Nkululeko S. Dlamini

Mr. Nkululeko S. Dlamini

orcid

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

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

Representative Publications

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1 May 2019 in Agricultural Water Management
Verified
Journal Article
Closed access
Md Rowshon KamalMd Rowshon Kamal
Md Rowshon Kamal
NDNkululeko S. Dlamini
Nkululeko S. Dlamini
Mohammad Abdul MojidMohammad Abdul Mojid
Mohammad Abdul Mojid
MAM.N.M. Adib
M.N.M. Adib
MAM.S.M. Amin
M.S.M. Amin
SLS.H. Lai
S.H. Lai

20 March 2017 in Water
Verified
Journal Article
Open access
PDF file
NDNkululeko S. Dlamini
Nkululeko S. Dlamini
Md Rowshon KamalMd Rowshon Kamal
Md Rowshon Kamal
AAAhmad Fikri Abdullah
Ahmad Fikri Abdullah
MMMOHD SYAZWAN FAISAL BIN MOHD
MOHD SYAZWAN FAISAL BIN MOHD
AAAhmad Fikri Bin Abdullah
Ahmad Fikri Bin Abdullah
HGHamed Benisi Ghadim
Hamed Benisi Ghadim
Potential impacts of climate change on the streamflow of the Bernam River Basin in Malaysia are assessed using ten Global Climate Models (GCMs) under three Representative Concentration Pathways (RCP4.5, RCP6.0 and RCP8.5). A graphical user interface was developed that integrates all of the common procedures of assessing climate change impacts, to generate high resolution climate variables (e.g., rainfall, temperature, etc.) at the local scale from large-scale climate models. These are linked in one executable module to generate future climate sequences that can be used as inputs to various models, including hydrological and crop models. The generated outputs were used as inputs to the SWAT hydrological model to simulate the hydrological processes. The evaluation results indicated that the model performed well for the watershed with a monthly R2, Nash–Sutcliffe Efficiency (NSE) and Percent Bias (PBIAS) values of 0.67, 0.62 and −9.4 and 0.62, 0.61 and −4.2 for the calibration and validation periods, respectively. The multi-model projections show an increase in future temperature (tmax and tmin) in all respective scenarios, up to an average of 2.5 °C for under the worst-case scenario (RC8.5). Rainfall is also predicted to change with clear variations between the dry and wet season. Streamflow projections also followed rainfall pattern to a great extent with a distinct change between the dry and wet season possibly due to the increase in evapotranspiration in the watershed. In principle, the interface can be customized for the application to other watersheds by incorporating GCMs’ baseline data and their corresponding future data for those particular stations in the new watershed. Methodological limitations of the study are also discussed.