51 The outcome of the falsification test will determine the next step in the workflow. If H1 is not falsified, Approximate Bayesian Computation will be applied to generate posterior realisations conditioned on the observations, providing probabilistic forecasts of pressure evolution under the planned dewatering scenario with quantified uncertainty bounds. If H1 is falsified, the diagnostic information from the sensitivity analysis will be used to identify whether the prior parameter ranges are too narrow (in which case the prior is revised, the Monte Carlo ensemble regenerated, and the falsification test repeated) or whether the model is missing a physical mechanism, in particular delayed drainage from the rock matrix into the fracture system, requiring progression to hypothesis H2 with explicit dual porosity. 4. RESULTS The work reported here represents stages one through three of the Popper-Bayes protocol described in Section 3.1. The decision problem has been formulated, prior probability distributions have been specified for matrix permeability across twelve stratigraphic units, vertical anisotropy in the Bancroft Dolostone and Nchanga Member confining units, a fracture permeability multiplier, and three regional aquifer recharge boundaries (Tables 1 and 2). One hundred Monte Carlo realisations have been generated and forward-simulated under the fiveyear dewatering scenario, producing a high-dimensional ensemble of predicted pore pressure responses across multiple monitoring locations and time steps. Visual inspection of the simulated ensemble confirms that predicted pressure responses span a wide range across the realisations, indicating that the prior uncertainty distributions encompass physically plausible outcomes for the Mingomba setting. This wide ensemble spread is itself a meaningful preliminary observation: it confirms that decisions about dewatering design at this site cannot be reliably made based on a single deterministic forecast, since the predicted response varies substantially with parameter combinations that are all consistent with current knowledge of the site. The next analytical stage is the application of DGSA over one thousand simulations to identify the dominant controlling parameters in this ensemble. The output of that stage will be a ranked
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