An elevated nitrogen concentration in water is one of the main problems affecting water quality in Mediterranean rivers. The objectives of this study were (1) to evaluate the contribution of the Tafna catchment to the nitrate load entering the Mediterranean Sea, (2) to quantify the impact of agriculture on the nitrate concentration in water bodies, (3) to evaluate nitrate loads entering groundwater, and (4) to quantify the role of reservoirs in nitrate retention. A SWAT model was applied during the period 2003 to 2011. The discharge calibration was based on a previous study by Zettam et al. (2017). NSE efficiencies ranged from 0.421 to 0.75, R² ranged from 0.25 to 0.84, and PBIAS ranged from 3.68 to 39.42. The simulations of monthly nitrate loads were satisfactory in the upstream sampling stations, with NSE between 0.48 and 0.65 and R² between 0.63 and 0.68. The PBIAS was satisfactory in all the sampling stations (− 36.30 to 10.42). In the downstream sampling stations, the calibration of the monthly nitrate loads was unsatisfactory (NSE ranged from − 0.26 to 0.21 and R² ranged from 0.02 to 0.25). Fertilisation was the main N input in the catchment, while the main N output was plant uptake. The Tafna River carried an annual average of 37 to 85.5 t N year⁻¹ into the Mediterranean Sea. The simulation also showed that reservoirs in the Tafna basin contain a large quantity of nitrates, i.e. 62% on average of the total amount of nitrates transported annually by the Tafna River.

中文翻译：

---

应用SWAT模型评估塔夫纳集水区（西北非洲）对进入地中海的硝酸盐负荷的贡献。

水中高浓度的氮是影响地中海河流水质的主要问题之一。这项研究的目的是（1）评估塔夫纳河流域对进入地中海的硝酸盐负荷的贡献；（2）量化农业对水体中硝酸盐浓度的影响；（3）评估硝酸盐负荷（4）量化储层在硝酸盐滞留中的作用。在2003年至2011年期间应用了SWAT模型。排放校准基于Zettam等人先前的研究。（2017）。NSE效率从0.421到0.75，R ²范围从0.25到0.84，PBIAS范围从3.68到39.42。在上游采样站，每月硝酸盐负荷的模拟令人满意，NSE在0.48和0.65之间，R ²在0.63和0.68之间。在所有采样站（− 36.30至10.42）中，PBIAS均令人满意。在下游采样站，每月硝酸盐负荷的校准不令人满意（NSE范围为− 0.26至0.21，R ²范围为0.02至0.25）。施肥是流域的主要氮输入，而氮的主要输出是植物吸收。塔夫纳河的年平均年氮含量为37至85.5吨^-1进入地中海。模拟还表明，塔夫纳河流域的水库中含有大量的硝酸盐，即平均每年由塔夫纳河输送的硝酸盐总量的62％。