WC-KNNG-PC: Watershed clustering based on k-nearest-neighbor graph and Pauta Criterion

•Propose a new watershed clustering based on k-nearest-neighbor graph and Pauta Criterion to deal with complex dataset.•Introduce neighbor information and Pauta Criterion to altitude and point-to-point aggregation.•propose a two-step immersion to accomplish the point-to-point aggregation.•This algorithm utilize stability to determine outliers and mergeable subclusters.•The algorithm presents a basin-level similarity measure to merge sub-clusters.