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Spatial Decision Support System: Controlled Tile Drainage – Calculate Your Benefits
1G. Kaur, 1A. Kross, 1D. Callegari, 2M. Sunohara, 3L. van Vliet, 3H. Rudy, 2D. Lapen, 2H. McNairn
1. Department of Geography, Planning and environment, Concordia University, Montreal, QC
2. Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
3. Research and Business development, Ontario Soil and Crop Improvement Association, Guelph, ON, Canada

Climate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water from their fields, which allows producers to maintain soil water on their fields during periods of crop demand or allows free drainage to facilitate field trafficking and earlier spring seeding. The result is a dampening of the negative impact of extreme events on crop yields. In this study, a spatial decision support system was developed that will 1) allow farmers and other stakeholders to explore potential sites for implementation of tile drainage systems; 2) show predicted yield benefits of crops (corn and soybean) from CTD fields compared to crops associated with uncontrolled tile drainage (UCTD) systems, during varying growing season precipitation. A Multi-Criteria Suitability Analysis was performed to determine potential sites for the implementation of tile drainage systems. Crop yield was characterized by ground yield measurements and satellite-derived  Normalized Difference Vegetation Index (NDVI). Yield benefits from CTD fields were determined as the difference between ground yield measurements or NDVI values from CTD compared to UCTD fields. Yield benefits were finally related to precipitation data to enable the creation of yield benefit prediction scenarios under varying precipitation. The results of the suitability analysis and yield difference prediction were combined in the tool, along with additional slope, soil drainage and precipitation layers. The tool development is ongoing and functional on https://demo.gatewaygeomatics.com/ctd/.

Keyword: Controlled Tile Drainage, Uncontrolled Tile Drainage, Climate change, corn, soybean, yield, remote sensing, NDVI, Multi-Criteria Suitability Analysis, Spatial Decision Support Tool
G. Kaur    A. Kross    D. Callegari    M. Sunohara    L. Van vliet    H. Rudy    D. Lapen    H. Mcnairn    Decision Support Systems    Poster    2018