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Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan

Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the... In this article, we used the inverse distance weighting (IDW) method to estimate the rainfall distribution in the middle of Taiwan. We evaluated the relationship between interpolation accuracy and two critical parameters of IDW: power (α value), and a radius of influence (search radius). A total of 46 rainfall stations and rainfall data between 1981 and 2010 were used in this study, of which the 12 rainfall stations belonging to the Taichung Irrigation Association (TIA) were used for cross-validation. To obtain optimal interpolation data of rainfall, the value of the radius of influence, and the control parameter-α were determined by root mean squared error. The results show that the optimal parameters for IDW in interpolating rainfall data have a radius of influence up to 10–30 km in most cases. However, the optimal α values varied between zero and five. Rainfall data of interpolation using IDW can obtain more accurate results during the dry season than in the flood season. High correlation coefficient values of over 0.95 confirmed IDW as a suitable method of spatial interpolation to predict the probable rainfall data in the middle of Taiwan. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Paddy and Water Environment Springer Journals

Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan

Chen, Feng-Wen; Liu, Chen-Wuing
Paddy and Water Environment , Volume 10 (3) – Feb 25, 2012
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References (40)

Publisher
Springer Journals
Copyright
Copyright © 2012 by Springer-Verlag
Subject
Life Sciences; Soil Science & Conservation; Hydrogeology; Agriculture; Geoecology/Natural Processes; Ecotoxicology; Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution
ISSN
1611-2490
eISSN
1611-2504
DOI
10.1007/s10333-012-0319-1
Publisher site
See Article on Publisher Site

Abstract

In this article, we used the inverse distance weighting (IDW) method to estimate the rainfall distribution in the middle of Taiwan. We evaluated the relationship between interpolation accuracy and two critical parameters of IDW: power (α value), and a radius of influence (search radius). A total of 46 rainfall stations and rainfall data between 1981 and 2010 were used in this study, of which the 12 rainfall stations belonging to the Taichung Irrigation Association (TIA) were used for cross-validation. To obtain optimal interpolation data of rainfall, the value of the radius of influence, and the control parameter-α were determined by root mean squared error. The results show that the optimal parameters for IDW in interpolating rainfall data have a radius of influence up to 10–30 km in most cases. However, the optimal α values varied between zero and five. Rainfall data of interpolation using IDW can obtain more accurate results during the dry season than in the flood season. High correlation coefficient values of over 0.95 confirmed IDW as a suitable method of spatial interpolation to predict the probable rainfall data in the middle of Taiwan.

Journal

Paddy and Water Environment – Springer Journals

Published: Feb 25, 2012

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