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ET maize Northern Cape 2012

This data is linked to a WRC project titled "Water Use Efficiency of Selected Irrigated Crops Determined with Satellite Imagery" (WRC Report No. TT 602/14). From selected project data a publication was produced focusing on different methods to estimate irrigated maize evapotranspiration and calculate green and blue water footprints (Van der Laan, M., Jarmain, C., Bastidas-Obando, E., Annandale, J. G., Fessehazion, M., & Haarhoff, D. (2019). Are water footprints accurate enough to be useful? A case study for maize (Zea mays L.). Agricultural water management, 213, 512-520). Abstract The application of water footprint accounting is mostly done at large scales, but the estimation of crop- and region-specific water footprints for up-scaling is dependent on accurate and representative in-field measurements of evapotranspiration (ET), yield and irrigation. In a field trial we assessed the influence of maize (Zea mays L.) ET estimates using soil water balance accounting, remote sensing with satellite imagery (SEBAL model), eddy covariance measurements and three crop models (SWB, CROPWAT, SAPWAT) on water footprint estimates. We simultaneously assessed the influence of yield spatial variability as measured by a precision harvester. Seasonal ET estimations differed by as much as 15% for the different methods, and yield differed by as much as 42%, representing the error which can be introduced as a result of point measurements. Using a combination of the highest/lowest ET estimates and the 5th/95th percentile yield, water footprint values differed by as much as 100%, ranging from 338-680m3 t−1. Applying spatially-linked SEBAL ET estimates and precision harvester yield at the 30×30m scale reduced the range of estimated water footprints to 493-663 m3 t -1, with an average of 547m3 t-1. This was 15% higher than the water footprint estimated using average SEBAL ET and average yield for the whole pivot (467m3 t -1). Any error introduced at this stage of water footprint accounting can be transferred during up-scaling of the results. For example, based on the minimum and maximum estimated water footprints, maize production was expected to consume between 4.4 and 8.3%, respectively, of the Orange River (South Africa’s largest river) flow during the season in that region. Biophysical scientists have the role of providing high quality data for accurate water consumption estimates. Thereafter, their application by various stakeholders should be done with caution.

Data and Resources

Additional Info

Field Value
Email vanderlaanm@arc.agric.za
Authors
Author 1
Author first name
Michael
Author surname
van der Laan
Email
vanderlaanm@arc.agric.za
Author organization
Department
Plant and Soil Sciences
Is this author a contact person for the dataset?
true
Contact person
Contact 1
Contact name
Email
Contact organization
Department
Recommended citation
Did the author / contact organization collect the data? false
Name of organization that collected the data University of Pretoria
Dataset language English
Publisher University of Pretoria / Water Research Commission
Publication date 2022-09-11
Project number WRC Report No. TT 602/14
License Open (Creative commons)
License URL
Keywords maize, Zea mays L., evapotranspiration, SWB, Cropwat, SAPWAT, SEBAL, Douglas, Northern Cape, soil water balance method
Geographic location or bounding box coordinates [-22.1265, 16.4699, -34.8212, 32.8931]
Topic category Agriculture
Data structure category Structured (clearly labelled and in a standardised format)
Uploader estimation of extent to which data have been processed Refined
Is the data time series or static Time series
Data reference date
Data reference date 1
Data reference date (from)
2013-05-31
Data reference date (to)
2012-11-01
Alternate identifier
Vertical extent datum masl
Vertical minimum-maximum extent
Vertical minimum-maximum extent 1
Minimum vertical extent
0
Maximum vertical extent
5
I agree to the data management plan and terms and conditions of the WRO false