Reconstructive Mapping from Sparsely-Sampled Groundwater Data Using Compressive Sensing

Compressive sensing is a powerful method for reconstruction of sparsely-sampled data, based on statistical optimization. It can be applied to range flow measurement and visualization in this work we show the usage groundwater mapping. Due scarcity water many regions world, including southwestern United States, monitoring management utmost importance. A complete mapping difficult since monitored sites are far from one another, thus data sets considered extremely “sparse”. To overcome difficulty groundwater, compressive an ideal tool, as it bypasses classical Nyquist criterion. We that effectively used reconstructions level maps, by validating against data. This approach have impact geographical information, effective enabled without constructing numerous or expensive groundwater.