Uncovering causes and effects of desertification using a Leopold matrix in Binh Thuan Province, Vietnam

Hai, Le Trinh; Gobin, Anne; Hens, Luc

doi:10.1080/10042857.2014.883052

Cited by 7 publications

(9 citation statements)

References 13 publications

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“…Based on local knowledge of environmental contributing factors to risk of desertification in the Binh Thuan Province of Vietnam (Hai et al, 2013(Hai et al, , 2014(Hai et al, , 2016, we included indicators for climate, soil-landscape classification, vegetation, water resources management, population density and human activities into a common framework. Each of these factors required a different methodology since different processes are involved that relate to land degradation and desertification.…”

Section: Methodsmentioning

confidence: 99%

“…We hypothesised that the area currently at severe risk of desertification can be explained by different socio-economic and biophysical factors, using local knowledge of environmental contributing factors as elucidated by Hai et al (2013Hai et al ( , 2014Hai et al ( , 2016. The objectives were to develop a framework that integrates the important biophysical and socio-economic factors contributing to the risk of desertification, spatially delineate areas at risk of desertification in the year 2010 as a baseline, and demonstrate the developed framework for potential vulnerable areas under projected climate change and population growth.…”

Section: Introductionmentioning

confidence: 99%

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Spatial indicators for desertification in southeast Vietnam

Hiền

Gobin

Hương

2019

Nat. Hazards Earth Syst. Sci.

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Abstract. Desertification is influenced by different factors that relate to climate, soil, topography, geology, vegetation, human pressure, and land and water management. The quantification of these factors into spatially explicit indicators and subsequent evaluation provides for a framework that allows us to identify areas currently at risk of desertification and to evaluate important contributing biophysical and socio-economic factors. Based on local knowledge of environmental contributing factors to the risk of desertification in the Binh Thuan Province of southeast Vietnam, a baseline 2010 map showed that 14.4 % of the area, mainly along the coast and in the northeast, is desertified with another 35.4 % at severe risk of desertification. The Vietnamese Ministry of Natural Resource and Environment has defined the area with a ratio of rainfall to evapotranspiration smaller or equal to 0.65, which equals 1233 km2 or 15 % of the province, as desertified area, which corresponds well with the baseline 2010 map. The developed framework incorporates the important contributing factors and therefore allows for decision support in a “what if” structure and for the projection of potentially vulnerable areas under future scenarios. With projected climate change and population growth, the desertified area is expected to increase by 122 % (or 137 850 ha) towards 2050. The developed methodology can be extended to neighbouring provinces that experience similar sensitivities to desertification.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial indicators for desertification in southeast Vietnam

Hiền

Gobin

Hương

2019

Nat. Hazards Earth Syst. Sci.

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“…Based on the major factors that determine environmental sensitivity to desertification in the Binh Thuan Province of Vietnam (Hai et al, 2013(Hai et al, , 2014(Hai et al, , 2016 we included indicators for climate, soil-landscape, vegetation, water resources management and human activities into a common framework. Local knowledge on these different contributing factors relate to resources management and pressures from human population densities.…”

Section: Methodsmentioning

confidence: 99%

“…A multi-factorial approach was developed and based on local knowledge of environmental processes as documented in Hai et al (2013Hai et al ( , 2014Hai et al ( , 2016, thereby including socio-economic and bio-physical factors. We hypothesised that the area currently at severe risk of desertification can be explained by the different socio-economic and bio-physical factors.…”

Section: ;mentioning

confidence: 99%

Spatial indicators for desertification in south-east Vietnam

Hiền¹,

Gobin²,

Hương³

2019

Preprint

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Abstract. Desertification is influenced by different factors that relate to climate, soil, topography, geology, vegetation, human pressure and land and water management. The quantification of these factors into spatially explicit indicators and subsequent evaluation provides for a framework that allows to identify areas currently at risk of desertification and to evaluate important contributing bio-physical and socio-economic factors. Applied to south-east Vietnam, a baseline 2010 map showed that 14.4 % of the area, mainly along the coast and in the north east, is desertified with another 35.4 % at severe risk of desertification. The Ministry of Environment has defined the area with a ratio of rainfall to evapotranspiration smaller or equal to 0.65, which equals 1,233 km2 or 15 % of the province, as desertified area. The developed framework allows for decision support in a what if structure, and for the projection of potentially vulnerable areas under future scenarios. With projected climate change and current population growth the desertified area is expected to increase with 122 % (or 137,850 ha) towards 2050. The methodology can be extended to neighbouring provinces that experience similar sensitivities to desertification.

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“…Initially, Leopold matrix is a semi-qualitative environmental impact assessment method pioneered in the last century by Leopold, Clarke, Hanshaw, and Balsley (1971). So, by facilitating the interactive participation of varied, hierarchical and antagonistic experts with stakeholder knowledge or opinions as valid input to research in an inexact research area, this matrix is an adequate tool according to Hai, Gobin, and Hens (2014). But, its most distinctive feature is his allowance to meta-analysis of issues to be investigated.…”

Section: Importance and Significance Calculationmentioning

confidence: 99%

Dynamic Matrix for an Adaptive Environment Management in Mining: A Feed-engineering Alternative?

Lagnika

Häusler

Glaus

2018

EMSD

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Environment impacts are usually determined by quantification or an evaluation system derived from several methodologies including environmental assessment, matrices, and data cross-referencing. This study uses a dataset obtained from validated mining Environmental Impact Assessments (EIAs), some monitoring reports and scientific insights on open-pit mines (OPM). The purpose here is to build a dynamic matrix system over time to facilitate a systemic evaluation of environmental impacts and to find in-depth preventive measures in any OPM. The four dynamic matrices are built with qualitative and numerical values in both magnitude and significance terms. As one of the issues is to minimize negative risks in OPMs, one outcome points out the environmental factors of mining operations sensitive to the variations over time and the variability of the parameters themselves. The results show secondly that the data (qualitative and quantitative) vary from EIA stage to a post EIA status like activities or environmental factors numbers. Thirdly, the impact of activities on each part of environment components and the incidence of all activities during the mines’ life cycle is easier to identify whatever the data density. In the fourth line, this paper indicates that the dynamic matrix in an optimal alternative in the process of determining preventive measures to mitigate the risks and the need for an interactive environmental follow-up program in mining or similar industry. This approach reduces the following-up monitoring weaknesses and allows managers, as a multi-criterion decision-making approach, to take enlightened actions.

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Uncovering causes and effects of desertification using a Leopold matrix in Binh Thuan Province, Vietnam

Cited by 7 publications

References 13 publications

Spatial indicators for desertification in southeast Vietnam

Spatial indicators for desertification in southeast Vietnam

Spatial indicators for desertification in south-east Vietnam

Dynamic Matrix for an Adaptive Environment Management in Mining: A Feed-engineering Alternative?

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