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AnnAGNPS is a watershed-scale hydrological model designed to analyze the impact of nonpoint source pollution in agricultural environments. Its unique capabilities have defined it as an essential model that is used globally to evaluate agricultural management scenarios. However, it does not currently have a user-friendly graphical interface that provides a simple way for users to perform simulations. This article presents QAnnAGNPS, a plugin developed in QGIS to facilitate access to the simulation capabilities of AnnAGNPS through a user-friendly interface and the addition of extra features, including data visualization. QAnnAGNPS, in addition to fulfilling this valuable task, opens the door to the incorporation of additional functions already included in other similar hydrological models. The plugin has been tested in the Latxaga cereal basin in Navarra, Spain, and has demonstrated that it provides a simpler way to perform simulations and visualize results compared to AnnAGNPS. • The QAnnAGNPS plugin has been developed to integrate the AnnAGNPS model into QGIS. • QAnnAGNPS allows using AnnAGNPS model capabilities in an easier way than before. • QAnnAGNPS adds new functionalities to AnnAGNPS, facilitating the whole process. • QAnnAGNPS brings the capabilities of AnnAGNPS to a wider range of users. • QAnnAGNPS opens many possibilities of adding new functionalities. [ABSTRACT FROM AUTHOR]

Agricultural activities contribute to water pollution through sediments and nutrient export, negatively affecting water quality and aquatic ecosystems. However, implementing best management practices (BMPs) could help control sediments and nutrient losses from agricultural catchments. This study used the Soil Water Assessment Tool (SWAT) model to assess the effectiveness of four BMPs in reducing sediment and phosphorus export in a small agricultural catchment (33 km2) in southeastern Sweden. The SWAT model was first evaluated for its ability to simulate streamflow, sediment load, and total phosphorous load from 2005 to 2020. Then, the calibrated parameters were used to simulate the agricultural BMP scenarios by modifying relevant parameters. The model performed satisfactorily during calibration and validation for streamflow (NSE = 0.80/0.84), sediment load (NSE = 0.67/0.69), and total phosphorous load (NSE = 0.61/0.62), indicating its suitability for this study. The results demonstrate varying effects of BMP implementation on sediment and phosphorus (soluble and total) export, with no significant change in streamflow. Filter strips were highly effective in reducing sediment (−32%), soluble phosphorus (−67%), and total phosphorous (−66%) exports, followed by sedimentation ponds with −35%, −36%, and −50% reductions, respectively. Grassed waterways and no-tillage were less impactful on pollutant reduction, with grassed waterways showing a slight increase (+4%) in soluble phosphorus and no-tillage having a minimal effect on sediment (−1.3%) and total phosphorus (−0.2%) export. These findings contribute to the ongoing efforts to mitigate sediment and nutrient pollution in Swedish agricultural areas, thereby supporting the conservation and restoration of aquatic ecosystems, and enhancing sustainable agricultural practices. • Filter strips and sedimentation ponds were highly effective in pollutant reduction. • Grassed waterways and no-tillage had less impact on pollutant reduction. • Filter strip effectiveness in pollutant reduction increased with increasing width. • Total phosphorous export from the catchment is dependent on sediment export. • The analyzed BMPs had no significant impact on streamflow. [ABSTRACT FROM AUTHOR]

Predicting water quality and quantity response to climate change in a watershed is very difficult due to the complexity and uncertainties in estimating and understanding future hydrological conditions. However, hydrological models could simplify the processes and predict future impacts of agricultural activities. This study aimed to evaluate the applicability of the Soil Water Assessment Tool (SWAT) model for climate change prediction of streamflow and nitrate load in an agricultural Mediterranean watershed in northern Spain. The model was first evaluated for simulating streamflow and nitrate load under rainfed agricultural conditions in the Cidacos River watershed in Navarre, Spain. Then, climate change impact analysis on streamflow and nitrate load was conducted in the short-term (2011–2040), medium-term (2041–2070), and long-term (2071–2100) future projections relative to the historical baseline period (1971–2000) under the RCP4.5 and RCP8.5 CO 2 emission scenarios. The model evaluation showed a good model performance result during calibration (2000–2010) and validation (2011–2020) for streamflow (NSE = 0.82/0.83) and nitrate load (NSE = 0.71/0.68), indicating its suitability for adoption in the watershed. The climate change projection results showed a steady decline in streamflow and nitrate load for RCP4.5 and RCP8.5 in all projections, with the long-term projection scenario of RCP8.5 greatly affected. Autumn and winter saw a considerable drop in comparison to spring and summer. The decline in streamflow was attributed to the projected decrease in precipitation and increase in temperatures, while the nitrate load decline was consistent with the projected streamflow decline. Based on these projections, the long-term projection scenarios of RCP8.5 indicate dire situations requiring urgent policy changes and management interventions to minimize and mitigate the resulting climate change effects. Therefore, adapted agricultural management practices are needed to ensure sustainable water resource utilization and efficient nitrogen fertilizer application rates in the watershed to reduce pollution. [Display omitted] • The SWAT model was used to simulate streamflow and nitrate load response to climate change. • The key climate change drivers were declining precipitation and rising temperature. • Decrease in future streamflow and nitrate load, particularly in the long-term RCP8.5 projection. • Climate change affects agriculture through changes in phenology and cropping cycle. [ABSTRACT FROM AUTHOR]