On the use of the Land Degradation Neutrality concept in mediterranean watersheds for land restoration and erosion counteraction

Sayah, Mario J. Al; Abdallah, Chadi; Khouri, Michel; Nedjaï, Rachid; Darwich, Talal

doi:10.1016/j.jaridenv.2021.104465

Cited by 12 publications

(5 citation statements)

References 30 publications

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“…The level of erosion that occurs is not only determined by the height of the location, but also by the K factor, soil erodibility, or the sensitivity of the soil to erosion (Sulistyo, 2015). Integration of soil erosion will be a consideration or have an impact on the occurrence of land degradation heterogeneity (Al Sayah et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Erosion Analysis in the Mrica Reservoir Catchment Area in Indonesia using the Soil Erosion Status Method

Harjadi¹

2021

For. Geo.

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The reservoir catchment area (RCA) of Mrica in Banjarnegara district is a powerplant in Central Java with a capacity of 184.5 MW. Mrica Dam, also called the dam of Great Commander General Sudirman, has seen its functions gradually decrease due to sedimentation from massive erosion that has occurred in the upland regions. RCA Mrica, with the upland area in Wonosobo district, has an area of 93,546.4 hectares, consisting of six sub-watersheds, Lumajang, Serayu upstream, Begaluh, Serayu, Tulis and Merawu. In 2017, sedimentation in the dam reached 238,236,588.20 m3/year, resulting from an erosion rate of 524,948.33 tons/year. In light of this serious erosion problem in the Mrica RCA, this study aims to estimate the distribution of the erosion level, categorised as slight, moderate and severe, using the SES (soil erosion status) formula. SES was calculated by mapping the level of each influential aspect: aspect, drainage, land cover, slope and soil texture. The calculation used SRTM (Shuttle Radar Topography Mission) satellite imagery and 2017 Landsat TM7 images. The results show slight erosion (50 tons/ha/year) in 1,468.7 ha (1.6%); moderate erosion (50-100 tons/ha/yr) in 56,258.8 ha (60.1%); and severe erosion ( 100 tons/ha/year) in 35,818.9 ha (38.29%). Sampling in the field took into account the slope class of nine classes and was repeated three times, so the number of samples taken in the field was 27. From field visits to the 27 location points, there was conformity in the results of the sensing analysis is much more than 85%”. The results of the erosion calculation using the SES method showed severe erosion of 27.9% (26,137 ha); moderate erosion of 70.2% (65,679 ha); and slight erosion =of 1.8% (1,731 ha). Further erosion calculation using the SES method needs to be compared with calculation using other methods.

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Section: Discussionmentioning

confidence: 99%

Erosion Analysis in the Mrica Reservoir Catchment Area in Indonesia using the Soil Erosion Status Method

Harjadi¹

2021

For. Geo.

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“…These actions seem particularly pertinent in light of land degradation neutrality (LDN), defined as a given contextual state whereby the amount and quality of land resources, necessary to support ecosystem functions and services and enhance food security, remains stable or increases within specified temporal and spatial scales and ecosystems. Despite being strongly encouraged at different planning and operational scales-from supra-national (e.g., UNCCD) to localstrategies addressing LDN targets are still heterogeneous and mixed in most affluent economies and require additional information to be correctly designed and developed in specific socioeconomic contexts of Southern Europe (Smetanová et al 2019;Pena et al 2020;Al Sayah et al 2021).…”

Section: The Role Of Strategic Policies In Desertification-sustainabl...mentioning

confidence: 99%

‘Old’ Territorial Disparities and ‘New’ Spatial Patterns: Unraveling the Latent Nexus between Sustainable Development and Desertification Risk in Italy

et al. 2022

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Although sustainable development and desertification risk are hegemonic concepts in environmental economics, their intimate relationship was occasionally studied and made spatially explicit. The present study contributes to fill this knowledge gap by delineating a statistical procedure that investigates, at the municipal scale in Italy, the association between two composite indexes of sustainable development (SDI) and desertification risk (ESAI). Based on a refined knowledge of the local context, results of a geographically weighted regression delineate two distinctive territorial models reflecting the mutual interplay of sustainable development and desertification risk in Italy. The level of sustainable development was negatively associated with desertification risk in Southern Italy, a region classified as ‘affected’ based on the Italian National Action Plan (NAP) to combat desertification. These findings document a traditional ‘downward spiral’ between local development and early desertification processes, suggesting that a high desertification risk is associated with local contexts having structural conditions that lead to unsustainable development, e.g., population growth, industrial development, tourism pressure, crop intensification, agricultural mechanization, and land abandonment. In non-affected regions such as Northern and Central Italy, the level of sustainable development was positively associated with desertification risk, indicating that sustainability conditions can be unable, at least in some local contexts, to assure a significant containment of environmental degradation. Policy strategies reconnecting local development with more specific environmental conservation targets in development countries are increasingly required to adapt to (and differentiate on the base of) heterogeneous local contexts.

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“…Besides, they proposed pathways towards sustainable development based on the general LDN strategies of “avoid, reduce and reverse” (Al Sayah, Abdallah, Der Sarkissian, & Abboud, 2021). Some other studies started from a diagnosis of degraded lands in the studied areas and then investigated their trends and drivers and proposed routes towards LDN following the same strategies (Al Sayah, Abdallah, Khouri, et al, 2021; Kapović Solomun et al, 2018; Mandal et al, 2021; Sims et al, 2020). This group of studies comprised discussions about the accomplishment of LDN through ample landscape reconfigurations, as for example afforestation of large areas to counterbalance degraded cropland areas, including the necessary investments (Dallimer & Stringer, 2018; Schulze et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A structural equation model of land capability and related drivers: Implications for land degradation forecasting in a tropical river basin

et al. 2023

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Land degradation is a worldwide problem with natural and anthropogenic causes. An important anthropogenic cause of land degradation is land uses that deviate from land capability, which is the “natural” use. Despite the conscience of scientists about this issue, studies are lacking that set up a quantitative nexus between land capability and related drivers. This nexus is essential because it allows anticipating changes in the drivers that promote or recede degradation. In this study, a partial least squares–path model (PLS–PM) was used to help closing this gap. The pilot study occurred in seven Paraopeba River sub‐basins located in the State of Minas Gerais (Brazil), where capability is dominated by mosaics of forests and pastures. Land capability was assessed by the ruggedness number, being inversely proportional to it. Among multiple potential drivers of land capability initially included in the model, collinearity and other consistency and performance analyses indicated the percentage of latosols and (re)forested areas, annual rainfall, and water‐related processes (e.g., weathering, nutrient leaching) as prominent in the studied region. The results linked increases of latosol and forest occupation to runoff reduction [runoff = latosol × (−0.640) + forest × (−0.156) + reforestation × (−0.379)], suggesting an attenuation of erosion by these parameters, namely gully erosion that impacts on the ruggedness number and land capability in the sequel. The weathering of carbonate rocks was also related to land capability changes because the PLS–PM model exposed a relationship between the ruggedness number and products of carbonate rock dissolution: ruggedness number = alkalinity × (−0.578) + total magnesium × (0.462) + dissolved oxygen × (−0.418). In addition to highlighting processes capable of changing land capability overtime, the model equations brought attention to measures that could improve it in the region thus preventing degradation. The measures included management practices capable to raise the soil's dissolved oxygen (e.g., through aeration) or preventing soil's magnesium deficiency (e.g., through foliar sprays). The network of cause‐and‐effect relationships set up by the PLS–PM model was finally used to elucidate about potential land use changes that would bring capability in the Paraopeba River basin towards a better status, such as conversions to pasture land. Future work is expected to further elucidate about the benefits for land capability of specific land use changes, through the testing of expected socioeconomic development scenarios.

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On the use of the Land Degradation Neutrality concept in mediterranean watersheds for land restoration and erosion counteraction

Cited by 12 publications

References 30 publications

Erosion Analysis in the Mrica Reservoir Catchment Area in Indonesia using the Soil Erosion Status Method

Erosion Analysis in the Mrica Reservoir Catchment Area in Indonesia using the Soil Erosion Status Method

‘Old’ Territorial Disparities and ‘New’ Spatial Patterns: Unraveling the Latent Nexus between Sustainable Development and Desertification Risk in Italy

A structural equation model of land capability and related drivers: Implications for land degradation forecasting in a tropical river basin

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