Published October 17, 2022 | Version v1

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

  • 1. School of Civil Engineering, College of Engineering, University of Tehran

Description

These datasets provide precipitation data over Central Plateau watershed of Iran. Four different variants of the Inverse Distance Weighting (IDW) method are utilized to create these datasets. Two out of four IDW variants are proposed and developed by the authors to enhance the performance of the available standard models.

 

Data Format: xlsx

Spatial Resolution: ~0.08˚ & 0.25˚

Spatial Coverage: Central Plateau watershed, Iran (48˚07'E to 61˚25'E - 26˚33'N to 37˚27'N)

Temporal Resolution: Monthly

Temporal Coverage: 2005 - 2015 (Inclusively)

 

How to cite:

Arash Ghomlaghi, Mohsen Nasseri & Bardia Bayat (2022): How to enhance the inverse distance weighting method to detect the precipitation pattern in a large-scale watershed, Hydrological Sciences Journal, DOI: 10.1080/02626667.2022.2124874

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