Arnaud Cerbelaud, Cédric H. David, Sylvain Biancamaria, Jeffrey Wade, Manu Tom, Renato Prata de Moraes Frasson, George H. Allen, Hana Thurman, Denis Blumstein
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We propose the use of peak event spatial coverage, referred to as “length”, as an analog to event duration. Our analysis is performed in the Mississippi basin using a dense in situ network. We reveal that peak flow events range in length from around 75 to 1,800 km with a median (mean) value of 330 (520) km along the basin's largest rivers. Our analysis also suggests that spatial sampling needs to be a factor of 4 (2) finer in resolution than peak flow lengths to detect 81% ± 13% (70% ± 20%) of events and to estimate their length within 84% ± 3% (67% ± 12%) median accuracy. We evaluate the connection between temporal and spatial scales of peak flows and show that events with longer durations also affect larger extents. We finally discuss the implications for the design of satellite missions concerned with capturing floods across space.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"25 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatial Hydrographs of River Flow and Their Analysis for Peak Event Detection in the Context of Satellite Sampling\",\"authors\":\"Arnaud Cerbelaud, Cédric H. David, Sylvain Biancamaria, Jeffrey Wade, Manu Tom, Renato Prata de Moraes Frasson, George H. Allen, Hana Thurman, Denis Blumstein\",\"doi\":\"10.1029/2024wr038444\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The study of river dynamics has long relied on the analysis of traditional in situ hydrographs. 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Spatial Hydrographs of River Flow and Their Analysis for Peak Event Detection in the Context of Satellite Sampling
The study of river dynamics has long relied on the analysis of traditional in situ hydrographs. This graphical representation of temporal variability at a given location is so ubiquitous that the mere term “hydrograph” is widely recognized as a time series. While such a “temporal hydrograph” is well suited for in situ data analysis, it fails to represent hydrologic variability across space at a given time; a perspective that characterizes satellite-based hydrologic observations. Here we argue that the concept of “spatial hydrograph” should be the focus of its own dedicated scrutiny. We build “space series” of river discharge and present their analysis in the context of peak flow event detection. We propose the use of peak event spatial coverage, referred to as “length”, as an analog to event duration. Our analysis is performed in the Mississippi basin using a dense in situ network. We reveal that peak flow events range in length from around 75 to 1,800 km with a median (mean) value of 330 (520) km along the basin's largest rivers. Our analysis also suggests that spatial sampling needs to be a factor of 4 (2) finer in resolution than peak flow lengths to detect 81% ± 13% (70% ± 20%) of events and to estimate their length within 84% ± 3% (67% ± 12%) median accuracy. We evaluate the connection between temporal and spatial scales of peak flows and show that events with longer durations also affect larger extents. We finally discuss the implications for the design of satellite missions concerned with capturing floods across space.
期刊介绍:
Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.