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Multiple hazards, such as, earthquake, strong wind, snow, flood-induced scour, tsunami, landslide, rain, blast, explosion, fire outbreak, etc. have caused extensive global devastations to civil structure and infrastructure systems in terms of physical and socio-economic losses. The catastrophic losses are largely due to the complex effects of these multiple hazards, as the existing provisions currently do not address the intriguing effects of multi-hazard. The associated complex and multifaceted effects, hence, warrant urgent attention for establishing new design code provisions to assess new and retrofit existing structures. In this context, this article presents a detailed and comprehensive review about the multi-hazard effects on structures and infrastructures exposed to different natural and manmade hazards. The prevailing global challenges are addressed for consideration of the complex interaction and inter-relation effects under the multiple hazard scenarios. The existing information on multi-hazard analysis is critically synthesized, and the similarities and differences of existing multi-hazard studies along with the future challenges are provided. Moreover, existing assessment techniques for optimal design of structures are discussed, emphasizing the mitigation strategies adopted under the multi-hazard scenarios. Special attention is also focused in developing the scientific knowhow to protect the structures for better performance under a selection of the complex and intriguing multi-hazard scenarios.

This study investigates the synoptic conditions that led to the heavy rainfall/flood (HRF) event in Mindanao Island, Philippines (122 −127°E; 5 −10°N), on January 2009 (JAN2009 HRF) that are less emphasized in previous works. Extensive flooding was reported over Cagayan de Oro City in the northern part of Mindanao, where the rainfall on January 10, 11, and 13, 2009, exceeded the 99th percentile of daily rainfall records of all January of the city from 1979 to 2017 by almost two times. A similar exceedance was also felt in Hinatuan station over the eastern coast of Mindanao Island on January 15, 2009. The interaction of a cold surge shearline over the northern Mindanao Island and the warm tropical easterlies led to enhanced moisture convergence. The warmer air mass is forced to ascend by the advancing colder air mass because it has lower density than the colder air mass. The enhanced moisture convergence and buoyancy difference by the air masses led to enhanced ascent and consequently rainfall along the cold surge shearline. Further analysis shows that enhanced anomalous easterly and northerly winds at 925 hPa are apparent over the Philippines. The anomalous easterly winds sustained the supply of warmer easterlies and collaboratively interacted with the northerly winds that supplied colder temperature air mass.The climatology of this HRF event was examined for all January from 1979 to 2017. The authors identified 15 other cases that are similar to the JAN2009 HRF event and performed lag composite analyses. The results show that the occurrence of these HRF events is facilitated by the southward expansion of the high-pressure system to the north of the Philippines, enhanced cold and warm temperature advections, and enhanced moisture convergence along the cold surge shearline. The results of this study have important implications for disaster mitigation during the northeast monsoon season when rainfall activities are, in general, less intensive over this region.

Research on disaster mitigation and prevention has tended to focus on the impact of natural disasters on the economy and strategies for risk reduction and mitigation. There has been significant research on disaster prevention and treatment efficiencies, however, most analyses have employed traditional data envelopment analysis (DEA) radial models that do not consider undesirable output. Differing from previous research, this study employed a non‐radial directional distance function DEA that included an undesirable output analysis to evaluate the natural hazard management efficiency in 27 provinces/municipalities/autonomous regions in China. Results show that: (a) economic losses from natural disasters were lower due to the increase in natural disaster prevention and control program expenditure; (b) the overall natural disaster control efficiencies varied significantly across the provinces; and (c) Tibet and Xinjiang, which have the lowest general disaster prevention efficiencies, could benefit from following the example set by provinces such as Sichuan and Guangdong, which have the highest disaster prevention efficiencies. Disaster prevention efficiencies measure the overall performance of each province in disaster prevention. This efficiency index is measured by input (disaster prevention expenditure) and output (number of natural disasters prevented and natural disaster economic losses), and its calculation method is the ratio of the actual value of each input and output to the target value. This ratio is called the efficiency score, and the efficiency score is between 0 and 1. An efficiency score of 1 represents the most efficient.

The main objective of this paper is to present the techno-economic analysis of an off-grid Photovoltaic system, which prepared to support disaster mitigation scheme in remote areas. As a case study, a regency in Mentawai Island, Sumatera Barat is chosen to represent a remote area in a disaster-prone location. The proposed system capacity is 20 kWp PV system as a single electricity source for medical facility in the island. As a tool in this study, RETScreen software was used to analyze the technical, environmental, and economical feasibility analysis. As a base case scenario, the medical facility was supported by a diesel-fueled generator and the PV system can deliver 10.14 MWh of electricity to load annually. Net annual GHG emission reduction of the system is 19.4 ton of CO2 equivalent. With the total initial cost for the whole PV system at USD 41,380, RETScreen simulation result showed that the equity payback of the project is 6.0 years with IRR of 11.9% hence the project is financially viable.

Several marine research have attempted to design a data observation system using Internet of Things (IoT). In the future, this system is predicted to become a necessity for marine researchers as a strategic technology to continuously access data. Therefore, this study provides information on the development and application of observation and data collection systems using IoT. The coastal weather and tidal data were obtained via the automatic coastal weather station and acoustic gauge respectively. Meanwhile, the various research activities commenced in July, 2018. In the first year, an operational observation system was developed, while comprehensive baseline data such as air temperature, humidity, wind speed, and sea surface level were also collected. This collection system is reliable, provides real-time data, and easily accessible with internet connection. Furthermore, the Bintan Marine Observation System (The Bintan MOS) is also suitable for other uses such as; monitoring water quality and marine mammals, as well as disaster mitigation. The adoption of this system by other sectors potentially conditions marine researchers for data exchange, to fully understand the fluctuations in coastal weather of Western and Eastern Indonesia as well as the tropical and sub-tropical marine weather. This study successfully developed the Bintan MOS, capable of providing reliable information both off-line and real-time.Keywords:Marine observation systemCoastal weatherTidalBintan

Heavy rain in Semarang on 1 January 2020 caused flooding. The existence of heavy rain cannot be separated from the dynamics of weather parameters which are closely related to the convection process and cloud formation. In this paper research has been conducted using Weather Research and Forecasting (WRF), to analyze the growth patterns of convective clouds as an effort to mitigate the initial events of extreme rainfall disasters. Several weather parameters that support cloud growth are very significant, namely the parameter values ​​that support the convection process to form convective clouds (Cumulonimbus). The results of the model show that there has been extreme rainfall which can be used as initial mitigation of hydrometeorological disasters.

Impact forecasting has been applied to estimate flood damage in many different countries based on accurate weather forecasts. This study develops a model forecasting the impact of rainfall on riverside flood risks in the Busan Metropolitan City. The rainfall impact forecasting equations were obtained on a 1km x 1km grid with respect to water levels and critical rainfall thresholds. Critical rainfall was determined based on the end point of river and the discharge-water level relationship between design flood discharge and design flood level by analyzing water-rainfall in 3-hour critical rainfall. Model verification was performed using a heavy rain event with a total of 283.3 mm from July 22 to 24, 2020. According to the rainfall impact forecasting, 60 to 70% of the design flood level (“MEDIUM” alert) was issued on rivers between 10-11pm on July 23. In the rivers where the rainfall impact alert was issued, actual damages were found such as flooded roads and floodplain, which confirmed the appropriateness of the model. The high model accuracy was also validated by comparing the alert standard for water level with forecasted rainfall impact at the water level station in Suyeong River.

Mitigation education is a stage of preparedness to minimize losses due to a disaster. The purpose of this study is to develop teaching materials with the SETS (Science, Environment, Technology, and Society) approach Integrated Science subjects of solar system competencies and the earth surface structure to reduce the risk of the Mount Lokon volcanic ash disaster in North Sulawesi Province. This research uses Research and Development Methods. The subjects in this study were 30 students at SMP Kristen Credo Kolongan, Minahasa Regency. The results showed that the teaching material developed was declared valid by experts, practical was used, and effectively viewed from the cognitive aspect with an increase in the pretest score (54.5) to the posttest (92), and the affective aspects of the average score very good average (87.3) so that this teaching material is valid, practical, and effectively used in learning activities to reduce the risk of volcanic ash disaster.

Landslides triggered by intense rainfall are hazards that impact people and infrastructure across the world, but comprehensively quantifying exposure to these hazards remains challenging. Unlike earthquakes or flooding, which cover large areas, landslides occur only in highly susceptible parts of a landscape affected by intense rainfall, which may not intersect human settlement or infrastructure. Existing datasets of landslides around the world generally include only those reported to have caused impacts, leading to significant biases toward areas with higher reporting capacity, limiting our understanding of exposure to landslides in developing countries. In this study, we use an alternative approach to estimate exposure to landslides in a homogenous fashion. We have combined a global landslide hazard proxy derived from satellite data with open-source datasets on population, roads and infrastructure to consistently estimate exposure to rapid landslide hazards around the globe. These exposure models compare favourably with existing datasets of rainfall-triggered landslide fatalities, while filling in major gaps in inventory-based estimates in parts of the world with lower reporting capacity. Our findings provide a global estimate of exposure to landslides from 2001 to 2019 that we suggest may be useful to disaster mitigation professionals.

To develop disaster mitigation measures in coastal regions affected by earthquakes, it is important to consider the effects of both seismic and tsunami hazards on road structures and assess the soc...

This article describes improvement of the rapid earthquake analysis system, accurate and quick analysis system for source parameters (AQUA), which has automatically determined the location, magnitude, and fault type of M 7 except nearly simultaneous events. Source parameters with and without fixed horizontal locations are provided within 100–250 and 100–600 s of the first P arrival, respectively. This system is valuable for disaster mitigation because it rapidly provides information for use in tsunami warning and early damage assessment.

The frequency of landslides and the fact that a large number of people live in the landslides-prone areas lead to a high death toll in Java Island, Indonesia – over 1,112 people in the period between 1999 and 2005. Indonesian National Disaster Management Agency (Badan Nasional Penanggulangan Bencana [BNPB]) reported 2,766 landslides that occurred in Java from 2014 to 2019, with 662 deaths. From its state, it looks as if Indonesia 's disaster mitigation is still weak. It is very essential to a deep understanding of landslides disaster mitigation weakness in Indonesia with the approach of governments, researchers, and local communities action. This research is a review of landslides disaster mitigation in Java Island with the approach of governments, researchers, and local communities action. Furthermore, the purpose of this study is to highlight the driving forces of landslides disaster mitigation in Java Island, Indonesia. From the assessment of each stakeholder (government, researchers, and local communities), the driving forces of landslides disaster mitigation in Java Island are the central government has commanding disaster management activities to local governments. However, the implementation of landslides disaster mitigation at the regional level has some obstacles such as the lack of residential development planning.Many landslide research results have only become scientific papers but the landslides-prone areas have not been fully paid attention by the local government such as the absence of landslide danger warning signs.In addition, the level of preparedness and awareness among local communities is not constant at any given time. Usually, community preparedness levels can be high following a disaster. It is likely, however, to diminish over time.

Bekasi Regency, one of the districts affected when rainfall is high occurs according to data from BPS during 2016 the average rainfall reached 2,000.12 mm. Public Middle School 3 East Cikarang, one of the areas that has the potential for flooding, is caused by a lower land surface than the surrounding area. Biopori Infiltration Hole, is one of the techniques carried out for disaster mitigation and can be applied easily by everyone. The purpose of this study is to find out how much the benefits of biopori as a solution to minimize the potential for flooding applied in schools that are often affected by flooding. The benefit of this research is that students and the community know the benefits of biopori as a whole, not just as a flood prevention. The results obtained are overall knowledge about biopori, the benefits of applying biopori, designing a good biopori installation location, and also designing an effective biopori manufacture.

Projecting future change of monsoon rainfall is essential for water resource management, food security, disaster mitigation, and infrastructure planning. Here we assess the future change and explore the causes of the changes using 15 models that participated in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The multimodel ensemble projects that, under the shared socioeconomic pathway (SSP) 2–4.5, the total land monsoon rainfall will likely increase in the Northern Hemisphere (NH) by about 2.8% per one degree Celsius of global warming (2.8% °C−1) in contrast to little change in the Southern Hemisphere (SH; −0.3% °C−1). In addition, in the future the Asian–northern African monsoon likely becomes wetter while the North American monsoon becomes drier. Since the humidity increase is nearly uniform in all summer monsoon regions, the dynamic processes must play a fundamental role in shaping the spatial patterns of the global monsoon changes. Greenhouse gas (GHG) radiative forcing induces a “NH-warmer-than-SH” pattern, which favors increasing the NH monsoon rainfall and prolonging the NH monsoon rainy season while reducing the SH monsoon rainfall and shortening the SH monsoon rainy season. The GHG forcing induces a “land-warmer-than-ocean” pattern, which enhances Asian monsoon low pressure and increases Asian and northern African monsoon rainfall, and an El Niño–like warming, which reduces North American monsoon rainfall. The uncertainties in the projected monsoon precipitation changes are significantly related to the models’ projected hemispheric and land–ocean thermal contrasts as well as to the eastern Pacific Ocean warming. The CMIP6 models’ common biases and the processes by which convective heating drives monsoon circulation are also discussed.

This study examines the application of a landslide disaster monitoring system based on soil activity information that utilizes humidity, temperature, and accelerometer sensors. An artificial highland was built as the research object, and the landslide process was triggered by supplying the system with continuous artificial rainfall. The soil activities were observed through its slope movement, temperature, and moisture content, utilizing an accelerometer, temperature, and humidity sensors both in dry and wet conditions. The system could well observe the soil activities, and the obtained data could be accessed in real-time and online mode on a website. The time delay in sending the data to the server was 2 seconds. Moreover, the characteristics of soil porosity and its relevance to soil saturation level due to water pressure were studied as well. Kinetic study showed that the water adsorption to soil followed the intraparticle diffusion model with a coefficient of determination R2 0.99043. The system prototype should be used to build the information center of disaster mitigation, particularly in Indonesia.

Sewu Village is annually experience by river flooding. The application of Biopore Infiltration Holes (BIH) is one of the measures to reduce river flood disaster risk. This research was aimed to determine the proper location of the BIH. Hydrology tools by using flow direction analysis was used to obtain the best place of BIH. It utilized Digital Elevation Model (DEM), existing landuse and morphology analysis to know the river flooding prone area and to identify the potential flow direction of surface water (run off). The conformity of those data can be used as determination of BIH. Moreover, the number of BIH had been obtained from flow direction analysis where the lower ground elevation was the best place to arrange BIH. Overall, the flood disaster risk in Sewu Village can be potentially overcome by using BIH.

Flood verification and mitigation based on ground survey has been impeded by many factors. For instance, damage assessment exclusively by onsite expedition could be delayed by restricted access, especially during heavy flooding. To devise appropriate mitigation measures, resources required to thoroughly investigate the incidents in response to disaster could be overwhelming. Moreover, inadequate equipment and non-standardized flood reporting process could also undermine the maneuver. As a consequent, rescue mission was inevitably deferred until the reported incidents had been confirmed. To address these issues, this paper presents an internetworking system for assisting flooding disaster mitigation. Its main contributions were two folds. Firstly, its data intelligent was driven by convergence of both user and official reports of flood incidents and those automatically detected from remotely sensed images. Secondly, the reliability of reported information was ensured by two-factor verification, i.e. by using a state-of-the-art deep learning strategy and by official investigations. The verified incidents were then presented in augmented graphical reports, which were practical in public inquiry and official uses in devising efficient and cost-effective disaster mitigation measures. The developed system was deployed in different cities, most affected by recent floods. Numerical and subjective assessments herein demonstrate the merits of the system.

Institute Technology of Sumatera (ITERA) located on Sumatera Island, take place on Lampung Selatan (South Lampung. As the coastal region, Lampung Selatan dominated by the sandy soil which allows the possibility of the Liquifaction. The objectives of this research is to mitigate the Liquifaction with analyze using Liquifaction of the safety factor map under the deterministic method. In order to establish the development of Institute Technology of Sumatera (ITERA, this research expected can be used as the consideration to mitigate the damage in relation with the site condition. Deterministic method is the ratio comparison of the Cyclic Resistant Ratio (CRR) and the Cyclic Stress Ratio (CSR) effected by the earthquakes. Cyclic Stress Ratio (CSR) depends on the depth of the soil layer, total vertical pressure, effective vertical pressure, earthquake’s magnitude and the peak ground acceleration. Meanwhile, the Cyclic Resistance Ratio (CRR) calculated by the correlation of the empirical result of CPT. The safety factor value analyzed by the comparison value of CSR and CRR that pointed on 12 CPT location. In result, take the test location on ITERA, it is known that the safety factor in this site is on the safe zone and have been described on the color zone on the map as the disaster mitigation.

Flash floods frequently occur in Indonesia. Flash flood can be caused by natural and human factors. This paper discusses the causes and mitigation of flash flood using a case study in Banyuwangi. On June 22th 2018, flash floods occurred in the residential areas of Garit, Karang Asem, and Bangunrejo Hamlets. Flash floods were triggered by heavy rainfall the day before, which reached 90 mm/day. The three hamlets are located in Alasmalang Village, Singojuruh Subdistrict, Banyuwangi District. The study began with a field survey, analysis of the damage, and the causes of a flash flood, and its alternative treatments. The suspected source of the material was the landslide material, approximately two million cubic meters from the Pendil Mountain. Some of the material were carried away by the river flooding caused flash floods in the three hamlets. The small width of the bridge was not able to be passed by trees and other flash flood material, so water overflowed the roads and houses. Based on the results of the study, it is recommended for disaster mitigation in the form of structural and non-structural actions. Structural measure in the form of bridge elevation and construction of sediment retaining weirs, while non-structural actions are in the form of an early warning system and dissemination of flash flood hazards.

Landslide and erosion disasters are become increasingly common in the last decade which resulted in financial losses and even human casualties. Therefore, disaster mitigation efforts of landslide and erosion are very important to be done immediately. A breakthrough of comprehensive and practical solution is highly expected for mitigation. Vegetation can improve slope stability, provide positive aspects for the environment, and provide mechanical and hydrological effects on slopes that are prone to landslide and erosion. The use of vegetation to mitigate landslide and erosion disasters is very potential to be developed because besides being effective, it is also economical and environmentally friendly. The mechanical aspects of plant roots is able to strengthen the soil. Plant root characteristics such as root architecture, root anchor index (IJA), root grip index (ICA) are important variables to determine the types of plants that will be used in mitigating landslide and erosion.

Large-scale water management systems were introduced to the Ganges-Brahmaputra and Mekong Deltas in the latter half of the twentieth century to manage extreme water hazards and increase foo...

Disaster mitigation activities require the availability of a potentially flooded area (PFA) map. One of the causes of flooding is the criticality of water catchment areas; the higher the criticality level, the higher the flooding potential. This study aims to determine the accuracy of the model for determining the PFA around Bengkulu City, which was derived from the Level of Critical Water Catchment Area (LCWCA) model developed by the Ministry of Forestry. After obtaining the LCWCA Map, another analysis was performed in order to obtain the PFA Map. Furthermore, the overlaying was carried out with the Existing Flood Map in such a way that the level of accuracy is known. The threshold values from Justice are used to justify the level of accuracy in three categories, namely Good (> 85%), Moderate (70 - 85%), and Poor ( 85%), which means that there was > 85% overlap between areas on the Potentially Flooded Area Map as a result of the analysis of The LCWCA with the area on the Existing Flood Map. There are three sub-watersheds with Moderate accuracy (70 - 85%) and three sub-watersheds with Poor accuracy (

Accurate precipitation prediction is of great significance for regional flood control and disaster mitigation. This study introduced a prediction model based on the least square support vector machine (LSSVM) optimized by the genetic algorithm (GA). The model was used to estimate the precipitation of each meteorological station over the source region of the Yellow River (SRYE) in China for 12 months. The Ensemble empirical mode decomposition (EEMD) method was used to select meteorological factors and realize precipitation prediction, without dependence on historical data as a training set. The prediction results were compared with each other, according to the determination coefficient (R2), mean absolute errors (MAE), and root mean square error (RMSE). The results show that sea surface temperature (SST) in the Niño 1 + 2 region exerts the largest influence on accuracy of the prediction model for precipitation in the SRYE (RSST2= 0.856, RMSESST= 19.648, MAESST= 14.363). It is followed by the potential energy of gravity waves (Ep) and temperature (T) that have similar effects on precipitation prediction. The prediction accuracy is sensitive to altitude influences and accurate prediction results are easily obtained at high altitudes. This model provides a new and reliable research method for precipitation prediction in regions without historical data.

The Tsunami's natural disaster causes severe impacts such as significant loss of life and massive property damage in the coastal areas. Modeling tsunami hazards is one of the preparedness and mitigation measures to promote tsunami safety. However, there are several issues in tsunami hazards modeling for the development of hazard mitigation strategies. This paper systematically reviews various Tsunami hazard model, which focuses on (1) identifying the effectiveness of the model in conveying the information for the policymakers and society, (2) identifying the constraints of the models if applied in other areas. This study also proposes a model, which is assumed to improve tsunami hazards modeling in disaster mitigation. We will build, test, and implement the model in the future.

ALOS-2 and ALOS-4 (Advanced Land Observing Satellite-2/4) are Japanese earth observation satellites with L-band SAR (Synthetic Aperture Radar) sensors. ALOS-2 has been operating since 2014, and its observations have been utilized for disaster mitigation, environmental monitoring such as forest and sea/land ice, land monitoring such as agriculture and natural resources, and technology development. ALOS-4 is now being developed for launch in JFY2022. The ALOS-4 aims to expand swath width and increasing observation frequency while keeping the high spatial resolution of ALOS-2 for improving the response of disaster monitoring, early detection of anomalies on the earth’s surface, and enabling time-series analysis. In this paper, the ALOS-2/4 mission summary and SAR system design are introduced.

Mapping of potential flood hazards is an important element in ensuring proper planning of development and implementing flood disaster mitigation efforts for flooded areas. Therefore, this study was conducted to assess the regional-scale flood hazard areas in Gorontalo District using an AHP-GIS integration technique with the focus on factors such as annual rainfall, elevation, slope, soil type, distance to the water bodies, and land-use. The flood hazard was divided into five classes, ranging from very low to very high, and 13.61% of the total area in Gorontalo Regency is classified as either high or very high. Moreover, the distribution of the hazard was verified and 65 events were recorded to have a level of 90.7% and this indicates the model is reliable to assess flood hazard. The results showed GIS-AHP integration is a promising method to accurately predict flood-hazard areas, especially in those with limited data.

Warming has strongly influenced the quantity and variability of natural disasters around the globe. This study aims to characterize the varying patterns between rising temperatures and climate-related natural disasters in China from 1951 to 2010. We examined the overall trend in the patterns of an 11-year cycle, and climate-related natural disaster responses to periods of rising and dropping temperature. We used Morlet wavelet analysis to determine the length of a temperature cycle period, and the arc elasticity coefficient to assess the number of climate-related natural disasters in response to the changing temperature. We found that: (1) the overall relationship between temperature and the number of climate-related natural disasters was positive, (2) however, on the cycle level, the pattern of climate-related natural disasters was found to be independent of temperature variation, (3) on the rise-drop level, temperature increases were associated with declines in the number of climate-related natural disasters. Moreover, as temperature decreased, the number of climate-related natural disasters increased substantially, such that temperature had a more considerable influence on the quantity of climate-related natural disasters during the temperature-drop period. Findings in this study can help enhance the dissemination of warning and mitigation efforts to combat natural disasters in the changing climate.

In this study, we collected the data of 172 typhoon storm surge disasters that occurred in China during 1983-2018 to show the temporal and spatial distribution of their frequency and damage. Our results indicated that: (1) there was an increase in the frequency of typhoons storm surge disasters during 1983-2018, and 98% of these disasters occurred from June to October; (2) the damage decreased over time, especially after 1997; (3) the frequency and damage caused by typhoon storm surge disasters were higher in the southern and eastern regions than in the northern regions; (4) Guangdong, Fujian, and Zhejiang experienced the highest disaster occurreneces and damages, and the number of disaster occurrences and damages in these three regions accounted for approximately 57% and 80% of the total disaster occurrences and damages, respectively. Furthermore, we mainly analyzed the spatiotemporal characteristics of typhoon storm surge disasters from three aspects: contributors and damage records of extreme typhoon storm surge disasters, mitigation measures, and tropical cyclone tracks. These findings and analyses can help disaster managers improve their understanding of typhoon storm surge disasters and strengthen protection in disaster hotspots and sensitive months.

A rainfall-induced debris flow disaster occurred in Shelong Gully on the 22th June, 2019. More than 26,300 m2 of farmland and 14 houses were buried and transportation and power supply broke down in the worst catastrophe in the history of Shelong area. To investigate this disaster, a detailed interpretation was carried out using (Unmanned Aerial Vehicle) UAV-based images. Analysis of disaster characteristics based on images and field survey revealed that the disaster could be identified as a consequence of compound mountain hazards including mass movements and mountain torrent in Shelong Gully. Moreover, the dynamic process of debris flow was analysed by using the finite difference method. Its dynamic characteristics indicated that the structure of debris materials changed during the movement process of debris flow. The results reveal that the loose materials, steep terrain condition and abundant rainfall are the main causal factors of this disaster event. This research on the analysis of hazard formation conditions and dynamic process for debris flows is of guiding significance to the formulation of disaster risk assessment and disaster mitigation plans.

Radar rainfall data will be used as an input for the distributed hydrological model to understand flood disaster mitigation. By using multiparameter weather radar data during 13 - 15 February 2016 to calculate total rainfall amount and simulate the inundation area over the Ciliwung river basin. This preliminary study has been supported by Insinas - Ministry of Research and Technology.

Lockdown measures in response to the new Covid‐19 virus have caused the largest ever fall of annual greenhouse gas emissions. A key question that we attempt to answer in this study is which, if any, of these measures can be productively encouraged post‐lockdown in efforts to sustain at least part of this reduction in emissions. Sweden is uniquely suited for our study because the voluntary nature of lockdown in Sweden allowed us to assess the level of compliance to recommendations and its effects on greenhouse gas emissions. First, we assessed the change of perceived quality of life (QOL) among 746 individuals from Stockholm region due to adhering to lockdown measures. Second, we calculated the associated change of annual per capita greenhouse emissions. We found that avoiding travel for work, avoiding purchasing, and avoiding restaurants had the least negative effect on QOL, and at the same time the largest positive effect on carbon dioxide equivalent (CO2e) emission reductions. We conclude that these are potential leverage points for stimulating behavioral change that has a positive climatic impact., Key Points Lockdown measures in response to the new Covid‐19 virus have caused the largest ever fall of annual greenhouse gas emissionsAvoiding work travel, purchasing, and restaurants are associated with larger reductions in emissions and smaller impacts on quality of lifeThese measures are promising targets for sustaining greenhouse gas emissions post‐lockdown

Hydrometeorological disaster management in Indonesia such as floods, drought, tornadoes, etc., which occur almost every year in Indonesian territory, is carried out with structural efforts, however, it seems that the occurrence of disasters is still occurring even the intensity is increasing. To minimize the occurrence of hydrometeorological disasters, it is necessary to try a non-structural approach, namely the Weather Modification Technology (WMT). The application of WMT for hydrometeorological disaster mitigation can be used as an alternative solution in disaster risk reduction in Indonesia. The current WMT can be used to increase rainfall, to reduce rainfall, to mitigate floods and to reduce smoke due to forest and land fires. The application of WMT for additional rainfall is able to increase rainfall by about 30%, while to reduce rainfall, it can reduce rainfall by about 30-35%. This technology can be used as an integral part in the management of water resources in Indonesia.

The Linbeiken area is located in the village of Pingding, Taiwan. Since the Mindulle and Aere Typhoons in 2004, and as a result of the landslide triggered by the continuous heavy rainfall on 9 June 2006, there has been a persistent collapse of side slopes in the area. This paper describes the equipment that was installed to collect on-site topographic and hydrological information in the Linbeiken area upstream of the Pingding River and to monitor changes in the landslide area, as well as the measurements that were collected during the 2008 Typhoon Sinlaku. A case study of a landslide in Pingding, Taiwan was used to monitor the accurate coordinate changes in the potential landslide areas during typhoons. The goal of this study was to establish warning indexes, and to strengthen the software and hardware at the local disaster response center in the hope of gaining a full idea of the surface movement in landslide areas in future flood seasons. This is important for boosting the preparedness to adapt to landslide hazards, for improving disaster warnings, and for reporting efficiently to better protect the lives and property of local residents. The results show that the landslide disaster monitoring and warning system in Taiwan, as applied during Typhoon Sinlaku in 2008, is both effective and comprehensive.

Significant recent advances in satellite remote sensing allow environmental managers to detect and monitor cyanobacterial harmful algal blooms (cyanoHAB), and these capabilities are being used more frequently in water quality management. A quantitative estimate of the socioeconomic benefits generated from these new capabilities, known as an impact assessment, was missing from the growing literature on cyanoHABs and remote sensing. In this paper, we present an impact assessment framework to characterize the socioeconomic benefits of satellite remote sensing for detecting cyanoHABs and managing recreational advisories at freshwater lakes. We then apply this framework to estimate the socioeconomic benefits of satellite data that were used to manage a 2017 cyanoHAB event in Utah Lake. CyanoHAB events on Utah Lake can pose health risks to people who interact with the blooms through recreation. We find that the availability of satellite data yielded socioeconomic benefits by improving human health outcomes valued at approximately $370,000, though a sensitivity analysis reveals that this central estimate can vary significantly ($55,000–$1,057,000 in benefits) as a result of different assumptions regarding the time delay in posting a recreational advisory, the number of people exposed to the cyanoHAB, the number of people who experience gastrointestinal symptoms, and the cost per case of illness., Key Points Cyanobacterial harmful algal blooms (cyanoHABs) are a human health risk that is typically mitigated by recreational advisories and warningsWe present a framework to quantify the socioeconomic benefits of using remote sensing technology to test for the presence of cyanoHABsSatellite technology yielded between $55,000 and $1,057,000 in socioeconomic benefits associated with improved human health outcomes

All metropolitan cities in Japan are located in low-lying areas that surround ports. Accordingly, significant floods that occur in these cities will trigger the simultaneous occurrence of flooding by river water and inland flooding. However, existing studies have focused on the impact of flooding by river water, inland flooding, and high tide in tidal rivers, and disaster mitigation measures focused on detailed flooding processes in such flooding areas have not been conducted thus far. This study focused on a tidal river, i.e., Katabira River of Yokohama city, one of Japan&rsquo, s metropolitan cities, to construct a simultaneous occurrence model of flooding by river water and inland flooding, including the impact of a high tide. Numerical analysis was conducted using this model, and the results show that the flooded area significantly changed from 0.004 to 0.149 km2 according to the tide level of the estuary. Moreover, by simultaneously solving the calculation of flooding by river water and inland flooding, we found that there was a difference of 50 min between the occurrences of these floods. Therefore, we found that there is a possibility that, if evacuation is not conducted at the time of occurrence of inland flooding, evacuation during subsequent river-water flooding may not be possible. Based on these results, our proposed method was found to be useful for tidal rivers of metropolitan cities.

In this paper, we propose a simple algorithm for detecting a vehicle trapped in flooded urban area by using quad-polarimetric SAR data. The four-component scattering power decomposition and phase difference of HH-VV co-pol ratio are effectively used in the proposed algorithm. Here we carry out polarimetric scattering measurement for a scaled vehicle model surrounded by two buildings model in an anechoic chamber, to acquire the quad-polarimetric SAR data. It is confirmed from the results of the image analysis for the measured SAR data that the proposed algorithm for vehicle detection works well even under severe environment where the vehicle is set in the shadow of the building and/or the alignment of the vehicle or the buildings is obliquely oriented to direction of the radar line of sight.

Contribution to water cycle and climate studies, disaster mitigation, and various operational applications, including weather forecast, fishery, and agriculture, is a big target of JAXA’s Earth observation missions. JAXA launched the Greenhouse-gases Observing SATellite-2 (GOSAT-2), which is a successor of the GOSAT satellite, in October 2018. GOSAT series satellites are a joint mission among Ministry of the Environment Government of Japan (MOE), National Institute for Environmental Studies (NIES) and JAXA to provide accurate measurement of greenhouse-gases for researchers and policymakers. Another series of satellites that contribute to water cycle and climate studies is the Global Change Observation Mission (GCOM). It consists of two satellite missions, GCOM-W (Water) and GCOM-C (Climate) and aims to provide comprehensive information of the Essential Climate Variables (ECVs) of atmosphere, ocean, land, cryosphere and ecosystem by combined information of optical and microwave imagers. The GCOM-W satellite carries the Advanced Microwave Scanning Radiometer 2 (AMSR2), a successor of AMSR-E on NASA’s EOS Aqua satellite, to monitor water-related variables. On the other hand, the GCOM-C satellite carries the Second-generation Global Imager (SGLI) to monitor various parameters related to carbon cycle and energy budget. In December 2019, we started development of the Global Observation SATellite for Greenhouse gases and Water Cycle (GOSAT-GW) that is a joint mission of AMSR2 follow-on (AMSR3) and GOSAT-2 follow-on to be launched in Japanese Fiscal Year (JFY) 2023. AMSR3 will be almost equivalent capability to that of AMSR2 except additional high-frequency channels (166 & 183 GHz) for snowfall retrievals and numerical weather prediction. For water cycle studies, JAXA and NASA led the Global Precipitation Measurement (GPM) mission under international partnership. JAXA provides the Dual-frequency Precipitation Radar (DPR) onboard the GPM core observatory and GCOM-W for the GPM mission to provide high-frequent and accurate global precipitation observation. One of its major outcomes is the Global Satellite Mapping of Precipitation (GSMaP), which is a set of hourly merged-satellite global precipitation products. In June 2019, we have released GSMaP realtime version (GSMaP_NOW) with 0-hour latency over global area, while near-real-time version (GSMaP_NRT) is 4-hour latency. GSMaP is especially used in areas where ground observation capability is not enough, such as isolated islands and developing countries, for heavy rainfall and tropical cyclone monitoring. For land monitoring and disaster mitigation, including flood plain detection, JAXA currently operates the Advanced Land Observing Satellite-2 (ALOS-2) carrying Synthetic Aperture Radar (SAR). Two ALOS series satellites are waiting for launch in near future -- ALOS-3 carrying advanced optical imager to be launched in JFY2020 and ALOS-4 carrying advanced SAR is to be launched in JFY2021. Combination use of multi-satellite and numerical models is one of JAXA’s targets to expand satellite data utilization in various fields. JAXA collaborates with Japan Meteorological Agency (JMA) in various operational applications. The recent outcome in this collaboration is that JMA will start operational data assimilation of Himawari-8 aerosol products into model for aerosol forecasts in January 2020. Further collaboration with model communities are underway to utilize multi-satellite data into various models for better monitoring and forecasts.

The forest development has consistently increased that Korea is composed of almost 64% mountain area. The large-scale facilities, like a wind power system foundation, are planned along the top of mountain. As installation of the large-scale facilities, there is a potential risk in the mountain area like landslide, debris flow and so on. Therefore, we has performed some assessments to slopes and streams at mountain areas and roads of a wind power system foundation, which is being a large-scale change topography (1. Risk assessment using GIS analysis and design data, 2. Basic investigation research and detailed investigation research based on a standard from authorities, 3. Vulnerability analysis using a numerical analysis and a quantitative criteria). As a result, we are able to investigate a primary cause for a mountain disaster risk, and establish a planning of disaster mitigation facilities, which are consistent with a local and a geographical characteristic, for the mountain area involved potential risk.

Deep uncertainty describes situations when there is either ignorance or disagreement over (1) models used to describe key system processes and (2) probability distributions used to characterize the uncertainty of key variables and parameters. Future projections of Antarctic ice sheet (AIS) mass loss remain characterized by deep uncertainty. This complicates decisions on long‐lived coastal protection projects when determining what margin of safety to implement. If the chosen margin of safety does not properly account for uncertainties in sea level rise, the effectiveness of flood protection could decrease over time, potentially putting lives and properties at a greater risk. To address this issue, we develop a flood damage allowance framework for calculating the height of a flood protection strategy needed to ensure that a given level of financial risk is maintained. The damage allowance framework considers decision maker preferences such as planning horizons, protection strategies, and subjective views of AIS stability. We use Manhattan—with the population and built environment fixed in time—to illustrate how our framework could be used to calculate a range of damage allowances based on multiple plausible scenarios of AIS melt. Under high greenhouse gas emissions, we find that results are sensitive to the selection of the upper limit of AIS contributions to sea level rise. Design metrics that specify financial risk targets, such as expected flood damage, allow for the calculation of avoided flood damages (i.e., benefits) that can be combined with estimates of construction cost and then integrated into existing financial decision‐making approaches (e.g., benefit‐cost analysis)., Key Points Not accounting for sea-level rise when designing ood protection could cause the originally selected margin of safety to decrease over timeDamage allowances provide the heights of flood protection strategies needed to maintain the expected flood damage as sea levels riseBenefit‐cost analysis used for flood protection decision‐making should consider multiple scenarios of Antarctic ice sheet melt

Buildings in seismic zones are required to provide proper stiffness and load-bearing capacity to resist frequent earthquakes, and possess proper ductility and energy-dissipating capacity to prevent collapse under rare earthquakes. To meet these requirements, the concept of structural energy-dissipation techniques for the bi-functions of load-bearing and energy dissipating are proposed. A number of structural metal energy-dissipation elements, such as buckling-restrained steel plate shear walls, non-buckling corrugated steel plate shear walls, two-level yielding steel coupling beams and energy-dissipative columns, have been developed. They are designed to provide stiffness/strength to guarantee the operation of buildings under frequent earthquakes, but also dissipate energy to reduce seismic effects to a considerable extent for collapse-prevention of buildings. The experimental and theoretical studies on these structural metal energy-dissipating dampers are presented. The efficiency of these structural dampers for disaster mitigation of buildings against earthquakes are also presented to provide a reference for their practical application.

Tropical cyclone (TC) disaster loss assessment is an important and difficult problem in TC prevention and disaster mitigation. Few studies have focused on combined model in this area. This study introduced a new combination model method to predict TC disaster loss, taking Guangdong province as an example. We analysed and collected 67 TC data from 1993 to 2009, which had impact on Guangdong province, in which 60 were randomly for training data and another 7 were for testing data. We conducted three models – GA–Elman neural networks, support vector regression (SVR) and generalized regression neural networks (GRNN), and the root mean square error (RMSE) value we got are 5.05, 7.85 and 3.82, respectively. Then the three models are combined into a comprehensive evaluation model by model combination method. The RMSE of the test results is 3.30. The results show that the combined model is superior to one individual model and it is a more accurate and stable method.

Seismic instrumentation for earthquake early warnings (EEWs) has improved significantly in the last few years, considering the station coverage, data quality, and the related applications. The official EEW system in Taiwan is operated by the Central Weather Bureau (CWB) and is responsible for issuing the regional warning for moderate-to-large earthquakes occurring in and around Taiwan. The low-cost micro-electro-mechanical system (MEMS)-based P-Alert EEW system is operational in Taiwan for on-site warnings and for producing shakemaps. Since 2010, this P-Alert system, installed by the National Taiwan University (NTU), has shown its importance during various earthquakes that caused damage in Taiwan. Although the system is capable of acting as a regional as well as an on-site warning system, it is particularly useful for on-site warning. Using real-time seismic signals, each P-Alert system can provide a 2–8 s-long warning time for the locations situated in the blind zone of the CWB regional warning system. The shakemaps plotted using this instrumentation help to assess the damage pattern and rupture directivity, a key feature in the risk mitigation process. These shakemaps are delivered to the intended users, including the disaster mitigation authorities, for possible relief purposes. Earlier, the network provided only peak ground acceleration (PGA) shakemaps, but has now been updated to include peak ground velocity (PGV), spectral acceleration (Sa) at different periods, and CWB intensity maps. The PGA and PGV shakemaps plotted using this network have proven helpful in establishing the fact that PGV is a better indicator of damage detection than PGA. This instrumentation is also useful in structural health-monitoring and estimating co-seismic deformations. Encouraged by the performance of the P-Alert network, more instruments are installed in Asia-Pacific countries.

In the Southeast Sulawesi region, the area most frequently experiencing drought and clean water crises is Dana Sub-District, Watopute District, Muna Regency. This disaster was caused by physical and social factors. This study aims to describe the mitigation efforts of drought and clean water crisis in the Dana Sub-District, Watopute District. This research uses descriptive qualitative research methods. The population in this study were all the heads of families in Dana Sub-District, totaling 604 people. The sample in this study was selected using simple random sampling technique where the sample was randomly selected as much as 10% of the total population, so the sample in this study was 60 people. The results showed that the drought and water crisis in the Dana Sub-District, Watopute District occurred due to climate change and geomorphological conditions of the area as well as the lack of cooperation in the community in paying water bills. The peak of drought and clean water crisis in this region often occurs from July to November. To overcome this, various efforts have been made by the community, for example taking water from rivers and springs, buying clean water, and collecting water in storage tanks. Furthermore, the local government has also issued several policies, namely the development of the District Capital City Drinking Water Supply System and procurement of water pumps from springs, but according to the local community these government policies have not been effective. Furthermore, water dropping is also not maximally done because the community is less cooperative in paying water bills.

The purpose of the research is to develop a Real-Time Landslide Early Disaster Mitigation Warning System with the ADXL345 Gyroscope Sensor and to know the exact system designed in a prototype. The method used is research and development with a prototyping model which is divided into several stages, namely stage (1) problems, (2) data collection, (3) prototype design, (4) prototype testing, and (5) production. The resulting system is a prototype based on an Arduino microcontroller called “ERT-Ladister” with an ADXL345 Gyroscope sensor. Other features include SMS-Gateway, buzzer, and Monitoring via Monitor. Based on the feasibility test and the effectiveness test on a lab scale and field scale, it can be concluded that the system is feasible and effective. The value of the effectiveness test shows that there is a significant difference between before the system is installed and after the system is installed in field trials. The Real-Time Landslide Early Disaster Mitigation Warning System can increase community awareness around landslide-prone areas.

Based on the statistical data of rainstorm-induced catastrophe about Shenzhen city during 1980–2014, this paper constructs a calculation model of disaster magnitude, which includes three influence factors: death toll, direct economic loss and disaster affected population. At the same time, the relationship between the disaster magnitude and the temporal, spatial and cause of the rainstorm-induced catastrophe about Shenzhen city is analysed, The results show that (1) The classification of catastrophe risk is carried out by the result of the disaster magnitude model. (2) The region where the disaster occurs frequently and seriously is located in the Midwest, and the disaster occurs infrequently and lightly is located in the south-east. (3) The rainstorm-induced catastrophe about Shenzhen City is mostly caused by persistent short-time heavy rainfall. While it occurs most frequently in July, and the most serious in September affected by the typhoon. (4) The main reasons for the occurrence of rainstorm-induced catastrophe about Shenzhen City are flood, waterlogging, tide and typhoon, of these factors waterlogging is the primary one. Finally, this paper puts forward the corresponding countermeasures of flood hazard mitigation in Shenzhen City.

This paper is retracted by editor due to publication ethics missconducted by author (simultaneously publication in other journal).