scholarly journals Bias Correction of Satellite-Based Rainfall Estimates for Modeling Flash Floods in Semi-Arid regions: Application to Karpuz River, Turkey

2016 ◽  
Author(s):  
Mohamed Saber ◽  
Koray Yilmaz
Keyword(s):  
Bias Correction ◽  
Flash Flood ◽  
Flash Floods ◽  
Rainfall Rate ◽  
Assessment Model ◽  
Model Parameters ◽  
Flood Events ◽  
Rain Gauges ◽  
Semi Arid ◽  
Rainfall Estimates

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.

Radar-based rainfall nowcasting for flash flood hazard assessment: recent results at regional and Continental scales

2020 ◽  
Author(s):  
Marc Berenguer ◽  
Shinju Park ◽  
Daniel Sempere-Torres
Keyword(s):  
Real Time ◽  
Hazard Assessment ◽  
Flash Flood ◽  
Flood Hazard ◽  
Spatial Scales ◽  
Flash Floods ◽  
Radar Rainfall ◽  
European Projects ◽  
Rainfall Estimates ◽  
Ne Spain

<p>Radar rainfall estimates and nowcasts have been used in Catalonia (NE Spain) for real-time flash flood hazard nowcasting based on the basin-aggregated rainfall for several years. This approach has been further developed within the European Projects ERICHA (www.ericha.eu) and ANYWHERE (www.anywhere-h2020.eu), where it has been demonstrated to monitor flash floods in real time in several locations and at different spatial scales (from regional to Continental coverage).</p><p>The work summarizes the main results of the recent projects, analysing the performance of the flash flood nowcasting system. The results obtained on recent events  show the main advantages and some of the limitations of the system.</p>

scholarly journals Post-event analysis and flash flood hydrology in Slovakia

2016 ◽  
Vol 64 (4) ◽  
pp. 304-315 ◽  
Author(s):  
Kamila Hlavčová ◽  
Silvia Kohnová ◽  
Marco Borga ◽  
Oliver Horvát ◽  
Pavel Šťastný ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Flash Flood ◽  
Flash Floods ◽  
Event Analysis ◽  
Distributed Hydrological Model ◽  
Rainfall Runoff ◽  
Flood Events ◽  
Spatially Distributed ◽  
Catchment Size ◽  
Flood Peaks

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.

scholarly journals Flash flood occurrence and relation to the rainfall hazard in a highly urbanized area

2015 ◽  
Vol 3 (5) ◽  
pp. 3119-3149
Author(s):  
K. Papagiannaki ◽  
K. Lagouvardos ◽  
V. Kotroni ◽  
A. Bezes
Keyword(s):  
Flash Flood ◽  
Flood Hazard ◽  
Local Level ◽  
Geographical Area ◽  
Fire Service ◽  
Flood Events ◽  
Rain Gauges ◽  
Weather Events ◽  
Urbanized Region

Abstract. The paper examines the flash flood events that occurred during a decade in the Attica prefecture, the most urbanized region of Greece, with the aim of assessing the local vulnerability to the flash flood hazard and the effect of rainfall upon the magnitude of the induced damages. The analysis incorporates rainfall records from a network of 28 surface meteorological stations and information on the spatial distribution of the flash flood events that is derived from the active database of damaging weather events maintained by the atmospheric modelling group of the National Observatory of Athens. The main findings concern the relation between the flash flood impact, as measured by the Fire Service operations in flooded properties, and precipitation in various time intervals, as well as the possibility to define rainfall intensity thresholds for flood triggering at a more local level. It is shown that the quality of the produced thresholds depends on the distribution and density of the rain gauges that cover each specified geographical area of the Attica region.

scholarly journals Effectiveness of the Submersible Embankment in Haor Area in Bangladesh

2018 ◽  
Vol 13 (4) ◽  
pp. 780-792
Author(s):  
Mohammad Hossain Mahtab ◽  
Miho Ohara ◽  
Mohamed Rasmy ◽  
◽  
Keyword(s):  
Flash Flood ◽  
Flash Floods ◽  
Rainfall Runoff ◽  
Flood Events ◽  
Monsoon Period ◽  
Flash Flooding ◽  
The North ◽  
North Eastern ◽  
Embankment Height ◽  
North Eastern Part

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.

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.

Satellite Data Application to Cover Lack of In-situ Observations for Mapping Precipitation and Direct Runoff in Semi-arid Basin

2020 ◽  
Author(s):  
Mahdi Akbari ◽  
Ali Torabi Haghighi
Keyword(s):  
Hydrological Modeling ◽  
Rain Gauge ◽  
Model Parameters ◽  
Lake Basin ◽  
Lake Urmia ◽  
Direct Runoff ◽  
Rain Gauges ◽  
High Elevations ◽  
Semi Arid

<div> <p>Hydrological modeling in arid basins located in developing countries often lacks sufficient hydrological data because, e.g., rain gauges are typically absent at high elevations and inflow to ungauged areas around large closed lakes such as Lake Urmia is difficult to estimate. We tried to improve precipitation and runoff estimation in Lake Urmia, Iran as an arid basin using satellite-based data. We estimated precipitation using interpolation of rain gauge data by kriging, downscaling Tropical Rainfall Measuring Mission (TRMM), and cokriging interpolation of in-situ records with Remote Sensing (RS)-based data. Using RS-based data in estimations gave more precise results, by compensating for lack of data at high elevations. Cokriging interpolation of rain gauges by TRMM and Digitized Elevation Model (DEM) gave 4–9 mm lower Root Mean Square Error (RMSE) in different years compared with kriging. Downscaling TRMM improved its accuracy by 14 mm. Using the most accurate precipitation model, we modeled annual direct runoff with Kennessey and Soil Conservation Service Curve Number (SCS-CN) models. These models use land use, permeability, slope maps and climatic parameter (Ia) to represent the annual climatic condition of modeled basin in sense of wetness or dryness. In runoff modeling, Kennessey gave higher accuracy in annual scale. It was found that classification of years to wet, dry and normal states in Kennessey by default assumptions on Ia is not accurate enough for semi-arid basins so by solving this issue and calibration Kennessey model parameters, we made this model applicable for Urmia Lake basin. Calibrating Kennessey reduced the Normalized RMSE (NRMSE) from 1 in the standard model to 0.44. Direct runoff coefficient map by 1 km spatial resolution was generated by calibrated Kennessey. Validation by the closest gauges to the lake gave a NRMSE of 0.41 which approved the accuracy of modeling.</p> </div>

From Flash Flood Vulnerability and Risk Assessment to Property Damage Prediction: the Value of Machine Learning

2020 ◽  
Author(s):  
Atieh Alipour ◽  
Peyman Abbaszadeh ◽  
Ali Ahmadalipour ◽  
Hamid Moradkhani
Keyword(s):  
Machine Learning ◽  
Flash Flood ◽  
Rapid Onset ◽  
Flash Floods ◽  
Flood Damage ◽  
Flood Events ◽  
Property Damage ◽  
Damage Prediction ◽  
Financial Consequences

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

scholarly journals Rainstorms able to induce flash floods in a Mediterranean-climate region (Calabria, southern Italy)

2014 ◽  
Vol 14 (9) ◽  
pp. 2423-2434 ◽  
Author(s):  
O. G. Terranova ◽  
S. L. Gariano
Keyword(s):  
Mediterranean Climate ◽  
Southern Italy ◽  
Flash Flood ◽  
Temporal Structure ◽  
Flash Floods ◽  
Rain Gauges ◽  
Mediterranean Countries ◽  
Preliminary Validation ◽  
The Mediterranean ◽  
Landslides And Debris Flows

Abstract. Heavy rainstorms often induce flash flooding, one of the natural disasters most responsible for damage to man-made infrastructures and loss of lives, also adversely affecting the opportunities for socio-economic development of Mediterranean countries. The frequently dramatic damage of flash floods are often detected, with sufficient accuracy, by post-event surveys, but rainfall causing them are still only roughly characterized. With the aim of improving the understanding of the temporal structure and spatial distribution of heavy rainstorms in the Mediterranean context, a statistical analysis was carried out in Calabria (southern Italy) concerning rainstorms that mainly induced flash floods, but also shallow landslides and debris flows. Thus, a method is proposed – based on the overcoming of heuristically predetermined threshold values of cumulated rainfall, maximum intensity, and kinetic energy of the rainfall event – to select and characterize the rainstorms able to induce flash floods in the Mediterranean-climate countries. Therefore, the obtained (heavy) rainstorms were automatically classified and studied according to their structure in time, localization, and extension. Rainfall-runoff watershed models can consequently benefit from the enhanced identification of design storms, with a realistic time structure integrated with the results of the spatial analysis. A survey of flash flood events recorded in the last decades provides a preliminary validation of the method proposed to identify the heavy rainstorms and synthetically describe their characteristics. The notable size of the employed sample, including data with a very detailed resolution in time that relate to several rain gauges well-distributed throughout the region, gives robustness to the obtained results.

scholarly journals Using High-Resolution Satellite Rainfall Products to Simulate a Major Flash Flood Event in Northern Italy

2013 ◽  
Vol 14 (1) ◽  
pp. 171-185 ◽  
Author(s):  
Efthymios I. Nikolopoulos ◽  
Emmanouil N. Anagnostou ◽  
Marco Borga
Keyword(s):  
High Resolution ◽  
Complex Terrain ◽  
Flash Flood ◽  
Flash Floods ◽  
Hydrologic Model ◽  
Flood Event ◽  
Medium Size ◽  
Soil Conditions ◽  
Model Parameters ◽  
Satellite Rainfall

Abstract Effective flash flood warning procedures are usually hampered by observational limitations of precipitation over mountainous basins where flash floods occur. Satellite rainfall estimates are available over complex terrain regions, offering a potentially viable solution to the observational coverage problem. However, satellite estimates of heavy rainfall rates are associated with significant biases and random errors that nonlinearly propagate in hydrologic modeling, imposing severe limitations on the use of these products in flood forecasting. In this study, the use of three quasi-global and near-real-time high-resolution satellite rainfall products for simulating flash floods over complex terrain basins are investigated. The study uses a major flash flood event that occurred during 29 August 2003 on a medium size mountainous basin (623 km2) in the eastern Italian Alps. Comparison of satellite rainfall with rainfall derived from gauge-calibrated weather radar estimates showed that although satellite products suffer from large biases they could represent the temporal variability of basin-averaged precipitation. Propagation of satellite rainfall through a distributed hydrologic model revealed that systematic error in rainfall was severely magnified when transformed to error in runoff under dry initial soil conditions. Simulation hydrographs became meaningful only after recalibrating the model for each satellite rainfall input separately. However, the unrealistic values of model parameters after recalibration show that this approach is erroneous and that model recalibration using satellite rainfall data should be treated with care. Overall, this study highlights the need for improvement of satellite rainfall retrieval algorithms in order to allow a more appropriate use of satellite rainfall products for flash flood applications.

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