Importance

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Abstract

Techniques are described for predicting groundwater for a locale, which is a subregion of a geographic region for which measurements of water storage are available at a coarse level. In a method, in response to receiving an input locale, a prediction of groundwater level for the input locale is provided. The prediction of groundwater level at the input locale is computed using a machine learning model. The machine learning model uses a plurality of parameters, which are weighted during a training phase of the machine learning model, and water storage measurements for a geographic region that encompasses the locale, the geographic region being larger than the locale, and wherein a resolution of the water storage measurements is downscaled. The prediction of groundwater level is outputted for the input locale.

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First Claim