Flood Early Warning System Research Articles

Understanding the Barriers Restraining Effective Operation of Flood Early Warning Systems

Over the years, a variety of structural and non-structural measures have been employed by the human societies to counter the growing frequency and intensity of natural disasters. Among the various measures, Early Warning Systems (EWSs) have globally been acknowledged as one of the key non-structural measures for disaster mitigation and preparedness, especially due to their multi-faceted benefits. However, their effective operation during rapid-onset disasters like floods is often disrupted pertaining to a variety of reasons. These manifold reasons have today become critical barriers which restrain the smooth functioning of EWSs. This paper theorizes that the numerous barriers restraining the effective operation of EWSs can primarily be categorized into Knowledge, Technology and Institutional aspects. To support this argument, the study presents an overview of three selected examples of flood disasters in Cameron Highlands (Malaysia), North Kyushu (Japan) and Sri Lanka. Based on published literature, the study lists out key reasons that affected the timely functioning of Flood-EWSs in all the selected cases and explains them in relation to the three theorized categories of barriers. In view of the current limited understanding, this study provides a new perspective for understanding the barriers in EWSs and correspondingly enhancing their operation during disaster situations.

Building an Intelligent Hydroinformatics Integration Platform for Regional Flood Inundation Warning Systems

Flood disasters have had a great impact on city development. Early flood warning systems (EFWS) are promising countermeasures against flood hazards and losses. Machine learning (ML) is the kernel for building a satisfactory EFWS. This paper first summarizes the ML methods proposed in this special issue for flood forecasts and their significant advantages. Then, it develops an intelligent hydroinformatics integration platform (IHIP) to derive a user-friendly web interface system through the state-of-the-art machine learning, visualization and system developing techniques for improving online forecast capability and flood risk management. The holistic framework of the IHIP includes five layers (data access, data integration, servicer, functional subsystem, and end-user application) and one database for effectively dealing with flood disasters. The IHIP provides real-time flood-related data, such as rainfall and multi-step-ahead regional flood inundation maps. The interface of Google Maps fused into the IHIP significantly removes the obstacles for users to access this system, helps communities in making better-informed decisions about the occurrence of floods, and alerts communities in advance. The IHIP has been implemented in the Tainan City of Taiwan as the study case. The modular design and adaptive structure of the IHIP could be applied with similar efforts to other cities of interest for assisting the authorities in flood risk management.

Assessment on Regional Flood Risk Trend in Northern Region of Malaysia: Case Study in Muda River Basin, Kedah

Flood is a major issue during monsoon season in Northern region of Malaysia especially in Muda River Basin. This study focused on the specific hydrology parameters that lead to the flood events in Muda River Basin, Kedah. There were 4 hydrologic parameters for thirty years of collected data from selected hydrology monitoring stations provided by Department of Irrigations and Drainage, Malaysia. The study applied Principal Component Analysis (PCA) and result shown that stream flow and suspended solid stand with highest correlation of coefficient variables with the changes of water level in the study area. Statistical Process Control (SPC) applied in this study was to determine the control limit for every selected parameter obtained from PCA. The Upper Control Limit value for water level reported from SPC analysis in the study area was 7.568m and starting from this level and above, the risk of flood is high to occur in the study area. This research proved that the flood risk model created in this study was accurate and flexible for flood early warning system at Muda River Basin.

A Flash Flood Early Warning System for Rural Kenya: A Pilot Study

The cost of climate change has increased phenomenally in recent years. Therefore, understanding climate change and its impacts, that are likely to get worse and worse into the future, gives us the ability to predict scenarios and plan for them. Flash floods, which are a common result of climate change, follow increased precipitation which then increases risk and associated vulnerability due to the unpredictable rainfall patterns. Developing countries suffer grave consequences in the event that weather disasters strike because they have the least adaptive capacity. At the equator where the hot days are hotter and winds carrying rainfall move faster, Kenya’s Tana River County is noted for its vulnerability towards flash floods. Additionally, this county and others that are classified as rural areas in Kenya do not receive short term early warnings for floods. This county was therefore selected as the study area for its vulnerability. The aim of the study is therefore to propose a flash flood early warning system framework that delivers short term early warnings. Using questionnaires, information about the existing warning system will be collected and analyzed using SPSS. The results will be used to interpret the relationships between variables of the study, with a particular interest in the moderation effect in order to confirm that the existing system can be modified; that is, if the moderation effect is confirmed.

A Flash Flood Early Warning System for Rural Kenya: A Pilot Study

The cost of climate change has increased phenomenally in recent years. Therefore, understanding climate change and its impacts, that are likely to get worse and worse into the future, gives us the ability to predict scenarios and plan for them. Flash floods, which are a common result of climate change, follow increased precipitation which then increases risk and associated vulnerability due to the unpredictable rainfall patterns. Developing countries suffer grave consequences in the event that weather disasters strike because they have the least adaptive capacity. At the equator where the hot days are hotter and winds carrying rainfall move faster, Kenya’s Tana River County is noted for its vulnerability towards flash floods. Additionally, this county and others that are classified as rural areas in Kenya do not receive short term early warnings for floods. This county was therefore selected as the study area for its vulnerability. The aim of the study is therefore to propose a flash flood early warning system framework that delivers short term early warnings. Using questionnaires, information about the existing warning system will be collected and analyzed using SPSS. The results will be used to interpret the relationships between variables of the study, with a particular interest in the moderation effect in order to confirm that the existing system can be modified; that is, if the moderation effect is confirmed.

A Support Vector Machine Forecasting Model for Typhoon Flood Inundation Mapping and Early Flood Warning Systems

Accurate real-time forecasts of inundation depth and extent during typhoon flooding are crucial to disaster emergency response. To manage disaster risk, the development of a flood inundation forecasting model has been recognized as essential. In this paper, a forecasting model by integrating a hydrodynamic model, k-means clustering algorithm and support vector machines (SVM) is proposed. The task of this study is divided into four parts. First, the SOBEK model is used in simulating inundation hydrodynamics. Second, the k-means clustering algorithm classifies flood inundation data and identifies the dominant clusters of flood gauging stations. Third, SVM yields water level forecasts with 1–3 h lead time. Finally, a spatial expansion module produces flood inundation maps, based on forecasted information from flood gauging stations and consideration of flood causative factors. To demonstrate the effectiveness of the proposed forecasting model, we present an application to the Yilan River basin, Taiwan. The forecasting results indicate that the simulated water level forecasts from the point forecasting module are in good agreement with the observed data, and the proposed model yields the accurate flood inundation maps for 1–3 h lead time. These results indicate that the proposed model accurately forecasts not only flood inundation depth but also inundation extent. This flood inundation forecasting model is expected to be useful in providing early flood warning information for disaster emergency response.

Study on implementation of flood early warning system with internet of things in peri-urban settlement of Palembang for sustainability

Community role is very important to solve flood by developing flood early warning system using Internet of Things namely combining a SMS gateway and a wi-fi network module. This research is about a study of both modules and community’s response to system applied or not in peri-urban settlement of Palembang for sustainability. The conducted methodology is identification of strengths and weaknesses of some variables and community’s responses of two system. Survey resulted that community needs flood early warning system with information technology using SMS to prevent flood risk impact and sustainability.

Evaluating the Performance of Remotely Sensed Precipitation Estimates against In-Situ Observations during the September 2014 Mega-Flood in the Kashmir Valley

In the present study, 4 gridded satellite precipitation data products for September 2014 flood, IMERG (Integrated Multi-satellitE Retrievals for GPM), GSMaP (Global Satellite Mapping of Precipitation), TRMM-3B42 (Tropical Rainfall Measuring Mission) and INSAT-3D-IMR (INSAT Multispectral Rain), were evaluated against the Indian Meteorological Department rain-gauge data from Sep-1st to Sep-7th 2014. Three evaluation indices; Correlation coefficient (CC), the Relative bias (RB) and the Nash-Sutcliffe coefficient (NSC), were used to evaluate the robustness of satellite precipitation estimates with actual rainfall measurements. IMERG precipitation product has a near perfect positive CC and NSC values of 0.94 and 0.99 respectively; while the CC and NSC values are 0.7 and 0.5 for GSMaP_Gauge; 0.69 and 0.05 for INSAT-3D-IMR; and 0.9 and 0.8 for TRMM-3B42 respectively. The RB estimates indicate that IMERG, with a bias of 2%, is a best-fit dataset when compared to the surface rain-gauge observations. In contrast, TRMM-3B42, GSMaP and INSAT-3D-IMR have underestimation biases of −31%, −58%, and − 86% respectively. Analysis of the indices indicates that IMERG precipitation product performed better than other three satellite precipitation products owing to the closeness of values with surface gauge station data over Kashmir. Owing to scanty observation of rainfall in the region, IMERG has a potential to become a cost effective input data source for designing a flood early warning system (FEWS) for Kashmir. However, it is suggested to evaluate the robustness of different satellite-derived precipitation estimates compared to rain gauge observations by incorporating more extreme events from different mountain regions globally for establishing the best satellite derived precipitation product.

Flood vulnerability and coping mechanisms around the Weija Dam near Accra, Ghana

This paper argues that flood vulnerability around the Weija Dam, near Accra, the capital of Ghana, can be explained by the city’s complex peri-urbanization trajectories. The dam, which was constructed 40 years ago, supplies water to many parts of the Greater Accra Metropolitan Area. To offset the impacts of potential dam failure due to seismic activities, as well as accidental and planned water spillages, about 100 m of lands around the dam and 30 m of riparian lands around River Densu were reserved. Despite planning prohibitions, these reservations have largely been encroached by homebuilders and business operators. Analyses of time-series rainfall data and hazard mapping showed that during periods of torrential rainfall, the dam and the river are overwhelmed with storm water hence exposing the Weija Township located downstream to flood hazards. Questionnaire surveys, in-depth interviews with selected homebuilders, and institutional consultations revealed that the spatial and institutional management dynamics, customary land ownership, along with the growing defiance of planning regulations were the key influences of floods in the Weija Township. The affected households have attempted to mitigate the effects of flooding by elevating structures with stones and sandbags, strengthening walls, constructing drains and pumping water out during flooding events, but with little success. However, given the lack of political will to remove the unauthorized structures constructed within the buffers and reservations, the challenge now is to minimize flood vulnerabilities by flood-proofing buildings, improving drains and channelizing portions of the river within the township. These structural measures should be complemented by flood vulnerability maps, early flood warning and evacuation systems, mandatory property insurance policies, and above all, improved institutional coordination and collaboration for flood management. The paper recommends a re-examination of Ghana’s urban land use planning and management of water bodies in urban areas.

Design of Flood Warning System Based IoT and Water Characteristics

Indonesia is one of the tropical country with high rainfall. It causes a flood disaster that with the loss of property and life. Currently handling flood disasters in developing countries are still using many conventional ways. By using conventional way the flood early warning system is still not able to reach the wider community so that information too late of impending disaster received by the public. Besides that the speed of information is needed in the handling of disasters. Therefore a rapid flood warning system that can reach a wide area such as the internet is necessary to minimize the effects of disasters. IoT (Internet of Thing) is smart technology which has capability to send data in real time, connected to the smart phone, sensor and web service. This ability can be used for smart application to control and manage an early warning system. In this research we also use IoT technology to monitor and control the early detection system of flood disaster. By using IoT technology, sensor data can be sent in real time from sensor to smartphone through internet network. The sensor data contains the water characteristics data on the dam that will be processed in the data base. The processing data of water characteristic will be a decision of hazard level. That decision will be sent to users as notification into the user smartphone application. This research will be useful for deeply research on disaster management system and flood early detection system in Indonesia.

Sistem Peringatan Dini Banjir Sungai Bengawan Solo Menggunakan Teknologi Internet Of Things (IoT)

<em>Flood disaster is a natural disaster that causes many losses, both soul and meteriil. Bengawan Solo River is one of the rivers that every year experiencing flood disaster. To improve preparedness for flooding in solo bengawan river, a flood early warning system was created using the Internet of Things (IoT) technology. This system consists of a water level detector, using ultrasonic sensors and arduino uno, and iot servers. Information about the water level of the bengawan solo river can be accessed by users through the website and android. Users will get river water level infromation in real time. Warning level can be set independet for each user. Flood warnings are sent using sms and notification messages for android versions.</em>

Framework for assessing the performance of flood adaptation innovations using a risk‐based approach

The application of risk‐based approaches for the design of flood infrastructure has become increasingly common in flood management. This approach, based on risk reduction and reliability, is used to assess the performance of conventional interventions (e.g., flood defences and dams) and to support decisions regarding their implementation. However, for more innovative solutions, performance has often not been quantified by means of these metrics and, therefore, end‐users are hesitant to implement them in existing flood risk reduction systems. To overcome the gap between innovators and end‐users, we present a framework based on four performance indicators, to ensure the required insights in risk and reliability are provided. The four indicators: effectiveness, durability, reliability and costs, allow end‐users to evaluate, select, and implement flood adaptation innovations, and provide innovators with insight into the performance of the technology and the criteria and information necessary for successful market uptake of their innovation. The practical application of the framework is demonstrated for a (hypothetical) case of a hospital complex built in an area that has subsided below the surrounding area, which is subject to tropical rain showers. The following innovations are considered: an early flood warning system, a green roof, and a temporary flood barrier.

Rainfall-runoff modelling calibration on the watershed with minimum stream gage network data

The hydrological model has an important role to present the accurate and reliable information for water resources management. In this research, combination of HEC-GeoHMS and HEC-HMS that adopt the SCS-CN model have been chosen to analyse the hydrological characteristic at Upper Ciliwung Watershed. Ciliwung Watershed is one of 13 watersheds that has big influence to flood management in Jakarta. Flooding is the natural hazard that occurs every year at Jakarta. One of important part of flood early warning system at Jakarta is Katulampa Weir that located at Upper Ciliwung watershed. The area of it watershed is about 150 km2 that only has one stream gauge station at Katulampa. Accurate representation of rainfall runoff modelling at this location is important in order to predict the discharge and water infrastructure design. The objective of this paper is to obtain the parameter combination of Upper Ciliwung Watershed which can produce the discharge close to the discharge observation using HEC-HMS. The comparison between HEC-HMS and observation gage at Upper Ciliwung Watershed was calculated by Nash-Sutcliffe Efficiency (NSE) method. Nash value of discharge simulation at Upper Ciliwung Watershed compare with the discharge observation at Katumpa Weir reach up until 0,9.

Loss of Life Estimation Due to Flash Floods in Residential Areas using a Regional Model

Flood is a severe natural disaster which causes major damages in most regions including in Iran. Loss of human lives as a consequence of flash flood has not been sufficiently studied despite its high annual rate. Review of related literature indicates relatively low accuracy of available global relationships for estimating loss of life due to flash floods. As a result, regional equations dealing with loss of life estimation relying on all effective hydraulic and evacuation variables is a way forward. In this study, hydraulic variables, such as depth, velocity and rise rate, and evacuation parameters, including available time for evacuation and fraction of people evacuated, were adopted to develop a regional loss of life equation in residential areas of Kan watershed case study, Tehran, Iran, using a calibrated 2DHEC-RAS model. Different number of fatalities in downstream and upstream villages revealed the importance of evacuation time when an early flood warning system is operational. Comparison of the proposed regional equation with available global equations showed that the proposed equation provides more accurate estimation of the number of fatalities in the study area. Regarding the estimated mortality, a local sensitivity analysis performed on the developed equation showed the importance of flood depth to evacuation time ratio, water rising rate and flow velocity, respectively.

Community Based Flash Flood Early Warning System: a Low-cost Technology for Nepalese Mountains

Every year, flood impose substantial economic, social and environmental cost on Nepalese community through direct damage to residential, commercial, educational and structures. Moreover, the flood destroys animal farm, commercial stock and records and other content of the building and pollutes the water. Early Warning Systems are important to save such lives and properties which involves computer, satellite data and high accurate operating system but this system is very costly in terms of installation as well as operation and maintenance leading to hindrance in the sustainability of the system. However, high-tech technology is very expensive and not feasible in Nepal and therefore low-cost and easy operating system is needed in the rural parts of Nepal. The system includes Solar panel, Siren, Ultrasonic sensor, processing unit, and battery. The ultrasonic sensor sense water level and the siren will automatically start. The threshold can be set up according to the space and time. Bulletin of Department of Geology, vol. 20-21, 2018, pp: 87-92

Modelo hidrológico de onda cinemática de la cuenca del río Turbio, Guanajuato, México

Objective: To apply the HEC-HMS methodology based on kinematic wave theory in the Turbio river basin to increase the accuracy of the model in predicting storm runoff. Methodology: Calculations were made for: 1) rainfall depth to runoff depth, through the Soil Conservation Service (SCS) runoff curve number method, 2) runoff depth to hydrograph, for which the SCS unit hydrograph method and kinematic wave (KW) method were used, 3) flood routing in channels, by the Muskingum and KW methods, and 4) flood routing in dams, with the mass balance method. All steps were executed with the HEC-HMS program. Combinations and comparisons of methods 2 and 3 were made, while 1 and 4 remained constant. Results: The hydrologic model that presented the highest Nash-Sutcliffe efficiency index (NSE) was the KW-Muskingum combination, where the runoff depth becomes a hydrograph through the KW and the flood routing in channels is carried out with the Muskingum method, and the lowest value was shown by the KW-KW combination. Study limitations: The models were calibrated for only one event, due to the simultaneous availability of sub-hourly rainfall and flows. This limitation implies that subsequent efforts should focus on validating the kinematic wave model. Originality: The hydrologic model presented here is by events and could be implemented in a flood early warning system. Conclusions: According to the NSE, the three methods were satisfactory; however, the best was the KW-Muskingum combination.

Integration Method of Local-global SVR and Parallel Time Variant PSO in Water Level Forecasting for Flood Early Warning System

Integration Method of Local-global SVR and Parallel Time Variant PSO in Water Level Forecasting for Flood Early Warning System

Integration Method of Local-global SVR and Parallel Time Variant PSO in Water Level Forecasting for Flood Early Warning System

Integration Method of Local-global SVR and Parallel Time Variant PSO in Water Level Forecasting for Flood Early Warning System

Integration Method of Local-global SVR and Parallel Time Variant PSO in Water Level Forecasting for Flood Early Warning System

Flood is one type of natural disaster that can’t be predicted, one of the main causes of flooding is the continuous rain (natural events). In terms of meteorology, the cause of flood is come from high rainfall and the high tide of the sea, resulting in increased the water level. Rainfall and water level analysis in each period, still not able to solve the existing problems. Therefore in this study, the proposed integration method of Parallel Time Variant PSO (PTVPSO) and Local-Global Support Vector Regression (SVR) is used to forecast water level. Implementation in this study combine SVR as regression method for forecast the water level, Local-Global concept take the role for the minimization for the computing time, while PTVPSO used in the SVR to obtain maximum performance and higher accurate result by optimize the parameters of SVR. Hopefully this system will be able to solve the existing problems for flood early warning system due to erratic weather.

A Case Study for the Application of an Operational Two-Dimensional Real-Time Flooding Forecasting System and Smart Water Level Gauges on Roads in Tainan City, Taiwan

An operational two-dimensional real-time flood forecasting system has been developed to prevent urban inundation in Taiwan, and it uses the Delft-FEWS (Flood Early Warning System) platform to integrate the SOBEK models to forecast flooding. A new generation of smart water level gauges, integrating power charging, recording, transmission, and sensing into one, can monitor the inundation on roads in real-time. This study took Annan District in Tainan City, Taiwan, as the study object and presented the application of the flood forecasting system and smart water level gauges in the urban environment. The collected data from Storm 0611 and Typhoon Megi in 2016 were used to assess the accuracy of the flood forecasting system. The analysis of three water level stations in the drainage showed that the one-dimensional simulation results were fairly accurate. According to the 18 observed and simulated inundation depths on the roads, the true positive, false positive, false negative, and true negative values were 8, 0, 2, and 8, respectively. The accuracy, sensitivity, and precision of the flood forecasting system were 0.889, 0.800, and 1.000, respectively, indicating that the two-dimensional simulation results were highly accurate.