Evidence map›Paper›PMID 38528086›Full record

ArticleNature communications2024

Field-scale crop water consumption estimates reveal potential water savings in California agriculture.

Anna Boser, Kelly Caylor, Ashley Larsen, Madeleine Pascolini-Campbell, John T Reager, Tamma Carleton

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Anna BoserBren School of Environmental Science and Management, UC Santa Barbara, 2400 Bren Hall, Santa Barbara, 93106, CA, USA. annaboser@ucsb.edu.ORCID http://orcid.org/0000-0002-7336-0117
Kelly CaylorBren School of Environmental Science and Management, UC Santa Barbara, 2400 Bren Hall, Santa Barbara, 93106, CA, USA.ORCID http://orcid.org/0000-0002-6466-6448
Ashley LarsenBren School of Environmental Science and Management, UC Santa Barbara, 2400 Bren Hall, Santa Barbara, 93106, CA, USA.ORCID http://orcid.org/0000-0001-7491-9245
Madeleine Pascolini-CampbellNASA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, 91109, CA, USA.ORCID http://orcid.org/0000-0002-6449-0841
John T ReagerNASA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, 91109, CA, USA.ORCID http://orcid.org/0000-0001-7575-2520
Tamma CarletonBren School of Environmental Science and Management, UC Santa Barbara, 2400 Bren Hall, Santa Barbara, 93106, CA, USA.ORCID http://orcid.org/0000-0002-5518-0550

Funding

National Science Foundation (NSF) 1650114National Science Foundation (NSF) CNS-1725797National Science Foundation (NSF) DEB-1924309National Science Foundation (NSF) DEB-2042526National Science Foundation (NSF) ITE-2236021
6 · The paper itself

Abstract

Efficiently managing agricultural irrigation is vital for food security today and into the future under climate change. Yet, evaluating agriculture's hydrological impacts and strategies to reduce them remains challenging due to a lack of field-scale data on crop water consumption. Here, we develop a method to fill this gap using remote sensing and machine learning, and leverage it to assess water saving strategies in California's Central Valley. We find that switching to lower water intensity crops can reduce consumption by up to 93%, but this requires adopting uncommon crop types. Northern counties have substantially lower irrigation efficiencies than southern counties, suggesting another potential source of water savings. Other practices that do not alter land cover can save up to 11% of water consumption. These results reveal diverse approaches for achieving sustainable water use, emphasizing the potential of sub-field scale crop water consumption maps to guide water management in California and beyond.

Identifiers

PMID38528086
PMCPMC10963747

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.