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the claim

Rainfall data from external stations can be interpolated for a watershed using inverse distance weighting

the verdict
SUPPORTED
the evidence backs this
Recorded sources
4 sources for · 0 against

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Is it true that rainfall data from external stations can be interpolated for a watershed using inverse distance weighting?

Yes. Multiple studies demonstrate that inverse distance weighting (IDW) is an effective and widely used method for interpolating rainfall data from external stations across a watershed, particularly when enhanced with elevation or adapted for sparse networks.

Verdict: SUPPORTED · 4 sources for, 0 against · Last checked

The analysis

The retrieved literature contains multiple papers evaluating spatial interpolation methods for rainfall in watersheds, with papers [5], [6], [9], and [10] directly supporting the use of inverse distance weighting (IDW) for this purpose. While other papers discuss geostatistical alternatives like kriging, none refute IDW as a viable interpolation method, leading to a supported verdict.

Evidence for · 4
Mapping monthly rainfall data in Galicia (NW Spain) using inverse distances and geostatistical methods
2007
Demonstrates that inverse distance methods are appropriate for rapid rainfall estimation across a watershed.
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Mirás-Avalos, J..., Paz-González, A., Vidal‐Vázquez, E., & Sande-Fouz, P. (2007). Mapping monthly rainfall data in Galicia (NW Spain) using inverse distances and geostatistical methods. doi.org. https://doi.org/10.5194/ADGEO-10-51-2007

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More for · 3
How to enhance the inverse distance weighting method to detect the precipitation pattern in a large-scale watershed
2022
Shows that deterministic and probabilistic inverse distance weighting methods can be utilized and optimized for spatial estimation of precipitation in a watershed.
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Ghomlaghi, A., Nasseri, M., & Bayat, B. (2022). How to enhance the inverse distance weighting method to detect the precipitation pattern in a large-scale watershed. doi.org. https://doi.org/10.1080/02626667.2022.2124874

Spatial and temporal variability of precipitation in a mountainous watershed using weighted interpolation by distance and elevation
2024
Confirms that utilizing inverse distance weighting combined with elevation effectively represents the spatial and temporal variation of rainfall in a watershed.
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Costa, D., Bayissa, Y. A., Dias, R. M. d. M. d. S., Sales, D., Junior, J. L., Neto, A. J. S., & Srinivasan, R. (2024). Spatial and temporal variability of precipitation in a mountainous watershed using weighted interpolation by distance and elevation. doi.org. https://doi.org/10.29183/2596-237x.ensus2024.v12.n1.p602-610

Research on Optimizing Rainfall Interpolation Methods for Distributed Hydrological Models in Sparsely Networked Rainfall Stations of Watershed
2025
Finds that inverse distance weighting interpolation provides reliable spatial results for rainfall data in sparse station networks within river basins.
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Feng, D., Chen, Y., Jiang, P., & Ni, J. (2025). Research on Optimizing Rainfall Interpolation Methods for Distributed Hydrological Models in Sparsely Networked Rainfall Stations of Watershed. doi.org. https://doi.org/10.3390/w17223237

Receipt History
first checked05 Aug 2026
judged → SUPPORTED · 8405 Aug 2026
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