Geostatistical interpolation of space–time rainfall on Tamshui River basin, Taiwan

Taiwan suffers from heavy storm rainfall during the typhoon season. This usually causes large river runoff, overland flow, erosion, landslides, debris flows, loss of power, etc. In order to evaluate storm impacts on the downstream basin, a real-time hydrological modelling is used to estimate potential hazard areas. This can be used as a decision-support system for the Emergency Response Center, National Fire Agency Ministry, to make ‘real-time’ responses and minimize possible damage to human life and property. This study used 34 observed events from 14 telemetered rain-gauges in the Tamshui River basin, Taiwan, to study the spatial–temporal characteristics of typhoon rainfall. In the study, regionalized theory and cross-semi-variograms were used to identify the spatial-temporal structure of typhoon rainfall. The power form and parameters of the cross-semi-variogram were derived through analysis of the observed data. In the end, cross-validation was used to evaluate the performance of the interpolated rainfall on the river basin. The results show the derived rainfall interpolator represents the observed events well, which indicates the rainfall interpolator can be used as a spatial-temporal rainfall input for real-time hydrological modelling. Copyright © 2007 John Wiley & Sons, Ltd.

[1]  Dionissios T. Hristopulos,et al.  On the physical geometry concept at the basis of space/time geostatistical hydrology , 2000 .

[2]  Marshall E. Moss,et al.  An intercomparison of hydrological network-design technologies , 1991 .

[3]  J. Chilès,et al.  Geostatistics: Modeling Spatial Uncertainty , 1999 .

[4]  Shahrokh Rouhani,et al.  Multivariate geostatistical approach to space‐time data analysis , 1990 .

[5]  James P. Hughes,et al.  Data requirements for kriging: Estimation and network design , 1981 .

[6]  Georges Bastin,et al.  Variogram identification by the mean-squared interpolation error method with application to hydrologic fields , 1985 .

[7]  R. B. Clapp,et al.  Cokriging model for estimation of water table elevation , 1989 .

[8]  G. Bastin,et al.  On the Accuracy of Areal Rainfall Estimation - a Case-study , 1987 .

[9]  P. Goovaerts.  Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall , 2000 .

[10]  Soroosh Sorooshian,et al.  Spatial characteristics of thunderstorm rainfall fields and their relation to runoff , 2003 .

[11]  N. T. Kottegoda,et al.  Rainfall network design through comparative kriging methods , 1991 .

[12]  Shin-jen Cheng,et al.  An approach for evaluating the hydrological effects of urbanization and its application , 2002 .

[13]  Rafael L. Bras,et al.  Optimal estimators of mean areal precipitation in regions of orographic influence , 1982 .

[14]  Michel Gevers,et al.  OPTIMAL ESTIMATION OF THE AVERAGE AREAL RAINFALL AND OPTIMAL SELECTION OF RAIN-GAUGE LOCATIONS , 1984 .

[15]  J. Salas,et al.  A COMPARATIVE ANALYSIS OF TECHNIQUES FOR SPATIAL INTERPOLATION OF PRECIPITATION , 1985 .