Suitability of ANN applied as a hydrological model coupled with statistical downscaling model: a case study in the northern area of Peninsular Malaysia

dc.contributor.authorZulkarnain Hassan
dc.contributor.authorSupiah Shamsudin
dc.contributor.authorSobri Harun
dc.contributor.authorMarlinda Abdul Malek
dc.contributor.authorNuramidah Hamidon
dc.coverage.publicationMalaysia
dc.date.accessioned2024-05-20T07:34:05Z
dc.date.available2024-05-20T07:34:05Z
dc.date.issued2015
dc.description.abstractThe increase in global surface temperature in response to the changing composition of the atmosphere will significantly impact upon local hydrological regimes and water resources. This situation will then lead to the need for an assessment of regional climate change impacts. The objectives of this study are to determine current and future climate change scenarios using statistical downscaling model (SDSM) and to assess climate change impact on river runoff using artificial neural network (ANN) and identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data (IHACRES) models, respectively.
dc.identifier.citationHassan, Z., Shamsudin, S., Harun, S., Malek, M. A., & Hamidon, N. (2015). Suitability of ANN applied as a hydrological model coupled with statistical downscaling model: a case study in the northern area of Peninsular Malaysia. Environmental earth sciences, 74, 463-477.
dc.identifier.urihttps://repoemc.ukm.my/handle/123456789/1621
dc.language.isoen
dc.publisherSpringer
dc.publisher.alternativeEnvironmental Earth Sciences
dc.subjectStatistical downscaling
dc.subjectIHACRES
dc.subjectArtificial neural network
dc.subjectRiver runoff
dc.subjectMalaysia
dc.titleSuitability of ANN applied as a hydrological model coupled with statistical downscaling model: a case study in the northern area of Peninsular Malaysia
dc.typeJournal

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