This paper introduces a novel application of spatial-temporal graph neural networks (ST-GNNs) to predict groundwater levels. Groundwater level prediction is inherently complex, influenced by various ...
Surface and groundwater resources interact continuously at different spatial and temporal scales, and they are used in the agriculture sector in many plains. It is important, therefore, accurately to ...
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