Titel Deelnemers "Korte inhoud" "Adjustment of extreme rainfall statistics accounting for multidecadal climate oscillation" "Patrick Willems" "Rainfall extremes exhibit temporal clustering at multi-decadal time scales, most probably as a result of persistence in large scale atmospheric circulation over such time scales. Analysis of a 107-year time series of 10 min rainfall intensities since 1898 at Uccle, Brussels, has shown that the 1960s and the 1990-2000s had a higher frequency and amplitude of high rainfall intensities at various time scales in the range between 10 min and 1 month. These periods are alternated with periods of lower rainfall quantiles, e.g. in the 1970-1980s. The climate oscillations have to be accounted for when calculating extreme rainfall statistics, e.g. IDF relation ships and synthetic storms commonly applied on the basis of urban drainage systems design. The importanc e of this and how this climate oscillation accounting can be done is demonstrated in this pap er based on the Uccle rainfall data. Old and new IDF statistics, based on, respectively, shorter and longer rainfall series have been compared. It is shown that recent increases in rainfall statistics should not necessarily be attributed to climate change but may also be due to a different positioning of the periods with availabl e rainfall data in comparison with the climate oscillation high and low periods. Comparison of old IDF statistics based on the period 1967-1993 versus new statistics based on the full period 1898-2007 or the period 1970-2007 covering one climate oscillation cycle, shows 7.5% differenc e in extreme rainfall quantiles for return periods higher than 1 year. Adjustment with +7.5% is required to remove the bias in the old rainfall design values in comparison with the long-term statistics." "Adjustment of extreme rainfall statistics accounting for multidecadal climate oscillations" "Patrick Willems" "Rainfall extremes exhibit temporal clustering at multi-decadal time scales, most probably as a result of persistence in large scale atmospheric circulation over such time scales. Analysis of a 107-year time series of 10-minute rainfall intensities since 1898 at Uccle, Brussels, has shown that the 1960s and the 1990s-2000s had a higher frequency and amplitude of high rainfall intensities at various time scales in the range between 10 minutes and 1 month. These periods are alternated with periods of lower rainfall quantiles, e.g. in the 1970s-1980s. The climate oscillations have to be accounted for when calculating extreme rainfall statistics, e.g. IDF relationships and synthetic storms commonly applied on the basis of urban drainage systems design. The importance of this and how this climate oscillation accounting can be done is demonstrated in this paper based on the Uccle rainfall data. Old and new IDF statistics, based on, respectively, shorter and longer rainfall series have been compared. It is shown that recent increases in rainfall statistics should not necessarily be attributed to climate change but may also be due to a different positioning of the periods with available rainfall data in comparison with the climate oscillation high and low periods. Comparison of old IDF statistics based on the period 1967-1993 versus new statistics based on the full period 1898-2007 or the period 1970-2007 covering one climate oscillation cycle, shows 7.5% difference in extreme rainfall quantiles for return periods higher than 1 year. Adjustment with +7.5% is required to remove the bias in the old rainfall design values in comparison with the long-term statistics." "Are stochastic point rainfall models able to preserve extreme flood statistics?" "Sander Vandenberghe, P Cabus, C Onof, T Meca-Figueras, S Jameleddine" "Statistical approach to downscaling of urban rainfall extremes" "Patrick Willems" "How will be future rainfall IDF curves in the context of climate change?" "Hossein Tabari, P. Hosseinzadehtalaei, P. Willems, S. Saeed, E. Brisson, N. Van Lipzig" "The design statistics for water infrastructures are typically derived from rainfall intensity- duration-frequency (IDF) curves which compound frequency and intensity aspects of rainfall events for different durations. Current IDF curves are constructed based on historical time series, with an underlying temporal stationarity assumption for the probability distribution of extreme values. However, climate change casts doubt on the validity of this assumption due to ongoing and projected changes in the intensity and frequency of extreme rainfall. In this study, IDF curves for historical periods obtained from the convection permitting CCLM model with spatial and temporal resolutions of 2.8 km and 15 minutes and an ensemble of climate models (CMIPS) are validated based on observations-based curves. After this validation, future climate IDF relationships are obtained based on a quantile perturbation approach. It is concluded that the sub-hourly precipitation intensities at 15 and 30 minutes in the IDF curves derived from the CCLM 2.8 km model underestimate the observed extreme rainfall intensities. For the daily intensities, less deviation is observed for both the CCLM and the CMIP5 GCM runs. Future climate projections show potentially strong changes in extreme rainfall intensities, making the historical climate based IDF design standards unsuitable for the future extreme events." "At-site and regional frequency analysis of extreme precipitation from radar-based estimates" "Edouard Goudenhoofdt, Patrick Willems" "In Belgium, only rain gauge time series have been used so far to study extreme rainfall at a given location. In this paper, the potential of a 12-year quantitative precipitation estimation (QPE) from a single weather radar is evaluated. For the period 2005–2016, 1 and 24 h rainfall extremes from automatic rain gauges and collocated radar estimates are compared. The peak intensities are fitted to the exponential distribution using regression in Q-Q plots with a threshold rank which minimises the mean squared error. A basic radar product used as reference exhibits unrealistic high extremes and is not suitable for extreme value analysis. For 24 h rainfall extremes, which occur partly in winter, the radar-based QPE needs a bias correction. A few missing events are caused by the wind drift associated with convective cells and strong radar signal attenuation. Differences between radar and gauge rainfall values are caused by spatial and temporal sampling, gauge underestimations and radar errors. Nonetheless the fit to the QPE data is within the confidence interval of the gauge fit, which remains large due to the short study period. A regional frequency analysis for 1 h duration is performed at the locations of four gauges with 1965–2008 records using the spatially independent QPE data in a circle of 20 km. The confidence interval of the radar fit, which is small due to the sample size, contains the gauge fit for the two closest stations from the radar. In Brussels, the radar extremes are significantly higher than the gauge rainfall extremes, but similar to those observed by an automatic gauge during the same period. The extreme statistics exhibit slight variations related to topography. The radar-based extreme value analysis can be extended to other durations." "Intercomparison of five lumped and distributed models for catchment runoff and extreme flow simulation" "Thomas Vansteenkiste, Victor Ntegeka, Niels Van Steenbergen, Florimond De Smedt, Okke Batelaan, Patrick Willems" "Five hydrological models with different spatial resolutions and process descriptions were applied to a medium sized catchment in Belgium in order to assess the accuracy and differences of simulated hydrological variables, including peak and low flow extremes and quick and slow runoff subflows. The models varied from the lumped conceptual NAM, PDM and VHM models over the intermediate detailed and distributed WetSpa model to the highly detailed and fully distributed MIKE SHE model. The latter model accounts for the 3D groundwater processes and interacts bi-directionally with a full hydrodynamic MIKE 11 river model. A consistent protocol to model calibration was applied to all models. This protocol uses information on the response behaviour of the catchment extracted from the river flow and input time series and explicitly focuses on reproducing the quick and slow runoff subflows, and the extreme high and low flows next to testing the conventional model performance statistics. Also the model predictive capacity under high rainfall intensities, which might become more extreme under future climate change was explicitly verified for the models. The tail behaviour of the extreme flow distributions was graphically evaluated as well as the changes in runoff coefficients in relation to the changing rainfall intensities. After such calibration, all tested models succeed to produce high performance for the total runoff and quick and slow runoff subflow dynamics and volumes, peak and low flow extremes and their frequency distributions. Calibration of the lumped parameter models is much less time consuming and produced higher overall model performance in comparison to the more complex distributed models." "Evaluation and inter-comparison of Global Climate Models’ performance over Katonga and Ruizi Catchments in Lake Victoria Basin" "P.o. Nyeko, G. Ngirane-Katashaya, Patrick Willems, V. Ntegeka" "Regional impact assessments of climate change on hydrological extremes require robust examinations of climate model simulations. The climate models may satisfy mean statistics but fail to reproduce extreme quantiles which are crucial for applications of climate change impact analysis on water resources. Through statistical analysis, this paper evaluates and inter-compares the performance of Global Climate Model (GCM) simulations for their ability to predict changes in hydrological extremes for given locations or catchments in the Nile basin. Two catchments were considered: Katonga and Ruizi catchments in the Lake Victoria basin. Models that differ significantly from the observed extremes were considered unreliable for impact assessments on hydrological extremes. A graphical approach (rainfall quantile/frequency analysis), which allows for easy spotting of discordant models, in combination with several statistics, was used to evaluate 18 GCM control simulations against observed rainfall data. Standard deviation, coefficient of variation and root mean squared error (about the mean) of the observed rainfall, were used to derive error margins against which GCM simulations were evaluated. Model results outside the error margins were considered inconsistent with the observed rainfall. Model inter-comparison was also carried out for the rainfall change projections till the 2050s and 2090s through analysis of perturbations and percentage changes based on A1B, A2, and B1 SRES scenarios. It is noted that the GCM outputs are more consistent in reproducing rainfall signatures at annual aggregation level than at monthly aggregation levels with tendency of overestimation of the rainfall depths but with significant variation among different GCM simulations. The GCMs perform better in reproducing rainfall frequency with higher return periods compared with lower return periods. Most of the GCMs perform better for the wet months than the drier months. The GCMs CGCM3.2a, CM3.O, CM4.1, PCM1, CGCM3.1T47, MIROC3.2.HIRES, CCSM3.0 and FGOALS, are the most inconsistent with the observed rainfall for both catchments. Good performing models are MK3.5, MK3.0, ECHAM5, CM2.1U.H2 and CM2.0. In general, most GCMs perform poorly for both catchments. This signals the need for significant improvements in the rainfall modelling of the climate models for the study region. There is no strong evidence to suggest that GCM performance improves with higher spatial resolution. Models which are highly inconsistent with other models in reproducing the observed rainfall are not necessarily inconsistent with other models in the future projections. Differences in projections for the A1B, B2, and B1 scenarios were found to be smaller than the differences between the GCM simulations." "Evaluation and inter-comparison of Global Climate Models' performance over Katonga and Ruizi catchments in Lake Victoria basin" "Paul Nyeko Ogira, Patrick Willems, Victor Ntegeka" "Regional impact assessments of climate change on hydrological extremes require robust examinations of climate model simulations. The climate models may satisfy mean statistics but fail to reproduce extreme quantiles which are crucial for applications of climate change impact analysis on water resources. Through statistical analysis, this paper evaluates and inter-compares the performance of Global Climate Model (GCM) simulations for their ability to predict changes in hydrological extremes for given locations or catchments in the Nile basin. Two catchments were considered: Katonga and Ruizi catchments in the Lake Victoria basin. Models that differ significantly from the observed extremes were considered unreliable for impact assessments on hydrological extremes. A graphical approach (rainfall quantile/frequency analysis), which allows for easy spotting of discordant models, in combination with several statistics, was used to evaluate 18 GCM control simulations against observed rainfall data. Standard deviation, coefficient of variation and root mean squared error (about the mean) of the observed rainfall, were used to derive error margins against which GCM simulations were evaluated. Model results outside the error margins were considered inconsistent with the observed rainfall. Model inter-comparison was also carried out for the rainfall change projections till the 2050s and 2090s through analysis of perturbations and percentage changes based on A1B. A2. and B1 SRES scenarios. It is noted that the GCM outputs are more consistent in reproducing rainfall signatures at annual aggregation level than at monthly aggregation levels with tendency of overestimation of the rainfall depths but with significant variation among different GCM simulations. The GCMs perform better in reproducing rainfall frequency with higher return periods compared with lower return periods. Most of the GCMs perform better for the wet months than the drier months. The GCMs CGCM3.2a, CM3.O, CM4.1, PCM1, CGCM3.1T47, MIROC3.2.HIRES, CCSM3.0 and FGO-ALS, are the most inconsistent with the observed rainfall for both catchments. Good performing models are MK3.5, MK3.0, ECHAM5, CM2.1U.H2 and CM2.0. In general, most GCMs perform poorly for both catchments. This signals the need for significant improvements in the rainfall modelling of the climate models for the study region. There is no strong evidence to suggest that GCM performance improves with higher spatial resolution. Models which are highly inconsistent with other models in reproducing the observed rainfall are not necessarily inconsistent with other models in the future projections. Differences in projections for the A1B, B2, and B1 scenarios were found to be smaller than the differences between the GCM simulations. (C) 2010 Elsevier Ltd. All rights reserved." "Influence of climate variability versus change at multi-decadal time scales on hydrological extremes" "Patrick Willems" "Recent studies have shown that rainfall and hydrological extremes do not randomly occur in time, but are subject to multidecadal oscillations. In addition to these oscillations, there are temporal trends due to climate change. Design statistics, such as intensity-duration-frequency (IDF) for extreme rainfall or flow-duration-frequency (QDF) relationships, are affected by both types of temporal changes (short term and long term). This presentation discusses these changes, how they influence water engineering design and decision making, and how this influence can be assessed and taken into account in practice. The multidecadal oscillations in rainfall and hydrological extremes were studied based on a technique for the identification and analysis of changes in extreme quantiles. The statistical significance of the oscillations was evaluated by means of a non-parametric bootstrapping method. Oscillations in large scale atmospheric circulation were identified as the main drivers for the temporal oscillations in rainfall and hydrological extremes. They also explain why spatial phase shifts (e.g. north-south variations in Europe) exist between the oscillation highs and lows. Next to the multidecadal climate oscillations, several stations show trends during the most recent decades, which may be attributed to climate change as a result of anthropogenic global warming. Such attribution to anthropogenic global warming is, however, uncertain. It can be done based on simulation results with climate models, but it is shown that the climate model results are too uncertain to enable a clear attribution. Water engineering design statistics, such as extreme rainfall IDF or peak or low flow QDF statistics, obviously are influenced by these temporal variations (oscillations, trends). It is shown in the paper, based on the Brussels 10-minutes rainfall data, that rainfall design values may be about 20% biased or different when based on short rainfall series of 10 to 15 years length, and still 8% for series of 25 years lengths. Methods for bias correction are demonstrated. The definition of “bias” depends on a number of factors, which needs further debate in the hydrological and water engineering community. References: Willems P. (2013), ‘Multidecadal oscillatory behaviour of rainfall extremes in Europe’, Climatic Change, 120(4), 931–944 Willems, P. (2013). ‘Adjustment of extreme rainfall statistics accounting for multidecadal climate oscillations’, Journal of Hydrology, 490, 126-133 Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012), ‘Impacts of climate change on rainfall extremes and urban drainage’, IWA Publishing, 252p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263"