Effects of kriging and inverse modeling on conditional simulation of the Avra Valley Aquifer in southern Arizona

摘要: The Avra Valley aquifer in southern Arizona is modeled stochastically at three levels of uncertainty. highest level uncertainty occurs when log transmissivity estimates are based on measured values this parameter but without regard to the geographic location each measurement point. resulting steady state hydraulic heads aquifer, computed by unconditional simulation with aid a multivariate normal random number generator coupled finite element model, have relatively large variance. This variance can be reduced conditioning spatial arrangement data means kriging. When conditional performed intermediate same technique as case, predicted head factor 3.2. lowest achieved further conditioned relating flow regime, such rates and water observation wells, statistical inverse procedure. Conditional novel concept. It results prediction that 14.3 times lower than corresponding kriged transmissivities. net effect kriging modeling reduce 46.0. A similar study Binsarti (1980) Cortaro showed insignificant reduction due kriging, four after modeling. These indicate method may much greater fact 46 implies one should cautious dealing stochastic models which effects disregarded.