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  • 1
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    Spatial representation of direct loss estimates on the residential building stock of Lima (Peru) from decoupled earthquake and tsunami scenarios on variable resolutions exposure models (2021)
    GFZ Data Services
    Details
    Publication Date: 2022-02-15
    Description: Abstract
    Description: This data repository contains the spatial distribution of the direct financial loss computed expected for the residential building stock of Metropolitan Lima (Peru) after the occurrence of six decoupled earthquake and tsunami risk scenarios (Gomez-Zapata et al., 2021a; Harig and Rakowsky, 2021). These risk scenarios were independently calculated making use of the DEUS (Damage Exposure Update Service) available in https://github.com/gfzriesgos/deus. The reader can find documentation about this programme in (Brinckmann et al, 2021) where the input files required by DEUS and outputs are comprehensively described. Besides the spatially distributed hazard intensity measures (IM), other inputs required by DEUS to computed the decoupled risk loss estimates comprise: spatially aggregated building exposure models classified in every hazard-dependent scheme. Each class must be accompanied by their respective fragility functions, and financial consequence model (with loss ratios per involved damage state). The collection of inputs is presented in Gomez-Zapata et al. (2021b). The risk estimates are computed for each spatial aggregation areas of the exposure model. For such a purpose, the initial damage state of the buildings is upgraded from undamaged (D0) to any progressive damage state permissible by the fragility functions. The resultant outputs are spatially explicit .JSON files that use the same spatial aggregation boundaries of the initial building exposure models. An aggregated direct financial loss estimate is reported for each cell after every hazard scenario. It is reported one seismic risk loss distribution outcome for each of the 2000 seismic ground motion fields (GMF) per earthquake magnitude (Gomez-Zapata et al., 2021a). Therefore, 1000 seismic risk estimates from uncorrelated GMF are stored in “Clip_Mwi_uncorrelated” and 1000 seismic risk estimates from spatially cross-correlated GMF (using the model proposed by Markhvida et al. (2018)) are stored in “Clip_ Mwi_correlated”. It is worth noting that the prefix “clip” of these folders refers to the fact that, all of the seismic risk estimates were clipped with respect to the geocells were direct tsunami risk losses were obtained. This spatial compatibility in the losses obtained for similar areas and Mw allowed the construction of the boxplots that are presented in Figure 16 in Gomez-Zapata et al., (2021). The reader should note that folder “All_exposure_models_Clip_8.8_uncorrelated_and_correlated” also contains another folder entitled “SARA_entire_Lima_Mw8.8” where the two realisations (with and without correlation model) selected to produce Figure 10 in Gomez-Zapata et al., (2021) are stored. Moreover, the data to produce Figure 9 (boxplots comparing the variability in the seismic risk loss estimates for this specific Mw 8.8, are presented in the following .CSV file: “Lima_Mw_8.8_direct_finantial_loss_distributions_all_spatial_aggregations_Corr_and_NoCorr.csv”. Naturally, 1000 values emulating the 1000 realisations are the values that compose the variability expressed in that figure. Since that is a preliminary study (preprint version), the reader is invited to track the latest version of the actually published (if so) journal paper and check the actual the definitive numeration of the aforementioned figures.
    Keywords: tsunami risk ; earthquake risk ; risk scenario ; physical vulnerability ; loss ; deterministic risk ; fragility function ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 EARTHQUAKES ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 TSUNAMIS ; EARTH SCIENCE SERVICES 〉 HAZARDS MANAGEMENT
    Type: Dataset , Dataset
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    DATA GFZ
  • 2
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    RRVS Building survey for building exposure modelling in Valparaiso and Viña del Mar (Chile) (2021)
    GFZ Data Services
    Details
    Publication Date: 2022-11-23
    Description: Abstract
    Description: The dataset contains a set of structural and non-structural attributes collected using the GFZ RRVS (Remote Rapid Visual Screening) methodology. It is composed by 604 randomly distributed buildings in the urban area of Valparaiso and Viña del Mar (Chile). The survey has been carried out between November and December 2018 using a Remote Rapid Visual Screening system developed by GFZ and employing omnidirectional images from Google StreetView (vintage: December 2018) and footprints from OpenStreetMap (OSM). The buildings were inspected by local structural engineers from the Chilean Research Centre for Integrated Disaster Risk Management (CIGIDEN) while collecting their attribute values in terms of the GEM v.2.0 taxonomy
    Keywords: taxonomy ; RRVS ; GEM ; risk exposure ; attributes ; survey ; Valparaiso ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region
    Type: Dataset , Dataset
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    DATA GFZ
  • 3
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    Residential building exposure and physical vulnerability models for ground-shaking and tsunami risk in Lima and Callao (Peru) (2021)
    GFZ Data Services
    Details
    Publication Date: 2022-11-23
    Description: Abstract
    Description: This data publication is composed by two main folders: (1) “Top-down_exposure_modelling_Lima” and (2) “Vulnerability_models_Lima/”. The first one contains a complete collection of data models used to represent the residential building portfolio of Lima and Callao (Peru) using a top-down approach (census-based desktop study). Therein, the reader can find a comprehensive description of the procedure of how the exposure models were constructed. This includes python scripts and postprocessed geodatasets to represent these building stock into predefined and separate classes for earthquake and tsunami physical vulnerabilities. The second folder contains sets of fragility functions for these building classes and the assumed economic consequence model. These models are suplement material of a submitted paper (Gomez-Zapata et al., 2021b). Please note it is an unpublished preprint version at the time of writing this document. The reader is strongly advised to look for the definitive version once (if so) it is accepted and published.
    Keywords: exposure modelling ; physical vulnerability ; consequence model ; fragility function ; earthquake vulnerability ; tsnami vulnerability ; occupancy types ; residential building ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 EARTHQUAKES ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 TSUNAMIS
    Type: Dataset , Dataset
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    DATA GFZ
  • 4
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    Tsunami flow depth in Lima/Callao (Peru) caused by six hypothetical simplified tsunami scenarios offshore Lima (2021)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: This data collection contains six inundation maps in Lima and Callao (Peru) based on tsunami simulations with the wave propagation and run-up model TsunAWI (see Rakowsky et al. 2015). The simulations were carried out in the framework of the RIESGOS project (see riesgos.de). The sources are hypothetical earthquake events in the magnitude range Mw 8.5 to Mw 9.0 offshore Lima. The source area of the events is based on the historical event from October 1746, the parameters are derived from the study Jimenez et al. (2013). The sources are considerably simplified since we aim at a systematic investigation of the tsunami impact and restrict the parameter variation between scenarios to one parameter only, the slip value. The source area is split into five subfaults, however we use a constant slip distribution. The corresponding tsunami simulations are carried out in a triangular mesh with resolution ranging from 7km in the deep ocean to a finest value of about 7m in the coastal land part of the pilot area Lima/Callao. The flow depth distribution in Lima/Callao obtained from the simulation is interpolated to a raster file and provided as Golden Software Binary Grids. The numerical results are obtained from simulations with the finite element model TsunAWI (Rakowsky et al. 2015). The mesh resolution in the pilot area Lima/Callao is approximately 20m, the smallest edge length is about 7m. The main model parameters are listed in Table 1. Concerning the bottom roughness, we use a constant Manning coefficient of 0.02 in all of the model domain.
    Keywords: tsnami vulnerability ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 EARTHQUAKES ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 TSUNAMIS
    Type: Dataset , Dataset
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    DATA GFZ
  • 5
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    Seismic ground motion fields for six deterministic earthquake scenarios (Mw 8.5-9.0) for Lima (Peru) (2021)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: This repository contains spatially distributed ground motion fields (GMF) for six determinist subduction earthquake scenarios for Metropolitan Lima and Callao (Peru). They have moment magnitudes between Mw 8.5 to 9.0 and emulate the historical earthquake that occurred in 1746 and caused extensive damage to that area. 1000 ground motion realisations in .XML format are generated using a single ground motion prediction equation per earthquake rupture with uncorrelated and cross-correlated residuals.
    Keywords: RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; ground motion ; seismic ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 EARTHQUAKES ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 TSUNAMIS
    Type: Dataset , Dataset
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    DATA GFZ
  • 6
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    Quakeledger: a web service to serve earthquake scenarios (2021)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: This version of Quakeledger (V.1.0) is a Python3 program that can also be used as a WPS (Web Processing Service). It returns the available earthquake events contained within a given local database (so called catalogue) that must be customised beforehand (e.g. historical, expert and/or stochastic events). This is a rewrite from: https://github.com/GFZ-Centre-for-Early-Warning/quakeledger and https://github.com/bpross-52n/quakeledger. In these original codes, an earthquake catalogue had to be initially provided in .CSV format. The main difference with this version is that, this code is refactored and uses a SQLITE database. The user can find the parser code in: “quakeledger/assistance/import_csv_in_sqlite.py”
    Description: Other
    Description: License: BSD 3-Clause Copyright © 2021 Early Warning and Impact Assessment Group at Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences Quakeledger is free software: you can redistribute it and/or modify it under the terms of the BSD 3-Clause License. Quakeledger is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the BSD 3-Clause License for more details. You should have received a copy of the BSD 3-Clause License along with this program. If not, see 〈https://opensource.org/licenses〉
    Keywords: Earthquake catalogue ; provider ; script ; python ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING ; EARTH SCIENCE SERVICES 〉 WEB SERVICES ; EARTH SCIENCE SERVICES 〉 WEB SERVICES 〉 DATA PROCESSING SERVICES
    Type: Software , Software
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    DATA GFZ
  • 7
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    Shakyground: a web service to serve GMPE-based ground motion fields (2021)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: This version of Shakyground (V.1.0) comprise several Python3 scripts and returns the median values of spatially-distributed ground motion fields for a selected area and a given synthetic earthquake rupture. These values are simulated by means of a set of GMPEs (Ground Motion Prediction Equations) developed by several experts for specific tectonic areas. The outputs can be provided in community standard formats (.xml). A simple ipython notebook to visualise these results is also included.
    Description: TechnicalInfo
    Description: License: BSD 3-Clause Copyright © 2021 Early Warning and Impact Assessment Group at Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences Shakyground is free software: you can redistribute it and/or modify it under the terms of the BSD 3-Clause License. Shakyground is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the BSD 3-Clause License for more details. You should have received a copy of the BSD 3-Clause License along with this program. If not, see 〈https://opensource.org/licenses〉.
    Keywords: python ; ground motion ; RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; EARTH SCIENCE SERVICES 〉 DATA MANAGEMENT/DATA HANDLING
    Type: Software , Software
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    DATA GFZ
  • 8
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    Assetmaster and Modelprop: web services to serve building exposure models and fragility functions for physical vulnerability to natural-hazards (2021)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: Assetmaster and Modelprop are WPS (Web Processing Services) software components written in Python 3. They are implementing two of the several steps of a multi-hazard scenario-based decentralized risk assessment for the RIESGOS project. The reader can find more details in https://github.com/riesgos. Assetmaster provides as output a structural exposure model defined in terms of risk-oriented building classes (for a reference geographical region) in GeoJSON format. The simple service is based on an underlying exposure model in GeoPackage format (.gpkg). Modelprop provides as output for each defined building class the correspondent fragility function. The python code implementing the service can also be run locally in your computer to assess the physical vulnerability of a given building portfolio computing the direct financial losses associated to hazard and multi-hazard scenarios making use of the DEUS program. It is available in: https://github.com/gfzriesgos/deus/.
    Description: TechnicalInfo
    Description: Copyright [2019] Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
    Keywords: RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; python ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; EARTH SCIENCE SERVICES 〉 WEB SERVICES
    Type: Software , Software
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    DATA GFZ
  • 9
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    DEUS: Damage-Exposure-Update-Service (2021)
    GFZ Data Services
    Details
    Publication Date: 2024-04-29
    Description: Abstract
    Description: The software component DEUS (Damage-Exposure-Update-Service) is a Python3 script to evaluate/ update the physical damage and the structural vulnerability of a given building stock classified in terms of hazard-dependent classes (i.e. exposure model). This is obtained by estimating the damage evolution of the building stock given their initial damage state; the location of the scenario-based IM; and the use of selected fragility functions that must be compatible with the predefined building classes and IM. It can be run locally on your computer as well as a WPS (Web Processing Service). This version can handle single or consecutive deterministic hazard scenarios with spatially distributed Intensity Measures (IM). For single hazard scenarios, the process requires a single execution. In the case of consecutive deterministic hazard scenarios, the executions are proportional to the number of consecutive risk scenario (events) of interest.
    Description: Other
    Description: Apache License, Version 2.0 (January 2004) Copyright © 2021 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
    Keywords: RIESGOS ; Scenario-based multi-risk assessment in the Andes region ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 EARTHQUAKES ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 TSUNAMIS ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 VOLCANIC ERUPTIONS
    Type: Software , Software
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    DATA GFZ
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