Using R in Water Resources Education

Čistý, Milan; Celar, Lubomir

doi:10.31686/ijier.vol3.iss10.451

Cited by 5 publications

(1 citation statement)

References 28 publications

(25 reference statements)

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“…Furthermore, some introductory statistics textbooks also focus on R [9], [10], [11]. Applications of R include experimental design [12], analyzing means [13], dose-response analysis [14], big data [15], and water resources [16], among many more.…”

Section: Introductionmentioning

confidence: 99%

Fast Graphs of Statistical Distributions Using R

Garren¹

2016

ACRI

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When teaching elementary statistics courses, instructors may find themselves frequently drawing by hand the probability density functions of normal and t distributions. The author presents the R-package fastGraph, containing new functions in R, allowing graphs of probability density functions and cumulative distribution functions to be drawn on the computer with few keystrokes. These functions also allow shading under the curve of the probability density function to illustrate concepts such as p-values and critical values. An additional function which fits the line for simple linear regression is also introduced.

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Section: Introductionmentioning

confidence: 99%

Fast Graphs of Statistical Distributions Using R

Garren¹

2016

ACRI

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Assessment of flooding in future periods using the flow of the watershed (Case study: west and south of the Urmia watershed)

Jahangir

kaleshani

Ebrahimpour

2023

Natural Hazards Research

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Temporal Variability and Trends of Rainfall and Streamflow in Tana River Basin, Kenya

2017

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This study investigated temporal variabilities and trends of rainfall and discharges in Tana River Basin in Kenya using Mann-Kendall non-parametric test. Monthly rainfall data from ten stations spanning from 1967 to 2016 and daily streamflow data time series of observations from 1941 to 2016 (75 years) were analyzed with the aim of capturing and detecting multiannual and seasonal variabilities and monotonic trends. The results for the datasets suggested that the streamflow is largely dependent on increasing rainfall at the highlands. The rainfall trends seemed to have been influenced by altitudinal factors. The coefficient of variation of the ten rainfall stations ranged from 12% to 17% but 70% of rainfall stations showed negative monotonic trends and 30% show significant trends. The streamflow showed statistically significant upward monotonic trend and seasonal variability indicating a substantial change in the streamflow regime. Although the increasing trend of the streamflow during this period may not pose future risks and vulnerability of energy and irrigated agricultural production systems across the basin, variability observed indicates the need for enhanced alternative water management strategies during the low flow seasons. The trends and time series data indicate the potential evidence of climate and land use change and their impacts on the availability of water and sustainability of ecology and energy and agricultural production systems across the basin. Variability and trends of rainfall and streamflow are useful for planning studies, hydrological modeling and climate change impacts assessment within Tana River Basin.

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Using R in Water Resources Education

Cited by 5 publications

References 28 publications

Fast Graphs of Statistical Distributions Using R

Fast Graphs of Statistical Distributions Using R

Assessment of flooding in future periods using the flow of the watershed (Case study: west and south of the Urmia watershed)

Temporal Variability and Trends of Rainfall and Streamflow in Tana River Basin, Kenya

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