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GISAREG--A GIS based irrigation scheduling simulation model to support improved water use Export

Agricultural Water Management In Special Issue on Land and Water Use: Environmental Management Tools and Practices, Vol. 77, No. 1-3. (22 August 2005), pp. 159-179.

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geography gis irrigation resourcemanagement water wateruse

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To support improved irrigation scheduling in the Syr Darya basin, Uzbekistan, the ISAREG model was selected due to previous applications in similar climates. It is a conceptual non-distributed water balance model for simulating crop irrigation schedules at field level and to compute irrigation requirements under optimal and/or water stressed conditions. To provide for the use of the model at the project scale, a new version of the model, integrated with a Geographical Information System (GIS), was developed. This GIS based application is aimed at supporting the implementation of improved farm irrigation management and, in a later phase, to also help project management. The integration concerns the creation of spatial and weather GIS databases usable by ISAREG, the models operation for different water management scenarios, and the production of crop irrigation maps and time dependent irrigation depths at selected aggregation modes, including the farm scale. The resulting information on alternative irrigation schedules is, therefore, spatially distributed and shall be used both to support irrigation scheduling advising and to help in the identification of practices that may lead to water saving and provide for salinity control. The paper includes brief descriptions of the models, the databases and the integration of the models, as well as main features of the GISAREG application. Results relative to the comparative analysis of irrigation scheduling scenarios show the capabilities of the model to support the selection of water saving alternatives. The appropriateness of implementing 15-20-day time intervals between irrigations is shown. In addition, results relative to compare net irrigation requirements for wet and dry years show the usefulness of the model in handling time series of weather data.


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