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Data for Irrigation Modelling Hector M Malano

This outline discusses the processes involved in irrigation modelling and highlights the data gaps that need to be addressed. It includes topics such as water allocation, allocation policy changes, crop mix, evapotranspiration, soil moisture, soil salinity, soil permeability, and channel seepage.

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Data for Irrigation Modelling Hector M Malano

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  1. Data for Irrigation ModellingHector M Malano

  2. Outline • Modelling: what processes? • What data gaps are there? • Frequency of collection • Level of disaggregation

  3. Processes(1)? • Water allocation (system & catchment level) • Assessment of allocation policy changes, e.g. env flows, water trading, economic impact, infrastructure planning, etc. • Data requirement: • Seasonal disaggregated crop mix (crop types) at demand centre level is a critical input for allocation modelling • Frequency: Seasonal or more frequent depending on cropping pattern (NSW more variable than Victoria) • Distributed evapotranspiration and soil moisture: Water balance modelling at farm and area levels (needs multitemporal analysis)

  4. Water application HC is a critical parameter for model parameterisationand real-time control logic Processes (2) ?

  5. Processes (3) • Soil salinity: Correlation of airborne data with soil moisture content and salinity point measurement (0-0.5 m) for use in salinity mapping (Data available for Coleambally). • Correlation of soil permeability with recharge discharge areas to predict impacts of irrigation and drainage options. • Channel Seepage: Identification of seepage zones. Correlate shallow soil saturation measurements (10-20 m) with EM surveys.

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