Are water footprints accurate enough to be useful? A case study for maize (Zea mays L.)

M. van der Laan, C. Jarmain, E. Bastidas-Obando, J.G. Annandale, M. Fessehazion and D. Haarhoff

Agricultural Water Management, 2019, vol. 213, issue C, 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 338-680 m3 t−1. Applying spatially-linked SEBAL ET estimates and precision harvester yield at the 30 × 30 m scale reduced the range of estimated water footprints to 493-663 m3 t -1, with an average of 547 m3 t-1. This was 15% higher than the water footprint estimated using average SEBAL ET and average yield for the whole pivot (467 m3 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.

Keywords: Crop modelling; Eddy covariance; CROPWAT; Remote sensing; SEBAL (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378377418306772
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:agiwat:v:213:y:2019:i:c:p:512-520

DOI: 10.1016/j.agwat.2018.10.026

Access Statistics for this article

Agricultural Water Management is currently edited by B.E. Clothier, W. Dierickx, J. Oster and D. Wichelns

More articles in Agricultural Water Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().