scholarly journals Sampling uncertainty of UK design flood estimation

2021 ◽  
Author(s):  
Anthony Hammond
Keyword(s):  
Sampling Error ◽  
Uncertainty Estimation ◽  
Design Flow ◽  
Single Site ◽  
Design Flood ◽  
Sampling Uncertainty ◽  
Flood Estimation ◽  
The Uk ◽  
Analytical Expressions ◽  
Quantifying Uncertainty

Abstract The UK standard for estimating flood frequencies is outlined by the flood estimation handbook (FEH) and associated updates. Estimates inevitably come with uncertainty due to sampling error as well as model and measurement error. Using resampling approaches adapted to the FEH methods, this paper quantifies the sampling uncertainty for single site, pooled (ungauged), enhanced single site (gauged pooling) and across catchment types. This study builds upon previous progress regarding easily applicable quantifications of FEH-based uncertainty estimation (Kjeldsen 2015, 2021; Dixon 2017). Where these previous studies have provided simple analytical expressions for quantifying uncertainty for single site and ungauged design flow estimates, this study provides an easy-to-use method for quantifying uncertainty for enhanced single site estimates.

scholarly journals Uncertainty Estimation Using the Glue and Bayesian Approaches in Flood Estimation: A case Study—Ba River, Vietnam

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1641 ◽  
Author(s):  
Phuong Cu Thi ◽  
James Ball ◽  
Ngoc Dao
Keyword(s):  
Threshold Value ◽  
Uncertainty Estimation ◽  
Design Flow ◽  
Design Flood ◽  
Bayesian Techniques ◽  
Flood Estimation ◽  
Glue Method ◽  
Generalized Likelihood Uncertainty Estimation ◽  
Parameter Values ◽  
The Impact

In the last few decades tremendous progress has been made in the use of catchment models for the analysis and understanding of hydrologic systems. A common application involves the use of these models to predict flows at catchment outputs. However, the outputs predicted by these models are often deterministic because they focused only on the most probable forecast without an explicit estimate of the associated uncertainty. This paper uses Bayesian and Generalized Likelihood Uncertainty Estimation (GLUE) approaches to estimate uncertainty in catchment modelling parameter values and uncertainty in design flow estimates. Testing of join probability of both these estimates has been conducted for a monsoon catchment in Vietnam. The paper focuses on computational efficiency and the differences in results, regardless of the philosophies and mathematical rigor of both methods. It was found that the application of GLUE and Bayesian techniques resulted in parameter values that were statistically different. The design flood quantiles estimated by the GLUE method were less scattered than those resulting from the Bayesian approach when using a closer threshold value (1 standard deviation departed from the mean). More studies are required to evaluate the impact of threshold in GLUE on design flood estimation.

Revisiting design flood estimation of Nam River Dam basin considering climate change

2016 ◽  
Vol 49 (8) ◽  
pp. 719-729
Author(s):  
Hyunseung Lee ◽  
Taesam Lee ◽  
Taewoong Park ◽  
Chanyoung Son
Keyword(s):  
Climate Change ◽  
Design Flood ◽  
Flood Estimation

scholarly journals Contrasting seasonality of storm rainfall and flood runoff in the UK and some implications for rainfall-runoff methods of flood estimation

2019 ◽  
Vol 50 (5) ◽  
pp. 1309-1323 ◽  
Author(s):  
Jamie Ledingham ◽  
David Archer ◽  
Elizabeth Lewis ◽  
Hayley Fowler ◽  
Chris Kilsby
Keyword(s):  
Soil Moisture ◽  
Risk Estimation ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Rainfall Runoff ◽  
Frequency Model ◽  
Soil Moisture Storage ◽  
Flood Estimation ◽  
Storm Rainfall ◽  
The Uk

Abstract Using data from 520 gauging stations in Britain and gridded rainfall datasets, the seasonality of storm rainfall and flood runoff is compared and mapped. Annual maximum (AMAX) daily rainfall occurs predominantly in summer, but AMAX floods occur most frequently in winter. Seasonal occurrences of annual daily rainfall and flood maxima differ by more than 50% in dry lowland catchments. The differences diminish with increasing catchment wetness, increase with rainfalls shorter than daily duration and are shown to depend primarily on catchment wetness, as illustrated by variations in mean annual rainfall. Over the whole dataset, only 34% of AMAX daily flood events are matched to daily rainfall annual maxima (and only 20% for 6-hour rainfall maxima). The discontinuity between rainfall maxima and flooding is explained by the consideration of coincident soil moisture storage. The results have serious implications for rainfall-runoff methods of flood risk estimation in the UK where estimation is based on a depth–duration–frequency model of rainfall highly biased to summer. It is concluded that inadequate treatment of the seasonality of rainfall and soil moisture seriously reduces the reliability of event-based flood estimation in Britain.

scholarly journals Hydrological implications of spatial and altitudinal variation in temperature in the upper Indus basin

2004 ◽  
Vol 35 (3) ◽  
pp. 209-222 ◽  
Author(s):  
David Archer
Keyword(s):  
River Flow ◽  
Daily Rainfall ◽  
Indus Basin ◽  
Design Flood ◽  
Freezing Level ◽  
Correlation And Regression Analysis ◽  
Energy Inputs ◽  
Flood Estimation ◽  
Seasonal Correlation ◽  
Practical Implications

Runoff in the upper Indus in Pakistan is primarily fed by meltwater from snow and ice. Successful modelling of runoff thus depends on knowledge of the energy inputs for melt, and temperature provides a practical index. In this study, spatial and altitudinal variations in air temperature are investigated using correlation and regression analysis. The high levels of seasonal correlation between widely separated stations and with altitude suggest that conditions over a wide surrounding area and up to the freezing level may be inferred with reasonable reliability from climate stations at the valley level. Investigation of concurrent daily rainfall, temperature and runoff in extreme monsoon incursions shows that precipitation is accompanied by a sharp fall in temperature, reduced ablation and, most frequently, a decrease in river flow. Such temperature reductions have practical implications for short term flood forecasting and for design flood estimation.

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