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Journal articles on the topic 'Flash floods forecasting'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Chang, Tzu-Yin, Hongey Chen, Huei-Shuin Fu, et al. "An Operational High-Performance Forecasting System for City-Scale Pluvial Flash Floods in the Southwestern Plain Areas of Taiwan." Water 13, no. 4 (2021): 405. http://dx.doi.org/10.3390/w13040405.

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A pluvial flash flood is rapid flooding induced by intense rainfall associated with a severe weather system, such as thunderstorms or typhoons. Additionally, topography, ground cover, and soil conditions also account for the occurrence of pluvial flash floods. Pluvial flash floods are among the most devastating natural disasters that occur in Taiwan, and these floods always /occur within a few minutes or hours of excessive rainfall. Pluvial flash floods usually threaten large plain areas with high population densities; therefore, there is a great need to implement an operational high-performan

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Younis, J., S. Anquetin, and J. Thielen. "The benefit of high-resolution operational weather forecasts for flash flood warning." Hydrology and Earth System Sciences Discussions 5, no. 1 (2008): 345–77. http://dx.doi.org/10.5194/hessd-5-345-2008.

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Abstract. In Mediterranean Europe, flash flooding is one of the most devastating hazards in terms of human life loss and infrastructures. Over the last two decades, flash floods brought losses of a billion Euros of damage in France alone. One of the problems of flash floods is that warning times are very short, leaving typically only a few hours for civil protection services to act. This study investigates if operationally available shortrange numerical weather forecasts together with a rainfall-runoff model can be used as early indication for the occurrence of flash floods. One of the challen

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Nguyen Van Ha, Tran Dang Hung, Doan Tran Anh, Giang Hoang Hiep, Nguyen Thi Huyen Trang, and Doan Ha Phong. "APPLICATION OF GIS AND REMOTE SENSING FOR MAPPING FLASH FLOOD RISE IN HOA BINH PROVINCE UNDER CLIMATE CHANGE CONTEXT." Tạp chí Khoa học Biến đổi khí hậu, no. 23 (December 28, 2022): 53–68. http://dx.doi.org/10.55659/2525-2496/23.75013.

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Hoa Binh is one of the provinces strongly suffering from natural disasters, especially flash floods. High slope mountainous terrains, reduced vegetation cover and unfavorable weather conditions form favorable conditions for flash floods to occur. This article develops a map of flash flood risk zoning in Hoa Binh using remote sensing and GIS technology. First, the factors affecting the risk of flash floods are identified, and each factor is classified based on the level of influence, then proceed to overlay the component maps causing flash floods. Factors affecting flash flood risk include: Slo

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Younis, J., S. Anquetin, and J. Thielen. "The benefit of high-resolution operational weather forecasts for flash flood warning." Hydrology and Earth System Sciences 12, no. 4 (2008): 1039–51. http://dx.doi.org/10.5194/hess-12-1039-2008.

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Abstract. In Mediterranean Europe, flash flooding is one of the most devastating hazards in terms of loss of human life and infrastructures. Over the last two decades, flash floods have caused damage costing a billion Euros in France alone. One of the problems of flash floods is that warning times are very short, leaving typically only a few hours for civil protection services to act. This study investigates if operationally available short-range numerical weather forecasts together with a rainfall-runoff model can be used for early indication of the occurrence of flash floods. One of the chal

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Nguyen, Duyen Thi My, and Hai Quang Ha. "Flash floods potential area mapping at Huong Khe district, Ha Tinh prov." Science and Technology Development Journal - Natural Sciences 1, T4 (2017): 249–54. http://dx.doi.org/10.32508/stdjns.v1it4.487.

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Ha Tinh is one of the provinces most affected by natural hazards, especially flash floods. Sloping hilly terrain conditions, reduced covering density of forest and unfavorable weather conditions are potential hazards to flash floods. Flash floods potential area mapping at Huong Khe district, Ha Tinh province was carried out using Remote Sensing and GIS technologies. Factors causing flash floods was indentified and classified basing n their afecting level. Component maps of flash flood–causing factors were overlayed. Factors causing flash floods as noted by Greg Smith included: slope, soil type

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Chen, Y., J. Li, S. Huang, and Y. Dong. "Study of Beijiang catchment flash-flood forecasting model." Proceedings of the International Association of Hydrological Sciences 368 (May 6, 2015): 150–55. http://dx.doi.org/10.5194/piahs-368-150-2015.

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Abstract. Beijiang catchment is a small catchment in southern China locating in the centre of the storm areas of the Pearl River Basin. Flash flooding in Beijiang catchment is a frequently observed disaster that caused direct damages to human beings and their properties. Flood forecasting is the most effective method for mitigating flash floods, the goal of this paper is to develop the flash flood forecasting model for Beijiang catchment. The catchment property data, including DEM, land cover types and soil types, which will be used for model construction and parameter determination, are downl

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Chen, Yung-Ming, Che-Hsin Liu, Hung-Ju Shih, et al. "An Operational Forecasting System for Flash Floods in Mountainous Areas in Taiwan." Water 11, no. 10 (2019): 2100. http://dx.doi.org/10.3390/w11102100.

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Flash floods are different from common floods because they occur rapidly over short time scales, and they are considered to be one of the most devastating natural hazards worldwide. Mountainous areas with high population densities are particularly threatened by flash floods because steep slopes generate high flow velocities. Therefore, there is a great need to develop an operational forecasting system (OFS) for better flash flood prediction and warning in mountainous regions. This study developed an OFS through the integration of meteorological, hydrological, and hydrodynamic models. Airborne

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Godet, Juliette, Olivier Payrastre, Pierre Javelle, and François Bouttier. "Assessing the ability of a new seamless short-range ensemble rainfall product to anticipate flash floods in the French Mediterranean area." Natural Hazards and Earth System Sciences 23, no. 11 (2023): 3355–77. http://dx.doi.org/10.5194/nhess-23-3355-2023.

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Abstract. Flash floods have dramatic economic and social consequences, and efficient adaptation policies are required to reduce their impacts, especially in the context of global change. Developing more efficient flash flood forecasting systems can largely contribute to these adaptation requirements. The aim of this study was to assess the ability of a new seamless short-range ensemble quantitative precipitation forecast (QPF) product, called PIAF-EPS (Prévision Immédiate Agrégée Fusionnée ensemble prediction system) and recently developed by Météo-France, to predict flash floods when used as

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Šaur, David, and Kateřina Víchová. "Forecasting of flash floods by Algorithm of Storm Prediction." MATEC Web of Conferences 210 (2018): 04033. http://dx.doi.org/10.1051/matecconf/201821004033.

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This article focuses on the forecasting of flash floods using the Algorithm of Storm Prediction as a new tool to predict convective precipitation, severe phenomena and the risk of flash floods. The first part of the article contains information on methods for predicting dangerous severe phenomena. This algorithm uses mainly data from numerical weather prediction models (NWP models), database of historic weather events and relief characteristics describing the influence of orography on the initiation of atmospheric convection. The result section includes verification of predicted algorithm outp

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Asaly, Saed, Lee-Ad Gottlieb, Yoav Yair, Colin Price, and Yuval Reuveni. "Predicting Eastern Mediterranean Flash Floods Using Support Vector Machines with Precipitable Water Vapor, Pressure, and Lightning Data." Remote Sensing 15, no. 11 (2023): 2916. http://dx.doi.org/10.3390/rs15112916.

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Flash floods in the Eastern Mediterranean (EM) region are considered among the most destructive natural hazards, which pose a significant challenge to model due to their high complexity. Machine learning (ML) methods have made a significant contribution to the advancement of flash flood prediction systems by providing cost-effective solutions with improved performance, enabling the modeling of the complex mathematical expressions underlying physical processes of flash floods. Thus, the development of ML methods for flash flood prediction holds the potential to mitigate risks, inform policy rec

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Wu, Jian, Haixing Liu, Guozhen Wei, Tianyu Song, Chi Zhang, and Huicheng Zhou. "Flash Flood Forecasting Using Support Vector Regression Model in a Small Mountainous Catchment." Water 11, no. 7 (2019): 1327. http://dx.doi.org/10.3390/w11071327.

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Flash floods in mountainous catchments are often caused by the rainstorm, which may result in more severe consequences than plain area floods due to less timescale and a fast-flowing front of water and debris. Flash flood forecasting is a huge challenge for hydrologists and managers due to its instantaneity, nonlinearity, and dependency. Among different methods of flood forecasting, data-driven models have become increasingly popular in recent years due to their strong ability to simulate nonlinear hydrological processes. This study proposed a Support Vector Regression (SVR) model, which is a

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Pham, Huong Giang, and Quoc Lap Kieu. "Research on the factors contributing to flash floods in the Northern mountainous region of Vietnam: criteria, weights, and evaluation indexes." Bulletin of Geography. Physical Geography Series, no. 28 (April 28, 2025): 17–31. https://doi.org/10.12775/bgeo-2025-0002.

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Flash floods are one of the most severe natural disasters, particularly in the northern mountainous regions of Vietnam, where steep terrain and dense river and stream networks are prevalent. These flash floods cause significant loss of life and property, threatening the sustainable development of these areas. However, assessing and forecasting flash flood risks remains challenging due to the lack of specific scientific analysis methods. This study aims to systematically analyze both natural and anthropogenic factors contributing to flash flood risks and to develop a comprehensive, multi-criter

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Song, Tianyu, Wei Ding, Jian Wu, Haixing Liu, Huicheng Zhou, and Jinggang Chu. "Flash Flood Forecasting Based on Long Short-Term Memory Networks." Water 12, no. 1 (2019): 109. http://dx.doi.org/10.3390/w12010109.

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Flash floods occur frequently and distribute widely in mountainous areas because of complex geographic and geomorphic conditions and various climate types. Effective flash flood forecasting with useful lead times remains a challenge due to its high burstiness and short response time. Recently, machine learning has led to substantial changes across many areas of study. In hydrology, the advent of novel machine learning methods has started to encourage novel applications or substantially improve old ones. This study aims to establish a discharge forecasting model based on Long Short-Term Memory

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Semie, Addisu G., Gulilat T. Diro, Teferi Demissie, Yonas M. Yigezu, and Binyam Hailu. "Towards Improved Flash Flood Forecasting over Dire Dawa, Ethiopia Using WRF-Hydro." Water 15, no. 18 (2023): 3262. http://dx.doi.org/10.3390/w15183262.

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Flash floods are increasingly frequent worldwide. Recent flooding in eastern Ethiopia resulted in casualties, destruction of property and interruptions of service. National flash flood forecasts made today primarily consider precipitation, putting less emphasis on surface processes. Enhancing accurate flash flood forecasts by accounting for surface processes and hydrological models together with a deeper understanding of heavy precipitation mechanisms is of paramount importance. To this end, an uncoupled WRF-Hydro model was calibrated for eastern Ethiopia to simulate extreme floods. Sensitivit

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Anafi, Nurin Fadhlina Mohd, Norzailawati Mohd Noor, and Hasti Widyasamratri. "A Systematic Review of Real-time Urban Flood Forecasting Model in Malaysia and Indonesia -Current Modelling and Challenge." Jurnal Planologi 20, no. 2 (2023): 150. http://dx.doi.org/10.30659/jpsa.v20i2.30765.

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Several metropolitan areas in tropical Southeast Asia, mainly in Malaysia and Indonesia have lately been witnessing unprecedentedly severe flash floods owing to unexpected climate change. The fast water flooding has caused extraordinarily serious harm to urban populations and social facilities. In addition, urban Southeast Asia generally has insufficient capacity in drainage systems, complex land use patterns, and a largely susceptible population in confined urban regions. To lower the urban flood risk and strengthen the resilience of vulnerable urban populations, it has been of fundamental re

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Xiong, Junnan, Chongchong Ye, Weiming Cheng, Liang Guo, Chenghu Zhou, and Xiaolei Zhang. "The Spatiotemporal Distribution of Flash Floods and Analysis of Partition Driving Forces in Yunnan Province." Sustainability 11, no. 10 (2019): 2926. http://dx.doi.org/10.3390/su11102926.

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Flash floods are one of the most serious natural disasters, and have a significant impact on economic development. In this study, we employed the spatiotemporal analysis method to measure the spatial–temporal distribution of flash floods and examined the relationship between flash floods and driving factors in different subregions of landcover. Furthermore, we analyzed the response of flash floods on the economic development by sensitivity analysis. The results indicated that the number of flash floods occurring annually increased gradually from 1949 to 2015, and regions with a high quantity o

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Martinaitis, Steven M., Jonathan J. Gourley, Zachary L. Flamig, et al. "The HMT Multi-Radar Multi-Sensor Hydro Experiment." Bulletin of the American Meteorological Society 98, no. 2 (2017): 347–59. http://dx.doi.org/10.1175/bams-d-15-00283.1.

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Abstract There are numerous challenges with the forecasting and detection of flash floods, one of the deadliest weather phenomena in the United States. Statistical metrics of flash flood warnings over recent years depict a generally stagnant warning performance, while regional flash flood guidance utilized in warning operations was shown to have low skill scores. The Hydrometeorological Testbed—Hydrology (HMT-Hydro) experiment was created to allow operational forecasters to assess emerging products and techniques designed to improve the prediction and warning of flash flooding. Scientific goal

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Li, Hanze, Jie Zhang, Guohua Yu, et al. "Research on Regional Early Warning of Flash Flood Disasters in Small Watershed Based on Multi-source Early Warning Data Fusion." Advances in Computer and Engineering Technology Research 1, no. 2 (2024): 406. http://dx.doi.org/10.61935/acetr.2.1.2024.p406.

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The research on the early warning method of flash floods serves as an important groundwork for the prediction and early warning of flash flood disasters. Being restricted by various objective factors such as lack of data and complicated formation mechanism of flash flood disasters in small watersheds, accurate and targeted early warning has consistently been a weak link within the flash flood control system. In this regard, focusing on a series of problems, such as "short risk forecasting period", "frequent missing and false reports" and "poor early warning accuracy", this research explores a

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Alfieri, L., P. J. Smith, J. Thielen-del Pozo, and K. J. Beven. "A staggered approach to flash flood forecasting – case study in the Cévennes region." Advances in Geosciences 29 (February 25, 2011): 13–20. http://dx.doi.org/10.5194/adgeo-29-13-2011.

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Abstract. A staggered approach to flash flood forecasting is developed within the IMPRINTS project (FP7-ENV-2008-1-226555). Instead of a single solution system, a chain of different models and input data is being proposed that act in sequence and provide decision makers with information of increasing accuracy in localization and magnitude as the events approach. The first system in the chain is developed by adapting methodologies of the European Flood Alert System (EFAS) to forecast flash floods and has the potential to provide early indication for probability of flash floods at the European s

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Sharif, Hatim O., David Yates, Rita Roberts, and Cynthia Mueller. "The Use of an Automated Nowcasting System to Forecast Flash Floods in an Urban Watershed." Journal of Hydrometeorology 7, no. 1 (2006): 190–202. http://dx.doi.org/10.1175/jhm482.1.

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Abstract Flash flooding represents a significant hazard to human safety and a threat to property. Simulation and prediction of floods in complex urban settings requires high-resolution precipitation estimates and distributed hydrologic modeling. The need for reliable flash flood forecasting has increased in recent years, especially in urban communities, because of the high costs associated with flood occurrences. Several storm nowcast systems use radar to provide quantitative precipitation forecasts that can potentially afford great benefits to flood warning and short-term forecasting in urban

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Ren, Juanhui, Bo Ren, Qiuwen Zhang, and Xiuqing Zheng. "A Novel Hybrid Extreme Learning Machine Approach Improved by K Nearest Neighbor Method and Fireworks Algorithm for Flood Forecasting in Medium and Small Watershed of Loess Region." Water 11, no. 9 (2019): 1848. http://dx.doi.org/10.3390/w11091848.

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Sudden floods in the medium and small watershed by a sudden rainstorm and locally heavy rainfall often lead to flash floods. Therefore, it is of practical and theoretical significance to explore appropriate flood forecasting model for medium and small watersheds for flood control and disaster reduction in the loess region under the condition of underlying surface changes. This paper took the Gedong basin in the loess region of western Shanxi as the research area, analyzing the underlying surface and floods characteristics. The underlying surface change was divided into three periods (HSP1, HSP

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Broxton, Patrick, Peter A. Troch, Mike Schaffner, Carl Unkrich, and David Goodrich. "An All-Season Flash Flood Forecasting System for Real-Time Operations." Bulletin of the American Meteorological Society 95, no. 3 (2014): 399–407. http://dx.doi.org/10.1175/bams-d-12-00212.1.

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Flash floods can cause extensive damage to both life and property, especially because they are difficult to predict. Flash flood prediction requires high-resolution meteorological observations and predictions, as well as calibrated hydrological models, which should effectively simulate how a catchment filters rainfall inputs into streamflow. Furthermore, because of the requirement of both hydrological and meteorological components in flash flood forecasting systems, there must be extensive data handling capabilities built in to force the hydrological model with a variety of available hydromete

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Varlas, George, Anastasios Papadopoulos, George Papaioannou, Vassiliki Markogianni, Angelos Alamanos, and Elias Dimitriou. "Integrating Ensemble Weather Predictions in a Hydrologic-Hydraulic Modelling System for Fine-Resolution Flood Forecasting: The Case of Skala Bridge at Evrotas River, Greece." Atmosphere 15, no. 1 (2024): 120. http://dx.doi.org/10.3390/atmos15010120.

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Ensemble weather forecasting involves the integration of multiple simulations to improve the accuracy of predictions by introducing a probabilistic approach. It is difficult to accurately predict heavy rainfall events that cause flash floods and, thus, ensemble forecasting could be useful to reduce uncertainty in the forecast, thus improving emergency response. In this framework, this study presents the efforts to develop and assess a flash flood forecasting system that combines meteorological, hydrological, and hydraulic modeling, adopting an ensemble approach. The integration of ensemble wea

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Saharia, Manabendra, Pierre-Emmanuel Kirstetter, Humberto Vergara, Jonathan J. Gourley, Yang Hong, and Marine Giroud. "Mapping Flash Flood Severity in the United States." Journal of Hydrometeorology 18, no. 2 (2017): 397–411. http://dx.doi.org/10.1175/jhm-d-16-0082.1.

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Abstract Flash floods, a subset of floods, are a particularly damaging natural hazard worldwide because of their multidisciplinary nature, difficulty in forecasting, and fast onset that limits emergency responses. In this study, a new variable called “flashiness” is introduced as a measure of flood severity. This work utilizes a representative and long archive of flooding events spanning 78 years to map flash flood severity, as quantified by the flashiness variable. Flood severity is then modeled as a function of a large number of geomorphological and climatological variables, which is then us

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Sofia, Giulia, Qing Yang, Xinyi Shen, et al. "A Nationwide Flood Forecasting System for Saudi Arabia: Insights from the Jeddah 2022 Event." Water 16, no. 14 (2024): 1939. http://dx.doi.org/10.3390/w16141939.

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Saudi Arabia is threatened by recurrent flash floods caused by extreme precipitation events. To mitigate the risks associated with these natural disasters, we implemented an advanced nationwide flash flood forecast system, boosting disaster preparedness and response. A noteworthy feature of this system is its national-scale operational approach, providing comprehensive coverage across the entire country. Using cutting-edge technology, the setup incorporates a state-of-the-art, three-component system that couples an atmospheric model with hydrological and hydrodynamic models to enable the predi

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Darras, T., F. Raynaud, V. Borrell Estupina, et al. "Neural network modeling and geochemical water analyses to understand and forecast karst and non-karst part of flash floods (case study on the <i>Lez</i> river, Southern France)." Proceedings of the International Association of Hydrological Sciences 369 (June 11, 2015): 43–48. http://dx.doi.org/10.5194/piahs-369-43-2015.

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Abstract. Flash floods forecasting in the Mediterranean area is a major economic and societal issue. Specifically, considering karst basins, heterogeneous structure and nonlinear behaviour make the flash flood forecasting very difficult. In this context, this work proposes a methodology to estimate the contribution from karst and non-karst components using toolbox including neural networks and various hydrological methods. The chosen case study is the flash flooding of the Lez river, known for his complex behaviour and huge stakes, at the gauge station of Lavallette, upstream of Montpellier (4

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Ntelekos, Alexandros A., Konstantine P. Georgakakos, and Witold F. Krajewski. "On the Uncertainties of Flash Flood Guidance: Toward Probabilistic Forecasting of Flash Floods." Journal of Hydrometeorology 7, no. 5 (2006): 896–915. http://dx.doi.org/10.1175/jhm529.1.

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Abstract Quantifying uncertainty associated with flash flood warning or forecast systems is required to enable informed decision making by those responsible for operation and management of natural hazard protection systems. The current system used by the U.S. National Weather Service (NWS) to issue flash-flood warnings and watches over the Unites States is a purely deterministic system. The authors propose a simple approach to augment the Flash Flood Guidance System (FFGS) with uncertainty propagation components. The authors briefly discuss the main components of the system, propose changes to

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Chitwatkulsiri, Detchphol, and Hitoshi Miyamoto. "Real-Time Urban Flood Forecasting Systems for Southeast Asia—A Review of Present Modelling and Its Future Prospects." Water 15, no. 1 (2023): 178. http://dx.doi.org/10.3390/w15010178.

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Many urban areas in tropical Southeast Asia, e.g., Bangkok in Thailand, have recently been experiencing unprecedentedly intense flash floods due to climate change. The rapid flood inundation has caused extremely severe damage to urban residents and social infrastructures. In addition, urban Southeast Asia usually has inadequate capacities in drainage systems, complicated land use patterns, and a large vulnerable population in limited urban areas. To reduce the urban flood risk and enhance the resilience of vulnerable urban communities, it has been of essential importance to develop real-time u

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Zhang, Ruikang, Dedi Liu, Lihua Xiong, Jie Chen, Hua Chen, and Jiabo Yin. "Determining the threshold of issuing flash flood warnings based on people's response process simulation." Hydrology and Earth System Sciences 28, no. 23 (2024): 5229–47. https://doi.org/10.5194/hess-28-5229-2024.

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Abstract. The effectiveness of flash flood warnings depends on people's response processes to the warnings. And false warnings and missed events cause people's negative responses. It is crucial to find a way to determine the threshold of issuing the warnings that reduces the false-warning ratio (FWR) and the missed-event ratio (MER), especially for uncertain flash flood forecasting. However, most studies determine the warning threshold based on the natural processes of flash floods rather than the social processes of warning responses. Therefore, an agent-based model (ABM) was proposed to simu

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Zanchetta, Andre, and Paulin Coulibaly. "Recent Advances in Real-Time Pluvial Flash Flood Forecasting." Water 12, no. 2 (2020): 570. http://dx.doi.org/10.3390/w12020570.

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Recent years have witnessed considerable developments in multiple fields with the potential to enhance our capability of forecasting pluvial flash floods, one of the most costly environmental hazards in terms of both property damage and loss of life. This work provides a summary and description of recent advances related to insights on atmospheric conditions that precede extreme rainfall events, to the development of monitoring systems of relevant hydrometeorological parameters, and to the operational adoption of weather and hydrological models towards the prediction of flash floods. With the

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Chitwatkulsiri, Detchphol, Hitoshi Miyamoto, Kim Neil Irvine, Sitang Pilailar, and Ho Huu Loc. "Development and Application of a Real-Time Flood Forecasting System (RTFlood System) in a Tropical Urban Area: A Case Study of Ramkhamhaeng Polder, Bangkok, Thailand." Water 14, no. 10 (2022): 1641. http://dx.doi.org/10.3390/w14101641.

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In urban areas of Thailand, and especially in Bangkok, recent flash floods have caused severe damage and prompted a renewed focus to manage their impacts. The development of a real-time warning system could provide timely information to initiate flood management protocols, thereby reducing impacts. Therefore, we developed an innovative real-time flood forecasting system (RTFlood system) and applied it to the Ramkhamhaeng polder in Bangkok, which is particularly vulnerable to flash floods. The RTFlood system consists of three modules. The first module prepared rainfall input data for subsequent

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Hao, Sijia, Qiang Ma, Xiaoyan Zhai, et al. "A New Machine Learning Approach for parameter regionalization of Flash Flood Modelling in Henan Province, China." E3S Web of Conferences 300 (2021): 02010. http://dx.doi.org/10.1051/e3sconf/202130002010.

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China is one of the countries in the world that seriously affected by flash floods disasters. The flash flood caused by extreme rainfall occurred at mountainous small-sized watersheds in China often leads to serious economic damages and obstructs the social development. Setting up an efficient forecasting system for flash flood has been widely accepted as one of the key non-structural measures to improve the control and prevention capability of China. However, due to the data limitation, establishing forecast models in those flash flood areas is challenged by the lack of parameter references.

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Nguyen, Dinh Ty, and Shien-Tsung Chen. "Real-Time Probabilistic Flood Forecasting Using Multiple Machine Learning Methods." Water 12, no. 3 (2020): 787. http://dx.doi.org/10.3390/w12030787.

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Probabilistic flood forecasting, which provides uncertain information in the forecasting of floods, is practical and informative for implementing flood-mitigation countermeasures. This study adopted various machine learning methods, including support vector regression (SVR), a fuzzy inference model (FIM), and the k-nearest neighbors (k-NN) method, to establish a probabilistic forecasting model. The probabilistic forecasting method is a combination of a deterministic forecast produced using SVR and a probability distribution of forecast errors determined by the FIM and k-NN method. This study p

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Nadeem, Muhammad Umer, Zeeshan Waheed, Abdul Mannan Ghaffar, et al. "Application of HEC-HMS for flood forecasting in hazara catchment Pakistan, south Asia." International Journal of Hydrology 6, no. 1 (2022): 7–12. http://dx.doi.org/10.15406/ijh.2022.06.00296.

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Floods have become more severe and frequent as a result of climate change around the world, posing a hazard to public safety and economic development. This study investigates the use of distributed hydrological models in flash flood risk management in a small watershed in Hazara, Pakistan, with the goal of improving Pakistan's early warning lead time. First, the HEC-HMS model was built using geographic data and the river network's structure, then calibrated and verified using eight high rainfall events from 2013. demonstrating that the HEC-HMS model could simulate floods in the research area S

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Kobold, M., and M. Brilly. "The use of HBV model for flash flood forecasting." Natural Hazards and Earth System Sciences 6, no. 3 (2006): 407–17. http://dx.doi.org/10.5194/nhess-6-407-2006.

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Abstract. The standard conceptual HBV model was originally developed with daily data and is normally operated on daily time step. But many floods in Slovenia are usually flash floods as result of intense frontal precipitation combined with orographic enhancement. Peak discharges are maintained only for hours or even minutes. To use the HBV model for flash flood forecasting, the version of HBV-96 has been applied on the catchment with complex topography with the time step of one hour. The recording raingauges giving hourly values of precipitation have been taken in calibration of the model. The

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Wang, Xiekang, Philippe Goreville, and Changjun Liu. "Flash Floods: Forecasting, Monitoring and Mitigation Strategies." Water 15, no. 9 (2023): 1700. http://dx.doi.org/10.3390/w15091700.

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Acosta-Coll, Melisa, Francisco Ballester-Merelo, Marcos Martinez-Peiró, and Emiro De la Hoz-Franco. "Real-Time Early Warning System Design for Pluvial Flash Floods—A Review." Sensors 18, no. 7 (2018): 2255. http://dx.doi.org/10.3390/s18072255.

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Pluvial flash floods in urban areas are becoming increasingly frequent due to climate change and human actions, negatively impacting the life, work, production and infrastructure of a population. Pluvial flooding occurs when intense rainfall overflows the limits of urban drainage and water accumulation causes hazardous flash floods. Although flash floods are hard to predict given their rapid formation, Early Warning Systems (EWS) are used to minimize casualties. We performed a systematic review to define the basic structure of an EWS for rain flash floods. The structure of the review is as fol

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Šercl, Petr, Martin Pecha, Vojtěch Svoboda, and Tomáš Vlasák. "Flash Flood Indicator – operational experience." Meteorologické zprávy 76, no. 5 (2023): 138–47. http://dx.doi.org/10.59984/mz.2023.05.01.

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Flash floods are one of the most risky natural phenomena. It is very difficult to predict exactly where they will occur and they usually come very quickly. When there is a threat of flash floods, early warning is exactly what decides on the protection of the lives and property of inhabitants. For these reasons, a Flash Flood Indicator (FFI) has being developed in the Czech Hydrometeorological Institute (CHMI) for a long time, aiming to draw attention to the possibility of a flash flood or local flooding. The main purpose of this contribution is not to describe details of FFI algorithms, but to

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Li, Z., D. Yang, Y. Hong, Y. Qi, and Q. Cao. "Evaluation of radar-based precipitation estimates for flash flood forecasting in the Three Gorges Region." Proceedings of the International Association of Hydrological Sciences 368 (May 6, 2015): 89–95. http://dx.doi.org/10.5194/piahs-368-89-2015.

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Abstract. Spatial rainfall pattern plays a critical role in determining hydrological responses in mountainous areas, especially for natural disasters such as flash floods. In this study, to improve the skills of flood forecasting in the mountainous Three Gorges Region (TGR) of the Yangtze River, we developed a first version of a high-resolution (1 km) radar-based quantitative precipitation estimation (QPE) consideration of many critical procedures, such as beam blockage analysis, ground-clutter filter, rain type identification and adaptive Z–R relations. A physically-based distributed hydrolog

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Harats, N., B. Ziv, Y. Yair, V. Kotroni, and U. Dayan. "Lightning and rain dynamic indices as predictors for flash floods events in the Mediterranean." Advances in Geosciences 23 (March 29, 2010): 57–64. http://dx.doi.org/10.5194/adgeo-23-57-2010.

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Abstract. The FLASH EU funded project aims to observe, analyze and model lightning activity in thunderstorms for use in short term forecasting of flash floods in the Mediterranean region. Two new indices, aimed to assess the potential for heavy precipitation and flash-floods, are proposed and evaluated. The first is a lightning index – the MKI, which is a modified version of the KI-index. The applied index gives more weight to the lower- and mid-level relative humidity. The second is a new rain index, the RDI, which is the integrated product of specific humidity and vertical velocity. With the

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Le Bihan, Guillaume, Olivier Payrastre, Eric Gaume, David Moncoulon, and Frédéric Pons. "The challenge of forecasting impacts of flash floods: test of a simplified hydraulic approach and validation based on insurance claim data." Hydrology and Earth System Sciences 21, no. 11 (2017): 5911–28. http://dx.doi.org/10.5194/hess-21-5911-2017.

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Abstract. Up to now, flash flood monitoring and forecasting systems, based on rainfall radar measurements and distributed rainfall–runoff models, generally aimed at estimating flood magnitudes – typically discharges or return periods – at selected river cross sections. The approach presented here goes one step further by proposing an integrated forecasting chain for the direct assessment of flash flood possible impacts on inhabited areas (number of buildings at risk in the presented case studies). The proposed approach includes, in addition to a distributed rainfall–runoff model, an automatic

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Koutsovili, Eleni-Ioanna, Ourania Tzoraki, Nicolaos Theodossiou, and George E. Tsekouras. "Early Flood Monitoring and Forecasting System Using a Hybrid Machine Learning-Based Approach." ISPRS International Journal of Geo-Information 12, no. 11 (2023): 464. http://dx.doi.org/10.3390/ijgi12110464.

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The occurrence of flash floods in urban catchments within the Mediterranean climate zone has witnessed a substantial rise due to climate change, underscoring the urgent need for early-warning systems. This paper examines the implementation of an early flood monitoring and forecasting system (EMFS) to predict the critical overflow level of a small urban stream on Lesvos Island, Greece, which has a history of severe flash flood incidents requiring rapid response. The system is supported by a network of telemetric stations that measure meteorological and hydrometric parameters in real time, with

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Láng-Ritter, Josias, Marc Berenguer, Francesco Dottori, Milan Kalas, and Daniel Sempere-Torres. "Compound flood impact forecasting: integrating fluvial and flash flood impact assessments into a unified system." Hydrology and Earth System Sciences 26, no. 3 (2022): 689–709. http://dx.doi.org/10.5194/hess-26-689-2022.

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Abstract. Floods can arise from a variety of physical processes. Although numerous risk assessment approaches stress the importance of taking into account the possible combinations of flood types (i.e. compound floods), this awareness has so far not been reflected in the development of early warning systems: existing methods for forecasting flood hazards or the corresponding socio-economic impacts are generally designed for only one type of flooding. During compound flood events, these flood type-specific approaches are unable to identify overall hazards or impacts. Moreover, from the perspect

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Vincendon, B., V. Ducrocq, O. Nuissier, and B. Vié. "Perturbation of convection-permitting NWP forecasts for flash-flood ensemble forecasting." Natural Hazards and Earth System Sciences 11, no. 5 (2011): 1529–44. http://dx.doi.org/10.5194/nhess-11-1529-2011.

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Abstract. Mediterranean intense weather events often lead to devastating flash-floods. Extending the forecasting lead times further than the watershed response times, implies the use of numerical weather prediction (NWP) to drive hydrological models. However, the nature of the precipitating events and the temporal and spatial scales of the watershed response make them difficult to forecast, even using a high-resolution convection-permitting NWP deterministic forecasting. This study proposes a new method to sample the uncertainties of high-resolution NWP precipitation forecasts in order to quan

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Šaur, David, and Juan Carlos Beltrán-Prieto. "Algorithm of conversion of meteorological model parameters." MATEC Web of Conferences 292 (2019): 01032. http://dx.doi.org/10.1051/matecconf/201929201032.

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This article is focused on the forecasting severe storms with the Algorithm of Storm Prediction as a new forecasting tool for the prediction of the convective precipitation, severe storm phenomena and the risk of flash floods. The first chapter contains information about two applications on which basis are computed forecast ouptuts of this algorithm. Further, this chapter is also objected on more detailed descripition of the second application known as the Algorithm of conversion of meteorological model parameters . Predictive outputs generated by this algorithm are verified on 63 storm events

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Borrell Estupina, V., F. Raynaud, N. Bourgeois, et al. "Operational tools to help stakeholders to protect and alert municipalities facing uncertainties and changes in karst flash floods." Proceedings of the International Association of Hydrological Sciences 370 (June 11, 2015): 201–8. http://dx.doi.org/10.5194/piahs-370-201-2015.

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Abstract. Flash floods are often responsible for many deaths and involve many material damages. Regarding Mediterranean karst aquifers, the complexity of connections, between surface and groundwater, as well as weather non-stationarity patterns, increase difficulties in understanding the basins behaviour and thus warning and protecting people. Furthermore, given the recent changes in land use and extreme rainfall events, knowledge of the past floods is no longer sufficient to manage flood risks. Therefore the worst realistic flood that could occur should be considered. Physical and processes-b

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Rhein, Belinda, and Heidi Kreibich. "Causes of the exceptionally high number of fatalities in the Ahr valley, Germany, during the 2021 flood." Natural Hazards and Earth System Sciences 25, no. 2 (2025): 581–89. https://doi.org/10.5194/nhess-25-581-2025.

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Abstract. Over the last 40 years (1980–2020), 159 people died in inland floods in Germany. The flood of 2021 caused 190 flood fatalities in Germany, 134 of them in the Ahr valley. We investigate what made this event so deadly in order to help improve flood risk management and prevent future fatalities. A comprehensive analysis of the factors influencing the occurrence of fatalities is carried out on the basis of the death investigation files of the public prosecutor's office. This unprecedented flash flood was characterised by high water levels and high flow velocities. The extent of inundatio

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Janál, Petr, and Miloš Starý. "Fuzzy Model Used for the Prediction of a State of Emergency for a River Basin in the Case of a Flash Flood - PART 2." Journal of Hydrology and Hydromechanics 60, no. 3 (2012): 162–73. http://dx.doi.org/10.2478/v10098-012-0014-3.

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Fuzzy Model Used for the Prediction of a State of Emergency for a River Basin in the Case of a Flash Flood - PART 2This article is a continuation of a previous one named Fuzzy model use for prediction of the state of emergency of river basin in the case of flash flood (Janál&Starý, 2009), where the potential applications of fuzzy logic in the field of flash flood forecasting were described. Flash flood forecasting needs a specific approach because of the character of torrential rainfall. Storms are very difficult to forecast in space and time. The hydrological models designed for flash flo

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Bertin, Dominique, Anne Johannet, Nathalie Gaffet, and Frédéric Lenne. "Neural networks-based operational prototype for flash flood forecasting: application to Liane flash floods (France)." E3S Web of Conferences 7 (2016): 18025. http://dx.doi.org/10.1051/e3sconf/20160718025.

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Gourley, Jonathan J., Jessica M. Erlingis, Yang Hong, and Ernest B. Wells. "Evaluation of Tools Used for Monitoring and Forecasting Flash Floods in the United States." Weather and Forecasting 27, no. 1 (2012): 158–73. http://dx.doi.org/10.1175/waf-d-10-05043.1.

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Abstract This paper evaluates, for the first time, flash-flood guidance (FFG) values and recently developed gridded FFG (GFFG) used by the National Weather Service (NWS) to monitor and predict imminent flash flooding, which is the leading storm-related cause of death in the United States. It is envisioned that results from this study will be used 1) to establish benchmark performance of existing operational flash-flood prediction tools and 2) to provide information to NWS forecasters that reveals how the existing tools can be readily optimized. Sources used to evaluate the products include off

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