considering spatiotemporal dynamics of population exposure to flash floods and presents an important improvement in exposure assessment methods. Such improved characterization of road user exposures can present valuable information for flood risk management services.

scholarly journals The Anthropology of Plague: Insights from Bioarcheological Analyses of Epidemic Cemeteries

2015 ◽  
Vol 1 (1) ◽  
pp. 97-123
Author(s):  
Sharon N. Dewitte
Keyword(s):  
Historical Record ◽  
Skeletal Remains ◽  
Black Death ◽  
Documentary Evidence ◽  
The Past ◽  
Bear Witness

Most research on historic plague has relied on documentary evidence, but recently researchers have examined the remains of plague victims to produce a deeper understanding of the disease. Bioarcheological analysis allows the skeletal remains of epidemic victims to bear witness to the contexts of their deaths. This is important for our understanding of the experiences of the vast majority of people who lived in the past, who are not typically included in the historical record. This paper summarizes bioarcheological research on plague, primarily investigations of the Black Death in London (1349–50), emphasizing what anthropology uniquely contributes to plague studies.

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