NRU :: Browsing by Author "Willems, Patrick"

Browsing by Author "Willems, Patrick"

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Analyses of rainfall trends in the Nile River Basin
(Journal of hydro-environment research, 2016) Onyutha, Charles; Tabari, Hossein; Taye, Meron T.; Nyandwaro, Gilbert N.; Willems, Patrick
Trends in rainfall at 39 locations of the Nile River Basin (NRB) in Africa were analyzed. Comparison was made between rainfall trend results from the long-term data and those of short-term series selected over different time periods. The bias on trend results from series of short-term records was quantified. Homogeneity test was conducted to assess the coherence of the trend directions on a regional basis. Based on an assumed population (for simplicity) of rainfall data time periods in the range 75–100 years, bias in the short-term trend analysis was noted to reduce by about 10% for every 10% increase in record length. Under some conditions if respected, it was possible to derive trends at stations with short records based on those at nearby stations with longer term records but in the same region. Using the same data record length and uniform time period at all the selected stations, an improved regional coherence of rainfall trend results was obtained. In the equatorial region, trend in annual rainfall was found mainly positive and significant at level α = 5% in 4 of the 7 stations. Collectively for Sudan, Ethiopia and Egypt, trends in the annual rainfall were mostly negative and significant at α = 5% in 69% of the 32 stations. Heterogeneity in the trend directions for the entire NRB was confirmed at α = 1% in 13% of the 39 stations. These findings are vital for water and agricultural management practices. © 2015 International Association for Hydro-environment Engineering and Research, Asia Pacific Division. Published by Elsevier B.V. All rights reserved.
Decadal Analysis of River Flow Extremes Using Quantile-Based Approaches
(er Resources Management, 2017) Tabari, Hossein; Teferi Taye, Meron; Onyutha, Charles; Willems, Patrick
Next to the traditional analysis of trends in time series of hydro-climatological variables, analysis of decadal oscillations in these variables is of particular importance for the risk assessment of hydro-climatological disasters and risk-based decision-making. Conventional parametric and nonparametric tests, however, need implementing a set of background assumptions related to serial structure and statistical distribution of data. They neither focus on the extreme events and their probability of occurrence. In order to get rid of these limitations, we suggest a modified version of the Sen Method (SM), combined with the Quantile Perturbation Method (QPM) for examining temporal variation of extreme hydrological events. The developed method is tested for decadal analysis of monthly and annual river flows at 10 hydrometric stations in the Qazvin plain in Iran. The results show oscillatory patterns in extreme river flow quantiles, with a positive anomaly during the 1990s and a negative one during the 2000s. It is also shown that the concurrent use of the two methods allows to set a complete picture on the temporal changes in high and low extremes in historical river flow observations in different seasons.
Empirical statistical characterization and regionalization of amplitude–duration–frequency curves for extreme peak flows in the Lake Victoria Basin, East Africa
(Hydrological Sciences Journal, 2015) Onyutha, Charles; Willems, Patrick
This paper focuses on a regionalization attempt to partly solve data limitation problems in statistical analysis of high flows to derive discharge–duration–frequency (QDF) relationships. The analysis is based on 24 selected catchments in the Lake Victoria Basin (LVB) in East Africa. Characteristics of the theoretical QDF relationships were parameterized to capture their slopes of extreme value distributions (evd), tail behaviour and scaling measures. To enable QDF estimates to be obtained for ungauged catchments, interdependence relationships between the QDF parameters were identified, and regional regression models were developed to explain the regional difference in these parameters from physiographic characteristics. In validation of the regression models, from the lowest (5 years) to the highest (25 years) return periods considered, the percentage bias in the QDF estimates ranged from –2% for the 5-year return period to 27% for 25-year return period.
How well do climate models reproduce variability in observed rainfall? A case study of the Lake Victoria basin considering CMIP3, CMIP5 and CORDEX simulations
(Stochastic Environmental Research and Risk Assessment, 2019) Onyutha, Charles; Rutkowska, Agnieszka; Nyeko-Ogiramoi, Paul; Willems, Patrick
In this study, how well the climate models reproduce variability in observed rainfall was assessed based on General Circulation Models (GCMs) from phase 3 and phase 5 of the Coupled Model Inter-comparison Project, i.e., CMIP3 and CMIP5, respectively as well as the Regional Climate Models (RCMs) of COordinated Regional Climate Downscaling EXperiment (CORDEX) over Africa. Observed and climate model based daily rainfall across the Lake Victoria Basin, which is one of the wettest parts of Africa, was considered. Temporal variability was assessed based on the coefficient of variation of daily and annual rainfall, and the maximum dry and wet spell in each year. Furthermore, variation in daily rainfall was assessed in terms of the long-range dependence. Comparison of variability results from observed and climate model based rainfall was made. It was found that the capacity to reproduce variability in observed wet and dry conditions depends on the specific GCM (of CMIP3 or CMIP5) or CORDEX RCM. However, the CORDEX RCMs replicated variability in observed daily rainfall better than the CMIP3 and CMIP5 GCMs. This was due to the spatial resolutions of the CORDEX RCMs which are higher than those of the CMIP3 and CMIP5 GCMs. The ensemble mean of the coefficients of correlation between the variability in observed and that of climate model based rainfall was close to zero for both the GCMs or RCMs. This suggests that analyses can be done on a case by case basis. In other words, GCMs or RCMs which adequately reproduce variability in observed wet and dry conditions can be considered for further statistical analysis of the changes especially on the basis of statistical methods for downscaling. For daily timescale, both the GCMs and RCMs from all the three sets of climate models generally exhibited poor performance in capturing the time of occurrences and the magnitudes of rainfall events (when considered in a combined way). To reliably assess long-term rainfall changes, it is vital to characterize natural variation in terms of the statistical dependence. With respect to natural variability of rainfall at local scales, there is room for further improvement of the climate models; however, whether theory of fractals and/or concepts of scaling behavior or self-similarity can explicitly contribute in that respect is a crucial consideration. Results from this study gave some insights in the reasonableness of the future rainfall projections.
Influence of Spatial and Temporal Scales on Statistical Analyses of Rainfall Variability in the River Nile Basin
(Dynamics of Atmospheres and Oceans, 2016) Onyutha, Charles; Willems, Patrick
In this study, empirical orthogonal function was applied to analyze rainfall variability in the Nile Basin based on various spatio-temporal scales. The co-occurrence of rainfall variability and the variation in selected climate indices was analyzed based on various spatio-temporal scales. From the highest to the lowest, the cumulative amount of variance explained by the first two principal components (PCs) for any selected size of the spatial domain was obtained for the annual, seasonal, and monthly rainfall series respectively. The variability in the annual rainfall of 1⁰×1⁰ spatial coverage explained by only the first PC was about 55% on average. However, this percentage reduced to about 40% on average across the study area when the size of the spatial domain was increased from 1⁰×1⁰ to 10⁰×10⁰. The variation in climate indices was shown to explain rainfall variability more suitably at a regional than location-specific spatial scale. The magnitudes and sometimes signs of the correlation between rainfall variability and the variation in climate indices tended to vary from one time scale to another. These findings are vital in the selection of spatial and temporal scales for more considered attribution of rainfall variability across the study area.
Investigation of flow-rainfall co-variation for catchments selected based on the two main sources of River Nile
(Stochastic environmental research and risk assessment, 2018) Onyutha, Charles; Willems, Patrick
The co-variation of rainfall and flow was assessed in four selected catchments of the River Nile which has two main sources including the White Nile (in the Equatorial region) and the Blue Nile (from the Ethiopian highlands). The selected catchments included Kyoga and Kagera (from the Equatorial region), as well as Blue Nile and Atbara (in Sudan and Ethiopia). In each catchment, the flow-rainfall co-variation was investigated at both seasonal and annual time scales. To explain aggregated variation at larger temporal scale while investigating the possible change in catchment behavior, which may interfere with the flow-rainfall relationship, rainfall-runoff modeling was done at daily time scale using data (falling within the period 1949-2003) from Kagera and Blue Nile i.e. the major catchment of each region where the River Nile emanates. Correlation analysis was conducted to assess how well the variation of flow and that of catchment-wide rainfall resonate. The co-occurrence of the changes in observed and simulated overland flow was examined using the Quantile Perturbation Method (QPM). Trends in the model residuals were detected using the Mann-Kendal (MK) and Cumulative Rank Difference (CRD) tests. The null hypothesis H0 (no correlation between rainfall and flow) was rejected at the significance level α of 5% for all the selected catchments. The temporal changes in terms of the QPM anomalies for both the observed and simulated flow were in a close agreement. The evidence to reject the H0 (no trend in the model residuals) was generally statistically insufficient at α = 5% for all the models and selected catchments considering both the MK and CRD tests. These results indicate that change in catchment behavior due to anthropogenic influence in the Nile basin over the selected time period was minimal. Thus, the overall rainfall-runoff generation processes of the catchments did not change in a significant way over the selected data period. The temporal flow variation could be attributed mainly to the rainfall variation.
Space-time variability of extreme rainfall in the River Nile basin
(International Journal of Climatology, 2017) Onyutha, Charles; Willems, Patrick
In this study, spatio-temporal variability in daily rainfall extremes based on 0.5∘ × 0.5∘ gridded data over the Nile basin was analysed using the quantile perturbation method. The co-occurrence of the extreme rainfall variability with the variation in the large-scale ocean–atmosphere conditions was also investigated. Based on a 15-year moving window, it was found that the extreme rainfall shows oscillatory behaviour over multi-decadal time scales. The latitudinal difference in the multi-decadal extreme rainfall oscillations divides the study area into the Northern, Central, and Southern regions. The variability in the extreme rainfall of the Central region is dominantly driven by the variation in the sea surface temperatures of the Atlantic and Pacific Oceans. For the Southern region, extreme rainfall variability is linked to the anomalies in the sea level pressure of the North Atlantic Ocean and the variation in the sea surface temperature of the Indian Ocean. The variation in the extreme rainfall of the Northern region corresponds to the anomalies in sea surface temperatures of the Indian and Atlantic Oceans as well as from the Pacific Ocean.
Uncertainties in Flow-Duration-Frequency Relationships of High and Low Flow Extremes in Lake Victoria Basin
(Water, 2013) Onyutha, Charles; Willems, Patrick
This paper focuses on uncertainty analysis to aid decision making in applications of statistically modeled flow-duration-frequency (FDF) relationships of both daily high and low flows. The analysis is based on 24 selected catchments in the Lake Victoria basin in Eastern Africa. The FDF relationships were derived for aggregation levels in the range 1–90 days for high flows and 1–365 days for low flows. The validity of the projected FDF quantiles for high return periods T was checked using growth factor curves. Monte Carlo simulations were used to construct confidence intervals CI on both the estimated Ts for given flows and the estimated FDF quantiles for given T. The average bias of the modeled T of high and low flows are for all catchments and Ts up to 25 years lower than 8%. Despite this relatively small average bias in the modeled T, the limits of the CI on the modeled 25-year flows go up to more than 100% for high flows and more than 150% for low flows. The assessed FDF relationships and accompanied uncertainties are useful for various types of risk based water engineering and water management applications related to floods and droughts.
Uncertainty in calibrating generalised Pareto distribution to rainfall extremes in Lake Victoria basin
(Hydrology Research, 2015) Onyutha, Charles; Willems, Patrick
Uncertainty in the calibration of the generalised Pareto distribution (GPD) to rainfall extremes is assessed based on observed and large number of global climate model rainfall time series for nine locations in the Lake Victoria basin (LVB) in Eastern Africa. The class of the GPD suitable for capturing the tail behaviour of the distribution and extreme quantiles is investigated. The best parameter estimation method is selected following comparison of the method of moments, maximum likelihood, L-moments, and weighted linear regression in quantile plots (WLR) to quantify uncertainty in the extreme intensity quantiles by employing the Jackknife method and nonparametric percentile bootstrapping in a combined way. The normal tailed GPD was found suitable. Although the performance of each parameter estimation method was acceptable in a number of evaluation criteria, generally the WLR technique appears to be more robust than others. The difference between upper and lower limits of the 95% confidence intervals expressed as a percentage of the empirical 10-year rainfall intensity quantile ranges from 9.25 up to 59.66%. The assessed uncertainty will be useful in support of risk based planning, design and operation of water engineering and water management applications related to floods in the LVB.

Browsing by Author "Willems, Patrick"

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