Characterisation of evapotranspiration in the Orange River Basin of South Africa-Lesotho with climate and MODIS data

Simple item page
dc.contributor.authorMahasa, Pululu S.
dc.contributor.authorXulu, Sifiso
dc.contributor.authorMbatha, Nkanyiso
dc.date.accessioned2024-02-08T05:18:30Z
dc.date.available2024-02-08T05:18:30Z
dc.date.issued2023
dc.description.abstractEvapotranspiration (ET) is crucial to the management of water supplies and the functioning of numerous terrestrial ecosystems. To understand and propose planning strategies for water-resource and crop management, it is critical to examine the geo-temporal patterns of ET in drought-prone areas such as the Upper Orange River Basin (UORB) in South Africa. While information on ET changes is computed from directly observed parameters, capturing it through remote sensing is inexpensive, consistent, and feasible at different space–time scales. Here, we employed the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived spectral indices within Google Earth Engine (GEE) to analyze and characterize patterns of ET over the UORB from 2003 to 2021, in association with various climatic parameters. Our results show spatially consistent ET patterns with the Vegetation Condition Index (VCI), with lower values in the west, increasing toward the eastern section of the basin, over the Lesotho highlands. We noted that the UORB faced significant variability in ET and VCI during pronounced drought episodes. The random forests (RF) model identified precipitation, temperature, Standardized Precipitation Index (SPI)-6, Palmer Drought Severity Index (PDSI), and VCI as variables of high importance for ET variability, while the wavelet analysis confirmed the coherence connectivity between these variables with periodicities ranging from eight to 32 months, suggesting a strong causal influence on ET, except for PDSI, that showed an erratic relationship. Based on the sequential Mann–Kendall test, we concluded that evapotranspiration has exhibited a statistically downward trend since 2011, which was particularly pronounced during the dry periods in 2015–2016, 2019, and 2021. Our study also confirmed the high capacity of the GEE and MODIS-derived indices in mapping consistent geo-temporal ET patterns.en_ZA
dc.description.versionPublisher's versionen_ZA
dc.identifier.citationMahasa, P. S., Xulu, S., & Mbatha, N. (2023). Characterisation of evapotranspiration in the Orange River Basin of South Africa-Lesotho with climate and MODIS data. Water, 15, 1501. https://doi.org/10.3390/w15081501en_ZA
dc.identifier.issn2073-4441
dc.identifier.urihttp://hdl.handle.net/11660/12378
dc.identifier.urihttps://doi.org/10.3390/w15081501en_ZA
dc.language.isoenen_ZA
dc.publisherMDPIen_ZA
dc.rights.holderAuthor(s)en_ZA
dc.rights.licensehttps://creativecommons.org/licenses/by/4.0/en_ZA
dc.subjectEvapotranspirationen_ZA
dc.subjectVCIen_ZA
dc.subjectMODISen_ZA
dc.subjectRandom forestsen_ZA
dc.subjectWavelet transformen_ZA
dc.subjectUpper Orange River Basinen_ZA
dc.subjectSSEBopen_ZA
dc.subjectGoogle Earth Engineen_ZA
dc.subjectSouth Africaen_ZA
dc.subjectLesothoen_ZA
dc.titleCharacterisation of evapotranspiration in the Orange River Basin of South Africa-Lesotho with climate and MODIS dataen_ZA
dc.typeArticleen_ZA
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Mahasa_Characterization_2023.pdf
Size:
13.04 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.76 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Research Articles (Geography)