Impacts of climate change on wind erosion in Southern Africa between 1991 and 2015

Zhao, Chaonan; Zhang, Hanbing; Wang, Man; Jiang, Hong; Peng, Jian; Wang, Yanglin

doi:10.1002/ldr.3895

Cited by 26 publications

(14 citation statements)

References 79 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Zhao et al (2021) investigated the impacts of climate change on wind erosion in Southern Africa by implementing the RWEQ to conduct an average wind erosion modulus for each year of the period 1991–2015, to perform a trend analysis. The fluctuation of the wind erosion dynamics from 2005 to 2015 are in good agreement with our annual modeled outcome.…”

Section: Discussionmentioning

confidence: 99%

“…In arid and semi‐arid regions wind erosion accounts for 46% of total land degradation (Zheng, 2009). Wind erosion is also a threat to Southern Africa favored by dry climates and seasonal droughts, affecting natural and anthropogenic‐influenced sensitive biomes (Huang et al, 2016; Zhao et al, 2021). Against a backdrop of increasing population in the area and regional food production already reaching its natural limits, wind erosion‐induced declines in soil fertility will put further pressure on crop production and ecosystem services and drive up economic costs (Department of Environmental Affairs, 2014; Kirui & Mirzabaev, 2014; Kotze & Rose, 2015).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spatiotemporal variability of the potential wind erosion risk in Southern Africa between 2005 and 2019

2023

View full text Add to dashboard Cite

Regional assessments of the wind erosion risk are rare and vary due to the methods used and the available data to be included. The adaptation of existing methods has the advantage that the results can be compared directly. We adopted an already successfully applied methodology (ILSWE—applied in East Africa), to investigate the spatiotemporal variability of the wind erosion risk between 2005 and 2019 in Southern Africa. The approach integrates climatic variables, a vegetation index, and soil properties to describe the potential impact of wind erosion at the landscape scale. The annual and seasonal variability is determined by the vegetation cover, whereas droughts and strong El Niño events had only regional effects. We estimated that 8.3% of the study area experiences a moderate to elevated wind erosion risk over the 15‐year period with annual and inter‐annual fluctuations showing a slight upward trend. In general, the desert and drylands in the west have the highest proportion of risk areas, the moist forests in the east are characterized by a very low risk of wind erosion, while the grasslands, shrublands, and croplands in the interior most likely react to changes of climatic conditions. The validation process is based on a comparison with the estimated frequency of dust storms derived from the aerosol optical depth and angstrom exponent and revealed an overall accuracy of 65%. The results of this study identify regions and yearly periods prone to wind erosion to prioritize for further analysis and conservation policies for mitigation and adaptation strategies.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatiotemporal variability of the potential wind erosion risk in Southern Africa between 2005 and 2019

2023

View full text Add to dashboard Cite

show abstract

“…The SC was evaluated by the revised universal soil loss equation model (RUSLE) (Renard et al, 1991;Zhang et al, 2021). The SL was evaluated by the revised wind erosion equation model (RWEQ) (Lin et al, 2021;Lyu et al, 2021;Zhao et al, 2021). The HQ was evaluated by the habitat quality module of the InVEST model (Dou et al, 2020;Wang et al, 2022).…”

Section: Ecosystem Services Assessmentmentioning

confidence: 99%

Linking regional sustainable development goals with ecosystem services to identify ecological security patterns

Lyu

Wang

et al. 2022

Land Degrad Dev

View full text Add to dashboard Cite

Ecological security patterns (ESPs) have become an important spatial approach to alleviate the contradiction between ecological protection and economic development. The identification of ecological sources is the primary part of studying ESPs, and methods based on ecosystem services (ESs) have been widely used. However, the current method of simply overlaying ESs for ecological source identification has difficulty supporting different regional decision-making needs of the target. Taking the West Liaohe River basin in China as an example, this study aims at developing four regional sustainable development goals (RSDGs) of carbon neutrality, water security, soil security, and biodiversity protection. Six ESs, including net primary production (NPP), water retention (WR), water purification (WP), soil conservation (SC), soil loss by wind (SL), and habitat quality (HQ), in the West Liaohe River basin from 2010 to 2020 were evaluated. Based on the current mainstream research paradigm of 'source identification-resistance surface construction-corridor extraction-safety pattern identification', combined RSDGs and ESs, the minimum cumulative resistance (MCR) model was used to identify the West Liaohe River basin development goals.The pattern of ecological security was discussed, and the identification, optimization, and construction plan of the regional comprehensive ESP were discussed in combination with the actual situation of the region. The study found that simply overlaying ESs to identify ecological sources leads to the neglect of some areas that provide key ESs, and it is difficult to directly support regional ecological protection decisions under different objectives, while a multiobjective-oriented comprehensive ecological security pattern helps to promote ESs and their relationships. The research results will help to improve the understanding of the ESP and provide a basis for the ecological protection and restoration of the basin and the optimization of the spatial structure to promote the sustainable development of the 'social-economic-ecological' complex system in the West Liaohe River basin.

show abstract

“…Sand transport rate is a measure of the capacity of transporting sand particles by wind. It is the amount of sand carried by the air flow through the unit width in unit time, also known as the solid flow of drifting sand flux (Lancaster et al, 1996;Zhao et al, 2021). There are many factors affecting the sand transport rate, including wind force, density, particle size, specific gravity and shape of sand, as well as moisture rate of sand, earth surface features and atmosphere stability (Kok et al, 2012;Miao et al, 2012;Avecilla et al, 2017;Favaro et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Characteristics of Sand Transport on the Surface of Transverse Ridge Microtopography

Jia

et al. 2022

Preprint

View full text Add to dashboard Cite

Through wind tunnel experiments, we measured the surface drifting sand flux structure and sand transport rate at height of 0~70 cm on a bed surface under conditions of ridge microtopography with different height and different spacing. The results show that the percentage of sand transport in 0~10 cm layer above the bed surface is significantly reduced under ridge microtopography condition compared with no ridges condition. Under ridge microtopography condition, the percentage of sand transport in 0~10 cm layer decreases with the increase of ridge height, while it generally increases with the increase of ridge spacing and wind velocity. Under no ridges condition, the sand transport rate decreases in a power function law with the increase of height. The variation of sand transport rate with height under ridge microtopography condition could be divided into two cases: one shows that sand transport rate decreases exponentially with the increase of height, while the other shows that sand transport rate increases with the increase of height under a certain height, and above the certain height it decreases exponentially with the increase of height, known as “elephant nose” effect which seems similar to the structure of drifting sand flux in Gobi desert. For all the ridge heights and spacings, the total sand transport rate at height of 0~70 cm increases with the increase of friction velocity in a power function law, and it increases with the increase of ridge spacing. The simulation of the drifting sand flux structure and the relationship between sand transport rate and height shows that the ridge microtopography reduces the sand transport ratio of near surface air flow compared with no ridges condition. The results will contribute to studies on recognizing the process and mechanism of soil wind erosion in ridge farmland.

show abstract

Impacts of climate change on wind erosion in Southern Africa between 1991 and 2015

Cited by 26 publications

References 79 publications

Spatiotemporal variability of the potential wind erosion risk in Southern Africa between 2005 and 2019

Spatiotemporal variability of the potential wind erosion risk in Southern Africa between 2005 and 2019

Linking regional sustainable development goals with ecosystem services to identify ecological security patterns

Characteristics of Sand Transport on the Surface of Transverse Ridge Microtopography

Contact Info

Product

Resources

About