SEBAL-A: A Remote Sensing ET Algorithm that Accounts for Advection with Limited Data. Part II: Test for Transferability Article Swipe
Mcebisi Mkhwanazi
,
José L. Chávez
,
Allan A. Andales
,
Kendall C. DeJonge
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.3390/rs71115068
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.3390/rs71115068
Because the Surface Energy Balance Algorithm for Land (SEBAL) tends to underestimate ET when there is advection, the model was modified by incorporating an advection component as part of the energy usable for crop evapotranspiration (ET). The modification involved the estimation of advected energy, which required the development of a wind function. In Part I, the modified SEBAL model (SEBAL-A) was developed and validated on well-watered alfalfa of a standard height of 40–60 cm. In this Part II, SEBAL-A was tested on different crops and irrigation treatments in order to determine its performance under varying conditions. The crops used for the transferability test were beans (Phaseolus vulgaris L.), wheat (Triticum aestivum L.) and corn (Zea mays L.). The estimated ET using SEBAL-A was compared to actual ET measured using a Bowen Ratio Energy Balance (BREB) system. Results indicated that SEBAL-A estimated ET fairly well for beans and wheat, only showing some slight underestimation of a Mean Bias Error (MBE) of −0.7 mm·d−1 (−11.3%), a Root Mean Square Error (RMSE) of 0.82 mm·d−1 (13.9%) and a Nash Sutcliffe Coefficient of Efficiency (NSCE) of 0.64. On corn, SEBAL-A resulted in an ET estimation error MBE of −0.7 mm·d−1 (−9.9%), a RMSE of 1.59 mm·d−1 (23.1%) and NSCE = 0.24. This result shows an improvement on the original SEBAL model, which for the same data resulted in an ET MBE of −1.4 mm·d−1 (−20.4%), a RMSE of 1.97 mm·d−1 (28.8%) and a NSCE of −0.18. When SEBAL-A was tested on only fully irrigated corn, it performed well, resulting in no bias, i.e., MBE of 0.0 mm·d−1; RMSE of 0.78 mm·d−1 (10.7%) and NSCE of 0.82. The SEBAL-A model showed less or no improvement on corn that was either water-stressed or at early stages of growth. The errors incurred under these conditions were not due to advection not accounted for but rather were due to the nature of SEBAL and SEBAL-A being single-source energy balance models and, therefore, not performing well over heterogeneous surfaces. Therefore, it was concluded that SEBAL-A could be used on a wide range of crops if they are not water stressed. It is recommended that the SEBAL-A model be further studied to be able to accurately estimate ET under dry and sparse surface conditions.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs71115068
- https://www.mdpi.com/2072-4292/7/11/15068/pdf?version=1447397547
- OA Status
- gold
- Cited By
- 10
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2190658778
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2190658778Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/rs71115068Digital Object Identifier
- Title
-
SEBAL-A: A Remote Sensing ET Algorithm that Accounts for Advection with Limited Data. Part II: Test for TransferabilityWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-11-10Full publication date if available
- Authors
-
Mcebisi Mkhwanazi, José L. Chávez, Allan A. Andales, Kendall C. DeJongeList of authors in order
- Landing page
-
https://doi.org/10.3390/rs71115068Publisher landing page
- PDF URL
-
https://www.mdpi.com/2072-4292/7/11/15068/pdf?version=1447397547Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2072-4292/7/11/15068/pdf?version=1447397547Direct OA link when available
- Concepts
-
Advection, Mean squared error, Environmental science, Mathematics, Energy balance, Algorithm, Physics, Statistics, ThermodynamicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
10Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 3, 2023: 1, 2021: 1, 2019: 1, 2018: 2Per-year citation counts (last 5 years)
- References (count)
-
26Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2190658778 |
|---|---|
| doi | https://doi.org/10.3390/rs71115068 |
| ids.doi | https://doi.org/10.3390/rs71115068 |
| ids.mag | 2190658778 |
| ids.openalex | https://openalex.org/W2190658778 |
| fwci | 0.82468704 |
| type | article |
| title | SEBAL-A: A Remote Sensing ET Algorithm that Accounts for Advection with Limited Data. Part II: Test for Transferability |
| biblio.issue | 11 |
| biblio.volume | 7 |
| biblio.last_page | 15081 |
| biblio.first_page | 15068 |
| topics[0].id | https://openalex.org/T10266 |
| topics[0].field.id | https://openalex.org/fields/23 |
| topics[0].field.display_name | Environmental Science |
| topics[0].score | 0.9997000098228455 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2306 |
| topics[0].subfield.display_name | Global and Planetary Change |
| topics[0].display_name | Plant Water Relations and Carbon Dynamics |
| topics[1].id | https://openalex.org/T11404 |
| topics[1].field.id | https://openalex.org/fields/11 |
| topics[1].field.display_name | Agricultural and Biological Sciences |
| topics[1].score | 0.996399998664856 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1111 |
| topics[1].subfield.display_name | Soil Science |
| topics[1].display_name | Irrigation Practices and Water Management |
| topics[2].id | https://openalex.org/T10330 |
| topics[2].field.id | https://openalex.org/fields/23 |
| topics[2].field.display_name | Environmental Science |
| topics[2].score | 0.9929999709129333 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2312 |
| topics[2].subfield.display_name | Water Science and Technology |
| topics[2].display_name | Hydrology and Watershed Management Studies |
| is_xpac | False |
| apc_list.value | 2500 |
| apc_list.currency | CHF |
| apc_list.value_usd | 2707 |
| apc_paid.value | 2500 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 2707 |
| concepts[0].id | https://openalex.org/C5072599 |
| concepts[0].level | 2 |
| concepts[0].score | 0.5785072445869446 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q379788 |
| concepts[0].display_name | Advection |
| concepts[1].id | https://openalex.org/C139945424 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5728511214256287 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q1940696 |
| concepts[1].display_name | Mean squared error |
| concepts[2].id | https://openalex.org/C39432304 |
| concepts[2].level | 0 |
| concepts[2].score | 0.5626952052116394 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q188847 |
| concepts[2].display_name | Environmental science |
| concepts[3].id | https://openalex.org/C33923547 |
| concepts[3].level | 0 |
| concepts[3].score | 0.48087078332901 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[3].display_name | Mathematics |
| concepts[4].id | https://openalex.org/C2777423268 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4739425480365753 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q3663116 |
| concepts[4].display_name | Energy balance |
| concepts[5].id | https://openalex.org/C11413529 |
| concepts[5].level | 1 |
| concepts[5].score | 0.40686291456222534 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[5].display_name | Algorithm |
| concepts[6].id | https://openalex.org/C121332964 |
| concepts[6].level | 0 |
| concepts[6].score | 0.19063350558280945 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[6].display_name | Physics |
| concepts[7].id | https://openalex.org/C105795698 |
| concepts[7].level | 1 |
| concepts[7].score | 0.18193161487579346 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[7].display_name | Statistics |
| concepts[8].id | https://openalex.org/C97355855 |
| concepts[8].level | 1 |
| concepts[8].score | 0.0 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q11473 |
| concepts[8].display_name | Thermodynamics |
| keywords[0].id | https://openalex.org/keywords/advection |
| keywords[0].score | 0.5785072445869446 |
| keywords[0].display_name | Advection |
| keywords[1].id | https://openalex.org/keywords/mean-squared-error |
| keywords[1].score | 0.5728511214256287 |
| keywords[1].display_name | Mean squared error |
| keywords[2].id | https://openalex.org/keywords/environmental-science |
| keywords[2].score | 0.5626952052116394 |
| keywords[2].display_name | Environmental science |
| keywords[3].id | https://openalex.org/keywords/mathematics |
| keywords[3].score | 0.48087078332901 |
| keywords[3].display_name | Mathematics |
| keywords[4].id | https://openalex.org/keywords/energy-balance |
| keywords[4].score | 0.4739425480365753 |
| keywords[4].display_name | Energy balance |
| keywords[5].id | https://openalex.org/keywords/algorithm |
| keywords[5].score | 0.40686291456222534 |
| keywords[5].display_name | Algorithm |
| keywords[6].id | https://openalex.org/keywords/physics |
| keywords[6].score | 0.19063350558280945 |
| keywords[6].display_name | Physics |
| keywords[7].id | https://openalex.org/keywords/statistics |
| keywords[7].score | 0.18193161487579346 |
| keywords[7].display_name | Statistics |
| language | en |
| locations[0].id | doi:10.3390/rs71115068 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S43295729 |
| locations[0].source.issn | 2072-4292 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2072-4292 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Remote Sensing |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/2072-4292/7/11/15068/pdf?version=1447397547 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Remote Sensing |
| locations[0].landing_page_url | https://doi.org/10.3390/rs71115068 |
| locations[1].id | pmh:oai:doaj.org/article:0d621496ac974ae8b58dd2230f4b49a8 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | cc-by-sa |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Remote Sensing, Vol 7, Iss 11, Pp 15068-15081 (2015) |
| locations[1].landing_page_url | https://doaj.org/article/0d621496ac974ae8b58dd2230f4b49a8 |
| locations[2].id | pmh:oai:mdpi.com:/2072-4292/7/11/15068/ |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306400947 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | True |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | MDPI (MDPI AG) |
| locations[2].source.host_organization | https://openalex.org/I4210097602 |
| locations[2].source.host_organization_name | Multidisciplinary Digital Publishing Institute (Switzerland) |
| locations[2].source.host_organization_lineage | https://openalex.org/I4210097602 |
| locations[2].license | cc-by |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | https://openalex.org/licenses/cc-by |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Remote Sensing; Volume 7; Issue 11; Pages: 15068-15081 |
| locations[2].landing_page_url | https://dx.doi.org/10.3390/rs71115068 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5029963444 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Mcebisi Mkhwanazi |
| authorships[0].countries | US |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I92446798 |
| authorships[0].affiliations[0].raw_affiliation_string | Civil and Environmental Engineering Department, Colorado State University, Fort Collins, CO 80523, USA |
| authorships[0].institutions[0].id | https://openalex.org/I92446798 |
| authorships[0].institutions[0].ror | https://ror.org/03k1gpj17 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I92446798 |
| authorships[0].institutions[0].country_code | US |
| authorships[0].institutions[0].display_name | Colorado State University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Mcebisi Mkhwanazi |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Civil and Environmental Engineering Department, Colorado State University, Fort Collins, CO 80523, USA |
| authorships[1].author.id | https://openalex.org/A5077934130 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-6456-0822 |
| authorships[1].author.display_name | José L. Chávez |
| authorships[1].countries | US |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I92446798 |
| authorships[1].affiliations[0].raw_affiliation_string | Civil and Environmental Engineering Department, Colorado State University, Fort Collins, CO 80523, USA |
| authorships[1].institutions[0].id | https://openalex.org/I92446798 |
| authorships[1].institutions[0].ror | https://ror.org/03k1gpj17 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I92446798 |
| authorships[1].institutions[0].country_code | US |
| authorships[1].institutions[0].display_name | Colorado State University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | José Chávez |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | Civil and Environmental Engineering Department, Colorado State University, Fort Collins, CO 80523, USA |
| authorships[2].author.id | https://openalex.org/A5002235296 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-7640-6723 |
| authorships[2].author.display_name | Allan A. Andales |
| authorships[2].countries | US |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I92446798 |
| authorships[2].affiliations[0].raw_affiliation_string | Soil and Crop Sciences Department, Colorado State University, Fort Collins, CO 80523, USA |
| authorships[2].institutions[0].id | https://openalex.org/I92446798 |
| authorships[2].institutions[0].ror | https://ror.org/03k1gpj17 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I92446798 |
| authorships[2].institutions[0].country_code | US |
| authorships[2].institutions[0].display_name | Colorado State University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Allan Andales |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Soil and Crop Sciences Department, Colorado State University, Fort Collins, CO 80523, USA |
| authorships[3].author.id | https://openalex.org/A5035069792 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-3683-4149 |
| authorships[3].author.display_name | Kendall C. DeJonge |
| authorships[3].countries | US |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I1336096307, https://openalex.org/I4210145274 |
| authorships[3].affiliations[0].raw_affiliation_string | United States Department of Agriculture, Agricultural Research Service, Fort Collins, CO 80526, USA |
| authorships[3].institutions[0].id | https://openalex.org/I4210145274 |
| authorships[3].institutions[0].ror | https://ror.org/03sqy6516 |
| authorships[3].institutions[0].type | government |
| authorships[3].institutions[0].lineage | https://openalex.org/I1312222531, https://openalex.org/I1336096307, https://openalex.org/I4210145274 |
| authorships[3].institutions[0].country_code | US |
| authorships[3].institutions[0].display_name | Agricultural Research Service - Plains Area |
| authorships[3].institutions[1].id | https://openalex.org/I1336096307 |
| authorships[3].institutions[1].ror | https://ror.org/01na82s61 |
| authorships[3].institutions[1].type | government |
| authorships[3].institutions[1].lineage | https://openalex.org/I1336096307 |
| authorships[3].institutions[1].country_code | US |
| authorships[3].institutions[1].display_name | United States Department of Agriculture |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Kendall DeJonge |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | United States Department of Agriculture, Agricultural Research Service, Fort Collins, CO 80526, USA |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/2072-4292/7/11/15068/pdf?version=1447397547 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | SEBAL-A: A Remote Sensing ET Algorithm that Accounts for Advection with Limited Data. Part II: Test for Transferability |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10266 |
| primary_topic.field.id | https://openalex.org/fields/23 |
| primary_topic.field.display_name | Environmental Science |
| primary_topic.score | 0.9997000098228455 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2306 |
| primary_topic.subfield.display_name | Global and Planetary Change |
| primary_topic.display_name | Plant Water Relations and Carbon Dynamics |
| related_works | https://openalex.org/W2051487156, https://openalex.org/W3036101264, https://openalex.org/W2163151373, https://openalex.org/W1986676657, https://openalex.org/W4238257821, https://openalex.org/W2073681303, https://openalex.org/W2165001118, https://openalex.org/W2477137736, https://openalex.org/W1973075756, https://openalex.org/W3100623684 |
| cited_by_count | 10 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 3 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 1 |
| counts_by_year[2].year | 2021 |
| counts_by_year[2].cited_by_count | 1 |
| counts_by_year[3].year | 2019 |
| counts_by_year[3].cited_by_count | 1 |
| counts_by_year[4].year | 2018 |
| counts_by_year[4].cited_by_count | 2 |
| counts_by_year[5].year | 2017 |
| counts_by_year[5].cited_by_count | 1 |
| counts_by_year[6].year | 2015 |
| counts_by_year[6].cited_by_count | 1 |
| locations_count | 3 |
| best_oa_location.id | doi:10.3390/rs71115068 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S43295729 |
| best_oa_location.source.issn | 2072-4292 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2072-4292 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Remote Sensing |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/2072-4292/7/11/15068/pdf?version=1447397547 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Remote Sensing |
| best_oa_location.landing_page_url | https://doi.org/10.3390/rs71115068 |
| primary_location.id | doi:10.3390/rs71115068 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S43295729 |
| primary_location.source.issn | 2072-4292 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2072-4292 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Remote Sensing |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/2072-4292/7/11/15068/pdf?version=1447397547 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Remote Sensing |
| primary_location.landing_page_url | https://doi.org/10.3390/rs71115068 |
| publication_date | 2015-11-10 |
| publication_year | 2015 |
| referenced_works | https://openalex.org/W2194186503, https://openalex.org/W2054461673, https://openalex.org/W2316931610, https://openalex.org/W4298466131, https://openalex.org/W2025977407, https://openalex.org/W2034006829, https://openalex.org/W2170523364, https://openalex.org/W2044245979, https://openalex.org/W2130031595, https://openalex.org/W1987557279, https://openalex.org/W1964536255, https://openalex.org/W2300301246, https://openalex.org/W2069732630, https://openalex.org/W212354674, https://openalex.org/W2142458723, https://openalex.org/W2163606831, https://openalex.org/W2014015648, https://openalex.org/W2047884674, https://openalex.org/W6741979189, https://openalex.org/W2058998445, https://openalex.org/W2033904036, https://openalex.org/W2002071141, https://openalex.org/W1505525984, https://openalex.org/W2100585318, https://openalex.org/W4285719527, https://openalex.org/W2741856653 |
| referenced_works_count | 26 |
| abstract_inverted_index.= | 205 |
| abstract_inverted_index.a | 49, 68, 129, 154, 163, 174, 197, 231, 238, 340 |
| abstract_inverted_index.ET | 12, 119, 126, 141, 189, 225, 367 |
| abstract_inverted_index.I, | 54 |
| abstract_inverted_index.In | 52, 74 |
| abstract_inverted_index.It | 351 |
| abstract_inverted_index.On | 183 |
| abstract_inverted_index.an | 23, 188, 210, 224 |
| abstract_inverted_index.as | 26 |
| abstract_inverted_index.at | 287 |
| abstract_inverted_index.be | 337, 358, 362 |
| abstract_inverted_index.by | 21 |
| abstract_inverted_index.if | 345 |
| abstract_inverted_index.in | 87, 187, 223, 255 |
| abstract_inverted_index.is | 15, 352 |
| abstract_inverted_index.it | 251, 331 |
| abstract_inverted_index.no | 256, 278 |
| abstract_inverted_index.of | 28, 41, 48, 67, 71, 153, 159, 169, 178, 181, 193, 199, 227, 233, 240, 260, 264, 270, 290, 313, 343 |
| abstract_inverted_index.on | 64, 81, 212, 246, 280, 339 |
| abstract_inverted_index.or | 277, 286 |
| abstract_inverted_index.to | 10, 89, 124, 301, 310, 361, 364 |
| abstract_inverted_index.0.0 | 261 |
| abstract_inverted_index.II, | 77 |
| abstract_inverted_index.L.) | 111 |
| abstract_inverted_index.MBE | 192, 226, 259 |
| abstract_inverted_index.The | 36, 96, 117, 272, 292 |
| abstract_inverted_index.and | 62, 84, 112, 146, 173, 203, 237, 268, 315, 370 |
| abstract_inverted_index.are | 347 |
| abstract_inverted_index.but | 306 |
| abstract_inverted_index.cm. | 73 |
| abstract_inverted_index.dry | 369 |
| abstract_inverted_index.due | 300, 309 |
| abstract_inverted_index.for | 6, 32, 99, 144, 218, 305 |
| abstract_inverted_index.its | 91 |
| abstract_inverted_index.not | 299, 303, 324, 348 |
| abstract_inverted_index.the | 1, 17, 29, 39, 46, 55, 100, 213, 219, 311, 355 |
| abstract_inverted_index.was | 19, 60, 79, 122, 244, 283, 332 |
| abstract_inverted_index.(Zea | 114 |
| abstract_inverted_index.0.78 | 265 |
| abstract_inverted_index.0.82 | 170 |
| abstract_inverted_index.1.59 | 200 |
| abstract_inverted_index.1.97 | 234 |
| abstract_inverted_index.Bias | 156 |
| abstract_inverted_index.L.), | 107 |
| abstract_inverted_index.L.). | 116 |
| abstract_inverted_index.Land | 7 |
| abstract_inverted_index.Mean | 155, 165 |
| abstract_inverted_index.NSCE | 204, 239, 269 |
| abstract_inverted_index.Nash | 175 |
| abstract_inverted_index.Part | 53, 76 |
| abstract_inverted_index.RMSE | 198, 232, 263 |
| abstract_inverted_index.Root | 164 |
| abstract_inverted_index.This | 207 |
| abstract_inverted_index.When | 242 |
| abstract_inverted_index.able | 363 |
| abstract_inverted_index.and, | 322 |
| abstract_inverted_index.corn | 113, 281 |
| abstract_inverted_index.crop | 33 |
| abstract_inverted_index.data | 221 |
| abstract_inverted_index.less | 276 |
| abstract_inverted_index.mays | 115 |
| abstract_inverted_index.only | 148, 247 |
| abstract_inverted_index.over | 327 |
| abstract_inverted_index.part | 27 |
| abstract_inverted_index.same | 220 |
| abstract_inverted_index.some | 150 |
| abstract_inverted_index.test | 102 |
| abstract_inverted_index.that | 138, 282, 334, 354 |
| abstract_inverted_index.they | 346 |
| abstract_inverted_index.this | 75 |
| abstract_inverted_index.used | 98, 338 |
| abstract_inverted_index.well | 143, 326 |
| abstract_inverted_index.were | 103, 298, 308 |
| abstract_inverted_index.when | 13 |
| abstract_inverted_index.wide | 341 |
| abstract_inverted_index.wind | 50 |
| abstract_inverted_index.(ET). | 35 |
| abstract_inverted_index.(MBE) | 158 |
| abstract_inverted_index.0.24. | 206 |
| abstract_inverted_index.0.64. | 182 |
| abstract_inverted_index.0.82. | 271 |
| abstract_inverted_index.Bowen | 130 |
| abstract_inverted_index.Error | 157, 167 |
| abstract_inverted_index.Ratio | 131 |
| abstract_inverted_index.SEBAL | 57, 215, 314 |
| abstract_inverted_index.beans | 104, 145 |
| abstract_inverted_index.being | 317 |
| abstract_inverted_index.bias, | 257 |
| abstract_inverted_index.corn, | 184, 250 |
| abstract_inverted_index.could | 336 |
| abstract_inverted_index.crops | 83, 97, 344 |
| abstract_inverted_index.early | 288 |
| abstract_inverted_index.error | 191 |
| abstract_inverted_index.fully | 248 |
| abstract_inverted_index.i.e., | 258 |
| abstract_inverted_index.model | 18, 58, 274, 357 |
| abstract_inverted_index.order | 88 |
| abstract_inverted_index.range | 342 |
| abstract_inverted_index.shows | 209 |
| abstract_inverted_index.tends | 9 |
| abstract_inverted_index.there | 14 |
| abstract_inverted_index.these | 296 |
| abstract_inverted_index.under | 93, 295, 368 |
| abstract_inverted_index.using | 120, 128 |
| abstract_inverted_index.water | 349 |
| abstract_inverted_index.well, | 253 |
| abstract_inverted_index.wheat | 108 |
| abstract_inverted_index.which | 44, 217 |
| abstract_inverted_index.(BREB) | 134 |
| abstract_inverted_index.(NSCE) | 180 |
| abstract_inverted_index.(RMSE) | 168 |
| abstract_inverted_index.Energy | 3, 132 |
| abstract_inverted_index.Square | 166 |
| abstract_inverted_index.actual | 125 |
| abstract_inverted_index.either | 284 |
| abstract_inverted_index.energy | 30, 319 |
| abstract_inverted_index.errors | 293 |
| abstract_inverted_index.fairly | 142 |
| abstract_inverted_index.height | 70 |
| abstract_inverted_index.model, | 216 |
| abstract_inverted_index.models | 321 |
| abstract_inverted_index.nature | 312 |
| abstract_inverted_index.rather | 307 |
| abstract_inverted_index.result | 208 |
| abstract_inverted_index.showed | 275 |
| abstract_inverted_index.slight | 151 |
| abstract_inverted_index.sparse | 371 |
| abstract_inverted_index.stages | 289 |
| abstract_inverted_index.tested | 80, 245 |
| abstract_inverted_index.usable | 31 |
| abstract_inverted_index.wheat, | 147 |
| abstract_inverted_index.−0.7 | 160, 194 |
| abstract_inverted_index.−1.4 | 228 |
| abstract_inverted_index.(10.7%) | 267 |
| abstract_inverted_index.(13.9%) | 172 |
| abstract_inverted_index.(23.1%) | 202 |
| abstract_inverted_index.(28.8%) | 236 |
| abstract_inverted_index.(SEBAL) | 8 |
| abstract_inverted_index.40–60 | 72 |
| abstract_inverted_index.Balance | 4, 133 |
| abstract_inverted_index.Because | 0 |
| abstract_inverted_index.Results | 136 |
| abstract_inverted_index.SEBAL-A | 78, 121, 139, 185, 243, 273, 316, 335, 356 |
| abstract_inverted_index.Surface | 2 |
| abstract_inverted_index.alfalfa | 66 |
| abstract_inverted_index.balance | 320 |
| abstract_inverted_index.energy, | 43 |
| abstract_inverted_index.further | 359 |
| abstract_inverted_index.growth. | 291 |
| abstract_inverted_index.showing | 149 |
| abstract_inverted_index.studied | 360 |
| abstract_inverted_index.surface | 372 |
| abstract_inverted_index.system. | 135 |
| abstract_inverted_index.varying | 94 |
| abstract_inverted_index.advected | 42 |
| abstract_inverted_index.aestivum | 110 |
| abstract_inverted_index.compared | 123 |
| abstract_inverted_index.estimate | 366 |
| abstract_inverted_index.incurred | 294 |
| abstract_inverted_index.involved | 38 |
| abstract_inverted_index.measured | 127 |
| abstract_inverted_index.modified | 20, 56 |
| abstract_inverted_index.original | 214 |
| abstract_inverted_index.required | 45 |
| abstract_inverted_index.resulted | 186, 222 |
| abstract_inverted_index.standard | 69 |
| abstract_inverted_index.vulgaris | 106 |
| abstract_inverted_index.−0.18. | 241 |
| abstract_inverted_index.(SEBAL-A) | 59 |
| abstract_inverted_index.(Triticum | 109 |
| abstract_inverted_index.Algorithm | 5 |
| abstract_inverted_index.Sutcliffe | 176 |
| abstract_inverted_index.accounted | 304 |
| abstract_inverted_index.advection | 24, 302 |
| abstract_inverted_index.component | 25 |
| abstract_inverted_index.concluded | 333 |
| abstract_inverted_index.determine | 90 |
| abstract_inverted_index.developed | 61 |
| abstract_inverted_index.different | 82 |
| abstract_inverted_index.estimated | 118, 140 |
| abstract_inverted_index.function. | 51 |
| abstract_inverted_index.indicated | 137 |
| abstract_inverted_index.irrigated | 249 |
| abstract_inverted_index.mm·d−1 | 161, 171, 195, 201, 229, 235, 266 |
| abstract_inverted_index.performed | 252 |
| abstract_inverted_index.resulting | 254 |
| abstract_inverted_index.stressed. | 350 |
| abstract_inverted_index.surfaces. | 329 |
| abstract_inverted_index.validated | 63 |
| abstract_inverted_index.(Phaseolus | 105 |
| abstract_inverted_index.(−9.9%), | 196 |
| abstract_inverted_index.Efficiency | 179 |
| abstract_inverted_index.Therefore, | 330 |
| abstract_inverted_index.accurately | 365 |
| abstract_inverted_index.advection, | 16 |
| abstract_inverted_index.conditions | 297 |
| abstract_inverted_index.estimation | 40, 190 |
| abstract_inverted_index.irrigation | 85 |
| abstract_inverted_index.mm·d−1; | 262 |
| abstract_inverted_index.performing | 325 |
| abstract_inverted_index.therefore, | 323 |
| abstract_inverted_index.treatments | 86 |
| abstract_inverted_index.(−11.3%), | 162 |
| abstract_inverted_index.(−20.4%), | 230 |
| abstract_inverted_index.Coefficient | 177 |
| abstract_inverted_index.conditions. | 95, 373 |
| abstract_inverted_index.development | 47 |
| abstract_inverted_index.improvement | 211, 279 |
| abstract_inverted_index.performance | 92 |
| abstract_inverted_index.recommended | 353 |
| abstract_inverted_index.modification | 37 |
| abstract_inverted_index.well-watered | 65 |
| abstract_inverted_index.heterogeneous | 328 |
| abstract_inverted_index.incorporating | 22 |
| abstract_inverted_index.single-source | 318 |
| abstract_inverted_index.underestimate | 11 |
| abstract_inverted_index.water-stressed | 285 |
| abstract_inverted_index.transferability | 101 |
| abstract_inverted_index.underestimation | 152 |
| abstract_inverted_index.evapotranspiration | 34 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5077934130 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I92446798 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8600000143051147 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.79391913 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |