scholarly journals The RainBO Platform for Enhancing Urban Resilience to Floods: An Efficient Tool for Planning and Emergency Phases

Climate ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 145
Author(s):  
Giulia Villani ◽  
Stefania Nanni ◽  
Fausto Tomei ◽  
Stefania Pasetti ◽  
Rita Mangiaracina ◽  
...  
Keyword(s):  
Flood Risk ◽  
Extreme Precipitation ◽  
Urban Areas ◽  
Early Warning Systems ◽  
Economic Losses ◽  
Urban Resilience ◽  
Multiple Sources ◽  
Life Project ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Many urban areas face an increasing flood risk, which includes the risk of flash floods. Increasing extreme precipitation events will likely lead to greater human and economic losses unless reliable and efficient early warning systems (EWS) along with other adaptation actions are put in place in urban areas. The challenge is in the integration and analysis in time and space of the environmental, meteorological, and territorial data from multiple sources needed to build up EWS able to provide efficient contribution to increase the resilience of vulnerable and exposed urban communities to flooding. Efficient EWS contribute to the preparedness phase of the disaster cycle but could also be relevant in the planning of the emergency phase. The RainBO Life project addressed this matter, focusing on the improvement of knowledge, methods, and tools for the monitoring and forecast of extreme precipitation events and the assessment of the associated flood risk for small and medium watercourses in urban areas. To put this into practice, RainBO developed a webGIS platform, which contributes to the “planning” of the management of river flood events through the use of detailed data and flood risk/vulnerability maps, and the “event management” with real-time monitoring/forecast of the events through the collection of observed data from real sensors, estimated/forecasted data from hydrologic models as well as qualitative data collected through a crowdsourcing app.

Extreme precipitation events in the Mediterranean region: their characteristics and connection to large-scale atmospheric patterns

2020 ◽  
Author(s):  
Nikolaos Mastrantonas ◽  
Linus Magnusson ◽  
Florian Pappenberger ◽  
Jörg Matschullat
Keyword(s):  
Natural Hazards ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Mediterranean Region ◽  
Large Scale ◽  
Early Warning Systems ◽  
Spatiotemporal Variability ◽  
Extreme Precipitation Events ◽  
The Mediterranean ◽  
Precipitation Events

<p>The Mediterranean region is an area with half a billion population, about 10 percent contribution to the world’s GDP, and locations of global natural, historical and cultural significance. In this context, natural hazards in the area have the potential for severe negative impacts on society, economy, and environment. </p><p>Some of the most frequent and devastating natural hazards that affect the Mediterranean relate to extreme precipitation events causing flash floods and landslides. Thus, given their adverse consequences, it is of immense importance to better understand their statistical characteristics and connection to large-scale atmospheric patterns. Such advances can substantially support the accurate and early identification of these extreme events, improve early warning systems, and contribute to mitigating related risks. </p><p>This work focuses on the characteristics and spatiotemporal variability of extreme precipitation events of large spatial coverage across the Mediterranean region. The study uses the ERA5 dataset, the latest, state of the art, reanalysis dataset from Copernicus/ECMWF. Initially, exploratory analysis is performed to assess the different characteristics at various subdomains within the study area. Furthermore, composite analysis is used to understand the connection of extreme events with large-scale atmospheric patterns. Finally, the Empirical Orthogonal Function (EOF) analysis is implemented to quantify the importance of weather regimes with respect to the frequency of extreme precipitation events. </p><p>Preliminary results indicate that there is a spatial division in the occurrence of identified events. Winter and autumn are the seasons of the highest frequency of extreme precipitation for the east and west Mediterranean respectively. Troughs and cut-off lows in the lower and middle-level troposphere have a strong association with such extreme events, and the effect is modulated by other parameters, such as local orography. Results of this work are in accordance with previous studies in the region and provide information that can be utilized by future research for improving the predictability of such events in the medium- and extended-range forecasts. </p><p>This work is part of the Climate Advanced Forecasting of sub-seasonal Extremes (CAFE) project. The project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813844.</p>

scholarly journals Quantitative Agricultural Flood Risk Assessment Using Vulnerability Surface and Copula Functions

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1229 ◽  
Author(s):  
Yongfang Wang ◽  
Guixiang Liu ◽  
Enliang Guo ◽  
Xiangjun Yun
Keyword(s):  
Flood Risk ◽  
Extreme Precipitation ◽  
Joint Distribution ◽  
Disaster Risk ◽  
Flood Disaster ◽  
Surface Model ◽  
Copula Functions ◽  
Extreme Precipitation Events ◽  
Flood Disasters ◽  
Precipitation Events

Agricultural flood disaster risk assessment plays a vital role in agricultural flood disaster risk management. Extreme precipitation events are the main causes of flood disasters in the Midwest Jilin province (MJP). Therefore, it is important to analyse the characteristics of extreme precipitation events and assess the flood risk. In this study, the Multifractal Detrended Fluctuation Analysis (MF-DFA) method was used to determine the threshold of extreme precipitation events. The total duration of extreme precipitation and the total extreme precipitation were selected as flood indicators. The copula functions were then used to determine the joint distribution to calculate the bivariate joint return period, which is the flood hazard. Historical data and flood indicators were used to build an agricultural flood disaster vulnerability surface model. Finally, the risk curve for agricultural flood disasters was established to assess the flood risk in the MJP. The results show that the proposed approaches precisely describe the joint distribution of the flood indicators. The results of the vulnerability surface model are in accordance with the spatiotemporal distribution pattern of the agricultural flood disaster loss in this area. The agricultural flood risk of the MJP gradually decreases from east to west. The results provide a firm scientific basis for flood control and drainage plans in the area.

Extreme precipitation events in the Mediterranean area. A contrasting Lagrangian and Eulerian approach for moisture evaporation sources identification.

2020 ◽  
Author(s):  
Sara Cloux González ◽  
A. Daniel Garaboa Paz ◽  
Damian Insua Costa ◽  
Vicente Perez Muñuzuri ◽  
Gonzálo Miguez Macho
Keyword(s):  
Extreme Precipitation ◽  
Lagrangian Model ◽  
Precipitation Event ◽  
Economic Losses ◽  
Correct Identification ◽  
Geophysical Research ◽  
Moisture Sources ◽  
Extreme Precipitation Events ◽  
The Mediterranean ◽  
Precipitation Events

<div> <p>Concern about heavy precipitation events has increasingly grown in the last years in the South of Europe, especially in the Mediterranean region. These occasional episodes can result in more than 200 mm of rainfall in less than 24 h, producing flash floods with very high social and economic losses.  </p> </div><div> <p>To improve their predictability, the correct identification of the origin of the moisture must be done. The Eulerian and Lagrangian models provide a good approach to detect moisture sources. However, they show some limitations. </p> </div><div> <p>Here, we present a comparison between both methods through a case study of an extreme precipitation event on the region of the Mediterranean coast which take place in 1982. Using the Lagrangian model FLEXPART-WRF to backtrack the moisture, we identify the evaporation sources. Then, we compare it with the results obtained through Eulerian WRF-WVT method [1]. Also, we evaluate the accuracy of E-P balance in contrast to Evaporation patterns. Finally, we implemented a further identification of moisture uptake method which enables us to directly compare results from both strategies [2]. </p> </div><div> <p> </p> </div><div> <p>[1] Insua-Costa, D., Miguez-Macho, G., and Llasat, M. C.: Local and remote moisture sources for extreme precipitation: a study of the two catastrophic 1982 western Mediterranean episodes, Hydrol. Earth Syst. Sci., 23, 3885–3900, https://doi.org/10.5194/hess-23-3885-2019, 2019. </p> </div><div> <p>[2] Sodemann, Harald, C. Schwierz, and Heini Wernli.: Interannual variability of Greenland winter precipitation sources: Lagrangian moisture diagnostic and North Atlantic Oscillation influence. Journal of Geophysical Research: Atmospheres 113.D3 (2008). </p> </div>

scholarly journals Semiarid grasslands and extreme precipitation events: Do experimental results scale to the landscape?

Ecology ◽  
2021 ◽  
Author(s):  
Alison K. Post ◽  
Kristin P. Davis ◽  
Jillian LaRoe ◽  
David L. Hoover ◽  
Alan K. Knapp
Keyword(s):  
Extreme Precipitation ◽  
Experimental Results ◽  
Extreme Precipitation Events ◽  
Precipitation Events

scholarly journals Recognizing the Aggregation Characteristics of Extreme Precipitation Events Using Spatio-Temporal Scanning and the Local Spatial Autocorrelation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 218
Author(s):  
Changjun Wan ◽  
Changxiu Cheng ◽  
Sijing Ye ◽  
Shi Shen ◽  
Ting Zhang
Keyword(s):  
Spatial Autocorrelation ◽  
Extreme Precipitation ◽  
Eastern China ◽  
Temporal Aggregation ◽  
Global Changes ◽  
Percentile Method ◽  
Extreme Precipitation Events ◽  
Spatio Temporal ◽  
Precipitation Events ◽  
Local Spatial Autocorrelation

Precipitation is an essential climate variable in the hydrologic cycle. Its abnormal change would have a serious impact on the social economy, ecological development and life safety. In recent decades, many studies about extreme precipitation have been performed on spatio-temporal variation patterns under global changes; little research has been conducted on the regionality and persistence, which tend to be more destructive. This study defines extreme precipitation events by percentile method, then applies the spatio-temporal scanning model (STSM) and the local spatial autocorrelation model (LSAM) to explore the spatio-temporal aggregation characteristics of extreme precipitation, taking China in July as a case. The study result showed that the STSM with the LSAM can effectively detect the spatio-temporal accumulation areas. The extreme precipitation events of China in July 2016 have a significant spatio-temporal aggregation characteristic. From the spatial perspective, China’s summer extreme precipitation spatio-temporal clusters are mainly distributed in eastern China and northern China, such as Dongting Lake plain, the Circum-Bohai Sea region, Gansu, and Xinjiang. From the temporal perspective, the spatio-temporal clusters of extreme precipitation are mainly distributed in July, and its occurrence was delayed with an increase in latitude, except for in Xinjiang, where extreme precipitation events often take place earlier and persist longer.

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