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This section presents the challenges of disseminating disaster early warning information to communities at-risk in different local environments and different types of hazards. It particularly presents the early warning systems in: 1) coastal communities of Bangladesh that are prone to tropical cyclone; 2) communities of Bhutan Himalayas that are prone to glacial lake flood outburst (GLOF); and 3) herder communities of Mongolia that are prone to dzud.
Tropical cyclone warning in Bangladesh
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Due to its geographical condition as a low-lying country, Bangladesh experiences tropical cyclones with an average of 17 occurrences every year that often impacted fisherfolks and farmers[14]. Following the tragic experience from Cyclone Bhola on 12 November 1970 that caused the loss of lives of about 500,000 people, the Government of Bangladesh has been introducing disaster risk reduction (DRR) measures, including early warning systems, to prevent such large-scale disaster from reoccurring[15]. The government also learns from other past experiences so that communities can prepare and appropriately respond to future cyclone disasters.
Challenges in early warning as experienced by the communities
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Impacts of tropical cyclones are exacerbated when communities do not receive timely and actionable early warning information. In Bangladesh, a range of factors are attributed to this. First, lack of access to media. While broadcast media, newspapers, and websites could be effective in disseminating cyclone warnings, most coastal communities lack access to these channels. During cyclone Sidr of 2007, communities reported that they did not receive the warning information for the following reasons: (1) they live in remote areas that could not be reached by megaphones; (2) they did not have access to radio/television; and (3) they live in remote areas without media[14]. Second, insufficient warning information. Even if the communities could receive the warning information, if it is insufficient, this could lead to confusion. Rahman mentioned three examples to show why the warning information is insufficient[17]. (1) The weather bulletin, which the government authority issues, usually describes the path of the cyclone by focusing on the nearest seaport (e.g., 'the cyclone is located 50 km southeast of Chittagong port'). This is an old-fashion approach of warning that was introduced by the British Colonial Power way back in 1935 to protect ports instead of communities. (2) The Danger Warning Signals, which shows the scale between 1 and 10, are not understood by many community members since it is complicated to memorize. (3) The warning information is expressed in metric systems (e.g., 'flooding in the locality will likely increase by 20 centimeters in the next 24 hours') that people in the rural communities cannot relate to since very few have a formal education. Third, delayed arrival of warning information. Fishing communities reported that during the July 2018 cyclone, hundreds of fishermen, along with their fishing-boats, went missing in the Bay of Bengal due to the delay of disseminating the early warning information[16].
Early warning system for tropical cyclone
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The Bangladesh Meteorological Department (BMD) is the lead agency for cyclone early warning. To facilitate cyclone forecasting, the Storm Warning Centre (SWC) of BMD obtains information from radar observations, satellite imagery, field observatories, and the Regional Specialized Meteorological Centre (RSMC) of New Delhi. After analyzing the information, SWC/BMD will then create an early warning message that will be disseminated to the media (i.e., television, radio, and newspaper) and to the Cyclone Preparedness Programme (CPP) – a unique institutional arrangement within the government for community preparedness, comprising over 74,000 volunteers[15,17]. When CPP receives the warning information, it will be forwarded to the Coastal Zonal Offices (CZO) at the district level, which will then forward it to the Upazila Disaster Management Committees (UzDMC) at the sub-district level, and down to the Union Disaster Management Committees (UDMC) at the lowest level. As the message reaches the lowest level, the CPP volunteers will disseminate the warning information to the neighborhoods by blowing of sirens, hoisting of flags, and announcement by megaphones (Fig. 2).
There are obvious limitations of the BMD's early warning system for tropical cyclones. In terms of creating the warning information, at least two limitations are observed. On one hand, the warning information uses technical terms that people in the communities don't understand, such as 'forecasted movement direction' and 'surge height'[18]. On the other hand, the accuracy of the warning information is poor. SWC/BMD often fails to correctly forecast the landfall trajectories of cyclones – a performance that is far behind compared to the National Hurricane Center (NHC) of the USA or the Japan Meteorological Agency (JMA), as both agencies have credible and reliable capacity in forecasting complex, rapidly-forming, and fluctuating tropical cyclones[16]. In terms of disseminating the warning information, the most notable limitations according to Rahman are: (1) there is a long chain of information flow that causes distortion or delay of warning message; and (2) communities can only receive the warning information from the CPP volunteers instead of getting it directly from the SWC/BMD[17].
While the BMD's early warning system for tropical cyclone has contributed in reducing the number of casualties in the past decade, it still has limitations in effectively disseminating the warning information to the communities at-risk. This is evident from the recent tropical cyclones like Sidr of 2007 and Aila of 2009 that severely impacted the lives and livelihoods of coastal communities. In fact, during the last three decades (1991-2021), Bangladesh recorded over 160,000 deaths from tropical cyclones[15]. In view of this, the BMD keeps improving the early warning system by strengthening the wireless communication at all levels as well as introducing the Interactive Voice Response (IVR) service, where communities can dial '10941' to receive daily weather forecast, including tropical cyclones[19].
Considerations for introducing QZSS-EWS
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Lack of immediacy or delay of disseminating the warning information is one of the challenges in the EWS of Bangladesh. In the existing system, the CPP volunteers play a great role in disseminating the warning information by blowing of sirens, hoisting of flags, and announcement by megaphones. In other words, the community as-a-whole receives the warning information and not through a single individual. In this context, the introduction of the QZSS-EWS may be more effective if it is integrated in the CPP.
GLOF warning in Bhutan
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Bhutan is a mountainous landscape exposed to high weather variability and extreme events, particularly glacial lake outburst floods (GLOFs). Since 70% of Bhutanese settlements are located along the river basins, most communities are exposed to GLOF and other hydro-meteorological hazards, including floods and landslides[20]. While many major GLOF events occurred in Bhutan in the past, the GLOF on 7 October 1994 caused the greatest impacts, prompting the government to establish an early warning system[21]. However, the limitations of that early warning system were revealed following the GLOF events that occurred on 28 June 2015 and on 20 June 2019 causing massive damage to infrastructure and livelihoods[22].
Challenges in early warning as experienced by the communities
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Living in Bhutan Himalayas is considered a challenge due to the difficult terrains. On top of that, Bhutan has 677 glaciers and 2,674 glacial lakes that pose risk of flooding[23]. Under these topographical conditions, communities are not only scattered and remote, but they also have limited access to communication, transportation, and knowledge sharing. During the 1994 Lugge Tsho GLOF, Bhutan did not have a well-established early warning system, and it resulted in 22 people killed along with massive damage to properties, livestock, and agricultural lands[21]. To reduce risk, the Royal Government installed the first automatic GLOF early warning system with the support from UNDP, and later expanded with the support from the governments of Australia and Japan[24]. However, after experiencing subsequent GLOF events, the EWS did not effectively function in disseminating the warning information to the communities at-risk. Records between 1994 and 2011 showed that GLOF events caused 304 deaths and adversely affected the lives of approximately 87,370 people[20]. In the most recent GLOF events on 28 June 2015 and on 20 June 2019, massive damage to infrastructure and livelihoods were observed, further suggesting that the existing GLOF early warning system needs improvement[22].
The communities felt the limitations of the EWS as well as their own. According to Tshering[25], communities have limited access to communication technologies (e.g., radio, TV, and mobile phones) since the telecommunications infrastructure in Bhutan is still limited. In addition, members of the communities have no formal education, and therefore experiencing difficulties in reading, interpreting, and understanding the early warning information. While most people in the communities have experienced GLOF, they have limited knowledge about its causes and the unpredictability of its occurrence. These limitations are exacerbated since communities have no regular evacuation drills that facilitate skill transfer as well as enhance practical capacities to evacuate during actual disaster events[26].
GLOF early warning system
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The National Center for Hydrology and Meteorology (NCHM) of the Royal Government of Bhutan is the lead agency for GLOF early warning system. Since installing the first early warning system in 1994, Bhutan Himalayas constantly experience climatic variabilities that is affecting the effectiveness of the system. In view of this, NCHM introduced improvements to the system, including the utilization of earth observation satellites[27]. The system has also been enhanced to adapt to the projected climatic changes[22]. Part of the enhancements is the installation of 10 Remote Automatic Water Level Stations (AWLS) and Automatic Weather Stations (AWS) as well as 18 sirens to warn vulnerable communities along the river valley downstream Punakha-Wangdue[24]. The main function of these remote stations is to monitor and detect GLOF in real-time. In producing the automatic alerts, data from the remote stations are transmitted to the Control Room using iridium satellite communication. These remote stations are linked to a network of sirens that are activated in the event of eminent GLOF threats (i.e., when water level reaches the Alarm Level). In addition, operators at the Control Room also monitor the latest data from the remote stations using customized software. So, if the water level reaches the point of the Alarm Level, the operators can activate the sirens manually. After activating the sirens, the Control Room operators will also disseminate the GLOF warning information to all relevant officials (Fig. 3):
• GLOF focal persons at the Department of Disaster Management, the Ministry of Home and Cultural Affairs, and the National Emergency Operation Centre
• Dzongkhag Disaster Focal Person, Dasho Dzongda, Dzongkhag Administration Gasa, Punakha, Wangdue, or Dzongkhag Emergency Operation Centre
• Focal person from Hydropower Plants
Under this system, the estimated lead time (which is the time available for people to take preventive and protective actions) is between 5 and 7 h. However, this lead time is not guaranteed since the flow of flood water depends on many factors and scenarios, such as: (1) the volume of flood water released from the lakes, i.e., either full or partial breach of glacier lakes; (2) the formation of artificial dams along the river course; and (3) the amount of debris and the distance of the glacier lakes to the communities at-risk. Another limitation of the system is the incident of False Alarm that confuses the communities at-risk. Since most of the sensors in the glacial lakes are installed about 4,500 meters above sea level, these sensors are often jammed by ice. When this happens, the water level will falsely rise at Alarm Level, and triggers automatic activation of the sirens. False alarm therefore occurs under two circumstances: instrument failure due to false rise of water level or absence of personnel in the Control Room to prevent the false alarm. To avoid confusion, NCHM officials inform the residents that in the event of a false alarm, sirens can be heard only 2 to 3 times while in the real GLOF alarm, the sirens can be heard at least 12 times in a 5 min interval[20]. This approach is insufficient since the main challenge lies in the limited technical and institutional capacity of the NCHM to manage the GLOF early warning system.
Considerations for introducing QZSS-EWS
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Lack of robustness in the EWS is one of the challenges in Bhutan. So, when part of the system (e.g., sensors) is disrupted by erratic climatic changes, there is no alternative means of sending the warning message to the communities at-risk. It should be recognized that NCHM has developed a Standard Operating Procedure (SOP) for GLOF early warning system. If QZSS-EWS will be introduced to augment the system, it is best to integrate its operations into the existing SOP. The incidents of false alarm (either due to sensor failure or absence of staff) must also be considered to tailor the QZSS-EWS functions to the conditions of the Bhutan Himalayas.
Dzud early warning in Mongolia
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Mongolia's topography is predominantly steppe and desert. One third (approximately 1 million) of its total population are herders, who are living a nomadic life and depend on livestock for livelihoods[28]. The land area that herders occupy is characterized as semi-arid, too dry or too barren, to support vegetation. In the steppes, herders are exposed to extreme weathers (i.e., scorching heat of summer and freezing cold of winter). Under these conditions, herder communities are prone to dzud – a weather phenomenon that causes a summer to be unusually dry, followed by a winter that is unusually cold, making forage unavailable[29]. When herders are impacted by dzud, their livestock would get weak, sick, or die leading to a disaster.
Challenges in early warning that were experienced by the herders
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The most severe dzuds in Mongolia were experienced during the winters of 1999‐2002 and 2009‐2010 that killed about 10 million and 8 million livestock, respectively[30]. These events resulted in significant damage not only to the livelihoods of herders but also to the national economy. Horses and yaks froze to death in the mountain pasture while sheep and goats died of starvation, as all grazing lands were covered by snow[31]. When these dzud events occurred, the capacity of the government for weather forecasting was limited, and early warning system for dzud was not yet fully established[32]. Shaazan[33] enumerated the challenges in dzud early warning that were experienced by the herders: (1) in most cases, herders did not receive a warning information at all, as the communication capacity of the local governments to reach the steppes was limited; (2) while some of the herders have mobile phones to receive warning information via SMS, the system was limited to 160 characters, and on top of that, there was either poor connectivity or no mobile service in the steppes; and (3) due to their nomadic lifestyles, most herders don't have televisions or radios, making it difficult for the local government to issue mass transmission of warning information. In view of these, the national government collaborated with key stakeholders to leverage capacities and resources to improve the early warning system for dzud[34].
Early warning system for dzud
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The National Agency of Meteorology and Environmental Monitoring (NAMEM) is the lead agency responsible for dzud early warning system. The key component of the system is the Dzud Risk Map, which is developed by the Information and Research Institute of Meteorology, Hydrology and Environment (IRIMHE) of NAMEM. Using indicators, such as snow cover days, weather patterns, and agricultural vulnerability to show medium or high-risk areas, IRIMHE analyzes the climate data and use modelling software to develop Dzud Risk Maps[34]. IRIMHE issues these maps monthly by uploading it on its website, and making it accessible to decisionmakers, herders, and the general public[28]. IRIMHE also disseminates the warning information to all relevant channels when an upcoming dzud is imminent (Fig. 4).
While the Dzud Risk Map serves as an essential early warning tool to protect livestock and livelihoods, its effective usage requires capacity building among herders. In particular, the capacity to receive and understand qualitative and quantitative data quickly and accurately is required[28]. It is also important that IRIMHE releases the map ahead of the dzud season so that herders can have enough lead time to evacuate. Aside from collaborating with the Food and Agriculture Organization (FAO), IRIMHE also partners with Mercy Corps Mongolia in implementing the Livestock Early Warning System (LEWS) Project, which serves as a mechanism for providing drought and winter disaster warnings[32].
Considerations for introducing QZSS-EWS
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Lack of comprehensiveness in EWS for dzud is one of the challenges in Mongolia. The Dzud Risk Map does not contain forecast or specific locations that will be impacted by dzud. Due to their nomadic lifestyles, herders have limited or no access to television, radio, or mobile phones. Hence, sending early warning information is a big challenge for the government. If the QZSS-EWS will be introduced for dzud early warning, it is useful to tailor the QZSS-EWS software with the Dzud Risk Maps that are issued by IRIMHE. This integration will be useful to the herders in confirming their position in the steppes using the Dzud Risk Map in the event they will receive warning information and act immediately by evacuating safely with their livestock.