scholarly journals EXPERIMENTAL FLOOD EARLY WARNING SYSTEM IN PARTS OF BEAS BASIN USING INTEGRATION OF WEATHER FORECASTING, HYDROLOGICAL AND HYDRODYNAMIC MODELS

2018 ◽  
Vol XLII-5 ◽  
pp. 221-225 ◽  
Author(s):  
P. R. Dhote ◽  
P. K. Thakur ◽  
S. P. Aggarwal ◽  
V. C. Sharma ◽  
V. Garg ◽  
...  
Keyword(s):  
Early Warning ◽  
Weather Forecasting ◽  
Monsoon Season ◽  
Human Life ◽  
Mitigation Strategies ◽  
Economic Losses ◽  
Simulation Accuracy ◽  
Rainfall Forecast ◽  
Outer Domain ◽  
Basin Scale

<p><strong>Abstract.</strong> The flood early warning for any country is very important due to possible saving of human life, minimizing economic losses and devising mitigation strategies. The present work highlights the experimental flood early warning study in parts of Beas Basin, India for the monsoon season of 2015. The entire flood early warning was done in three parts. In first part, rainfall forecast for every three days in double nested Weather Research and Forecasting (WRF) domain (9<span class="thinspace"></span>km for outer domain and 3<span class="thinspace"></span>km for inner domain) was done for North Western Himalaya NWH using National Centres for Environmental Prediction (NCEP) Global Forecasting System (GFS) 0.25 degree data as initialization state. Rainfall forecast was validated using Indian Meteorological Department (IMD) data, the simulation accuracy of WRF in rainfall prediction above 100<span class="thinspace"></span>mm is about 60%. Rainfall induced flood event of August 05&amp;ndash;08, 2015 in Sone River (tributary of Beas River) Basin, near Dharampur, Mandi district of Himachal Pradesh caused very high damages. This event was picked three days in advance by WRF model based rainfall forecast. In second part, mean rainfall at sub-basin scale for hydrological model (HEC-HMS) was estimated from forecasted rainfall at every three hours in netcdf format using python script and flood hydrographs were generated. In third part, flood inundation map was generated using Hydrodynamic (HD) model (MIKE 11) with flood hydrographs as boundary condition to see the probable areas of inundation.</p>

SEISMIC RISK AND RESILIENCE ASSESSMENT OF INDUSTRIAL FACILITIES: CASE STUDY ON A BLACK CARBON PLANT

2020 ◽  
Author(s):  
George Karagiannakis
Keyword(s):  
Seismic Risk ◽  
Numerical Models ◽  
Fragility Curves ◽  
Human Life ◽  
Mitigation Strategies ◽  
Economic Losses ◽  
Risk And Resilience ◽  
Industrial Plants ◽  
Plant Equipment

This paper deals with state of the art risk and resilience calculations for industrial plants. Resilience is a top priority issue on the agenda of societies due to climate change and the all-time demand for human life safety and financial robustness. Industrial plants are highly complex systems containing a considerable number of equipment such as steel storage tanks, pipe rack-piping systems, and other installations. Loss Of Containment (LOC) scenarios triggered by past earthquakes due to failure on critical components were followed by severe repercussions on the community, long recovery times and great economic losses. Hence, facility planners and emergency managers should be aware of possible seismic damages and should have already established recovery plans to maximize the resilience and minimize the losses. Seismic risk assessment is the first step of resilience calculations, as it establishes possible damage scenarios. In order to have an accurate risk analysis, the plant equipment vulnerability must be assessed; this is made feasible either from fragility databases in the literature that refer to customized equipment or through numerical calculations. Two different approaches to fragility assessment will be discussed in this paper: (i) code-based Fragility Curves (FCs); and (ii) fragility curves based on numerical models. A carbon black process plant is used as a case study in order to display the influence of various fragility curve realizations taking their effects on risk and resilience calculations into account. Additionally, a new way of representing the total resilience of industrial installations is proposed. More precisely, all possible scenarios will be endowed with their weighted recovery curves (according to their probability of occurrence) and summed together. The result is a concise graph that can help stakeholders to identify critical plant equipment and make decisions on seismic mitigation strategies for plant safety and efficiency. Finally, possible mitigation strategies, like structural health monitoring and metamaterial-based seismic shields are addressed, in order to show how future developments may enhance plant resilience. The work presented hereafter represents a highly condensed application of the research done during the XP-RESILIENCE project, while more detailed information is available on the project website https://r.unitn.it/en/dicam/xp-resilience.

scholarly journals Integrating earthquake early warning system and a smart robot for post-earthquake automated inspection and emergency response

2021 ◽  
Author(s):  
Tzu-Hsuan Lin ◽  
Jing-Ting Huang ◽  
Alan Putranto
Keyword(s):  
Emergency Response ◽  
Early Warning ◽  
Early Warning System ◽  
Human Life ◽  
Warning System ◽  
Integrated System ◽  
Earthquake Early Warning ◽  
Economic Losses ◽  
Automated Inspection ◽  
Earthquake Early Warning System

Abstract The natural hazard, mainly earthquake, has caused substantial economic losses and human life loss to many countries. Taiwan, which is located on the western Circum-Pacific seismic belt, has encountered the problem as mentioned earlier in Meishan, Hsinchu-Taichung, and Chi-Chi earthquakes a few years ago. In this study, the researchers propose a novel robot-event integrated system capable of doing the automated inspection and emergency response due to a significant earthquake. When the household’s earthquake warning receiving device picks up an alert, its built-in wireless communications system will send a signal to the robot. The robot commences inspection of the indoor area via real-time image recognition and tracking. It will approach them upon detecting fallen people, regulating their movements via a robot operating system (ROS) monitoring interface. The robot is designed to operate in a house that remains standing with acceptable damage in which the furniture might falling and injure the occupants after an earthquake hit. The indoor experiment conducted to verify the robot system and operation with a designed condition such as fallen and non-fallen people as a detected object. The robot tested to deliver food or medicine for fallen people while waiting for rescuers to arrive. Tests indicate that the proposed smart robot has prospective implementation to the real-world application with more research and development. The smart robot integrated with an earthquake early warning system has a promising approach to the temporary care of people affected by earthquakes.

scholarly journals A systematic literature review on multi-criteria decision making in disaster management

2020 ◽  
Vol 2 (2) ◽  
pp. 1-7
Author(s):  
Fawz Manyaga ◽  
Mariam Yasmin ◽  
Nilufer Nilufer ◽  
Zineb Hajaoui
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Disaster Management ◽  
Systematic Literature Review ◽  
Monsoon Season ◽  
Human Life ◽  
Economic Losses ◽  
Multi Criteria Decision Making ◽  
Planning And Management ◽  
Effective Planning

This paper through a systematic literature review portrays the academic work that has been done in disaster management by applying multi-criteria decision making. This study reviews 36 academic articles that applied multi-criteria decision-making planning and management of natural disasters i.e. tsunami, floods, heavy rains, earthquake, land sliding, epidemic, pandemic, etc. This study finds out that lack of effective planning and management pre and post disasters is causing loss of human life, temporary migration of locals to safer places, loss of properties, and economic losses. Once the crisis is over, it requires efforts and additional finances to bring life to normal. There are regions where disasters are periodic such as floods in rivers or due to monsoon season. But with effective planning and pre-determined priorities, loss to human life can be mitigated. Disaster management departments need effective planning tools to forecast imminent disasters and prepare accordingly. This study is very relevant to the recent global pandemic COVID-19 that has caused human and economic losses and will leave footprints for the coming years and generations

Catastrophic Effects of Floods on Environment and Health: Evidence from Pakistan

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Falak Shad Memon ◽  
M. Yousuf Sharjeel
Keyword(s):  
Paradigm Shift ◽  
Weather Forecasting ◽  
Human Life ◽  
National Level ◽  
Operational Cost ◽  
Site Assessment ◽  
Environment And Health ◽  
Forecasting System ◽  
Frame Work ◽  
Multiple Levels

<span>Torrential rains and floods have been causing irreplaceable losses to both human lives and environment in <span>Pakistan. This loss has reached to an extent of assively aggrieved situation to reinstate life at <span>operationally viable position. This paper unfolds the notion that only constructive paradigm shift to <span>overcome this phenomenon is vital as a strategy. Multiple levels of observations and on-site assessment <span>of various calamity-prone venues were considered to probe into this scenario. Some of the grave site in <span>Sindh and Punjab were observed and necessarily practicable measures were recommended to avoid loss to <span>human health and environment. The paper finds that a consistent drastic management authority on <span>national level with appropriate caliber and forecasting expertise can reduce the damage to human life and <span>environment to great extent. Weather forecasting system need to be installed at many appropriately <span>observed cities and towns in the country with adequate man power, funds and technical recourses. By <span>implementing the proper frame work of prevention and mitigation of floods country can save the major <span>costs cleanup and recovery. These measures are expected to reduce operational cost of state in terms of <span>GDP and GNP to restore life and environment.</span></span></span></span></span></span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span>

scholarly journals Development of an early warning system for loose automobile tires

2020 ◽  
Vol 103 (3) ◽  
pp. 003685042094088
Author(s):  
Huibo Wu ◽  
Fei Song ◽  
Kainan Wu ◽  
Cheng Chen ◽  
Xiaohua Wang
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Traffic Accidents ◽  
Warning System ◽  
Working Environment ◽  
Vehicle Body ◽  
Economic Losses ◽  
Control Module ◽  
Alarm Signal ◽  
Monitoring Module

The looseness of tires or even falling off from cars will lead to serious traffic accidents. Once it occurs, it will bring casualties and huge economic losses to society, seriously affecting the traffic safety. To mitigate such possible safety concerns, an early loosening warning system is developed in this article. The system consists of the tire monitoring module and the working control module. The tire monitoring module is installed on the tire and is designed with no power supply. The control module is installed in the vehicle body. Signal transmission between the two modules is achieved through wireless radio frequency. In the driving, once the tire is loosened, the monitoring device will send out the alarm signal automatically and wirelessly. After the driver gets the alarm signal, he can immediately perform the emergency processing, parking, and inspection, which can avoid traffic accidents caused by it. This article introduces the detailed structure, working principle, and operation process of the system. This early warning system has simple structure, high reliability, and is easy to use. It can be used in the common working environment of automobiles. Meanwhile, it is also the foundation of intelligent connected vehicle.

The economic costs of extreme weather events: a hydrometeorological CGE analysis for Malawi

2011 ◽  
Vol 16 (2) ◽  
pp. 177-198 ◽  
Author(s):  
KARL PAUW ◽  
JAMES THURLOW ◽  
MURTHY BACHU ◽  
DIRK ERNST VAN SEVENTER
Keyword(s):  
Computable General Equilibrium ◽  
Computable General Equilibrium Model ◽  
Extreme Weather ◽  
Mitigation Strategies ◽  
Extreme Weather Events ◽  
Economic Losses ◽  
Historical Events ◽  
Weather Events ◽  
Repeated Sampling ◽  
Droughts And Floods

ABSTRACTExtreme weather events such as droughts and floods have potentially damaging implications for developing countries. Previous studies have estimated economic losses during hypothetical or single historical events, and have relied on historical production data rather than explicitly modeling climate. However, effective mitigation strategies require knowledge of the full distribution of weather events and their isolated effects on economic outcomes. We combine stochastic hydrometeorological crop-loss models with a regionalized computable general equilibrium model to estimate losses for the full distribution of possible weather events in Malawi. Results indicate that, based on repeated sampling from historical events, at least 1.7 per cent of Malawi's gross domestic product (GDP) is lost each year due to the combined effects of droughts and floods. Smaller-scale farmers in the southern region of the country are worst affected. However, poverty among urban and nonfarm households also increases due to national food shortages and higher domestic prices.

scholarly journals Impact of Climate Change on Agriculture and Its Mitigation Strategies: A Review

2021 ◽  
Vol 13 (3) ◽  
pp. 1318
Author(s):  
Gurdeep Singh Malhi ◽  
Manpreet Kaur ◽  
Prashant Kaushik
Keyword(s):  
Climate Change ◽  
Plant Productivity ◽  
Mitigation Strategies ◽  
Economic Losses ◽  
Agriculture Sector ◽  
Pest Infestation ◽  
Average Global Temperature ◽  
Metabolic Activities ◽  
Global Threat ◽  
Food And Nutritional Security

Climate change is a global threat to the food and nutritional security of the world. As greenhouse-gas emissions in the atmosphere are increasing, the temperature is also rising due to the greenhouse effect. The average global temperature is increasing continuously and is predicted to rise by 2 °C until 2100, which would cause substantial economic losses at the global level. The concentration of CO2, which accounts for a major proportion of greenhouse gases, is increasing at an alarming rate, and has led to higher growth and plant productivity due to increased photosynthesis, but increased temperature offsets this effect as it leads to increased crop respiration rate and evapotranspiration, higher pest infestation, a shift in weed flora, and reduced crop duration. Climate change also affects the microbial population and their enzymatic activities in soil. This paper reviews the information collected through the literature regarding the issue of climate change, its possible causes, its projection in the near future, its impact on the agriculture sector as an influence on physiological and metabolic activities of plants, and its potential and reported implications for growth and plant productivity, pest infestation, and mitigation strategies and their economic impact.

scholarly journals Direct and indirect economic impacts of drought in the agri-food sector in the Ebro River basin (Spain)

2013 ◽  
Vol 13 (10) ◽  
pp. 2679-2694 ◽  
Author(s):  
M. Gil ◽  
A. Garrido ◽  
N. Hernández-Mora
Keyword(s):  
Water Scarcity ◽  
Agricultural Sector ◽  
Economic Impacts ◽  
Economic Loss ◽  
Mitigation Strategies ◽  
Economic Losses ◽  
Drought Risk ◽  
Drought Event ◽  
Drought Impacts ◽  
Indirect Impacts

Abstract. The economic evaluation of drought impacts is essential in order to define efficient and sustainable management and mitigation strategies. The aim of this study is to evaluate the economic impacts of a drought event on the agricultural sector and measure how they are transmitted from primary production to industrial output and related employment. We fit econometric models to determine the magnitude of the economic loss attributable to water storage. The direct impacts of drought on agricultural productivity are measured through a direct attribution model. Indirect impacts on agricultural employment and the agri-food industry are evaluated through a nested indirect attribution model. The transmission of water scarcity effects from agricultural production to macroeconomic variables is measured through chained elasticities. The models allow for differentiating the impacts deriving from water scarcity from other sources of economic losses. Results show that the importance of drought impacts are less relevant at the macroeconomic level, but are more significant for those activities directly dependent on water abstractions and precipitation. From a management perspective, implications of these findings are important to develop effective mitigation strategies to reduce drought risk exposure.

scholarly journals High-resolution analysis of 1 day extreme precipitation in Sicily

2015 ◽  
Vol 15 (10) ◽  
pp. 2347-2358 ◽  
Author(s):  
M. Maugeri ◽  
M. Brunetti ◽  
M. Garzoglio ◽  
C. Simolo
Keyword(s):  
High Resolution ◽  
Extreme Precipitation ◽  
Human Life ◽  
Extreme Value Distribution ◽  
Generalized Extreme Value Distribution ◽  
Return Level ◽  
Regional Frequency Analysis ◽  
Economic Losses ◽  
Data Set ◽  
High Quantiles

Abstract. Sicily, a major Mediterranean island, has experienced several exceptional precipitation episodes and floods during the last century, with serious damage to human life and the environment. Long-term, rational planning of urban development is indispensable to protect the population and to avoid huge economic losses in the future. This requires a thorough knowledge of the distributional features of extreme precipitation over the complex territory of Sicily. In this study, we perform a detailed investigation of observed 1 day precipitation extremes and their frequency distribution, based on a dense data set of high-quality, homogenized station records in 1921–2005. We estimate very high quantiles (return levels) corresponding to 10-, 50- and 100-year return periods, as predicted by a generalized extreme value distribution. Return level estimates are produced on a regular high-resolution grid (30 arcsec) using a variant of regional frequency analysis combined with regression techniques. Results clearly reflect the complexity of this region, and show the high vulnerability of its eastern and northeastern parts as those prone to the most intense and potentially damaging events.

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