## 4 Antibiotic Fate Models
Compared to 1D models, 2D/3D water quality models may better describe the fate, interactions, mixing, and transport of antibiotics within water bodies (e.g., reservoirs and lakes). In each model, hydrology can be characterized in two ways: gridded approaches incorporating extensive process-based hydrological models, or segmenting the river network into discreet river segments with calibration against measured hydrologic data and exploration to ungauged sites [95]. Both approaches have different data requirements, processing efforts, and computational efficiency. In addition to using different hydrological characterization, probabilistic simulations are applied to account for temporal variability of concentration caused by flow variabilities. The probability distribution depicts the expected change in concentrations over time due to discharge fluctuations and uncertainty in the input parameter. Moreover, the model coupling is a common practice in antibiotic transport simulation. Often models employ coupling of external hydrological, hydrodynamic, and fate emission models. The coupling is expected to increase the integrity of the model, save the time spent on developing the external coupler model, and allow for a better prediction [24]. Moreover, the simulation of antibiotics from a process-based reactive transport model is dependent on the instream reaction kinetics [65; 63; 96]. Therefore, modeling the fate of antibiotics in a river must represent the possible processes affecting the persistence of the antibiotics. However, the physical representation of the transport process has dynamic, distinct, and complex properties, making developing a precise quantification mechanism a tough job. Ease of complexity in the expression of transport kinetics and parameter dependencies is possible through user customization flexibility in the models. A hybrid modeling framework that combines laboratory kinetic results with numerical modeling may help better understand the instream removal reactions effectively [24]. Therefore, the validity of the simulated concentration of antibiotics from these hybrid models can be assessed by correlating the simulated concentration with actual field monitoring data [17; 97]. Validated prediction from the models is used for risk characterization to estimate the likelihood of the adverse effect due to exposure to predicted concentration. Generally, the assessment and monitoring practice of antibiotic contamination in the environment requires selecting an appropriate fate model, parameter estimation, spatial resolution, emission, and fate estimation mechanism. The selection of a suitable model requires consideration of various factors depending on the level and purpose of the assessment. For instance, onsite wastewater treatment and direct discharge are not considered in some models. In most cases, antibiotic fate models have a stationary emission calculation and fail to consider the bypass flow from the WWTP. On the other hand, different models consider different instream decay mechanisms differently and have different parameter estimations. More notably, most of the models use spatially coarse-resolution river flow data. Hence, because different models use river flow data with varying resolutions, flow computation in the models would introduce significant prediction uncertainties. A detailed review of the base formulation, applicability, and ease of use of commonly used antibiotic fate models is presented in the following section. The selected models focus on local, regional, and global antibiotic fate modeling. However, fate and transport models that have not been developed explicitly for antibiotics but have direct applications are included. The models are chosen based on their popularity and use in various regions (e.g., Asia, Europe, and North America).