Agnieszka Rutkowska

Probabilistic Properties of a Curve Number: A Case Study for Small Polish and Slovak Carpathian Basins

The proper determination of the curve number (CN) in the SCS-CN method reduces errors in predicting runoff volume. In this paper the variability of CN was studied for 5 Slovak and 5 Polish Carpathian catchments. Empirical curve numbers were applied to the distribution fitting. Next, theoretical characteristics of CN were estimated. For 100-CN the Generalized Extreme Value (GEV) distribution was identified as the best fit in most of the catchments. An assessment of the differences between the characteristics estimated from theoretical distributions and the tabulated values of CN was performed. The comparison between the antecedent runoff conditions (ARC) of Hawkins and Hjelmfelt was also completed. The analysis was done for various magnitudes of rainfall. Confidence intervals (CI) were helpful in this evaluation. The studies revealed discordances between the tabulated and estimated CNs. The tabulated CNs were usually lower than estimated values; therefore, an application of the median value and the probabilistic ARC of Hjelmfelt for wet runoff conditions is advisable. For dry conditions the ARC of Hjelmfelt usually better estimated CN than ARC of Hawkins did, but in several catchments neither the ARC of Hawkins nor Hjelmfelt sufficiently depicted the variability in CN.

Direct runoff assessment using modified SME method in catchments in the Upper Vistula River Basin

Correct determination of direct runoff is crucial for proper and safe dimensioning of hydroengineering structures. It is commonly assessed using SCS-CN method developed in the United States. However, due to deficiencies of this method, many improvements and modifications have been proposed. In this paper, a modified Sahu–Mishra–Eldo (SME) method was introduced and tested for three catchments located in the upper Vistula basin. Modification of SME method involved a determination of maximum potential retention S based on CN parameter derived from SCS-CN method. The modified SME method yielded direct runoff values very similar to those observed in the investigated catchments. Moreover, it generated significantly smaller errors in the direct runoff estimation as compared with SCS-CN and SME methods in the analyzed catchments. This approach may be used for estimating the runoff in uncontrolled catchments.

Regional L-Moment-Based Flood Frequency Analysis in the Upper Vistula River Basin, Poland

The Upper Vistula River basin was divided into pooling groups with similar dimensionless frequency distributions of annual maximum river discharge. The cluster analysis and the Hosking and Wallis (HW) L-moment-based method were used to divide the set of 52 mid-sized catchments into disjoint clusters with similar morphometric, land use, and rainfall variables, and to test the homogeneity within clusters. Finally, three and four pooling groups were obtained alternatively. Two methods for identification of the regional distribution function were used, the HW method and the method of Kjeldsen and Prosdocimi based on a bivariate extension of the HW measure. Subsequently, the flood quantile estimates were calculated using the index flood method. The ordinary least squares (OLS) and the generalised least squares (GLS) regression techniques were used to relate the index flood to catchment characteristics. Predictive performance of the regression scheme for the southern part of the Upper Vistula River basin was improved by using GLS instead of OLS. The results of the study can be recommended for the estimation of flood quantiles at ungauged sites, in flood risk mapping applications, and in engineering hydrology to help design flood protection structures.

Temporal and spatial variability of extreme river flow quantiles in the Upper Vistula River basin, Poland

Temporal and spatial variability in extreme quantile anomalies of seasonal and annual maximum river flows was studied for 41 gauging stations at rivers in the Upper Vistula River basin, Poland. Using the quantile perturbation method, the temporal variability in anomalies was analysed. Interdecadal oscillating components were extracted from the series of anomalies using the Hilbert-Huang transform method. Period length, part of variance of each component, and part of unexplained variance were assessed. Results show an oscillating pattern in the temporal occurrence of extreme flow quantiles with clusters of high values in the 1960–1970s and since the late 1990s and of low values in the 1980s and at the beginning of the 1990s. The anomalies show a high variability on the right bank of the Upper Vistula River basin during the summer season with the highest values in catchments located in the western and south-western parts of the basin. River flow extreme quantiles were found to be associated with large-scale climatic variables from the regions of the North Atlantic Ocean, Scandinavia, Eastern Europe, Asia, and, to a lesser extent, the Pacific Ocean. Similarities between temporal variability of river flows and climatic factors were revealed. Results of the study are important for flood frequency analysis because a long observation period is necessary to capture clusters of high and low river flows.

Temporal and spatial variability of flood quantiles in the Upper Vistula River basin, Poland

Temporal and spatial variability in extreme quantile anomalies of seasonal and annual maximum river flows was studied for 41 gauging stations at rivers in the Upper Vistula River basin, Poland. Using the quantile perturbation method, the temporal variability in anomalies was analysed. Interdecadal oscillating components were extracted from the series of anomalies using the Hilbert-Huang transform method. Period length, part of variance of each component, and part of unexplained variance were assessed. Results show an oscillating pattern in the temporal occurrence of extreme flow quantiles with clusters of high values in the 1960–1970s and since the late 1990s and of low values in the 1980s and at the beginning of the 1990s. The anomalies show a high variability on the right bank of the Upper Vistula River basin during the summer season with the highest values in catchments located in the western and south-western parts of the basin. River flow extreme quantiles were found to be associated with large-scale climatic variables from the regions of the North Atlantic Ocean, Scandinavia, Eastern Europe, Asia, and, to a lesser extent, the Pacific Ocean. Similarities between temporal variability of river flows and climatic factors were revealed. Results of the study are important for flood frequency analysis because a long observation period is necessary to capture clusters of high and low river flows.

Relation between design floods based on daily maxima and daily means: use of the Peak Over Threshold approach in the Upper Nysa Kłodzka Basin (SW Poland)

ABSTRACT The estimation of flood quantiles is crucial in the assessment of the magnitude and frequency of floods. We carried out a comparative analysis of design discharges estimated from both daily maximum flows and daily mean flows for four mountainous catchments located in the Upper Nysa Kłodzka river basin (SW Poland). After separation of baseflow, split of the riverflow time series in independent events, and selection of the Peak Over Threshold sample, the parameters of the Generalized Pareto Distribution were estimated using the Hill statistic, after bias correction, and considering asymptotic properties. The comparison was performed for various return periods, where the long return periods were of main concern. The jack-knife approach was used to assess the uncertainty of the predicted flood quantiles, and comparison was made with an alternative approach based on annual maxima. We found a meaningful level of differences between daily maximum and mean design discharges and between the rate of change of flood magnitude for which the level (i) stabilized with increasing return period, (ii) decreased downstream, and (iii) was large for catchments susceptible to flooding and with high elevation change. Results are useful in practice when daily maximum discharge is not routinely recorded.

The Cucconi Test for Location-scale Alternatives in Application to Asymmetric Hydrological Variables

To identify location-scale trends, which environmental data often exhibit, location-scale tests have to be addressed. The aim of this article was to estimate size and power of the Cucconi rank-based test when applied to various skewed distributions, typical in hydrology. Results of the Monte Carlo simulation revealed great power for series with low coefficient of variation, time of change close to the middle, not very heavy tail, and with length of at least 60. Comparison to the Lepage test discovered larger usefulness of the Cucconi test for short series and change close to the middle. Several practical applications were presented.

Properties of the Cox–Stuart Test for Trend in Application to Hydrological Series: The Simulation Study

The size and power properties of the Cox–Stuart test for detection of a monotonic deterministic trend in hydrological time series are analyzed using the Monte Carlo method. The influence of distribution properties, lengths of series, and trend slopes is studied. Results indicate good size in all cases. The power is high for: length over 60 and strong trend slope, low or medium variation, and medium slope. The power declines if slope and length decrease and if variability increases. The properties are better for skewed distributions than for symmetrical. The test is slightly weaker in comparison to the Mann–Kendall test.

Usefulness of the Modified NRCS-CN Method for the Assessment of Direct Runoff in a Mountain Catchment

The aim of this study was to evaluate the usefulness of modified methods, developed on the basis of NRCS-CN method, in determining the size of an effective rainfall (direct runoff). The analyses were performed for the mountain catchment of the Kamienica river, right-hand tributary of the Dunajec. The amount of direct runoff was calculated using the following methods: (1) Original NRCS-CN model, (2) Mishra—Singh model (MS model), (3) Sahu Mishra Eldho model (SME model), (4) Sahu 1-p model, (5) Sahu 3-p model, and (6) Q_base model. The study results indicated that the amount of direct runoff, determined on the basis of the original NRCS-CN method, may differ significantly from the actually observed values. The best results were achieved when the direct runoff was determined using the SME and Sahu 3-p model.

How well do climate models reproduce variability in observed rainfall? A case study of the Lake Victoria basin considering CMIP3, CMIP5 and CORDEX simulations

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.