The Role of Local Precipitation Models in Designing Rainwater Drainage Systems in Urban Areas: a Case Study in Krakow, Poland

Wałęga, Andrzej; Kaczor, G.; Stęplewski, Błażej

doi:10.15244/pjoes/62961

Cited by 8 publications

(10 citation statements)

References 28 publications

(31 reference statements)

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“…In fact, determining the maximum annual daily precipitation with a specific probability of exceedance (P maxp% ) is necessary to tackle the issues of excessive or deficient precipitation and, thus, to meet regional water needs. The estimation of P maxp% is also important for determining flood hazard zones, for designing specific hydraulic structures or systems [2] or for assessing the performance of sewage treatment plants under variable weather conditions [3]. However, the growing atmospheric content of greenhouse gases and the resulting global warming we have been experiencing for a few decades significantly 2 of 17 affected the precipitation structure (height and spatial variability), thus making the prediction of P maxp% increasingly difficult [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Estimating Maximum Daily Precipitation in the Upper Vistula Basin, Poland

et al. 2019

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The aim of this study was to determine the best probability distributions for calculating the maximum annual daily precipitation with the specific probability of exceedance (Pmaxp%). The novelty of this study lies in using the peak-weighted root mean square error (PWRMSE), the root mean square error (RMSE), and the coefficient of determination (R2) for assessing the fit of empirical and theoretical distributions. The input data included maximum daily precipitation records collected in the years 1971–2014 at 51 rainfall stations from the Upper Vistula Basin, Southern Poland. The value of Pmaxp% was determined based on the following probability distributions of random variables: Pearson’s type III (PIII), Weibull’s (W), log-normal, generalized extreme value (GEV), and Gumbel’s (G). Our outcomes showed a lack of significant trends in the observation series of the investigated random variables for a majority of the rainfall stations in the Upper Vistula Basin. We found that the peak-weighted root mean square error (PWRMSE) method, a commonly used metric for quality assessment of rainfall-runoff models, is useful for identifying the statistical distributions of the best fit. In fact, our findings demonstrated the consistency of this approach with the RMSE goodness-of-fit metrics. We also identified the GEV distribution as recommended for calculating the maximum daily precipitation with the specific probability of exceedance in the catchments of the Upper Vistula Basin.

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Section: Introductionmentioning

confidence: 99%

Estimating Maximum Daily Precipitation in the Upper Vistula Basin, Poland

et al. 2019

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“…There were also calculated relative residual mean square error statistics, covering the entire range of data (t = 5 min). In this case R RMSE = 2.9% for h calculated by (5) and R RMSE = 41.5% for h calculated by (10). The fit quality of the equations for rainfall data from Legnica is shown in the h-h plot (Fig.…”

Section: Resultsmentioning

confidence: 75%

“…The analysis of the results clearly indicates that the extrapolation of the GED distribution parameters does not produce acceptable results. Calculated according to (10) rainfall heights of a t = 5 min duration do not correlate with the results of measurements.…”

Section: Resultsmentioning

confidence: 79%

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The impact of the time series resolution on the reliability of the maximum precipitation models

2017

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Abstract. In the paper, two maximum precipitation models for Legnica were developed. For this purpose archival pluviographic records from the time span 1961-2010 were used. The first model was developed on the basis of rainfall data of durations ranging from 5 minutes to 6 days. In the second model, rainfall data with durations ranging from 10 min to 6 days were used, and precipitation amounts for 5 minutes duration were extrapolated. Generalized exponential distribution was used to develop the models. Both models were compared with measurement data using relative residual mean square error.

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“…The maximal precipitation depth P (mm) with the probability of exceedance p (-) depending on the duration time t (min) is as follows [19]: Local rain models are based on local precipitation data. It is worth mentioning the results obtained for Kraków [20][21] and Wrocław [22][23]. For the Gdańsk region Weinerowska-Bords established the local rain formula based on 122 rain episodes collected by the GUT meteorological station in the period 1991-2010 [3].…”

Section: Characteristics Of Used Rain Modelsmentioning

confidence: 99%