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Water Resources Management

Erschienen in:

01.12.2012

Estimation of Daily Pan Evaporation Using Two Different Adaptive Neuro-Fuzzy Computing Techniques

verfasst von: Hadi Sanikhani, Ozgur Kisi, Mohammad Reza Nikpour, Yagob Dinpashoh

Erschienen in: Water Resources Management | Ausgabe 15/2012

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Abstract

This paper investigates the ability of two different adaptive neuro-fuzzy inference systems (ANFIS) including grid partitioning (GP) and subtractive clustering (SC), in modeling daily pan evaporation (E_pan). The daily climatic variables, air temperature, wind speed, solar radiation and relative humidity of two automated weather stations, San Francisco and San Diego, in California State are used for pan evaporation estimation. The results of ANFIS-GP and ANFIS-SC models are compared with multivariate non-linear regression (MNLR), artificial neural network (ANN), Stephens-Stewart (SS) and Penman models. Determination coefficient (R²), root mean square error (RMSE) and mean absolute relative error (MARE) are used to evaluate the performance of the applied models. Comparison of results indicates that both ANFIS-GP and ANFIS-SC are superior to the MNLR, ANN, SS and Penman in modeling E_pan. The results also show that the difference between the performances of ANFIS-GP and ANFIS-SC is not significant in evaporation estimation. It is found that two different ANFIS models could be employed successfully in modeling evaporation from available climatic data.

Vorheriger Artikel A Systematic Review of Water Vulnerability Assessment Tools

Nächster Artikel Regional-Specific Numerical Models of Evapotranspiration Using Gene-Expression Programming Interface in Sahel

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Titel: Estimation of Daily Pan Evaporation Using Two Different Adaptive Neuro-Fuzzy Computing Techniques
verfasst von: Hadi Sanikhani
Ozgur Kisi
Mohammad Reza Nikpour
Yagob Dinpashoh
Publikationsdatum: 01.12.2012
Verlag: Springer Netherlands
Erschienen in: Water Resources Management / Ausgabe 15/2012
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI: https://doi.org/10.1007/s11269-012-0148-4

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