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Abdulla, Fayez; Amayreh, Jumah; Hossain, A

doi:10.1023/a:1020258808869

Cited by 18 publications

(5 citation statements)

References 4 publications

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“…The Weibull distribution provides the best fit for Kota Kinabalu station. This result is also consistent with Abdulla and Hossain [12], who conducted a study using maximum temperature for Patuakhali stations. Lastly, Subang station favours both of the Normal and Lognormal distributions as the best distributions.…”

Section: Resultssupporting

confidence: 91%

“…The Generalized Skew Logistic distribution is selected as the best fit to observe the monthly maximum temperature of Dhaka station [11]. In 2018, Abdulla and Hossain [12] found the Generalized Skew Logistic distribution was the favoured distribution for Cox's Bazar station while the Weibull distribution describes the best for Patuakhali station.…”

Section: Introductionmentioning

confidence: 99%

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Selecting the probability distribution of annual maximum temperature in Malaysia

Supian

Hasan

2021

ITM Web Conf.

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The issues on global warming have become very popular and been discussed both locally and internationally. This phenomenon due to the temperature rises will increase the variability of climate and more natural disasters were expected to occur. Increasing of global temperature will affect the agricultural sector, increase some of the infectious diseases that may lead to high mortality rates in humans, high demand for electricity, water and food which eventually affecting the economy of Malaysia. Hence, this work aims to study the best fitted probability distribution that describes the annual maximum temperature recorded at seventeen meteorological stations in Malaysia. The Normal, Lognormal, Gamma, Weibull and Generalized Skew Logistic distributions are considered using the maximum likelihood estimation method to estimate the parameters. The goodness of fit test and model selection criteria such as Kolmogorov-Smirnov and AndersonDarling tests, Corrected Akaike Information Criterion and Bayesian Information Criterion are used to measure the accuracy of the predicted data using theoretical probability distributions. The results show that most of the stations favour the Generalized Skew Logistic distribution as the best fitted probability distribution. Also, some stations favour the Normal, Lognormal as well as Weibull distribution as the best fitted distribution to describe the annual maximum temperature.

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Section: Resultssupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Selecting the probability distribution of annual maximum temperature in Malaysia

Supian

Hasan

2021

ITM Web Conf.

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“…Many countries in Southeast Asia, Africa, and the Middle East have created efforts to scheme and develop techniques to gather, store, and consume rainwater for farming actions [7,8]. For human beings, the process of valuation, management, and planning of rainwater harvesting becomes a significant issue, particularly in those areas where rainwater is inadequate, and the groundwater source is scarce [9,10]. Watershed planning is the main technique which leads to a catchment zone improvement based on the topography of the area, which can then be used throughout the year for different purposes.…”

mentioning

confidence: 99%

Suitable Site Selection for Rainwater Harvesting and Storage Case Study Using Dohuk Governorate

Ibrahim

Rasul

Hamid

et al. 2019

Water

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The Middle East is an inherently dry zone. It has experienced severe drought for the last seven years, and climate change has made the situation worse. The Dohuk governorate has been suffering from an appalling water crisis. One possible way of relieving this water crisis is by properly harvesting the rainwater. Rainwater harvesting is a widely used method of storing rainwater in the countries presenting with drought characteristics. Several pieces of research have derived and developed different criteria and techniques to select suitable sites for harvesting rainwater. The main aim of this research was to identify and select suitable sites for the potential erection of dams, as well as to derive a model builder in ArcMap 10.4.1. The model combined several parameters, such as slope, runoff potential, land cover/use, stream order, soil quality, and hydrology to determine the suitability of the site for harvesting rainwater. To compute the land use/cover categories, the study depended on Landsat image data from 2018. Supervised classification was applied using the ENVI 5 software, while the slope mapping and drainage order were extracted using a digital elevation model. Inverse distance weighting (IDW) was used for the spatial interpolation of the rain data. The results demonstrated that suitable areas for water harvesting, are located in the middle and northern part of the research area, and in intensively cultivated zones. The main soil texture in these suitable sites was loam, while the rainfall rate amounted to 750 to 900 mm. This research shows that 15% and 13% of the area studied can be categorized as having excellent and good suitability for water harvesting, respectively. Furthermore, 21% and 27% of the area studied were of moderate and poor suitability, while the remaining 24% were not suitable at all.

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“…Innovative new techniques have been employed to enable RWH, which is the most abundant water resource available. In areas receiving a relatively small amount of rainfall, the method for prioritizing, assessing, and preparing RWH becomes significant [7,8]. In semi-arid areas, however, identifying potential RWH zones is crucial in rising water supply and land productivity.…”

Section: Introductionmentioning

confidence: 99%

Integrating GIS-Based MCDA Techniques and the SCS-CN Method for Identifying Potential Zones for Rainwater Harvesting in a Semi-Arid Area

Al-Ghobari

Dewidar

2021

Water

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An increasing scarcity of water, as well as rapid global climate change, requires more effective water conservation alternatives. One promising alternative is rainwater harvesting (RWH). Nevertheless, the evaluation of RWH potential together with the selection of appropriate sites for RWH structures is significantly difficult for the water managers. This study deals with this difficulty by identifying RWH potential areas and sites for RWH structures utilizing geospatial and multi-criteria decision analysis (MCDA) techniques. The conventional data and remote sensing data were employed to set up needed thematic layers using ArcGIS software. The soil conservation service curve number (SCS-CN) method was used to determine surface runoff, centered on which yearly runoff potential map was produced in the ArcGIS environment. Thematic layers such as drainage density, slope, land use/cover, and runoff were allotted appropriate weights to produced RWH potential areas and zones appropriate for RWH structures maps of the study location. Results analysis revealed that the outcomes of the spatial allocation of yearly surface runoff depth ranging from 83 to 295 mm. Moreover, RWH potential areas results showed that the study areas can be categorized into three RWH potential areas: (a) low suitability, (b) medium suitability, and (c) high suitability. Nearly 40% of the watershed zone falls within medium and high suitability RWH potential areas. It is deduced that the integrated MCDA and geospatial techniques provide a valuable and formidable resource for the strategizing of RWH within the study zones.

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Cited by 18 publications

References 4 publications

Selecting the probability distribution of annual maximum temperature in Malaysia

Selecting the probability distribution of annual maximum temperature in Malaysia

Suitable Site Selection for Rainwater Harvesting and Storage Case Study Using Dohuk Governorate

Integrating GIS-Based MCDA Techniques and the SCS-CN Method for Identifying Potential Zones for Rainwater Harvesting in a Semi-Arid Area

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