. Probabilistic hazard assessments are a fundamental tool for assessing the threats posed by hazards to communities and are important for underpinning evidence-based decision-making regarding risk mitigation activities. Indonesia has been the focus of intense tsunami risk mitigation efforts following the 2004 Indian Ocean tsunami, but this has been largely concentrated on the Sunda Arc with little attention to other tsunami prone areas of the country such as eastern Indonesia. We present the first nationally consistent probabilistic tsunami hazard assessment (PTHA) for Indonesia. This assessment produces time-independent forecasts of tsunami hazards at the coast using data from tsunami generated by local, regional and distant earthquake sources. The methodology is based on the established monte carlo approach to probabilistic seismic hazard assessment (PSHA) and has been adapted to tsunami. We account for sources of epistemic and aleatory uncertainty in the analysis through the use of logic trees and sampling probability density functions. For short return periods (100 years) the highest tsunami hazard is the west coast of Sumatra, south coast of Java and the north coast of Papua. For longer return periods (500–2500 years), the tsunami hazard is highest along the Sunda Arc, reflecting the larger maximum magnitudes. The annual probability of experiencing a tsunami with a height of > 0.5 m at the coast is greater than 10% for Sumatra, Java, the Sunda islands (Bali, Lombok, Flores, Sumba) and north Papua. The annual probability of experiencing a tsunami with a height of > 3.0 m, which would cause significant inundation and fatalities, is 1–10% in Sumatra, Java, Bali, Lombok and north Papua, and 0.1–1% for north Sulawesi, Seram and Flores. The results of this national-scale hazard assessment provide evidence for disaster managers to prioritise regions for risk mitigation activities and/or more detailed hazard or risk assessment.

https://nhess.copernicus.org/articles/14/3105/2014/nhess-14-3105-2014.pdf

A probabilistic tsunami hazard assessment for Indonesia

Remote sensing data and methods are widely deployed in order to contribute to the assessment of numerous components of earthquake risk. While for earthquake hazard-related investigations, the use of remotely sensed data is an established methodological element with a long research tradition, earthquake vulnerability–centred assessments incorporating remote sensing data are increasing primarily in recent years. This goes along with a changing perspective of the scientific community which considers the assessment of vulnerability and its constituent elements as a pivotal part of a comprehensive risk analysis. Thereby, the availability of new sensors systems enables an appreciable share of remote sensing first. In this manner, a survey of the interdisciplinary conceptual literature dealing with the scientific perception of risk, hazard and vulnerability reveals the demand for a comprehensive description of earthquake hazards as well as an assessment of the present and future conditions of the elements exposed. A review of earthquake-related remote sensing literature, realized both in a qualitative and quantitative manner, shows the already existing and published manifold capabilities of remote sensing contributing to assess earthquake risk. These include earthquake hazard-related analysis such as detection and measurement of lineaments and surface deformations in pre- and post-event applications. Furthermore, pre-event seismic vulnerability–centred assessment of the built and natural environment and damage assessments for post-event applications are presented. Based on the review and the discussion of scientific trends and current research projects, first steps towards a roadmap for remote sensing are drawn, explicitly taking scientific, technical, multi- and transdisciplinary as well as political perspectives into account, which is intended to open possible future research activities.

Remote sensing contributing to assess earthquake risk: from a literature review towards a roadmap

Forecasting and early warning systems are important investments to protect lives, properties, and livelihood. While early warning systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services, or financial loss. Complementing early warning systems with impact forecasts has a twofold advantage: It would provide decision makers with richer information to take informed decisions about emergency measures and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multihazard early warning systems. This review discusses the state of the art in impact forecasting for a wide range of natural hazards. We outline the added value of impact‐based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe. Plain Language Summary Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While such systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, they rarely provide impact estimates, such as the expected physical damage, human consequences, disruption of services, or financial loss. Extending hazard forecast systems to include impact estimates promises many benefits for the emergency phase, for instance, for organizing evacuations. We review and compare the state of the art of impact forecasting across a wide range of natural hazards and outline opportunities and key challenges for research and development of impact forecasting.

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2020RG000704

Impact Forecasting to Support Emergency Management of Natural Hazards

Natural hazard risk is largely projected to increase in the future, placing growing responsibility on decision makers to proactively reduce risk. Consequently, decision support systems (DSSs) for natural hazard risk reduction (NHRR) are becoming increasingly important. In order to provide directions for future research in this growing area, a comprehensive classification system for the review of NHRR-DSSs is introduced, including scoping, problem formulation, the analysis framework, user and organisational interaction with the system, user engagement, monitoring and evaluation. A review of 101 papers based on this classification system indicates that most effort has been placed on identifying areas of risk and assessing economic consequences resulting from direct losses. However, less effort has been placed on testing risk-reduction options and considering future changes to risk. Furthermore, there was limited evidence within the reviewed papers on the success of DSSs in practice and whether stakeholders participated in DSS development and use. Classification system of different aspects of natural hazard risk-reduction DSSs.Aspects covered are scoping, analysis, user interaction, monitoring and evaluation.Review of 101 papers detailing 77 DSSs using proposed classification system.Good coverage of hydrological hazards, structural mitigation and economic impact.Limited coverage of multiple hazards, future impacts and DSS use and evaluation.

/pdf/review-of-literature-on-decision-support-systems-for-natural-3yyndftamh.pdf

Review of literature on decision support systems for natural hazard risk reduction

Earthquakes are natural phenomena, which induce natural hazard that seriously threatens urban areas, despite significant advances in retrofitting urban buildings and enhancing the knowledge and ability of experts in natural disaster control Iran is one of the most seismically active countries in the world The purpose of this study was to evaluate and analyze the extent of earthquake vulnerability in relation to demographic, environmental, and physical criteria An earthquake risk assessment (ERA) map was created by using a Fuzzy-Analytic Hierarchy Process coupled with an Artificial Neural Networks (FAHP-ANN) model generating five vulnerability classes Combining the application of a FAHP-ANN with a geographic information system (GIS) enabled to assign weights to the layers of the earthquake vulnerability criteria The model was applied to Sanandaj City in Iran, located in the seismically active Sanandaj-Sirjan zone which is frequently affected by devastating earthquakes The Multilayer Perceptron (MLP) model was implemented in the IDRISI software and 250 points were validated for grades 0 and 1 The validation process revealed that the proposed model can produce an earthquake probability map with an accuracy of 95% A comparison of the results attained by using a FAHP, AHP and MLP model shows that the hybrid FAHP-ANN model proved flexible and reliable when generating the ERA map The FAHP-ANN model accurately identified the highest earthquake vulnerability in densely populated areas with dilapidated building infrastructure The findings of this study are useful for decision makers with a scientific basis to develop earthquake risk management strategies

Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

. In the framework of the German Indonesian Tsunami Early Warning System (GITEWS) the assessment of tsunami risk is an essential part of the overall activities. The scientific and technical approach for the tsunami risk assessment has been developed and the results are implemented in the national Indonesian Tsunami Warning Centre and are provided to the national and regional disaster management and spatial planning institutions in Indonesia. The paper explains the underlying concepts and applied methods and shows some of the results achieved in the GITEWS project (Rudloff et al., 2009). The tsunami risk assessment has been performed at an overview scale at sub-national level covering the coastal areas of southern Sumatra, Java and Bali and also on a detailed scale in three pilot areas. The results are provided as thematic maps and GIS information layers for the national and regional planning institutions. From the analyses key parameters of tsunami risk are derived, which are integrated and stored in the decision support system of the national Indonesian Early Warning Centre. Moreover, technical descriptions and guidelines were elaborated to explain the developed approach, to allow future updates of the results and the further development of the methodologies, and to enable the local authorities to conduct tsunami risk assessment by using their own resources.

/pdf/tsunami-risk-assessment-in-indonesia-4kd7maufnk.pdf

Tsunami risk assessment in Indonesia

Kwatisore waters in the Cenderawasih Bay National Park area is one of the whale sharks’ habitats in Indonesia. As shark sightings seem to occur daily there is the opportunity for ecotourism development in the area. This study aims to quantify the occurrence of whale sharks at Kwatisore, and estimate the carrying capacity of the area, together with its suitability for ecotourism based on whale shark aggregations. Primary data collection on the appearance of whale sharks was carried out every day through a census technique on 7 designated areas (Apr to Aug, 2022). Every whale shark that appears on the surface of the water is photographed and identified by an ID number based on the I3Sv2.0 and its sex determined. During the census period, 709 whale sharks’ sightings were recorded mostly in the morning. There were 15 individuals in total, all males with a total length ranging from 3-7 m. The carrying capacity of the area for whale shark ecotourism in Kwatisore waters is a maximum of 252 people per day who are allowed to interact with whale sharks, while the tourism suitability index is included in the very appropriate category for whale shark tourism.

Occurrence of whale sharks (Rhincodon typus) in the Kwatisore Waters within the Cenderawasih Bay National Park as a basis for carrying capacity estimations and assessments for ecotourism suitability

The purpose of this study was to determine the extent of forest land change due to deforestation and forest degradation in Manokwari Regency as a development activity through land cover dynamics using satellite imagery data and make a land change prediction based on land change data analysis. This study used a descriptive method with an analysis of land cover changes using an overlay technique to determine land cover change. The results showed the change in land cover that occurred during the period 2009-2017 is dominated by changing of forested land to become settlement and plantation areas. The land cover has experienced a significant change in primary dryland forest, where nearly four thousand hectares of forest land have experienced degradation and deforestation. The land use prediction in 2025 was a reduction of the dry land forested area by about 9.1% while plantation and settlement were increased by about 4.5% and 2.0% respectively. Based on the comparison results, it was found that the predicted land use of Manokwari Regency in 2025 has land use suitability with the Regional Spatial Planning of 85.87%, not suitable at 6.8 %, and land use that allows for change at 7.33%.

/pdf/land-use-and-land-cover-change-in-manokwari-west-papua-1xoioqgu.pdf

Sumaryono

Papers

Tsunami risk assessment in Indonesia

Occurrence of whale sharks (Rhincodon typus) in the Kwatisore Waters within the Cenderawasih Bay National Park as a basis for carrying capacity estimations and assessments for ecotourism suitability

Land use and land cover change in Manokwari, West Papua Province