scholarly journals Annual Peak-Flow Frequency Characteristics and (or) Peak Dam-Pool-Elevation Frequency Characteristics of Dry Dams and Selected Streamflow-Gaging Stations in the Great Miami River Basin, Ohio

2009 ◽  
Author(s):  
G.F. Koltun
Keyword(s):  
River Basin ◽  
Peak Flow ◽  
Frequency Characteristics ◽  
Annual Peak ◽  
Flow Frequency

scholarly journals Automatic Web Procedure for Calculating Flood Flow Frequency

Water ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 14 ◽  
Author(s):  
Pierluigi De Rosa ◽  
Andrea Fredduzzi ◽  
Annalisa Minelli ◽  
Corrado Cencetti
Keyword(s):  
River Basin ◽  
Return Period ◽  
Peak Flow ◽  
Curve Number ◽  
Computational Procedure ◽  
Difficult Problem ◽  
Run Off ◽  
Tiber River ◽  
Flow Frequency ◽  
Flood Flow

The estimated flood flow frequency in a particular cross-section of a riverbed for a given return period is a topic of great interest for its application in hydrological, geomorphological and hydrogeological fields. Nevertheless, to establish a one-to-one relationship between rainfall and peak flow is a difficult problem to solve, due to the great number of factors involved (intensity and distribution of rainfall, hydromorphological characteristics of the watershed, type and distribution of vegetation, soil saturation conditions, etc.). In Italy, the Tiber River Basin Authority has developed a method to evaluate peak flows in the watersheds within the Tiber Basin. The relationship between rainfall depth with an assigned return period (RP) and the duration of the event was determined using data from 165 gauging stations throughout the Basin and in the neighbourhoods with respect to rainfall from 1 to 24 h and/or from 1 to 5 days. To calculate the peak flow with an assigned RP in small watersheds (area < 100 km 2 ), the Tiber River Basin Authority proposed a methodology that combines the results of regional precipitation analysis of a duration from 1 to 24 h with the Curve Number method, which allows the volume of net rainfall (i.e., the rainfall that contributes to producing the peak flow) to be quantified. Such procedure includes the calculation of various parameters (run-off time, local rainfall and areal rainfall, net rainfall) in order to obtain the value of peak flow. To facilitate the use of this procedure, a WebGIS system has been developed, based on a series of scripts that calculate the values for the above parameters. The user only has to choose the point corresponding to the section of the channel in order to determine the peak flow and the return period. The computational procedure is performed using GRASS GIS that interfaces with the system using the standard WPS; the system returns to output a report with details of the various calculations of parameters and, as a final result, the value of requested peak flow.

COMPARISON OF FLOOD DISTRIBUTION MODELS FOR JOHOR RIVER BASIN

2015 ◽  
Vol 74 (11) ◽  
Author(s):  
Ahmad Zuhdi Ismail ◽  
Zulkifli Yusop ◽  
Zainab Yusof
Keyword(s):  
River Basin ◽  
Peak Flow ◽  
Maximum Flow ◽  
Flood Event ◽  
Distribution Model ◽  
Annual Maximum ◽  
Flow Data ◽  
Water Control ◽  
Distribution Models ◽  
Annual Peak

One of the most useful and commonly used parameters to describe a flood event is peak flow or annual maximum flood. In many localities, storm water control facilities are required and their sizes are determined based on certain peak flow magnitude. This study aimed at estimating the average recurrent interval (ARI) of flood event for Johor River basin based on the distributions of annual peak flow. The analysis used annual maximum flow data from July 1965 to June 2010 recorded at the Rantau Panjang gauging station. Five distribution models, namely Generalized Extreme Value (GEV), Lognormal, Pearson 5, Weibull and Gamma were tested. The goodness fit test (GOF) of Kolmogorov-Smirnov (K-S) was used to evaluate and estimate the best-fitted distribution. The results reaffirm the current practice that GEV is still the best-fitted distribution model for fitting the annual peak flow data. On the other hand, gamma distribution showed the poorest result.

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 Dependence Between Extreme Rainfall Events and the Seasonality and Bivariate Properties of Floods. A Continuous Distributed Physically-Based Approach

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1896 ◽  
Author(s):  
Gabriel-Martin ◽  
Sordo-Ward ◽  
Garrote ◽  
García
Keyword(s):  
Peak Flow ◽  
Total Duration ◽  
Weather Generator ◽  
Return Periods ◽  
Storm Events ◽  
Stochastic Weather Generator ◽  
Rainfall Events ◽  
Annual Peak ◽  
Extreme Flood ◽  
Physically Based

This paper focuses on proposing the minimum number of storms necessary to derive the extreme flood hydrographs accurately through event-based modelling. To do so, we analyzed the results obtained by coupling a continuous stochastic weather generator (the Advanced WEather GENerator) with a continuous distributed physically-based hydrological model (the TIN-based real-time integrated basin simulator), and by simulating 5000 years of hourly flow at the basin outlet. We modelled the outflows in a basin named Peacheater Creek located in Oklahoma, USA. Afterwards, we separated the independent rainfall events within the 5000 years of hourly weather forcing, and obtained the flood event associated to each storm from the continuous hourly flow. We ranked all the rainfall events within each year according to three criteria: Total depth, maximum intensity, and total duration. Finally, we compared the flood events obtained from the continuous simulation to those considering the N highest storm events per year according to the three criteria and by focusing on four different aspects: Magnitude and recurrence of the maximum annual peak-flow and volume, seasonality of floods, dependence among maximum peak-flows and volumes, and bivariate return periods. The main results are: (a) Considering the five largest total depth storms per year generates the maximum annual peak-flow and volume, with a probability of 94% and 99%, respectively and, for return periods higher than 50 years, the probability increases to 99% in both cases; (b) considering the five largest total depth storms per year the seasonality of flood is reproduced with an error of less than 4% and (c) bivariate properties between the peak-flow and volume are preserved, with an error on the estimation of the copula fitted of less than 2%.

scholarly journals Seasonal Surface Runoff Characteristics in the Semiarid Region of Western Heilongjiang Province in Northeast China—A Case of the Alun River Basin

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 557
Author(s):  
Jinbai Huang ◽  
Kotaro Tagawa ◽  
Bin Wang ◽  
Jiawei Wen ◽  
Jingcai Wang
Keyword(s):  
River Basin ◽  
Surface Runoff ◽  
Peak Flow ◽  
Annual Runoff ◽  
Annual Rainfall ◽  
Semiarid Region ◽  
Heilongjiang Province ◽  
Runoff Coefficient ◽  
Total Runoff ◽  
Annual Means

Water resource issues are a challenging area of research in semiarid regions of the world. The objective of the current study was to reveal the main characteristics of seasonal surface runoff for the semiarid western Heilongjiang Province of China. The Alun River Basin, which has hydrological and meteorological characteristics of the local region, was adopted as the study location. A distributed rainfall-runoff combined with snowmelt hydrological model was used to carry out the runoff calculation for the six years (2011–2016). The results indicated that: The mean annual runoff coefficient was 0.34; snowmelt runoff accounted for 2.2% of annual total runoff in 2011–2016; the main part of annual rainfall and runoff was concentrated in the rainy season from June to September, the proportions of rainfall and runoff in this period were 78% and 86% to that of the annual means of 2011–2016; the peak flow represents a decreased trend since 2013, and evidently decreased in 2015 and 2016; less annual precipitation complex with paddy field retention of rainwater and runoff led to the peak flow and annual runoff coefficient in 2016 were obviously lower than that of annual means of 2011–2016. The results are expected to provide the basis for rational development and utilization of surface runoff, and further researches on surface runoff and water resources of the semiarid western Heilongjiang Province of China.

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