C1.3 Modelling in IWRM
Modelling and Decision Support Systems (DSS) are complementary tools. A model is a simplified description of a system to assist calculations and predictions. A Decision Support System is a means of collecting data from many sources to inform a decision. Information can include experimental or survey data, output from models and expert or local knowledge.
Modelling at the sub-catchment or river basin level can integrate the hydrological, technical, ecological, environmental, economic, social, institutional and legal aspects of water problems into a coherent framework. Hydrological models simulating water balance elements (such as river run-off, groundwater and evapotranspiration) are quite well developed, as are water quality models for rivers, groundwater and lakes. However, models for most other aspects of water (ecological, environmental, economic, social, institutional and legal) need significant improvement (see C1.5).
At the river basin level, GIS-based modelling techniques can allow policy makers and managers to test “what if” scenarios, on topics such as integrated water quantity, water quality and environmental regulation, the impacts of land use changes on flow regimes, climate change effects on flood and drought frequency / severity, inter-sectoral water allocation policies, effects of uncertainty and risks on water resources management and the impacts of economic incentives for pollution control, water conservation and more efficient irrigation (see also C8.1).
A multi-objective DSS (MODSS) allows users to integrate data in five phases, each requiring consultation with all potential stakeholders:
Today, the output of many models is available and accessible on the Internet to any user with a personal computer and the necessary software. Easy access to the output of other models can greatly assist managers in developing their own DSS. There is keen competition among research institutions, universities and consultants to provide modelling products, the price of which is small relative to the time required to learn to use the models effectively. Users of models should be confident that they have access to relevant expertise to provide guidance in the application of these tools, and ensure that appropriate delivery methods have been worked out.