Soil porewater chemistry underpins the quantification of carbon dioxide removal (CDR) in enhanced rock weathering (ERW), where alkalinity and dissolved ion measurements are used within monitoring, reporting and verification (MRV) frameworks. The reliability of these measurements depends on the extraction method, with many in-field techniques constrained by soil moisture availability. This dependence can limit data continuity, reduce comparability across sites and seasons and introduce uncertainty into CDR-relevant interpretations. Here, we present and evaluate a new soil porewater extraction method, SATuration–Centrifugation (SAT-C), designed to obtain porewater from a defined soil volume independent of moisture conditions. The method combines saturation of intact soil cores using deionized water with centrifugation to recover porewater for chemical analysis. We compare SAT-C with conventional sampling using soils collected from grassland field sites, including sites amended with crushed basalt as part of ERW field trials. Across sites, SAT-C porewater chemistry shows strong agreement with rhizon samples for major ions, and bicarbonate concentrations inferred from charge balance are consistent with measured alkalinity. These initial results show that SAT-C provides a robust and reproducible approach for soil porewater extraction, with the potential to improve sampling reliability across variable conditions and thereby support more reliable carbon accounting in ERW.

In this paper, we first propose a statistical model, called the Coherent Incurred Paid model, to predict future claims, using simultaneously the information contained in incurred and paid claims. This model does not assume log-normality of the levels (or normality of the growth rates) and is semi-parametric since it only specifies the first and the second moments; however, in order to evaluate the impact of the normality assumption, we also propose a benchmark Gaussian version of our model. Correlations between growth rates of incurred and paid claims are allowed and the tail development period is estimated. We also provide methods for computing the Claim Development Results and their Values at Risk in the semi-parametric framework. Moreover, we show how to take into account the updating of the estimation in the computation of the Claim Development Results. An application highlights the practical importance of relaxing the normality assumption and of updating the estimation of the parameters.