The Agriculture Water Demand Model is based on a Geographic Information System (GIS) database that contains information on cropping, irrigation system type, soil texture and climate data. An explanation of how information was compiled for each is given below.

The survey area included all properties within the ALR and areas that were zoned for agriculture by the local government. The inventory was undertaken by Ministry of Agriculture (AGRI) staff, hired professional contractors and summer students. Figure 2 provides a schematic of the map sheets that were generated to conduct the survey.

Cadastre

Cadastre information was provided by the Regional District of Nanaimo (RDN). The entire regional district is covered in one dataset which allows the Model to report out on each sub-basin, local government, water purveyor or groundwater aquifer.

A GIS technician used aerial photographs to conduct an initial review of cropping information by cadastre, and divided the cadastre into polygons that separated farmstead and driveways from cropping areas.

Different crops were also separated into different polygons if the difference could be identified on the aerial photographs. This data was entered into the database that was used by the field teams to conduct and complete the land use survey.

Land Use Survey

The survey maps and database were created by AGRI for the survey crew to enter data about each property. Surveys were done during the summer of 2012. The survey crew drove by each property where the team checked the database for accuracy using visual observation and the aerial photographs on the survey maps.

A Professional Agrologist verified what was on the site and a GIS technician altered the codes in the database as necessary (Figure 3). Corrections were handwritten on the maps. The map sheets were then brought back to the office to have the hand- drawn lines digitized into the GIS system and have the additional polygons entered into the database.

Once acquired through the survey, the land use data was brought into the GIS to facilitate analysis and produce maps. Digital data, in the form of a database and GIS shape files (for maps), is available upon request through a data sharing agreement with the Ministry of Agriculture.

Figure 4 provides an example of a map sheet from the RDN. The region was divided into 107 map sheets. Each map sheet also had a key map to indicate where it was located in the region.

The smallest unit for which water use is calculated are the polygons within each cadastre. A polygon is determined by a change in land use or irrigation system within a cadastre. Polygons are designated as blue lines within each cadastre as shown in Figures 4 and 5.

The dataset for RDN encompasses 5,632 inventoried land parcels that are in or partially in the ALR. There are a total of 17,060 polygons generated within these land parcels.

Figure 5 provides an enhanced view of a cadastre containing three polygons. Each cadastre has a unique identifier as does each polygon. The polygon identifier is acknowledged by PolygonID.

This allows the survey team to call up the cadastre in the database, review the number of polygons within the cadastre and ensure the land use is coded accurately for each polygon.

Soil Information

Soil information was obtained digitally from the Ministry of Environment’s Terrain and Soils Information System. The Computer Assisted Planning and Map Production application (CAPAMP) provided detailed (1:20,000 scale) soil surveys that were conducted in the Lower Mainland, on Southeast Vancouver Island, and in the Okanagan-Similkameen areas during the early 1980s. Products developed include soil survey reports, maps, agriculture capability and other related themes.

Soil information required for this project was the soil texture (loam, etc.), the available water storage capacity and the peak infiltration rate for each texture type. The intersection of soil boundaries with the cadastre and land use polygons creates additional polygons that the Model uses to calculate water demand.

Figure 6 shows how the land use information is divided into additional polygons using the soil boundaries. The Model calculates water demand using every different combination of crop, soil and irrigation system as identified by each polygon.

Climate Information

The agricultural water demand is calculated using climate, crop, irrigation system and soil information data. To incorporate the climatic diversity, climate layers were developed for the entire region on a 500 m x 500 m grid. Each grid cell contains daily climate data, minimum and maximum temperature (T_min and T_max), and precipitation which allows the Model to calculate a daily reference evapotranspiration rate (ET_o) value.

A range of agro-climatic indices such as growing degree days (GDD), corn heat units (CHU), frost free days and temperature sum (T_sum) can also be calculated for each grid cell based on temperature data. These values are used to determine seeding dates and the length of the growing season in the Model.

The climate dataset has been developed by using existing data from climate stations in and around RDN from 1961 to 2003. This climate data set was then interpolated to provide a climate data layer for the entire watershed on the 500 m x 500 m grid. A detailed description of the Model can be obtained by contacting the authors.

Some of the existing climate stations that were used to determine the climate coverage are shown in Figure 7. The attributes attached to each climate grid cell include:

• Latitude
• Longitude
• Elevation
• Aspect
• Slope
• Daily Precipitation
• Daily T_max and T_min

The climate database generated contains T_min, T_max, T_mean and Precipitation for each day of the year from 1961 to 2003. The parameters that need to be selected, calculated and stored within the Model are evapotranspiration (ET_o), T_sum of 1,000 (for the Island), effective precipitation (EP), frost free days, GDD with base temperatures of 5 ^oC and 10 ^oC, CHU, and first frost date. These climate and crop parameters are used to determine the growing season length as well as the beginning and end of the growing season in Julian day.

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