Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake

Non-point source pollution loads estimation in Three Gorges Reservoir Area based on improved observation experiment and export coefficient model

The non-point source (NPS) pollution has become an important limitation to the sustainable development of the Three Gorges Reservoir Area (TGRA) water resources. NPS load estimation research has theoretical and realistic significance for water environment security and water pollution control. Therefore, the TGRA was chosen to be the study area, and the export coefficients of different land-use type were calculated through literature consultation method combined with improved observation experiment. The load of total nitrogen (TN) and total phosphorus (TP) of NPS from different pollution sources including farmland, decentralized livestock and poultry breeding and domestic pollution sources were estimated. The results are shown as follows: the order of TN load of different sources in the TGRA from high to low was land use, livestock and poultry breeding, rural life; the TN from land use was 372% higher than that of rural; the order of TP load of different sources in the TGRA from high to low was livestock and poultry breeding, rural life, land use; the TP from livestock and poultry breeding was 114.5% higher than that of land use. Therefore, control of livestock and poultry sewage discharges was the key practice to limit the TP loss, while the optimization of agricultural management was the key practice to control the loss of TN.

Performance of AnnAGNPS model in predicting runoff and sediment yields in Nan Province, Thailand

Land use changes such as deforestation and urban development influences the river discharge, soil erosion and sediment yield. It is important to evaluate tools which can be used to assess such impacts on water and sediment yield. Therefore, this study evaluated the Annualized Agricultural Non-Point Source Pollutant (AnnAGNPS) model's performance in simulating runoff and sediment loads in Nan Province, Thailand using seven years of continuous monitoring data. The river discharge and sediment yield data from 2011–2013 were used for calibration, and data from 2014–2017 were used for validation. Several input parameters were computed using methods suggested by other researchers and previous studies. In this study, the runoff curve number, soil erodibility factor (K), and RUSLE-C value were used to accurately simulate runoff and sediment loads. The results indicate that the model satisfactorily simulated runoff and sediment loads (R² = 0.65 and NSE = 0.53 for runoff volume, and R² = 0.62 and NSE = 0.60 for sediment yields). Moreover, the model estimated the total sediment yield, which contributed 12,932 hundred tons of material to the Nan River in 2017. The maximum sediment yield was obtained below the catchment (Na Noi sub-district, Na Noi district), which corresponds to areas with high crop densities. Cropland generated the highest soil erosion of all investigated land use (87.52% of total soil erosion). Thus, the AnnAGNPS model has the potential to use for investigating management practices to reduce soil erosion and controlling floods and droughts in Nan Province of Thailand.

The reduction effects of riparian reforestation on runoff and nutrient export based on AnnAGNPS model in a small typical watershed, China

The continuous deterioration of the aquatic environment in rivers and streams is increasingly causing social and political tensions. To alleviate aquatic environmental problems, especially for the nonpoint source pollution, establishment of riparian forest buffers has been demonstrated as an effective control measure. However, few comprehensive studies of the reduction effects of riparian reforestation on the aquatic environment have been performed, particularly in identifying the suitable widths of reforestation projects. In this paper, the Annualized Agricultural Non-Point Source (AnnAGNPS) model was used to simulate the reduction effects of riparian reforestation on runoff and nutrient loads in Wucun watershed, China. The results showed that 20-m, 40-m, and 60-m widths of riparian buffer reforestation had significant effects on the yearly loads of total nitrogen (TN) and total phosphorus (TP), with reduced rates of 23.21 to 56.2% and 18.16 to 52.14%, respectively. The reduction effect on annual runoff varied from 2.8 to 5.4%. Furthermore, the reduction effect of nutrients performed best during the transition period, while the best runoff reduction was found during the dry period. These distinct reductions indicated that the implementation of riparian forest buffers was capable of reducing the risk and frequency of flooding and eutrophication, especially during the wet and transition periods. Additionally, the 20-m width of riparian buffer reforestation achieved the highest reduction efficiency for runoff, and the 40-m width was the most suitable reforested riparian buffer width for TN and TP. Therefore, 40 m may be the optimum buffer width for the implementation of riparian reforestation in the Wucun watershed. These research results provided scientific information on selecting the optimum buffer width for aquatic environmental regulators and managers as the reduction effects of different widths of riparian buffers on runoff and nutrients were different when considering buffer reforestation.

Comprehensive study on parameter sensitivity for flow and nutrient modeling in the Hydrological Simulation Program Fortran model

Numerous parameters are used to construct the HSPF (Hydrological Simulation Program Fortran) model, which results in significant difficulty in calibrating the model. Parameter sensitivity analysis is an efficient method to identify important model parameters. Through this method, a model's calibration process can be simplified on the basis of understanding the model's structure. This study investigated the sensitivity of the flow and nutrient parameters of HSPF using the DSA (differential sensitivity analysis) method in the Xitiaoxi watershed, China. The results showed that flow was mostly affected by parameters related to groundwater and evapotranspiration, including DEEPFR (fraction of groundwater inflow to deep recharge), LZETP (lower-zone evapotranspiration parameter), and AGWRC (base groundwater recession), and most of the sensitive parameters had negative and nonlinear effects on flow. Additionally, nutrient components were commonly affected by parameters from land processes, including MON-SQOLIM (monthly values limiting storage of water quality in overland flow), MON-ACCUM (monthly values of accumulation), MON-IFLW-CONC (monthly concentration of water quality in interflow), and MON-GRND-CONC (monthly concentration of water quality in active groundwater). Besides, parameters from river systems, KATM20 (unit oxidation rate of total ammonia at 20 °C) had a negative and almost linear effect on ammonia concentration and MALGR (maximal unit algal growth rate for phytoplankton) had a negative and nonlinear effect on ammonia and orthophosphate concentrations. After calibrating these sensitive parameters, our model performed well for simulating flow and nutrient outputs, with R ² and E_NS (Nash-Sutcliffe efficiency) both greater than 0.75 for flow and greater than 0.5 for nutrient components. This study is expected to serve as a valuable complement to the documentation of the HSPF model to help users identify key parameters and provide a reference for performing sensitivity analyses on other models.