Salt Accumulation and Redistribution in the Dry Plains of Southern South America: Lessons from Land Use Changes

Jobbágy, Estéban G.; Giménez, Raúl; Marchesini, Victoria A.; Díaz, Yésica; Jayawickreme, Dushmantha H.; Nosetto, Marcelo D.

doi:10.1007/978-3-030-52592-7_3

Cited by 7 publications

(5 citation statements)

References 62 publications

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“…The South American Gran Chaco hosts a wealth of biodiversity in an area where native dry forests and expanding, mostly rainfed, agriculture for crops and cattle ranching are competing in a changing landscape [24,25]. Despite its large latitudinal extent and vegetative and climatic variability, the Dry Chaco is a well-delineated ecoregion in the western part of the larger Gran Chaco and covers an area of about 787 000 km 2 in southern Bolivia, western Paraguay and northern Argentina [26], east of the Andean mountain range (Fig.…”

Section: A Study Areamentioning

confidence: 99%

“…Saline soils are common in the region owing to its semi-arid climate, flat topography and shallow groundwater table [24]. Large natural salt deposits occur in the presence of paleo-lakes (e.g.…”

Section: A Study Areamentioning

confidence: 99%

“…The key question of this paper is therefore what we can learn from L-band TB observations about land surface variables such as soil salinity, soil moisture, temperature and vegetation. To this end, the South-American Dry Chaco, with its naturally saline soils [24] at risk of future salinization, forms a unique large-scale testbed.…”

Section: Introductionmentioning

confidence: 99%

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L-Band Microwave Satellite Data and Model Simulations Over the Dry Chaco to Estimate Soil Moisture, Soil Temperature, Vegetation, and Soil Salinity

Vincent

Maertens

Bechtold

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The Dry Chaco in South America is a semi-arid ecoregion prone to dryland salinization. In this region, we investigated coarse-scale surface soil moisture (SM), soil temperature, soil salinity and vegetation, using L-band microwave brightness temperature (TB) observations and retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellite missions, Catchment Land Surface Model (CLSM) simulations, and in situ measurements within 26 sampled satellite pixels. Across these 26 sampled pixels, the satellite-based SM outperformed CLSM SM when evaluated against field data, and forward L-band TB simulations derived from in situ SM and temperature performed better than those derived from CLSM estimates when evaluated against SMOS TB observations. The surface salinity for the sampled pixels was on average only 4 mg/g and only locally influenced the TB simulations, when including salinity in the dielectric mixing model of the forward radiative transfer model (RTM) simulations. To explore the potential of retrieving salinity together with other RTM parameters to optimize TB simulations over the entire Dry Chaco, the RTM was inverted using 10 years of multi-angular SMOS TB data and constraints of CLSM SM and temperature. However, the latter modeled SM was not sufficiently accurate and factors such as open surface water were missing in the background constraints, so that the salinity retrievals effectively represented a bulk correction of the dielectric constant, rather than salinity per se. However, the retrieval of vegetation, scattering albedo and surface roughness resulted in realistic values.

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Section: A Study Areamentioning

confidence: 99%

Section: A Study Areamentioning

confidence: 99%

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L-Band Microwave Satellite Data and Model Simulations Over the Dry Chaco to Estimate Soil Moisture, Soil Temperature, Vegetation, and Soil Salinity

Vincent

Maertens

Bechtold

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…A su vez, estos procesos de salinización no son homogéneos y resultan de la interacción entre la geomorfología local, las condiciones climáticas y el tipo de vegetación. Por otra parte, el ascenso de napas, el anegamiento y la salinización en sitios con historia de uso agrícola evidencian el efecto de la vegetación en la regulación hídrica y en la acumulación y la distribución de sales (Jobbágy et al 2008(Jobbágy et al , 2021a, ya que los excedentes hídricos se relacionan con el incremento de la superficie dedicada a cultivos (Bertram and Chiacciera 2013).…”

Section: ₈₂₆ Yr D�� unclassified

Neo-humedales en las llanuras agrícolas del Chaco Seco-Espinal argentino: ¿Cómo son, dónde se originan y qué hacer con ellos?

2022

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R��.En las últimas décadas, la transformación de los sistemas ecológicos dio lugar a la formación de 'neo-ecosistemas'. En las llanuras del Chaco Seco-Espinal argentino, la expansión agrícola en reemplazo de bosques, arbustales y pastizales naturales ha generado excedentes hídricos, lo que favoreció la formación de neo-humedales caracterizados por un aumento de los niveles freáticos, anegamiento y salinización. En este trabajo nos proponemos describir los neo-humedales del Chaco Seco-Espinal argentino y los factores que favorecen su formación, tomando como caso de

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“…Changes in land use and vegetation can alter water fluxes, affecting salt retention mechanisms (Jobbágy et al, 2021). Secondary salt-affected soils in Latin America, often developed under irrigation, result from low irrigation water quality and inefficient water management (Taleisnik, 2021).…”

Section: Introductionmentioning

confidence: 99%

First National Report on Soil Salinity Across Paraguay

Encina Rojas,

Sevilla-Linares,

Guevara-Santamaría

et al. 2023

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Assessing soil salinity on a national scale provides crucial information on soil fertility. Our objective was to map soil salinity in Paraguay at the topsoil layer (0-30 cm) using indicators such as Electrical Conductivity (EC), pH, and Exchangeable Sodium Percent (ESP). We employed a model with 80 data points for Electrical Conductivity (EC) and 204 points for pH and Exchangeable Sodium Percent (ESP). The statistical model used to map soil salinity properties was the "quantile random forest." For validation and accuracy calculation, we utilized "cross-validation" with all soil sampling sites and a "Random" selection parameter. To ensure result consistency, we repeated the validation five times, calculating the average of the results. Uncertainty was estimated using "predUncertain-quantile random forest," implemented in the R programming language. In general, Paraguayan soils at a depth of 0 to 30 cm exhibit low salt levels, with the soils in the Paraguayan Chaco region showing higher levels. Two primary factors contribute to soil salinity in Paraguay: natural factors, such as a dry climate, high temperatures, and high evapotranspiration, and secondary factors, including soil parent material with alluvial deposits and groundwater with significant salt content. It’s worth noting that actual salinity values, both in Paraguayan Chaco and the eastern region, might surpass those mentioned in this study due to limited available data and the spatial resolution of the map. This study represents the first effort to develop a soil salinity map of Paraguay, providing the initial national baseline for the development of salinity/sodicity monitoring frameworks. It can be instrumental in addressing regional gaps in salinity/sodicity within South America.

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Salt Accumulation and Redistribution in the Dry Plains of Southern South America: Lessons from Land Use Changes

Cited by 7 publications

References 62 publications

L-Band Microwave Satellite Data and Model Simulations Over the Dry Chaco to Estimate Soil Moisture, Soil Temperature, Vegetation, and Soil Salinity

L-Band Microwave Satellite Data and Model Simulations Over the Dry Chaco to Estimate Soil Moisture, Soil Temperature, Vegetation, and Soil Salinity

Neo-humedales en las llanuras agrícolas del Chaco Seco-Espinal argentino: ¿Cómo son, dónde se originan y qué hacer con ellos?

First National Report on Soil Salinity Across Paraguay

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