scholarly journals Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

2018 ◽  
Vol 34 ◽  
pp. 02048
Author(s):  
Zulkarnain Hassan ◽  
Ahmad Haidir ◽  
Farah Naemah Mohd Saad ◽  
Afizah Ayob ◽  
Mustaqqim Abdul Rahim ◽  
...  
Keyword(s):  
Spatial Interpolation ◽  
Rainfall Intensity ◽  
Southwest Monsoon ◽  
Peninsular Malaysia ◽  
Seasonal Rainfall ◽  
Seasonal Patterns ◽  
Northeast Monsoon ◽  
Rainfall Characteristics ◽  
Distance Weighted ◽  
Inverse Distance

The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015) data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM), as compared to Southwest monsoon (SWM). Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

scholarly journals Spatio-Temporal Analysis of PM10 in Southern Peninsular Malaysia

2018 ◽  
Vol 7 (3.9) ◽  
pp. 27
Author(s):  
Mohamad Saiful Mohamad Khir ◽  
Khalida Muda ◽  
Norelyza Hussein ◽  
Mohd Faisal Abdul Khanan ◽  
Mohd Nor Othman ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Pollutant Dispersion ◽  
Temporal Analysis ◽  
Peninsular Malaysia ◽  
Inverse Distance Weighted ◽  
Distance Weighted ◽  
Haze Episode ◽  
Spatio Temporal ◽  
Inverse Distance

In this study, the particulate matter with diameter less than 10 micrometers (PM10) is being observed. Other factors that influenced the pollutant dispersion are also being studied prior to identification of their relationship. The aim of this study is to identify the trend of PM10 concentrations in the Southern Peninsular of Malaysia during the period 2005 to 2015 by using spatio-temporal analysis in regards to air pollution. The inverse distance weighted (IDW) is used for the spatio interpolation data and mapping. The trends of the PM10 concentration are illustrated via map which indicates the affected and vulnerable area of Southern Peninsular Malaysia especially during Haze episode.  

scholarly journals Spatial Interpolation on Rainfall Data over Peninsular Malaysia Using Ordinary Kriging

2013 ◽  
Vol 63 (2) ◽  
Author(s):  
Suhaila Jamaludin ◽  
Hanisah Suhaimi
Keyword(s):  
Spatial Analysis ◽  
Ordinary Kriging ◽  
Spatial Interpolation ◽  
Rainfall Intensity ◽  
Peninsular Malaysia ◽  
Rainfall Data ◽  
Kriging Method ◽  
Intensity Index ◽  
Dry Conditions ◽  
Two Indices

This study presents the spatial analysis of the rainfall data over Peninsular Malaysia. 70 rainfall stations were utilized in this study. Due to the limited number of rainfall stations, the Ordinary Kriging method which is one of the techniques in Spatial Interpolation was used to estimate the values of the rainfall data and to map their spatial distribution. This spatial analysis was analysed according to the two indices that describe the wet events and another two indices that characterize dry conditions. Large areas at the east experienced high rainfall intensity compared to the areas in the west, northwest and southwest. The small value that has been obtained in Aridity Intensity Index (AII) reflects that the high amount of rainfall in the eastern areas is not contributed by low-intensity events (less than 25th percentile). In terms of number of consecutive dry days, Northwestern areas in Peninsular Malaysia recorded the highest value. This finding explains the occurrence of a large number of floods and soil erosions in the eastern areas.

scholarly journals Variability and Trend in Integrated Water Vapour from ERA-Interim and IGRA2 Observations over Peninsular Malaysia

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 1012
Author(s):  
Ezekiel Kaura Makama ◽  
Hwee San Lim
Keyword(s):  
Water Vapour ◽  
Precipitable Water ◽  
Southwest Monsoon ◽  
Peninsular Malaysia ◽  
Radiation Budget ◽  
Global Changes ◽  
Western Boundary ◽  
Northeast Monsoon ◽  
Integrated Water Vapour ◽  
Slope Estimator

Integrated water vapour (IWV) is the total amount of precipitable water in an atmospheric column between the Earth’s surface and space. The implication of its variability and trend on the Earth’s radiation budget and precipitation makes its monitoring on a regular basis important. ERA-Interim reanalysis (ERA) and radiosonde (RS) data from 1988 to 2018 were used to investigate variability and trend in IWV over Peninsular Malaysia. ERA performed excellently when gauged with RS. Trend analysis was performed using the non-parametric Mann–Kendall and Theil–Sen slope estimator tests. ERA and RS IWV revealed double fluctuations at the seasonal time scale, with maxima in May and November, which are the respective beginnings of the southwest monsoon (SWM) and northeast monsoon (NEM) seasons, as well as coincidental peaks of precipitation in the region. IWV decreased in a southeast–northwest orientation, with regional maximum domiciled over the southeastern tip of the region. Steep orography tended to shape intense horizontal gradients along the edges of the peninsular, with richer gradients manifesting along the western boundary during SWM, which harbours more water vapour in the peninsular. IWV trends, both at the annual and seasonal time series, were positive and statistically significant at the 95% level across the stations, except at Kota Bharu, where a nonsignificant downward trend manifested. Trends were mostly higher in the NEM, with the greatest rate being 0.20 ± 0.42 kgm−2 found at Penang. Overall, the IWV trend in Peninsular Malaysia was positive and consistent with the upward global changes in IWV reported elsewhere.

scholarly journals The Utilization of Remote Sensing Imagery and Inverse Distance Weighted Scheme to Simulate the White Oil Effects on Soil Geotechnical Properties

2021 ◽  
pp. 2824-2833
Author(s):  
L. A. Jawad ◽  
H. W. Abdulwadud ◽  
Z. A. Hameed
Keyword(s):  
Spatial Interpolation ◽  
Liquid Limit ◽  
Soil Samples ◽  
Strength Parameter ◽  
Undisturbed Soil ◽  
Inverse Distance Weighted ◽  
Area Of Interest ◽  
Clayey Silt ◽  
Distance Weighted ◽  
Inverse Distance

     This research aims to utilize a complementarity of field excavations and laboratory works with spatial analyses techniques for a highly accurate modeling of soil geotechniques properties (i.e. having lower root mean square error value for the spatial interpolation). This was conducted, for a specified area of interest, firstly by adopting spatially sufficient and  well distributed samples (cores). Then, in the second step, a simulation is performed for the variations in properties when soil is contaminated with commonly used industrial material, which is white oil in our case. Cohesive (disturbed and undisturbed) soil samples were obtained from three various locations inside Baghdad University campus in AL-Jadiriya section of Baghdad, Iraq. The unified soil categorization system (USCS) was adopted and soil was categorized  as clayey silt of low plasticity (CL). The cores were contaminated in a synthetically manner using two specified values of white oil (5 and 10 % of its dry weight). Then, the samples were left for three days to certify homogeneity. The results of laboratory tests were enhanced by spatial interpolation mapping, using Inverse Distance Weighted scheme for normal soil samples and those with synthetic pollution. The liquid limit rates were raised slightly as contamination rates raised, while particle size was reduced; in contrary, shear strength parameter values were decreased.

scholarly journals Caracterização da variabilidade espacial e temporal da precipitação pluviométrica do Centro Sul Baiano (Characterization of the space and temporary variability of the pluviometric precipitation of South Bahia Center )

2017 ◽  
Vol 10 (4) ◽  
pp. 1143
Author(s):  
Weslei Pereira Oliveira ◽  
Marcos Antônio Vanderlei Silva ◽  
Silas Alves Souza ◽  
Charles Cardoso Santana ◽  
Adenilson Do Rego Oliveira Junior
Keyword(s):  
Spatial Interpolation ◽  
Agricultural Development ◽  
Rainfall Intensity ◽  
Rainfall Variability ◽  
Climatic Conditions ◽  
Rainy Period ◽  
Spatial Characterization ◽  
Average Monthly Rainfall ◽  
Inverse Distance

O desenvolvimento agrícola de uma região está relacionado com vários fatores, sobretudo com as condições climáticas locais. É de suma importância o conhecimento das variáveis de precipitação, desta maneira possibilitando a realização de prognósticos e uma dedução lógica das melhores épocas de preparo de solo, semeadura e colheita. Dessa forma, este trabalho tem por objetivo realizar a caracterização da variabilidade da precipitação pluvial do Centro Sul Baiano, analisando a variabilidade de precipitação interanual e os meses mais significativos dentro do período de 1976 a 2016. Utilizou-se para tal, uma série de dados médios mensais de Precipitação Pluvial no período de 1976 a 2016, proveniente de 15 estações meteorológicas convencionais, localizadas no Centro Sul Baiano e municípios adjacentes, obtidos do Banco de Dados Meteorológicos para Ensino e Pesquisa – BDMEP, no site do INMET. O preenchimento de falhas dos dados foi realizado através do software estatístico R. Realizou-se, então, uma estatística descritiva apenas dos dados das estações meteorológicas compreendidas dentro da região. Para a caracterização espacial da temperatura da região realizou-se a espacialização, através da interpolação espacial utilizando o método do peso pelo inverso da distancia (IDW) no programa QGIS. Verificou-se que dezembro foi o mês em que se apresentou as maiores médias para a maioria dos municípios, exceto para Lençóis e Vitória da Conquista, cujas médias foram maiores no mês de novembro A região apresentou aumento na intensidade das chuvas no período chuvoso de leste para oeste, e o nos meses considerados secos houve uma maior precipitação na parte leste que no oeste.   A B S T R A C TThe agricultural development of a region is related to several factors, especially with local climatic conditions. It is extremely important to know the precipitation variables, thus making possible the prognosis and of the best times of tillage, sowing and harvesting. The objective of this work is to characterize rainfall variability in the Southern Center of Bahia, analyzing the interannual precipitation variability and the most significant months within the period from 1976 to 2016. A series of data were used Average monthly rainfall from 1976 to 2016, from 15 conventional meteorological stations, located in the South Center of Bahia and adjacent municipalities, obtained from the Meteorological Database for Teaching and Research - BDMEP, on the INMET website. Filling of the data was performed using the statistical software R. A descriptive statistic was then made only of the data of the meteorological stations included within the region. Spatial characterization of the temperature of the region was performed by spatial interpolation using the inverse distance weight (IDW) method in the QGIS program. It was verified that December was the month that presented the highest averages for most of the municipalities, except for Lençóis and Vitória da Conquista, whose averages were higher in the month of November. The region presented increase in rainfall intensity in the eastern rainy period to the west, and in the months considered dry there was a greater precipitation in the east than in the west.Keywords: Climatic Variation, Interpolation, Espacialization, QGIS. 

scholarly journals Rainfall Dynamics of Terengganu Malaysia and Its Recent Trends Analysis Using the Mann-Kendall Test.

2014 ◽  
Vol 4 (2) ◽  
pp. 372-381 ◽  
Author(s):  
Musa Garba Abdullahi ◽  
Mohd Ekhwan Toriman ◽  
Mohd Barzani Gasim ◽  
Hafizan Juahir
Keyword(s):  
Rainfall Intensity ◽  
Daily Rainfall ◽  
Kendall Test ◽  
Southwest Monsoon ◽  
The State ◽  
Northeast Monsoon ◽  
Monsoon Period ◽  
Mann Kendall Test ◽  
Recent Trends ◽  
Increasing Trends

This study investigated the pattern and trends of the daily rainfall data in Terengganu Malaysia based on seasonal rainfall indices. The statistics of rainfall indices were calculated in terms of their means for seven stations in Terengganu Malaysia for the period 2000 to 2012. The findings indicate that the trend in the study area has no significant changes in stations (1, 4 and 6) while station (2, 3, 5 and 7) shows significant changes and southwest monsoon had the greatest impact on the whole stations, particularly in characterizing the rainfall pattern of the area. During this season, the study area could be considered as the wettest region since all rainfall indices tested are higher than in other neighboring state of the Peninsula. Otherwise, the northwest of the area is denoted as the driest part of the state during the northeast monsoon period. The northwest of the state is less influenced by the northeast monsoon because of the existence of the Titiwangsa Range, which blocks some part of the region from receiving heavy rainfall. On the other hand, it is found that the areas with lowlands are strongly characterized by the northeast monsoonal flow.The results of the Mann-Kendall test, shows that, trends of the total amount of rainfall during the southwest monsoon decrease at some of the stations. The rainfall intensity increases in contrast, increasing trends in the total amount of rainfall were observed at three stations during the northeast monsoon, which give rise to the increasing trend of rainfall intensity. The results for the combined stations in both seasons indicate that there are no significant changes in trends during the extreme events for the Terengganu Malaysia. However, a smaller number of significant trends were found for extreme intensity. 

scholarly journals Comparison of spatial interpolation methods for estimation of weekly rainfall in West Bengal, India

MAUSAM ◽  
2021 ◽  
Vol 68 (1) ◽  
pp. 41-50
Author(s):  
MADHURIMA DAS ◽  
ARNAB HAZRA ◽  
ADITI SARKAR ◽  
SABYASACHI BHATTACHARYA ◽  
PABITRA BANIK
Keyword(s):  
Spatial Interpolation ◽  
West Bengal ◽  
Agricultural Practices ◽  
Rainfall Data ◽  
Absolute Deviation ◽  
Interpolation Technique ◽  
Distance Weighted ◽  
Interpolation Techniques ◽  
Discrete Values ◽  
Inverse Distance

Rainfall is one of the most eloquently researched contemporary meteorological phenomena affecting the agricultural practices dramatically, particularly along the humid, sub-tropics, where agriculture is predominantly rainfed. It is a key parameter of agricultural production in West Bengal due to lack irrigation facilities in most of the areas. Thus, it is very important to have detailed information of rainfall distribution pattern of West Bengal. In practice rainfall data is collected only at few discrete stations scattered all over the whole state. However, rainfall is a spatially continuous phenomenon rather than discrete. Thus it becomes essential to apply a robust spatial interpolation technique to transform the discrete values into a continuous spatial pattern. In the present study, three spatial interpolation techniques namely Kriging, Inverse Distance Weighted (IDW) and SPLINE, are used for a comparative analysis to identify the most efficient interpolation technique. Weekly average rainfall data available between 1901 and 1985 for 19 standard meteorological weeks (SMW), Week 22 to Week 40 are used for the analysis. The errors of the three interpolation techniques are analyzed and the best method is chosen based on the minimum mean absolute deviation (MAD) and the minimum mean squared deviation (MSD) criteria. The IDW method is found to be the best spatial interpolation technique.

scholarly journals Effects of Seasonal Variability on the Physicochemical, Biochemical, and Nutritional Composition of Western Peninsular Malaysia Gracilaria manilaensis

Molecules ◽  
2019 ◽  
Vol 24 (18) ◽  
pp. 3298 ◽  
Author(s):  
Abdul Qudus Aroyehun ◽  
Kishneth Palaniveloo ◽  
Farid Ghazali ◽  
Mohammed Rizman-Idid ◽  
Shariza Abdul Razak
Keyword(s):  
Saturated Fatty Acids ◽  
Antibacterial Properties ◽  
Essential Amino Acids ◽  
Southwest Monsoon ◽  
Nutritional Composition ◽  
Peninsular Malaysia ◽  
Northeast Monsoon ◽  
Mineral Contents ◽  
Crude Lipid ◽  
Palmitic Acids

This study evaluated the effect of seasonal variation on the physicochemical, biochemical, and nutritional composition of Gracilaria manilaensis. Sampling was designed during the main monsoon seasons in Malaysia—the Southwest monsoon (SWM) and Northeast monsoon (NEM)—to understand the intraspecific variation (p < 0.05). Carbohydrates, protein, and dietary fiber were found to be higher in NEM–G. manilaensis, whereas a higher ash content was quantified in SWM–G. manilaensis. No significant differences were found in crude lipid and moisture content (p > 0.05). Vitamin B2 was calculated as (0.29 ± 0.06 mg 100 g−1) and (0.38 ± 0.06 mg 100 g−1) for the NEM and SWM samples, respectively (p < 0.05). The fatty acid profile showed the dominance of saturated fatty acids (SFAs)—palmitic acids, stearic acid, and myristic acid—while the mineral contents were found to be good sources of calcium (1750.97–4047.74 mg 100 g−1) and iron (1512.55–1346.05 mg 100 g−1). Tryptophan and lysine were recorded as the limiting essential amino acids (EAAs) in NEM G. manilaensis, while leucine and phenylalanine were found to be the limiting EAAs in the SWM samples. None of the extracts exhibited antibacterial properties against the screened strains. The study concluded that seasonal changes have a great effect on the biochemical composition of G. manilaensis.

scholarly journals 695. Regional and Longitudinal Mapping of Escherichia coli Antibiotic Susceptibility

2018 ◽  
Vol 5 (suppl_1) ◽  
pp. S250-S251
Author(s):  
Laurel Legenza ◽  
Susanne Barnett ◽  
Jim Lacy ◽  
Natalee Desotell ◽  
Andrea Eibergen ◽  
...  
Keyword(s):  
Antibiotic Susceptibility ◽  
Regional Differences ◽  
Spatial Interpolation ◽  
Public Display ◽  
E Coli ◽  
Susceptibility Data ◽  
Distance Weighted ◽  
Inverse Distance ◽  
System Point ◽  
Spatial Interpolation Methods

Abstract Background Antimicrobial resistance (AMR) is a serious threat to global health with local implications. AMR varies regionally; however, limited tools are available to aid practitioners in appropriate antibiotic selection based on statewide antimicrobial susceptibilities. The objective of this study was to map E. coli antibiotic susceptibility regionally and longitudinally in Wisconsin. Methods. Antibiograms from 2009, 2013, and 2015 were collected from health systems, hospitals, and clinics in Wisconsin, resulting in 218 antibiograms representing 201,091 Gram-negative isolates. E. coli antibiotic susceptibility percentages were weighted by number of isolates and aggregated by county per year. Results. Spatial interpolation methods (inverse distance weighted, Kriging) were tested by both county center points and facility geocode where available. Susceptibility data for clinically relevant urinary tract infection antibiotics were interpolated to create geographic visualizations of AMR in Wisconsin. Antibiotics included amoxicillin, trimethoprim/sulfamethoxazole, ciprofloxacin, nitrofurantoin, ampicillin, ampicillin/sulbactam, levofloxacin. The interpolation extends to the furthest health system point in each direction and is presented within state boundaries. Facility geocodes were masked from public display for confidentiality. City names were added for orientation. The mapping depicts regional differences, such as 2015 ampicillin susceptibilities ranging 55–64% (Figure 1). The maps provide a preliminary susceptibility prediction in areas where no AMR data were available. Average susceptibilities were compared across 2009, 2013, and 2015 to map areas with the highest rates of AMR change. Conclusion. The described mapping provides a novel visualization of AMR across Wisconsin. The maps created will be utilized in continued efforts to improve the functionality of AMR data in clinical practice to optimize antimicrobial choice. Disclosures All authors: No reported disclosures.

scholarly journals Drought Index Mapping at Different Spatial Units

2008 ◽  
Vol 9 (6) ◽  
pp. 1523-1534 ◽  
Author(s):  
Jinyoung Rhee ◽  
Gregory J. Carbone ◽  
James Hussey
Keyword(s):  
Spatial Interpolation ◽  
Drought Index ◽  
Cross Validation ◽  
Interpolation Method ◽  
Inverse Distance Weighted ◽  
Frequency Distributions ◽  
Distance Weighted ◽  
Cross Validation Error ◽  
Index Mapping ◽  
Inverse Distance

Abstract This paper investigates the influence of spatial interpolation and aggregation of data to depict drought at different spatial units relevant to and often required for drought management. Four different methods for drought index mapping were explored, and comparisons were made between two spatial operation methods (simple unweighted average versus spatial interpolation plus aggregation) and two calculation procedures (whether spatial operations are performed before or after the calculations of drought index values). Deterministic interpolation methods including Thiessen polygons, inverse distance weighted, and thin-plate splines as well as a stochastic and geostatistical interpolation method of ordinary kriging were compared for the two methods that use interpolation. The inverse distance weighted method was chosen based on the cross-validation error. After obtaining drought index values for different spatial units using each method in turn, differences in the empirical binned frequency distributions were tested between the methods and spatial units. The two methods using interpolation and aggregation introduced fewer errors in cross validation than the two simple unweighted average methods. Whereas the method performing spatial interpolation and aggregation before calculating drought index values generally provided consistent drought information between various spatial units, the method performing spatial interpolation and aggregation after calculating drought index values reduced errors related to the calculations of precipitation data.

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