Nowadays, mathematical models of hydrological systems are used routinely to guide decision making in diverse subjects, such as: environmental and risk assessments, design of remediation strategies for contaminated sites, and evaluation of the impact of climate change on water resources. The correct development and use of them is relevant beyond the realm of hydrology. The continuous improvement in computational power and data collection are leading to the development of increasingly complex models, which integrate multiple coupled physical processes to achieve a better representation of the modeled system. Most of the parameters included in models are difficult to measure directly, so they must be estimated from collected data through a calibration procedure. Furthermore, when models are used to make forecasts about future or hypothetical scenarios, it is important to bound the uncertainty of their results. Therefore, the application of systematic approaches for parameter estimation, sensitivity, and uncertainty analysis to integrate data and models and quantify potential errors, is more necessary now than it was in the past. Even though methodological frameworks for these purposes exist, they have had a slow adoption due to their high computational cost and the required technical knowledge to apply them. We analyze existing methodologies, discuss remaining challenges, and present a survey of emerging trends for the application of parameter estimation and uncertainty analysis in hydrological modeling. Thus, the main objective of this overview article is contributing to improving the quality of models and to their correct use as support tools for decision-making.

Farmland soils are prone to contamination with micro- and nanoplastics through a variety of agricultural practices. Concerns are recurrently raised that micro- and nanoplastics act as vector for organic contaminants to deeper soil layers and endanger groundwater resources. Whether and to what extent micro- and nanoplastics facilitate the transport of organic contaminants in soil remains unclear. Here we calculated the ratio between transport and desorption time scales using two diffusion models for micro- and nanoplastics between 100 nm and 1 mm. To identify micro- and nanoplastics bound contaminant transport we evaluated diffusion and partitioning coefficients of prominent agrochemicals and additives and of frequently used polymers e.g., polyethylene and tire material. Our findings suggest that the desorption of most organic contaminants is too fast for micro- and nanoplastics to act as transport facilitators in soil. Contaminant transport enabled by microplastics was found to be relevant only for very hydrophobic contaminants (logKow >5) under preferential flow conditions. While micro- and nanoplastics might be a source of potentially harmful contaminants in farmland soils this study suggests that they do not considerably enhance contaminant mobility.

Heavy metals in motorway adjoined aqueous environments have increased at an alarming rate over recent years. This increase has been primarily attributed to anthropogenic activities such as the increase of motor vehicle use. Current remediation techniques, such as balancing ponds have the potential to leave toxic residue with the associated removal costs often proving prohibitive. In this study biochar and wood ash amended biochar were evaluated as remediators of inorganic vehicular pollutants found in motorway runoff, specifically Pb, Cu, Zn and Cd. Biochar from European larch (Larix decidua (L.) Karst.) was produced via fast pyrolysis-gasification (485–530 °C for 90 s) and amended with wood ash post pyrolysis. Pristine larch biochar (BC), larch biochar cold mixed with wood ash (WA) and larch biochar sintered with wood ash (WAS) were studied to evaluate metal immobilisation mechanisms and maximum removal capacities. This study demonstrates that the amendment of biochar with wood ash increases Pb, Cu, Zn, and Cd immobilisation by an order of magnitude compared to BC. The addition of wood ash increases pH whilst adding minerals causing precipitation. Precipitation and ion exchange dominate metal immobilisation and were not correlated to surface area. Sustainability of feedstock, low feedstock/production costs and maximum measured contaminant removal (61.5 mg/g, 38.9 mg/g, 12.1 mg/g and 10.2 mg/g for Pb, Cu, Zn and Cd respectively) indicate that wood ash amended biochar is a viable option to immobilise Pb, Cu, Zn and Cd from motorway runoff.