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I. Maghami

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Open access Oct 2026

Improving National Water Model Evapotranspiration Forecasts Using Machine Learning Post-Processing: A California Case Study

Evapotranspiration (ET) forecasts from the U.S. National Water Model (NWM) carry systematic biases that are most apparent in water-stressed, intensively managed regions. This study develops a machine learning (ML) post-processing framework that bias-corrects 1–7 day accumulated ET (ACCET) forecasts from the NWM medium-...

Abin Raj Chapagain, I. Maghami, Daniel P. Ames et al. · 0 citations

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