Evaluating the impacts of soil data on hydrological and nonpoint source pollution prediction.

Soil data are one key input for most hydrological and nonpoint source (H/NPS) models, and quantifying the error transmission from soil data to H/NPS predictions is of great importance. In this study, two typical soil datasets were compared using the Soil and Water Assessment Tool (SWAT) in a typical mountainous watershed, the Three Gorges Reservoir Region, China. Besides, the effects of soil data resolution were evaluated, and the error transmission from soil data to watershed management strategy was assessed. The results indicate that model outputs are not sensitive to changes of soil data resolution but the choice of soil data greatly impacts the application of watershed models, in terms of the goodness-of-fit indicator, predicted data and related uncertainty. This soil data-induced error would be inevitably magnified from the flow simulation to the NPS prediction stage. This study could indicate that the choice of soil data will lead to significant differences in management schemes for specific pollution periods. These results provide information on the impacts of soil data on the functionality of watershed models and valuable information for the appropriateness of each soil database.

Using site-specific soil samples as a substitution for improved hydrological and nonpoint source predictions.

Soil databases are one of the most important inputs for watershed models, and the quality of soil properties affects how well a model performs. The objectives of this study were to (1) quantify the sensitivity of model outputs to soil properties and to (2) use site-specific soil properties as a substitution for more accurate hydrological and nonpoint source (H/NPS) predictions. Soil samples were collected from a typical mountainous watershed in China, and the impacts of soil sample parameters on H/NPS predictions were quantified using the Soil and Water Assessment Tool (SWAT). The most sensitive parameters related to predicting flow, sediment, and total phosphorus (TP) mainly were the soil hydrological, the channel erosion processes, and the initial soil chemical environment, respectively. When the site-specific soil properties were used, the uncertainties (coefficient of variation) related to predicting the hydrology, sediment and TP decreased by 75∼80 %, 75∼84 %, and 46∼61 %, respectively. Based on changes in the Nash-Sutcliff coefficient, the model performance improved by 4.9 and 19.45 % for the hydrological and sediment model, accordingly. However, site-specific soil properties did not contribute to better TP predictions because of the high spatial variability of the soil P concentrations across the large watershed. Thus, although site-specific soil samples can be used to obtain more accurate H/NPS predictions, more sampling sites are required to apply this method in large watersheds.

Identifying non-point source priority management areas in watersheds with multiple functional zones.

The concept of water functional zones promotes the comprehensive supervision and scientificoversight of non-point source (NPS) pollution at the watershed scale. Therefore,understanding the spatial distributions and temporal trends in watershed priority managementareas (PMAs) is important in the study and efficient management of NPS pollution.However, no comprehensive studies of PMAs have been conducted to protect waterquality effectively in watersheds with multiple water functional zones. In this study, a newframework is presented that quantifies the perturbations of multiple spatial assessmentunits to the quality of nearby water bodies in various water functional zones. This innovativeapproach, which combines the Soil and Water Assessment Tool (SWAT) and statisticalanalysis, was applied to characterize multiple-level PMAs with a case study of theDaning River watershed in China. Based on the results, the advantage of this new frameworkis better suited to downstream areas, particularly in dry periods and severely pollutedwatersheds. This paper reinforces the view that the concept of zoning should be takenseriously in the framework of PMAs targeting. From the aspect of watershed management,these new PMAs can offer an optimal strategy for locating comprehensive and costeffectivemanagement practices at the watershed scale, particularly in large watershedsor long river systems.

Targeting priority management areas for multiple pollutants from non-point sources.

The control of multiple pollutants from non-point sources is very difficult because their loss potentials are not consistent on the same spatial distributions. In this research, an innovative approach was established for multiple-pollutant priority management areas (MP-PMAs). In the new framework, the MP-PMA approach focused on the sensitive areas that contributed a variety of pollutants instead of a specific targeted pollutant by integrating a watershed model and a Pareto-based multi-criteria evaluation approach. Based on the results, multiple levels of MP-PMAs were established with respect to the corresponding requirements of clean water statutes. Compared to traditional separate strategies, the MP-PMA approach would lead to more cost-effective watershed management because those moderate-level PMAs for specific targeted pollutant might be the high-level MP-PMAs. With respect to spatial distribution, the MP-PMA approach provided more accurate target results for the high-level PMAs, especially among the headwater areas. From a scientific view, the MP-PMA approach provides an integrated suggestion for the placement and removal potentials of best management practices at the watershed scale.