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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
refutedsupported
the weight of evidence
4 sources for · 0 against

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.

Evidence for · 4
2007 · cited by 27
Demonstrates that inverse distance methods are appropriate for rapid rainfall estimation across a watershed.
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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.

More for · 3
2022 · cited by 19
Shows that deterministic and probabilistic inverse distance weighting methods can be utilized and optimized for spatial estimation of precipitation in a watershed.
2024 · cited by 2
Confirms that utilizing inverse distance weighting combined with elevation effectively represents the spatial and temporal variation of rainfall in a watershed.
2025 · cited by 2
Finds that inverse distance weighting interpolation provides reliable spatial results for rainfall data in sparse station networks within river basins.
The paper trail · every fact has a biography
first checked05 Aug 2026
judged → SUPPORTED · 8405 Aug 2026
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