The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
Water use indicators and economic analysis for on-farm irrigation decision: A case study of a super high density olive tree orchard
Abstract
Abstract Increasing the efficiency of on-farm water use requires wise decisions on the irrigation system, the irrigation strategy and the method to schedule irrigation, among other factors related to water management. Since the early 2000s, the water productivity approach has been widely used to address this issue. It provides useful indicators to both the biophysical water productivity and the economic performance of irrigation. Analysis of the literature, however, shows both confusion on the use of terms and lack of agreement on the equations. We have addressed the rational use of the water productivity approach for the irrigator to improve both biophysical and economic water productivity at the field scale. We also addressed the increasing use of the water footprint approach at the field scale. The literature shows a lack of consensus on the reliability of the conceptual framework behind that approach. We focused on its potential for irrigation decision making, and concluded that it is not advantageous, as compared to the water productivity approach, for assessing on-farm water use. In addition, we show a case study of a super high density olive orchard which analyses the joint use of economic water productivity indicators and both production and profit functions to improve decision making.
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Cites
Crop evapotranspiration : guidelines for computing crop water requirements
Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998) · FAO eBooks · Cited by 20,520
Our Ecological Footprint: reducing human impact on the earth
Bazan, G. (1997) · Electronic Green Journal · doi:10.5070/g31710273 · Cited by 4,654
Deficit irrigation for reducing agricultural water use
Fereres, E., & Soriano, M. A. (2006) · Journal of Experimental Botany · doi:10.1093/jxb/erl165 · Cited by 1,923
The Water Footprint Assessment Manual. Setting the Global Standard
Egan, M. (2011) · Social and Environmental Accountability Journal · doi:10.1080/0969160x.2011.593864 · Cited by 1,741
Water management: Current and future challenges and research directions
Cosgrove, W. J., & Loucks, D. P. (2015) · Water Resources Research · doi:10.1002/2014wr016869 · Cited by 1,362
Sustainable intensification of agriculture for human prosperity and global sustainability
Rockström, J., Williams, J., Daily, G., Noble, A., Matthews, N., Gordon, L., Wetterstrand, H., DeClerck, F., Shah, M., Steduto, P., et al. (2017) · Ambio · doi:10.1007/s13280-016-0793-6 · Cited by 1,145
Improving agricultural water productivity: Between optimism and caution
Molden, D., Oweis, T., Steduto, P., Bindraban, P., Hanjra, M. A., & Kijne, J. (2010) · Agricultural Water Management · doi:10.1016/j.agwat.2009.03.023 · Cited by 1,108
Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas
Geerts, S., & Raes, D. (2009) · Agricultural Water Management · doi:10.1016/j.agwat.2009.04.009 · Cited by 1,095
The paradox of irrigation efficiency
Grafton, R. Q., Williams, J., Perry, C. J., Molle, F., Ringler, C., Steduto, P., Udall, B., Wheeler, S. A., Wang, Y., Garrick, D., et al. (2018) · Science · doi:10.1126/science.aat9314 · Cited by 1,022
Ay, H. (2003) · Medical Entomology and Zoology · Cited by 856
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Pereira, L. S., Paredes, P., & Jovanovic, N. (2020) · Agricultural Water Management · doi:10.1016/j.agwat.2020.106357 · Cited by 268
Metadata
- Authors
- Fernández, J. E., Alcon, F., Diaz-Espejo, A., Hernandez-Santana, V., & Cuevas, M. V.
- Venue
- Agricultural Water Management
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 237
- Pages
- 106074
- ISSN
- 0378-3774 (ISSN-L)
- OpenAlex
- W3012015081
- Cited by
- 593
- References
- 57
- FWCI
- 43.45
- Type
- journal article
- Language
- en
- Open access
- closed
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- Fernández, J. E., Alcon, F., Diaz-Espejo, A., Hernandez-Santana, V., & Cuevas, M. V. (2020). Water use indicators and economic analysis for on-farm irrigation decision: A case study of a super high density olive tree orchard. Agricultural Water Management. https://doi.org/10.1016/j.agwat.2020.106074
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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