Relevant bibliographies by topics / Flash floods forecasting

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Flash floods forecasting'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Flash floods forecasting"

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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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Dissertations / Theses on the topic "Flash floods forecasting"

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Hatter, Elizabeth. "Using radar and hydrologic data to improve forecasts of flash floods in Missouri /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p1422929.

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Michaud, Jene Diane. "RAINFALL-RUNOFF MODELING OF FLASH FLOODS IN SEMI-ARID WATERSHEDS." Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ), 1992. http://hdl.handle.net/10150/614156.

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Flash floods caused by localized thunderstorms are a natural hazard of the semi -arid Southwest, and many communities have responded by installing ALERT flood forecasting systems. This study explored a rainfall- runoff modeling approach thought to be appropriate for forecasting in such watersheds. The kinematic model KINEROS was evaluated because it is a distributed model developed specifically for desert regions, and can be applied to basins without historic data. This study examined the accuracy of KINEROS under data constraints that are typical of semi -arid ALERT watersheds. The mo
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Artigue, Guillaume. "Prévision des crues éclair par réseaux de neurones : généralisation aux bassins non jaugés." Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20188/document.

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Dans les régions méditerranéennes françaises, des épisodes pluvieux diluviens se produisent régulièrement et provoquent des crues très rapides et volumineuses que l'on appelle crues éclair. Elles font fréquemment de nombreuses victimes et peuvent, sur un seul évènement, coûter plus d'un milliard d'euros. Face à cette problématique, les pouvoirs publics mettent en place des parades parmi lesquelles la prévision hydrologique tient une place essentielle.C'est dans ce contexte que le projet BVNE (Bassin Versant Numérique Expérimental) a été initié par le SCHAPI (Service Central d'Hydrométéorologie
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Zevin, Susan Faye 1949. "A probabilistic approach to flash flood forecasting." Diss., The University of Arizona, 1986. http://hdl.handle.net/10150/191119.

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A major area targeted for hydrometeorological forecast service improvements is in flash flood forecasting. Verification data show that general public service products of flash flood forecasts do not provide enough lead time in order for the public to make effective response. Sophisticated users of flash flood forecasts could use forecast probabilities of flash flooding in order to make decisions in preparation for the predicted event. To this end, a systematic probabilistic approach to flash flood forecasting is presented. The work first describes a deterministic system which serves as a conce
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Keefer, Timothy Orrin, and Timothy Orrin Keefer. "Likelihood development for a probabilistic flash flood forecasting model." Thesis, The University of Arizona, 1993. http://hdl.handle.net/10150/192077.

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An empirical method is developed for constructing likelihood functions required in a Bayesian probabilistic flash flood forecasting model using data on objective quantitative precipitation forecasts and their verification. Likelihoods based on categorical and probabilistic forecast information for several forecast periods, seasons, and locations are shown and compared. Data record length, forecast information type and magnitude, grid area, and discretized interval size are shown to affect probabilistic differentiation of amounts of potential rainfall. Use of these likelihoods in Bayes' Theorem
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Yatheendradas, Soni. "Flash Flood Forecasting for the Semi-Arid Southwestern United States." Diss., The University of Arizona, 2007. http://hdl.handle.net/10150/195244.

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Flash flooding in the semi-arid United States poses a significant danger to life and property. One effective way to mitigate flood risk is by implementing a rainfall-runoff model in a real-time forecast and warning system. This study investigated the feasibility of using the mechanistic, distributed semi-arid rainfall-runoff model KINEROS2 driven by high resolution radar rainfall input estimates obtained from the NEXRAD WSR-88D DHR reflectivity measurements in such a system. The original procedural paradigm-based KINEROS2 Fortran 77 code with space-time looping was recoded into an object-orien
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Brong, Brian S. "A study of flash flood potential in western Nevada and eastern California to enhance flash flood forecasting and awareness." abstract and full text PDF (free order & download UNR users only), 2005. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1433282.

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Terti, Galateia. "Forecasting of flash-flood human impacts integrating the social vulnerability dynamics." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAU004/document.

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Au XXIe siècle, la prévision de l'aléa hydrométéorologique et des impacts associés aux crues rapides demeurent un défi pour les prévisionnistes et les services de secours. Les mesures structurelles et / ou les avancées des systèmes de prévision hydrologique ne garantissent pas, à elles seules, la réduction des décès lors de ces phénomènes d'inondation rapide. La littérature souligne la nécessité d'intégrer d'autres facteurs, liés aux processus de vulnérabilité sociaux et comportementaux, afin de mieux prendre en compte les risques encourus par les populations lors de ces épisodes extrêmes. Cet
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Lincoln, W. Scott. "A modeling approach for operational flash flood forecasting for small-scale watersheds in central Iowa." [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1468110.

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Khajehei, Sepideh. "From Probabilistic Socio-Economic Vulnerability to an Integrated Framework for Flash Flood Prediction." PDXScholar, 2018. https://pdxscholar.library.pdx.edu/open_access_etds/4666.

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Flash flood is among the most hazardous natural disasters, and it can cause severe damages to the environment and human life. Flash floods are mainly caused by intense rainfall and due to their rapid onset (within six hours of rainfall), very limited opportunity can be left for effective response. Understanding the socio-economic characteristics involving natural hazards potential, vulnerability, and resilience is necessary to address the damages to economy and casualties from extreme natural hazards. The vulnerability to flash floods is dependent on both biophysical and socio-economic factors
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Books on the topic "Flash floods forecasting"

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Sene, Kevin. Flash Floods: Forecasting and Warning. Springer Netherlands, 2013.

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Sene, Kevin. Flash floods: Forecasting and warning. Springer, 2013.

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United States. National Weather Service, ed. Flash floods and floods--: The awesome power! : a preparedness guide. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, 1992.

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Fleming, Eric L. Characteristics of western region flash flood events in GOES imagery and conventional data. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1986.

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Scofield, Roderick A. The use of water vapor for detecting environments that lead to convectively produced heavy precipitation and flash floods. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 2000.

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Scofield, Roderick A. The use of water vapor for detecting environments that lead to convectively produced heavy precipitation and flash floods. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 2000.

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Scofield, Roderick A. The use of water vapor for detecting environments that lead to convectively produced heavy precipitation and flash floods. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 2000.

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Scofield, Roderick A. The use of water vapor for detecting environments that lead to convectively produced heavy precipitation and flash floods. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 2000.

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Specialty Conference on Delineation of Landslide, Flash Flood and Debris Flow Hazards in Utah (1984 Utah State University). Delineation of landslide, flash flood, and debris flow hazards in Utah: Proceedings of a specialty conference held at Utah State University, Logan, Utah, June 14-15, 1984. Utah State University, 1985.

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United States. Office of Hydrology, ed. Modernized areal flash flood guidance. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, Office of Hydrology, 1992.

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Book chapters on the topic "Flash floods forecasting"

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Sene, Kevin. "Rainfall Forecasting." In Flash Floods. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5164-4_4.

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Sene, Kevin. "Flood Forecasting." In Flash Floods. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5164-4_5.

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Boutaghane, Hamouda, Tayeb Boulmaiz, El Khansa Lameche, et al. "Flood Analysis and Mitigation Strategies in Algeria." In Natural Disaster Science and Mitigation Engineering: DPRI reports. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2904-4_3.

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AbstractFloods are frequent hazard in Algeria. They cause severe casualties, destroy infrastructures, and impair economies. In the past decades, Algeria experienced devastating floods. The dominant type of occurring floods are flash floods, which tend to be not well documented and studied in Algeria. This chapter presents a brief introduction to the flood phenomena within the Algerian climatic and management context, based on databases, scientific publications, and local technical reports. Existing studies about floods are reviewed. It also provides an analysis of the most disastrous floods th
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Pushpa Rani, M., Bashiru Aremu, and Xavier Fernando. "Forecasting Flash Floods with Optimized Adaptive Neuro-Fuzzy Inference System and Internet of Things." In Pervasive Computing and Social Networking. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2840-6_3.

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Borga, Marco. "Forecasting, Early Warning and Event Management: Non-structural Protection Measures for Flash Floods and Debris Flows." In Advances in Global Change Research. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4336-6_27.

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Kong A Siou, L., A. Johannet, S. Pistre, and V. Borrell. "Flash Floods Forecasting in a Karstic Basin Using Neural Networks: the Case of the Lez Basin (South of France)." In Advances in Research in Karst Media. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12486-0_33.

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Alfieri, Lorenzo, Marc Berenguer, Valentin Knechtl, Katharina Liechti, Daniel Sempere-Torres, and Massimiliano Zappa. "Flash Flood Forecasting Based on Rainfall Thresholds." In Handbook of Hydrometeorological Ensemble Forecasting. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-40457-3_49-1.

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Alfieri, Lorenzo, Marc Berenguer, Valentin Knechtl, Katharina Liechti, Daniel Sempere-Torres, and Massimiliano Zappa. "Flash Flood Forecasting Based on Rainfall Thresholds." In Handbook of Hydrometeorological Ensemble Forecasting. Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-642-39925-1_49.

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Brahm Parkash Yadav, A., B. S. K. Asok Raja, C. Rahul Saxena, et al. "Recent Advances in Pluvial Flash Flood Forecasting of India." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0304-5_44.

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Březková, Lucie, Milan Šálek, Petr Novák, Hana Kyznarová, and Martin Jonov. "New Methods of Flash Flood Forecasting in the Czech Republic." In IFIP Advances in Information and Communication Technology. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22285-6_59.

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Conference papers on the topic "Flash floods forecasting"

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Yordanova, Anna, Irena Ilcheva, Elen� Bojilov�, �lga Nitcheva, and Yordan Dimitrov. "ARMA MODELS APPLICATION FOR FORECASTING OF THE RIVER DISCHARGE AND THE HYDROLOGICAL DROUGHT INDEX SRI IN DAMS MANAGEMENT." In 24th SGEM International Multidisciplinary Scientific GeoConference 2024. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024/3.1/s12.04.

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Reproducing the hydrological process of river runoff is a fundamental part of water resources planning and management. Finding a mathematical model to reproduce the runoff time series aims not only to extract maximum information from the limited available data, but also to extrapolate into the future by representatively generating the historical runoff process. Almost all management decisions are based on forecasts. Our present is characterized by the increasingly frequent occurrence of hydrometeorological processes that lead to flash floods and critical droughts. The river runoff, as the main
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Yordanova, Valeriya, Silviya Stoyanova, Snezhanka Balabanova, Georgy Koshinchanov, and Vesela Stoyanova. "FLASH FLOOD FORECASTING USING FLASH FLOOD GUIDANCE SYSTEM PRODUCTS." In 22nd SGEM International Multidisciplinary Scientific GeoConference 2022. STEF92 Technology, 2022. http://dx.doi.org/10.5593/sgem2022/3.1/s12.11.

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Flash floods are defined as rapidly developing extreme events caused by heavy or excessive amounts of rainfall. Flash floods usually occur over a relatively small area within six hours or less of the extreme event with quite a rapid streamflow rise and fall. Increased occurrence of flash flood events is expected due to climate change and increase in extreme precipitation events [1]. Flash flood forecasting is still a challenge for hydrologists and water professionals due to the complex nature of the event itself. Besides having sufficient background in hydrological and meteorological forecasti
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Stoyanova, Vesela, Georgy Koshinchanov, and Silviya Stoyanova. "COMPARISON OF NATIONAL, EUROPEAN AND BLACK SEA REGION FLASH FLOOD FORECASTING PRODUCTS FOR THE TERRITORY OF BULGARIA." In 23rd SGEM International Multidisciplinary Scientific GeoConference 2023. STEF92 Technology, 2023. http://dx.doi.org/10.5593/sgem2023/3.1/s12.07.

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Flash floods occur in small areas and in a short time after an extreme precipitation event - generally less than six hours. The intensity of the precipitation, the location and distribution of the precipitation, the land use and topography, soil type, etc. determine just how quickly Flash Flooding can occur. These types of floods are extremely dangerous and it is very important to pay special attention to their forecasting. Due to the complex nature of flash floods, in addition to the qualification and experience of the hydrologist involved in forecasting this type of extreme event, it is impo
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BÎLBÎE, Florin, and Liliana ZAHARIA. "Flash Flood Forecasting Using Machine Learning Models: A Scientometric Analysis." In Air and Water – Components of the Environment 2024 Conference Proceedings. Casa Cărţii de Ştiinţă, 2024. http://dx.doi.org/10.24193/awc2024_01.

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Hydro-meteorological hazards are a major issue in many regions of the world, including Romania. Among these, flash floods are the most frequent phenomena, generating significant annual socio-economic and environmental damages. In recent years, flash flood forecasting using machine learning algorithms has become an useful tool for data-based hydrologic modeling. Machine learning allows to create mathematical relationships between the river discharge and other climatic and physico-geographic parameters from the training dataset. This paper aims to perform a scientometric analysis using open-sour
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Ogale, Suraj, and Sanjay Srivastava. "Modelling and short term forecasting of flash floods in an urban environment." In 2019 National Conference on Communications (NCC). IEEE, 2019. http://dx.doi.org/10.1109/ncc.2019.8732193.

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Izyan 'Izzati Abdul Rahman and Nik Mohd Asrol Alias. "Rainfall forecasting using an artificial neural network model to prevent flash floods." In 2011 High Capacity Optical Networks and Enabling Technologies (HONET). IEEE, 2011. http://dx.doi.org/10.1109/honet.2011.6149841.

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Sumi*, Tetsuya, Sameh Kantoush, and Mohammed Saber. "Integrated management of Wadi Flash Floods in arid environment: Forecasting, mitigating, and water harvesting." In Fifth International Conference on Engineering Geophysics (ICEG), 21–24 October 2019, Al Ain, UAE. Society of Exploration Geophysicists, 2020. http://dx.doi.org/10.1190/iceg2019-024.1.

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LEE, SUK HO, DONG HO KANG, KYUNG SU CHU, and BYUNG SIK KIM. "STUDY OF THE INUNDATION ANALYSIS OF FLASH FLOODS IN URBAN AREAS FOR RAINFALL IMPACT FORECASTING." In DISASTER MANAGEMENT 2019. WIT Press, 2019. http://dx.doi.org/10.2495/dman190141.

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Smith, P. J., and K. J. Beven. "Forecasting river levels during flash floods using data based mechanistic models, online data assimilation and metrological forecasts." In BHS 3rd International Conference. British Hydrological Society, 2010. http://dx.doi.org/10.7558/bhs.2010.ic82.

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Artigue, G., A. Johannet, V. Borrell, and S. Pistre. "Flash floods forecasting without rainfalls forecasts by recurrent neural networks. Case study on the Mialet basin (Southern France)." In 2011 Third World Congress on Nature and Biologically Inspired Computing (NaBIC). IEEE, 2011. http://dx.doi.org/10.1109/nabic.2011.6089612.

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Reports on the topic "Flash floods forecasting"

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Hugeback, Kyle. A Comparison of HREF and HRRRE Predictions for Ensemble Flash Flood Forecasting. Iowa State University, 2018. http://dx.doi.org/10.31274/cc-20240624-24.

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Provision of Flood Forecasting, Flash Flood Guidance, Dry Season Monitoring and Dissemination of Information and Warning and Alert Services. Mekong River Commission Secretariat, 2020. http://dx.doi.org/10.52107/mrc.ajg4si.

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