Runoff is analyzed by using mathematical models in combination with various water quality sampling methods. Measurements can be made using continuous automated water quality analysis instruments targeted on pollutants such as specific organic or inorganic chemicals, pH, turbidity etc. or targeted on secondary indicators such as dissolved oxygen. Measurements can also be made in batch form by extracting a single water sample and conducting any number of chemical or physical tests on that sample.
In the 1950s or earlier hydrology transport models appeared to calculate quantities of runoff, primarily for flood forecasting. Beginning in the early 1970s computer models were developed to analyze the transport of runoff carrying water pollutants, which considered dissolution rates of various chemicals, infiltration into soils and ultimate pollutant load delivered to receiving waters.
One of the earliest models addressing chemical dissolution in runoff and resulting transport was developed in the early 1970s under contract to the United States Environmental Protection Agency (EPA).  This computer model formed the basis of much of the mitigation study that led to strategies for land use and chemical handling controls.
Increasingly, stormwater practitioners have recognized the need for Monte Carlo models to simulate stormwater processes because of natural variations in multiple variables that affect the quality and quantity of runoff. The benefit of the Monte Carlo analysis is not to decrease uncertainty in the input statistics, but to represent the different combinations of the variables that determine potential risks of water-quality excursions. One example of this type of stormwater model is the stochastic empirical loading and dilution model (SELDM) is a stormwater quality model. SELDM is designed to transform complex scientific data into meaningful information about the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks. SELDM provides a method for rapid assessment of information that is otherwise difficult or impossible to obtain because it models the interactions among hydrologic variables (with different probability distributions) that result in a population of values that represent likely long-term outcomes from runoff processes and the potential effects of different mitigation measures. SELDM also provides the means for rapidly doing sensitivity analyses to determine the potential effects of different input assumptions on the risks for water-quality excursions.
Other computer models have been developed (such as the DSSAM Model) that allow surface runoff to be tracked through a river course as reactive water pollutants. In this case the surface runoff may be considered to be a line source of water pollution to the receiving waters.