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Predicting Streamflow and Nutrient Loadings in a Semi-Arid Mediterranean Watershed with Ephemeral Streams Using the SWAT Model.
- Source :
- Agronomy; Jan2020, Vol. 10 Issue 1, p2-2, 1p
- Publication Year :
- 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<superscript>−1</superscript> year<superscript>−1</superscript>, while for total nitrogen and total phosphorus, the simulated values were 4.8 and 1.18 kg ha<superscript>−1</superscript> year<superscript>−1</superscript>, 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20734395
- Volume :
- 10
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Agronomy
- Publication Type :
- Academic Journal
- Accession number :
- 141411469
- Full Text :
- https://doi.org/10.3390/agronomy10010002