This paper evaluated the applicability of four AAR (areal average rainfall) estimation methods in the mountainous Kamo River watershed by using measured monthly rainfall at nine stations within and near this watershed between 1998 and 2010. The four methods were (i) the arithmetic mean, (ii) the Thiessen polygon, (iii) the elevation regression and (iv) the combination of (ii) and (iii). Method (iv) was newly developed in this study. For methods (iii) and (iv), linear monthly relationship between elevation and monthly rainfall was applied and it was evaluated as useful for predicting rainfall even at a high elevation. Firstly, the applicability of the four AAR methods was evaluated by relationships between annual AAR (= P) and annual evapotranspiration ratio (Et/Ep). Annual evapotranspiration (Et) was obtained using the water balance equation by incorporating each AAR and measured discharge, and Ep was calculated using Penman equation. The low Et/Ep by methods (i) and (ii) was caused by the underestimation of AAR, which resulted in the underestimation of Et, mainly because these methods did not include the effect of larger rainfall in the higher elevation area. Methods (iii) and (iv) produced Et/Ep reasonably and demonstrated closer relationship to that in another mountainous watershed. Secondly, the applicability was evaluated by examining relationships between annual Ep/P and annual Et/P with a rational method of Fu (1981), where the watershed parameter w was optimized for each method. Methods (i) and (ii) produced relatively low w as a value of a mountainous watershed, which would be caused by the underestimation of annual AAR. Method (iii) produced relatively high w as a value of a mountainous watershed and R2 was relatively low. As a result, the newly presented combination method (iv) was determined to be most applicable for AAR method in this mountainous watershed.
CITATION STYLE
Limin, S. G., Oue, H., & Takase, K. (2015). Estimation of areal average rainfall in the mountainous Kamo River watershed, Japan. Journal of Agricultural Meteorology, 71(2), 90–97. https://doi.org/10.2480/agrmet.D-14-00055
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