<abstract xmlns="http://www.w3.org/1999/xhtml">The article presents a method of selecting critical areas (4th river basin) in terms of landscape degradation, with an emphasis on water retention, from a relatively larger unit (3rd river basin). For this purpose, indicators that point directly or indirectly to soil and landscape degradation or water retention were selected with regard to the scale of processing. The indicators were processed in a multi-criteria context using principal component analysis, which, based on the spatial layout pattern of the indicators, assigns weights of importance. These weights were then subsequently used to calculate the aggregation index, which indirectly indicates the sensitivity of the area to degradation and, in particular, water retention. Two catchment areas of the 3rd order – Čížina and Kyjovka – with different soil, climatic and economic conditions were selected for the study. Among the indicators of water retention in the landscape, our analysis included the share of agricultural land in the total area, the share of arable land, the average size of the field block, soil degradation according to the degradation model, runoff curve number, potential water erosion and surface drainage. The resulting procedure can be used to evaluate smaller areas. For a more detailed solution, a number of other methods and indicators could be used, which are also outlined in the article.</abstract>

The article presents a method of selecting critical areas (4th river basin) in terms of landscape degradation, with an emphasis on water retention, from a relatively larger unit (3rd river basin). For this purpose, indicators that point directly or indirectly to soil and landscape degradation or water retention were selected with regard to the scale of processing. The indicators were processed in a multi-criteria context using principal component analysis, which, based on the spatial layout pattern of the indicators, assigns weights of importance. These weights were then subsequently used to calculate the aggregation index, which indirectly indicates the sensitivity of the area to degradation and, in particular, water retention. Two catchment areas of the 3rd order – Čížina and Kyjovka – with different soil, climatic and economic conditions were selected for the study. Among the indicators of water retention in the landscape, our analysis included the share of agricultural land in the total area, the share of arable land, the average size of the field block, soil degradation according to the degradation model, runoff curve number, potential water erosion and surface drainage. The resulting procedure can be used to evaluate smaller areas. For a more detailed solution, a number of other methods and indicators could be used, which are also outlined in the article.

The Use of Multi-Criteria Analysis for Identifying Areas Sensitive to Land Degradation and water Retention

Department of Ecology and Environmental Sciences, Faculty of Science

Ekológia (Bratislava)

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The article presents a method of selecting critical areas (4th river basin) in terms of landscape degradation, with an emphasis on water retention, from a...

The Use of Multi-Criteria Analysis for Identifying Areas Sensitive to Land Degradation and water Retention

Pubblicato online: 20 mar 2018

Pagine: 90 - 100

DOI: https://doi.org/10.2478/eko-2018-0009

Parole chiave
sensitivity analysis, landscape, degradation, retention, modelling

© 2018 Marek Bednář et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The Use of Multi-Criteria Analysis for Identifying Areas Sensitive to Land Degradation and water Retention

Pubblicato online: 20 mar 2018

Pagine: 90 - 100

DOI: https://doi.org/10.2478/eko-2018-0009

Parole chiavesensitivity analysis, landscape, degradation, retention, modelling

© 2018 Marek Bednář et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Parole chiave
sensitivity analysis, landscape, degradation, retention, modelling