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Individual site-based assessment (assumed ungauged one by one) resulted in the comparatively poorest method being the IDW, followed by the IDW-PC method. In comparison to the IDW-PC, the M1 provided overall significant results for the study area, except for sites 1, 2, 6, and 13, while the IDW-PC resulted in slightly better performance, as shown in Figure 5. In comparison to the studied models, it was noted that the M2 model produced a significantly accurate prediction by exhibiting a comparatively lower RMSE for the entire study area. Similarly, employing the overall mean RMSE as the performance indicator, the worst method was the IDW, followed by the IDW-PC method (Table 3). The suggested models performed better than the contender methods. Among the suggested models, the performance of M2 based on overall mean RMSE for varying C was found to be the highest, followed by M1, having values of 10.20 and 11.28, respectively. These results verified that consideration of a large number of influential factors (physiographical space-based weights) reduced the estimation error.
Table 3

Overall average interpolation error| (RMSE) resulting from proposed and contender methods

 IDWIDW-PCM1M2
Average RMSE 14.09 11.65 11.28 10.20 
 IDWIDW-PCM1M2
Average RMSE 14.09 11.65 11.28 10.20 
Figure 5

Average RMSE value at individual catchment by using comparative interpolation models (e.g., IDW, IDW-PC, M1, and M2).

Figure 5

Average RMSE value at individual catchment by using comparative interpolation models (e.g., IDW, IDW-PC, M1, and M2).

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