Deterministic models are not a type of water quality model. Water quality models are typically classified into empirical, mechanistic, stochastic, and hybrid models.

Water quality models are used for a variety of purposes, including predicting future water quality conditions, identifying sources of pollution, and developing water quality management strategies.

Distributed parameter models are often used to represent complex water quality processes because they can account for spatial variations in water quality.

Empirical water quality models are relatively easy to develop and apply, making them a popular choice for modeling water quality.

Designing water quality monitoring programs is not a common application of water quality models. Water quality models are typically used for assessing the impact of land use changes on water quality, developing TMDLs, and predicting the fate and transport of contaminants.

Mechanistic water quality models are often difficult to develop and apply due to the complexity of the processes they represent.

Model parameters are not typically considered inputs to a water quality model. Land use data, meteorological data, and water quality data are common types of inputs.

Stochastic water quality models can be used to predict future water quality conditions under uncertainty, which is a major advantage over deterministic models.

Model parameters are not typically considered outputs of a water quality model. Water quality concentrations, flow rates, and sediment transport rates are common types of outputs.

Hybrid water quality models can be difficult to develop and apply due to the complexity of the processes they represent.

Data assimilation is not a common type of water quality model calibration. Manual calibration, automatic calibration, and semi-automatic calibration are common types of calibration.

Water quality model validation is used to assess the accuracy and reliability of the model, identify sources of error in the model, and improve the model's performance.

Parameter estimation is not a common type of water quality model sensitivity analysis. Local sensitivity analysis, global sensitivity analysis, and uncertainty analysis are common types of sensitivity analysis.

Water quality models can be difficult to communicate to decision-makers, which can make it challenging to use them for decision-making.

Designing water quality monitoring programs is not a common type of water quality model application. Water quality models are typically used for assessing the impact of land use changes on water quality, developing TMDLs, and predicting the impact of climate change on water quality.