{"title":"Beyond a fixed number: Investigating uncertainty in popular evaluation metrics of ensemble flood modeling using bootstrapping analysis","authors":"Tao Huang, Venkatesh Merwade","doi":"10.1111/jfr3.12982","DOIUrl":"https://doi.org/10.1111/jfr3.12982","url":null,"abstract":"<p>Evaluation of the performance of flood models is a crucial step in the modeling process. Considering the limitations of single statistical metrics, such as uncertainty bounds, Nash Sutcliffe efficiency, Kling Gupta efficiency, and the coefficient of determination, which are widely used in the model evaluation, the inherent properties and sampling uncertainty in these metrics are demonstrated. A comprehensive evaluation is conducted using an ensemble of one-dimensional Hydrologic Engineering Center's River Analysis System (HEC-RAS) models, which account for the uncertainty associated with the channel roughness and upstream flow input, of six reaches located in Indiana and Texas of the United States. Specifically, the effects of different prior distributions of the uncertainty sources, multiple high-flow scenarios, and various types of measurement errors in observations on the evaluation metrics are investigated using bootstrapping. Results show that the model performances based on the uniform and normal priors are comparable. The statistical distributions of all the evaluation metrics in this study are significantly different under different high-flow scenarios, thus suggesting that the metrics should be treated as “random” variables due to both aleatory and epistemic uncertainties and conditioned on the specific flow periods of interest. Additionally, the white-noise error in observations has the least impact on the metrics.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"17 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.12982","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140895286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using geomorphologic indicators in preparation for flood zoning and flood risk maps in the Kashafroud basin, Iran","authors":"Ghasem Panahi, Saeed Reza Khodashenas, Alireza Faridhosseini","doi":"10.1111/jfr3.12981","DOIUrl":"https://doi.org/10.1111/jfr3.12981","url":null,"abstract":"<p>The risk of flooding has become more significant in many parts of the world due to climate change and increased urbanization. Flood has devastating effects on infrastructure, and communities, causing damage to property and loss of life. Simulation of flood extent in a particular area is done by using various mathematical models, hydrologic-hydraulic models, and datasets. Flood modeling using hydraulic-hydrological models has many errors due to the lack of hydraulic-hydrologic data and insufficient statistical period length. This study demonstrates the fact that the geomorphological index (GI) method, which is based on the digital elevation model and requires little hydraulic-hydrologic data, is an effective method for flood modeling. Flood zoning based on GI was performed within the Kashafroud basin with 25, 100, and 200-year return periods by using geomorphic flood area (GFA) plugin in QGIS software. The true positive rates were 0.985, 0.989, and 0.992, respectively, which showed the high accuracy of flood zoning based on the GI method. Here proposed method showed that using the GFA plugin offers a good way for the flood risk assessment in a basin with the lack of measured data as an alternative to the hydraulic-hydrological methods.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"17 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.12981","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140895284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Monger, D. V. Spracklen, M. J. Kirkby, T. Willis
{"title":"Investigating the impact of woodland placement and percentage cover on flood peaks in an upland catchment using spatially distributed TOPMODEL","authors":"F. Monger, D. V. Spracklen, M. J. Kirkby, T. Willis","doi":"10.1111/jfr3.12977","DOIUrl":"10.1111/jfr3.12977","url":null,"abstract":"<p>Woodlands can reduce downstream flooding, but it is not well known how the extent and distribution of woodland affects reductions in peak flow. We used the spatially distributed TOPMODEL to simulate peak flow during a 1 in 50 year storm event for a range of broadleaf woodland scenarios across a 2.6 km<sup>2</sup> catchment in Northern England. Woodland reduced peak flow by 2.6%–15.3% depending on the extent and spatial distribution of woodland cover. Cross slope and riparian woodland resulted in larger reductions in peak flow, 4.9% and 3.3% for a 10-percentage point increase in woodland cover respectively, compared to a 2.7% reduction for woodland randomly located across the catchment. Our results demonstrate that increased woodland cover can reduce peak flows during a large storm event and suggest that targeted placement of woodland can maximise the effectiveness of natural flood management interventions.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"17 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.12977","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140425975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nafiseh Ghasemian Sorboni, Jinfei Wang, Mohammad Reza Najafi
{"title":"Automated first floor height estimation for flood vulnerability analysis using deep learning and Google Street View","authors":"Nafiseh Ghasemian Sorboni, Jinfei Wang, Mohammad Reza Najafi","doi":"10.1111/jfr3.12975","DOIUrl":"10.1111/jfr3.12975","url":null,"abstract":"<p>Flood events can cause extensive damage to physical infrastructure, pose risks to human life, and necessitate the reoccupation and rehabilitation of affected areas. A key parameter for flood vulnerability assessment is the first floor height (FFH), which also plays an important role in setting insurance premiums. Traditional methods for FFH estimation rely on ground surveys and site inspections, yet these approaches are both time-consuming and labor-intensive. In this study, we propose an alternative approach based on measurements derived from Google Street View (GSV) images and Deep Learning (DL). We employ the YOLOv5s algorithm, which belongs to a family of compound-scaled object detection models trained on the COCO dataset, for the detection of crucial building elements such as the Front Door (FD), stairs, and overall building extent. Additionally, we utilized the YOLOv5s algorithm to identify basement windows and assess the existence of basements. To validate our methodology, we conducted tests in both the Greater Toronto Area (GTA) and the state of Virginia in the United States. The results demonstrate an achievement of RMSE and Bias values of 81 cm and −50 cm for GTA, and 95 cm and −20 cm for the Virginia region, respectively.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"17 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.12975","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140428110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Questioning the use of ensembles versus individual climate model generated flows in future peak flood predictions: Plausibility and implications","authors":"Laxmi Prasad Devkota, Utsav Bhattarai, Rohini Devkota, Tek Maraseni, Suresh Marahatta","doi":"10.1111/jfr3.12978","DOIUrl":"10.1111/jfr3.12978","url":null,"abstract":"<p>Accurate estimation of design floods is necessary for developing effective flood-management strategies. Climate change (CC) studies on floods generally consider alterations in mean runoff using ensembles compared to a base period. In this study, we examined the plausibility and implications of applying individual climate model-generated flows versus their ensembles to estimate peak floods (magnitude and timing of occurrence), using Budhigandaki River Basin of Nepal as a case study. Annual maximum one-day floods were derived for four future climate scenario projections (<i>cold-dry</i>, <i>cold-wet</i>, <i>warm-wet</i>, and <i>warm-dry</i>) from simulated daily flow series. Future floods of six return periods estimated for the individual climate scenarios were compared with their “Ensemble” (combiner for the ensemble series is the arithmetic mean of daily floods), “Average,” and ‘Baseline.” Results showed that magnitudes of the flood peaks are such that those estimated using “Ensemble” < “Average” < individual series. We conclude that ensemble series should not be used for flood estimation because of the averaging effect. Designers should consider at the least the “Average” instead of the “Ensemble” series while designing climate-resilient flood structures. Furthermore, the occurrences of flood peaks are likely to be confined within the monsoon season for the “Ensemble” but spread out in the other months for the individual climate scenarios. This could have direct implications on the availability and mobilization of resources as well as the need for a year-round operational early warning system for flood risk management.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"17 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.12978","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140434452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Selection of representative indicators for flood risk assessment using marginal entropy and mutual information","authors":"Hongjun Joo, Wonyoung Choi, Chansoo Jeon","doi":"10.1111/jfr3.12976","DOIUrl":"10.1111/jfr3.12976","url":null,"abstract":"<p>Floods are the most frequent types of natural disasters. From the perspective of disaster management, indicators associated with floods are important for accurate flood risk assessment. However, the application of all indicators related to flood risk assessment decreases the evaluation efficiency, because the definitions of the indicators may overlap. Moreover, the volume of data required for collection and evaluation is significantly large, making the evaluation practically impossible. Thus, a scientific and objective method to select indicators for flood risk assessment based on the entropy theory was developed herein. First, the existing 28 assessment indicators were analyzed and probability-based data were constructed for each indicator considering 28 districts in a midwestern region of Korea. The information quantity for each indicator was then obtained using marginal entropy and mutual information generated in the entropy theory. Next, the total information quantity based on the numbers of combination of indicators was derived by considering the information quantity for each indicator and the overlapping mutual information between the indicators. The maximum amount of information (161.55) was obtained by combining 18 out of the 28 flood risk indicators. The selected 18 indicators reflected regional characteristics better than those used in the existing method, demonstrating that the flood risk of the target area could be adequately assessed.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"17 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.12976","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140438049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Flood risk investigation of pedestrians and vehicles in a mountainous city using a coupled coastal ocean and stormwater management model","authors":"Fei Liu, Chunjiao Ren, Yao Chen","doi":"10.1111/jfr3.12979","DOIUrl":"10.1111/jfr3.12979","url":null,"abstract":"<p>To examine the attributes, underlying mechanisms, and impacts of rainfall patterns on the vulnerability of pedestrians and vehicles to flood-induced instability within mountainous urban areas, we introduced an integrated urban flood model that combined the Storm Water Management Model (SWMM) and Finite Volume Coastal Ocean Model (FVCOM). We implemented this model in the Yuelai New Town of Chongqing, China. Our findings indicated that in the case of early peak rainfalls, there was a rapid surge in flood volume during the initial stages of rainfall , while this increase was more gradual when the peak rainfall was delayed. Furthermore, for events with the same return period, flood peaks resulting from later peak rainfalls covered a larger area compared with those from earlier peak rainfalls; however, this effect diminished with increasing return periods. As the return period was extended, the exposed risk area for pedestrians and vehicles expanded. Analysis of instability indices revealed that pedestrians exhibit a lower index compared with vehicles, adults fare better than children, and SUVs outperform sedans. The efficacy of our proposed model framework was demonstrated through its successful application in assessing urban flood risk and evaluating the instability index for pedestrians and vehicles within a mountainous urban setting.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"17 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.12979","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140448953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alistair Geddes, Andrew R. Black, Michael Cranston
{"title":"Integrating direct messaging with flood alerts and warnings: Insights into effectiveness from a registered public user population","authors":"Alistair Geddes, Andrew R. Black, Michael Cranston","doi":"10.1111/jfr3.12972","DOIUrl":"10.1111/jfr3.12972","url":null,"abstract":"<p>Direct messaging involving simultaneous mass transmission of brief text or voice messages to large numbers of recipients has become a frontline method in flood hazard communications. Messages are intended to serve as cues, drawing recipients' attention to changing conditions, yet the actual effectiveness of direct messaging among recipient groups remains under-examined. This article considers direct messaging within the Floodline public flood warning service in Scotland, implemented by the Scottish Environment Protection Agency (SEPA). Within Floodline, messaging is integrated with alerting and warning information, termed straightforwardly ‘Flood Alerts’ and ‘Flood Warnings’. Collaborating with SEPA, we conducted an online questionnaire survey of registered Floodline direct messaging recipients. In this article, our analysis focusses specifically on responses to three open-ended questions included in this survey, with an iterative qualitative coding approach employed to interpret themes of meaning from the question responses. This analysis gives a clear indication that recipients value Floodline and direct messaging. However, there are also questions raised over the utility of Flood Alerts and related messaging, which we elaborate in the findings and discussion, along with the scope for adding content, linking to other information, and developing closer relationships. Changes being developed by SEPA align with several of these findings.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.12972","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139959597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spatiotemporal variability of fall daily maximum flows in southern Quebec (Canada) from 1930 to 2018","authors":"Ali A. Assani","doi":"10.1111/jfr3.12971","DOIUrl":"10.1111/jfr3.12971","url":null,"abstract":"<p>Quebec is experiencing a significant increase in summer and fall temperatures and rainfall. This study compares the spatiotemporal variability of maximum daily flows generated by rainfall during the fall season (September–December) in relation to this climatic change and physiographic and land use factors. Analysis of the spatial variability of these maximum flows measured from 1930 to 2018 in 17 watersheds revealed that the magnitude of flows is approximately twice as low on the north shore as it is on the south shore south of 47° N. This difference is explained by three main factors: wetlands (negative correlation) and agricultural (positive correlation) surface area, and summer–fall total precipitation (positive correlation). As for the temporal variability of flows, the different Mann–Kendall statistical tests showed a significant increase in flows due to increased rainfall. The increase of flows was more widespread on the north shore than on the south because the storage capacity of wetlands and other water bodies does not change over time to store excess rainfall. On the south shore, the increase in flows over time is limited due to the significant reduction in agricultural areas since the modernization of agriculture. This reduction favored infiltration to the detriment of runoff.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"17 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.12971","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140455456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Peter S. Larson, Jamie Steis Thorsby, Xinyu Liu, Eleanor King, Carol J. Miller
{"title":"Crowd-based spatial risk assessment of urban flooding: Results from a municipal flood hotline in Detroit, MI","authors":"Peter S. Larson, Jamie Steis Thorsby, Xinyu Liu, Eleanor King, Carol J. Miller","doi":"10.1111/jfr3.12974","DOIUrl":"10.1111/jfr3.12974","url":null,"abstract":"<p>Climate change is increasing the frequency and intensity of extreme precipitation events, raising the risk of urban flood disasters. This study uses a crowd-sourced municipal call database to characterize the spatial distribution of flood risk in Detroit, MI. Call data including dates and addresses were obtained from the City of Detroit Department of Public Works for 2021. Calls were mapped and aggregated to census tract counts and merged with neighborhood-level data. Associations of predictors with flood calls were tested using spatial regression models. Flooding calls were located throughout the city but were concentrated in specific areas. Multivariate models of census tract level call counts indicated that increased poverty and Black, immigrant, and older residents were positively associated with flood calls, while increased elevation was associated with protective effects. Longer distances from waste water interceptors were associated with higher risk for calls. Crowd-sourced flood hotline call data can be used for effective spatial flood risk assessment. Though flooding occurs throughout the city of Detroit, infrastructural, neighborhood, and household factors influence flooding extent. Limitations included the self-reported nature of calls. Future modeling efforts might include input from local stakeholders to improve spatial risk assessment.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"17 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.12974","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139780877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}