Identifying critical source areas of nonpoint source pollution in a watershed with SWAT–ECM and AHP methods

Identification of critical source areas (CSAs) is pivotal for the management of nonpoint source (NPS) pollution of watersheds. Most studies focus on source (S) factors and ignore the driving (D) factors of such pollution. The Soil and Water Assessment Tool (SWAT) model and the export coefficient method (ECM) were incorporated to quantify the S factors of ammonia nitrogen (NH4–N) and total phosphorus (TP) as NPS pollution. Specifically, S factors coupled with D factors, including precipitation, slope, soil and land use, were regarded as multi–factors. Moreover, the analytical hierarchy process (AHP) method was adopted to determine the respective weights of multi–factors after overlaying the factor maps to identify the CSAs. These CSAs accounted for 23.86% of the total area, and generated 54.94% of NH4–N and 42.59% of the TP loads. In contrast with single and multi–factors, we found that using multi–factors having differing weights was more accurate for identifying CSAs. Our study results indicate this approach is reasonable for CSAs' identification in watersheds, and it can provide insights into different pollution sources and migration, thus providing a sounder basis for future decision–making.

Present and potential future critical source areas of nonpoint source pollution: a case of the Nakdong River watershed, South Korea

Identifying critical source areas (CSAs) is the first step to effectively managing nonpoint source (NPS) pollution. Increasing variability in climate can affect identification of CSAs. In this study, we identified present and future CSAs of NPS pollution in the Nakdong River watershed and examined how climate change will influence the identification of CSAs. Nine NPS pollution-related factors affecting the watershed environment and water quality were considered. These factors were rescaled through a min-max normalization to propose an index system that ranks basins based on the sensitivity of basins to climate change on identifying CSAs. For analyses, past rainfall was replaced with future rainfall under two RCP scenarios, RCP 2.6 and RCP 8.5. Results showed insignificant differences in the spatial distribution of CSAs between the present and the future and between the future scenarios. Basins that are on or adjacent to the Nakdong River mainstream were mainly identified as CSAs, in addition to many basins of the Geumho and Nam rivers. Highly ranked CSAs including the level 1 CSAs, were mainly distributed in the mid- and downstream areas of the Nakdong River, indicating high need of NPS pollution management. This study can provide a foundation for the effective management of NPS pollution in the present and the future.

Phosphorus critical source areas identification in an agricultural watershed of Three Gorges Reservoir Area, China

<p>Agricultural non-point sources (ANPS) pollution are considered to pose risks to water quality in Three Gorges Reservoir Areas (TGRA), especially when those pollution source comes from the hydrologically sensitive areas (HSAs) that generate surface runoff pathways. Therefore, it is necessary to identify the critical source areas (CSAs) or the sensitive regions of pollutants from agricultural lands in order to control and mitigate ANPS pollution effectively. In this study, an improved method integrating the Phosphorus Index (PI) and the Soil Topographic Index (STI) was applied to predict the risk of phosphorus loss and delineate the CSAs of phosphorus in a typical agricultural watershed in TGRA, China. The results showed that using a STI threshold value of 8.5, the HSA was identified 22.08% of watershed areas. The intersection of above two parts account 5.47% of the total watershed, compared with 24.41% of watershed areas based on an existing approach that uses just one criterion. As the results showed , the CSAs of phosphorus loss were mainly located near streams, with high or relatively high soil phosphorus contents or phosphorus fertilizer, or intense soil erosion are observed. The calculated results are in good agreement with the actual situation. Since the approach is based on GIS, and is a relatively simple application uses readily available geospatial data, therefore the technic could be used to improve cost-effectiveness and provide a useful screening tool for water resource managers responsible for identifying and remediating critical NPS source areas. </p>

Currents Status, Challenges, and Future Directions in Identifying Critical Source Areas for Non-Point Source Pollution in Canadian Conditions

Non-point source (NPS) pollution is an important problem that has been threatening freshwater resources throughout the world. Best Management Practices (BMPs) can reduce NPS pollution delivery to receiving waters. For economic reasons, BMPs should be placed at critical source areas (CSAs), which are the areas contributing most of the NPS pollution. The CSAs are the areas in a watershed where source coincides with transport factors, such as runoff, erosion, subsurface flow, and channel processes. Methods ranging from simple index-based to detailed hydrologic and water quality (HWQ) models are being used to identify CSAs. However, application of these methods for Canadian watersheds remains challenging due to the diversified hydrological conditions, which are not fully incorporated into most existing methods. The aim of this work is to review potential methods and challenges in identifying CSAs under Canadian conditions. As such, this study: (a) reviews different methods for identifying CSAs; (b) discusses challenges and the current state of CSA identification; and (c) highlights future research directions to address limitations of currently available methods. It appears that applications of both simple index-based methods and detailed HWQ models to determine CSAs are limited in Canadian conditions. As no single method/model is perfect, it is recommended to develop a ‘Toolbox’ that can host a variety of methods to identify CSAs so as to allow flexibility to the end users on the choice of the methods.