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Kachinga Silwimba

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Open access Aug 2026

Efficient Emulation, Uncertainty Quantification, and Sensitivity Analysis for a Land Surface Model Using Evidential Deep Learning

Training an evidential deep neural network emulator on a 500‐member CLM5 perturbed parameter ensemble generated via Latin hypercube sampling of 32 key plant physiological parameters captures seasonal cycles, interannual variability in LAI, and uncertainties in a single pass, yielding well‐calibrated probabilistic outpu...

Kachinga Silwimba, A. Flores, L. Hawkins et al. · 0 citations
Jul 2026

Integrating meteorological forcings and satellite-derived observations to emulate snow water equivalent in the Colorado Rocky Mountains using a spatiotemporal deep learning model

A deep learning–based emulator is developed to reproduce SWE simulated by Noah-MP using a Convolutional Long Short-Term Memory (ConvLSTM) network trained on meteorological forcings from the Weather Research and Forecasting model and augmented with static physiographic variables and remotely sensed snow cover and leaf a...

Stanley Akor, A. Flores, I. Alabi et al. · 0 citations

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