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From Conceptual Hydrologic Models to Conceptually Interpretable Neural Networks: A Snow-Water Mass-Conserving-Perceptron Framework for Discovering Catchment-Scale Precipitation-Storage-Runoff Representations

arXiv cs.LG · 2026-07-30 Cached

This paper presents a Mass-Conserving Perceptron (MCP) framework that reformulates conceptual hydrologic models into physically constrained, interpretable neural networks, evaluated across 513 CAMELS-US basins for snow-water representation.

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