Predicting the availability and quality of freshwater resources is a pressing concern in the Mediterranean area, where a number of agricultural systems depend solely on precipitation. This study aims at predicting streamflow and nonpoint pollutant loads in a temporary river system in the Mediterranean basin (Sulcis area, Sardinia, Italy). Monthly discharge, suspended sediment, nitrate nitrogen, total nitrogen, mineral phosphorus, and dissolved oxygen in-stream monitoring data from gauge stations were used to calibrate and validate the Soil and Water Assessment Tool model for the period 1979–2009. A Sequential Uncertainty Fitting procedure was used to auto-calibrate parameter uncertainties and model evaluation. Monthly simulation during the validation period showed a positive model performance for streamflow with Nash–Sutcliffe efficiency and percent bias values of 0.7% and 18.7%, respectively. The simulation results at a watershed level indicate that the sediment load was 1.13 t ha−1 year−1, while for total nitrogen and total phosphorus, the simulated values were 4.8 and 1.18 kg ha−1 year−1, respectively. These results were consistent with the values of soil and nutrient losses observed in the Mediterranean area, although hot-spot areas with high nutrient loadings were identified. The calibrated model could be used to assess long-term impacts on water quality associated with the simulated land use scenarios.

Predicting streamflow and nutrient loadings in a semi-arid Mediterranean watershed with ephemeral streams using the SWAT model / Giuseppe Pulighe, Guido Bonati, Marco Colangeli, Lorenzo Traverso, Flavio Lupia,Filiberto Altobelli , Anna Dalla Marta, Marco Napoli. - In: AGRONOMY. - ISSN 2073-4395. - STAMPA. - 10:(2020), pp. 1-22. [10.3390/agronomy10010002]

Predicting streamflow and nutrient loadings in a semi-arid Mediterranean watershed with ephemeral streams using the SWAT model

Filiberto Altobelli;Anna Dalla Marta;Marco Napoli
2020

Abstract

Predicting the availability and quality of freshwater resources is a pressing concern in the Mediterranean area, where a number of agricultural systems depend solely on precipitation. This study aims at predicting streamflow and nonpoint pollutant loads in a temporary river system in the Mediterranean basin (Sulcis area, Sardinia, Italy). Monthly discharge, suspended sediment, nitrate nitrogen, total nitrogen, mineral phosphorus, and dissolved oxygen in-stream monitoring data from gauge stations were used to calibrate and validate the Soil and Water Assessment Tool model for the period 1979–2009. A Sequential Uncertainty Fitting procedure was used to auto-calibrate parameter uncertainties and model evaluation. Monthly simulation during the validation period showed a positive model performance for streamflow with Nash–Sutcliffe efficiency and percent bias values of 0.7% and 18.7%, respectively. The simulation results at a watershed level indicate that the sediment load was 1.13 t ha−1 year−1, while for total nitrogen and total phosphorus, the simulated values were 4.8 and 1.18 kg ha−1 year−1, respectively. These results were consistent with the values of soil and nutrient losses observed in the Mediterranean area, although hot-spot areas with high nutrient loadings were identified. The calibrated model could be used to assess long-term impacts on water quality associated with the simulated land use scenarios.
2020
10
1
22
Giuseppe Pulighe, Guido Bonati, Marco Colangeli, Lorenzo Traverso, Flavio Lupia,Filiberto Altobelli , Anna Dalla Marta, Marco Napoli
File in questo prodotto:
File Dimensione Formato  
2020 - Pulighe et al. - SWAT.pdf

accesso aperto

Tipologia: Pdf editoriale (Version of record)
Licenza: Open Access
Dimensione 3.52 MB
Formato Adobe PDF
3.52 MB Adobe PDF

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

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1186674
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 28
  • ???jsp.display-item.citation.isi??? 24
social impact