Use of radar rainfall estimates and forecasts to prevent flash flood in real time by using a road inundation warning system

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).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 &#160;show the main advantages and some of the limitations of the system.

Download Full-text

Flood Forecasting and Warning System Structures: Procedure and Application to a Small Urban Stream in South Korea

Water ◽

10.3390/w11081571 ◽

2019 ◽

Vol 11 (8) ◽

pp. 1571 ◽

Cited By ~ 4

Author(s):

Song ◽

Park ◽

Lee ◽

Park ◽

Song

Keyword(s):

Decision Making ◽

Water Level ◽

Real Time ◽

Lead Time ◽

Flash Flood ◽

Warning System ◽

Flood Forecasting ◽

Urban Stream ◽

Forecasting And Warning ◽

Flood Warnings

The runoff from heavy rainfall reaches urban streams quickly, causing them to rise rapidly. It is therefore of great importance to provide sufficient lead time for evacuation planning and decision making. An efficient flood forecasting and warning method is crucial for ensuring adequate lead time. With this objective, this paper proposes an analysis method for a flood forecasting and warning system, and establishes the criteria for issuing urban-stream flash flood warnings based on the amount of rainfall to allow sufficient lead time. The proposed methodology is a nonstructural approach to flood prediction and risk reduction. It considers water level fluctuations during a rainfall event and estimates the upstream (alert point) and downstream (confluence) water levels for water level analysis based on the rainfall intensity and duration. We also investigate the rainfall/runoff and flow rate/water level relationships using the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) and the HEC’s River Analysis System (HEC-RAS) models, respectively, and estimate the rainfall threshold for issuing flash flood warnings depending on the backwater state based on actual watershed conditions. We present a methodology for issuing flash flood warnings at a critical point by considering the effects of fluctuations in various backwater conditions in real time, which will provide practical support for decision making by disaster protection workers. The results are compared with real-time water level observations of the Dorim Stream. Finally, we verify the validity of the flash flood warning criteria by comparing the predicted values with the observed values and performing validity analysis.

Download Full-text

Flash Flood Warning Sub-Systems for Rural Africa

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i3.32.18389 ◽

2018 ◽

Vol 7 (3.32) ◽

pp. 47

Author(s):

Stella N. Mbau ◽

Vinesh Thiruchelvam

Keyword(s):

Real Time ◽

Flash Flood ◽

Warning System ◽

Significant Variable ◽

Moderator Variable ◽

Flood Warning ◽

Moderated Mediation Model ◽

Rural Africa ◽

Power Application ◽

Early Warnings

This paper aims to present the need for sub-systems in rural Africa for real-time warning delivery. It has been reported in previous studies, that Sub-Sahara Africa lacks weather radars. This means that there are no real-time early warnings presenting a gap in knowledge that this study aims to address. This is done through the following objective; to examine the relationship between variables in the study and therefore, establish whether sub-systems are a significant variable in flash flood warning systems for rural Africa. The variables to be examined are; the independent variable (existing warning system), the dependent variable (early warnings), the moderator variable (ancillary elements) and the mediator variable (sub-systems). This is investigated through a closed-ended questionnaire that is administered to a sample of meteorologists whose email addresses are available on the World Meteorological Organization’s expert database. The target sample is determined through the G*Power application. The data is analyzed on SPSS. Variables in the study are found to be correlated after conducting a Pearson’s correlation test. Using PROCESS allows for the testing of various models where moderation is confirmed. A moderated mediation model is also confirmed. The results confirm that sub-systems are significant enough to be developed for rural Africa.

Download Full-text

Development and Testing of a Low-cost Water Level Sensor and a Mobile based Real-time Flood Warning System for the Flash Flood Prone North Eastern part of Bangladesh

International Journal of Sensors Wireless Communications and Control ◽

10.2174/2210327910999200614000455 ◽

2020 ◽

Vol 10 ◽

Author(s):

Nova Ahmed ◽

Md. Sirajul Islam ◽

Sifat Kalam ◽

Farzana Islam ◽

Nabila Chowdhury ◽

...

Keyword(s):

Water Level ◽

Real Time ◽

Flash Flood ◽

Low Cost ◽

Warning System ◽

Outdoor Environment ◽

Flood Warning ◽

North Eastern ◽

Flood Warning System ◽

North Eastern Part

Background: The North-Eastern part of Bangladesh is suffering from flash flood very frequently, causing colossal damage to life and properties, especially the vast croplands. A distributed sensing system can monitor the water level on a continuous basis to warn people near the riverbank beforehand and reduce the damage largely. However, the required communication infrastructure is not available in most of the remote rural areas in a developing country like Bangladesh. Objective: This study intends to develop a low-cost sensor based warning system, customizing to the Bangladesh context. Method: The system utilizes a low-cost ultrasound based sensor device, a lightweight mobile phone based server, low-cost IoT sensing nodes, and a central server for continuous monitoring of river stage data along with the provision of storage and long-term data analytics. Results: A flash flood warning system developed afterward with the sensors, mobile-based server, and appropriate webbased interfaces. The device was tested for some environmental conditions in the lab and deployed it later in the outdoor conditions for short-term periods. Conclusion: Overall, the warning system performed well in the lab as well as the outdoor environment, with the ability to detect water level at reasonable accuracy and transmit data to the server in real time. Some minor shortcomings still noted with the scope for improvements, which are in the way to improve further.

Download Full-text

A climatological approach for operational radar rainfall bias correction

10.5194/egusphere-egu21-6127 ◽

2021 ◽

Author(s):

Ruben Imhoff ◽

Claudia Brauer ◽

Klaas-Jan van Heeringen ◽

Hidde Leijnse ◽

Aart Overeem ◽

...

Keyword(s):

The Netherlands ◽

Real Time ◽

Grid Cell ◽

Rain Gauge ◽

Bias Reduction ◽

Training Dataset ◽

Correction Factors ◽

Spatial And Temporal Patterns ◽

Radar Rainfall ◽

Rainfall Estimates

Most radar quantitative precipitation estimation (QPE) products systematically deviate from the true rainfall amount. This makes radar QPE adjustments unavoidable for operational use in hydro-meteorological (forecasting) models. Most correction methods require a timely available, high-density network of quality-controlled rain gauge observations. Here, we introduce a set of fixed bias reduction factors for the Netherlands, which vary per grid cell and day of the year. With this approach, we aim to provide an alternative to current practice, because the climatological factors are both operationally available and independent of the real-time rain gauge availability.The correction factors were based on 10 years of 5-min radar QPE and reference rainfall data. We tested this method on the resulting rainfall estimates and subsequent discharge simulations for twelve Dutch catchment and polder areas. In addition, we compared the results to the operational mean field bias (MFB) corrected rainfall estimates and a reference dataset. This reference consisted of the radar QPE, spatially adjusted with a network of 356 validated rain gauge observations. Of this network, only 31 are automatic gauges. Hence, only these were available in real-time for the operational MFB corrections.The climatological correction factors show clear spatial and temporal patterns. The factors are higher far from the radars and higher during winter than in summer. The latter pattern is likely a result of sampling above the melting layer during the months December&#8211;March, which causes higher underestimations. Estimated yearly rainfall sums are generally comparable to the reference and outperform the MFB corrected rainfall estimates for catchments far from the radars (south and east of the country). This difference is absent for catchments closer to the radars, where both products tend to marginally overestimate the rainfall sums. The differences amplify when both QPE products are used to force the hydrologic models. Discharge simulations based on the proposed QPE product outperform the MFB corrected rainfall estimates for all but one basin. Moreover, the climatological factor derivation shows little sensitivity to the moving window length and to leaving individual years out of the training dataset. The presented method provides a robust and straightforward operational alternative. It can serve as a benchmark for further QPE algorithm development in the Netherlands and elsewhere.

Download Full-text

Use of Radar Quantitative Precipitation Estimates (QPEs) for Improved Hydrological Model Calibration and Flood Forecasting

Journal of Hydrometeorology ◽

10.1175/jhm-d-20-0267.1 ◽

2021 ◽

Author(s):

Dayal Wijayarathne ◽

Paulin Coulibaly ◽

Sudesh Boodoo ◽

David Sills

Keyword(s):

Real Time ◽

Model Calibration ◽

Hydrological Model ◽

Flood Forecasting ◽

Hydrological Models ◽

Radar Rainfall ◽

Precipitation Estimates ◽

Quantitative Precipitation Estimates ◽

Streamflow Simulation ◽

Rainfall Estimates

AbstractFlood forecasting is essential to minimize the impacts and costs of floods, especially in urbanized watersheds. Radar rainfall estimates are becoming increasingly popular in flood forecasting because they provide the much-needed real-time spatially distributed precipitation information. The current study evaluates the use of radar Quantitative Precipitation Estimates (QPEs) in hydrological model calibration for streamflow simulation and flood mapping in an urban setting. Firstly, S-band and C-band radar QPEs were integrated into event-based hydrological models to improve the calibration of model parameters. Then, rain gauge and radar precipitation estimates’ performances were compared for hydrological modeling in an urban watershed to assess radar QPE's effects on streamflow simulation accuracy. Finally, flood extent maps were produced using coupled hydrological-hydraulic models integrated within the Hydrologic Engineering Center- Real-Time Simulation (HEC-RTS) framework. It is shown that the bias correction of radar QPEs can enhance the hydrological model calibration. The radar-gauge merging obtained a KGE, MPFC, NSE, and VE improvement of about + 0.42, + 0.12, + 0.78, and − 0.23, respectively for S-band and + 0.64, + 0.36, + 1.12, and − 0.34, respectively for C-band radar QPEs. Merged radar QPEs are also helpful in running hydrological models calibrated using gauge data. The HEC-RTS framework can be used to produce flood forecast maps using the bias-corrected radar QPEs. Therefore, radar rainfall estimates could be efficiently used to forecast floods in urbanized areas for effective flood management and mitigation. Canadian flood forecasting systems could be efficiently updated by integrating bias-corrected radar QPEs to simulate streamflow and produce flood inundation maps.

Download Full-text

CLIMATOLOGICAL CALIBRATION OF Z-R RELATIONSHIP FOR PAHANG RIVER BASIN

Jurnal Teknologi ◽

10.11113/jt.v81.12566 ◽

2019 ◽

Vol 81 (4) ◽

Author(s):

Wardah Tahir ◽

Wan Hazdy Azad ◽

Nurul Husaif ◽

Sazali Osman ◽

Zaidah Ibrahim ◽

...

Keyword(s):

River Basin ◽

Disaster Preparedness ◽

Warning System ◽

Weather Radar ◽

Optimization Method ◽

Peninsular Malaysia ◽

Radar Rainfall ◽

Hourly Rainfall ◽

Reflectivity Data ◽

Rainfall Estimates

Flood disaster due to prolonged heavy rainfall had caused millions ringgit of property losses, infrastructure damages and numerous deaths in the east coast region of Peninsular Malaysia. One of the efforts taken to improve disaster preparedness in this region is by enhancing the flood forecasting and warning system (FFWS) using rainfall input from weather radar. Weather radar has the advantage of its ability to provide good spatial and temporal resolution of rainfall estimates but comes with inherent associated errors. In this study, the radar rainfall estimates were improved by climatological calibration of reflectivity-rain (Z-R) relationships for Pahang river basin. The reflectivity data for period of one year from Kuantan radar station and the hourly rainfall depths at 67 rainfall stations located in the basin for the same periods were used. Correlation analysis between radar and gauged rainfall indicates that the further the distance from the radar, the weaker the R2 coefficient value. Two Z-R equations were derived using optimization method for distance (1) 0-100 km and (2) above 100 km from Kuantan radar. The results in the form of Z = 24R1.7 and Z =5R1.6 represents the average relationship for Kuantan radar for distance (1) and (2). The radar rainfall estimates using the newly derived climatological Z-R equations enhanced the FFWS for Pahang river basin.

Download Full-text

Difficulties with Correcting Radar Rainfall Estimates Based on Rain Gauge Data: A Case Study of Severe Weather in Montana on 16–17 June 2007

Weather and Forecasting ◽

10.1175/2009waf2222154.1 ◽

2009 ◽

Vol 24 (5) ◽

pp. 1334-1344 ◽

Cited By ~ 9

Author(s):

Steven V. Vasiloff ◽

Kenneth W. Howard ◽

Jian Zhang

Keyword(s):

Quality Control ◽

Real Time ◽

Flash Flood ◽

Rain Gauge ◽

Data Quality Control ◽

Radar Rainfall ◽

Rain Gauge Data ◽

Gauge Data ◽

Precipitation Estimates ◽

Radar Calibration

Abstract The principal source of information for operational flash flood monitoring and warning issuance is weather radar–based quantitative estimates of precipitation. Rain gauges are considered truth for the purposes of validating and calibrating real-time radar-derived precipitation data, both in a real-time sense and climatologically. This paper examines various uncertainties and challenges involved with using radar and rain gauge data in a severe local storm environment. A series of severe thunderstorm systems that occurred across northeastern Montana illustrates various problems with comparing radar precipitation estimates and real-time gauge data, including extreme wind effects, hail, missing gauge data, and radar quality control. Ten radar–gauge time series pairs were analyzed with most found to be not useful for real-time radar calibration. These issues must be carefully considered within the context of ongoing efforts to develop robust real-time tools for evaluating radar–gauge uncertainties. Recommendations are made for radar and gauge data quality control efforts that would benefit the operational use of gauge data.

Download Full-text

Flash Flood Early Warning System in Colima, Mexico

Sensors ◽

10.3390/s20185231 ◽

2020 ◽

Vol 20 (18) ◽

pp. 5231

Author(s):

José Ibarreche ◽

Raúl Aquino ◽

R. M. Edwards ◽

Víctor Rangel ◽

Ismael Pérez ◽

...

Keyword(s):

Real Time ◽

Early Warning ◽

Early Warning System ◽

Flash Flood ◽

Warning System ◽

Social Consequences ◽

Long Term Effects ◽

Government Officials ◽

Flood Prediction ◽

Monitoring Stations

This paper presents a system of sensors used in flash flood prediction that offers critical real-time information used to provide early warnings that can provide the minutes needed for persons to evacuate before imminent events. Flooding is one of the most serious natural disasters humans confront in terms of loss of life and results in long-term effects, which often have severely adverse social consequences. However, flash floods are potentially more dangerous to life because there is often little or no forewarning of the impending disaster. The Emergency Water Information Network (EWIN) offers a solution that integrates an early warning system, notifications, and real-time monitoring of flash flood risks. The platform has been implemented in Colima, Mexico covering the Colima and Villa de Alvarez metropolitan area. This platform consists of eight fixed riverside hydrological monitoring stations, eight meteorological stations, nomadic mobile monitoring stations called “drifters” used in the flow, and a sniffer with data muling capability. The results show that this platform effectively compiles and forwards information to decision-makers, government officials, and the general public, potentially providing valuable minutes for people to evacuate dangerous areas.

Download Full-text

Early Warning of Impending Flash Flood Based on AIoT

10.21203/rs.3.rs-850371/v1 ◽

2021 ◽

Author(s):

Wen-Tsai Sung ◽

Ihzany Vilia Devi ◽

Sung-Jung Hsiao

Keyword(s):

Natural Disasters ◽

Real Time ◽

Early Warning ◽

Urban Areas ◽

Flash Flood ◽

Warning System ◽

Observation System ◽

Mountainous Areas ◽

Hiking Trails ◽

Flood Detection

Abstract According to data from the Earth's Volcano and Geological Disaster Reduction Center, a country like Indonesia has experienced many natural disasters, one of which is flooding. Floods are an annual natural disaster, especially on mountain slopes. Mountainous areas experience more dangerous than floods than the urban areas because they can cause other natural disasters, such as landslides and damage the hiking trails. The steep and winding roads minimize and limit the number of officers working in the mountains. Therefore, flood detection and monitoring equipment is needed. The proposed system based on AIoT technology provides real-time flood analysis so that the authorities can monitor residents around mountainous areas and provide early warning. This research focuses on the flood observation system as an early warning system to effectively monitor the flood-prone mountain slopes in real time while taking into account the cost, time efficiency, and safety measurement. The proposed system design includes the integration of sensors into the microcontroller, and the communication between the posts using LoRa and SIM900 sends data to the cloud server via the Internet. All sensor readings for each post are displayed on the app, and alerts are sent via SMS and the app.

Download Full-text