High resolution spatiotemporal analysis of erosion risk per land cover category in Korçe region, Albania

Zdruli, Pandi; Karydas, Christos; Dedaj, Klarent; Salillari, Ilir; Cela, Florjana; Lushaj, Sherif; Panagos, Panos

doi:10.1007/s12145-016-0269-z

Cited by 9 publications

(6 citation statements)

References 28 publications

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“…The test showed that the simulated R values were close to the true (calculated with the 30’-interval rain intensity data), only for some months (January, May, June, July, August, October, and November), whereas for the rest of months (or for other stations) uncertainty remained unknown. Similar approaches, modified according to the local data availability and particularities, were followed also in another two case-studies conducted in Albania ( Karydas et al, 2015a , Karydas et al, 2015b , Zdruli et al, 2016 ).…”

Section: Erosion Factorsmentioning

confidence: 99%

“…In the fifth case-study (Korce, Albania), the very high density of the available soil data (one soil sample per 6.5 km 2 ) allowed for first time, downscaling the output maps to a 30-m resolution. Beyond that, the study emphasised extraction of detailed erosion statistics per land cover/use according to the CORINE nomenclature ( Zdruli et al, 2016 ).…”

Section: G2 Case-studiesmentioning

confidence: 99%

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The G2 erosion model: An algorithm for month-time step assessments

Karydas¹,

Panagos

2018

Environmental Research

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A detailed description of the G2 erosion model is presented, in order to support potential users. G2 is a complete, quantitative algorithm for mapping soil loss and sediment yield rates on month-time intervals. G2 has been designed to run in a GIS environment, taking input from geodatabases available by European or other international institutions. G2 adopts fundamental equations from the Revised Universal Soil Loss Equation (RUSLE) and the Erosion Potential Method (EPM), especially for rainfall erosivity, soil erodibility, and sediment delivery ratio. However, it has developed its own equations and matrices for the vegetation cover and management factor and the effect of landscape alterations on erosion. Provision of month-time step assessments is expected to improve understanding of erosion processes, especially in relation to land uses and climate change. In parallel, G2 has full potential to decision-making support with standardised maps on a regular basis. Geospatial layers of rainfall erosivity, soil erodibility, and terrain influence, recently developed by the Joint Research Centre (JRC) on a European or global scale, will further facilitate applications of G2.

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Section: Erosion Factorsmentioning

confidence: 99%

Section: G2 Case-studiesmentioning

confidence: 99%

The G2 erosion model: An algorithm for month-time step assessments

Karydas¹,

Panagos

2018

Environmental Research

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“…Similar studies have also been conducted in surrounding countries (Diodato, 2006;Mikoš et al, 2010;Simic Belnovic et al, 2013;Valjarević et al, 2014;Blinkov, 2015;Zdruli et al, 2016;Traykova-Pavlova et al, 2017;Bon Gregorič et al, 2018;Micić Ponjiger et al, 2021;Milentijević et al, 2021;Pandey et al, 2021). The RUSLE method in combination with GIS has been used in numerous modern works and research studies (Kouli et al, 2008;Prasannakumar et al, 2012;Tošić et al, 2013;Blackey et al, 2015;Efthimiou, 2016;Nasir and Selvakumar, 2018;Lanorte et al, 2019;Nolė et al, 2020;Polykretis et al, 2020;Milentijević et al, 2021;Sánchez Sánchez et al, 2021), which led to very satisfactory results.…”

Section: Introductionmentioning

confidence: 79%

Estimation of potential soil erosion reduction using GIS-based RUSLE under different land cover management models: A case study of Pale Municipality, B&H

Golijanin

Nikolić

Valjarević

et al. 2022

Front. Environ. Sci.

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Spatial assessment of soil erosion is an important indicator of ecological soil change and global environmental changes. This is especially true for countries with rich forest cover such as Bosnia and Herzegovina. In this study, the risk of soil erosion was assessed using the Revised Universal Soil Loss Equation (RUSLE) model and the impact of changes in the forest ecosystem, current conditions were compared with possible future forest management scenarios, and measures and solutions were proposed to reduce soil erodibility in vulnerable areas of the Pale Municipality in Bosnia and Herzegovina. The studied area is at increased risk of soil erosion due to natural conditions (mountain relief, climate change, and the frequency of extreme climatic events—drought and heavy rains, which occur more and more frequently in a short period of time) and due to anthropogenic factors, such as large-scale deforestation and conversion of mountain areas for tourism purposes, tracing and construction of ski slopes and ski resorts in general, and expansion of settlements. All this leads to threats to water conservation areas, landslides, floods, forest fires, and additional reduction of forest areas due to drying of forests and expansion of settlements. GIS as a tool provides us with a quick and accurate way to find possible solutions to problems resulting from the intensive use and inadequate monitoring. In this study, we have tried to offer possible solutions and show the benefits that can be obtained by varying the factors that affect soil erodibility and depend on vegetation cover, that is, land use (C-factor). This study presents the application of RUSLE methods in combination with GIS for the purpose of planning economic activities, such as winter tourism development in the community of Pale. An increase in soil loss due to inappropriate land use was found, with the average annual soil loss due to deforestation in the ski area increasing to 909.43 t ha−1 year−1.

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“…Several studies were conducted based on this principle. However, the spatial and temporal resolution of the images (Landsat or MODIS) in most of the existing literature is relatively low (around 30-250 m) compared to the also freely available Sentinel-2 data [32,[93][94][95][96]. Improved spatial accuracy and flyover frequency of satellite imagery leads to better erosion modeling results [97,98].…”

Section: Benefits From the Integration Of Sentinel-2 Data In Erosion Modelingmentioning

confidence: 99%

To What Extent Can a Sediment Yield Model Be Trusted? A Case Study from the Passaúna Catchment, Brazil

Sotiri

Hilgert

Durães

et al. 2021

Water

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Soil degradation and reservoir siltation are two of the major actual environmental, scientific, and engineering challenges. With the actual trend of world population increase, further pressure is expected on both water and soil systems around the world. Soil degradation and reservoir siltation are, however, strongly interlinked with the erosion processes that take place in the hydrological catchments, as both are consequences of these processes. Due to the spatial scale and duration of erosion events, the installation and operation of monitoring systems are rather cost- and time-consuming. Modeling is a feasible alternative for assessing the soil loss adequately. In this study, the possibility of adopting reservoir sediment stock as a validation measure for a monthly time-step sediment input model was investigated. For the assessment of sediment stock in the reservoir, the commercial free-fall penetrometer GraviProbe (GP) was used, while the calculation of sediment yield was calculated by combining a revised universal soil loss equation (RUSLE)-based model with a sediment delivery ratio model based on the connectivity approach. For the RUSLE factors, a combination of remote sensing, literature review, and conventional sampling was used. For calculation of the C Factor, satellite imagery from the Sentinel-2 platform was used. The C Factor was derived from an empirical approach by combining the normalized difference vegetation index (NDVI), the degree of soil sealing, and land-use/land-cover data. The key research objective of this study was to examine to what extent a reservoir can be used to validate a long-term erosion model, and to find out the limiting factors in this regard. Another focus was to assess the potential improvements in erosion modeling from the use of Sentinel-2 data. The use of such data showed good potential to improve the overall spatial and temporal performance of the model and also dictated further opportunities for using such types of model as reliable decision support systems for sustainable catchment management and reservoir protection measures.

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High resolution spatiotemporal analysis of erosion risk per land cover category in Korçe region, Albania

Cited by 9 publications

References 28 publications

The G2 erosion model: An algorithm for month-time step assessments

The G2 erosion model: An algorithm for month-time step assessments

Estimation of potential soil erosion reduction using GIS-based RUSLE under different land cover management models: A case study of Pale Municipality, B&H

To What Extent Can a Sediment Yield Model Be Trusted? A Case Study from the Passaúna Catchment, Brazil

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