Suitability of ANN applied as a hydrological model coupled with statistical downscaling model

a case study in the northern area of Peninsular Malaysia

Zulkarnain Hassan, Supiah Shamsudin, Sobri Harun, Marlinda Abdul Malek, Nuramidah Hamidon

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

The 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. This study investigates the potential of ANN to project future runoff influenced by large-scale atmospheric variables for selected watershed in Peninsular Malaysia. In this study, simulations of general circulation models from Hadley Centre 3rd generation with A2 and B2 scenarios have been used. According to the SDSM projection, daily rainfall and temperature during the 2080s will increase by up to 2.23 mm and 2.02 °C, respectively. Moreover, river runoff corresponding to downscaled future projections presented a maximum increase in daily river runoff of 52 m3/s. The result revealed that the ANN was able to capture the observed runoff, as well as the IHACRES. However, compared to the IHACRES model, the ANN model was unable to provide an identical trend for daily and annual runoff series.

Original languageEnglish
Pages (from-to)463-477
Number of pages15
JournalEnvironmental Earth Sciences
Volume74
Issue number1
DOIs
Publication statusPublished - 19 Jul 2015

Fingerprint

downscaling
hydrologic models
statistical models
Runoff
artificial neural network
Malaysia
neural networks
runoff
case studies
Neural networks
Climate change
Rivers
climate change
rivers
Rain
river
needs assessment
rain
unit hydrograph
rainfall

All Science Journal Classification (ASJC) codes

  • Global and Planetary Change
  • Environmental Chemistry
  • Water Science and Technology
  • Soil Science
  • Pollution
  • Geology
  • Earth-Surface Processes

Cite this

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title = "Suitability of ANN applied as a hydrological model coupled with statistical downscaling model: a case study in the northern area of Peninsular Malaysia",
abstract = "The 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. This study investigates the potential of ANN to project future runoff influenced by large-scale atmospheric variables for selected watershed in Peninsular Malaysia. In this study, simulations of general circulation models from Hadley Centre 3rd generation with A2 and B2 scenarios have been used. According to the SDSM projection, daily rainfall and temperature during the 2080s will increase by up to 2.23 mm and 2.02 °C, respectively. Moreover, river runoff corresponding to downscaled future projections presented a maximum increase in daily river runoff of 52 m3/s. The result revealed that the ANN was able to capture the observed runoff, as well as the IHACRES. However, compared to the IHACRES model, the ANN model was unable to provide an identical trend for daily and annual runoff series.",
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Suitability of ANN applied as a hydrological model coupled with statistical downscaling model : a case study in the northern area of Peninsular Malaysia. / Hassan, Zulkarnain; Shamsudin, Supiah; Harun, Sobri; Abdul Malek, Marlinda; Hamidon, Nuramidah.

In: Environmental Earth Sciences, Vol. 74, No. 1, 19.07.2015, p. 463-477.

Research output: Contribution to journalArticle

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