Irrigation Scheduling & Meteorology

CanePro utilizes a simulated water balance approach to irrigation scheduling. A multi-layered soil water balance is combined with a well validated sugarcane-specific version of the Penman-Monteith equation. Crop development is calculated using a thermal time-driven canopy development model, and water stress feedback on both crop development and photosynthesis is dealt with in the model. Simulated soil water content can be manually adjusted in response to field inspection or direct soil water measurement, effectively overriding the modeled balance.

Fields are linked to user-defined rain gauges, weather stations and irrigation system types, used to define water supply constraints. Actual data (irrigation events and rainfall) are captured through CanePro’s easy-to-use calendar interface.

An extensive graphical interface allows the user to analyse the water balance and components of growth and development in detail. CanePro schedules future irrigation events, and water requirements can be rolled up to higher levels allowing the user to generate estate-wide water orders.

Numerous reports allow the user to evaluate the management of individual fields, or higher-level management units. CanePro’s integrated GIS tools allows the user to view current stress levels and prioritize fields with regard to current moisture status.

Key Features

Sugarcane specific energy balance

Schedule future irrigation events

Override simulated water balance to match in-field inspection

CanePro’s Meteorological module is the source of data for other climate-driven modules such as the irrigation scheduling and yield forecasting modules.

The module’s primary aim is to be a store of meteorological data from multiple sites, both manual and automatic. Manual data is entered through CanePro’s input screen. Data checks ensure that only valid combinations of data are captured. Automatic stations are usually queried directly from the site by the SQL Server database engine, eliminating the need for manual capture. Hourly data is stored in the database from automatic sites and a daily record computed from hourly values.

Graphical reports allow for meaningful comparisons between sites, and trend analysis enables the user to interpret long-term trends and changes in climate. Tabular reports ensure that standard reporting requirements are met.