Suppose that we must delete stations from a monitoring network. Which stations should be deleted if we wish the remaining network to have the smallest possible trend estimate variances? We use the spatial-temporal model described in Oehlert (1993, J. Am. Statist. Assoc., 88, 390{\textendash}399), to model concentration of sulfate in wet deposition. Based on this model and three criteria, we choose good sets of candidate stations for deletion from the NADP/NTN network. We use the criteria: that the sum of 11 regional trend estimate variances be as small as possible, that the sum of local trend estimation variance be as small as possible, and that the sum of local mean estimation variance be as small as possible. Good choices of stations for deletion result in a modest increase in criteria (about 7 to 34\%) for 100 stations deleted from the network, while random sets of 100 stations can increase criteria by a factor of two or more.

}, keywords = {Monitoring network, network design, spatial smoothing, trend analysis}, doi = {10.1016/1352-2310(95)00333-9}, author = {Oehlert, Gary W.} }