Estimation Of Non-point Source Pollution Research Articles

Enhanced streamflow prediction with SWAT using support vector regression for spatial calibration: A case study in the Illinois River watershed, U.S.

Accurate streamflow prediction plays a pivotal role in hydraulic project design, nonpoint source pollution estimation, and water resources planning and management. However, the highly non-linear relationship between rainfall and runoff makes prediction difficult with desirable accuracy. To improve the accuracy of monthly streamflow prediction, a seasonal Support Vector Regression (SVR) model coupled to the Soil and Water Assessment Tool (SWAT) model was developed for 13 subwatersheds in the Illinois River watershed (IRW), U.S. Terrain, precipitation, soil, land use and land cover, and monthly streamflow data were used to build the SWAT model. SWAT Streamflow output and the upstream drainage area were used as two input variables into SVR to build the hybrid SWAT-SVR model. The Calibration Uncertainty Procedure (SWAT-CUP) and Sequential Uncertainty Fitting-2 (SUFI-2) algorithms were applied to compare the model performance against SWAT-SVR. The spatial calibration and leave-one-out sampling methods were used to calibrate and validate the hybrid SWAT-SVR model. The results showed that the SWAT-SVR model had less deviation and better performance than SWAT-CUP simulations. SWAT-SVR predicted streamflow more accurately during the wet season than the dry season. The model worked well when it was applied to simulate medium flows with discharge between 5 m3 s-1 and 30 m3 s-1, and its applicable spatial scale fell between 500 to 3000 km2. The overall performance of the model on yearly time series is "Satisfactory". This new SWAT-SVR model has not only the ability to capture intrinsic non-linear behaviors between rainfall and runoff while considering the mechanism of runoff generation but also can serve as a reliable regional tool for an ungauged or limited data watershed that has similar hydrologic characteristics with the IRW.

Nonpoint source pollution

A comprehensive review of the research papers published in 2018 focusing on nonpoint source (NPS) pollution is presented in this review article. The identification of pollution from different sources and estimation of NPS pollution using various models are summarized in this review paper. Various innovative techniques are also examined to abate NPS pollution. PRACTITIONER POINTS: The non-point source pollution in 2018 is systematically reviewed and documented. This review evaluates and summarizes the identification, quantification, reduction, and management of NPS pollution. Future perspectives of NPS pollution research are discussed.

Non-point source pollution estimation in the Pingqiao River Basin, China, using a spatial hydrograph-separation approach

ABSTRACTFor efficient and targeted management, this study demonstrates a recently developed non-point source (NPS) pollution model for a year-long estimation in the Pingqiao River Basin (22.3 km2) in China. This simple but physically reasonable model estimates NPS export in terms of land use by reflecting spatial hydrological features and source runoff measurements under different land-use types. The NPS export was separately analysed by a distributed hydrological model, a spatial hydrograph-separation technique, and an empirical water quality sub-model. Simulation results suggest that 57 890 kg of total nitrogen (TN) and 1148 kg of total phosphorus (TP) were delivered. The results, validated with observed stream concentrations, show relative errors of 23.3% for TN and 47.4% for TP. Countermeasures for urban areas (5.3% of total area) were prioritized because of the high contribution rate to TN (14.1%) and TP (26.2%) which is caused by the high degree of runoff (8.5%) and pollution source.

Sensitivity of Initial Abstraction Coefficient on Prediction of Rainfall- Runoff for Various Land Cover Classes of 'Ton Watershed' Using Remote Sensing & GIS Based 'Rinspe' Model

Rainfall, Runoff, Infiltration are most important parameters in water balance equation of any hydrological problems. Among these parameters the real prediction of surface runoff is the crucial task. Many hydrologic models are available to estimate surface runoff from precipitation data. The development of a GIS based model that would make it possible to assess the surface runoff accurately and efficiently. On the basis of this requirement a model called „Runoff, Infiltration and Nonpoint Source Pollution Estimation‟ (RINSPE) was developed for estimating runoff, infiltration and nonpoint source pollution in the Ton river catchment based on the different land cover type distribution within the catchment. The Curve Number method for estimating direct runoff from rainstorms is now widely used in engineering design, post-event appraisals, and environmental impact estimation. In the present investigation the Initial Abstraction coefficient in the Curve Number method considered with 2 different scenarios by assuming „λ‟ value as 0.2 for general conditions and 0.3 for Indian conditions to run RINSPE model. The results reveal that the surface runoff of 860.79 mm occurred with a loss of 62.93 mm in the form of infiltration for scenarios: 1. The most occupied area in the Ton watershed is forest which is having a runoff of 656 mm with 124mm infiltration and a very slight variation in prediction of runoff and infiltration for scenario: 2 for the same land cover classes. In the present study the results reveals that „λ‟ value is 0.2 of Ia gave minute higher runoff values than „λ‟ value with 0.3. This experimental investigation makes sure that, higher the initial abstraction lowers the

Water and nonpoint source pollution estimation in the watershed with limited data availability based on hydrological simulation and regression model.

Nonpoint source (NPS) pollution is considered as the main reason for water quality deterioration; thus, to quantify the NPS loads reliably is the key to implement watershed management practices. In this study, water quality and NPS loads from a watershed with limited data availability were studied in a mountainous area in China. Instantaneous water discharge was measured through the velocity-area method, and samples were taken for water quality analysis in both flood and nonflood days in 2010. The streamflow simulated by Hydrological Simulation Program-Fortran (HSPF) from 1995 to 2013 and a regression model were used to estimate total annual loads of various water quality parameters. The concentrations of total phosphorus (TP) and total nitrogen (TN) were much higher during the flood seasons, but the concentrations of ammonia nitrogen (NH3-N) and nitrate nitrogen (NO3-N) were lower during the flood seasons. Nevertheless, only TP concentration was positively correlated with the flow rate. The fluctuation of annual load from this watershed was significant. Statistical results indicated the significant contribution of pollutant fluxes during flood seasons to annual fluxes. The loads of TP, TN, NH3-N, and NO3-N in the flood seasons were accounted for 58-85, 60-82, 63-88, 64-81% of the total annual loads, respectively. This study presented a new method for estimation of the water and NPS loads in the watershed with limited data availability, which simplified data collection to watershed model and overcame the scale problem of field experiment method.

Small-scale watershed extended method for non-point source pollution estimation in part of the Three Gorges Reservoir Region

Non-point source (NPS) pollution has been increasingly recognized as a major contributor to the declining quality of aquatic environment in recent years. Because of the data shortage, the non-point source loads estimation in the large-scale watershed is always difficult in most developing countries. In this study, small-scale watershed extended method (SWEM) was introduced with a case study in the middle part of Three Gorges Reservoir Region (TGRR). Small-scale watershed extended method is the method which uses physical-based models in some small typical catchments of the targeted large watershed, and then the parameters obtained from those small catchments are extended to the surrounding area until the non-point source pollution loads in the entire watershed or region are obtained. The selected small catchments should have sufficient data. Here, the middle part of the Three Gorges Reservoir Region, about 12,500 km2, was chosen as the targeted region for the case study. In this region, considering the data availability, Xiaojiang River was screened as a typical watershed and was simulated with Soil and Water Assessment Tool model through accurate parameter calibration and validation. And then the parameter group obtained in Xiaojiang River Watershed was extended to the entire study area to quantify the total non-point source pollution loads. After which, the spatio-temporal characteristics of the non-point source pollution in the middle part of the Three Gorges Reservoir Region were analyzed, as well as the pollution from each tributary and different under layer surface conditions. The small-scale watershed extended method provides a practical approach for non-point source pollution loads estimation in the large-scale watershed or region.

The application of the Bp neutral network in the estimation of non-point source pollution

In view of the relatively large basin area in China and the application limitations of small-scale, non-point source (NPS) pollution models, we developed an estimation platform for NPS based on a back propagation (Bp) network with the combination of Visual Basic 6.0 (Microsoft Corporation) and Supermap Objects 2.1 (Supermap Corporation). In addition, the total nitrogen (TN) load and its spatial characteristics in the Songliao Basin were estimated and analyzed with our estimation platform. Analysis of the estimation platform demonstrated that it is well suited to nonlinear mapping and spatial analysis. The estimation of NPS in the Songliao Basin revealed that the TN load generally decreased in the basin from 1980 to 2000. In addition, the TN load in the Songliao Basin was characterized by being significantly influenced by loads in neighboring zones. Concerning administrative areas, the TN load in Jilin Province was the highest in 1985 and 1995, while it was highest in the Inner Mongolia autonomous region in 2000. Concerning water systems, the Second Songhuajiang Basin had the highest nitrogen load in 1985 and 1995, while the Daliao Basin had the highest nitrogen load per unit area. Similarly, the Eerguna River Basin had the highest nitrogen load and nitrogen load per unit area in 2000. Finally, the applicability of the NPS platform in small- and medium-sized basins of semi-arid regions in the northwestern, such as the Weihe River Basin, was studied

Effects of seasonal variation in precipitation on estimation of non-point source pollution

The extent of nonpoint source pollution (NPSP) generated from upstream catchment areas of a reservoir is normally estimated based on a design rainfall. However, rainfall generally varies in different seasons. This seasonal change may significantly influence the estimation of runoff volume and associated NPSP arising within a reservoir watershed. The NPSP management, reservoir operation, and water treatment operation strategies developed based on the estimation will also be altered. This study analyzes the effects of monthly and seasonal variation in precipitation on the estimation of pollution levels from nonpoint sources in a reservoir watershed. The area studied is the Derchi reservoir watershed located in central Taiwan. This watershed is subdivided into twenty-six sub-watersheds, and the Thiessen method is used to determine the rainfall intensity in each sub-watershed. Runoff pattern and NPSP contributions for each sub-watershed are estimated using the AGNPS model. Results show significant seasonal variation in precipitation; estimated NPSP loads likewise vary significantly over time. Seven- to one hundred-fold differences among monthly and seasonal estimations of phosphorus and sediment loads are observed.