Zulkifli Yusop

Prof. Zulkifli Yusop

orcid

Research Focus & Metrics

Academic Career Length

27Years (2000-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 April 2018 in Water
Verified
Journal Article
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NLNor Hafizi Md Lani
Nor Hafizi Md Lani
ZYZulkifli Yusop
Zulkifli Yusop
ASAchmad Syafiuddin
Achmad Syafiuddin
The mismatch between freshwater demand and its availability is a major problem that causes global water scarcity. The exploration and utilization of rainwater seem to be viable options for minimizing the aforementioned issue. This manuscript reviews the prospects and challenges of the rainwater harvesting system (RWHS) in Malaysia. Malaysia can be categorized as a country that has high annual rainfall, as well as high domestic water consumption. Thus, Malaysia is well positioned to harvest rainwater for both potable and non-potable uses. Although the RWH guidelines were issued in Malaysia in 1999, the implementation of RWHS as an alternative water resource is still very limited due to its long return on investment and poor public acceptance. Major future challenges on the implementation of RWHS in Malaysia are to achieve competitive cost, the wide application of commercial buildings, a cost effective treatment system, effective policy implementation, the application of green materials, public perception improvement, and reliable first flush technology. Some recommendations such as providing appropriate subsidies and limiting the use of piped water are necessary for implementing RWHS at wider scales.

1 March 2018 in Atmospheric Research
Verified
Journal Article
Closed access
FHFoo Hui-Mean
Foo Hui-Mean
ZYZulkifli Yusop
Zulkifli Yusop
FYFadhilah Yusof
Fadhilah Yusof

24 October 2021 in Forests
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Journal Article
Open access
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NLN. Zafirah Ab Lah
N. Zafirah Ab Lah
ZYZulkifli Yusop
Zulkifli Yusop
Mazlan HashimMazlan Hashim
Mazlan Hashim
JSJamilah Mohd Salim
Jamilah Mohd Salim
SNShinya Numata
Shinya Numata
Gelam tree or Melaleuca cajuputi (M. cajuputi) is an important species for the local economy as well as coastal ecosystem protection in Terengganu, Malaysia. This study aimed at producing a current habitat suitability map and predicting future potential habitat distribution for M. cajuputi in Terengganu based on Species distribution modeling (SDM) using the Maximum Entropy principle. Our modeling results show that for the current potential distribution of M. cajuputi species, only 10.82% (1346.5 km2) of Terengganu area is suitable habitat, which 0.96% of the areas are under high, 2.44% moderate and 7.42% poor habitat suitability. The model prediction for future projection shows that the habitat suitability for M. cajuputi would decrease significantly in the year 2050 under RCP 4.5 where the largest contraction from suitable to unsuitable habitat area is about 442.1 km2 and under RCP 2.6 is the highest expansion from unsuitable to suitable habitat area (267.5 km2). From the future habitat suitability projection, we found that the habitat suitability in Marang would degrade significantly under all climate scenarios, while in Setiu the habitat suitability for M. cajuputi remains stable throughout the climate change scenarios. The modeling prediction shows a significant influence on the soil properties, temperature, and precipitation during monsoon months. These results could benefit conservationist and policymakers for decision making. The present model could also give a perception into potential habitat suitability of M. cajuputi in the future and to improve our understanding of the species’ response under the changing climate.

11 July 2013 in Water Resources Management
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Journal Article
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FYFadhilah Yusof
Fadhilah Yusof
FHFoo Hui-Mean
Foo Hui-Mean
SJShariffah Suhaila Syed Jamaludin
Shariffah Suhaila Syed Jamaludin
ZYZulkifli Yusop
Zulkifli Yusop

7 June 2017 in Meteorology and Atmospheric Physics
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Journal Article
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SJShariffah Suhaila Syed Jamaludin
Shariffah Suhaila Syed Jamaludin
ZYZulkifli Yusop
Zulkifli Yusop

2 November 2016 in Water
Verified
Journal Article
Open access
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CWChee Loong Wong
Chee Loong Wong
LJLiew Juneng
Liew Juneng
ZYZulkifli Yusop
Zulkifli Yusop
Tarmizi IsmailTarmizi Ismail
Tarmizi Ismail
RVRaymond Venneker
Raymond Venneker
SUStefan Uhlenbrook
Stefan Uhlenbrook
Daily gridded rainfall data over Peninsular Malaysia are delineated using an objective clustering algorithm, with the objective of classifying rainfall grids into groups of homogeneous regions based on the similarity of the rainfall annual cycles. It has been demonstrated that Peninsular Malaysia can be statistically delineated into eight distinct rainfall regions. This delineation is closely associated with the topographic and geographic characteristics. The variation of rainfall over the Peninsula is generally characterized by bimodal variations with two peaks, i.e., a primary peak occurring during the autumn transitional period and a secondary peak during the spring transitional period. The east coast zones, however, showed a single peak during the northeast monsoon (NEM). The influence of NEM is stronger compared to the southwest monsoon (SWM). Significantly increasing rainfall trends at 95% confidence level are not observed in all regions during the NEM, with exception of northwest zone (R1) and coastal band of west coast interior region (R3). During SWM, most areas have become drier over the last three decades. The study identifies higher variation of mean monthly rainfall over the east coast regions, but spatially, the rainfall is uniformly distributed. For the southwestern coast and west coast regions, a larger range of coefficients of variation is mostly obtained during the NEM, and to a smaller extent during the SWM. The inland region received least rainfall in February, but showed the largest spatial variation. The relationship between rainfall and the El Niño Southern Oscillation (ENSO) was examined based on the Multivariate ENSO Index (MEI). Although the concurrent relationships between rainfall in the different regions and ENSO are generally weak with negative correlations, the rainfall shows stronger positive correlation with preceding ENSO signals with a time lag of four to eight months.