Improving knowledge of the exposure of Moroccan buildings to flooding
(1) Thomas Esch - German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR), Oberpfaffenhofen, D-82234 Weßling, Germany
(2) Mattia Marconcini - German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR), Oberpfaffenhofen, D-82234 Weßling, Germany
(3) Miguel A. Belenguer-Plomer - Indra Sistemas S.A., Ctra. Loeches, 9, 28850, Torrejón de Ardoz , Madrid, Spain
(4) Alberto Lorenzo - Indra Sistemas S.A., Ctra. Loeches, 9, 28850, Torrejón de Ardoz , Madrid, Spain
(5) Abderrahim Chaffai - Fonds de solidarité contre les événements catastrophiques (FSEC), RDC, Immeuble D, Résidence Sun City, rue Al Bourtoukal, Rabat, Morocco
(6) Abderrahim Oulidi - Fonds de solidarité contre les événements catastrophiques (FSEC), RDC, Immeuble D, Résidence Sun City, rue Al Bourtoukal, Rabat, Morocco
(7) Noureddine Filali - Fonds de solidarité contre les événements catastrophiques (FSEC), RDC, Immeuble D, Résidence Sun City, rue Al Bourtoukal, Rabat, Morocco
(8) Ahmed Reda Hadji - Fonds de solidarité contre les événements catastrophiques (FSEC), RDC, Immeuble D, Résidence Sun City, rue Al Bourtoukal, Rabat, Morocco
(9) Reda Aboutajdine - The World Bank, Washington, DC, USA
(10) Fabio Cian - The World Bank, Washington, DC, USA
(11) Jean-Philippe Naulin - Modelling, R&D Department, CCR
(12) Roxane Marchal - Modelling, R&D Department, CCR
(13) Thomas Onfroy - Modelling, R&D Department, CCR
(14) David Moncoulon - Modelling, R&D Department, CCR
INTRODUCTION
Moroccan territory is particularly exposed to earthquake and flood risks. In this context, the Kingdom of Morocco has set up, with the support of the World Bank (WB), a dual system of coverage against these hazards, involving private capital to develop the private insurance market, as well as a solidarity-based mechanism to compensate vulnerable populations unable to insure themselves. This solidarity-based mechanism is ledby the Fonds de solidarité contre les évènements catastrophiques (FSEC), which was set up and operational by 2020.
Given its mandate, the FSEC needs to rely on a detailed and granular understanding of flood risk and its distribution over the Moroccan territory. A first flood damage model was developed as part of a World Bank tender in 2020, awarded to the consortium formed by Atmoterra, RWT and CCR. Since delivering the model, ongoing discussions between the partners have highlighted the robustness of the hazard module, while also stressing the limitations due to an insufficiently granular exposure module and insufficiently specific vulnerability curves for Morocco.
A new project to update Moroccan building data has started in partnership with the FSEC, the European Space Agency (ESA), the World Bank and CCR. The objectives of the work are to better estimate exposure (ESA) and to develop vulnerability curves specific to Morocco (CCR). These improvements will increase the reliability of flood damage assessment for the placement of a risk transfer tool in international markets.
This paper presents the method and results of remote sensing mapping of buildings at national level.
METHODOLOGY
The flood impact model is based on 3 modules. A hazard module to physically characterise floods, an exposure module to identify the types of property as well as their nature (private, professional, house, flat, etc.) and their value. A vulnerability module relates the nature and value of the exposed entity to the level of severity of each hazard scenario. The combination of these three modules in the impact model provides an estimate of the associated amounts of damage.
Exposure module
The exposure module allows the spatial distribution of the different building types to be defined to distribute the estimated total exposure value appropriately. The exposure module initially developed was built from multiple data sources, including the 2014 census of Moroccan households conducted by the High Commission for Planning. In order to locate households, a random draw method was used to determine the spatial distribution of buildings. This method was based on Open Street Map buildings and satellite processing data that identified the number of inhabitants at a certain resolution. To improve the exposure module and better understand the spatial distribution of buildings in Morocco, ESA mobilised its innovative Earth observation capabilities for exposure mapping in the GDA Disaster Resilience project[1]. ESA’s Sentinel-1 and Sentinel-2 satellite images were analysed for a granular spatial assessment of buildings at risk of flooding. A mapping of building types was carried out in the Rabat-Salé-Kenitra area selected as a study site. The settlement areas delineated in GIS-viewable shapefile format are based on the OSM+Facebook street network and the World Settlement Footprint 2019 product[2]. A set of manually collected samples of building typologies was used as input data to train an automatic Random Forest (RF) (Table ). Based on the resulting RF model, the whole country of Morocco was classified according to the following building typology (Table 1): villa, flat, Moroccan house, rural areas, informal settlements, rural houses and others. These typologies and their spatial distribution will be used to adequately distribute the exposed value of the building in space.
Vulnerability Module
The vulnerability module provides a better understanding of the adverse effects of flooding on exposed buildings depending on their typology and the severity of a given flood. The vulnerability module used in the first study launched in 2020 was based on vulnerability curves constructed by expert opinion and derived from the MnhPRA (Morocco Natural Hazards Probabilistic Risk Analysis) model, the first multi-hazard modelling tool rolled out in Morocco. To enhance and refine the vulnerability module and adapt it to the specificities of the Moroccan builds, CCR will develop a statistical empirical approach to calibrate new vulnerability curves on the basis of the data to be collected. The results of this collection will allow the recalibration of damage curves specific to each type of risk and relevant to the Moroccan territory and the needs of the FSEC. Specific focus will be paid to the damage threshold at which a property becomes uninhabitable. Indeed, the Solidarity Fund scheme currently compensates victims of floods whose main residence becomes uninhabitable. This threshold is therefore important not to consider the multiple dwellings that may be slightly damaged by a flood.
# exposure
# vulnerability
# building
# flooding
# Morocco
# remote sensing
Table 1 - Typology of buildings used in the flood damage model.
Figure 1 - Example of the results of remote sensing work on a urban area and the corresponding classification
RESULTS
The building classification product allows the typology of establishments to be determined based on a customised requirement, considering very specific classes such as Moroccan houses (Figure 1). This new development based on Earth observation demonstrates, once again, the huge potential of satellite data, which allows the quick, synoptic and inexpensive countrywide mapping of building typologies and, consequently, the estimation not only of the financial value of each property but also of its vulnerability to natural hazards. The product is intended to become an effective tool to support the allocation of early recovery funds in the case of floods, where costs vary according to the specific typology of buildings affected by a given event. The accuracy of the final classification may vary depending on the quantity, spatial distribution and reliability of the reference information for the various target classes. In addition, performance could be partially affected by the different spatial resolutions and time stamps of the different datasets used. These results will be used in the calibration of damage curves specific to each type of risk and meeting the needs of the FSEC. Attention will be paid to the damage threshold at which a building becomes uninhabitable, which is a central element of the Moroccan flood compensation scheme.
CONCLUSION
Accurate damage modelling is a key element in identifying the sums involved in the claims process, forecasting them adequately and reducing reinsurance placement costs. More generally, the work presented in this article will contribute to the improvement of this modelling chain, in the dynamics of the continuous improvement process, initiated from the first modelling work. Further improvements may be considered at a later stage, such as improving the simulation of hazard through the use of a more detailed digital terrain model (DTM), taking into account runoff and incorporating risk reduction structures (dykes, dams, etc.). The design of tailor-made vulnerability curves for Morocco could also benefit from a structural engineering approach, complementary to the statistical approach presented in this article./
THE PARTNERS
As a continuation of the project financed in 2020 by the World Bank, CCR and the FSEC wish to continue their long-term collaboration for the development of the Cat model. The integration of these various partners contributes to the improvement of the data and tools used in the model.
REFERENCES
1. GDA Disaster Resilience, https://gda.esa.int/thematic-area/ disaster-resilience/
2. German Aerospace Center (DLR) World Settlement Footprint & Evolution, https://geecommunity-catalog.org/projects/ wsf/
CITATION
Esch et al, Improving knowledge of the exposure and vulnerability to flooding of buildings in Morocco. In CCR 2022 Scientific Report; CCR, Paris, France, 2022, pp. 64-67