scholarly journals Estimation of synthetic flood design hydrographs using a distributed rainfall–runoff model coupled with a copula-based single storm rainfall generator

2014 ◽  
Vol 14 (7) ◽  
pp. 1819-1833 ◽  
Author(s):  
A. Candela ◽  
G. Brigandì ◽  
G. T. Aronica
Keyword(s):  
Curve Number ◽  
Geographical Information ◽  
Rainfall Runoff ◽  
Unit Hydrograph ◽  
Digital Elevation ◽  
Design Hydrographs ◽  
Rainfall Runoff Model ◽  
Storm Rainfall ◽  
Elevation Model ◽  
Runoff Model

Abstract. In this paper a procedure to derive synthetic flood design hydrographs (SFDH) using a bivariate representation of rainfall forcing (rainfall duration and intensity) via copulas, which describes and models the correlation between two variables independently of the marginal laws involved, coupled with a distributed rainfall–runoff model, is presented. Rainfall–runoff modelling (R–R modelling) for estimating the hydrological response at the outlet of a catchment was performed by using a conceptual fully distributed procedure based on the Soil Conservation Service – Curve Number method as an excess rainfall model and on a distributed unit hydrograph with climatic dependencies for the flow routing. Travel time computation, based on the distributed unit hydrograph definition, was performed by implementing a procedure based on flow paths, determined from a digital elevation model (DEM) and roughness parameters obtained from distributed geographical information. In order to estimate the primary return period of the SFDH, which provides the probability of occurrence of a hydrograph flood, peaks and flow volumes obtained through R–R modelling were treated statistically using copulas. Finally, the shapes of hydrographs have been generated on the basis of historically significant flood events, via cluster analysis. An application of the procedure described above has been carried out and results presented for the case study of the Imera catchment in Sicily, Italy.

scholarly journals Estimation of flood design hydrographs using bivariate analysis (copula) and distributed hydrological modelling

2014 ◽  
Vol 2 (1) ◽  
pp. 27-79
Author(s):  
A. Candela ◽  
G. Brigandí ◽  
G. T. Aronica
Keyword(s):  
Curve Number ◽  
Geographical Information ◽  
Bivariate Analysis ◽  
Rainfall Runoff ◽  
Unit Hydrograph ◽  
Design Flood ◽  
Design Hydrographs ◽  
Rainfall Runoff Model ◽  
Elevation Model ◽  
Definition Of

Abstract. In this paper a procedure to derive Flood Design Hydrographs (FDH) using a bivariate representation of rainfall forcing (rainfall duration and intensity) using copulas, which describe and model the correlation between these two variables independently of the marginal laws involved, coupled with a distributed rainfall-runoff model is presented. Rainfall-runoff modelling for estimating the hydrological response at the outlet of a watershed used a conceptual fully distributed procedure based on the soil conservation service – curve number method as excess rainfall model and a distributed unit hydrograph with climatic dependencies for the flow routing. Travel time computation, based on the definition of a distributed unit hydrograph, has been performed, implementing a procedure using flow paths determined from a digital elevation model (DEM) and roughness parameters obtained from distributed geographical information. In order to estimate the return period of the FDH which give the probability of occurrence of a hydrograph flood peaks and flow volumes obtained through R-R modeling has been statistically treated via copulas. The shape of hydrograph has been generated on the basis of a modeled flood events, via cluster analysis. The procedure described above was applied to a case study of Imera catchment in Sicily, Italy. The methodology allows a reliable and estimation of the Design Flood Hydrograph and can be used for all the flood risk applications, i.e. evaluation, management, mitigation, etc.

scholarly journals Application of a continuous Rainfall-Runoff model to the basin of Kosynthos river using the hydrological software HEC-HMS

2014 ◽  
Vol 16 (1) ◽  
pp. 188-203 ◽  
Keyword(s):  
Soil Conservation ◽  
Curve Number ◽  
Hydrologic Model ◽  
Army Corps ◽  
Soil Conservation Service ◽  
Rainfall Runoff ◽  
Runoff Hydrograph ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Continuous Rainfall

<div> <h1 style="text-align: justify;"><span style="font-size:11px;"><span style="font-family:arial,helvetica,sans-serif;">In this paper, the application of a continuous rainfall-runoff model to the basin of Kosynthos River (district of Xanthi, Thrace, northeastern Greece), as well as the comparison of the computational runoff results with field discharge measurements are presented. The rainfall losses are estimated by the widely known Soil Conservation Service-Curve Number model, while the transformation of rainfall excess into direct runoff hydrograph is made by using the dimensionless unit hydrograph of Soil Conservation Service. The baseflow is computed by applying an exponential recession model. The routing of the total runoff hydrograph from the outlet of a sub-basin to the outlet of the whole basin is achieved by the Muskingum-Cunge model. The application of this complex hydrologic model was elaborated with the HEC-HMS 3.5 Hydrologic Modeling System of the U.S. Army Corps of Engineers. The results of the comparison between computed and measured discharge values are very satisfactory.</span></span></h1> </div> <p>&nbsp;</p>

scholarly journals Uncertainty and sensitivity analysis of GIS based continuous hydrological modelling

2021 ◽  
Author(s):  
Harry R. Manson
Keyword(s):  
Sensitivity Analysis ◽  
Curve Number ◽  
Monte Carlo Analysis ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Lumped Model ◽  
Daily Average ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

The impact of uncertainty in spatial and a-spatial lumped model parameters for a continuous rainfall-runoff model is evaluated with respect to model prediction. The model uses a modified SCS-Curve Number approach that is loosely coupled with a geographic information system (GIS). The rainfall-runoff model uses daily average inputs and is calibrated using a daily average streamflow record for the study site. A Monte Carlo analysis is used to identify total model uncertainty while sensitivity analysis is applied using both a one-at-a-time (OAT) approach as well as through application of the extended Fourier Amplitude Sensitivity Technique (FAST). Conclusions suggest that the model is highly followed by model inputs and finally the Curve Number. While the model does not indicate a high degree of sensitivity to the Curve Number at present conditions, uncertainties in Curve Number estimation can potentially be the cause of high predictive errors when future development scenarios are evaluated.

scholarly journals Development of rainfall – runoff model for extreme storm events in the Bagmati River Basin, Nepal

2021 ◽  
Vol 1 (1) ◽  
pp. 158-173
Author(s):  
Nirajan Devkota ◽  
Narendra Man Shrestha
Keyword(s):  
River Basin ◽  
Monsoon Season ◽  
Capital City ◽  
Rainfall Runoff ◽  
Unit Hydrograph ◽  
Peak Maximum ◽  
Hourly Data ◽  
Rainfall Runoff Model ◽  
Bagmati River ◽  
Runoff Model

This study is based on the Bagmati river basin that flows along with the capital city, Kathmandu which is a small and topographically steep basin. Major flood occurring in 1993 and 2002 as stated in the report of DWIDP shows that the basin is subjected to water-induced disaster in monsoon season affecting people and property. This study focuses on the development of a rainfall-runoff model for Bagmati basin in HEC-HMS using the Synthetic Unit Hydrograph (SUH) with Khokana as the outlet. The coefficients for SUH like Lag time coefficient (Ct), peak discharge coefficient (Cp), unit hydrograph widths at 50% and 75% of peak and base time were determined calibrating the Synder’s equation where Ct varies from 0.244 to 1.016 and Cp varies from 0.439 to 0.410. The rainfall-runoff model in HEC-HMS has been calibrated from daily data of 1992-2013 and validated from hourly data for July 2011, August 2012, and July 2013. Furthermore, the model has been tested to compare the discharge for various return periods with the observed ones which are in close agreement. The determination of Peak Maximum Flood (PMF) using the calculated Peak Maximum Precipitation (PMP) is also another application of the model which can be used to design various hydraulic structures. Thus the values of coefficients, Ct and Cp can be used to construct unit hydrograph for the basin. Moreover, the satisfactory performance of the model during calibration and validation proves the applicability of the model in flood forecasting and early warning.

HYDROGEOMORPHOLOGICAL MODELING OF KHOR OMAR OMDURMAN - SUDAN BY USING GIS

2020 ◽  
pp. 20-36
Author(s):  
Omar Abd Almajd Sayd AHMMAD ◽  
Alimam omar ALİMAM AİL ◽  
Hussein Salem Hussein SALEM ◽  
Muzamil Elrais Ahmed ALI
Keyword(s):  
Meteorological Data ◽  
Satellite Image ◽  
Curve Number ◽  
Digital Data ◽  
Geographical Information ◽  
Hydrologic Modelling ◽  
Model Soil ◽  
Digital Elevation ◽  
Elevation Model

e study addressed the hydro geomorphological modeling of koher Omar Oum Dorman Area by analyzing many digital data, including satellite Image, and Digital Elevation Model, soil and meteorological data, by using ARC.GIS -WMS - Hydrologic Engineering Center – Hydrologic Modelling System, (HEC-HMS). in order to analyzing geomorphological characteristics and hydro geomorphological, estimation of the amount of runoff and determination of affected areas through Hydro morphometric measurements, determination of soil varieties and land cover to extract Curve number (CN) the study found that the annual surface runoff volume is 21830.5M3 – 33938.1M3 areas affected by runoff are located to the east and south-east of the basin of koher Omar, and the study Reflced Meany recommendetoin, the most important of which is the utilization of water in development processes and the application of Geographical information system in hydro geomorphological studies. Key words: : GIS – RS - Rain off - WMS.

scholarly journals Uncertainty and sensitivity analysis of GIS based continuous hydrological modelling

2021 ◽  
Author(s):  
Harry R. Manson
Keyword(s):  
Sensitivity Analysis ◽  
Curve Number ◽  
Monte Carlo Analysis ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Lumped Model ◽  
Daily Average ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

The impact of uncertainty in spatial and a-spatial lumped model parameters for a continuous rainfall-runoff model is evaluated with respect to model prediction. The model uses a modified SCS-Curve Number approach that is loosely coupled with a geographic information system (GIS). The rainfall-runoff model uses daily average inputs and is calibrated using a daily average streamflow record for the study site. A Monte Carlo analysis is used to identify total model uncertainty while sensitivity analysis is applied using both a one-at-a-time (OAT) approach as well as through application of the extended Fourier Amplitude Sensitivity Technique (FAST). Conclusions suggest that the model is highly followed by model inputs and finally the Curve Number. While the model does not indicate a high degree of sensitivity to the Curve Number at present conditions, uncertainties in Curve Number estimation can potentially be the cause of high predictive errors when future development scenarios are evaluated.

Digital Elevation Hydrological Modelling in a Small Catchment in South Australia

2003 ◽  
Vol 34 (3) ◽  
pp. 161-178
Author(s):  
H. Sun ◽  
P. S. Cornish ◽  
T. M. Daniell
Keyword(s):  
Soil Moisture ◽  
Spatial Data ◽  
South Australia ◽  
Moisture Distribution ◽  
Rainfall Runoff ◽  
Estimation Errors ◽  
Small Catchment ◽  
Digital Elevation ◽  
Rainfall Runoff Model ◽  
Runoff Model

A rainfall runoff model based on a digital elevation model (DEM) was applied to a small catchment in Happy Valley, South Australia to predict catchment storm runoff. The DEM was used to partition the catchment into several thousand irregular shaped elements. These elements, with an average size of 825 m2 each, form an interconnected one-dimensional flow network for runoff routing. The rainfall runoff model is a kinematic flow model which combines the solving of flow continuity equation and the Manning's equation to generate surface and subsurface runoff. This study improves on the existing rainfall runoff model in several areas. It adds spatial rainfall averaging methods to derive spatial rainfalls for catchment modelling; and it improves the catchment soil moisture representation by developing a boundary wetness index, and relates this index to antecedent catchment flow to derive spatial catchment moisture distribution. Improved runoff predictions were obtained as a result of the improvement in spatial data input and spatial soil moisture representation. The study identifies these improvements as the key areas for better runoff prediction. It demonstrates that where prediction results showed larger than expected variance, it is frequently caused by the inability to derive good spatially distributed input data rather than parameter estimation errors.

Sign in / Sign up

Export Citation Format

Share Document