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| Titel |
A spatial neural fuzzy network for estimating pan evaporation at ungauged sites |
| VerfasserIn |
C.-H. Chung, Y.-M. Chiang, F.-J. Chang |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 16, no. 1 ; Nr. 16, no. 1 (2012-01-25), S.255-266 |
| Datensatznummer |
250013127
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| Publikation (Nr.) |
 copernicus.org/hess-16-255-2012.pdf |
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| Zusammenfassung |
| Evaporation is an essential reference to the management of water resources.
In this study, a hybrid model that integrates a spatial neural fuzzy network
with the kringing method is developed to estimate pan evaporation at
ungauged sites. The adaptive network-based fuzzy inference system (ANFIS)
can extract the nonlinear relationship of observations, while kriging is an
excellent geostatistical interpolator. Three-year daily data collected from
nineteen meteorological stations covering the whole of Taiwan are used to
train and test the constructed model. The pan evaporation (Epan) at
ungauged sites can be obtained through summing up the outputs of the
spatially weighted ANFIS and the residuals adjusted by kriging. Results
indicate that the proposed AK model (hybriding ANFIS and kriging) can
effectively improve the accuracy of Epan estimation as compared with
that of empirical formula. This hybrid model demonstrates its reliability in
estimating the spatial distribution of Epan and consequently provides
precise Epan estimation by taking geographical features into
consideration. |
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