scholarly journals Enhancing Flood Early Warning System in the HKH Region

2021 ◽  
pp. 169-200
Author(s):  
Karma Tsering ◽  
Kiran Shakya ◽  
Mir A. Matin ◽  
Jim Nelson ◽  
Birendra Bajracharya
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Natural Hazard ◽  
Environmental Changes ◽  
Warning System ◽  
Flood Forecasting ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Events ◽  
Forecasting And Warning

AbstractFlooding is a chronic natural hazard with disastrous impacts that have magnified over the last decade due to the rising trend in extreme weather events and growing societal vulnerability from global socioeconomic and environmental changes (WMO 2011 in Manual on flood forecasting and warning (WMO-No. 1072)).

scholarly journals Early warning system on extreme weather events for disaster risk reduction

2019 ◽  
pp. 80-87
Author(s):  
Jacipt Alexander Ramón-Valencia ◽  
Jordi Rafael Palacios-González ◽  
Germán Rircardo Santos-Granados ◽  
Jarol Derley Ramón-Valencia
Keyword(s):  
Risk Management ◽  
Risk Reduction ◽  
Early Warning ◽  
Early Warning System ◽  
Disaster Risk Reduction ◽  
Warning System ◽  
Disaster Risk ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Events

The objective of this research was to propose a strategy based on the design and implementation of an early warning system (EWS) for extreme weather events. This project had the following phases: training for municipal and regional actors, preliminary technical diagnosis of the study areas, monitoring network, and the weather forecasts using numerical models WRF and GFS. This EWS is the result of the Macro-project EWS for Climate Events in the basins of the Pamplonita River and Zulia in the North of Santander (SATC), executed by the University of Pamplona and financed by the National Risk Management Unit (UNGRD) and the German Cooperation Agency (GIZ). The research concluded that the application of a disaster risk reduction strategy through an EWS for extreme weather events is an important tool and instrument for the planning of higher risk management because it helps anticipate disasters and consequently preserve lives.

scholarly journals Learning Case Study of a Shallow-Water Model to Assess an Early-Warning System for Fast Alpine Muddy-Debris-Flow

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 750
Author(s):  
Antonio Pasculli ◽  
Jacopo Cinosi ◽  
Laura Turconi ◽  
Nicola Sciarra
Keyword(s):  
Debris Flow ◽  
Shallow Water ◽  
Early Warning ◽  
Debris Flows ◽  
Early Warning System ◽  
Warning System ◽  
Extreme Weather Events ◽  
Water Model ◽  
Computational Time ◽  
Processing Unit

The current climate change could lead to an intensification of extreme weather events, such as sudden floods and fast flowing debris flows. Accordingly, the availability of an early-warning device system, based on hydrological data and on both accurate and very fast running mathematical-numerical models, would be not only desirable, but also necessary in areas of particular hazard. To this purpose, the 2D Riemann–Godunov shallow-water approach, solved in parallel on a Graphical-Processing-Unit (GPU) (able to drastically reduce calculation time) and implemented with the RiverFlow2D code (version 2017), was selected as a possible tool to be applied within the Alpine contexts. Moreover, it was also necessary to identify a prototype of an actual rainfall monitoring network and an actual debris-flow event, beside the acquisition of an accurate numerical description of the topography. The Marderello’s basin (Alps, Turin, Italy), described by a 5 × 5 m Digital Terrain Model (DTM), equipped with five rain-gauges and one hydrometer and the muddy debris flow event that was monitored on 22 July 2016, were identified as a typical test case, well representative of mountain contexts and the phenomena under study. Several parametric analyses, also including selected infiltration modelling, were carried out in order to individuate the best numerical values fitting the measured data. Different rheological options, such as Coulomb-Turbulent-Yield and others, were tested. Moreover, some useful general suggestions, regarding the improvement of the adopted mathematical modelling, were acquired. The rapidity of the computational time due to the application of the GPU and the comparison between experimental data and numerical results, regarding both the arrival time and the height of the debris wave, clearly show that the selected approaches and methodology can be considered suitable and accurate tools to be included in an early-warning system, based at least on simple acoustic and/or light alarms that can allow rapid evacuation, for fast flowing debris flows.

scholarly journals Perbandingan Estimasi Radar Cuaca Dopler Baron Terhadap Data Observasi Kejadian Hujan Di Kota Kupang

2020 ◽  
Vol 20 (2) ◽  
pp. 1
Author(s):  
Ni Putu Nonik Prianti ◽  
Roddialek Pollo ◽  
Judi K. Nasjoro ◽  
Sulton Kharisma
Keyword(s):  
Early Warning ◽  
Warning System ◽  
Heavy Rain ◽  
Radar Data ◽  
Extreme Weather ◽  
Disaster Mitigation ◽  
Extreme Weather Events ◽  
Observation Data ◽  
Weather Information ◽  
The Impact

Radar is able to provide information about extreme weather observations in the form of heavy rain, so it is important to find the level of accuracy of the radar in providing extreme weather information. So that with accurate data disaster mitigation can be done by creating an early warning system using radar data in order to minimize the impact that will occur. Comparative analysis of the estimated rainfall events on the radar with surface observation data shows a good level of accuracy, but the blankness of the data on the radar due to damage thus influences the decision making of the forecasters when providing extreme weather information quickly to the public. By knowing the radar accuracy level is quite good in estimating rain events, BMKG can provide weather information in the form of appropriate early warning so that people can anticipate extreme weather events

scholarly journals Neurology in a Changing Climate: A Scoping Review

2021 ◽  
Author(s):  
Shreya Louis ◽  
Alise Carlson ◽  
Abhilash Suresh ◽  
Joshua Rim ◽  
MaryAnn Mays ◽  
...  
Keyword(s):  
Climate Change ◽  
Infectious Diseases ◽  
Environmental Changes ◽  
Temperature Fluctuations ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Neurologic Disease ◽  
Neurologic Symptom ◽  
Airborne Pollutants ◽  
Weather Events

Importance: Although the international community collectively seeks to reduce global temperature rise to less than 1.5C, there are already irreversible environmental changes that have occurred, and currently available evidence suggests these changes will continue to occur. As we begin to witness the effects of a warming planet on human health, it is imperative that as neurologists we anticipate the ways in which the epidemiology and incidence of neurologic disease may be affected. Objective: In this review, we organize our analysis around three key themes related to climate change and neurologic health: extreme weather events and temperature fluctuations, emerging neuro-infectious diseases, and pollutant impacts. Across each of these key themes, we appraise and review recent literature relevant to neurological disease and the practice of neurology. Evidence Review: Studies were identified using a set of relevant search terms relating to climate change and neurologic diseases in the PubMed repository for publications between 1990 and 2021. Studies were included if they pertained to human incidence or prevalence of disease, were in the English language, and were relevant to neurologic disease. Findings: We identified a total of 136 articles, grouped into the three key themes of our study; extreme weather events and temperature fluctuations (23 studies), emerging neuro-infectious diseases (42 studies), and pollutant impacts (71 studies). Broadly, the studies included highlighted the relationships between neurologic symptom exacerbation and temperature variability, tick-borne infections and warming climates, and airborne pollutants and cerebrovascular disease incidence and severity. Conclusions and Relevance: Our work highlights three key priorities for further work; namely, neuro-infectious disease risk mitigation, an understanding of the pathophysiology of airborne pollutants on the nervous system, and research into how to improve delivery of neurologic care in the face of climate-related disruptions.

VAWG and the Environment

2020 ◽  
Author(s):  
Jacqui True
Keyword(s):  
Environmental Changes ◽  
Extreme Weather ◽  
Resource Scarcity ◽  
Extreme Weather Events ◽  
Traditional Practices ◽  
Gender Based Violence ◽  
Weather Events ◽  
Gender Based ◽  
Harmful Traditional Practices

How are environmental changes related to VAWG? Environmental changes that cause resource scarcity exacerbate VAWG. In societies where harmful traditional practices continue to regard women as property, resource scarcities intensify gender-based VAWG. Moreover, extreme weather events can exacerbate insecurities and foreshadow gender-based violence. For...

Building the Flood Early Warning System in Guyana at the National scale, with real-time forecast of inundated areas for selected flood prone communities.

2020 ◽  
Author(s):  
Alessandro Masoero ◽  
Imra Hodzic ◽  
Colis Allen ◽  
Andrea Libertino ◽  
Andrea Giusti ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Flood Forecasting ◽  
Local Scale ◽  
Civil Defense ◽  
Data Availability ◽  
Inundation Maps ◽  
Extreme Flood

<p>Within the framework of the project “Strengthening Disaster Management Capacity of Women in Guyana and Dominica”, the National Flood Early Warning System (NFEWS) for Guyana is currently under development. The technical component of the system aims at implementing an operational flood forecasting modelling chain linking meteorological, hydrological and inundation models to provide timely early warnings and predicted flood scenarios, allowing the decision maker to take prevention actions and reduce the impacts of the forecasted event.</p><p>The objective is to implement, together with the Hydromet Service of Guyana, a technical tool able to provide daily forecasts of extreme flood events 1 to seven 7 days in advance, up to the local scale of inundation maps for selected locations.</p><p>The forecasting chain implemented is composed of five (5) main components: i) the weather forecasts, using the limited area WRF model executed twice a day at Hydromet; ii) observational inputs preparation, in particular rain maps through conditional merging between local ground stations and satellite information; iii) rainfall downscaling in several equiprobable scenarios using RAINFARM stochastic model; iv) the distributed hydrological model CONTINUUM, able to estimate river discharge and soil moisture conditions from the meteorological inputs (observation and forecasts), and v)the hydraulic model HYDRA-2D, that using a simplification of the shallow water equations allows fast and reliable inundation mapping.</p><p>At four (4) selected locations, corresponding to relevant flood-prone communities in Guyana, an innovative coupling between the hydrological and the inundation models allows to trigger an operational execution of several hydraulic simulations, resulting in real-time probabilistic forecast of inundation maps. The outflow volumes, derived from CONTINUUM hydrological routing, for different rainfall scenarios are used as inflow inputs for HYDRA-2D. Scalability between hydrological (1.5km) and hydraulic (12m) scales has been achieved through detailed field data collection, that was also used, together with local knowledge, to calibrate the inundation model.</p><p>Through the complete flood forecasting chain set up for Guyana, probability of exceeding significant water depths can be provided in advance to involved stakeholders, triggering early actions and thus enhancing flood resilience at the local scale.</p><p>The hydrological component of the forecasting chain has been implemented at the national level for the whole country, at a feasible spatial and temporal resolution based on a balance between input data availability and expected response time for civil defense activities.</p><p>Being developed using an open source model, as for all the other elements of the forecasting system, the hydraulic modelling component can be, in future, extended and replicated in other areas of interests.</p>

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