Development of a Web-Based GIS of Flood Zones in the Municipality of Ouagadougou in Burkina Faso

This document describes the creation of an informative Web GIS aimed at mitigating the impacts of flooding in the municipality of Ouagadougou, in Burkina Faso, a region that is highly sensitive to climate change. Burkina Faso, which is undergoing rapid urbanization, faces major natural threats, particularly flooding, as demonstrated by the severe floods of 2009 that caused loss of life, injury, structural damage and economic losses in Ouagadougou. The aim of this research is to develop a web map highlighting the municipality’s flood-prone areas, with a view to informing and raising awareness of flood risk reduction. Using the Leaflet JavaScript mapping library, the study uses HTML, CSS and JavaScript to implement web mapping technology. Data on Ouagadougou’s flood zones is generated by a multi-criteria analysis combining Saaty’s AHP method and GIS in QGIS, integrating seven (7) parameters including hydrography, altitude, slope, rainfall, soil types, land use and soil moisture index. QGIS processes and maps the themes, PostgreSQL with PostGIS serves as the DBMS and GeoServer functions as the map server. The Web GIS platform allows users to visualize the different flood risks, from very low to very high, or the high-risk areas specific to Ouagadougou. The AHP calculations classify the municipality into five flood vulnerability zones: very low (24.48%), low (27.93%), medium (23.01%), high (17.11%) and very high (7.47%). Effective risk management requires communication and awareness-raising. This online mapping application serves as a tool for communication, management and flood prevention in Ouagadougou, helping to mitigate flood-related natural disasters.

Unsupervised GRNN flood mapping approach combined with uncertainty analysis using bi-temporal Sentinel-2 MSI imageries

Floods occur frequently worldwide.The timely,accurate mapping of the flooded areas is an important task.Therefore,an unsupervised approach is proposed for automated flooded area mapping from bitemporal Sentinel-2 multispectral images in this paper.First,spatial–spectral features of the images before and after the flood are extracted to construct the change magnitude image(CMI).Then,the certain flood pixels and non-flood pixels are obtained by performing uncertainty analysis on the CMI,which are considered reliable classification samples.Next,Generalized Regression Neural Network(GRNN)is used as the core classifier to generate the initial flood map.Finally,an easy-toimplement two-stage post-processing is proposed to reduce the mapping error of the initial flood map,and generate the final flood map.Different from other methods based on machine learning,GRNN is used as the classifier,but the proposed approach is automated and unsupervised because it uses samples automatically generated in uncertainty analysis for model training.Results of comparative experiments in the three sub-regions of the Poyang Lake Basin demonstrate the effectiveness and superiority of the proposed approach.Moreover,its superiority in dealing with uncertain pixels is further proven by comparing the classification accuracy of different methods on uncertain pixels.

Flash flood hazard mapping: A pilot case study in Xiapu River Basin, China

Flash flood hazard mapping is a supporting component of non-structural measures for flash flood prevention. Pilot case studies are necessary to develop more practicable methods for the technical support systems of flash flood hazard mapping. In this study, the headwater catchment of the Xiapu River Basin in central China was selected as a pilot study area for flash flood hazard mapping. A conceptual distributed hydrological model was developed for flood calculation based on the framework of the Xinanjiang model, which is widely used in humid and semi-humid regions in China. The developed model employs the geomorphological unit hydrograph method, which is extremely valuable when simulating the overland flow process in ungauged catchments, as compared with the original Xinanjiang model. The model was tested in the pilot study area, and the results agree with the measured data on the whole. After calibration and validation, the model is shown to be a useful tool for flash flood calculation. A practicable method for flash flood hazard mapping using the calculated peak discharge and digital elevation model data was presented, and three levels of flood hazards were classified. The resulting flash flood hazard maps indicate that the method successfully predicts the spatial distribution of flash flood hazards, and it can meet the current requirements in China.

Integration of Remote Sensing Data and GIS Tools for Accurate Mapping of Flooded Area of Kurigram, Bangladesh

Flood is the most devastating disaster in the present world which causes damage to environmental, social, economical and human lives at about 43% of all natural disasters. There are many flood hazard occurs in Bangladesh during the 19th century and 20th century in the different regions. These flood hazards have more catastrophic damages of huge area within human lives and other necessary properties of Bangladesh. The first step of flood management is to evaluate the area which is under threat of flood disaster. In this study here showed the importance of Remote Sensing (RS) data and Geographic Information System (GIS) tools to manage the flood related problems. Remote Sensing (RS) data and Geographic Information System (GIS) provide a lot of information to flood disaster management. ArcView GIS software tools are used for digitizing the base map and to create a flood risk zone of Kurigram, Bangladesh where images of remote sensing can be helped to determine the flood inundation areas. The integrated application of RS and GIS techniques for monitoring and flood mapping provides information for the decision makers. The study also grows attentions the need of cost-efficient methodology by creating a flood vulnerable map of Bangladesh.

Rainwater harvesting systems: An urban flood risk mitigation measure in arid areas

Rainwater harvesting (RWH) systems have been developed to compensate for shortage in the water supply worldwide. Such systems are not very common in arid areas, particularly in the Gulf Region, due to the scarcity of rainfall and their reduced efficiency in covering water demand and reducing water consumption rates. In spite of this, RWH systems have the potential to reduce urban flood risks, particularly in densely populated areas. This study aimed to assess the potential use of RWH systems as urban flood mitigation measures in arid areas. Their utility in the retention of stormwater runoff and the reduction of water depth and extent were evaluated. The study was conducted in a residential area in Bahrain that experienced waterlogging after heavy rainfall events. The water demand patterns of housing units were analyzed, and the daily water balance for RWH tanks was evaluated. The effect of the implementation of RWH systems on the flood volume was evaluated with a two-dimensional hydrodynamic model. Flood simulations were conducted in several rainfall scenarios with different probabilities of occurrence. The results showed significant reductions in the flood depth and flood extent, but these effects were highly dependent on the rainfall intensity of the event. RWH systems are effective flood mitigation measures, particularly in urban arid regions short of proper stormwater control infrastructure, and they enhance the resilience of the built environment to urban floods.

Flood Hazard Mapping of Lower Indus Basin Using Multi-Criteria Analysis

Flooding has been one of the recurring occurred natural disasters that induce detrimental impacts on humans, property and environment. Frequent floods is a severe issue and a complex natural phenomenon in Pakistan with respect to population affected, environmental degradations, and socio-economic and property damages. The Super Flood, which hit Sindh in 2010, has turned out to be a wakeup call and has underlined the overwhelming challenge of natural calamities, as 2010 flood and the preceding flood in 2011 caused a huge loss to life, property and land use. These floods resulted in disruption of power, telecommunication, and water utilities in many districts of Pakistan, including 22 districts of Sindh. These floods call for risk assessment and hazard mapping of Lower Indus Basin flowing in the Sindh Province as such areas were also inundated in 2010 flood, which were not flooded in the past in this manner. This primary focus of this paper is the use of Multi-criteria Evaluation (MCE) methods in integration with the Geographical Information System (GIS) for the analysis of areas prone to flood. This research demonstrated how GIS tools can be used to produce map of flood vulnerable areas using MCE techniques. Slope, Aspect, Curvature, Soil, and Distance from Drainage, Land use, Precipitation, Flow Direction, and Flow Accumulation are taken as the causative factors for flooding in Lower Indus Basin. Analytical Hierarchy Process-AHP was used for the calculation of weights of all these factors. Finally, a flood hazard Map of Lower Indus Basin was generated which delineates the flood prone areas in the Sindh province along Indus River Basin that could be inundated by potential flooding in future. It is aimed that flood hazard mapping and risk assessment using open source geographic information system can serve as a handy tool for the development of land-use strategies so as to decrease the impact from flooding.

Mapping floods due to Hurricane Sandy using NPP VIIRS and ATMS data and geotagged Flickr imagery

In this study,we present an approach to estimate the extent of large-scale coastal floods caused by Hurricane Sandy using passive optical and microwave remote sensing data.The approach estimates the water fraction from coarse-resolution VIIRS and ATMS data through mixed-pixel linear decomposition.Based on the water fraction difference,using the physical characteristics of water inundation in a basin,the flood map derived from the coarse-resolution VIIRS and ATMS measurements was extrapolated to a higher spatial resolution of 30 m using topographic information.It is found that flood map derived from VIIRS shows less inundated area than the Federal Emergency Management Agency(FEMA)flood map and the ground observations.The bias was mainly caused by the time difference in observations.This is because VIIRS can only detect flood under clear conditions,while we can only find some clear-sky data around the New York area on 4 November 2012,when most flooding water already receded.Meanwhile,microwave measurements can penetrate through clouds and sense surface water bodies under clear-or-cloudy conditions.We therefore developed a new method to derive flood maps from passive microwave ATMS observations.To evaluate the flood mapping method,the corresponding ground observations and the FEMA storm surge flooding(SSF)products are used.The results show there was good agreement between our ATMS and the FEMA SSF flood areas,with a correlation of 0.95.Furthermore,we compared our results to geotagged Flickr contributions reporting flooding,and found that 95%of these Flickr reports were distributed within the ATMS-derived flood area,supporting the argument that such crowd-generated content can be valuable for remote sensing operations.Overall,the methodology presented in this paper was able to produce high-quality and high-resolution flood maps over largescale coastal areas.

Rapid flood inundation mapping by differencing water indices from pre-and post-flood Landsat images

Following flooding disasters,satellite images provide valuable information required for generating flood inundation maps.Multispectral or optical imagery can be used for generating flood maps when the inundated areas are not covered by clouds.We propose a rapid mapping method for identifying inundated areas based on the increase in the water index value between the pre-and post-flood satellite images.Values of the Normalized Difference Water Index(NDWI)and Modified NDWI(MNDWI)will be higher in the post-flood image for flooded areas compared to the pre-flood image.Based on a threshold value,pixels corresponding to the flooded areas can be separated from non-flooded areas.Inundation maps derived from differencing MNDWI values accurately captured the flooded areas.However the output image will be influenced by the choice of the pre-flood image,hence analysts have to avoid selecting pre-flood images acquired in drought or earlier flood years.Also the inundation maps generated using this method have to be overlaid on the post-flood satellite image in order to orient personnel to landscape features.Advantages of the proposed technique are that flood impacted areas can be identified rapidly,and that the pre-existing water bodies can be excluded from the inundation maps.Using pairs of other satellite data,several maps can be generated within a single flood which would enable emergency response agencies to focus on newly flooded areas.

How Participatory is Participatory Flood Risk Mapping? Voices from the Flood Prone Dharavi Slum in Mumbai

Participatory flood risk mapping(PFRM) is a well-recognized and widely implemented tool for meaningful community involvement in disaster risk reduction(DRR). The effectiveness of PFRM remains anecdotal. The PFRM exercise has rarely been applied identically in two different places by two different organizations, which produces varied and uncertain outcomes. In the absence of any agreed and comprehensive framework for participatory DRR, existing studies struggle to provide a scientific account of how the structure, design, and process of PFRM ensure the effective participation of local communities.This study, examines what factors and methods make PFRM an effective participatory DRR tool. In this study,we first identified the process-based criteria of participation. Then we briefly introduced a participatory flood risk mapping exercise conducted in a flood-prone informal settlement in Dharavi, Mumbai. The exercise was carefully designed to meet the process criteria of effective participation. Finally, using qualitative research methods, we evaluated the effectiveness of our PFRM from the local community perspective. The findings show that ensuring community livelihood security and true involvement of marginalized groups, preparing an action plan, and incorporating fun and cultural connotations into the facilitation process are critical components that enhance community participation through PFRM in DRR.

Use of Sentinel-1 imagery for flood management in a reservoir-regulated river basin

Flood hazard monitoring and mapping is of great importance because it represents a significant contribution to risk management. The present study investigated the flood event that occurred downstream from the transboundary Strymon River basin, more specifically at Serres basin-a reservoir-regulated basin, in the beginning of 2015. The focus of this study was to better understand the spatio-temporal dynamic of the flood and the causes that initiated the hazard. Within the Serres basin, the Strymon transboundary river outflows to Lake Kerkini, which regulates water flow downstream for irrigation purposes and flood protection. For this research, a dataset of Sentinel-1 SAR GRD images was collected and processed covering the period of October 2014-October 2015 to investigate the water level changes in Lake Kerkini. Based on SAR images, binary water/non-water products and multitemporal RGB amplitude images were generated and interpreted. Sentinel-1 products have proved to be an effective tool on flood hazard dynamic extension mapping and estimation of water extent bodies retained by small reservoirs. In agreement with hydro-meteorological data and the high-resolution DEM, it was conceived that the flood event occurred due to the water volume flowing from upstream in the reservoir and the large amount of water draining from the tributaries into nearby sub-basins. Moreover, inefficient water management of the overwhelming water flow through the dam could further strengthen the flood event. The proposed approach, which is entirely based on open access remotely sensed data and processing tools, could be implemented in the same area for past flood events to produce archive retrospective data, as well as in other similar reservoir-regulated river basins in terms of water management and flood risk management.

The independent service validation in GMES RESPOND:the flood validation exercise

This article is aimed at providing a detailed description of the Flood Validation Exercise organised by the Independent Service Validation Group of the Global Monitoring for Environment and Security(GMES)RESPOND project.The aims of the validation exercise were:(1)providing a practical example of validation procedures in the frame of the GMES Emergency Response services;(2)executing a full-scale validation exercise able to cope with the requirements of an emergency service;and(3)better understanding the performances and limitations of Earth observation services for Flood Damage Mapping.This validation exercise is a first step of the main task to define the whole validation process for GMES services.When this is achieved,there will be knowledge concerning how well services meet the service specifications derived from the user needs.The present exercise has the purpose of gathering this knowledge.The output of this validation exercise can be used to characterise and qualify the performance and timeliness of Crisis and Damage Mapping Services.This paper summarises the methodology for the flood exercise validation and the results of product validation and inter-comparison.