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Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Sundareshwara, C. S. | - |
dc.date.accessioned | 2014-10-05T11:16:45Z | - |
dc.date.available | 2014-10-05T11:16:45Z | - |
dc.date.issued | 1980 | - |
dc.identifier | M.Tech | en_US |
dc.identifier.uri | http://hdl.handle.net/123456789/4146 | - |
dc.guide | Yoganarasimhan, G. N. | - |
dc.description.abstract | For most of rivers normally the historical data available Will be of short duration. The Water Resources. Projects based on. such records may not be fully reliable in respect of Planned diversion and storage characteristics. The plans based on the statistical. parameters of long term data is consdered superior to the alternative of depending on the historical sequence. Keeping this in voiw three mathematical models viz. (1) Markovian models both for seasonal and annual flows, (z) Fast Fractional Gaussian Noise models, (3) Broken line model and its modifications......... | en_US |
dc.language.iso | en | en_US |
dc.subject | WATER RESOURCES DEVELOPMENT AND MANAGEMENT | en_US |
dc.subject | SEQUENTIAL GENERATION | en_US |
dc.subject | HYDROLOGIC DATA | en_US |
dc.subject | MARKOVIAN MODELS | en_US |
dc.title | SEQUENTIAL GENERATION OF HYDROLOGIC DATA | en_US |
dc.type | M.Tech Dessertation | en_US |
dc.accession.number | 176177 | en_US |
Appears in Collections: | MASTERS' THESES (WRDM) |
Files in This Item:
File | Description | Size | Format | |
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WRDM176177.pdf | 11.12 MB | Adobe PDF | View/Open |
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