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United States Department of Agriculture

Agricultural Research Service

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Research Project: IMPROVED PREDICTION OF IRRIGATION WATER USE FOR CALIFORNIA CROPS FROM REMOTE SENSING

Location: Water Management Research

2012 Annual Report


1a.Objectives (from AD-416):
The objectives are to develop technology to estimate real-time crop coefficients for fields/crops in the San Joaquin Valley from remotely-sensed data and to develop and demonstrate a prototype decision support system that can efficiently deliver crop coefficient and estimated crop water use information to agricultural producers and water suppliers.


1b.Approach (from AD-416):
Refine and validate the relationship between crop canopy cover (fc) and remotely sensed NDVI. Use ground based multispectral camera to measure fc for a wide range of crops grown in the San Joaquin Valley and compare the fc values with NDVI values derived from both aerial and satellite (Landsat and Modis) multispectral images for the fields.

Conversion of fc to basal crop coefficient, Kcb. Collect a library of relationships between fc and basal crop coefficient generated from the UC Kearney/ARS peach and grape lysimeters, the ongoing ARS lysimeter studies of vegetable water use at the UC WSREC, and any relationships published in the literature.

Compare crop water use estimates with this methodology with that predicted by standard (FAO 56) and thermal surface energy balance approaches. Compare predicted ETc based on the proposed methodology (NDVI and localized CIMIS ETo, and estimates of soil evaporation) with estimates of crop water use based on remotely sensed thermal imagery and the Surface Energy Balance approach.

Develop software and packaging for retrieval and conversion of RS images to geo-rectified Kcb maps. Develop methodology to automatically retrieve appropriate imagery, efficiently calculate NDVI values from the remotely sensed (RS) images, convert the NDVI values to Kcb values, and present the data in a geometrically rectified GIS format that can be efficiently combined with the localized ETo data from CIMIS and other map layers.

Develop a prototype user interface. Develop a prototype user interface for spatially explicit query (eg, based on geo-coordinates, parcel number, etc) that allows users to efficiently download Kcb and ETo information and efficiently calculate ETc for their fields or districts.

Feasibility, Costs and Benefits. Estimate the benefits and costs of employing remote sensing technology to improve water use efficiency. Estimate the costs of delivering RS based crop coefficients for the San Joaquin Valley. Estimate the improved irrigation efficiency and water savings that can be expected with this scheduling technology compared to the use of CIMIS ETo data and a traditional crop coefficient approach.


3.Progress Report:

This project supports objective 1 of the parent project. Satellite imagery can be used to estimate crop growth conditions, and when combined with ground-based measurements, can also provide assessment of crop water status. During this reporting period, satellite Landsat TM and ETM+ data were merged over time and space to form an 8-day composite to facilitate use of overlapping portions of each scene to increase the frequency of observations and reduce data gaps due to cloud cover. Landsat provides the spatial resolution necessary to produce information at individual-field scale, while the higher temporal resolution of the MODIS satellite provides a gap-filling capability to ensure data availability. Gap-filling algorithms were employed to ensure spatially continuous data over agricultural regions. Current algorithms included the use of moving window averages and linear interpolation to fill small data gaps over agricultural fields. Prior to further processing, non-agricultural areas were masked out using the USDA NASS Cropland Data Layer, which was also used to differentiate annual crops from perennials. Each Landsat scene was atmospherically corrected. Normalized difference vegetation index (NDVI) was calculated from the composited scenes using the red and near infrared wavelengths which provides a measure of photosynthetic capacity. NDVI data were then transformed to fraction of ground cover (fc) by the empirical relationship developed under this study. Fc was then converted to basal crop coefficient (Kcb) based on a physical description of the crop canopy. For perennial crops in the initial prototype release, results from multi-year studies recently performed on large weighing lysimeters at the University of California Kearney Agricultural Center were used for fc-Kcb conversion. Both studies reported a strong relationship between mid-day canopy light interception (fc proxy) of trees and vines. As an additional step, basal crop evapotranspiration can then be estimated as the product of Kcb and potential evapotranspiration (ETo), as retrieved from the daily statewide ETo grids generated by California Department of Water Resources (CalDWR). Growers and water managers can then use the daily Kcb to make more informed decisions.


Last Modified: 7/23/2014
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