Prediction of future trend of the long term streamflow pattern in the context of climate change
Climate change has to be one of the greatest environmental threats to the world and it has been measured that a greater negative impacts on human society and to the natural environment changes when it climates are drastically change. General Circulation Models (GCM) stated that the increment of conc...
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| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2017
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| Online Access: | http://umpir.ump.edu.my/id/eprint/21115/1/Prediction%20of%20future%20trend%20of%20the%20long%20term%20streamflow%20pattern%20in%20the%20context%20of%20climate%20change.pdf |
| _version_ | 1796992706278326272 |
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| author | Nurul Hazirah, Mohd Saad |
| author_facet | Nurul Hazirah, Mohd Saad |
| author_sort | Nurul Hazirah, Mohd Saad |
| collection | UMP |
| description | Climate change has to be one of the greatest environmental threats to the world and it has been measured that a greater negative impacts on human society and to the natural environment changes when it climates are drastically change. General Circulation Models (GCM) stated that the increment of concentration of greenhouse gases will have significant implications for climate at regional scales. In this simulation which so-called “downscaling” techniques are used to describe as a decision support tool for local climate change impacts. Statistical Downscaling Model (SDSM) is beneficial the rapid development of multiple, low cost, single-site scenarios of daily weather variables and future regional climate force. The application of SDSM is applied to simulate with respect to the generation of daily temperature and rainfall scenarios for Temerloh River, Pahang for 2040-2069. However, in this studies is supported on the capability of IHACRES model in area where hydrological data has a limitation factor. The IHACRES model is being applied in a regionalization approach to develop streamflow prediction. Using IHACRES rainfall-runoff model, it is a non-linear loss module which is to calculate the effective rainfall and routing a linear module converting effective rainfall into streamflow. |
| first_indexed | 2024-03-06T12:23:44Z |
| format | Undergraduates Project Papers |
| id | UMPir21115 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:23:44Z |
| publishDate | 2017 |
| record_format | dspace |
| spelling | UMPir211152023-11-03T01:32:27Z http://umpir.ump.edu.my/id/eprint/21115/ Prediction of future trend of the long term streamflow pattern in the context of climate change Nurul Hazirah, Mohd Saad QC Physics TC Hydraulic engineering. Ocean engineering Climate change has to be one of the greatest environmental threats to the world and it has been measured that a greater negative impacts on human society and to the natural environment changes when it climates are drastically change. General Circulation Models (GCM) stated that the increment of concentration of greenhouse gases will have significant implications for climate at regional scales. In this simulation which so-called “downscaling” techniques are used to describe as a decision support tool for local climate change impacts. Statistical Downscaling Model (SDSM) is beneficial the rapid development of multiple, low cost, single-site scenarios of daily weather variables and future regional climate force. The application of SDSM is applied to simulate with respect to the generation of daily temperature and rainfall scenarios for Temerloh River, Pahang for 2040-2069. However, in this studies is supported on the capability of IHACRES model in area where hydrological data has a limitation factor. The IHACRES model is being applied in a regionalization approach to develop streamflow prediction. Using IHACRES rainfall-runoff model, it is a non-linear loss module which is to calculate the effective rainfall and routing a linear module converting effective rainfall into streamflow. 2017-06 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/21115/1/Prediction%20of%20future%20trend%20of%20the%20long%20term%20streamflow%20pattern%20in%20the%20context%20of%20climate%20change.pdf Nurul Hazirah, Mohd Saad (2017) Prediction of future trend of the long term streamflow pattern in the context of climate change. Faculty of Civil Engineering and Earth Resources, Universiti Malaysia Pahang. |
| spellingShingle | QC Physics TC Hydraulic engineering. Ocean engineering Nurul Hazirah, Mohd Saad Prediction of future trend of the long term streamflow pattern in the context of climate change |
| title | Prediction of future trend of the long term streamflow pattern in the context of climate change |
| title_full | Prediction of future trend of the long term streamflow pattern in the context of climate change |
| title_fullStr | Prediction of future trend of the long term streamflow pattern in the context of climate change |
| title_full_unstemmed | Prediction of future trend of the long term streamflow pattern in the context of climate change |
| title_short | Prediction of future trend of the long term streamflow pattern in the context of climate change |
| title_sort | prediction of future trend of the long term streamflow pattern in the context of climate change |
| topic | QC Physics TC Hydraulic engineering. Ocean engineering |
| url | http://umpir.ump.edu.my/id/eprint/21115/1/Prediction%20of%20future%20trend%20of%20the%20long%20term%20streamflow%20pattern%20in%20the%20context%20of%20climate%20change.pdf |
| work_keys_str_mv | AT nurulhazirahmohdsaad predictionoffuturetrendofthelongtermstreamflowpatterninthecontextofclimatechange |