AN ALTERNATIVE TO COKRIGING FOR SITUATIONS WITH SMALL SAMPLE SIZES

Lack of large datasets in soil protection studies and environmental en gineering applications may deprive these fields of achieving accurate spatial estimates as derived with geostatistical techniques. A new est imation procedure, with the acronym Co_Est, is presented for situation s involving primary and secondary datasets of sizes generally consider ed too small for geostatistical applications. For these situations, we suggest the transformation of the secondary dataset into the primary one using pedotransfer functions. The transformation will generate a l arger set of the primary data which subsequently can be used in geosta tistical analyses. The Co_Est procedure has provisions for handling me asurement errors in the primary data, estimation errors in the convert ed secondary data, and uncertainty in the geostatistical parameters. T wo different examples were used to demonstrate the applicability of Co _Est. The first example involves estimation of hydraulic conductivity random fields using 42 measured data and 258 values estimated from bor ehole profile descriptions. The second example consists of estimating chromium concentrations Scorn 50 measured chromium data and 150 values estimated from a relationship between chromium and copper concentrati ons. The examples indicate that in situations where the size of the pr imary data is small, Co Est can produce estimates which are comparable to cokriging estimates.