Three conceptual models are evaluated for estimating transmissivity (T) fields using data from sequential pumping tests at a field site and data from similar tests simulated in a synthetic aquifer. The three approaches are (1) an equivalent homogeneous approach, (2) a heterogeneous approach based on a single pumping test, and (3) a heterogeneous approach based on joint interpretation of the sequential pumping tests (i.e., hydraulic tomography, HT). They are evaluated on the basis of their abilities to obtain representative estimates of the T field of the aquifer and, more importantly, on the ability of their estimates to predict drawdown distributions in the aquifer induced by independent validation pumping tests. Results show that the first approach yields scenario-dependent T estimates, which vary with the location of the pumping well. Independent validation tests show that the predicted drawdowns in both aquifers are biased and dispersed. While the second approach produces scenario-dependent T spatial distributions capturing the general pattern of the aquifer, the T fields consistently yield better drawdown predictions than those based on the first approach. Lastly, the joint interpretation approach reduces the scenario dependence of the T estimates and improves the quality of the T estimates as more data sets from sequential pumping tests are included. More importantly, the resultant T estimates lead to the best prediction of different flow events. The robustness of the joint interpretation is then elucidated.