Remote sensing in irrigated onion production: Challenges & opportunities Hort Connections 2017 Adelaide Convention Centre Michael Cutting, Natural Resources SA MDB Region
Project Background: In 2004/05 an extensive automatic weather station network was established across the SA Murray-Darling Basin region Primary objective was to provide land managers with real time and location specific weather data to assist with on-farm decision making High density of stations in key irrigation areas across the region River Murray, Mallee Daily evapotranspiration data to assist with optimising irrigation scheduling
Project Background: Given the significant investment keen to promote the on-farm adoption of network data Looked into different decision support systems and tools that integrated on-ground weather data Collaborated on small scale trials of different remote sensing based systems including IrriEYE
IrriEYE: IrriEYE is an irrigation advisory service based on high resolution satellite monitoring of canopy satellite monitoring of canopy development IrriEYE provides farmers and water managers with real-time irrigation water needs from field and irrigation unit to district and river basin scale Generates crop co-efficient values that are then applied to local ETo data sourced from AWS Citrus, wine-grapes, almonds, stonefruit (2011-2013)
Remote sensing: A tool to monitor & evaluate? Since 2010 the SA MDB NRM Board has been involved as a Delivery Partner in the Australian Government funded On-Farm Irrigation Efficiency Program (OFIEP) OFIEP is a key water recovery initiative linked to the Murray- Darling Basin Plan Share of water savings generated through on-farm irrigation efficiency improvements returned to the environment What innovative ways could we evaluate on-farm improvements? before vs. after assessments
Remote sensing: A tool to monitor & evaluate? High resolution imagery (fixed wing aircraft) Water stress mapping (ambient vs. in canopy air temp) Note: Not deriving an irrigation volume
The IrriSAT system: With continuing drivers to extend weather based irrigation scheduling approaches along with monitoring and evaluation activities we started to utilise the IrriSAT system We were already familiar with the IrriSAT system from when it was developed through CRC for Irrigation Futures The IrriSAT methodology uses satellite images to determine the Normalized Difference Vegetation Index (NDVI) for each field https://irrisat-cloud.appspot.com/#
Benefits of the IrriSAT system: It is free! Just need a Gmail account Able to easily map specific patches/plots of interest IrriSAT system delivers regular satellite imagery Sentinel 2 & Landsat 7/8 Can generate a crop water balance and soil water deficit based on inputs (irrigation + rainfall) Also produces a forecast of crop water use based on crop coefficients derived from the satellite imagery
Monitoring sites in 2016/17 season: Sites were largely project based Not a formal trial of IrriSAT Value add to existing work programs Crop Types: Lucerne, perennial pasture, wine grapes, onions Irrigation Systems: Centre Pivot, Fixed Sprinklers, Border Check
Onion monitoring sites in 2016/17 season: Harvest: 28/12/16 Sites were largely project based Not a formal trial Value add to existing work Plant: 18/09/16 Harvest: 24/02/17 Onion site was chosen as farmer was using weather based approach to irrigation scheduling Collaborated with previous work (plant based) Good with feedback
Onion monitoring sites in 2016/17 season: Harvest: 28/12/16 Plant: 18/09/16 Harvest: 24/02/17 9 June 2016 Sentinel 2 satellite image (10m pixel)
Onion monitoring sites in 2016/17 season: 6 weeks Harvest: 4 28/12/16 weeks Sites were largely project based Not a formal trial Value add to existing work Plant: 18/09/16 Harvest: 24/02/17 11 July 2016 Note bottom (orange) patch not yet planted
Onion monitoring sites in 2016/17 season: Harvest: 28/12/16 Sites were largely project based Not a formal trial Value add to existing work Cloud cover Sentinel 2 excludes areas influenced Plant: 18/09/16 Harvest: 24/02/17 29 September 2016 Influence of composite images Landsat 8 (30m) & Sentinel 2 (10m) - different resolutions
Onion monitoring sites in 2016/17 season: Harvest: 28/12/16 Sites were largely project based Not a formal trial Value add to existing work Cloud cover Sentinel 2 excludes areas influenced Plant: 18/09/16 Harvest: 24/02/17 7 October 2016 Landsat 8 image only more uniformity
Onion monitoring sites in 2016/17 season: Harvest: 28/12/16 Sites were largely project based Not a formal trial Value add to existing work Cloud cover Sentinel 2 excludes areas influenced Plant: 18/09/16 Harvest: 24/02/17 31 October 2016 Crops continuing to develop > Kc value
Onion monitoring sites in 2016/17 season: Harvest: 28/12/16 Sites were largely project based Not a formal trial Value add to existing work Cloud cover Sentinel 2 excludes areas influenced Plant: 18/09/16 Harvest: 24/02/17 18 December 2016 Several beds not yet harvested Not a strong signature on late planting
Onion monitoring sites in 2016/17 season: Harvest: 28/12/16 Sites were largely project based Not a formal trial Value add to existing work Cloud cover Sentinel 2 excludes areas influenced Plant: 18/09/16 Harvest: 24/02/17 26 December 2016 NE plot harvested 04/12/16 Within crop variation visible in S plot
Onion monitoring sites in 2016/17 season: Harvest: 28/12/16 Sites were largely project based Not a formal trial Value add to existing work Cloud cover Sentinel 2 excludes areas influenced Plant: 18/09/16 Harvest: 24/02/17 17 January 2017 Persistence of low vigour - circle
Onion monitoring sites in 2016/17 season: Harvest: 28/12/16 Sites were largely project based Not a formal trial Value add to existing work Cloud cover Sentinel 2 excludes areas influenced Plant: 18/09/16 Harvest: 24/02/17 Whole of season statistics Field Visibility (%) Comparison to actual
Key observations and lessons: Can be challenges with the IrriSAT approach to onion irrigation management: - establishment with cover crop - not a bulky crop (biomass) Harvest: 28/12/16 Despite this the system provides a very visual Sites assessment were largely of project crop uniformity based assists Not a with formal troubleshooting trial Value add to existing work We did not incorporate local AWS data but SILO evapotranspiration was very similar: 924mm (SILO) vs. 981mm (local) Cloud cover Sentinel 2 excludes areas influenced Published Plant: crop 18/09/16 co-efficient data for onions suggest Harvest: 1:1 with 24/02/17 ETo ~ 9ML/ha Accurate ETo forecast = valued by farmer
thankyou