Community-based Early Warning System Research Articles

Why Are Community-Based Early Warning Systems Inadequate? A Case Study of the Licungo River Basin, in Mozambique

This study examined the effective implementation of a community-based early warning System (CBEWS) as an early evacuation tool in at-risk communities in the Licungo River Basin Mozambique. Using the United Nations Office for Disaster Risk Reduction (UNDRR) framework, this study evaluated the effectiveness of the CBEWS, focusing on the identification of factors that impede its functionality. The research employed a qualitative approach, conducting one-on-one interviews with key stakeholders at the national, provincial, and district levels, and group discussions with community members in the Licungo River Basin. Interviews and group discussions were conducted in Portuguese and Echuabo, facilitated by a local translator, and included a diverse representation of community members and leaders. The results revealed that the four pillars of the UNDRR framework - risk knowledge, monitoring and warning, communication and dissemination, and response capacity - lacked interdependence, resulting in the CBEWS failing to effectively facilitate early evacuation. Specifically, the study identified several critical factors: a lack of trust in the early warning system, inadequate monitoring and warning systems, communication challenges, and insufficient response resources. Additionally, the lack of social capital significantly affected community members’ willingness to implement and respond to CBEWS warnings and voluntarily evacuate. These findings highlight the need to address social capital and use incentive-based approaches to enhance the effectiveness of the CBEWS. Therefore, promoting strategies that strengthen social capital and incorporate incentives is essential to ensure community engagement and effective evacuation.

Community-Based Early Warning System Model for Stream Overflow In Barranquilla

Context: This work aims to design and create a community-based early warning model as an alternative for the mitigation of disasters caused by stream overflow in Barranquilla (Colombia). This model is based on contributions from social networks, which are consulted through their API and filtered according to their location. Methods: With the information collected, cleaning and debugging are performed. Then, through natural language processing techniques, the texts are tokenized and vectorized, aiming to find the vector similarity between the processed texts and thus generating a classification. Results: The texts classified as dealing with stream overflow are processed again to obtain a location or assign a default one, in order to for them to be georeferenced in a map that allows associating the risk zone and visualizing it in a web application to monitor and reduce the potential damage to the population. Conclusions: Three classification algorithms were selected (random forest, extra trees, and k-neighbors) to determine the best classifier. These three algorithms exhibited the best performance and R2 regarding the data processed in the regressions. These algorithms were trained, with the k-neighbor algorithm exhibiting the best performance.

The effectivity of community-based early warning system on reducing Semeru eruption impact post-eruption 2021

Disaster communication plays an essential role in the disaster risk management phase. In general, this disaster communication can be divided into three, namely: pre-disaster, during the disaster, and post-disaster. Disaster communication in Indonesia has been extensively implemented in various disaster events. Semeru volcano is one of the active volcanoes in Indonesia whose eruption period cannot be predicted with certainty. Hot clouds falling from the Semeru volcano in 2021, which resulted in casualties, loss, and property damage, proves that disaster communication in the Semeru Disaster Prone Area needs to run more effectively. The Early Warning System currently in effect in the Semeru Volcano disaster-prone area comes from several parties, including 1) Semeru Volcano Observation Post, 2) Field Officers of the Lumajang Regency Regional Disaster Management Agency, and the Community in Simbar Semeru in collaboration with Magma ESDM. This study analyzes disaster information and communication effectiveness in the Semeru Volcano Hazardous Area after the 2021 Eruption. Primary data collection was carried out through in-depth interviews and observations. In-depth interviews with each stakeholder responsible for providing information to the public. The study results show that the pre-eruption of Mount Semeru disaster communication in 2021 has yet to be maximized. This is evidenced by the fact that residents still need awareness and preparedness to face the dangers of Semeru Volcano eruptions. Meanwhile, after the Semeru eruption of 2021, the population has been alerting to any increase in Semeru Volcano activity.

Integrating “Top-Down” and “Community-Centric” Approaches for Community-Based Flood Early Warning Systems in Namibia

The United Nations Office for Disaster Risk Reduction (UNDRR) resolutely endorses the development of people-centred early warning systems. Moreover, several scientific studies have deprecated the vast technology-driven technocratic approaches to implementing these systems, contending the prioritisation of communities and their contextualised needs for systems that ensure effective risk protection and resilience building. However, both the UNDRR and the scientific literature have failed to define appropriate means of implementation (MoI) for community-based early warning system (CBEWS) development. Floods are a major hazard annually impacting several communities in rural sub-Saharan Africa, and though several opportunities for participatory systems have been identified, investment in developing countries is often lagging, and no defined mechanism for developing these systems exists. Adopting a modified Integrated Emergency Management Framework, this study demonstrates that an impact-based CBEWS can be established by leveraging existing resources, institutions and stakeholders, essentially merging last-mile and first-mile approaches. The study further reveals that directly linking technical capacities with community-based efforts allows communities to define system development parameters, strengthen risk knowledge and response, and build resilience for improved physical, economic and environmental protection, essentially bridging the gap between first and last-mile approaches. The study also highlights the need for governments to appropriately streamline DRR to improve coordination and communication.

Flood monitoring and community based flash flood warning system for Nasiri River, West Seram, Maluku

ABSTRACT On 1st of August 2012, two successive flash floods hit Nasiri hamlet in Maluku archipelago, Indonesia. The floods destroyed 61 houses and swept some of them down into the sea. A monitoring and community-based early warning system (MCBEWS) was developed 2 years later. This paper presents the approach, development, and implementation of the system. There are two components, namely community capacity-building and the establishment of telemetric monitoring. The flood warning system considers two causes: extreme rainfall and landslide dam breaks. Raising awareness, workshops, training, and disaster organisation establishment appeared to effectively increase flood disaster preparedness capacity and community commitment. The adoption of a rainfall depth vs. intensity chart method for issuing flood warnings seems to be promising. The presence of an unusual flow reduction in the record during extreme rainfall indicates damming at the upstream of the record station due to landslides. Possible landslide dams near the downstream to the middle reaches might provide dangerous high peak discharge flash floods with short warning times.

Assessment of community-based flood early warning system in Malawi.

One of the major natural hazards the world is facing these days are floods. Malawi has not been spared. Floods have affected the countries’ socio-economic developmental plans. River gauges have been installed along major rivers to monitor water levels in a bid to warn communities of imminent flooding. In Malawi, ever since the installation of river gauges no study has been done to assess their effectiveness. This study examines the effectiveness of these river gauges as part of community-based early warning system. The research employs both qualitative and quantitative approach. Questionnaires, interviews, group discussions, document analysis were all used in order to understand the behavioural aspect of communities under study. The current community-based early warning system practices were benchmarked against the following elements: risk knowledge, technical monitoring and warning services, dissemination and communication of warnings and response capability. The study revealed that Malawi has two distinct systems in place: at national level (managed by several government departments) and at community level [managed by Civil Protection Committees (CPCs)]. These systems were installed by non-governmental organisations (NGOs) and faith-based organisations. Apparently, no direct link exists between the two. Operational bureaucracy affects the speedy presentation of warning messages at national level. Lack of capacity and necessities affects the operation of the community-based system. Despite the efforts to develop the early warning systems, the failures outweigh the successes. Government needs to provide enough funding for systems sustainability, build capacity of CPCs and install more technologically advanced systems.

Assessment of a Ground-Based Lightning Detection and Near-Real-Time Warning System in the Rural Community of Swayimane, KwaZulu-Natal, South Africa

AbstractClimate change projections of increases in lightning activity are an added concern for lightning-prone countries such as South Africa. South Africa’s high levels of poverty, lack of education, and awareness, as well as a poorly developed infrastructure, increase the vulnerability of rural communities to the threat of lightning. Despite the existence of national lightning networks, lightning alerts and warnings are not disseminated well to such rural communities. We therefore developed a community-based early warning system (EWS) to detect and disseminate lightning threats and alerts in a timely and comprehensible manner within Swayimane, KwaZulu-Natal, South Africa. The system is composed of an electrical field meter and a lightning flash sensor with warnings disseminated via audible and visible alarms on site and with a remote server issuing short message services (SMSs) and email alerts. Twelve months of data (February 2018–February 2019) were utilized to evaluate the performance of the EWS’s detection and warning capabilities. Diurnal variations in lightning activity indicated the influence of solar radiation, causing convective conditions with peaks in lightning activity occurring during the late afternoon and early evening (between 1400 and 2100) coinciding with students being released from school and when most workers return home. In addition to detecting the threat of lightning, the EWS was beneficial in identifying periods that exhibited above-normal lightning activity, with two specific lightning events examined in detail. Poor network signals in rural communities presented an initial challenge, delaying data transmission to the central server until rectified using multiple network providers. Overall, the EWS was found to disseminate reliable warnings in a timely manner.

Modeling on the spatial vulnerability of lightning disaster in Bangladesh using GIS and IDW techniques

This paper tries to explore the spatial patterns of lightning disaster death susceptibility in Bangladesh. It is prior need to identify the factors of death due to lightning hazard, seasonal variability, and spatial risks to develop management strategies of this country. To reach the study goal, lightning fatalities data were collected from the Ministry of Disaster Management and Relief, Bangladesh. The geostatistical IDW model of GIS technology was applied to assess the spatial vulnerability of lightning disaster. The geospatial prediction maps produced from the study determines the spatial heterogeneity of lightning risk. Generated statistics demonstrates that the Surma Basin, northwest Brinda tract, and northern Tertiary hilly region of Bangladesh are more susceptible to lightning disaster during the time span 2015–2018. Analysis results also discloses numerous factors such as climatic variability, geomorphological diverseness and anthropogenic phenomena influencing lightning catastrophes. Moreover, this study suggests that government and non-government disaster management organizations can play vital role to take initiative in risk assess, policy creation review, awareness building and campaign, community-based early warning system, emergency management system and appropriate technology piloting as well as implementation. The rationale of this study will contribute to assess spatial lightning strikes, mitigate locational vulnerability and promote sustainable development plans for reducing lightning disaster risk. In the future, GIS-based communication model like this can applied to raise awareness and educating and engaging the public through public–private partnership of the lightning hot spot regions.

Participatory capacities and vulnerabilities assessment: Towards the realisation of community-based early warning system for deep-seated landslides.

Existing frameworks of community-based early warning systems (CBEWS) lack focus on its actual implementation. Furthermore, they do not describe how a top-down early warning system (EWS) can be transformed into a CBEWS. Hence, to support the establishment of a community-based early warning system for deep-seated landslides (CBEWS-L), this study aimed to assess the capacities and vulnerabilities of five barangays in the Philippines. The CBEWS-L to be established is envisioned to be information and communication technology (ICT)-based. An ICT4D perspective was therefore taken in conducting this participatory study. Stakeholder mapping, focus group discussions and key informant interviews were used to gather data. Validation was also done through triangulation and post-analysis consultations. The results showed that there are varying sets of capacities and vulnerabilities existing in each community. Moreover, ICT capacities are lacking and are outnumbered by vulnerabilities. Yet, site-specific action points to enhance capacities and resolve vulnerabilities were determined. Still, overall strategies were not uncovered. Furthermore, compounding the capacities and vulnerabilities in each site are indirect factors which, if examined thoroughly, may lead to more complex socio-political issues. It is therefore recommended that in establishing a CBEWS, a comprehensive community risk assessment is first conducted to exhaust all possible action points that can be used in formulating site-specific strategies. Moreover, development of technological solutions must be modular to allow flexibility in accommodating complex community capacities and vulnerabilities.Keywords: Early warning systems; community risk assessment; participatory research; information and communication technology or development; community-based disaster risk reduction and management.

Real-time evacuation and failure mechanism of a giant soil landslide on 19 July 2018 in Yanyuan County, Sichuan Province, China

A giant soil landslide named Boli landslide occurred on the right bank of Taozi Gully, a branch of the Jiami River in Taozi town, Sichuan Province, China, at approximately 5:40 am local time on 19 July 2018. The landslide destroyed 186 houses and nearly 300 acres of agricultural land in Boli village. Real-time evacuation was successfully implemented to avoid casualties of 281 people among 65 settlements due to the effective warning. This study revealed the typical characteristics, the cause, and the failure mechanism of Boli landslide on the basis of multi-temporal remote sensing images, field investigation, and analysis of the landslide soils. A simple, effective, and scalable community-based early warning system was also proposed in the study on the basis of real-time evacuation in response to landslide hazards in mountain in near future. Moreover, the experience and the effective risk avoidance mode of this study can be used by the concern parties to improve the disaster prevention and countermeasures of poor mountainous areas.

The Effectiveness of Community-Based Early Warning System of Kelud Volcano Eruption

The Effectiveness of Community-Based Early Warning System of Kelud Volcano Eruption

The effectiveness of community-based early warning system of Kelud volcano eruption 2014

Kelud Volcano is an active volcano in Indonesia. About 150 million meter cubic has erupted on 13 February 2013 at 22.30. People were successfully responded to the most significant eruption in history without any fatalities, by doing less than 2 hours evacuation, from 21.15 to 22.50. This research was conducted to show the success of the community in building the resilience process by applying a good system of community-based early warning. The study was conducted through documentary review and field assessment with participatory research methods, including mapping, transects, and historical studies. The result of research show that the community has four aspects of early warning system has been successfully fulfilled by communities. Those four aspects are (1) Knowledge of risk; (2) Monitoring and warning service; (3) Dissemination and communication; (4) Ability of the people to respond. Systematic data collection and risk assessment, with its pattern and tendency factors, ensured that disaster and vulnerability are well-known. Monitoring parameter to create accurate and timely pre-estimation has been ensured by disaster monitoring and early warning service. Communicating information and early warning ensured that the warning could be received by everyone that affected by disaster, risk, and its warning can be understood and useful. Establishing the people’s responsibility to ensure the response must be renewed, ability and local knowledge can be utilized, and people are ready to response warning. Simulation and training activities were implemented by the people within the disaster-prone area. Finally, the powerfulness of community preparedness can manage the tremendous level of a volcano eruption.

The role of Indigenous science and local knowledge in integrated observing systems: moving toward adaptive capacity indices and early warning systems

Community-based observing networks (CBONs) use a set of human observers connected via a network to provide comprehensive data, through observations of a range of environmental variables. Invariably, these observers are Indigenous peoples whose intimacy with the land- and waterscape is high. Certain observers can recall events precisely, describe changes accurately, and place them in an appropriate social context. Each observer is akin to a sensor and, linked together, they form a robust and adaptive sensor array that constitutes the CBON. CBONs are able to monitor environmental changes as a consequence of changing ecological conditions (e.g., weather, sea state, sea ice, flora, and fauna) as well as anthropogenic activities (e.g., ship traffic, human behaviors, and infrastructure). Just like an instrumented array, CBONs can be tested and calibrated. However, unlike fixed instruments, they consist of intelligent actors who are much more capable of parsing information to better detect patterns (i.e., local knowledge for global understanding). CBONs rely on the inclusion of Indigenous science and local and traditional knowledge, and we advocate for their inclusion in observing networks globally. In this paper, we discuss the role of CBONs in monitoring environmental change in general, and their utility in developing a better understanding of coupled social-ecological systems and developing decision support both for local communities as well as regional management entities through adaptive capacity indices and risk assessment such as a community-based early warning system. The paper concludes that CBONs, through the practice of Indigenous science in partnership with academic/government scientists for the purpose of knowledge co-production, have the potential to greatly improve the way we monitor environmental change for the purpose of successful response and adaptation.

Farmers' perceptions of implementation of climate variability disaster preparedness strategies in Central Uganda

This paper examines smallholder farmers' perceptions of the implementation of climate change disaster preparedness strategies in Mpigi district in Central Uganda. Furthermore, existing community early actions against climate change disasters were investigated. Data were collected through semi-structured interviews and focus group discussions at the community level. Using the Statistical Package for Social Sciences version 16, data obtained through semi-structured interviews were subjected to quantitative analysis to generate percentages for several variables and cross-tabulation analyses between selected variables. Farmers perceived prolonged droughts, increased pests and diseases outbreaks in crops and livestock as a consequence of climate change as the major climate change disasters. They considered the implementation of climate change disaster preparedness at community and village level as inadequate. This triggered implementation of various early actions by farmers as responses to climate change disasters. These actions constitute an informal community-based early warning system against climate change disasters.