Corine Land Cover

Girard, Michel‐Claude; Girard, Colette; Courault, Dominique; Gilliot, Jean-Marc; Loubersac, Lionel; Meyer-Roux, Jean; Monget, Jean‐Marie; Séguin, Bernard; Rao, Nitya

doi:10.1201/9780203741917-19

Cited by 7 publications

(3 citation statements)

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“…the CORINE Land Cover data (https://land.copernicus. eu, last access: 1 November 2023) (Girard et al, 2018) form the European inventory of land cover that was considered for defining vegetation interception and soil infiltration coefficients, spatial evapotranspiration flux, and root cohesion for landslide stability;…”

Section: Model Initializationmentioning

confidence: 99%

CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale

Abbate,

Mancusi,

Apadula

et al. 2024

Nat. Hazards Earth Syst. Sci.

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Abstract. This work presents the new model called CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment), a tool for geo-hydrological hazard evaluation. CRHyME is a physically based and spatially distributed model written in the Python language that represents an extension of the classic hydrological models working at the basin scale. CRHyME's main focus consists of simulating rainfall-induced geo-hydrological instabilities such as shallow landslides, debris flows, catchment erosion and sediment transport into a river. These phenomena are conventionally decoupled from a hydrological routine, while in CRHyME they are simultaneously and quantitatively evaluated within the same code through a multi-hazard approach. CRHyME is applied within some case studies across northern Italy. Among these, the Caldone catchment, a well-monitored basin of 27 km2 located near the city of Lecco (Lombardy), was considered for the calibration of solid-transport routine testing, as well as the spatial-scale dependence related to digital terrain resolution. CRHyME was applied across larger basins of the Valtellina (Alps) and Emilia (Apennines) areas (∼2600 km2) which have experienced severe geo-hydrological episodes triggered by heavy precipitation in the recent past. CRHyME's validation has been assessed through NSE (Nash–Sutcliffe efficiency) and RMSE (root mean square error) hydrological-error metrics, while for landslides the ROC (receiver operating characteristic) methodology was applied. CRHyME has been able to reconstruct the river discharge at the reference hydrometric stations located at the outlets of the basins to estimate the sediment yield at some hydropower reservoirs chosen as a reference and to individuate the location and the triggering conditions of shallow landslides and debris flows. The good performance of CRHyME was reached, assuring the stability of the code and a rather fast computation and maintaining the numerical conservativity of water and sediment balances. CRHyME has shown itself to be a suitable tool for the quantification of the geo-hydrological process and thus useful for civil-protection multi-hazard assessment.

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Section: Model Initializationmentioning

confidence: 99%

CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale

Abbate,

Mancusi,

Apadula

et al. 2024

Nat. Hazards Earth Syst. Sci.

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“…The main goal was to create a set of "hazard maps" using the critical rainfall ratio rcrit varying the precipitation duration d. In this regard, four scripts written in Python language were created: 1_SOIL_Elaboration.py, 2_DCA_Elaboration.py, 3_SLEM_Model.py, and 4_TR_Evaluation.py. 1_SOIL_Elaboration.py: Preparatory processing of the soil data was carried out to evaluate the key parameters required for rcrit computation: the saturated permeability Ksat, the soil thickness ht, the friction angle φ, the soil and root cohesion Cs and Cr, and the vegetation surcharge W. Worldwide and national databases and literature studies [88,90,92,93] were investigated to retrieve these parameters for the investigated area, as depicted in Figure 6. More precisely, the Soil Grids database [88] was considered for retrieving soil texture distribution across the investigated area, assessing the % of fine (sand, silt, and clay) and coarse soils, and extracting the predicted shallow soil thickness ht.…”

Section: Python Scripts and Model Parameters Derivationmentioning

confidence: 99%

“…Biomass influence on soil stability was taken into account, including the root cohesion Cr and the vegetation surcharge 𝑊 according to [95,96]. Because these parameters are related to vegetation coverage, the Corine Land Cover (𝐶𝐿𝐶) [93] map was included in the model to spatially distribute these quantities across the catchment. The contingency Table 2 reports the relation between some 𝐶𝐿𝐶 categories and the 𝐶 𝑟 and 𝑊 values retrieved from the literature.…”

Section: Python Scripts and Model Parameters Derivationmentioning

confidence: 99%

SLEM (Shallow Landslide Express Model): A Simplified Geo-Hydrological Model for Powerlines Geo-Hazard Assessment

Abbate,

Mancusi

2024

Water

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Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (rcrit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from rcrit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards.

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Evaluation of crop yield simulations of an eco-hydrological model at different scales for Germany

Gottschalk

Lüttger

Huang

et al. 2018

Field Crops Research

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Corine Land Cover

Cited by 7 publications

References 0 publications

CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale

CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale

SLEM (Shallow Landslide Express Model): A Simplified Geo-Hydrological Model for Powerlines Geo-Hazard Assessment

Evaluation of crop yield simulations of an eco-hydrological model at different scales for Germany

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