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Cranfield University Qualtrics

CatchIS (Catchment Information System) is a software decision support system developed by Cranfield University for the management of water quality at the catchment scale.  Currently, CatchIS is offered in two basic configurations; firstly as a software application and tool embedded in ArcGIS (providing the greatest flexibility), and secondly as a bureau service supplying risk assessment reports operated for you by Cranfield (offering the greatest ease of adoption).

The following survey is designed to gauge potential interest in a third configuration, as a set of web based tools and services for pesticide risk in drinking water for England and Wales.  The web based tools and data would be based on the CatchIS tools/models and ADAS data sets.

One of the datasets the tools use is provided by ADAS and is a forecast of pesticide usage and landuse characteristics on a catchment basis over the coming year, updated bi-annually with a spatial grid resolution of 1km x 1km on the ground.

For further information on CatchIS Tools see

For further information on ADAS data

CatchIS overview

An environmental management information system for catchment managers

CatchIS is a predictive software product aimed at assisting catchment managers and others such as water companies take well-informed strategic and operational business decisions for cost-effective resource management and investment planning.

CatchIS provides comprehensive risk assessments of pollution of river and groundwater potable sources from diffuse agricultural contaminants such as pesticides and nitrates With dense populations and competing land uses, the interaction of land and water is increasingly important and is recognised in UK and European laws through the integrated catchment management requirements of the Water Framework Directive. The ability to manage such complex relationships at the river catchment level is a key aim of CatchIS, which provides a set of powerful tools to address this problem.

CatchIS has extensive datasets on soil conditions, climatic conditions, land use, pesticide characteristics and application. Placing all these datasets within a simulation model allows CatchIS users to develop a clear picture of the effects of current practices by land-based industries, and to evaluate the likely impact of alternative strategies for land and water resource management. These alternatives can be taken to the farming community as ‘best practice’. Many farmers have already adopted ‘voluntary initiatives’ to promote sustainable use of agrochemicals because of this advice.
Based on more than 20 years of research and development by Cranfield University, CatchIS version 6.3 offers powerful:

  • Environmental impact assessment
  • Scenario-based decision support tools
  • ‘Snap-in’ contaminant fate and behaviour models

CatchIS is developed within the industry-standard GIS tool ‘ArcView’ ™ software, working either on standalone or networked PCs. CatchIS has the following easy to use features:

  • Strong mouse-driven user interface (for selecting study areas, models and data)
  • Topographical vector and raster locational data
  • The new Cranfield University ‘Natmap’ GIS soils database
  • Visual reports and plots and tabular statistical reports
  • Modular structure – CatchIS holds a range of risk assessment models

Cranfield University’s unique datasets allow CatchIS to be calibrated to operate within any part of the country. CatchIS works by firstly allowing a study area to be selected from a list, or identified directly from the map.

The sorts of study areas that can be used include:

  • Surface and groundwater catchments;
  • Administrative areas, such as Postcodes, Local authorities and Health authorities;
  • Water abstraction sites;
  • Sensitive environments or user-defined zones.

CatchIS users can associate with each of these areas files holding data relating to that feature, e.g. time-series data relating to water yield and quality associated with individual water abstraction points.

CatchIS also holds a broad range of digital data defining local environmental conditions that can affect water quality. These include:

  • Climate and weather patterns;
  • Land use and cropping patterns,
  • Pesticide usage and soil and
  • Hydrogeological characteristics.