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Fleischmann AS, Laipelt L, Papa F, Paiva RCDD, de Andrade BC, Collischonn W, Biudes MS, Kayser R, Prigent C, Cosio E, Machado NG, Ruhoff A. Patterns and drivers of evapotranspiration in South American wetlands. Nat Commun 2023; 14:6656. [PMID: 37863899 PMCID: PMC10589351 DOI: 10.1038/s41467-023-42467-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 10/12/2023] [Indexed: 10/22/2023] Open
Abstract
Evapotranspiration (ET) is a key process linking surface and atmospheric energy budgets, yet its drivers and patterns across wetlandscapes are poorly understood worldwide. Here we assess the ET dynamics in 12 wetland complexes across South America, revealing major differences under temperate, tropical, and equatorial climates. While net radiation is a dominant driver of ET seasonality in most environments, flooding also contributes strongly to ET in tropical and equatorial wetlands, especially in meeting the evaporative demand. Moreover, significant water losses through wetlands and ET differences between wetlands and uplands occur in temperate, more water-limited environments and in highly flooded areas such as the Pantanal, where slow river flood propagation drives the ET dynamics. Finally, floodplain forests produce the greatest ET in all environments except the Amazon River floodplains, where upland forests sustain high rates year round. Our findings highlight the unique hydrological functioning and ecosystem services provided by wetlands on a continental scale.
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Affiliation(s)
- Ayan Santos Fleischmann
- Instituto de Desenvolvimento Sustentável Mamirauá, Tefé, Amazonas, Brazil.
- Instituto de Pesquisas Hidráulicas (IPH), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
| | - Leonardo Laipelt
- Instituto de Pesquisas Hidráulicas (IPH), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Fabrice Papa
- Université de Toulouse, LEGOS (IRD, CNRS, CNES, UPS), Toulouse, France
- Universidade de Brasília (UnB), IRD, Instituto de Geociências, Brasília, Brazil
| | | | - Bruno Comini de Andrade
- Instituto de Pesquisas Hidráulicas (IPH), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Walter Collischonn
- Instituto de Pesquisas Hidráulicas (IPH), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | | | - Rafael Kayser
- Instituto de Pesquisas Hidráulicas (IPH), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | | | - Eric Cosio
- Instituto para la Naturaleza, Tierra y Energía (INTE), Pontificia Universidad Católica del Perú, Lima, Perú
| | | | - Anderson Ruhoff
- Instituto de Pesquisas Hidráulicas (IPH), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
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Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian. REMOTE SENSING 2022. [DOI: 10.3390/rs14081911] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Caatinga biome, located in the Brazilian semi-arid region, is the most populous semi-arid region in the world, causing intensification in land degradation and loss of biodiversity over time. The main objective of this paper is to determine and analyze the changes in land cover and use, over time, on the biophysical parameters in the Caatinga biome in the semi-arid region of Brazil using remote sensing. Landsat-8 images were used, along with the Surface Energy Balance Algorithm for Land (SEBAL) in the Google Earth Engine platform, from 2013 to 2019, through spatiotemporal modeling of vegetation indices, i.e., leaf area index (LAI) and vegetation cover (VC). Moreover, land surface temperature (LST) and actual evapotranspiration (ETa) in Petrolina, the semi-arid region of Brazil, was used. The principal component analysis was used to select descriptive variables and multiple regression analysis to predict ETa. The results indicated significant effects of land use and land cover changes on energy balances over time. In 2013, 70.2% of the study area was composed of Caatinga, while the lowest percentages were identified in 2015 (67.8%) and 2017 (68.7%). Rainfall records in 2013 ranged from 270 to 480 mm, with values higher than 410 mm in 46.5% of the study area, concentrated in the northern part of the municipality. On the other hand, in 2017 the lowest annual rainfall values (from 200 to 340 mm) occurred. Low vegetation cover rate was observed by LAI and VC values, with a range of 0 to 25% vegetation cover in 52.3% of the area, which exposes the effects of the dry season on vegetation. The highest LST was mainly found in urban areas and/or exposed soil. In 2013, 40.5% of the region’s area had LST between 48.0 and 52.0 °C, raising ETa rates (~4.7 mm day−1). Our model has shown good outcomes in terms of accuracy and concordance (coefficient of determination = 0.98, root mean square error = 0.498, and Lin’s concordance correlation coefficient = 0.907). The significant increase in agricultural areas has resulted in the progressive reduction of the Caatinga biome. Therefore, mitigation and sustainable planning is vital to decrease the impacts of anthropic actions.
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