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Transboundary aquifer compacts must forecast groundwater depletion from sparse piezometric networks and coarse satellite gravimetry, yet the joint assimilation of these two observation types into a predictive digital twin remains methodologically unsettled. The framework is evaluated as a climate-analytics construct: forecast skill is expressed as a function of observation density, gravimetric noise, and the ratio of storage coefficient to recharge variance, and the conditions under which satellite-only assimilation dominates, ties, or is dominated by sparse in-situ assimilation are stated as propositions with proofs. A worked calibration using NASA POWER monthly reanalysis for Kampala, Uganda (0.35°N, 32.58°E), 2000–2023, 312 monthly observations, gives a mean air temperature of 22.443 °C and a decadal trend of −0.1564 °C, which is used only to fix the climatic forcing envelope of the illustrative aquifer and not as a groundwater observation. The marginal value of piezometry is non-monotonic in network density, that gravimetric assimilation alone cannot resolve storage-coefficient error below a threshold set by the noise-to-signal ratio, and that compact-level forecast skill is bounded by the weaker of the two observation streams. The contribution is a decision-theoretic criterion for allocating observation effort across shared aquifer boundaries.
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Haroun et al. (2026) studied this question.