QUESTOR (Quality Evaluation and Simulation Tool for River Systems)

QUESTOR represents a river as a series of river reaches within which physical, chemical and biological processes operate.. The initial selection of reaches is based on the location of confluences, diffuse (catchment) sources, discharge points, abstraction points, monitoring sites, and weirs. Once this has been done, long reaches, say those greater than 10km, can be sub-divided. The flow and water quality out of a reach are calculated based on a mass balance of flows into the head of the reach plus contributions from point sources and diffuse sources minus abstractions. The determinands and processes modelled are not fixed within the QUESTOR modelling environment, but are tailored to the particular application. The QUESTOR model has sets of equations to simulates nitrogen and phosphorus species, pH and suspended sediment, the aspects of water quality of particular interest are those determinands indicative of the impacts on the river ecosystem, namely temperature, chlorophyll-a (Chl-a), BOD and DO. Chl-a is used as a surrogate for the algae using a fixed stoichiometry model whereby the ratio chl-a:C:N:P is 1:50:10:1. The growth of algae is limited by light, temperature and nutrient concentrations. The model was developed to help catchment managers assess the impact of their actions e.g. changing discharges consents, abstracting more water from a river or building a flood relief channel. The aim was to produce a physically realistic representation of a number of important measures of river water quality while being practical to run using generally available datasets.
QUESTOR is based on the earlier in-stream water quality models IHQM (Institute of Hydrology water Quality Model) and QUASAR (Quality Simulation Along Rivers). QUASAR was sold commercially for both VAX and PC systems, and is now available free of charge, but unsupported, as PC-QUASAR. The model formulation of the "basic" version of QUESTOR corresponds broadly with QUASAR.

Version CWC
Mike Hutchins, Centre for Ecology and Hydrology, Wallingford, Oxfordshire, OX10 8BB, Tel: 01491 692478, email:,
Executable is freely available. The code could be make available subject to a suitable license, but no support can be guaranteed.
Operating Requirements
Windows and Linux versions available.
Application Type
Provided as an Executable; Source code is Fortran
User Interface
Control Files, although a GUI exists of both Windows which helps the user with calibration.
Support Available
Model developer can give some very limited support.
Application Scale
Geographical Restrictions
Only tested in Temperate Climates
Temporal Resolution
Model operates at a daily time or hourly step, but can interpolate input data provided a coarser interval.
Spatial Resolution
Provides output by reach. Reach length is set by the user (typically 1000 – 5000 km depending on application and time step)
Primary Purpose
Simulate water quality in rivers especially eutrophication for scenario analysis
Key Output Variables
Stream N P species, Dissolved Oxygen, BOD, Algae (mixed species or individual), Macrophytes, Benthic Algae, Temperature
Key Input Variables
Flow and water quality data from upstream boundaries plus sewage treatment discharges and water abstractions volumes. Observed data for calibration.
Calibration Required
YES. Required optimization (manual) of model equation parameters values against observed data. Literature can provide suitable bounds to these parameters.
Model Structure
Dynamic, process-based, semi-empirical deterministic model (although there is a stochastic mode)
Model Parameterisation
Majority of key parameter values expert based or derived from observed data
Input Data Available on CaMMP Catalogue

Key References

  • Boorman DB. LOIS in-stream water quality modelling. Part 1. Catchments and methods. The Science of The Total Environment 2003; 314-316: 379-95.
  • Waylett AJ, Hutchins MG, Johnson AC, Bowes MJ, Loewenthal M. Physico-chemical factors alone cannot simulate phytoplankton behaviour in a lowland river. Journal of Hydrology 2013; 497: 223-33.
  • Hutchins MG, Williams RJ, Prudhomme C, Bowes MJ, Brown HE, Waylett AJ, Loewenthal M. Projections of future deterioration in UK river quality are hampered by climatic uncertainty under extreme conditions. Hydrological Sciences Journal 2016; 61: 2818-33.

Input Data

  • Flow data (m3/s) at daily time intervals, ASCII times series file of prescribed format
  • Calibration Data. Flow (cumecs) and Water Quality (mg/L) at locations along the river – Any time step, ASCII data in prescribed format.
  • Water Quality Data( mg/L), Daily time series (interpolated from routine data), ASCII times series file of prescribed format
  • Solar Radiation Data (W/m2), Daily values, ASCII times series file of prescribed format
  • Weirs, location (national grid reference), height (M), type (code) fixed in time

Output Data

  • Flow (m3/s) and) at all specified reach boundaries, time series (daily), ASCII files
  • Water Quality: N and P species concentrations (mg/L), Dissolved Oxygen (mg/l and % saturation), BOD (mg/L), Temperature (oC), Chlorophyl-a (mg/L), pH, Suspended sediment (mg/L), at all specified reach boundaries, time series (daily), ASCII files.

Quality Assurance

Developer Testing
Internal Peer Review
External Peer Review
Use of Version Control
Internal Model Audit
External Model Audit
Quality Assurance Guidelines and Checklists
Periodic Review