Mass conservation moves into a distributed hydrologic network: PECAN matches outlet streamflow in a Colorado snow basin but releases winter snowpack early
Mass-conservation constraints had been embedded only in lumped LSTMs, which yield basin-averaged time series and cannot test whether internal states are hydrologically meaningful. PECAN recasts the constraint in a distributed convolutional LSTM, with a strict precipitation-only variant, PECANMC, and a relaxed variant, PECANMCR, trained solely on streamflow at two gauges. In the snow-dominated North Platte Headwaters in Colorado, both variants match lumped deep-learning baselines and the distributed process model VIC on outlet streamflow and expose spatially explicit internal states, yet diagnostics show the model removes winter snow water storage prematurely instead of holding it for spring release.