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

Abstract

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.

Modelling the event‐based hydrological response of olive groves on steep slopes and clayey soils under mulching and tillage management using the SCS‐CN, Horton and USLE‐family models

“…Several authors proposed C‐values for cultivation operations in olive groves (Moreira Madueño, 1991, 0.4; Kok et al, 1995, 0.54; Giraldez et al, 1989, 0.4 for conventional tillage and 0.45 for no tillage; Gomez et al, 2003, 0.41 for conventional and no tillage). Gómez et al (2021) found a range between 0.12 and 0.50 for the different soil management declared by farmers in Southern Spain, while Brini et al (2021) and Chafai et al (2020) proposed for olive groves generic values of 0.2 and 0.5, respectively. Folly et al (1996) used much higher C‐values (0.7) for olive areas, and López‐Vicente and Navas (2009) even suggested a mean C‐factor of one for olive trees in a catchment of Spanish pre‐Pyrenees.…”

System Dynamics Modeling for Estimating the Locations of Road Icing Using GIS

“…2021, 11, x FOR PEER REVIEW 4 of 23 simulation for disaster assessment [30]. They detect topographic hazards using GIS models [31] or analyze hazards on slopes in cold regions [32]. In addition, they evaluate and estimate the size of a hazard in high-risk areas, such as roads in hazardous ranges, using spatial data on GIS [33,34].…”

Assessment of Water-Induced Soil Erosion as a Threat to Natura 2000 Protected Areas in Crete Island, Greece

“…Unfortunately, sub-hourly rainfall rate records from ground-based meteorological stations are rarely available in the Greek territory. Therefore, simplified mathematical equations have been developed in order to estimate rainfall erosivity based on daily or monthly rainfall data derived from gridded satellite and reanalysis products [79][80][81]. The higher the rainfall intensity, the greater the magnitude of soil loss.…”