USING THE IRRISAT APP TO IMPROVE ON-FARM WATER MANAGEMENT

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1 USING THE IRRISAT APP TO IMPROVE ON-FARM WATER MANAGEMENT John Hornbuckle 1, Janelle Montgomery 2, Jamie Vleeshouwer 3, Robert Hoogers 4 Carlos Ballester 1 1 Centre for Regional and Rural Futures, Deakin University, Research Station Rd, Griffith, NSW, 2680, 2 NSW DPI, PO Box 209, Moree, NSW, Land & Water Flagship: CSIRO, 41 Boggo Road, Dutton Park, QLD, NSW DPI, PMB, Yanco, NSW, , , j.hornbuckle@deakin.edu.au ABSTRACT IrriSAT is a cloud based app using the Google Earth Engine to provide irrigation management and benchmarking information from remote sensing technologies across large spatial scales. The IrriSAT app automates satellite processing and information delivery of satellite data and provides irrigators with water management information across a range of scales to assist in irrigation scheduling and crop productivity benchmarking. Spatial crop water use information determined by IrriSAT allows users to investigate water use differences within and between fields. Identifying over/under performing fields holds the key to improving water productivity. IrriSAT allow irrigators to make better informed water management decisions. INTRODUCTION Water availability is becoming the most limiting factor of crop production in semi-arid areas where rainfall does not cover the crop water requirements during most part of the seasons. During the last decade there has been a notable effort aimed to optimize water management in agriculture in order to improve water use efficiency and produce more crop per drop. Nowadays, as example, most of the farmers use soil moisture sensors to schedule irrigation based on the soil water content information, which to some extent has improved the on-farm water use efficiency. A proper irrigation scheduling adjusted to the actual crop water requirements is crucial to better use the available water resources. Weather based scheduling techniques have not been widely adopted in the irrigation industry due to the problem of determining site specific crop coefficients (Kc). With the use of the new remote sensing tools available and technology as IrriSAT, this issue can be overcome providing a great opportunity to have a notable impact on the efficiency with which producers used the water. IrriSAT is a weather based irrigation management and benchmarking technology that uses remote sensing to provide site specific crop water management information across large spatial scales (Hornbuckle et al. 2009). IrriSAT calculates Kc from relationships with satellite (Landsat

2 and Sentinel) derived Normalised Difference Vegetation Index (NDVI) data. Daily crop water use is determined by multiplying Kc and daily reference evapotranspiration (ETo) observations from a nearby weather station or ETo grid surfaces. A seven day forecast of ETo can also be used with the satellite data to produce a seven day forecast of crop water use. IrriSAT is moving weather-based scheduling into the future with a delivery platform being developed using the Google App Engine. A beta version of the cloud based app is currently available at IrriSAT APPROACH IrriSat integrates two sources of information, satellite imagery (to calculate NDVI and Kc) and ETo obtained from on-ground weather stations to estimate the crop water use (ETc) using the equation showed in figure 1. The crop coefficient is used to adjust the ETo for a specific crop type, where crop height, albedo, canopy resistance and bare soil evaporation is integrated into a single parameter specific to that crop type. Figure 1 shows a diagram of the process of how IrriSAT is used and information sources combined to deliver crop water use information. Figure 1: Overview of information feeds (satellite + on-ground) and delivery of information through an online app.

3 Satellite measurements Remote sensing of the crop is undertaken using the Landsat and Sentinel satellite platforms. These satellite platforms have been used because they are free and have the spectral (red and near-infrared), spatial (30m and 10m pixels respectively) and temporal (8-16 days and 5-10 days respectively) resolutions appropriate for IrriSAT. A number of authors (Trout and Johnson, 2007) have found strong relationships between NDVI and crop canopy cover for various crops in semi-arid areas. Since transpiration is proportional to crop cover it is reasonable to relate the NDVI to a Kc value. This approach allows NDVI values to be converted and hence produce a Kc map across the satellite image which is the approach used in IrriSAT. On ground climate measurements ETo is calculated from observations from a network of automatic weather stations installed across most cotton regions. ETo calculations are based on the ASCE Standard reference evapotranspiration equation as detailed in Allen et al. (2005). IrriSAT also allows the option to use gridded ETo surfaces and uses the SILO (Scientific Information for Landowners Jeffrey et al. 2001) gridded ETo data to provide ETo coverage across Australia. In the US IrriSAT makes use of the GridMET data provided by the University of Idaho Additionally, IrriSAT incorporates a 7 day global ETo forecast using parameters from which allows a seven day crop water use to be estimated to assist in planning irrigation activities (Figure 2).

4 Figure 2 Seven day forecasted crop water use derived from Forecast IO and satellite data IrriSAT CLOUD BASED APP An app is being developed to deliver information generated using the IrriSAT approach to any web enabled platform including smart phones, tablets and desktops. A beta version of the app is currently available at developed using Google App Engine (Vleeshouwer et al. 2014). Fields are added as polygons drawn by users who must also input the timing and quantity of irrigation and rainfall to drive a daily water balance model. Currently the IrriSAT app displays NDVI and Kc as surfaces (Figure 3). Time series of field averages of these data can be calculated and downloaded for further analysis or shared with a consultant or third party by allowing them access to the cloud based data.

5 Figure 3 Daily crop water use information for whole field and spatial variability in crop water use being shown in the IrriSAT app cloud based interface FUTURE DEVELOPMENTS Modifications to the IrriSAT interface are currently being undertaken to make the tool more user friendly and suitable for use in both a benchmarking and real-time use perspective. These include simple to use interfaces designed from irrigator feedback. Additionally, the integration of drone based remote sensing data and on-ground IoT (Internet of Things) data from point source measurements such as soil moisture and there seamless incorporation into IrriSAT are being developed and hope to be available in the future. SUMMARY The IrriSAT app provides easy access to IrriSAT crop water use data, which coupled with weather and ETc forecasts, will enable irrigators to track their soil moisture deficit and better manage irrigation schedules. Spatial crop water use information determined by IrriSAT will allow users to investigate water use differences within and between fields. IrriSAT will complement existing irrigation scheduling tools with the advantage of low cost and complete spatial coverage. Preliminary trials of the IrriSAT technology as a benchmarking tool have enabled irrigators to examine variation in crop productivity between fields and farms. Identifying over-and underperforming fields holds the key to improving water productivity.

6 References Allen, RG, Walter, IA, Elliot, RL, Howell, TA, Itenfisu, D, Jensen, ME & Snyder, RL 2005, ASCE Standardized Reference Evapotranspiration Equation, American Society of Civil Engineers. Hornbuckle, J, Car, NJ, Christen, EW, Stein TM & Williamson, B 2009, IrriSatSMS Irrigation water management by satellite and SMS A utilisation framework, CSIRO and CRC for Irrigation Futures, CSIRO Land and Water Science Report No 04/09. Jeffrey, S.J., Carter, J.O., Moodie, K.B. and Beswick, A.R. (2001). Using spatial interpolation to construct a comprehensive archive of Australian climate data External link icon, Environmental Modelling and Software, Vol 16/4, pp DOI: /S (01) Trout, TJ & Johnson, LF 2007, Estimating crop water use from remotely sensed NDVI, Crop Models and Reference ET, USCID Fourth International Conference on Irrigation and Drainage, The Role of Irrigation and Drainage in a sustainable Future, Eds. Clemmens, A.J., Anderson, S.S., Sacramento, California, October 3-6, Vleeshouwer, J, Car, N & Hornbuckle, J 2014, A cotton grower s decision support system and benchmarking tool using national, regional and local data, paper presented at the ISEE Conference, March 2015, Melbourne.