Search for a command to run...
“It is in the tentative stage that the affections enter with their blinding influence. Love was long since represented as blind…The moment one has offered an original explanation for a phenomenon which seems satisfactory, that moment affection for his intellectual child springs into existence…To guard against this, the method of multiple working hypotheses is urged. … The effort is to bring up into view every rational explanation of new phenomena, and to develop every tenable hypothesis respecting their cause and history. The investigator thus becomes the parent of a family of hypothesis: and, by his parental relation to all, he is forbidden to fasten his affections unduly upon any one” (Chamberlin, 1890).The MADE (macro-dispersion) natural-gradient tracer field experiments were conducted more than 35 years ago. It aimed to determine field-scale dispersion parameters based on detailed hydraulic conductivity measurements to support transport simulation. A decade of field experiments produced a 30-year paper trail of modelling studies with no clear resolution of a successful simulation approach for practical use in transport problems. As a result, accurately simulating contaminant transport in the subsurface remains a formidable challenge in hydrogeology.What went awry, and why do we often miss the mark?Herweijer et al. (2026) conducted a ‘back to basics’ review of the original MADE reports and concluded that there are significant inconvenient and unexplored issues that influenced the migration of the tracer plume and or biased observations. These issues include unreliable measurement of hydraulic conductivity, biased tracer concentrations, and underestimation of sedimentological heterogeneity and non-stationarity of the flow field. Many studies simulating the tracer plumes appeared to have ignored, sidestepped, or been unaware of these issues, raising doubts about the validity of the results.Our analysis shows that there is a persistent drive among researchers to conceptually oversimplify natural complexity to enable testing of single-method modelling, mostly driven by parametric stochastic approaches. Researchers tend to be anchored to a specialised, numerically driven methodology and have difficulty in unearthing highly relevant information from ‘unknown known’ data or applying approaches outside their own specialised scientific sub-discipline. Another important aspect of these ‘unkowns knowns’ is the tendency to accept published data verbatim. Too often, there is no rigorous investigation of the original measurement methods and reporting, and, if need be, additional testing to examine the root cause of data issues.Following the good old advice of Chamberlin (1890), we used a knowledge framework to systematically assess knowns, unknowns, and associated confidence levels, yielding a set of multi-conceptual models. Based on identified 'unknowns', these multi-models can be tested against reliable 'knowns' such as piezometric data and mass balance calculations. Chamberlin, T.C., 1890, The method of multiple working hypotheses. Science 15(366): 92-96. doi:10.1126/science.ns-15.366.92.Herweijer J.C., S. C Young, P. Hayes, and O. Batelaan, 2026, A multi-conceptual model approach to untangling the MADE experiment, Accepted for Publication in Groundwater.