scholarly journals Flooding duration and volume more important than peak discharge in explaining 18 years of gravel–cobble river change

2021 ◽  
Author(s):  
Arielle A. Gervasi ◽  
Gregory B. Pasternack ◽  
Amy E. East
Keyword(s):  
Peak Discharge ◽  
Flooding Duration

Peak discharge determinations for floods in Washington, November 1949 to June 1950

1951 ◽  
Author(s):  
G.L. Bodhaine ◽  
W.H. Robinson
Keyword(s):  
Peak Discharge

A STUDY ON RELATIONSHIP BETWEEN ACCUMULATED RAINFALL AND FLOOD PEAK DISCHARGE USING LARGE ENSEMBLE EXPERIMENT DATA

2019 ◽  
Vol 75 (2) ◽  
pp. I_1075-I_1080
Author(s):  
Yuya KAGEYAMA ◽  
Masafumi YAMADA ◽  
Satoshi WATANABE ◽  
Koji IKEUCHI
Keyword(s):  
Peak Discharge ◽  
Experiment Data ◽  
Large Ensemble ◽  
Flood Peak ◽  
Accumulated Rainfall

scholarly journals Unmanned Aerial Systems-Aided Post-Flood Peak Discharge Estimation in Ephemeral Streams

2020 ◽  
Vol 12 (24) ◽  
pp. 4183
Author(s):  
Emmanouil Andreadakis ◽  
Michalis Diakakis ◽  
Emmanuel Vassilakis ◽  
Georgios Deligiannakis ◽  
Antonis Antoniadis ◽  
...  
Keyword(s):  
Flash Flood ◽  
Traditional Approach ◽  
Peak Discharge ◽  
Unmanned Aerial Systems ◽  
Monitoring Networks ◽  
Response Dynamics ◽  
Hydrologic Modelling ◽  
Flood Peak ◽  
Field Evidence ◽  
Aerial Systems

The spatial and temporal scale of flash flood occurrence provides limited opportunities for observations and measurements using conventional monitoring networks, turning the focus to event-based, post-disaster studies. Post-flood surveys exploit field evidence to make indirect discharge estimations, aiming to improve our understanding of hydrological response dynamics under extreme meteorological forcing. However, discharge estimations are associated with demanding fieldwork aiming to record in small timeframes delicate data and data prone-to-be-lost and achieve the desired accuracy in measurements to minimize various uncertainties of the process. In this work, we explore the potential of unmanned aerial systems (UAS) technology, in combination with the Structure for Motion (SfM) and optical granulometry techniques in peak discharge estimations. We compare the results of the UAS-aided discharge estimations to estimates derived from differential Global Navigation Satellite System (d-GNSS) surveys and hydrologic modelling. The application in the catchment of the Soures torrent in Greece, after a catastrophic flood, shows that the UAS-aided method determined peak discharge with accuracy, providing very similar values compared to the ones estimated by the established traditional approach. The technique proved to be particularly effective, providing flexibility in terms of resources and timing, although there are certain limitations to its applicability, related mostly to the optical granulometry as well as the condition of the channel. The application highlighted important advantages and certain weaknesses of these emerging tools in indirect discharge estimations, which we discuss in detail.

scholarly journals Process-Based Modeling of the High Flow of a Semi-Mountain River under Current and Future Climatic Conditions: A Case Study of the Iya River (Eastern Siberia)

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1042
Author(s):  
Andrey Kalugin
Keyword(s):  
Water Level ◽  
River Basin ◽  
21St Century ◽  
Residential Buildings ◽  
High Flow ◽  
Peak Discharge ◽  
Future Climate ◽  
Future Climate Change ◽  
Generation Model ◽  
Annual Peak

The purpose of the study was to analyze the formation conditions of catastrophic floods in the Iya River basin over the observation period, as well as a long-term forecast of the impacts of future climate change on the characteristics of the high flow in the 21st century. The semi-distributed process-based Ecological Model for Applied Geophysics (ECOMAG) was applied to the Iya River basin. Successful model testing results were obtained for daily discharge, annual peak discharge, and discharges exceeding the critical water level threshold over the multiyear period of 1970–2019. Modeling of the high flow of the Iya River was carried out according to a Kling–Gupta efficiency (KGE) of 0.91, a percent bias (PBIAS) of −1%, and a ratio of the root mean square error to the standard deviation of measured data (RSR) of 0.41. The preflood coefficient of water-saturated soil and the runoff coefficient of flood-forming precipitation in the Iya River basin were calculated in 1980, 1984, 2006, and 2019. Possible changes in the characteristics of high flow over summers in the 21st century were calculated using the atmosphere–ocean general circulation model (AOGCM) and the Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES) as the boundary conditions in the runoff generation model. Anomalies in values were estimated for the middle and end of the current century relative to the observed runoff over the period 1990–2019. According to various Representative Concentration Pathways (RCP-scenarios) of the future climate in the Iya River basin, there will be less change in the annual peak discharge or precipitation and more change in the hazardous flow and its duration, exceeding the critical water level threshold, at which residential buildings are flooded.

scholarly journals Analysis on the Return Period of “7.26” Rainstorm and Flood in 2017 in the Wudinghe Basin

2018 ◽  
Vol 246 ◽  
pp. 01105
Author(s):  
Shuang-yan Jin ◽  
Wen-yong Gao ◽  
Si-wu Luo ◽  
Ya-jun Gao
Keyword(s):  
Return Period ◽  
Peak Discharge ◽  
Observation Data ◽  
Historical Survey ◽  
Annual Maximum ◽  
Frequency Curve ◽  
Recurrence Period ◽  
Fitting Method ◽  
Curve Fitting Method ◽  
Hydrological Station

The return period of "7.26" rainstorm flood in 2017 in Wudinghe basin is analyzed by the method of P-III distribution. The Lijiahe and Dingjiagou stations with long rainfall observation data in the rainstorm area are selected, and the frequency curve of the annual maximum 24 hours rainfall are established, and the recurrence period of rainfall stations in rainstorm area are estimated according to the parameters determined by the curve fitting method. The frequency curve of the annual maximum peak discharge of Baijiachuan hydrological stations and so on are established, and the return period are analyzed in combination with the historical survey floods. The results show that the return period of Zhaojiabian of heavy rainfall center is about 100 years, and which of the other stations over than 200mm in Wudinghe basin is about 30~90 years; while the return period of the peak discharge of Baijiachuan and Suide hydrological station is about 30 and 20 years respectively.

Digital model of corrected accumulated flow for peak discharge data acquisition and drainage system design

2003 ◽  
Vol 69 (3-4) ◽  
pp. 345-358 ◽  
Author(s):  
F.J Fernández ◽  
R Menéndez-Duarte ◽  
R Valdés-Riera
Keyword(s):  
Data Acquisition ◽  
System Design ◽  
Drainage System ◽  
Peak Discharge ◽  
Digital Model ◽  
Discharge Data

Closure to “Channel Slope Effect on Peak Discharge of Natural Streams”

1971 ◽  
Vol 97 (7) ◽  
pp. 1134-1134
Author(s):  
Charles L. Armentrout ◽  
Robert B. Bissell
Keyword(s):  
Peak Discharge ◽  
Natural Streams ◽  
Channel Slope

Discussion of “Channel Slope Effect on Peak Discharge of Natural Streams”

1970 ◽  
Vol 96 (12) ◽  
pp. 2620-2622
Author(s):  
Jayant P. Patel ◽  
Arvind P. Mody
Keyword(s):  
Peak Discharge ◽  
Natural Streams ◽  
Channel Slope
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