The use of kernel estimators to determine the distribution of groundwater level

Michalski, Andrzej

doi:10.26491/mhwm/62708

Cited by 6 publications

(5 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are other versions of the cross-validation method, e.g. biased cross-validation (BCV) or smoothed cross-validation (SCV), and other methods to obtain optimum smoothing coefficient (e.g., [40]). Some resulting examples are shown in Fig.…”

Section: Least Squares Cross Validation Methods (Lscv)mentioning

confidence: 99%

Kernel density estimation and its application

2018

View full text Add to dashboard Cite

Kernel density estimation is a technique for estimation of probability density function that is a must-have enabling the user to better analyse the studied probability distribution than when using a traditional histogram. Unlike the histogram, the kernel technique produces smooth estimate of the pdf, uses all sample points' locations and more convincingly suggest multimodality. In its two-dimensional applications, kernel estimation is even better as the 2D histogram requires additionally to define the orientation of 2D bins. Two concepts play fundamental role in kernel estimation: kernel function shape and coefficient of smoothness, of which the latter is crucial to the method. Several real-life examples, both for univariate and bivariate applications, are shown.

show abstract

Section: Least Squares Cross Validation Methods (Lscv)mentioning

confidence: 99%

Kernel density estimation and its application

2018

View full text Add to dashboard Cite

show abstract

“…The described procedure is presented in Figure 1 and has been used many times to simulate the maximum flows [1,2,3,4]. Finally, the probability distributions of the minimum flows were adjusted and analyzed based on literature analysis [1][2][19][20][21][22][23][24][25].…”

Section: River Flow Simulation Proceduresmentioning

confidence: 99%

Simulation of the minimum annual river flows based on the RCP climatic scenario, time horizon up to 2060-2080 and the Kaczawa River

2018

View full text Add to dashboard Cite

In this paper a new simulations of minimum daily flow for Kaczawa River a left side tributary of the Odra River in south-west Poland are presented. Generated data were made based on very long series of 35 years of observed data and 24 sites of meteorological stations for south-west Poland gathered from the the Institute of Meteorology and Water Management National Research Institute (IMGW). For the data generation the spatial weather generator SWGEN producing the multisite daily time series was applied. Data were generated for the present (the year 2000 are used as a background) as well for future climate condition for 2060 and 2080 according Representative Concentration Pathways (RCPs) scenarios. The flow simulation in the river catchment is made using MIKE SHE hydrological model. Simulations are done for 2060 and 2080. The large number of new simulated series determined by the lead time, two climate change scenarios (RCP4.5 and RCP6.0), and number of generated years (1000 for each case) is equal to 5000 for a single station. Finally, Lognormal Pdf function for the minimum flow is presented as well probability of exceedance of minimum values.

show abstract

“…For example, floods in Poland, which are accompanied by high flows, appeared mainly in the summer. However, in the last 20 years, as a results of changes in the course of winters, mainly higher temperatures, meltwater thaw floods began to appear more frequently and on a much larger scale [15,19,23]. In the studies, flows were simulated for the year 2060 according to the three most likely scenarios GISS Model E, HadCM3, and GFDL R15 which are considered to comply with the new scenarios of Representative Concentration Routes (RCPs) 4.5 and 6.0.…”

Section: Introductionmentioning

confidence: 99%

Comparison of daily flows simulated for the year 2060 on the Kaczawa River for various scenarios of climate change by simple time series analysis

et al. 2019

View full text Add to dashboard Cite

In this paper a time series analysis for daily flow simulations according three climate change scenario for Kaczawa River a left side tributary of the Odra River in south-west Poland is presented. The flow sequences were simulated using the hydrological model MIKE SHE and the spatial SWGEN meteorological data generator. Meteorological data for the hydrological model were generated based on data from 24 meteorological stations and 35-year daily data from the Institute of Meteorology and Water Management of the National Research Institute (IMGW). Data were generated for future climate condition for 2060 according GISS Model E, HadCM3, and GFDL R15 scenarios as well for the present conditions. The year 2000 was used as a reference year. The results obtained on the basis of a simple time series analysis point to small changes in flows for current and simulated conditions for 2060 for the Kaczawa River.

show abstract

The use of kernel estimators to determine the distribution of groundwater level

Cited by 6 publications

References 14 publications

Kernel density estimation and its application

Kernel density estimation and its application

Simulation of the minimum annual river flows based on the RCP climatic scenario, time horizon up to 2060-2080 and the Kaczawa River

Comparison of daily flows simulated for the year 2060 on the Kaczawa River for various scenarios of climate change by simple time series analysis

Contact Info

Product

Resources

About