Entropy Theory and Pearson Type-3 Distribution for Rainfall Frequency Analysis in Semi-arid Region

Abstract. West African populations are increasingly exposed to heavy rainfall events which cause devastating floods. For the design of rainwater drainage facilities (to protect populations), practitioners systematically use the Gumbel distribution regardless of rainfall statistical behaviour. The objective of this study is twofold. The first is to update existing knowledge on heavy rainfall frequency analysis in West Africa to check whether the systematic preference for Gumbel's distribution is not misleading, and subsequently to quantify biases induced by the use of the Gumbel distribution on stations fitting other distributions. Annual maximum daily rainfall of 12 stations located in the Benin sections of the Niger and Volta Rivers' basins covering a period of 96 years (1921–2016) were used. Five statistical distributions (Gumbel, GEV, Lognormal, Pearson type III, and Log-Pearson type III) were used for the frequency analysis and the most appropriate distribution was selected based on the Akaike (AIC) and Bayesian (BIC) criteria. The study shows that the Gumbel's distribution best represents the data of 2/3 of the stations studied, while the remaining 1/3 of the stations fit better GEV, Lognormal, and Pearson type III distributions. The systematic application of Gumbel's distribution for the frequency analysis of extreme rainfall is therefore misleading. For stations whose data best fit the other distributions, annual daily rainfall maxima were estimated both using these distributions and the Gumbel's distribution for different return periods. Depending on the return period, results demonstrate that the use of the Gumbel distribution instead of these distributions leads to an overestimation (of up to +6.1 %) and an underestimation (of up to −45.9 %) of the annual daily rainfall maxima and therefore to an uncertain design of flood protection facilities. For better validity, the findings presented here should be tested on larger datasets.

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Regional Rainfall Frequency Analysis on Seven Sites of Punjab, Pakistan using L-moments

STATISTICS, COMPUTING AND INTERDISCIPLINARY RESEARCH ◽

10.52700/scir.v2i2.13 ◽

2020 ◽

Vol 2 (2) ◽

pp. 25-35

Author(s):

Uzma Nawaz ◽

Zamir Hussain ◽

Tooba Nihal ◽

Saira Usman

Keyword(s):

Frequency Analysis ◽

Goodness Of Fit ◽

Regional Distribution ◽

Return Periods ◽

Goodness Of Fit Test ◽

Rainfall Frequency ◽

Pearson Type ◽

L Moments ◽

Rainfall Frequency Analysis ◽

Regional Rainfall

The hydro-meteorological variables of extreme rainfall are not easy to explain due to unexpected changes in climate and varied usage of water with growing population. Regional rainfall frequency analysis is the one such method that is useful for the requirement of more accurate estimates of rainfall yearly or desineally for the regions having lack of fresh water resources. The series of Annual Maximum Monthly Rainfall Totals (AMMRT) has been used for the seven sites of northern Punjab, Pakistan using L-moments. The results of different test, the run test, lag-1 correlation and Mann-Whitney U test illustrate that the data series of the seven sites of northern Punjab were found random and independently and identically distributed and have no serial correlation. Heterogeneity measure exposed that the region is homogeneous and discordancy measure gives the evidence that no site is discordant among the seven. The result of goodness of fit test including L-moment Ratio diagrams, ZDIST statistic and Mean Absolute Deviation Index exposed the Pearson Type III (PE3), Generalized Normal (GNO) and Generalized Extreme Value(GEV) are best suitable of the regional distribution for the quantiles estimation. The quantiles estimates obtained for different return periods. A linear regression model was developed with good fit between the at site characteristics and the mean of the AMMRT of the sites. The estimates of the study may be used for the estimation of the rainfall quantiles of the seven sites for different return periods. The estimates will be useful to design future preventive measures for the harmful impact of hydro meteorological events at these sites in Punjab Pakistan.

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Best-Fit Probability Distribution Model for Rainfall Frequency Analysis of Three Cities in South Eastern Nigeria

Nigerian Journal of Environmental Sciences and Technology - March 2018 ◽

10.36263/nijest.2017.01.0024 ◽

2017 ◽

Vol 1 (1) ◽

pp. 34-42 ◽

Cited By ~ 2

Author(s):

A. I. Agbonaye ◽

O. C. Izinyon

Keyword(s):

Probability Distribution ◽

Frequency Analysis ◽

Distribution Model ◽

Hydraulic Structures ◽

Annual Maximum ◽

Rainfall Frequency ◽

Pearson Type ◽

Rainfall Frequency Analysis ◽

Best Fit ◽

Annual Maximum Series

Rainfall frequency analysis is the estimation of how often rainfall of specified magnitude will occur. Such analyses are helpful in defining policies relating to water resources management. It serves as the source of data for flood hazard mitigation and the design of hydraulic structures aimed at reducing losses due to floods action. In this study rainfall frequency analysis for three (3) cities in South Eastern Nigeria were carried out using annual maximum series of daily rainfall data for the stations. The objective of the study was to select the probability distribution model from among six commonly used probability distribution models namely: Generalized Extreme value distribution (GEV), Extreme value type I distribution (EVI), Generalized Pareto distribution (GPA), Pearson Type III (PIII), log Normal (LN) and Log Pearson Type III (LP111) distributions. These distributions were applied to annual maximum series of daily precipitation data at each station using the parameters of the distributions estimated by the method of moments. The best fit probability distribution model at each location was selected based on the results of seven goodness of fit tests entry: root mean square error (RMSE), relative root mean square error (RRMSE), mean absolute deviation index (MADI) and probability plot correlation coefficient (PPCC), Maximum Absolute Error (MAE), Chi square test and D- Index and a scoring and ranking scheme. Our results indicate that the best fit probability distribution model at all study locations is GEV and this was used to forecast rainfall return values for the stations for return periods of between 5years and 500years. The values obtained are useful for planning, design and management of hydraulic structures for flood mitigation and prevention of flood damage at the location.

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Aerosol iron solubility in a semi-arid region: temporal trend and impact of anthropogenic sources

Tellus B ◽

10.3402/tellusb.v62i2.16519 ◽

2010 ◽

Vol 62 (2) ◽

Author(s):

Ashwini Kumar ◽

M. M. Sarin

Keyword(s):

Arid Region ◽

Temporal Trend ◽

Anthropogenic Sources ◽

Iron Solubility ◽

Semi Arid Region ◽

Semi Arid

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The Molecular Characterization and Biological Assessment of the Leaves Extracts of Loofah Reveal their Nutraceutical Potential

Recent Patents on Food Nutrition & Agriculturee ◽

10.2174/2212798411999201110211931 ◽

2020 ◽

Vol 11 ◽

Author(s):

Takoua Ben Hlel ◽

Feten Belhadj ◽

Fatih Gül ◽

Muhammed Altun ◽

Ayşe Şahin Yağlıoğlu ◽

...

Keyword(s):

Fatty Acids ◽

Phenolic Compounds ◽

Hela Cell ◽

Arid Region ◽

Biological Properties ◽

Biological Assessment ◽

Omega 3 ◽

Hela Cell Lines ◽

Semi Arid Region ◽

Semi Arid

Background:: Luffa cylindrica is a plant that is widely distributed in Africa and Asia and it can be grown in regions with tropical or subtropical climates. Few patents dealt with Loofah biological properties, including some functional foods formulated from its leaves. Objective:: This study aimed to structurally and functionally characterize the bioactive compounds of L. cylindrica leaves grown in two different environments. Methods:: The extracts of L. cylindrica leaves collected from two Tunisian locations: Essouasi (LE), a semi-arid region and Medenine (LM) an arid region, were investigated for their phenolic compounds and fatty acids using HPLC/TOF-MS and GCMS techniques respectively. Furthermore, the antioxidant capacity was evaluated with DPPH, Chelating effect, Hydroxyl radical and Superoxide anion scavenging activities while the anticancer activity against HeLa cell lines was assessed using xCELLigence real time cell analyzer and lactate dehydrogenase cytotoxicity assay. Results:: The antiproliferative capacity of both extracts was time and dose-dependent with LE presenting the lowest HeLa cell index (CI = 0.035 ± 0.018, 250 μg/ml). LE also showed the best cytotoxic capacity (56.49 ± 0.8%) and antioxidant potential (IC50 = 54.41 ± 1.12 μg/ml for DPPH and 12.12 ± 0.07 μg/ml for chelating effet). 14 phenolic compounds were detected in LE with ferulic acid being the major compound (5128.5 ± 4.09 μg Phenols/g) while LM had only 6 phenolics. GCMS analysis showed the presence of omega-3 fatty acids in LE. Conclusions:: Our findings suggest that L. cylindrica leaves, especially when collected from semi-arid regions, are promising for formulating nutraceuticals of interest.

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Space-time monitoring of soil organic carbon content across a semi-arid region of Australia

Geoderma Regional ◽

10.1016/j.geodrs.2021.e00367 ◽

2021 ◽

Vol 24 ◽

pp. e00367

Author(s):

Patrick Filippi ◽

Stephen R. Cattle ◽

Matthew J. Pringle ◽

Thomas F.A. Bishop

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Carbon Content ◽

Arid Region ◽

Space Time ◽

Organic Carbon Content ◽

Soil Organic Carbon Content ◽

Semi Arid Region ◽

Semi Arid

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An investigation of the relationship between surface albedo and urban cover types in a semi-arid region

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/1067/1/012021 ◽

2021 ◽

Vol 1067 (1) ◽

pp. 012021

Author(s):

Mustafa N Hamoodi ◽

Zainab R Mahdi

Keyword(s):

Arid Region ◽

Surface Albedo ◽

Semi Arid Region ◽

The Relationship ◽

Semi Arid

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Effect of Temperature on Sowing Dates of Wheat under Arid and Semi-Arid Climatic Regions and Impact Quantification of Climate Change through Mechanistic Modeling with Evidence from Field

Atmosphere ◽

10.3390/atmos12070927 ◽

2021 ◽

Vol 12 (7) ◽

pp. 927

Author(s):

Jamshad Hussain ◽

Tasneem Khaliq ◽

Muhammad Habib ur Rahman ◽

Asmat Ullah ◽

Ishfaq Ahmed ◽

...

Keyword(s):

Climate Change ◽

Grain Yield ◽

Arid Region ◽

Field Experiments ◽

Climatic Conditions ◽

Seasonal Temperature ◽

Sowing Dates ◽

Rcp 8.5 ◽

Semi Arid Region ◽

Semi Arid

Rising temperature from climate change is the most threatening factor worldwide for crop production. Sustainable wheat production is a challenge due to climate change and variability, which is ultimately a serious threat to food security in Pakistan. A series of field experiments were conducted during seasons 2013–2014 and 2014–2015 in the semi-arid (Faisalabad) and arid (Layyah) regions of Punjab-Pakistan. Three spring wheat genotypes were evaluated under eleven sowing dates from 16 October to 16 March, with an interval of 14–16 days in the two regions. Data for the model calibration and evaluation were collected from field experiments following the standard procedures and protocols. The grain yield under future climate scenarios was simulated by using a well-calibrated CERES-wheat model included in DSSAT v4.7. Future (2051–2100) and baseline (1980–2015) climatic data were simulated using 29 global circulation models (GCMs) under representative concentration pathway (RCP) 8.5. These GCMs were distributed among five quadrants of climatic conditions (Hot/Wet, Hot/Dry, Cool/Dry, Cool/Wet, and Middle) by a stretched distribution approach based on temperature and rainfall change. A maximum of ten GCMs predicted the chances of Middle climatic conditions during the second half of the century (2051–2100). The average temperature during the wheat season in a semi-arid region and arid region would increase by 3.52 °C and 3.84 °C, respectively, under Middle climatic conditions using the RCP 8.5 scenario during the second half-century. The simulated grain yield was reduced by 23.5% in the semi-arid region and 35.45% in the arid region under Middle climatic conditions (scenario). Mean seasonal temperature (MST) of sowing dates ranged from 16 to 27.3 °C, while the mean temperature from the heading to maturity (MTHM) stage was varying between 12.9 to 30.4 °C. Coefficients of determination (R2) between wheat morphology parameters and temperature were highly significant, with a range of 0.84–0.96. Impacts of temperature on wheat sown on 15 March were found to be as severe as to exterminate the crop before heading. The spikes and spikelets were not formed under a mean seasonal temperature higher than 25.5 °C. In a nutshell, elevated temperature (3–4 °C) till the end-century can reduce grain yield by about 30% in semi-arid and arid regions of Pakistan. These findings are crucial for growers and especially for policymakers to decide on sustainable wheat production for food security in the region.

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