River plume dispersion in response to flash flood events. Application to the Catalan shelf

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


2021 ◽  
Vol 12 (1-2) ◽  
pp. 117-125
Author(s):  
S Mondal ◽  
L Akter ◽  
HJ Hiya ◽  
MA Farukh

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


Author(s):  
G Stancalie ◽  
B Antonescu ◽  
C Oprea ◽  
A Irimescu ◽  
S Catana ◽  
...  

Author(s):  
M Velasco ◽  
A Cabello ◽  
I Escaler ◽  
J Barredo ◽  
A Barrera-Escoda

2017 ◽  
Vol 17 (9) ◽  
pp. 1631-1651 ◽  
Author(s):  
Saif Shabou ◽  
Isabelle Ruin ◽  
Céline Lutoff ◽  
Samuel Debionne ◽  
Sandrine Anquetin ◽  
...  

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.


2019 ◽  
Vol 11 (19) ◽  
pp. 5426 ◽  
Author(s):  
Saeid Janizadeh ◽  
Mohammadtaghi Avand ◽  
Abolfazl Jaafari ◽  
Tran Van Phong ◽  
Mahmoud Bayat ◽  
...  

Floods are some of the most destructive and catastrophic disasters worldwide. Development of management plans needs a deep understanding of the likelihood and magnitude of future flood events. The purpose of this research was to estimate flash flood susceptibility in the Tafresh watershed, Iran, using five machine learning methods, i.e., alternating decision tree (ADT), functional tree (FT), kernel logistic regression (KLR), multilayer perceptron (MLP), and quadratic discriminant analysis (QDA). A geospatial database including 320 historical flood events was constructed and eight geo-environmental variables—elevation, slope, slope aspect, distance from rivers, average annual rainfall, land use, soil type, and lithology—were used as flood influencing factors. Based on a variety of performance metrics, it is revealed that the ADT method was dominant over the other methods. The FT method was ranked as the second-best method, followed by the KLR, MLP, and QDA. Given a few differences between the goodness-of-fit and prediction success of the methods, we concluded that all these five machine-learning-based models are applicable for flood susceptibility mapping in other areas to protect societies from devastating floods.


2017 ◽  
Vol 65 (1) ◽  
pp. 89-102 ◽  
Author(s):  
Diana Meilutytė-Lukauskienė ◽  
Vytautas Akstinas ◽  
Jūratė Kriaučiūnienė ◽  
Diana Šarauskienė ◽  
Aldona Jurgelėnaitė

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