Practical modelling for management in data-limited catchments

✍ Scribed by W.R. Dawes; G.R. Walker; M. Stauffacher

• Publisher: Elsevier Science
• Year: 2001
• Tongue: English
• Weight: 846 KB
• Volume: 33
• Category: Article
• ISSN: 0895-7177
• DOI: 10.1016/s0895-7177(00)00267-3

✦ Synopsis

Drylend salinity ie an Bccelerating problem thet threatens some of Auetralii's most productive agricultural land. The problem with ueing modele for developing management options in dryland ereaa ia the general lack of data: there is no shortege of complex physical models, but we have little data with which to calibrate them. Not only la there the problem of having confidence in the equations and parameters ueed in the modele, but it ia diicult to follow the information trail that leads to the conclueione. Thie ia empheeised when the outputs of one model are used 88 inputs to another. In the cese of dryland ealiity, the catchment ie Rret broken into eo-ca&d homogeneous areas to drive a surface water balance model, which drivee a groundweter model, which ln turn driw an economics model, the reaulte of which influence managem ent de&ions. What confidence do we have in the model outputs, at any of theee stages, upon which decisions worth millions of dollam are made? This work presents an examination of field data leading from a conceptual model to a simple numerical model of groundwater flowe in the Liverpool Plains. We maintain the critical procem h&erections and derive a simple flow model, whose output can be coupled with production and economic models. The Liverpool Plains ls a National Dryland Salinity Program focus catchment. As such, there hae been more work done and more data available than for moet catchment& in Awtralla. Given a need to link physical and economic models and follow the information trails, we require conceptual and numerical models that include the critical pmcexexw and interactions, described by the simplest equations and feweat parameters. With theee models in place, we present common management ecenarloe, and draw conclusions about the current end prospective state of the system, and the modelling exercise.