The Vietnamese Mekong Delta(VMD),a critical agricultural hub,faces recurrent flooding that poses substantial threats to livelihoods and productivity.Ben Tre province,with its low-lying coastal terrain,is particularly ...The Vietnamese Mekong Delta(VMD),a critical agricultural hub,faces recurrent flooding that poses substantial threats to livelihoods and productivity.Ben Tre province,with its low-lying coastal terrain,is particularly vulnerable.Effective risk management and sustainable agricultural development necessitate a thorough understanding of these flood dynamics.This study leveraged the Google Earth Engine(GEE)platform and Sentinel-1 Synthetic Aperture Radar(SAR)imagery to analyze flood inundation patterns and their impacts on diverse agricultural land uses in Ben Tre province from 2015 to 2023.The methodology involved SAR data pre-processing,Otsu thresholding for water body delineation from VH polarization data and change detection using a 2020 land use map to quantify annual flooded areas and their impact on specific agricultural categories.The total inundated area peaked in 2018 at 58,334 ha,a significant increase from 27,934 ha in 2015,before stabilizing around 42,000–44,000 ha in 2021–2023.Flooded agricultural land mirrored this trend,increasing from 18,615 ha(2015)to a peak of 39,514 ha(2018),then decreasing to 28,841 ha(2023).Notably,wet rice cultivation experienced a 37.8%increase in its flooded area over the study period,while other annual crops and perennial crops saw increases of 38.9% and 68.4%,respectively.This research demonstrates the GEE platform’s efficacy with Sentinel-1 SAR for robust,long-term flood monitoring and impact assessment,revealing escalating flood pressure on key agricultural systems and an expansion of flooding beyond traditional low-lying zones,providing crucial data for adaptive land use planning.展开更多
The precision modeling of dam break floods can lead to formulation of proper emergency action plan to minimize flood impacts within the economic lifetime of the assets.Application of GIS techniques in integration with...The precision modeling of dam break floods can lead to formulation of proper emergency action plan to minimize flood impacts within the economic lifetime of the assets.Application of GIS techniques in integration with hydrological modeling for mapping of the flood inundated areas can play a momentous role in further minimizing the risk and likely damages.In the present study,dam break analysis using DAMBRK model was performed under various likely scenarios.Probable Maximum Flood (PMF)calculated for a return period of 1000 years using deterministic approach was adopted for dam break analysis of the proposed dam under various combinations of breach dimensions.The available downstream river cross-sections data sets were used as input in the model to generate the downstream flood profile.Dam break flow depths generated by the DAMBRK model under various combinations of structural failure are subsequently plotted on Digital Elevation Model(DEM)of the downstream of dam site to map the likely affected area.The simulation results reveals that in one particular case the flood without dam may be more intense if a rainfall of significant intensity takes place.展开更多
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 mult...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.展开更多
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. Burk...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.展开更多
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 fla...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.展开更多
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 Banglad...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 19<sup>th</sup> century and 20<sup>th</sup> 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.展开更多
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 wit...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.展开更多
Climate change and the increasing frequency of floods have undermined China’s food security.Creating detailed maps of flooded croplands is essential to improve prevention and adopt effective adaptation initiatives.Pr...Climate change and the increasing frequency of floods have undermined China’s food security.Creating detailed maps of flooded croplands is essential to improve prevention and adopt effective adaptation initiatives.Previous large-scale flood mapping efforts were hampered by limited meteorological and hydrological data,and the susceptibility of optical satellite images to cloud cover,leading to high uncertainty when downscaled to the cropland-scale.Here,using 4968 near-real-time(NRT)Sentinel-1 SAR(S1)images(spatial resolution:10 m),we generated China’s first set of high-resolution flooded cropland maps covering the period from 2017 to 2021.Our results demonstrate that croplands accounted for 43.8%to49.8%of China’s total flooded areas(ranging from 82,175 km^(2) to 122,037 km^(2)).We also created highresolution flood maps specifically for rice and maize crops.The inundated rice areas ranged from 8428 km^(2) to 22,123 km^(2),accounting for 22.34%to 41.91%of the annual flooded croplands,or 2.82%to7.45%of the annual rice cropland.In comparison,the inundated maize cropland fluctuated from 2619 km^(2) to 5397 km^(2),representing 5.38%to 13.56%of the annual flooded croplands.Our findings revealed extensive floods in rural areas,highlighting the urgent need to prioritize flood prevention and mitigation efforts in such regions.In light of China’s allocation of an additional 1-trillion-RMB treasury bonds for water infrastructure projects,the high-resolution flood maps can be used to select sites for flood control projects,and evaluate the impact of flooding on crop yields and food security,thus targeting poverty alleviation in rural areas of China.展开更多
Watershed management throughout the world has undergone revolutionary changes due to topographic data and the impact of climate change.Research in floodplain inundation mapping reflects these changes.As part of the cu...Watershed management throughout the world has undergone revolutionary changes due to topographic data and the impact of climate change.Research in floodplain inundation mapping reflects these changes.As part of the current research,two aspects are examined:the impact of climate change and the influence of Digital Elevation Model(DEM)error on the Nith River floodplain inundation mapping.The study uses terrain data generated from SWOOP elevation points as well as climate change emissions scenarios regionally assessed by CRCM and MNR(SRES A2 and SR B1).Using Log Pearson Type III,a widely used frequency analysis,floods with a 100-year return period for different climate scenarios and historical storm events were calculated,and a steady-state 1D hydrodynamic HEC-RAS model was applied to simulate extreme event floods.The impacts of DEM errors and climate change on flood simulations were quantified by analyzing the results of the model.A sensitivity analysis of the hydraulic models was performed consid-ering surface roughness and boundary conditions as potential uncertainties.As a result of the impact of climate change,the model indicated a significant increase in flood risk.It is not evident that DEM errors affect model perfor-mance,but they should be minimized to produce accurate flood maps.The sensitivity analyses demonstrated that surface roughness influences flood simulations.Geoprocessing procedures,HEC-RAS and GeoRAS in ArcGIS,have been used to extract the 100-year flood inundation maps for the current and future conditions and compare them with those for the existing conditions.The 19.8%increase in inundation corresponds specifically to the SRES A2 scenario,representing a high-emission future.The SR B1 scenario(low-emission)was analyzed for comparison,but did not produce the maximum inundation values.展开更多
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 ...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.展开更多
Flash floods(FFs)are amongst the most devastating hazards in arid regions in response to climate change and can cause the loss of agricultural land,human lives and infrastructure.One of the major challenges is the hig...Flash floods(FFs)are amongst the most devastating hazards in arid regions in response to climate change and can cause the loss of agricultural land,human lives and infrastructure.One of the major challenges is the high-intensity rainfall events affecting low-lying areas that are vulnerable to FF.Several works in this field have been conducted using ensemble machine learning models and geohydrological models.However,the current advancement of eXtreme deep learning,which is named eXtreme deep factorisation machine(xDeepFM),for FF susceptibility mapping(FSM)is lacking in the literature.The current study introduces a new model and employs a previously unapplied approach to enhance FSM for capturing the severity of floods.The proposed approach has three main objectives:(i)During-and after-flood effects are assessed through flood detection techniques using Sentinel-1 data.(ii)Flood inventory is updated using remote sensing-based methods.The derived flood effects are implemented in the next step.(iii)An FSM map is generated using an xDeepFM model.Therefore,this study aims to apply xDeepFM to estimate susceptible areas using 13 factors in the emirates of Fujairah,UAE.The performance metrics show a recall of 0.9488),an F1-score of 0.9107),precision of(0.8756)and an overall accuracy of 90.41%.The accuracy of the applied xDeepFM model is compared with that of traditional machine learning models,specifically the deep neural network(78%),support vector machine(85.4%)and random forest(88.75%).Random forest achieves high accuracy,which is due to its strong performance that depends on factors contribution,dataset size and quality,and available computational resources.Comparatively,the xDeepFM model works efficiently for complicated prediction problems having high non-collinearity and huge datasets.The obtained map denotes that the narrow basins,lowland coastal areas and riverbank areas up to 5 km(Fujairah)are highly prone to FF,whilst the alluvial plains in Al Dhaid and hilly regions in Fujairah show low probability.The coastal city areas are bounded by high-rise steep hills and the Gulf of Oman,which can elevate the water levels during heavy rainfall.Four major synchronised influencing factors,namely,rainfall,elevation,drainage density,distance from drainage and geomorphology,account for nearly 50%of the total factors contributing to a very high flood susceptibility.This study offers a platform for planners and decision makers to take timely actions on potential areas in mitigating the effects of FF.展开更多
Absence of reliable hydro-climatic information is among the bottlenecks for inadequate and improper management of stormwater runoff in rapidly-urbanizing catchments.This paper explores the influence of catchment heter...Absence of reliable hydro-climatic information is among the bottlenecks for inadequate and improper management of stormwater runoff in rapidly-urbanizing catchments.This paper explores the influence of catchment heterogeneity in understanding the proneness of urban catchments to stormwater-borne hazards.Using GIS techniques,satellite images,and field surveys,geomorphological features and hydrologic characteristics of the Mbezi River catchment in Dar es Salaam-Tanzania were modeled to understand variations in their influence on flood hazards occurrence throughout the study catchment.The findings reveal that with GIS techniques public,domain Digital Elevation Models(DEMs)can provide preliminary but useful insights to inform stormwater management decisions in cities with limited hydrological data.Specifically,the heterogeneity characterization of the case study catchment indicates that Mbezi River is fernleaf-shaped:it has a well-drained catchment(drainage density=1.9 km/km^(2)),with total relief and elongation ratios of 265 m and 0.25,respectively.Results further revealed that the catchment is comprised of many natural sinks(blue spots)that,upon enhancement,can retain about 18 percent of stormwater runoff that could otherwise contribute to downstream runoff challenges.About 68 percent of the major sinks(with potential volume>2.4 m3)are located along the river flood plain where land is publicly owned.Additionally,more than 11.6 ha of land(as property)and 168 buildings are in areas that were mapped to have large natural sinks and they are at risk to flooding when the sinks get filled.展开更多
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 fro...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.展开更多
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 ...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.展开更多
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 exerc...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.展开更多
Hydrologic analysis in watersheds lacking rain gauge stations has been a challenge and even those with stations that do not contain the required amount of data create problems in model verification.So,the study integr...Hydrologic analysis in watersheds lacking rain gauge stations has been a challenge and even those with stations that do not contain the required amount of data create problems in model verification.So,the study integrates the Next Generation Weather RadarIII precipitation data and the Personal Computer Storm Water Management Model(PCSWMM)for evaluating the model's effectiveness.The study further integrates 100-year return period precipitation intensity and PCSWMM to generate a one-dimensionalflood risk zone map,which shows the major sub-catchments under risk zones.Based on the identification of risk zones from PCSWMM,three different low-impact developments(LIDs),street plants,infiltration trenches,and green roofs are applied independently and uniformly to compare the decrease inflow.Thereafter,the prioritized list of critical sub-catchments from hydraulic modeling is compared with the compromise programming method,an approach for studying the decrement inflow by increasing LID application(infiltration trench)in thefirstfive critical sub-catchments,suggesting planners and researchers identify the most critical sub-catchments and develop future potential strategies.展开更多
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 transbou...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.展开更多
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 proje...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.展开更多
Flood control system risk evaluation is an effective measure for flood risk management and decisions.In order to make better flood risk decisions and thereby improve social and economic benefits,the flood control risk...Flood control system risk evaluation is an effective measure for flood risk management and decisions.In order to make better flood risk decisions and thereby improve social and economic benefits,the flood control risk evaluation index system should be built to quantify and normalize flood risk effectively and efficiently.Because the current evaluation index has the binary miscibility characteristic of fuzziness and clarity,this paper establishes a new flood control system risk evaluation method based on the theory of variable sets(VS).Through a comparison of flood control risk evaluation with variable fuzzy sets(VFS) in the same basin flood control system risk evaluation,it is revealed that the new method,i.e.,flood control risk evaluation with variable fuzzy/clear mixture sets(variable sets),will be reasonable in all cases.Finally,in one case study,i.e.,the flood control system risk evaluation of Fengman Reservoir Basin,which is located in the southeast central of Jilin Province in China,the risk evaluation levels for each county in the basin as well as the whole flood risk distribution map of the basin could be provided with the new method.This provides useful information for basin flood control planning and design.展开更多
基金funded by the University of Science,VNU-HCM under grant number T2023-107.
文摘The Vietnamese Mekong Delta(VMD),a critical agricultural hub,faces recurrent flooding that poses substantial threats to livelihoods and productivity.Ben Tre province,with its low-lying coastal terrain,is particularly vulnerable.Effective risk management and sustainable agricultural development necessitate a thorough understanding of these flood dynamics.This study leveraged the Google Earth Engine(GEE)platform and Sentinel-1 Synthetic Aperture Radar(SAR)imagery to analyze flood inundation patterns and their impacts on diverse agricultural land uses in Ben Tre province from 2015 to 2023.The methodology involved SAR data pre-processing,Otsu thresholding for water body delineation from VH polarization data and change detection using a 2020 land use map to quantify annual flooded areas and their impact on specific agricultural categories.The total inundated area peaked in 2018 at 58,334 ha,a significant increase from 27,934 ha in 2015,before stabilizing around 42,000–44,000 ha in 2021–2023.Flooded agricultural land mirrored this trend,increasing from 18,615 ha(2015)to a peak of 39,514 ha(2018),then decreasing to 28,841 ha(2023).Notably,wet rice cultivation experienced a 37.8%increase in its flooded area over the study period,while other annual crops and perennial crops saw increases of 38.9% and 68.4%,respectively.This research demonstrates the GEE platform’s efficacy with Sentinel-1 SAR for robust,long-term flood monitoring and impact assessment,revealing escalating flood pressure on key agricultural systems and an expansion of flooding beyond traditional low-lying zones,providing crucial data for adaptive land use planning.
文摘The precision modeling of dam break floods can lead to formulation of proper emergency action plan to minimize flood impacts within the economic lifetime of the assets.Application of GIS techniques in integration with hydrological modeling for mapping of the flood inundated areas can play a momentous role in further minimizing the risk and likely damages.In the present study,dam break analysis using DAMBRK model was performed under various likely scenarios.Probable Maximum Flood (PMF)calculated for a return period of 1000 years using deterministic approach was adopted for dam break analysis of the proposed dam under various combinations of breach dimensions.The available downstream river cross-sections data sets were used as input in the model to generate the downstream flood profile.Dam break flow depths generated by the DAMBRK model under various combinations of structural failure are subsequently plotted on Digital Elevation Model(DEM)of the downstream of dam site to map the likely affected area.The simulation results reveals that in one particular case the flood without dam may be more intense if a rainfall of significant intensity takes place.
基金supported by the National Key Research and Development Program of China under[grant number 2018YFF0215006]the Project Supported by the Open Fund of Key Laboratory of Urban Land R。
文摘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.
文摘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.
基金supported by the Key Project in the National Science and Technology Pillar Program during the Twelfth Five-Year Plan Period(Grant No.2012BAK10B04)the Specific Research Fund of the China Institute of Water Resources and Hydropower Research(Grant No.JZ0145B032014)
文摘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.
文摘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 19<sup>th</sup> century and 20<sup>th</sup> 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.
文摘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.
基金the Agritech National Research Center supported by European Union Next-Generation EU(PIANO NAZIONALE DI RIPRESA E RESILIENZA(PNRR)-MIS-SIONE 4 COMPONENTE 2,INVESTIMENTO 1.4-D.D.103217/06/2022,CN00000022)The China Scholarship Council。
文摘Climate change and the increasing frequency of floods have undermined China’s food security.Creating detailed maps of flooded croplands is essential to improve prevention and adopt effective adaptation initiatives.Previous large-scale flood mapping efforts were hampered by limited meteorological and hydrological data,and the susceptibility of optical satellite images to cloud cover,leading to high uncertainty when downscaled to the cropland-scale.Here,using 4968 near-real-time(NRT)Sentinel-1 SAR(S1)images(spatial resolution:10 m),we generated China’s first set of high-resolution flooded cropland maps covering the period from 2017 to 2021.Our results demonstrate that croplands accounted for 43.8%to49.8%of China’s total flooded areas(ranging from 82,175 km^(2) to 122,037 km^(2)).We also created highresolution flood maps specifically for rice and maize crops.The inundated rice areas ranged from 8428 km^(2) to 22,123 km^(2),accounting for 22.34%to 41.91%of the annual flooded croplands,or 2.82%to7.45%of the annual rice cropland.In comparison,the inundated maize cropland fluctuated from 2619 km^(2) to 5397 km^(2),representing 5.38%to 13.56%of the annual flooded croplands.Our findings revealed extensive floods in rural areas,highlighting the urgent need to prioritize flood prevention and mitigation efforts in such regions.In light of China’s allocation of an additional 1-trillion-RMB treasury bonds for water infrastructure projects,the high-resolution flood maps can be used to select sites for flood control projects,and evaluate the impact of flooding on crop yields and food security,thus targeting poverty alleviation in rural areas of China.
文摘Watershed management throughout the world has undergone revolutionary changes due to topographic data and the impact of climate change.Research in floodplain inundation mapping reflects these changes.As part of the current research,two aspects are examined:the impact of climate change and the influence of Digital Elevation Model(DEM)error on the Nith River floodplain inundation mapping.The study uses terrain data generated from SWOOP elevation points as well as climate change emissions scenarios regionally assessed by CRCM and MNR(SRES A2 and SR B1).Using Log Pearson Type III,a widely used frequency analysis,floods with a 100-year return period for different climate scenarios and historical storm events were calculated,and a steady-state 1D hydrodynamic HEC-RAS model was applied to simulate extreme event floods.The impacts of DEM errors and climate change on flood simulations were quantified by analyzing the results of the model.A sensitivity analysis of the hydraulic models was performed consid-ering surface roughness and boundary conditions as potential uncertainties.As a result of the impact of climate change,the model indicated a significant increase in flood risk.It is not evident that DEM errors affect model perfor-mance,but they should be minimized to produce accurate flood maps.The sensitivity analyses demonstrated that surface roughness influences flood simulations.Geoprocessing procedures,HEC-RAS and GeoRAS in ArcGIS,have been used to extract the 100-year flood inundation maps for the current and future conditions and compare them with those for the existing conditions.The 19.8%increase in inundation corresponds specifically to the SRES A2 scenario,representing a high-emission future.The SR B1 scenario(low-emission)was analyzed for comparison,but did not produce the maximum inundation values.
文摘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.
基金the University of Sharjah and Fujairah Research Centre(Grant No.1902041134-P)that helped to facilitate this research.
文摘Flash floods(FFs)are amongst the most devastating hazards in arid regions in response to climate change and can cause the loss of agricultural land,human lives and infrastructure.One of the major challenges is the high-intensity rainfall events affecting low-lying areas that are vulnerable to FF.Several works in this field have been conducted using ensemble machine learning models and geohydrological models.However,the current advancement of eXtreme deep learning,which is named eXtreme deep factorisation machine(xDeepFM),for FF susceptibility mapping(FSM)is lacking in the literature.The current study introduces a new model and employs a previously unapplied approach to enhance FSM for capturing the severity of floods.The proposed approach has three main objectives:(i)During-and after-flood effects are assessed through flood detection techniques using Sentinel-1 data.(ii)Flood inventory is updated using remote sensing-based methods.The derived flood effects are implemented in the next step.(iii)An FSM map is generated using an xDeepFM model.Therefore,this study aims to apply xDeepFM to estimate susceptible areas using 13 factors in the emirates of Fujairah,UAE.The performance metrics show a recall of 0.9488),an F1-score of 0.9107),precision of(0.8756)and an overall accuracy of 90.41%.The accuracy of the applied xDeepFM model is compared with that of traditional machine learning models,specifically the deep neural network(78%),support vector machine(85.4%)and random forest(88.75%).Random forest achieves high accuracy,which is due to its strong performance that depends on factors contribution,dataset size and quality,and available computational resources.Comparatively,the xDeepFM model works efficiently for complicated prediction problems having high non-collinearity and huge datasets.The obtained map denotes that the narrow basins,lowland coastal areas and riverbank areas up to 5 km(Fujairah)are highly prone to FF,whilst the alluvial plains in Al Dhaid and hilly regions in Fujairah show low probability.The coastal city areas are bounded by high-rise steep hills and the Gulf of Oman,which can elevate the water levels during heavy rainfall.Four major synchronised influencing factors,namely,rainfall,elevation,drainage density,distance from drainage and geomorphology,account for nearly 50%of the total factors contributing to a very high flood susceptibility.This study offers a platform for planners and decision makers to take timely actions on potential areas in mitigating the effects of FF.
文摘Absence of reliable hydro-climatic information is among the bottlenecks for inadequate and improper management of stormwater runoff in rapidly-urbanizing catchments.This paper explores the influence of catchment heterogeneity in understanding the proneness of urban catchments to stormwater-borne hazards.Using GIS techniques,satellite images,and field surveys,geomorphological features and hydrologic characteristics of the Mbezi River catchment in Dar es Salaam-Tanzania were modeled to understand variations in their influence on flood hazards occurrence throughout the study catchment.The findings reveal that with GIS techniques public,domain Digital Elevation Models(DEMs)can provide preliminary but useful insights to inform stormwater management decisions in cities with limited hydrological data.Specifically,the heterogeneity characterization of the case study catchment indicates that Mbezi River is fernleaf-shaped:it has a well-drained catchment(drainage density=1.9 km/km^(2)),with total relief and elongation ratios of 265 m and 0.25,respectively.Results further revealed that the catchment is comprised of many natural sinks(blue spots)that,upon enhancement,can retain about 18 percent of stormwater runoff that could otherwise contribute to downstream runoff challenges.About 68 percent of the major sinks(with potential volume>2.4 m3)are located along the river flood plain where land is publicly owned.Additionally,more than 11.6 ha of land(as property)and 168 buildings are in areas that were mapped to have large natural sinks and they are at risk to flooding when the sinks get filled.
基金supported by the NOAA JPSS Program Office[grant number#NA12NES4400008]NASA Disaster Program[grant number#NNX12AQ74G].
文摘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.
基金We thank the US Geological Survey (USGS) for providing no-cost Landsat data and supporting this work under Grant/Cooperative Agreement No. G18AP00077 to the first author.
文摘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.
基金supported by Future Development Research Funding Program FY 2017,Kyoto University Research Coordination Alliance。
文摘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.
基金University of Illinois System,Grant/Award Number:#107688。
文摘Hydrologic analysis in watersheds lacking rain gauge stations has been a challenge and even those with stations that do not contain the required amount of data create problems in model verification.So,the study integrates the Next Generation Weather RadarIII precipitation data and the Personal Computer Storm Water Management Model(PCSWMM)for evaluating the model's effectiveness.The study further integrates 100-year return period precipitation intensity and PCSWMM to generate a one-dimensionalflood risk zone map,which shows the major sub-catchments under risk zones.Based on the identification of risk zones from PCSWMM,three different low-impact developments(LIDs),street plants,infiltration trenches,and green roofs are applied independently and uniformly to compare the decrease inflow.Thereafter,the prioritized list of critical sub-catchments from hydraulic modeling is compared with the compromise programming method,an approach for studying the decrement inflow by increasing LID application(infiltration trench)in thefirstfive critical sub-catchments,suggesting planners and researchers identify the most critical sub-catchments and develop future potential strategies.
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China(Grant Nos.91547111,51379027&51409043)Natural Science Foundation of Liaoning Province(Grant No.2015020608)National Science and Technology Pillar Program during the Twelfth Five-year Plan Period(Grant No.2015BAB07B03)
文摘Flood control system risk evaluation is an effective measure for flood risk management and decisions.In order to make better flood risk decisions and thereby improve social and economic benefits,the flood control risk evaluation index system should be built to quantify and normalize flood risk effectively and efficiently.Because the current evaluation index has the binary miscibility characteristic of fuzziness and clarity,this paper establishes a new flood control system risk evaluation method based on the theory of variable sets(VS).Through a comparison of flood control risk evaluation with variable fuzzy sets(VFS) in the same basin flood control system risk evaluation,it is revealed that the new method,i.e.,flood control risk evaluation with variable fuzzy/clear mixture sets(variable sets),will be reasonable in all cases.Finally,in one case study,i.e.,the flood control system risk evaluation of Fengman Reservoir Basin,which is located in the southeast central of Jilin Province in China,the risk evaluation levels for each county in the basin as well as the whole flood risk distribution map of the basin could be provided with the new method.This provides useful information for basin flood control planning and design.
