Calibration using R-programming and parallel processing at the HUC12 subbasin scale in the Mid-Atlantic region: Development of national SWAT hydrologic calibration.

The first phase of a national scale Soil and Water Assessment Tool (SWAT) model calibration effort at the HUC12 (Hydrologic Unit Code 12) watershed scale was demonstrated over the Mid-Atlantic Region (R02), consisting of 3036 HUC12 subbasins. An R-programming based tool was developed for streamflow calibration including parallel processing for SWAT-CUP (SWAT- Calibration and Uncertainty Programs) to streamline the computational burden of calibration. Successful calibration of streamflow for 415 gages (KGE ≥0.5, Kling-Gupta efficiency; PBIAS ≤15%, Percent Bias) out of 553 selected monitoring gages was achieved in this study, yielding calibration parameter values for 2106 HUC12 subbasins. Additionally, 67 more gages were calibrated with relaxed PBIAS criteria of 25%, yielding calibration parameter values for an additional 150 HUC12 subbasins. This first phase of calibration across R02 increases the reliability, uniformity, and replicability of SWAT-related hydrological studies. Moreover, the study presents a comprehensive approach for efficiently optimizing large-scale multi-site calibration.

Projection of Sediment Loading from Pearl River Basin, Mississippi into Gulf of Mexico under a Future Climate with Afforestation.

Sediment load in rivers is recognized as both a carrier and a potential source of contaminants. Sediment deposition significantly changes river flow and morphology, thereby affecting stream hydrology and aquatic life. We projected sediment load from the Pearl River basin (PRB), Mississippi into the northern Gulf of Mexico under a future climate with afforestation using the SWAT (Soil and Water Assessment Tool)-based HAWQS (Hydrologic and Water Quality System) model. Three simulation scenarios were developed in this study: (1) the past scenario for estimating the 40-year sediment load from 1981 to 2020; (2) the future scenario for projecting the 40-year sediment load from 2025 to 2064, and (3) the future afforestation scenario that was the same as the future scenario, except for converting the rangeland located in the middle section of the Pearl River watershed of the PRB into the mixed forest land cover. Simulations showed a 16% decrease in sediment load for the future scenario in comparison to the past scenario due to the decrease in future surface runoff. Over both the past and future 40 years, the monthly maximum and minimum sediment loads occurred, respectively, in April and August; whereas the seasonal sediment load followed the order: spring > winter > summer > fall. Among the four seasons, winter and spring accounted for about 86% of sediment load for both scenarios. Under the future 40-year climate conditions, a 10% reduction in annual average sediment load with afforestation was observed in comparison to without afforestation. This study provides new insights into how a future climate with afforestation would affect sediment load into the northern Gulf of Mexico.

Application of the US-EPA's HAWQS model to predict future climate impacts on hydrological processes.

Climate change could add a variety of uncertainties to hydrological processes and water resources. Very limited efforts have been devoted to applying the US-EPA (Environmental Protection Agency)'s Hydrologic and Water Quality System (HAWQS) model for predicting climate change impacts on hydrological processes at basin scale. Here we applied the model to project the next 50 years' (from 2021 to 2070) hydrological processes at the Yazoo River basin in Mississippi, USA. Simulations showed that over the next 50 years, there are no significant trends in monthly precipitation, ET, runoff, and discharge; only 2% of the annual precipitation percolated into the deep aquifer; and dry seasons become dryer and wet seasons become wetter. These findings provide very useful information to stakeholders for water resource management. Our study further suggests that the HAWQS model is a user friendly and time-saving tool for basin scale hydrological modeling.

Analysis of alternative climate datasets and evapotranspiration methods for the Upper Mississippi River Basin using SWAT within HAWQS.

This study reports the application of Soil and Water Assessment Tool (SWAT) within the Hydrologic and Water Quality System (HAWQS) on-line platform, for the Upper Mississippi River Basin (UMRB). The UMRB is an important ecosystem located in the north central U.S. that is experiencing a range of ecological stresses. Specifically, testing of SWAT was performed for: (1) Hargreaves (HG) and Penman-Monteith (PM) PET methods, and (2) Livneh, National Climatic Data Center (NCDC) and Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate datasets. The Livneh-PM combination resulted in the highest average annual water yield of 380.6 mm versus the lowest estimated water yield of 193.9 mm for the Livneh-HG combination, in response to 23-year uncalibrated simulations. Higher annual ET and PET values were predicted with HG method versus the PM method for all three weather datasets in response to the uncalibrated simulations, due primarily to higher HG-based estimates during the growing season. Based on these results, it was found that the HG method is the preferred PET option for the UMRB. Initial calibration of SWAT was performed using the Livneh data and HG method for three Mississippi River main stem gauge sites, which was followed by spatial validation at 10 other gauge sites located within the UMRB stream network. Overall satisfactory results were found for the calibration and validation gauge sites, with the majority of R2 values ranging between 0.61 and 0.82, Nash-Sutcliffe modeling efficiency (NSE) values ranging between 0.50 and 0.79, and Kling-Gupta efficiency (KGE) values ranging between 0.61 and 0.84. The results of an additional experimental suite of six scenarios, which represented different combinations of climate data sets and calibrated parameters, revealed that suggested statistical criteria were again satisfied by the different scenario combinations. Overall, the PRISM data exhibited the strongest reliability for the UMRB.