Simulation and analysis for flood early warning system in small catchments caused by rainfall-induced disaster

Author(s):  
Ke-Sin Yu ◽  
Jihn-Sung Lai ◽  
Yi-Huan Hsieh

<p>Under the impact of climate change, rainfall-induced flood disasters have become more frequent in some areas. The development of an hourly rainfall forecast with higher time and spatial accuracy under different rainfall patterns and the connection between meteorological forecast and hydrological flood simulation are urgent issues. In this study, eight flood cases in 2019 in Taipei city, a high-risk urban area with high economic and social resource density, caused by different rainfall patterns were chosen to be analyzed. To improve the accuracy of meteorological data, WRF base ensemble prediction system (WEPS), a quantitative precipitation forecast (QPF) produced by Central Weather Bureau (CWB) of Taiwan was selected as the main meteorological data source, and after processed by objective quantitative analysis methods, the data then be input into the drainage–inundation model. As a one-dimensional and two-dimensional flood simulation system, SOBEK was used to verify the depth and location of floods. Results indicated that the WEPS data would have better performance in drainage–inundation model among the cases in 2019. Combining meteorological forecast data and hydrological simulation can somehow improve the accuracy of flood early warning system in a small catchment.</p>

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2319 ◽  
Author(s):  
Diego Fernández-Nóvoa ◽  
Orlando García-Feal ◽  
José González-Cao ◽  
Carlos de Gonzalo ◽  
José Antonio Rodríguez-Suárez ◽  
...  

Early warning systems have become an essential tool to mitigate the impact of river floods, whose frequency and magnitude have increased during the last few decades as a consequence of climate change. In this context, the Miño River Flood Alert System (MIDAS) early warning system has been developed for the Miño River (Galicia, NW Spain), whose flood events have historically caused severe damage in urban areas and are expected to increase in intensity in the next decades. MIDAS is integrated by a hydrologic (HEC-HMS) and a hydraulic (Iber+) model using precipitation forecast as input data. The system runs automatically and is governed by a set of Python scripts. When any hazard is detected, an alert is issued by the system, including detailed hazards maps, to help decision makers to take precise and effective mitigation measures. Statistical analysis supports the accuracy of hydrologic and hydraulic modules implemented to forecast river flow and flooded critical areas during the analyzed period of time, including some of the most extreme events registered in the Miño River. In fact, MIDAS has proven to be capable of predicting most of the alert situations occurred during the study period, showing its capability to anticipate risk situations.


2021 ◽  
Vol 95 (2) ◽  
pp. 17-28
Author(s):  
An Zhao Zhen ◽  

In 2020, the global economic and trading environment has undergone major changes due to the impact of the global epidemic of the COVID-19. It is not only the world economy that has seriously suffered, protectionism in international trade is growing, and economic and trade frictions between countries with many factors have sharply worsened. Faced with a new situation and new challenges, accelerating the construction of an early warning system for international trade conflicts in Heilongjiang Province has become an important strategic issue of general importance.


2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Gang Wang ◽  
Keming Wang ◽  
Yingying Zhou ◽  
Xiaoyan Mo ◽  
Weilin Xiao

The financial crisis is a realistic problem that the general enterprise must encounter in the process of financial management. Due to the impact of the COVID-19 and the Sino-US trade war, domestic companies with unsound financial conditions are at risk of shutdowns and bankruptcies. Therefore, it is urgently needed to study the financial warning of enterprises. In this study, three decision tree models are used to establish the financial crisis early warning system. These three decision tree models include C50, CART, and random forest decision trees. In addition, the ROC curve was used for comprehensive evaluation of the accuracy analysis of the model to confirm the predictive ability of each model. This result can provide reference for domestic financial departments and provide financial management basis for the investing public.


2019 ◽  
Vol 276 ◽  
pp. 04016
Author(s):  
Maulana Asrafi ◽  
Evi Anggraheni ◽  
Dwita Sutjiningsih

Based on the Comprehensive Flood Management Plan (CFMP), one of the flood control alternatives in the Ciliwung Watershed is using the dry dam construction. Construction of Ciawi dam and Sukamahi dam who are located in Bogor District, are expected to decrease the flood peak and increasing the time concentration in order to reduce the impact caused by a flood in DKI Jakarta due to Ciliwung River. With the construction of Ciawi dam and Sukamahi dam, it is necessary to conduct a research on the effect of both dams construction in Katulampa Weir, one of monitoring point dams on the DKI Jakarta Flood Early Warning System. Hydrological analysis with Win-TR 20 and HEC-RAS was conducted to identify the changes in the flood level of Flood Early Warning System in DKI Jakarta with and without both dams are available. The results of this study indicate that the peak floods decreased by around 2.5% after the implementation of Ciawi dam and Sukamahi dams. The impacts of this reduction will not affect the Flood Early Warning System level at Katulampa Weir significantly.


Climate ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 131
Author(s):  
Alfonso Gutierrez-Lopez ◽  
Ivonne Cruz-Paz ◽  
Martin Muñoz Mandujano

Forecasting extreme precipitations is one of the main priorities of hydrology in Latin America and the Caribbean (LAC). Flood damage in urban areas increases every year, and is mainly caused by convective precipitations and hurricanes. In addition, hydrometeorological monitoring is limited in most countries in this region. Therefore, one of the primary challenges in the LAC region the development of a good rainfall forecasting model that can be used in an early warning system (EWS) or a flood early warning system (FEWS). The aim of this study was to provide an effective forecast of short-term rainfall using a set of climatic variables, based on the Clausius–Clapeyron relationship and taking into account that atmospheric water vapor is one of the variables that determine most meteorological phenomena, particularly regarding precipitation. As a consequence, a simple precipitation forecast model was proposed from data monitored at every minute, such as humidity, surface temperature, atmospheric pressure, and dewpoint. With access to a historical database of 1237 storms, the proposed model allows use of the right combination of these variables to make an accurate forecast of the time of storm onset. The results indicate that the proposed methodology was capable of predicting precipitation onset as a function of the atmospheric pressure, humidity, and dewpoint. The synoptic forecast model was implemented as a hydroinformatics tool in the Extreme Precipitation Monitoring Network of the city of Queretaro, Mexico (RedCIAQ). The improved forecasts provided by the proposed methodology are expected to be useful to support disaster warning systems all over Mexico, mainly during hurricanes and flashfloods.


2018 ◽  
Author(s):  
Veronika Nugraheni Sri Lestari ◽  
Dwi Cahyono ◽  
Sri Susilowati

Currently the development of industrial area development is very rapid this will impact on society if the waste from this industry is not controlled and is known by the societywhose territory is passed by the river from industrial waste disposal.The rapid technological developments will also provide convenience and benefits for the community to be able to control the waste industry one of them is by utilizing android applications in the form of an early warning system application.This research uses survey method and literature study. This research is limited to 5 industry area which primary data sample is taken, 5 industrial area that is surabaya, gresik, mojokerto, lamongan and sidoarjo, research stages include sampling in the industrial area which is then analyzed by using pH detection devices after it is done testing detection devices communicated with mobile phones based on android application this is done several times intended to produce a good test devices.One of the results of this research is the design of pH detection devices communicated with android-based mobile phones, the design referred to in this paper is in the form of UML consisting of 3 diagrams that are use case diagrams, activity diagrams and sequence diagrams


2019 ◽  
Vol 17 ◽  
Author(s):  
Mohd Ramzi Mohd Hussain ◽  
Noor Suzilawati Rabe ◽  
Ismawi Zen ◽  
Izawati Tukiman ◽  
Rahsidi Sabri Muda ◽  
...  

In Cameron Highland, Lembah Bertam area and further downstream villages in Susu Dam area are prone and vulnerable to the highest occurrence of floods especially during monsoon season. Thus, Early Warning System (EWS) were set up to avoid or to reduce the impact of natural hazard turns disasters such as floods, landslides and storms with the aim to reduce the vulnerability and disaster risks that signifies the effectiveness of EWS in the realisation of affected community. To test the awareness and preparedness of community in the selected area, a questionnaire survey was employed as the data collection method. The questionnaire survey was conducted before the direct engagement on the EWS information with the community. Using the mixed sampling method of cluster random sampling, a total of 800 respondents from 11 villages, and 5 main ethnicity groups were involved in the survey. From the result, there was a positive relationship showing that respondents who claimed they knew about the EWS from information signage were those from the older age category and earninghigher monthly income. On the other hand, there is a negative relationship between respondents’ age and monthly income against other sources that indicates respondents who claimed they knew about the EWS from other sources were those in the younger age category and have low monthly income.


Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Ivan Marović ◽  
Ivana Sušanj ◽  
Nevenka Ožanić

The impact of natural disasters increases every year with more casualties and damage to property and the environment. Therefore, it is important to prevent consequences by implementation of the early warning system (EWS) in order to announce the possibility of the harmful phenomena occurrence. In this paper, focus is placed on the implementation of the EWS on the micro location in order to announce possible harmful phenomena occurrence caused by wind. In order to predict such phenomena (wind speed), an artificial neural network (ANN) prediction model is developed. The model is developed on the basis of the input data obtained by local meteorological station on the University of Rijeka campus area in the Republic of Croatia. The prediction model is validated and evaluated by visual and common calculation approaches, after which it was found that it is possible to perform very good wind speed prediction for time steps Δt=1 h, Δt=3 h, and Δt=8 h. The developed model is implemented in the EWS as a decision support for improvement of the existing “procedure plan in a case of the emergency caused by stormy wind or hurricane, snow and occurrence of the ice on the University of Rijeka campus.”


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