Hazard Assessment Process Research Articles

An overview of the preparation and implementation of the safety case in support of the 2nd JET deuterium–tritium experiment

An overview of the preparation and implementation of the JET 2nd deuterium-tritium experiment (DTE2) safety case is presented. The safety case regime, developed by UKAEA for fusion applications to demonstrate compliance with relevant regulations, and its implementation on UKAEA sites is outlined. The hazard assessment process and details of the methodology applied to assess key JET fault scenarios are provided. An outline of key inventories, their composition, and applied factors for consequence and risk assessment are discussed. The consequences resulting from key fault sequences, the designation of appropriate safety measures and the associated risks are summarised and compared against basic safety limits and objectives. Finally, some of the lessons learned from DTE2 following implementation are discussed.

Systematic Approaches for the Encoding of Chemical Groups: A Case Study.

Regulatory authorities aim to organize substances into groups to facilitate prioritization within hazard and risk assessment processes. Often, such chemical groupings are not explicitly defined by structural rules or physicochemical property information. This is largely due to how these groupings are developed, namely, a manual expert curation process, which in turn makes updating and refining groupings, as new substances are evaluated, a practical challenge. Herein, machine learning methods were leveraged to build models that could preliminarily assign substances to predefined groups. A set of 86 groupings containing 2,184 substances as published on the European Chemicals Agency (ECHA) website were mapped to the U.S. Environmental Protection Agency (EPA) Distributed Toxicity Structure Database (DSSTox) content to extract chemical and structural information. Substances were represented using Morgan fingerprints, and two machine learning approaches were used to classify test substances into 56 groups containing at least 10 substances with a structural representation in the data set: k-nearest neighbor (kNN) and random forest (RF), that led to mean 5-fold cross-validation test accuracies (average F1 scores) of 0.781 and 0.853, respectively. With a 9% improvement, the RF classifier was significantly more accurate than KNN (p-value = 0.001). The approach offers promise as a means of the initial profiling of new substances into predefined groups to facilitate prioritization efforts and streamline the assessment of new substances when earlier groupings are available. The algorithm to fit and use these models has been made available in the accompanying repository, thereby enabling both use of the produced models and refitting of these models, as new groupings become available by regulatory authorities or industry.

Carcinogenic Chemicals in Occupational Settings: A Tool for Comparison and Translation between Different Classification Systems

In the European Union, Occupational Safety and Health legislation generally refers to European Regulation (CE) n. 1272/2008 to define and classify carcinogens of concern for occupational risk assessment and exposure assessment. In Europe, the current reference is Directive (UE) 2022/431, regarding carcinogen, mutagen, and reprotoxic agent (CMR) exposure. However, at the worldwide level, different classification approaches are used to establish carcinogenicity of substances and it is often difficult to compare the classifications of carcinogenicity (CoCs) proposed by different international bodies. This study aims to investigate a list of carcinogens of concern in occupational settings based on the CLP (Classification Labelling Packaging) CoC and to create a tool that allows a rapid translation–comparison of some international CoCs with the reference one. CoCs proposed by various sources were consulted and used to apply a translation method, to favor an alignment of different CoCs according to a reference. Results outlined that, considering diverse sources, CoCs can result in different classifications of the same chemicals. Overall, this may have implications for the hazard assessment process, which is the base of risk assessment. The proposed tool is expected to help risk assessors in the occupational field when it is needed to have a comparison with different CoC systems.

Fusion calorimetric experiments and QSPR modeling to inversely explore the accuracy of thermodynamic methods: A case study of the apparent activation energies of 18 aromatic nitro compounds

The choice of thermodynamic analysis method will directly affect the accuracy of thermal hazard assessment. In this work, two advanced calorimetric experiments were used to obtain the pyrolysis parameters of 18 aromatic nitro compounds under dynamic and adiabatic conditions, aiming at the inherent thermal risk and explosion characteristics of aromatic nitro compounds in important chemical processes. The multiple linear regression (MLR) and artificial neural network (ANN) models corresponding to six typical thermodynamic analysis methods (FWO, Kissinger, Starink, Friedman, Townsend, and TMRad) were constructed by using the apparent activation energy (Ea) calculated by fitting as the basic sample data and combining with quantitative structure-property relationship (QSPR). Two kinds of parameters in internal and external validation were used as the main indexes to judge the accuracy and reliability of different kinetic analysis methods applied to aromatic nitro compounds. This study is expected to provide theoretical support and technical guidance for the chemical industry in the thermal hazard assessment process of nitro compounds.

A simple method for landslide risk assessment in the Rivière Aux Vases basin, Quebec, Canada

This research offers a simple approach for landslide risk assessment on a basin-scale in the Quebec Province of Canada, where landslides are common. Landslide inventory and distribution mapping are developed for the Aux Vases Watershed, the most landslide-affected area in the Saguenay region, for a detailed landslide hazard and risk assessment process. The study uses publicly available data from Google Earth images, published literature, Government data sources for topographic maps and landuse information, as well as the 2016 Census Profile of the Saguenay region of Quebec. ArcGIS software is used for spatial data processing and analyzing datasets to develop maps of landslide susceptibility, vulnerability, and lack of coping capacity, and a landslide risk map of the Aux Vases Watershed was developed. Landslide risk assessment is critical for minimizing the loss of life and property from potential landslides in the study area and empowers communities with useful information so they can make informed decisions to mitigate the risk and build coping capacities. In addition, risk reduction policies and strategies, public safety, and future development planning initiatives will benefit from this research.

Grouping MWCNTs based on their similar potential to cause pulmonary hazard after inhalation: a case-study

BackgroundThe EU-project GRACIOUS developed an Integrated Approach to Testing and Assessment (IATA) to support grouping high aspect ratio nanomaterials (HARNs) presenting a similar inhalation hazard. Application of grouping reduces the need to assess toxicity on a case-by-case basis and supports read-across of hazard data from substances that have the data required for risk assessment (source) to those that lack such data (target). The HARN IATA, based on the fibre paradigm for pathogenic fibres, facilitates structured data gathering to propose groups of similar HARN and to support read-across by prompting users to address relevant questions regarding HARN morphology, biopersistence and inflammatory potential. The IATA is structured in tiers, allowing grouping decisions to be made using simple in vitro or in silico methods in Tier1 progressing to in vivo approaches at the highest Tier3. Here we present a case-study testing the applicability of GRACIOUS IATA to form an evidence-based group of multiwalled carbon nanotubes (MWCNT) posing a similar predicted fibre-hazard, to support read-across and reduce the burden of toxicity testing.ResultsThe case-study uses data on 15 different MWCNT, obtained from the published literature. By following the IATA, a group of 2 MWCNT was identified (NRCWE006 and NM-401) based on a high degree of similarity. A pairwise similarity assessment was subsequently conducted between the grouped MWCNT to evaluate the potential to conduct read-across and fill data gaps required for regulatory hazard assessment. The similarity assessment, based on expert judgement of Tier 1 assay results, predicts both MWCNT are likely to cause a similar acute in vivo hazard. This result supports the possibility for read-across of sub-chronic and chronic hazard endpoint data for lung fibrosis and carcinogenicity between the 2 grouped MWCNT. The implications of accepting the similarity assessment based on expert judgement of the MWCNT group are considered to stimulate future discussion on the level of similarity between group members considered sufficient to allow regulatory acceptance of a read-across argument.ConclusionThis proof-of-concept case-study demonstrates how a grouping hypothesis and IATA may be used to support a nuanced and evidence-based grouping of ‘similar’ MWCNT and the subsequent interpolation of data between group members to streamline the hazard assessment process.

Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating snowpack model output for avalanche forecasting

Abstract. Snowpack models simulate the evolution of the snow stratigraphy based on meteorological inputs and have the potential to support avalanche risk management operations with complementary information relevant for their avalanche hazard assessment, especially in data-sparse regions or at times of unfavorable weather and hazard conditions. However, the adoption of snowpack models in operational avalanche forecasting has been limited, predominantly due to missing data processing algorithms and uncertainty around model validity. Thus, to enhance the usefulness of snowpack models for the avalanche industry, numerical methods are required that evaluate and summarize snowpack model output in accessible and relevant ways. We present algorithms that compare and assess generic snowpack data from both human observations and models, which consist of multidimensional sequences describing the snow characteristics of grain type, hardness, and age. Our approach exploits Dynamic Time Warping, a well-established method in the data sciences, to match layers between snow profiles and thereby align them. The similarity of the aligned profiles is then evaluated by our independent similarity measure based on characteristics relevant for avalanche hazard assessment. Since our methods provide the necessary quantitative link to data clustering and aggregating methods, we demonstrate how snowpack model output can be grouped and summarized according to similar hazard conditions. By emulating aspects of the human avalanche hazard assessment process, our methods aim to promote the operational application of snowpack models so that avalanche forecasters can begin to build an understanding of how to interpret and trust operational snowpack simulations.

Quality issues related to the presence of the fish parasitic nematode Hysterothylacium aduncum in export shipments of fresh Northeast Arctic cod (Gadus morhua)

The parasitic nematode Hysterothylacium aduncum commonly occurs in many fish species in the Northeast (NE) Atlantic. The parasite is considered non-pathogenic to humans. During spring and summer of 2018, lots of head-on eviscerated fresh NE Arctic cod (Gadus morhua) were shipped from Norway to Spain for commercialization. At arrival, the presence of lively roundworms (i.e. H. aduncum) in the transporting boxes was noticed. Consequently, fish lots were rejected causing substantial monetary losses to all involved parties. As part of the hazard assessment process, the epidemiology of H.aduncum in cod, NE Arctic saithe (Pollachius virens) and NE Arctic haddock (Melanogrammus aeglefinus) fished off West-Finnmark, Norway, was studied. Parasites were morphologically and molecularly identified to species level. Additionally, the viability of H. aduncum was assessed by simulating the conditions that prevail during transport of fresh cod to European market. The infection values of L4 larval stage or adult H. aduncum in the digestive tract of fish were highly variable, ranging from 100% prevalence with mean abundance (range) 238 (10–1092) in cod to 27% prevalence with mean abundance (range) 1 (0–22) in haddock. Fishing season was identified as most important explanatory factor for parasite abundance. Infection levels were higher during winter and early spring, and lower during late spring. Infection peaks of H. aduncum in the three fish species seemed to coincide with heavy predation on spawning capelin (Mallotus villosus) during winter and early spring. Thorough evisceration seems to remove most of the nematodes from the fish. However, parasites may remain hidden within the head cavities where they can stay alive and active under regular transport conditions for at least 14 days. Hysterothylacium aduncum can be completely removed from the product by evisceration, beheading and rinsing the fish prior to shipping. Alternatively, thorough cleaning or completely removal of the gills and pharynx may be considered.

Alignment of the Safety Assessment Method with New Zealand Legislative Responsibilities

Need—National legislative health and safety (H&S) frameworks impose requirements but grant self-management to organisations. Consequently variability arises in management systems, and some organisations struggle to achieve successful implementation. The risk assessment process is key to the H&S management system, and could benefit from greater consistency and better external alignment with the legislative framework of the jurisdiction. Approach—The harm categories in the New Zealand (NZ) Act were adapted into a consequence scale. A non-linear scale was developed for the consequence axis to represent the disproportional nature of catastrophic harm outcomes compared to minor injuries. A hazard assessment process was devised based on systems engineering methods. Organisational decision-criteria were derived from the communications requirement in the Act, and these thresholds linked to expected treatments. Originality—A method is providing for aligning risk assessments with a national legislative framework, and integrating the technical aspects of risk assessment with the management processes. The approach also more explicitly includes recovery actions in contrast to existing methods where prevention dominates. Regarding the management aspects, it shows how thresholds may be defined relative to the legislation, to give clear expectations regarding treatment and internal communication, thereby assisting executives (‘officers’ in terms of the NZ Act) meet their duties.

Correlation of IRTAM and FPMU data confirming the application of IRTAM to support ISS Program safety

A “Real-Time” plasma hazard assessment process was developed to support International Space Station (ISS) Program real-time decision-making providing solar array constraint relief information for Extravehicular Activities (EVAs) planning and operations. This process incorporates real-time ionospheric conditions, ISS solar arrays’ orientation, ISS flight attitude, and where the EVA will be performed on the ISS. This assessment requires real-time data that is presently provided by the Floating Potential Measurement Unit (FPMU) which measures the ISS floating potential (FP), along with ionospheric electron number density (Ne) and electron temperature (Te), in order to determine the present ISS environment. Once the present environment conditions are correlated with International Reference Ionosphere (IRI) values, IRI is used to forecast what the environment could become in the event of a severe geomagnetic storm. If the FPMU should fail, the Space Environments team needs another source of data which is utilized to support a short-term forecast for EVAs. The IRI Real-Time Assimilative Mapping (IRTAM) model is an ionospheric model that uses real-time measurements from a large network of digisondes to produce foF2 and hmF2 global maps in 15 min cadence. The Boeing Space Environments team has used the IRI coefficients produced in IRTAM to calculate the Ne along the ISS orbital track. The results of the IRTAM model have been compared to FPMU measurements and show excellent agreement. IRTAM has been identified as the FPMU back-up system that will be used to support the ISS Program if the FPMU should fail.

Principles and procedures for handling out-of-domain and indeterminate results as part of ICH M7 recommended (Q)SAR analyses

The International Council for Harmonization (ICH) M7 guideline describes a hazard assessment process for impurities that have the potential to be present in a drug substance or drug product. In the absence of adequate experimental bacterial mutagenicity data, (Q)SAR analysis may be used as a test to predict impurities’ DNA reactive (mutagenic) potential. However, in certain situations, (Q)SAR software is unable to generate a positive or negative prediction either because of conflicting information or because the impurity is outside the applicability domain of the model. Such results present challenges in generating an overall mutagenicity prediction and highlight the importance of performing a thorough expert review. The following paper reviews pharmaceutical and regulatory experiences handling such situations. The paper also presents an analysis of proprietary data to help understand the likelihood of misclassifying a mutagenic impurity as non-mutagenic based on different combinations of (Q)SAR results. This information may be taken into consideration when supporting the (Q)SAR results with an expert review, especially when out-of-domain results are generated during a (Q)SAR evaluation.

Human and veterinary antibiotics induce hormesis in plants: Scientific and regulatory issues and an environmental perspective

Veterinary and human pharmaceuticals have been widely used in the developed world, thus increasing their accumulation in the environment and thereby posing ecological risks. Earlier studies report that active pharmaceutical ingredients induce hormesis in plants, i.e. at low doses may enhance plant health whereas at high doses may suppress plant vigor. There is hitherto no study critically reviewing the effects of antibiotics on plants within a hormetic context despite effects of low doses on plants can have implications to animals, including humans, and to ecological processes. This study critically reviews for first time antibiotic-induced hormesis in plants, both quantitatively and qualitatively. Hormesis was induced by several antibiotics in a variety of species and endpoints. The maximum stimulatory response (MAX) was commonly <1.5-fold the control response and the distance from MAX to no-observed-adverse-effect level (NOAEL) was commonly up to 10–fold. Further quantitative and qualitative evaluations are provided and discussed in relation to scientific and regulatory aspects. Low doses of antibiotics are equally important as high doses as they can negatively affect plants, depending on plant tissues and the time tissues are subject to exposure. Antibiotic-induced hormesis in plants provides a significant environmental perspective and should be incorporated into the hazard and risk assessment process. CapsuleCommon antibiotics released in the environment induce hormesis in plants, urging for re-examination of the risk assessment practices by worldwide regulatory agencies.

Research on Safety Risk Pre-control Management System and Its Application in Coal Mines

In order to minimize safety accidents in coal mines, this paper starts from the basic theory on risk management, summarizing the status quo of work safety and existing problems in China’s coal mines. Based on the present safety risk pre-control management system of coal mines, a new safety risk pre-control management system satisfying hazard identification, assessment and management standard formulation process is designed. Through the implementation of the system, a systematic prevention management mechanism and effective preventive and control measures ensure that all kinds of safety dangers fall within the tolerable scope of coal mines.

Challenges of implementing integrated coastal zone management into local planning policies, a case study of Queensland, Australia

This review traces an almost 25-year history of implementing cornerstones of integrated coastal zone management (ICZM) and climate change adaption into the regulatory planning and decision-making in Queensland, Australia. It illustrates the seesawing changes between ICZM and the general planning policy and statutory framework to accommodate the political struggle of incorporating key climate change adaptation measures in sought after and economically important coastal areas. The result of this process is mixed. It could be best described as an almost total integration of ICZM into, rather than with, other legislation; and this has been accompanied by an ever-diminishing political focus on coastal management in favour of mostly project specific, generic risk and hazard assessment processes. This leaves local authorities with an even greater need of reliable and yet affordable scientific and legal tools, to effectively deal with these risks. The broader implication of the Queensland ICZM history certainly raises the question about the extent of integration that is desirable for coastal zone management, notably in conjunction with the ongoing debate about climate change adaptation. Although the State government has recently introduced a new climate change adaptation strategy and is financially supporting coastal local government in developing long-term adaptation plans, the concept of ICZM in Queensland should be revisited. In other words, there is still a need for practical approaches of implementing ICZM into existing regulatory planning, pollution control, natural resource management and biodiversity conservation frameworks.

Empirical Correlation between Inelastic and Elastic Spectral Displacement Demands

Inelastic spectral displacement demand is arguably one of the most effective, simplified means of relating earthquake intensity to building damage. However, seismic hazard assessment is typically conducted using empirical ground-motion prediction equations (GMPEs) that only provide indications of elastic spectral response quantities, which an engineer subsequently relates to inelastic demands using empirical relationships such as the equal-displacement rule. An alternative approach is to utilize relationships for the inelastic spectral displacement demand directly within the seismic hazard assessment process. Such empirical relationships are developed in this work, as a function of magnitude, distance, building period, and yield strength coefficient, for four different hysteretic models that are representative of a wide range of possible structural typologies found in practice. The new relationships are likely to be particularly useful for performance-based seismic design and assessment.

Influence of expertise on rockfall hazard assessment using empirical methods

Abstract. To date, many rockfall hazard assessment methods still consider qualitative observations within their analysis. Based on this statement, knowledge and expertise are supposed to be major parameters of rockfall assessment. To test this hypothesis, an experiment was carried out in order to evaluate the influence of knowledge and expertise on rockfall hazard assessment. Three populations were selected, having different levels of expertise: (1) students in geosciences, (2) researchers in geosciences and (3) confirmed experts. These three populations evaluated the rockfall hazard level on the same site, considering two different methods: the Laboratoire des Ponts et Chaussées (LPC) method and a method partly based on the "slope mass rating" (SMR) method. To complement the analysis, the completion of an "a priori" assessment of the rockfall hazard was requested of each population, without using any method. The LPC method is the most widely used method in France for official hazard mapping. It combines two main indicators: the predisposition to instability and the expected magnitude. Reversely, the SMR method was used as an ad hoc quantitative method to investigate the effect of quantification within a method. These procedures were applied on a test site divided into three different sectors. A statistical treatment of the results (descriptive statistical analysis, chi-square independent test and ANOVA) shows that there is a significant influence of the method used on the rockfall hazard assessment, whatever the sector. However, there is a non-significant influence of the level of expertise of the population the sectors 2 and 3. On sector 1, there is a significant influence of the level of expertise, explained by the importance of the temporal probability assessment in the rockfall hazard assessment process. The SMR-based method seems highly sensitive to the "site activity" indicator and exhibits an important dispersion in its results. However, the results are more similar with the LPC qualitative method, even in the case of sector 1.

Lahars in Java: Initiations, Dynamics, Hazard Assessment And Deposition Processes

Lahar has been applied as a general term for rapidly flowing, high-concentration, poorly sorted sediment-laden mixtures of rock debris and water (other than normal streamflow) from a volcano. Lahars are one of the most destructive phenomena associated with composite volcanoes, which are dominant in Java Island. Resulting deposits of lahar are poorly sorted, massive, made up of clasts (chiefly of volcanic composition), that generally include a mud-poor matrix. The aim of this research is threefold: to discuss the initiation of lahars occurrences, their dynamics, to assess the hazard and to analyse the deposition. Lahars are either a direct result of eruptive activity or not temporally related to eruptions. Syn-eruptive lahars may result from the transformation on pyroclastic flows or debris avalanches which transform to aqueous flows (e.g. at Papandayan in November 2002); They may be also generated through lake outburst or breaching (e.g. at Kelut in 1909 or 1966), and through removal of pyroclastic debris by subsequent heavy rainstorms. Post-eruptive lahar occurs during several years after an eruption. At Merapi, lahars are commonly rain-triggered by rainfalls having an average intensity of about 40 mm in 2 hours. Most occur during the rainy season from November to April. Non-eruptive lahars are flows generated without eruptive activity, particularly in the case of a debris avalanche or a lake outburst (e.g., Kelut). A lahar may include one or more discrete flow processes and encompass a variety of rheological flow types and flow transformations. As such, lahars encompass a continuum between debris flows and hyperconcentrated flows, as observed at Merapi, Kelut and Semeru volcanoes. Debris flows, with water contents ranging from 10 to no more than about 25% weight, are non-newtonian fluids that move as fairly coherent masses in what is thought to be predominantly laminar fashion. However, the relative importance of laminar versus turbulent regime is still debatable. Hyperconcentrated streamflows contain 25- to about 40%-weight-water; these flows possess some yield stress, but they are characteristically turbulent. Hazard-zone maps for lahar were produced for most of the the Javanese volcanoes, but these maps are on too small-scale to meet modern zoning requirements. More recently, a few large-scale maps (1/10,000 and 1/2,000-scale) and risk assessments have been completed for a few critical river systems at Merapi.

Molecular descriptors as proxies for the modeling of the materials and their environmental impact

For the prediction of material's properties and of interaction of molecules with the surroundings, one needs to know their properties. Usually, the molecular properties are revealed through experimental measurements. It can be a tedious, time-consuming, and costly work. On the other hand, computational chemistry readily generates a huge number of data which can provide various molecular descriptors. These can be various observable properties (bond lengths and angles, dipole moments, etc...), but also the unobservable properties (partial atomic charges, electronegativity, various latent variables ....). There is an urgent need to develop accurate and economical screening tools that predict potential toxicity and environmental burden of various chemicals. Equally important is the design of safer alternatives. Molecular modeling methods offer one of several complementary approaches to evaluate the risk to human health and the environment as a result of exposure to environmental chemicals. These tools can streamline the hazard assessment process by simulating possible modes of action and providing virtual screening tools that can help prioritize bioassay requirements. Tailoring these strategies to the particular challenges presented by environmental chemical interactions make them even more effective. Advances in the fields of computational chemistry and molecular toxicology in recent decades allow the development of predictive models that inform the design of molecules with reduced potential to be toxic to humans or to the environment. As an example we present the novel methodology for the computational evaluation of pKa values of various organic bases, based on calculation of partial atomic charges by a simple semiempirical QM method.

Analysis of macroseismic fields using statistical data depth functions: considerations leading to attenuation probabilistic modelling

Modelling seismic attenuation is one of the most critical points in the hazard assessment process. In this article we consider the spatial distribution of the effects caused by an earthquake as expressed by the values of the macroseismic intensity recorded at various locations surrounding the epicentre. Considering the ordinal nature of the intensity, a way to show its decay with distance is to draw curves—isoseismal lines—on maps, which bound points of intensity not smaller than a fixed value. These lines usually take the form of closed and nested curves around the epicentre, with highly different shapes because of the effects of ground conditions and of complexities in rupture propagation. Forecasting seismic attenuation of future earthquakes requires stochastic modelling of the decay on the basis of a common spatial pattern. The aim of this study is to consider a statistical methodology that identifies a general shape, if it exists, for isoseismal lines of a set of macroseismic fields. Data depth is a general nonparametric method for analysis of probability distributions and datasets. It has arisen as a statistical method to order points of a multivariate space, e.g., Euclidean space \({\mathbb {R}}^{p}\), \(p \ge 1\), according to the centrality with respect to a distribution or a given data cloud. Recently, this method has been extended to the ordering of functions and trajectories. In our case, for a fixed intensity decay \(\varDelta I\), we build a set of convex hulls that enclose the sites of felt intensity \(I_s \ge I_0 -\varDelta I\), one for each macroseismic field of a set of earthquakes that are considered as similar from the attenuation point of view. By applying data depth functions to this functional dataset, it is possible to identify the most central curve, i.e., the attenuation pattern, and to consider other properties like variability, outlyingness, and possible clustering of such curves. Results are shown for earthquakes that occurred on the Central Po Plain in May 2012, and on the eastern flank of Mt. Etna since 1865.

Development of an empirical model for rainfall-induced hillside vulnerability assessment: a case study on Chen-Yu-Lan watershed, Nantou, Taiwan

In Taiwan, the hillside is about 70 % of total area. These areas also have steep topography and geological vulnerability. When an event of torrential rain comes during a typhoon, the landslide disasters usually occur at these areas due to the long duration and high intensity of rainfall. Therefore, a design which considers the potential landslide has become an important issue in Taiwan. In this study, a temporal characteristic of landslide fragility curve (LFC) was developed, based on the geomorphological and vegetation factors using landslides at the Chen-Yu-Lan watershed in Taiwan, during Typhoon Sinlaku (September 2008) and Typhoon Morakot (August 2009). This study addressed an effective landslide hazard assessment process, linking together the post-landslide damage and post-rainfall data for LFC model. The Kriging method was used to interpolate the rainfall indices (R0, R, I) for numerical analysis. Remote sensing data from SPOT images were applied to analyze the landslide ratio and vegetation conditions. The 40-m digital elevation model was used for slope variation analysis in the watershed, and the maximum likelihood estimate was conducted to determine the mean and standard deviation parameters of the proposed empirical LFC model. This empirical model can express the probability of exceeding a damage state for a certain classification (or conditions) of landslides by considering a specific hazard index for a given event. Finally, the vulnerability functions can be used to assess the loss from landslides, and, in the future, to manage the risk of debris flow in the watershed.