2003 Fiscal Year Final Research Report Summary
Development of an accurate Evapotranspiration estimation methodology for water and energy cycle estimation in urban areas
| Project/Area Number |
14595003
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
水循環システム
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| Research Institution | The University of Tokyo |
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Principal Investigator |
DUTTA Dushmanta The University of Tokyo, Institute of Industrial Science, Associate Professor, 生産技術研究所, 助教授 (30291313)
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| Project Period (FY) |
2002 – 2003
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| Keywords | Evapotranspiration / Land Cover parameterization / Remote Sensing / Land Surface Scheme / Urban Environmental Energy cycle / Urban Water Cycle / Spectral analysis / Land classification for urban areas |
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| Research Abstract |
In this project the main objective was the improved assessment of evapotranspiration from urban areas. In order to achieve this, two activities were carried out. The first is to clarify the evapotranspiration process in the urban areas using detailed observations from two micro-climate towers. The evapotranspiration process was modeled using numerical simulation employing both hydrological and energy based models. The main vegetation characteristics important in the estimation of evapotranspiration were identified as the leaf area index, root depth and root density together with the evapotranspiration model parameters. It was found that hydrological observations such as variation of soil moisture with time can be simulated with more than one set of crop and soil parameters resulting in very close hydrological predictions, but very different evaporation estimates. However, when both water and energy equations are used in the solution, a unique set of parameters representative of the field can produce a range of hydrological and thermal characteristics of a site.
The second activity, carried out was to investigate land classification using remote sensing techniques to identify to accurately identify land cover information to improving evapotranspiration estimates over a large area. SPOT, Landsat and IKONOS satellite images were used in the remote sensing investigations. Hireachical statistical classification as well as combining with landscape geometrical forms were found to improve urban land classification.
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