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Evaluation of the soil and water assessment tool (SWAT) for simulating E. coli concentrations at the watershed-scale.

ABSTRACT: Water quality management at the watershed level requires a framework to identify sources, apportion water quality risks and develop mitigation strategies to reduce health risks. Watershed-scale models have been used as a support tool to understand the sources, fate and transport of fecal bacteria and pathogens in the environment. The Soil and Water Assessment Tool (SWAT) model was applied in this study to understand the sources and drivers of microbial water quality in the Clouds Creek watershed in Georgia, USA. A criterion to evaluate the performance of the SWAT bacterial model was also developed in this study using the Nash-Sutcliffe Efficiency (NSE) performance measure. The SWAT model was successfully calibrated and validated for flow with Nash-Sutcliffe Efficiency (NSE) of 0.81 and 0.55, respectively. Escherichia coli (E. coli) predictions were good with NSE of 0.32 and 0.34 for the calibration and validation timeframes, respectively. Based on the criteria developed in this study, SWAT bacterial model for E. coli and fecal coliform can be judged as "satisfactory" when NSE > 0.20. The contribution of sources followed this order: in-stream cattle manure deposition > cattle manure application > poultry manure application > septic systems > wildlife manure, suggesting that a reduction in livestock access to streams would be the most effective approach to reduce fecal bacterial loads in this watershed and others impacted by fecal contamination. Finally, our results suggest that the SWAT model is capable of simulating E. coli dynamics in the Clouds Creek watershed and can provide insights into source impacts for risk management.

SUBMITTER: Sowah RA

PROVIDER: S-EPMC8804978 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSoil organic carbon (SOC) plays a crucial role in the global carbon cycle and terrestrial ecosystem functions. It is widely known that climate change and soil water content (SWC) could influence the SOC dynamics; however, there are still debates about how climate change, especially climate warming, and SWC impact SOC. We investigated the spatiotemporal changes in SOC and its responses to climate warming and root-zone SWC change using the coupled hydro-biogeochemical model (SWAT-DayCent) and climate scenarios data derived under the three Representative Concentration Pathways (RCPs2.6, 4.5, and 8.5) from five downscaled Global Climate Models (GCMs) in a typical loess watershed--the Jinghe River Basin (JRB) on the Chinese Loess Plateau.ResultsThe air temperature would increase significantly during the future period (2017-2099), while the annual precipitation would increase by 2.0-13.1% relative to the baseline period (1976-2016), indicating a warmer and wetter future in the JRB. Driven by the precipitation variation, the root-zone SWC would also increase (by up to 27.9% relative to the baseline under RCP4.5); however, the SOC was projected to decrease significantly under the future warming climate. The combined effects of climate warming and SWC change could more reasonably explain the SOC loss, and this formed hump-shaped response surfaces between SOC loss and warming-SWC interactions under both RCP2.6 and 8.5, which can help explain diverse warming effects on SOC with changing SWC.ConclusionsThe study showed a significant potential carbon source under the future warmer and wetter climate in the JRB, and the SOC loss was largely controlled by future climate warming and the root-zone SWC as well. The hump-shaped responses of the SOC loss to climate warming and SWC change demonstrated that the SWC could mediate the warming effects on SOC loss, but this mediation largely depended on the SWC changing magnitude (drier or wetter soil conditions). This mediation mechanism about the effect of SWC on SOC would be valuable for enhancing soil carbon sequestration in a warming climate on the Loess Plateau.

Dataset Information

Evaluation of the soil and water assessment tool (SWAT) for simulating E. coli concentrations at the watershed-scale.

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