Influence of vegetation cover and rainfall intensity on soil attributes in an area undergoing desertification in Brazil

Lins, Cíntia Maria Teixeira; Souza, Eliane Helena Alvim de; Souza, Thais Emanuelle Monteiro dos Santos; Paulino, Martha Katharinne Silva Souza; Monteiro, Danilo Rodrigues; Júnior, Valdomiro Severino de Souza; Dourado, Pablo Rugero Magalhães; Rego, Francisco Ernesto de Andrade; Silva, Yuri Jacques Agra da; Schaffer, Bruce

doi:10.1016/j.catena.2022.106751

Cited by 9 publications

(4 citation statements)

References 43 publications

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“…Although the GeoWEPP model validation for crops requires future improvement, the pasture and natural vegetation we validated the model for make up a large percentage of the Cerrado savannah biome at 54.8% for such natural areas and 30.7% for pasture with crops taking up only 13.1% of the land area of the Cerrado biome [49]. Future studies using GeoWEPP can validate the model across a greater variation in types and density of natural vegetation cover since it has been shown in more arid environments such as Brazil's northeast region that denser vegetation cover is associated with lower erosion metrics and greater soil carbon [50]. Natural vegetation buffers in the Cerrado confer ecosystem service benefits such as biodiversity and improved soil and water quality [51].…”

Section: Future Directions For Sustainable Agricultural Developmentmentioning

confidence: 97%

Using the GeoWEPP Model to Predict Water Erosion in Micro-Watersheds in the Brazilian Cerrado

et al. 2023

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The GeoWEPP model has estimated water and soil losses caused by erosion at the watershed level in different parts of the world. However, this model was developed and its parameters have been adjusted for temperate climates, which are different from tropical climates such as those found in Brazil. Our study evaluated the performance of the GeoWEPP model in estimating soil erosion in three micro-watersheds in the Cerrado (i.e., savannah) of southeastern Mato Grosso state, Brazil. Major land uses modeled were soybean and corn cultivation, traditional pasture, and native vegetation. Input parameters for the GeoWEPP model involved climate, soil, land use and management, and topography. GeoWEPP was calibrated with input parameters for soil erodibility specified as interrill and rill soil erosion, soil critical shear stress, and saturated hydraulic conductivity obtained experimentally and estimated by internal routine equations of the GeoWEPP model. Soil losses observed in micro-watersheds with agriculture, pasture, and native vegetation were 0.11, 0.06, and 0.10 metric tons per hectare per year, respectively. GeoWEPP best modeled soil erosion for native vegetation and pasture, while over-estimating that for crops. Surface runoff was best modeled for crops versus native vegetation and pasture. The GeoWEPP model performed better when using soil erodibility input parameters.

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Section: Future Directions For Sustainable Agricultural Developmentmentioning

confidence: 97%

Using the GeoWEPP Model to Predict Water Erosion in Micro-Watersheds in the Brazilian Cerrado

et al. 2023

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“…Abdelhafid et al [3] utilized a multivariate point-line equation to assess the relationship between Landsat imagery and soil texture, dynamically analyzing desertification in the Nemamcha region and concluding there was a strong correlation between soil indicators and surface soil sand content, thereby indicating an increase in desertification signs. Maria et al [4] investigated the impacts of rainfall intensity on soil properties in Brazilian desertification areas using simulated rainfall and discovered that rainfall intensity significantly affects runoff time and accelerates soil erosion rates. Wang et al [5] extracted desertification land information based on Landsat data and analyzed the spatiotemporal variation characteristics of desertification in the eastern part of the Helan Mountain region in Ningxia using a centroid model.…”

Section: Introductionmentioning

confidence: 99%

A New Large-Scale Monitoring Index of Desertification Based on Kernel Normalized Difference Vegetation Index and Feature Space Model

Guo,

Zhang,

et al. 2024

Remote Sensing

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As a new vegetation monitoring index, the KNDVI has certain advantages in characterizing the evolutionary process of regional desertification. However, there are few reports on desertification monitoring based on KNDVI and feature space models. In this study, seven feature parameters, including the kernel normalized difference vegetation index (KNDVI) and Albedo, were introduced to construct different models for desertification remote-sensing monitoring. The optimal desertification remote-sensing monitoring index model was determined with the measured data; then, the spatiotemporal evolution pattern of desertification in Gulang County from 2013 to 2023 was analyzed and revealed. The main conclusions were as follows: (1) Compared with the NDVI and MSAVI, the KNDVI showed more advantages in the characterization of the desertification evolution process. (2) The point–line pattern KNDVI-Albedo remote-sensing index model had the highest monitoring accuracy, reaching 94.93%, while the point–line pattern NDVI-TGSI remote-sensing monitoring index had the lowest accuracy of 54.38%. (3) From 2013 to 2023, the overall desertification situation in Gulang County showed a trend of improvement with a pattern of “firstly aggravation and then alleviation.” Additionally, the gravity center of desertification in Gulang County first shifted to the southeast and then to the northeast, indicating that the northeast’s aggravating rate of desertification was higher than in the southwest during the period. (4) From 2013 to 2023, the area of stable desertification in Gulang County was the largest, followed by the slightly weakened zone, and the most significant transition area was that of extreme desertification to severe desertification. The research results provide important decision support for the precise monitoring and governance of regional desertification.

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“…The movement of water, the relationship between precipitation, runoff, and infiltration, as well as the way of managing water are relying on new insights resulting from the biohydrological interpretations. As such, the role of vegetation in reducing erosion (e.g., Levia et al, 2017;Zore et al, 2022), retaining precipitation (e.g., Chen and Jim, 2008;Wu et al, 2020), reducing runoff (e.g., Zabret and Šraj, 2015;Zabret and Šraj, 2019;Selbig et al, 2022) and increasing infiltration (e.g., Cui et al, 2022;Teixeira Lins et al, 2023) has been recognized and used as the way for mitigating the climate change impact. Additionally, the use of vegetation and its role in water management has been widely recognized in concepts of green infrastructure (e.g., Matthews et al, 2015;Vargas-Hernandez and Zdunek-Wielgołaska, 2021), naturebased solutions (e.g., Kato-Huerta and Geneletti, 2022;Zölch et al, 2017), and sponge cities (e.g., Yuan et al, 2022;Zhang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Temporal response of urban soil water content in relation to the rainfall and throughfall dynamics in the open and below the trees

Zabret

Sapač

Šraj

2023

Journal of Hydrology and Hydromechanics

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Rainfall interception process is an important part of the biohydrological cycle, in which vegetation plays an important role by regulating the amount and dynamics of rainfall reaching the ground. In this paper, an event-based analysis is performed to discuss the influence of vegetation on dynamic of temporal response of soil volumetric water content (VWC) in the upper soil layer during rainfall events. More specifically, six events that occurred between 19 November 2021 and 30 June 2022, characterized by different hydro-meteorological and vegetation conditions, are analyzed based on continuous measurements of VWC in the open and below groups of two deciduous (Betula pendula Roth.) and two coniferous trees (Pinus nigra Arnold), as well as rainfall in the open and throughfall on an urban experimental plot in Ljubljana, Slovenia. VWC values at the upper depth (16 cm) were the highest under the birch tree, followed by the location in the open and under the pine tree. However, in the lowest depth (74 cm) VWC values were the lowest under the birch tree. VWC responses to rainfall and throughfall showed seasonal patterns related to the pre-event wetness conditions, with a faster occurrence of maximum VWC values in the leafless period. Additionally, rainfall amount and its dynamics during the event significantly affect the response, as VWC in general reaches its peak after the occurrence of more intense rainfall. Such an event-based analysis, offering an insight into the dynamics of the event development, is crucial and very beneficial for understanding of the biohydrological processes.

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Influence of vegetation cover and rainfall intensity on soil attributes in an area undergoing desertification in Brazil

Cited by 9 publications

References 43 publications

Using the GeoWEPP Model to Predict Water Erosion in Micro-Watersheds in the Brazilian Cerrado

Using the GeoWEPP Model to Predict Water Erosion in Micro-Watersheds in the Brazilian Cerrado

A New Large-Scale Monitoring Index of Desertification Based on Kernel Normalized Difference Vegetation Index and Feature Space Model

Temporal response of urban soil water content in relation to the rainfall and throughfall dynamics in the open and below the trees

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