In European catchments, rainfall and overland flowtrigger erosive processes that could result in soil detachmentand transportation. However, estimation of both erosive rainfalls and sediment yields is very challenging, especiallyin historical times when only precipitations at seasonal or annual scales are available. This motivated us todevelop a parsimonious hydroclimatological model (ASCLIM, Annual Sediment CLImatological Model) forpredicting catchment scale sediment yield when temporal and spatial high-resolution precipitation data arenot available. The model was developed by using the annual data of suspended-sediment yield from Glonnbasin (1981–1995, gauge of Hohenkammer, Germany) and seasonal rainfall data from a NOAA data set. Thecorrelation coefficient between predicted and observed sediment yields was 0.94 and the efficiency index was0.89. Once parameterized, the model was able to capture annual sediment yield variability better than theLangbein–Schumm and the Fournier Index equations, also based on limited sets of inputs. The model holdspotential for historical reconstruction of sediment yields in the Glonn catchment (assuming constant landcover) and for simulating sediment fluxes from catchments with similar characteristics. Our application highlightsthe control of rainfall seasonality on sediment export and demonstrates that our sediment yield proxycould be considered as a good tool for the expectation and planning of soil conservation. Moreover, consideringthat we used modeled data to reconstruct past sediment loss,we could expect that using projected future rainfalldata our proxy could be able to assess future scenarios.

Estimating long-term sediment export using a seasonal rainfall-dependent hydrological model in the Glonn River basin, Germany

Diodato N;Guerriero L;Soriano M;Fiorillo F;Revellino P;Guadagno FM
2015-01-01

Abstract

In European catchments, rainfall and overland flowtrigger erosive processes that could result in soil detachmentand transportation. However, estimation of both erosive rainfalls and sediment yields is very challenging, especiallyin historical times when only precipitations at seasonal or annual scales are available. This motivated us todevelop a parsimonious hydroclimatological model (ASCLIM, Annual Sediment CLImatological Model) forpredicting catchment scale sediment yield when temporal and spatial high-resolution precipitation data arenot available. The model was developed by using the annual data of suspended-sediment yield from Glonnbasin (1981–1995, gauge of Hohenkammer, Germany) and seasonal rainfall data from a NOAA data set. Thecorrelation coefficient between predicted and observed sediment yields was 0.94 and the efficiency index was0.89. Once parameterized, the model was able to capture annual sediment yield variability better than theLangbein–Schumm and the Fournier Index equations, also based on limited sets of inputs. The model holdspotential for historical reconstruction of sediment yields in the Glonn catchment (assuming constant landcover) and for simulating sediment fluxes from catchments with similar characteristics. Our application highlightsthe control of rainfall seasonality on sediment export and demonstrates that our sediment yield proxycould be considered as a good tool for the expectation and planning of soil conservation. Moreover, consideringthat we used modeled data to reconstruct past sediment loss,we could expect that using projected future rainfalldata our proxy could be able to assess future scenarios.
File in questo prodotto:
File Dimensione Formato  
2015_Diodato et al_Geomorphology.pdf

non disponibili

Licenza: Non specificato
Dimensione 1.5 MB
Formato Adobe PDF
1.5 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/3446
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 7
social impact