Predicting Streamflow and Nutrient Loadings in a Semi-Arid Mediterranean Watershed with Ephemeral Streams Using the SWAT Model

Pulighe, Giuseppe; Bonati, Guido; Colangeli, Marco; Traverso, Lorenzo; Lupia, Flavio; Altobelli, Filiberto; Marta, Anna Dalla; Napoli, Marco

doi:10.3390/agronomy10010002

Cited by 27 publications

(17 citation statements)

References 62 publications

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“…It has been successfully applied to watershed research in different countries and regions and is one of the most widely used hydrological models for evaluating water resources in different types of basins globally [16][17][18][19][20][21]. For example, Pulighe et al [22] used the SWAT model to predict the runoff and nutrient load of a Mediterranean semiarid small watershed, and the evaluation results from the model were found to be consistent with observed values. Pradhan et al [23] applied the SWAT model and an artificial neural network to basins in tropical, subtropical, arid, and semiarid regions in Asia and showed that the SWAT model and the artificial neural network model performed better when used in low-and high-flow simulations instead of average traffic, respectively.…”

Section: Introductionmentioning

confidence: 94%

Hydrological process simulation in Manas River Basin using CMADS

Yang

et al. 2020

Open Geosciences

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The inability to conduct hydrological simulations in areas that lack historical meteorological data is an important factor limiting the development of watershed models, understanding of watershed water resources, and ultimate development of effective sustainability policies. This study focuses on the Manas River Basin (MRB), which is a high-altitude area with no meteorological stations and is located on the northern slope of the Tianshan Mountains, northern China. The hydrological processes were simulated using the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) using the Soil and Water Assessment Tool (SWAT) model. Simulated runoff was corrected using calibration/uncertainty and sensitivity program for the SWAT. Through parameter sensitivity analysis, parameter calibration, and verification, the Nash–Sutcliffe efficiency (NSE), adjusted R-square ({R}_{\text{adj}}^{2}), and percentage bias (\text{PBIAS}) were selected for evaluation. The results were compared with statistics obtained from Kenswat Hydrological Station, where the monthly runoff simulation efficiency was \text{NSE}\hspace{.25em}=0.64, {R}_{\text{adj}}^{2}\hspace{.25em}=0.69, and \text{PBIAS}\hspace{.25em}=\mbox{--}0.9, and the daily runoff simulation efficiency was \text{NSE}\hspace{.25em}=0.75, {R}_{\text{adj}}^{2} = 0.75, \text{PBIAS} = −1.5. These results indicate that by employing CMADS data, hydrological processes within the MRB can be adequately simulated. This finding is significant, as CMADS provide continuous temporal, detailed, and high-spatial-resolution meteorological data that can be used to build a hydrological model with adequate accuracy in areas that lack historical meteorological data.

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Section: Introductionmentioning

confidence: 94%

Hydrological process simulation in Manas River Basin using CMADS

Yang

et al. 2020

Open Geosciences

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“…The SWAT model is a distributed hydrological model, and several studies showed that the SWAT model can be better applied to simulate not only streamflow and runoff but also nutrient loadings, water quality, pollution, etc., all over the world in different climate regions [28][29][30][31][32][33][34][35].…”

Section: Kappa Coefficientmentioning

confidence: 99%

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

Lai

Xia

et al. 2021

Land

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The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the average runoff, high extreme runoff and intra-annual runoff distribution in the middle of the 21st century are analyzed. The following conclusions are obtained: (1) Compared with the base period (1970–1990), the average runoff of Tangnaihai, Toudaoguai, Sanmenxia and Lijin hydrological stations in the future period (2040–2060) all shows an increasing trend, and the probability of flood disaster also tends to increase; (2) Land use/cover change (LUCC) under the status quo continuation scenario will increase the possibility of future flood disasters; (3) The spring runoff proportion of the four hydrological stations in the future period shows a decreasing trend, which increases the risk of drought in spring. The winter runoff proportion tends to increase; (4) The monthly runoff proportion of the four hydrological stations in the future period tends to decrease in April, May, June, July and October. The monthly runoff proportion tends to increase in January, February, August, September and December.

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“…The SWAT model was developed to predict the impact of land management practices on water, sediments and agricultural chemical yields in ungauged river basins [14]. The model is widely used in hydrological [8,26] and water-quality analyses at the basin scale [27,28] to assess the impact of land-use changes or climate changes on surface waters [19,29].…”

Section: Quantifying Point and Non-point Source Pollutionmentioning

confidence: 99%

Source Apportionment of Nutrient Loads to a Mediterranean River and Potential Mitigation Measures

Girolamo

Porto

2020

Water

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The aims of the study were to quantify nutrient loads from point and diffuse pollution sources in the Rio Mannu stream and to simulate mitigation measures for reducing nutrient loads delivered to the Santa Gilla wetland. The Soil and Water Assessment Tool model was used for simulating hydrology, nutrient balance and water quality. At the basin scale, the input from fertilisers was 80.3 kg ha−1 year−1 total nitrogen (TN) (87.6% of the total input) and 27.6 kg ha−1 year−1 of total phosphorus (TP) (99.8% of the total input). Atmospheric deposition and biological N-fixation together accounted for about 12% of the total TN input. The TN and TP from wastewater treatment plants (WWTPs) were about 14.2 t year−1 and 3.1 t year−1, respectively. Nutrient loads delivered to the river system differed among the sub-basins, with TP ranging from 0.2 kg ha−1 year−1 to 2.7 kg ha−1 year−1, and the sum of organic N and NO3-N ranging from 1.8 kg ha−1 year−1 to 22.9 kg ha−1 year−1. Under high flow conditions, NO3-N and TP accounted for 89% and 99% of the total load, respectively. The low flow contribution to the total load was very low, with NO3-N and TP accounting for 2.8% and 0.7%, respectively. However, the natural hydrological regime in the study area is intermittent, and low flow represents a critical condition for the water quality due to the high concentrations of TP and NO3-N from WWTP discharge. To improve the water quality, the reuse of treated wastewater from three WWTPs for irrigation purposes on olive cultivation, coupled with a 20% reduction in fertiliser application, was simulated. The results showed a reduction in nutrient loads at the outlet for all hydrological conditions. However, additional measures are needed for improving water quality.

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Predicting Streamflow and Nutrient Loadings in a Semi-Arid Mediterranean Watershed with Ephemeral Streams Using the SWAT Model

Cited by 27 publications

References 62 publications

Hydrological process simulation in Manas River Basin using CMADS

Hydrological process simulation in Manas River Basin using CMADS

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

Source Apportionment of Nutrient Loads to a Mediterranean River and Potential Mitigation Measures

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