Table 5 shows the average AIC values of semivariograms for the rainfall depth and storm pattern ( and ), respectively, computed from 10 rainstorm events in the 10-cluster gauge network. It can be seen that the average values for the rainfall depth are generally higher than those for the storm pattern. On average, and values for the rainfall depth and storm pattern approximate –42 and –1640, respectively. To find the influential raingauge for each cluster, the weighted average AIC (*AIC*_{wavg}) values are calculated using Equation (10) as shown in Table 5. In the 1st cluster which includes four gauges, the average AIC values for the rainfall depth and the storm pattern are about –41.6 and –1627.05 , respectively. The corresponding *AIC*_{wavg} values are located between –882.3 and –836.7. Since the Qing-Liu (1) gauge has the maximum *AIC*_{wavg} value (–836.7), it can be selected as the influential gauge for the 1st cluster. Similarly, in the 2nd cluster, the value at the Cui-Luan gauge is –44.91 and it is the minimum in five gauges; however, its value for the storm pattern (about –1610.1) is significantly higher than those of the remaining four gauges. This results in its weighted average AIC value (*AIC*_{wavg} = –849.9) being the maximum value. Thus, the Cui-Luan gauge is defined as the sensitive gauge in the 2nd cluster. Additionally, for the 3rd cluster where two gauges are involved (i.e. Pu-Zhong and Liu-Fen-Liao), the average AIC values for the rainfall depth ( = –39.24) and the storm pattern ( = –1603.4) at the Pu-Zhong gauge are the maximum. Thus, the corresponding weighted average is at the maximum ( = –840.9). Therefore, the Zhong-Pu gauge should be identified as the influential gauge in the 3rd cluster. Using the same method as the aforementioned, the influential gauges in other clusters can also be determined as show in Figure 11. It can be seen that the 10 influential raingauges, the Qing-Liu gauge (RG1), Cui-Luan gauge (RG2), Liu-Fen-Liao gauge (RG3), Cao-Tun gauge (RG4), Ri-yue-tan gauge (RG8), Zhang-hu gauge (RG10), Taichung gauge (RG11), Pu-Li gauge (RG15), Feng-Shu-Liu gauge (RG17), and Bei-Shan (1) gauge (RG22), are approximately uniformly distributed throughout the Wu River Watershed. It concludes that these 10 raingauges can form a representative network for the Wu River watershed under the consideration of 10 clusters.

Table 5

. | . | Average AIC . | . | ||
---|---|---|---|---|---|

No of cluster . | Raingauge . | . | Rainfall depth . | Storm pattern . | Weighted average AIC_{wavg}
. |

1 | Qing-Liu (1) | RG1 | –42.58 | –1588.31 | –836.74* |

Hui-Sun | RG7 | –41.49 | –1617.49 | –850.24 | |

Qing-Liu | RG12 | –42.47 | –1679.75 | –882.34 | |

Ling-Xiao | RG14 | –40.11 | –1622.67 | –851.44 | |

2 | Cui-Luan | RG2 | –44.91 | –1610.10 | –849.96* |

Cui-Luan (1) | RG16 | –41.10 | –1696.38 | –889.29 | |

Kun-Yang | RG19 | –40.57 | –1646.60 | –863.86 | |

Rui-Yan | RG20 | –43.57 | –1668.08 | –877.61 | |

Cui-Feng | RG21 | –44.81 | –1622.81 | –856.22 | |

3 | Liu-Fen-Liao | RG3 | –39.24 | –1603.39 | –840.93* |

Pu-Zhong | RG26 | –39.99 | –1685.44 | –882.71 | |

4 | Cao-Tun | RG4 | –43.62 | –1611.26 | –849.25* |

5 | Bei-Shan (1) | RG5 | –41.87 | –1566.61 | –825.17* |

Bei-Shan | RG22 | –44.86 | –1637.54 | –863.63 | |

Wai-Da-Ping | RG25 | –42.11 | –1677.98 | –881.10 | |

6 | Tou-Bain-Keng | RG6 | –46.35 | –1655.45 | –874.07 |

Tai-Chung | RG11 | –38.15 | –1615.34 | –845.82* | |

Shui-Chang-Liu | RG23 | –39.58 | –1694.95 | –887.05 | |

Chang-Fu | RG24 | –40.25 | –1655.30 | –867.89 | |

7 | Feng-Shu-Lin | RG17 | –41.97 | –1634.72 | –859.33* |

Ren-Ai | RG18 | –46.14 | –1632.66 | –862.47 | |

8 | Ri-Yue_Tan | RG8 | –42.48 | –1631.12 | –858.04* |

Yu-Chi | RG9 | –43.55 | –1687.44 | –887.27 | |

9 | Da-Du-Cheng | RG13 | –40.44 | –1677.27 | –879.08 |

Pu-Li | RG15 | –45.08 | –1661.80 | –875.98* | |

10 | Zhang-Hu | RG10 | –40.69 | –1635.06 | –858.22* |

. | . | Average AIC . | . | ||
---|---|---|---|---|---|

No of cluster . | Raingauge . | . | Rainfall depth . | Storm pattern . | Weighted average AIC_{wavg}
. |

1 | Qing-Liu (1) | RG1 | –42.58 | –1588.31 | –836.74* |

Hui-Sun | RG7 | –41.49 | –1617.49 | –850.24 | |

Qing-Liu | RG12 | –42.47 | –1679.75 | –882.34 | |

Ling-Xiao | RG14 | –40.11 | –1622.67 | –851.44 | |

2 | Cui-Luan | RG2 | –44.91 | –1610.10 | –849.96* |

Cui-Luan (1) | RG16 | –41.10 | –1696.38 | –889.29 | |

Kun-Yang | RG19 | –40.57 | –1646.60 | –863.86 | |

Rui-Yan | RG20 | –43.57 | –1668.08 | –877.61 | |

Cui-Feng | RG21 | –44.81 | –1622.81 | –856.22 | |

3 | Liu-Fen-Liao | RG3 | –39.24 | –1603.39 | –840.93* |

Pu-Zhong | RG26 | –39.99 | –1685.44 | –882.71 | |

4 | Cao-Tun | RG4 | –43.62 | –1611.26 | –849.25* |

5 | Bei-Shan (1) | RG5 | –41.87 | –1566.61 | –825.17* |

Bei-Shan | RG22 | –44.86 | –1637.54 | –863.63 | |

Wai-Da-Ping | RG25 | –42.11 | –1677.98 | –881.10 | |

6 | Tou-Bain-Keng | RG6 | –46.35 | –1655.45 | –874.07 |

Tai-Chung | RG11 | –38.15 | –1615.34 | –845.82* | |

Shui-Chang-Liu | RG23 | –39.58 | –1694.95 | –887.05 | |

Chang-Fu | RG24 | –40.25 | –1655.30 | –867.89 | |

7 | Feng-Shu-Lin | RG17 | –41.97 | –1634.72 | –859.33* |

Ren-Ai | RG18 | –46.14 | –1632.66 | –862.47 | |

8 | Ri-Yue_Tan | RG8 | –42.48 | –1631.12 | –858.04* |

Yu-Chi | RG9 | –43.55 | –1687.44 | –887.27 | |

9 | Da-Du-Cheng | RG13 | –40.44 | –1677.27 | –879.08 |

Pu-Li | RG15 | –45.08 | –1661.80 | –875.98* | |

10 | Zhang-Hu | RG10 | –40.69 | –1635.06 | –858.22* |

‘*’ means the influential gauge selected in each cluster.

Figure 11

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