Travel-time based hydraulic tomography is a promising method to characterize heterogeneity of porous-fractured aquifers. However, there is inevitable noise in field-scale experimental data and many hydraulic signal travel times, which are derived from the pumping test’s first groundwater level derivative drawdown curves and are strongly influenced by noise. The required data processing is thus quite time consuming and often not accurate enough. Therefore, an effective and accurate de-noising method is required for travel time inversion data processing. In this study, a series of hydraulic tomography experiments were conducted at a porous-fractured aquifer test site in Goettingen, Germany. A numerical model was built according to the site’s field conditions and tested based on diagnostic curve analyses of the field experimental data. Gaussian white noise was then added to the model’s calculated pumping test drawdown data to simulate the real noise in the field. Afterward, different de-noising methods were applied to remove it. This study has proven the superiority of the wavelet de-noising approach compared with several other filters. A wavelet de-noising method with calibrated mother wavelet type, de-noising level, and wavelet level was then determined to obtain the most accurate travel time values. Finally, using this most suitable de-noising method, the experimental hydraulic tomography travel time values were calculated from the de-noised data. The travel time inversion based on this de-noised data has shown results consistent with previous work at the test site.

There is a burgeoning interest in reliably characterizing the intrinsic reactivity of metallic iron materials (Fe⁰) or zero-valent iron materials (ZVI) used in the water treatment industry. The present work is a contribution to a science-based selection of Fe⁰ for water treatment. A total of eight (8) granular ZVI materials (ZVI1 to ZVI8) were tested. Fe⁰ dissolution in ethylenediaminetetraacetic acid (EDTA test) and 1,10-Phenanthroline (Phen test) is characterized in parallel experiments for up to 250 h (10 days). 50 mL of each solution and 0.1 g of each Fe⁰ material are equilibrated in quiescent batch experiments using 2 mM EDTA or Phen. Results indicated a far higher extent of iron dissolution in EDTA than in Phen under the experimental conditions. The tested materials could be grouped into three reactivity classes: (i) low (ZVI4, ZVI6, ZVI7, and ZVI8), (ii) moderate (ZVI1 and ZVI5) and (iii) high (ZVI2 and ZVI3). The order of reactivity was the same for both tests: ZVI2 ≅ ZVI3 > ZVI1 ≅ ZVI5 > ZVI4 ≅ ZVI6 ≅ ZVI7 ≅ ZVI8. Phen results revealed for the first time the time-dependent variation of the kinetics of iron corrosion (corrosion rate) in short-term batch experiments. Overall, the results demonstrated the superiority of the Phen test for evaluating the initial stage of Fe⁰ dissolution. Long-term column experiments are recommended to deepen the acquired knowledge.

Travel time based hydraulic tomography is a technique for reconstructing the spatial distribution of aquifer hydraulic properties (e.g., hydraulic diffusivity). Simultaneous Iterative Reconstruction Technique (SIRT) is a widely used algorithm for travel time related inversions. Due to the drawbacks of SIRT implementation in practice, a modified SIRT with Cimmino iteration (SIRT-Cimmino) is proposed in this study. The incremental correction is adjusted, and an iteration-dependent relaxation parameter is introduced. These two modifications enable an appropriate speed of convergence, and the stability of the inversion process. Furthermore, a new result selection rule is suggested to determine the optimal iteration step and its corresponding result. SIRT-Cimmino and SIRT are implemented and verified by using two numerical aquifer models with different predefined (“true”) diffusivity distributions, where high diffusivity zones are embedded in a homogenous low diffusivity field. Visual comparison of the reconstructions shows that the reconstruction based on SIRT-Cimmino demonstrates the aquifer’s hydraulic features better than the conventional SIRT algorithm. Root mean square errors and correlation coefficients are also used to quantitatively evaluate the performance of the inversion. The reconstructions based on SIRT-Cimmino are found to preserve the connectivity of the high diffusivity zones and to provide a higher structural similarity to the “true” distribution.