Remote sensing in FIGARO

Transcription

1 FIGARO FLEXIBLE AND PRECISE IRRIGATION PLATFORM TO IMPROVE FARM SCALE WATER PRODUCTIVITY Remote sensing in FIGARO Final Meeting, Brussels 19/09/2016 Technical University of Valencia

2 Use of Remote sensing in irrigation management Calcultation of Crop Water Requirements (CWR) Estimation crop coefficients (k c ) from remotely sensed vegetation indices (VI) Surface energy balance methods (SEB) Crop monitoring Crop mapping Physiologycal parameters (Leaf Area Index, Biomass, GroundCover ) Irrigation assesment (Seasonal Irrigation Performance Index) Crop water stress detection Crop Water Stress Index (CWSI Temperature) Photochemical Reflectance Index (PRI) Water Deficit Index (WDI)

3 Remote sensing in FIGARO Calcultation of CropWater Requirements (CWR) Estimation crop coefficients (k c ) from remotely sensed vegetation indices (VI) ; ; ; Ground cover is the physiologic parameterused by Aquacrop Crop Kcb Parameter Reference Vine (wine) Kc = 1.44*NDVI 0.10 Kc = 1.79*SAVI 0.08 NDVI;SAVI Campos et al 2010 Vine(Table grape) Kc = *GC GC(%) Williams et al(2005) Citrus Kc= ( *GC) ( *GC 2 ) GC(%) Castel (2000) Potato Kc = SAVI SAVI Jayanthi et al (2007) Cotton Kc = 1.49 NDVI 0.12 (early vegetative) Kc=2.80 NDVI 1.17 (After full cover) NDVI Hunsaker et al (2003) Corn (Irrigated) Y = NDVI NDVI Singh and Imak (2009) Processing Tomato Kc = (0.0172)*GC GC(%) Hanson and May ( *GC 2) (2006)

4 Remote sensing in FIGARO Calcultation of CropWater Requirements (CWR) Estimation crop basal coefficients (k c ) from remotely sensed vegetation indices (VI) Advantages Only few bands are required (visible and NIR) Easy computation Drawbacks Empirical formulas are calculated with local data To use specific k c a crop map is required No vegetation stress is detected Spatial resolution can not be accurate enough to calculate parameters as ground cover for discontinuous canopies NDVI map Valencia region

5 RS inputs in crop models Fao model Remote sensing in FIGARO Ground cover Kc avg = ( x GC) ( x GC 2 ) Ground cover is related with Kc Estimates ET without crop water restriction Agroclimatic stations Crop Coefficient Crop water requirements (CWR) Irrrigation scheduling Irrrigation assessment Water registered (V) Seasonal Irrigation Performance Index SIPI=CWR/V

6 Remote sensing in FIGARO Seasonal Irrigation Performance Index. Picassent irrigation district SIPI=CWR/V SIPI 2014 SIPI 2015

7 USed Used imagery Remote sensing in FIGARO PNOA (National Plan of Aerial Ortophoto, Spain) Radiometric resolution: R, G, B, IR Spatial resolution: 0.25 m Temporal resolution: 2 years Data sets avalaible: (July) Rapid eye Radiometric resolution Spatial resolution: 5 m Temporal resolution: 1 5 days

8 Remote sensing in FIGARO Used imagery Sentinel 2 (Images avaliable from January 2016) 10 m spatial resolution bands 60 m spatial resolution bands Band number Central wavelength (nm) Bandwidth (nm) Band number Central wavelength (nm) Bandwidth (nm) (NIR) m spatial resolution bands Band number Central wavelength (nm) Bandwidth (nm) 10 m a 865 (NIR) Sentinel 2 10 m

9 Remote sensing in FIGARO Use of different spatial resolution images Ortophoto high spatial resolution, low temporal resolution. Obtained from simultanous images in july 2012 RapidEye medium spatial resolution, high temporal resolutionresolution.

10 Use of Remote sensing in irrigation management Calcultation of CropWater Requirements (CWR) Surface energy balance method (SEB) A model that calculates the latent heat (ET), as a residual of the surface energy balance. Sensible heat (H) is calculated using the radiometric surface temperature obtained from the thermal band imagery (Bastiaanssen et al 2002)

11 Use of Remote sensing in irrigation management Calcultation of CropWater Requirements (CWR) Surface energy blance methods (SEB) Advantages Actual evapotranspiration is calculated Vegetation stress can be detected Drawbacks Thermal band needed ET instantaneous has to be extrapolated. Platform sensors has a coarse spatial resolution for thermal band (Landsat 8, 30 m) ET map calculated by SEBAL

12 Spanish case study (citrus) Remote sensing in FIGARO Landsat images were used: Temporal resolution: 16 days Two scenes overlap on the citrus pilot site ( and ) Images avalaible each 7 and 9 days 2013: 13 avalaible images out of : 14 avalaible images out of : 20 avalaible images out of 28 year 2014

13 Irrigation procedure Citrus test site Each time a Landsat 8 image free of clouds is avalaible, actual ET is estimated and downscaled to daily values. ET FAO Vol 1 > 1, it is assumed that crop is irrigated less than required ET FAO Vol 1 < 1, it is assumed that crop is irrigated more than required ET SEBAL ET 1 FAO > 1, actual ET is higher than potential ET SEBA L ET 1 FAO < 1,actual ET is lower than potential Flexible and precise irrigation platform to improve farm scale water productivity Slide13

14 Irrigation procedure Citrus test site 22 plots were selected (0,3 3,5 ha) Flexible and precise irrigation platform to improve farm scale water productivity Slide14

15 Remote sensing in FIGARO SEBAL is a methodology that can be used for irrigation scheduling at irrigation district level It is able to detect those plots that suffer water stress due to it estimates the actual evapotrasnpiration instead of potential evapotrasnpiration Along with models based on the vegetation indices (Castel, 2000) and volume readings, it allows perform water stress maps for large areas The disadvantges are the cloudy days and the small spatial resolution by now

16 Remote sensing in FIGARO Architecture U Manage

17 Landsat 8 Sentinel 2 Landsat 7 Spot 6 Rapid Eye Deimos Spot 7 III Jornada sobre Gestión Eficiente del Agua de Riego 17