Linking Soil Erosion Modeling to Landscape Patterns and Geomorphometry: An Application in Crete, Greece

Soil erosion is a severe and continuous environmental problem caused mainly by natural factors, which can be enhanced by anthropogenic activities. The morphological relief with relatively steep slopes, the dense drainage network, and the Mediterranean climate are some of the factors that render the Paleochora region (South Chania, Crete, Greece) particularly prone to soil erosion in cases of intense rainfall events. In this study, we aimed to assess the correlation between soil erosion rates estimated from the Revised Universal Soil Loss Equation (RUSLE) and the landscape patterns and to detect the most erosion-prone sub-basins based on an analysis of morphometric parameters, using geographic information system (GIS) and remote sensing technologies. The assessment of soil erosion rates was conducted using the RUSLE model. The landscape metrics analysis was carried out to correlate soil erosion and landscape patterns. The morphometric analysis helped us to prioritize erosion-prone areas at the sub-basin level. The estimated soil erosion rates were mapped, showing the spatial distribution of the soil loss for the study area in 2020. For instance, the landscape patterns seemed to highly impact the soil erosion rates. The morphometric parameter analysis is considered as a useful tool for delineating areas that are highly vulnerable to soil erosion. The integration of three approaches showed that there is are robust relationships between soil erosion modeling, landscape patterns, and morphometry.

Global analysis of support practices in USLE-based soil erosion modeling

Support practices (SPs) influence the magnitude of soil loss and can be readily influenced by human interventions to mitigate soil loss. The SPs factor is expressed as the P-factor in the widely used soil erosion model – the universal soil loss equation (USLE) – and its revised version. Although the effects of SPs on soil erosion are well recognized, the quantification of the P-factor for soil loss modeling remains challenging. This limitation of the P-factor particularly restricts the applicability of USLE-based models at large scales. Here, we analyzed the P-factor values in USLE-based models from 196 published articles. The results were as follows: (a) an increasing trend in the number of studies has been observed in recent years, especially at large scales; (b) the P-factor values for paddy fields, orchards, and croplands were 0.16 ± 0.15, 0.47 ± 0.12, and 0.49 ± 0.21, respectively, and in terms of different types of SPs, the P-factor values for terracing, contouring, and strip-cropping were 0.28 ± 0.18, 0.52 ± 0.24, and 0.49 ± 0.28, respectively; (c) various methods have been developed for P-factor qualification, although the methods that consider SP conditions were most frequently used in studies with relatively smaller areas (< 100 km2), suggesting that USLE-based models are in need of improvement via the quantification of the P-factor, particularly with respect to the regional and global scale; and (d) further improvements of the P-factor for soil erosion modeling should concentrate on building P-factor datasets at the regional level according to data on the effectiveness of SPs on soil loss control based on field experiments in published articles, using advanced image processing techniques based on higher-resolution satellite imagery and developing proxy indicators for P-factors at large scales.

Soil Erosion Modelling at Watershed Level in Indonesia: a Review

Soil erosion is one of the most serious degradation problems in the world, so in Indonesia. The average level of global soil erosion ranges from 12-15 Ton/ha/yr, or it can be said that there is a surface soil loss of 0.90-0.95 mm of land. While the watershed in Indonesia is 458 in which 60 are critically heavy, 222 critical and 176 potentially critical. An action is needed to reduce erosion rates which is one of the causes of damage to the watershed. Soil erosion modeling is a method used in estimating the amount of soil erosion that occurs in an area. Various models of soil erosion are developed with the aim of producing precise erosion estimates. This study will discuss soil erosion modeling (definition, classification of models and proceed) and a review of erosion assessment models that are widely used in Indonesia (USLE, MUSLE, RUSLE, and SWAT). By knowing each erosion estimation model, hope can be able to choose the right model according to the study to be conducted.