Smart Kd-concept as efficient approach to improve geochemistry in reactive transport modelling

Understanding and appropriate modelling of geochemical processes is essential for predicting the contaminant transport in groundwater systems and, therefore, important in many application areas such as groundwater prediction, environmental remediation, or disposal of hazardous waste. One important natural retardation process is sorption on mineral surfaces of rocks or sediments. In order to treat the radionuclide sorption processes in natural systems more realistically, we developed the smart Kd-concept (www.smartkd-concept.de) to predict variations in sorption as consequence of changing physicochemical conditions which have to be considered in long-term safety assessments for radioactive waste repositories (Noseck et al., 2012, 2018; Stockmann et al., 2017).
In this presentation, we describe the fundamental strategy of the smart Kd-concept to calculate distribution coefficients (referred to as smart Kd-values) for a wide range of important environmental parameters. This mechanistic approach mainly based on surface complexation models and is combined with the “Component Additivity” approach to describe a natural system close to reality. This bottom-up approach based on the principle that the sorption of contaminants can be determined based on the competitive mineral-specific sorption of dissolved species on surfaces. Therefore, a full thermodynamic description of both the aqueous, solid and interface reactions is required. Using the geochemical speciation code PHREEQC (Parkhurst and Appelo, 2013), multidimensional smart Kd-matrices are computed as a function of varying (or uncertain) input parameters such as pH, ionic strength, concentration of competing cations and complexing ligands, e.g. calcium (Ca) and dissolved inorganic carbon (DIC). On the one hand, sensitivity and uncertainty statements for the distribution coefficients can be derived. On the other hand, smart Kd-matrices can be used in reactive transport codes (see abstract Noseck et al. 2020). This strategy has various benefits: (1) rapid computation of Kd-values for large numbers of environmental parameter combinations; (2) variable geochemistry is taken into account more realistically; (3) efficiency in computing time is ensured, and (4) uncertainty and sensitivity analysis are accessible. It is worth mentioning that the basic methodology described here can be transferred to any other transport code relying on conventional distribution coefficients as well as to any other complex natural site.
Results of a case study (serving as a comprehensive proof-of-concept) for a typical sedimentary rock system in Northern Germany as natural geological barrier for a deep geological repository site showed that the smart Kd approach goes considerably beyond the conventional concepts. We can illustrate that constant Kd values (see for U(VI) in Fig. 1, right, green line) previously used in transport simulations are a crude assumption, as in reality they rather range over several orders of magnitude. Moreover, with the results from the sensitivity analyses (SA) (Becker, 2016), the most important input parameters influencing the radionuclide retardation can be identified (key parameters of the model). The calculated sensitivity indices allowed us to assess the most and less sensitive parameters. From the visualized smart Kd matrix for U(VI) (Fig. 1, left) it is obvious that mainly the pH value and the DIC influences the sorption of U(VI) under the given conditions. SA is a useful means for reducing the complexity of a geochemical model by focusing on the most important input parameters.