Fuzzy Model Used for the Prediction of a State of Emergency for a River Basin in the Case of a Flash Flood - PART 2

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 flood prediction have to be able to work with very uncertain input data. Moreover, the models have to be capable of evaluating the level of danger in as short a time as possible because of the highly dynamic character of the modeled process. The fuzzy model described in the previous article was modified into a form usable in operational hydrology and a simulation of its operational application was run using this model. The selected time period for the simulation was the summer of 2009, when numerous flash floods occurred in Czech Republic. The topic of this article is the preparation of the model for practical use and the results of the simulation of its operation.

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FUZZY LOGIC BASED FLASH FLOOD FORECAST

Proceedings of the XXVII Conference of the Danubian Countries on Hydrological Forecasting and Hydrological Bases of Water Management ◽

10.15407/uhmi.conference.01.10 ◽

2020 ◽

Author(s):

Petr Janál ◽

◽

Tomáš Kozel ◽

Keyword(s):

Fuzzy Logic ◽

Czech Republic ◽

Flash Flood ◽

Fuzzy Model ◽

Flood Forecasting ◽

Hydrological Models ◽

The Czech Republic ◽

Flood Model ◽

Flash Flood Forecasting

The flash flood forecasting remains one of the most difficult tasks in the operative hydrology worldwide. The torrential rainfalls bring high uncertainty included in both forecasted and measured part of the input rainfall data. The hydrological models must be capable to deal with such amount of uncertainty. The artificial intelligence methods work on the principles of adaptability and could represent a proper solution. The application of different methods, approaches, hydrological models and usage of various input data is necessary. The tool for real-time evaluation of the flash flood occurrence was assembled on the bases of the fuzzy logic. The model covers whole area of the Czech Republic and the nearest surroundings. The domain is divided into 3245 small catchments of the average size of 30 km2. Real flood episodes were used for the calibration and future flood events can be used for recalibration (principle of adaptability). The model consists of two fuzzy inference systems (FIS). The catchment predisposition for the flash flood occurrence is evaluated by the first FIS. The geomorphological characteristics and long-term meteorological statistics serve as the inputs. The second FIS evaluates real-time data. The inputs are: The predisposition for flash flood occurrence (gained from the first FIS), the rainfall intensity, the rainfall duration and the antecedent precipitation index. The meteorological radar measurement and the precipitation nowcasting serve as the precipitation data source. Various precipitation nowcasting methods are considered. The risk of the flash flood occurrence is evaluated for each small catchment every 5 or 10 minutes (the time step depends on the precipitation nowcasting method). The Fuzzy Flash Flood model is implemented in the Czech Hydrometeorological Institute (CHMI) – Brno Regional Office. The results are available for all forecasters at CHMI via web application for testing. The huge uncertainty inherent in the flash flood forecasting causes that fuzzy model outputs based on different nowcasting methods could vary significantly. The storms development is very dynamic and hydrological forecast could change a lot of every 5 minutes. That is why the fuzzy model estimates are intended to be used by experts only. The Fuzzy Flash Flood model is an alternative tool for the flash flood forecasting. It can provide the first hints of danger of flash flood occurrence within the whole territory of the Czech Republic. Its main advantage is very fast calculation and possibility of variant approach using various precipitation nowcasting inputs. However, the system produces large number of false alarms, therefore the long-term testing in operation is necessary and the warning releasing rules must be set.

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An All-Season Flash Flood Forecasting System for Real-Time Operations

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-12-00212.1 ◽

2014 ◽

Vol 95 (3) ◽

pp. 399-407 ◽

Cited By ~ 6

Author(s):

Patrick Broxton ◽

Peter A. Troch ◽

Mike Schaffner ◽

Carl Unkrich ◽

David Goodrich

Keyword(s):

High Resolution ◽

Real Time ◽

Overland Flow ◽

Flash Flood ◽

Flood Forecasting ◽

Flash Floods ◽

Hydrological Models ◽

Flood Prediction ◽

Infiltration Excess ◽

Flash Flood Forecasting

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 hydrometeorological data and predictions, as well as to test the model with hydrological observations. The authors have developed a working prototype of such a system, called KINEROS/hsB-SM, after the hydrological models that are used: the Kinematic Erosion and Runoff (KINEROS) and hillslope-storage Boussinesq Soil Moisture (hsB-SM) models. KINEROS is an event-based overland flow and channel routing model that is designed to simulate flash floods in semiarid regions where infiltration excess overland flow dominates, while hsB-SM is a continuous subsurface flow model, whose model physics are applicable in humid regions where saturation excess overland flow is most important. In addition, KINEROS/hsB-SM includes an energy balance snowmelt model, which gives it the ability to simulate flash floods that involve rain on snow. There are also extensive algorithms to incorporate high-resolution hydrometeorological data, including stage III radar data (5 min, 1° by 1 km), to assist in the calibration of the models, and to run the model in real time. The model is currently being used in an experimental fashion at the National Weather Service Binghamton, New York, Weather Forecast Office.

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Fuzzy model use for prediction of the state of emergency of river basin in the case of flash flood

Journal of Hydrology and Hydromechanics ◽

10.2478/v10098-009-0013-1 ◽

2009 ◽

Vol 57 (3) ◽

Cited By ~ 1

Author(s):

Petr Janál ◽

Miloš Starý

Keyword(s):

River Basin ◽

Flash Flood ◽

Fuzzy Model ◽

The State ◽

State Of Emergency

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An operational flash-flood forecasting chain applied to the test cases of the EU project HYDROPTIMET

Natural Hazards and Earth System Science ◽

10.5194/nhess-5-703-2005 ◽

2005 ◽

Vol 5 (5) ◽

pp. 703-710 ◽

Cited By ~ 11

Author(s):

A. C. Taramasso ◽

S. Gabellani ◽

A. Parodi

Keyword(s):

Flash Flood ◽

Flood Forecasting ◽

Limited Area ◽

Probabilistic Forecasting ◽

Flood Prediction ◽

Forecasting System ◽

Spatio Temporal ◽

Eu Project ◽

The Eu ◽

Flash Flood Forecasting

Abstract. The application of a flash-flood prediction chain, developed by CIMA, to some testcases for the Tanaro river basin in the framework of the EU project HYDROPTIMET is presented here. The components of the CIMA chain are: forecast rainfall depths, a stochastic downscaling procedure and a hydrological model. Different meteorological Limited Area Models (LAMs) provide the rainfall input to the hydrological component. The flash-flood prediction chain is run both in a deterministic and in a probabilistic configuration. The sensitivity of forecasting chain performances to different LAMs providing rainfall forecasts is discussed. The results of the application show how the probabilistic forecasting system can give, especially in the case of convective events, a valuable contribution in addressing the uncertainty at different spatio-temporal scales involved in the flash flood forecasting problem in small and medium basins with complex orography.

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