AI RESEARCH
Evaluating Transformer and LSTM Frameworks for Prediction in Ungauged Basins
arXiv CS.AI
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ArXi:2606.02791v1 Announce Type: new Watershed networks exhibit convergent topologies in which multiple tributaries merge into downstream channels,integrating diverse upstream hydrological processes. In ungauged basins, the absence of direct observations increases uncertainty and limits the ability to anticipate extreme events. This study evaluates whether an encoder-only Transformer provides an advantage over an LSTM for upstream streamflow inference under limited hydrologic information, using retrospective simulations from the NOAA National Water Model.