Flood Risk Analysis Using Spatial Synthetic Population in the Upper Bengawan Solo Watershed, Indonesia

Enhancing flood risk maps by a participatory and collaborative design process

Since the beginning of the 21st Century, Europe has been affected by destructive floods. European Union Member States have an obligation to develop flood hazard and flood risk maps as support to the Flood Risk Management Plan (FRMP). The main objective of this study is to propose a methodological framework for hazard and risk assessment of pluvial flash floods in Croatia at the catchment level, which can be integrated into the FRMP. Therefore, a methodology based on the source–pathway–consequence approach for flood risk assessment is presented, which complies with the EU Floods Directive. This integrated and comprehensive methodology is based on high-resolution open data available for EU Member States. Three scenarios are defined for a low, medium, and high probability, defined by design storms of different durations. The proposed methodology consists of flood hazard analysis, vulnerability assessment, and risk analysis. Pluvial flash flood hazards are analyzed using a 2D hydrologic–hydraulic model. The flood vulnerability assessment consists of a GIS analysis to identify receptors potentially at risk of flooding and an assessment of susceptibility to potential flood damage using depth–damage curves. Flood risk is assessed both qualitatively in terms of risk levels and quantitatively in terms of direct damages expressed in monetary terms. The developed methodology was applied and tested in a case study in the Gospić catchment in Croatia, which surrounds a small rural town frequently affected by pluvial flash floods.

Flood is a natural part of the hydrologic cycle, a natural phenomenon known for its catastrophic impacts on the environment, livelihoods, and properties, both economically and socially. It is the leading natural disaster in the world today affecting so many people, especially in the Asia region. Papua New Guinea has an abundance of rich resources and still possesses most of its natural geographic habitats and environments, but is also familiar with natural disasters like floods, earthquakes, landslides, volcanic eruptions, and droughts. Floods bring about tremendous destructions to anything that lies in its path, but it restores the health of the waterways/channels and redistributes the fertile sediments onto the floodplain. This research paper is focused on flood risk analysis using GIS and remote sensing, multi-criteria decision approach (MCDA), analytical hierarchy process (AHP), and the weighted linear combination (WLC). GIS-based spatial analysis techniques are useful for flood risk and hazard mapping with remote sensing technologies which provides an alternative to the conventional/traditional survey techniques. GIS coupled with remote sensing provides a basic framework/platform that helps in all stages of disaster assessment and management from preparedness, to response and recovery. Multi-criteria decision analysis (MCDA) is a collection of techniques that aid decision-makers in properly structuring multi-faceted decisions and evaluating the alternatives. AHP is a tool under MCDA that is used for dealing with complex decision-making and helps decision-makers set priorities and draw better decisions. Altogether, GIS-based MCDA-AHP became an efficient technique in flood risk mapping where multiple flood influential factors/criteria are incorporated into the GIS analysis process to producing better flood risk maps. In the present study, nine independent variables, namely elevation, slope, soil texture, soil drainage, landform, rainfall, distance from the main river, land use/land cover, and surface runoff, are used for flood vulnerability analysis. The resulted output demonstrated a span of value ranging from 1.13 (least vulnerable) to 4.15 (most vulnerable). The final map with 5 distinct classes is developed based on the natural junk classification method. The result indicated that about 4.57% of land area as “very high” and 12.49% as “high” flood vulnerable class and a total of 6700 people are living in those vulnerable zones. Past flood events are compared with the flood vulnerable database to validate the modeled output in the present study. This type of study will be very useful to the local government for future planning and decision on flood mitigation plans.

GIScience 2016 Short Paper Proceedings Assessing Spatiotemporal Agreement between Multi- Temporal Built-up Land Layers and Integrated Cadastral and Building Data Johannes H. Uhl 1 , Stefan Leyk 1 , Aneta J. Florczyk 2 , Martino Pesaresi 2 , Deborah Balk 3 University of Colorado Boulder, Department of Geography, Boulder, CO 80309, U.S.A. Email: {johannes.uhl; stefan.leyk}@colorado.edu European Commission – Joint Research Centre (JRC), Institute for the Protection and Security of the Citizen (IPSC), Global Security and Crisis Management Unit, 21027 Ispra, Italy Email: {martino.pesaresi; aneta.florczyk}@jrc.ec.europa.eu City University of New York, Institute for Demographic Research and Baruch College, New York, NY 10010, U.S.A. Email: deborah.balk@baruch.cuny.edu Abstract There is an increasing availability of multi-temporal land use and built-up land datasets. However, little research has been done regarding the spatiotemporal uncertainty of these data products. In this work we present an approach that has the potential to be applicable for spatiotemporal evaluation of the novel Global Human Settlement Layer (GHSL) created by automatic classification of global collections of Landsat data recorded in the epochs 1975, 1990, 2000, and 2014. The proposed approach produces the reference data by integrating publicly available parcel and building data and derives agreement statistics with the GHSL. 1. Introduction The Global Human Settlement Layer (GHSL) project aims to assess the human presence in the planet by estimating the amount of built-up area based on remote sensing data and census data (Pesaresi et al. 2015). In Pesaresi et al. (2013) the GHSL information production workflow was tested for sensors ranging between 0.5 and 10m spatial resolution, which usually perform very well in detection of built-up areas but are typically constrained regarding data access, redistribution rights, and are typically not available consistently for long periods of time. For these reasons, these data are difficult to use for spatiotemporally uniform and systematic extraction of built-up areas on global, national or even regional level. Therefore, the GHSL workflow was tested with global collections of publicly available Landsat imagery collected in the past 40 years (Pesaresi et al. 2016). The Landsat GHSL dataset is available as seamless global mosaic at high spatial resolution (approx. 38m) and for various points in time (1975, 1990, 2000, 2014, see Figure 1a). GHSL data offers promising opportunities for population projections, disaster management and risk assessment (Freire et al. 2015; Freire et al. 2016), as well as for analysing and modelling urban dynamics and land use change. Before such novel data products can be made available to the research community, an extensive quality assessment is required. However, such assessments are difficult due to the lack of reliable reference data particularly for earlier time periods and in less developed regions. In this paper we present and discuss a novel approach to evaluate multi-temporal spatial data on built-up land such as GHSL or developed land cover classes using publicly available parcel (cadastral) data integrated with building footprints in the U.S. The aim of this study is to establish a protocol for future testing the accuracy of fine-scale multi-temporal products derived from automatic classification of satellite data featuring the presence of built-up areas. The selection of the test areas discussed here are driven and constrained by the availability of the reference data and consequently the results derived are

Abstract. Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks (the Flood Risk Directive) signifies that flood risk analysis methods are gaining ground in EC Member States and, therefore, also in the Czech Republic (CR). Procedures of flood risk analysis have been developed in the Czech Republic since the catastrophic floods of 1997 in line with European and worldwide trends and have been tested and applied in hundreds of case studies to date. Currently, the Flood Risk Directive Guideline based on past experience with flood risk analysis applications is being processed. The aim of the paper is to present flood risk analysis procedures and specially developed techniques for the assembly of flood hazard, danger and flood risk maps. Methods related to flood risk management plans are briefly mentioned as well. The following particular problems are discussed in more detail: an application and extension of the "danger matrix" approach, the definition of residual danger, the formulation of efficiency criteria and preliminary multi-criteria flood risk assessment. These issues were tested in practical applications at pilot locations in the Czech Republic. Present experience provides evidence that the flood risk analysis methods used in the Czech Republic are in harmony with the requirements of the Flood Risk Directive. The proposed and applied methods are based primarily on existing available data such as flood extent maps, cadastral maps, the Register of Census Districts and Structures and others.

Flood risk mapping and analysis have gained much attention globally due to the increasing rate of flood disasters in most coastal and riverine areas. As a key element of flood risk study, mapping and delineation of flood hazard areas are very important for risk management and disaster reduction. We analysed potential flood hazards zones in Ogunpa river basin using integrated hydraulic modelling, the height above nearest drainage (HAND) model and multi criteria decision analysis (MCDA). An event-based flood simulation using FLO-2D model was done for the 28 h of the flooding event, while HAND model was employed in modelling the terrain to delineate inundation extent in the basin. In addition, seven flood causative factors were integrated using the Analytical Hierarchical Process (AHP) to delineate potential hazard zones in the study area. Flood inundation model result from FLO-2D revealed inundation depths between 0 and 5.24 m, an indication of intense flood hazards capable of causing lots of damages. MCDA results were classified into least, low, moderate, high and extreme flood hazard zones, while the classified HAND model include none, very low, low, moderate and high flood hazard zones. The MCDA results revealed that the downstream portions of the basin are mostly susceptible to moderate flood hazard compared to low vulnerability observed majorly in the upriver parts of the catchment. The comparison between the estimated flood depths ranges of 0.3–5.2 m by the FLO-2D model and the HAND model value range of 0–5 m (high flood hazard zone) revealed a strong similarity. In all, areas closed to the river course are highly vulnerable to flooding. The output of this study can serve as policy and decision-making tools for future flood hazard analysis, prevention and reduction plans at the research location.

Flood risk mapping is important to prevent damage from flooding in urban areas. In this study, a flood risk map was produced with hydrological and hydraulic data. The methodology implemented in this article was based on both the mathematical calculation of the maximum flow rate and the software Iber 2.4.3 is used as a 2D hydraulic modelling tool verified using field observation data. The flood conditioning factors used in the modelling were precipitation, slope, depth, land use. Other factors, including urban density, socio-economic conditions and the responses of 500 questionnaires distributed to people in the study area, Zaio NORT EAST Morocco, were taken into account to analyze the vulnerability to flooding. A flood risk map was then produced using flood risk and vulnerability maps. The mapping method presented as a precautionary measure against flooding not only alerts the public to flood risk issues and reduces it more effectively in identified vulnerable areas, but also helps the authorities to make decisions about flooding strategies, land use and urban development.

In recent decades, the state of Tabasco, particularly its capital, Villahermosa, has faced recurrent flooding due to a combination of natural and human-induced factors. Situated in the southeast region of Mexico, the convergence of the powerful Usumacinta and Grijalva rivers, coupled with clayey soil and a semi-confined aquifer inhibiting water infiltration, has made the region susceptible to saturation and subsequent flooding. Deforestation in the river basins since the 1970s, transforming land use from forest to agriculture, has exacerbated runoff, contributing to increased flood risk.The intensification of tropical cyclones and extreme weather events, indicative of global climate change, further heightens the vulnerability of the region. Despite experiencing significant economic losses and ecological degradation in the past two decades, Tabasco's flood prevention policies have proven ineffective. Recognizing the need for a more proactive approach, this study emphasizes the importance of long-term flood risk assessment, incorporating both the probability of occurrence and potential impact.In Mexico, guidelines for flood risk maps were established in 2014, resulting in the National Atlas of Flood Risk. However, these maps predominantly focus on flood rates and historical occurrences, lacking a comprehensive approach to long-term forecasting. This study addresses this gap by constructing the first risk maps for Villahermosa. Following National Water Commission guidelines, the methodology considers hydrological studies, hydraulic simulations, and social vulnerability indexes.The vulnerability maps incorporate socio-economic factors like employment, education, and housing composition, while hazard maps determine the severity index and impact on residential structures. Through GIS-based intersection, risk maps are generated, revealing that even areas exposed to flooding during high-return period scenarios exhibit a medium risk index. Nevertheless, limitations arise from incomplete socio-economic and demographic data, hindering accurate vulnerability assessments.Despite challenges, the study estimates annual damages, projecting over 33,000 affected individuals and economic losses exceeding MXN 250 million (USD 14 million). The creation of risk maps for Villahermosa, albeit challenging with current data constraints, serves as an essential initial step. It calls for further research to develop comprehensive databases, fostering public awareness and informed territorial policies to address flood risks in Villahermosa and other flood-prone areas in Mexico.The methodology employed in this study lays a robust foundation for flood risk management, community safety, and sustainable development. It not only aids in precise identification of flood-prone areas but also serves as a crucial tool for the scientific community to address hydrological hazards. Furthermore, it supports the evaluation of existing public policies and the formulation of more effective strategies for reducing losses and enhancing resilience.

A two-dimensional flood routing and risk mapping system is designed and implemented based on Arc Engine and WPF technology in this paper. Combining DEM and DOM data, raster-vector data transformation and processing are realized in this system. The real-time dynamic display of two-dimensional flood routing and the production of risk mapping are realized based on the calculation of the two-dimensional shallow hydrodynamic model. The flood risk map which is created by the system based on 2D hydrodynamic model can be as an important decision-making basis of flood-control and rescue for the flood control departments at all levels, and help to promote the work of flood control to the intelligent, modern development.

Abstract. The Global Human Settlement Layer (GHSL) is supported by the European Commission, Joint Research Center (JRC) in the frame of his institutional research activities. Scope of GHSL is developing, testing and applying the technologies and analysis methods integrated in the JRC Global Human Settlement analysis platform for applications in support to global disaster risk reduction initiatives (DRR) and regional analysis in the frame of the European Cohesion policy. GHSL analysis platform uses geo-spatial data, primarily remotely sensed and population. GHSL also cooperates with the Group on Earth Observation on SB-04-Global Urban Observation and Information, and various international partners andWorld Bank and United Nations agencies. Some preliminary results integrating global human settlement information extracted from Landsat data records of the last 40 years and population data are presented.

Mapping of flood risk is a necessary phase for the establishment of prevention plans from flood risk, and is absolutely mandatory for defining the constructability rules in areas subject to flooding. The mapping of risk is based on the flood evaluation with specified return period. The proposed methodological approach is structured in three steps, characterized by the adoption of hydrological, hydraulic and mapping techniques, respectively. In the hydrological step, the input conditions are defined by the flow-duration-frequency modelling, the synthetic hydrographs and the objective of safety to attribute to an area through variables related to the vulnerability factor. The hydraulic calculation provides information on the hazard factor and allows the evaluation of the local rating curve. The mapping technique allows the translation of the results obtained following the two previous steps in the form of geographic maps, which respond to the hydrological model and operate as both pre- and post-processors of the hydraulic model. An application of the methodology proposed for the flood risk mapping is shown with reference to the Mekerra watershed in Western Algeria, aiming at an implementation of a prevention plan against the risk associated with

<p>The flood events of 13-15 July 2021 in Germany brought the relevance of flood prevention acutely and once again to our attention. As the earth's atmosphere heats up, nature has more and more intense events in store for us, which push our flood protection and management measures to their limits and beyond. For planning purposes, but also in case of an event, it is therefore highly relevant to improve the communication of uncertainties and the assessment of their potential impact, e.g. in the climate or flood forecast, in a target group-oriented manner.</p><p>In Germany and in the European Union, the conditions for flood risk management have been improved since 2007 with the implementation of the European Flood Risk Management Directive (FRMD) and the amendments to the Federal Water Act. Many new instruments such as flood hazard and risk maps, building regulations or the category of flood emergence areas were introduced. For example, flood hazard and flood risk maps and corresponding management plans have been prepared on the basis of historical discharge data, water levels and hydrological and hydraulic modelling. However, recent examples have shown that the objective of the FRMD to reduce flood-related risks to human health, the environment, infrastructure and property has only been achieved to a limited extent.</p><p>In this paper we discuss why the developed maps and plans do not lead to a sufficient risk perception and why, in case of a flood event, it is often not clear what actions need to be taken when and by whom. For this, we want to highlight three aspects in particular:</p><p>1) Data: importance of using measured data and dealing with historical flood events, which are only comparable to a limited extent to today's and future conditions, which are shaped by the influences of climate change.</p><p>2) Actors: importance of involving different actors in the flood risk management planning process to strengthen risk perception and responsibility.</p><p>3) Communication: Importance of communicating uncertainties target group-specific and visualising uncertainties and their possible impacts context-specific.</p><p>For effective and sustainable flood risk management, we therefore believe that we are in need of a communication and dissemination strategy in order to contribute to a transparent description of the roles of the actors and their responsibilities. Consequently, the already developed tools (e.g. flood hazard /risk maps) should be supplemented by involving regional actors, uncertainty information and its effects should be classified and communicated to all decision-making levels in a way that is appropriate for the target group.</p>

Floods are among the most occurring natural hazards that cause severe damage to infrastructure and loss of life. In India, southern Gujarat is affected during the monsoon season, facing multiple flood events in the Damanganga basin. As the basin is one of the data-scarce regions, evaluating the globally available dataset for flood risk mitigation studies in the Damanganga basin is crucial. In the present study, we compared four open-source digital elevation models (DEMs) (SRTM, Cartosat-1, ALOS-PALSAR, and TanDEMX) for hydrodynamic (HD) modeling and flood risk mapping. The simulated HD models for multiple flood events using HEC-RAS v6.3 were calibrated by adopting different roughness coefficients based on land-use land cover, observed water levels at gauge sites, and peak flood depths in the flood plain. In contrast to the previous studies on the Purna river basin (the neighboring basin of Damanganga), the present study shows that Cartosat-1 DEM provides reliable results with the observed flood depth. Furthermore, the calibrated HD model was used to determine the flood risk corresponding to 10, 25, 50, and 100-year return period floods calculated using Gumbel’s extreme value (GEV) and log-Pearson type III (LP-III) distribution techniques. Comparing the obtained peak floods corresponding to different return periods with the observed peak floods revealed that the LP-III method gives more reliable estimates of flood peaks for lower return periods, while the GEV method gives comparatively more reliable estimates for higher return period floods. The study shows that evaluating different open-source data and techniques is crucial for developing reliable flood mitigation plans with practical implications.

Given the increase in flood events in recent years, accurate flood risk assessment is an important component of flood mitigation in urban areas. This research aims to develop updated and accurate flood risk maps in the Don River Watershed within the Great Toronto Area (GTA). The risk maps use geographical information systems (GIS) and multi-criteria analysis along with the application of Analytical Hierarchy Process methods to define and quantify the optimal selection of weights for the criteria that contribute to flood risk. The flood hazard maps were generated for four scenarios, each with different criteria (S1, S2, S3, and S4). The base case scenario (S1) is the most accurate, since it takes into account the floodplain map developed by the Toronto and Region Conservation Authority. It also considers distance to streams (DS), height above nearest drainage (HAND), slope (S), and the Curve Number (CN). S2 only considers DS, HAND, and CN, whereas S3 considers effective precipitation (EP), DS, HAND, and S. Lastly, S4 considers total precipitation (TP), DS, HAND, S, and CN. In addition to the flood hazard, the social and economic vulnerability was included to determine the total flood vulnerability in the watershed under three scenarios; the first one giving a higher importance to the social vulnerability, the second one giving equal importance to both social and economic vulnerability, and the third one giving more importance to the economic vulnerability. The results for each of the four flood scenarios show that the flood risk generated for S2 is the most similar to the base case (S1), followed by S3 and S4. The inclusion of social and economic vulnerability highlights the impacts of floods that are typically ignored in practice. It will allow watershed managers to make more informed decisions for flood mitigation and protection. The most important outcome of this research is that by only using the digital elevation model, the census data, the streams, land use, and soil type layers, it is possible to obtain a reliable flood risk map (S2) using a simplified method as compared to more complex flood risk methods that use hydraulic and hydrological models to generate flood hazard maps (as was the case for S1).

Flood hazards and risk mapping using geospatial technologies in Jimma City, southwestern Ethiopia