How to enhance the inverse distance weighting method to detect the precipitation pattern in a large-scale watershed

ABSTRACT

Accurate spatial estimation of precipitation is central to hydroclimatic studies. In this study, deterministic and probabilistic inverse distance weighting (IDW) methods were utilized to provide spatial estimations of precipitation. To improve their accuracy, a modified version of IDW was developed involving a separation of IDW weights in the X-Y plane and Z direction. Moreover, four different weight functions were used to investigate how changing the pattern of the weights relative to the distance and elevation affects the accuracy of the interpolation. Finally, four IDW variants were implemented for spatial modelling of precipitation in the Central Plateau watershed located in Iran, using monthly data from 582 raingauge stations during 2005 to 2015. Based on the statistics, the modified IDW methods were about 8% more accurate than the standard IDW methods. Additionally, correlated triple collocation (CTC) analysis showed that the modified models resulted in 12% smaller root mean square errors in comparison with the standard models.

Graphical Abstract

• Performance of deterministic/probabilistic inverse distance weighting (IDW) models was enhanced by modifying the weight function.

• Precipitation datasets constructed by IDW variants were assessed point-wisely by statistical and uncertainty metrics through leave-one-out cross-validation (LOOCV) approach.

• To assess the datasets continuously, correlated triple collocation (CTC) method was utilized and error of the datasets was computed relative to the unknown truth in presence of TRMM and PERSIANN precipitation datasets.

KEYWORDS:

• inverse distance weighting (IDW)
• Tropical Rainfall Measuring Mission (TRMM)
• Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN)
• harmony search
• correlated triple collocation (CTC)
• jackknife resampling

Editor A. Fiori; Associate Editor M. Newcomer

Editor A. Fiori; Associate Editor M. Newcomer

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability

Precipitation datasets created by IDW_std, IDW_mod-p, IDW_std-jk, and IDW_mod-p-jk methods are available at http://doi.org/10.5281/zenodo.6992138. The rest of the data will be made available on request.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/02626667.2022.2124874