Estimating potential wind erosion of agricultural lands in northern China using the Revised Wind Erosion Equation and geographic information systems

Guo, Zhongling; Zobeck, Ted M.; Zhang, K.; Li, F.

doi:10.2489/jswc.68.1.13

Cited by 60 publications

(51 citation statements)

References 25 publications

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“…The equation is relatively simple and requires a limited amount of input data, which makes it suitable for upscaling (Zobeck et al, ; Youssef et al, ; Guo et al, ). Wind is the basic driving force in the model.…”

Section: Methodsmentioning

confidence: 99%

“…A number of studies have found good agreement between the yields predicted by RWEQ and the field measures (Buschiazzo & Zobeck, ; Youssef et al, ). The significant relationship between the observed and predicted transport capacity and soil loss (Zobeck et al, ), as well as the limited need for input data compared with mechanistic wind erosion models like the Wind Erosion Prediction System (Hagen, ), makes RWEQ a suitable tool for a large‐scale prediction of the wind erosion potential (Zobeck et al, ; Youssef et al, ; Guo et al, ).…”

Section: Introductionmentioning

confidence: 99%

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A New Assessment of Soil Loss Due to Wind Erosion in European Agricultural Soils Using a Quantitative Spatially Distributed Modelling Approach

et al. 2016

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Field measurements and observations have shown that wind erosion is a threat for numerous arable lands in the European Union (EU). Wind erosion affects both the semi-arid areas of the Mediterranean region as well as the temperate climate areas of the northern European countries. Yet, there is still a lack of knowledge, which limits the understanding about where, when and how heavily wind erosion is affecting European arable lands. Currently, the challenge is to integrate the insights gained by recent pan-European assessments, local measurements, observations and field-scale model exercises into a new generation of regional-scale wind erosion models. This is an important step to make the complex matter of wind erosion dynamics more tangible for decision-makers and to support further research on a field-scale level. A geographic information system version of the Revised Wind Erosion Equation was developed to (i) move a step forward into the largescale wind erosion modelling; (ii) evaluate the soil loss potential due to wind erosion in the arable land of the EU; and (iii) provide a tool useful to support field-based observations of wind erosion. The model was designed to predict the daily soil loss potential at a ca. 1 km 2 spatial resolution. The average annual soil loss predicted by geographic information system Revised Wind Erosion Equation in the EU arable land totalled 0·53 Mg ha À1 y À1 , with the second quantile and the fourth quantile equal to 0·3 and 1·9 Mg ha À1 y À1 , respectively. The crossvalidation shows a high consistency with local measurements reported in literature.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A New Assessment of Soil Loss Due to Wind Erosion in European Agricultural Soils Using a Quantitative Spatially Distributed Modelling Approach

et al. 2016

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show abstract

“…The 1 h meteorological records, soils characteristics and the soil coverage measurements were used to estimate 10 days wind erosion with a spreadsheet version of RWEQ (Fryrear et al, 1998;Guo et al, 2013). The RWEQ was found to be adequate to predict wind erosion in the semiarid Pampas of Argentina (Buschiazzo and Zobeck, 2008).…”

Section: Field Measurement and Wind Erosion Estimationmentioning

confidence: 99%

Soil coverage evolution and wind erosion risk on summer crops under contrasting tillage systems

Méndez

Buschiazzo

2015

Aeolian Research

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“…Similar conclusions have been made for varies areas; for example, Miao et al (2012) showed that regions with high levels of wind erosion had the lowest vegetative cover in the Yellow River Basin. Guo et al (2013) applied the Revised Wind Erosion Equation (RWEQ) for the agricultural lands near Inner Mongolia, and indicated that conservation tillage could eliminate the chances of heavy wind erosion for the study area. From the analysis of the NDVI data, Tan and Li (2015) confirmed that the shelter forests which were aimed at preventing the ongoing desertification, had achieved (2b) Stoch Environ Res Risk Assess significant improvement for the study area that covers 6.9 million km 2 in north China.…”

Section: Discussionmentioning

confidence: 99%

Estimation of desertification risk from soil erosion: a case study for Gansu Province, China

Zhang

McBean

2015

Stoch Environ Res Risk Assess

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Desertification is of increasing concern over recent decades. A methodology based on soil erosion from water and wind is developed, to evaluate desertification risk. The approach includes utilization of both the Universal Soil Loss Equation and the Wind Erosion Equation developed by California Air Resources Board. The desertification risk is mapped using ArcGIS techniques and is compared with the assessment from the environmentally sensitive areas model. The methodology, applied to Gansu as a case study, one of the driest regions in China, indicates that severe desertification is occurring in the Province, particularly through wind erosion. Approximately one-half the land areas in Gansu will experience high risk of desertification, especially in the western regions. The mean water and soil erosion in Gansu is 0.05 tonnes/ha and 44 tonnes/ha per year, respectively. The maximum per hectare soil loss through wind erosion is estimated as thirty times larger compared with water erosion. Improvements in vegetative cover as well as cropping methods would significantly reduce the high risk of desertification from 46 % of Gansu to less than 10 %. The analysis also shows that desertification is sensitive to climate and terrain slopes, and that human influences such as land use and population density can aggravate the degrees of desertification.

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Estimating potential wind erosion of agricultural lands in northern China using the Revised Wind Erosion Equation and geographic information systems

Cited by 60 publications

References 25 publications

A New Assessment of Soil Loss Due to Wind Erosion in European Agricultural Soils Using a Quantitative Spatially Distributed Modelling Approach

A New Assessment of Soil Loss Due to Wind Erosion in European Agricultural Soils Using a Quantitative Spatially Distributed Modelling Approach

Soil coverage evolution and wind erosion risk on summer crops under contrasting tillage systems

Estimation of desertification risk from soil erosion: a case study for Gansu Province, China

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