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1. Updating SWAT+ to Clarify Understanding of In‐Stream Phosphorus Retention and Remobilization: SWAT+P.R&R

   https://doi.org/10.1029/2022WR033283  

   Wallington, Kevin; Cai, Ximing (March 2023, Water Resources Research)

   Abstract Efforts to reduce riverine phosphorus (P) loads have not been as fruitful as expected or hoped. One reason for the failure of these efforts appears to be that models used for watershed P management have understated and misrepresented the role of in‐stream processes in shaping watershed P export. Here, we update the latest release of the Soil and Water Assessment Tool (SWAT+), a widely used watershed management model, to better represent in‐stream P retention and remobilization (SWAT+P.R&R). We add new streambed pools where P is stored and tracked, and we incorporate three new processes driving in‐stream P dynamics: (a) deposition and resuspension of sediment‐associated P, (b) diffusion of dissolved P between the water column and streambed, and (c) adsorption and desorption of mineral P. The objective of this modeling work is to provide a diagnostic tool that enables researchers to challenge existing assumptions regarding how watersheds store, transform, and transport P. Here, in a first diagnostic analysis, SWAT+P.R&R helps reconcile in‐stream P retention theory (that P is retained at low flows and remobilized at high flows) and a discordant data set in our validation watershed. SWAT+P.R&R results (a) clarify that the theorized relationship between P retention and flow is only valid (for this point‐source affected testbed, at least) at the temporal scale of a single rising‐or‐falling hydrograph limb and (b) illustrate that hysteresis obscures the relationship at longer temporal scales. Future work using SWAT+P.R&R could further challenge assumptions regarding timescales of in‐stream P legacies and sources of P load variability. 

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2. Improving SWAT Model Calibration Using Soil MERGE (SMERGE)

   https://doi.org/10.3390/w12072039  

   Tobin, Kenneth J.; Bennett, Marvin E. (July 2020, Water)

   This study examined eight Great Plains moderate-sized (832 to 4892 km2) watersheds. The Soil and Water Assessment Tool (SWAT) autocalibration routine SUFI-2 was executed using twenty-three model parameters, from 1995 to 2015 in each basin, to identify highly sensitive parameters (HSP). The model was then run on a year-by-year basis, generating optimal parameter values for each year (1995 to 2015). HSP were correlated against annual precipitation (Parameter-elevation Regressions on Independent Slopes Model—PRISM) and root zone soil moisture (Soil MERGE—SMERGE 2.0) anomaly data. HSP with robust correlation (r > 0.5) were used to calibrate the model on an annual basis (2016 to 2018). Results were compared against a baseline simulation, in which optimal parameters were obtained by running the model for the entire period (1992 to 2015). This approach improved performance for annual simulations generated from 2016 to 2018. SMERGE 2.0 produced more robust results compared with the PRISM product. The main virtue of this approach is that it constrains parameter space, minimizesing equifinality and promotesing modeling based on more physically realistic parameter values. 

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3. Multivariate Calibration of the SWAT Model Using Remotely Sensed Datasets

   https://doi.org/10.3390/rs15092417  

   Dangol, Sijal; Zhang, Xuesong; Liang, Xin-Zhong; Anderson, Martha; Crow, Wade; Lee, Sangchul; Moglen, Glenn E.; McCarty, Gregory W. (May 2023, Remote Sensing)

   Remotely sensed hydrologic variables, in conjunction with streamflow data, have been increasingly used to conduct multivariable calibration of hydrologic model parameters. Here, we calibrated the Soil and Water Assessment Tool (SWAT) model using different combinations of streamflow and remotely sensed hydrologic variables, including Atmosphere–Land Exchange Inverse (ALEXI) Evapotranspiration (ET), Moderate Resolution Imaging Spectroradiometer (MODIS) ET, and Soil MERGE (SMERGE) soil moisture. The results show that adding remotely sensed ET and soil moisture to the traditionally used streamflow for model calibration can impact the number and values of parameters sensitive to hydrologic modeling, but it does not necessarily improve the model performance. However, using remotely sensed ET or soil moisture data alone led to deterioration in model performance as compared with using streamflow only. In addition, we observed large discrepancies between ALEXI or MODIS ET data and the choice between these two datasets for model calibration can have significant implications for the performance of the SWAT model. The use of different combinations of streamflow, ET, and soil moisture data also resulted in noticeable differences in simulated hydrologic processes, such as runoff, percolation, and groundwater discharge. Finally, we compared the performance of SWAT and the SWAT-Carbon (SWAT-C) model under different multivariate calibration setups, and these two models exhibited pronounced differences in their performance in the validation period. Based on these results, we recommend (1) the assessment of various remotely sensed data (when multiple options available) for model calibration before choosing them for complementing the traditionally used streamflow data and (2) that different model structures be considered in the model calibration process to support robust hydrologic modeling. 

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4. Simulating eroded soil organic carbon with the SWAT-C model

   Zhang, Xuesong (January 2018, Environmental modelling & software)
5. A Coupled SWAT-AEM Modelling Framework for a Comprehensive Hydrologic Assessment

   https://doi.org/10.3390/w14172753  

   Sangeetha, K.; Narasimhan, Balaji; Srinivasan, R. (September 2022, Water)

   This study attempts to integrate a Surface Water (SW) model Soil and Water Assessment Tool (SWAT) with an existing steady-state, single layer, unconfined heterogeneous aquifer Analytic Element Method (AEM) based Ground Water (GW) model, named Bluebird AEM engine, for a comprehensive assessment of SW and GW resources and its management. The main reason for integrating SWAT with the GW model is that the SWAT model does not simulate the distribution and dynamics of GW levels and recharge rates. To overcome this issue, often the SWAT model is coupled with the numerical GW model (either using MODFLOW or FEFLOW), wherein the spatial and temporal patterns of the interactions are better captured and assessed. However, the major drawback in integrating the two models (SWAT with—MODFLOW/FEM) is its conversion from Hydrological Response Unit’s (HRU)/sub-basins to grid/elements. To couple them, a spatial translation system is necessary to move the inputs and outputs back and forth between the two models due to the difference in discretization. Hence, for effective coupling of SW and GW models, it may be desirable to have both models with a similar spatial discretization and reduce the need for rigorous numerical techniques for solving the PDEs. The objective of this paper is to test the proof of concept of integrating a distributed hydrologic model with an AEM model at the same spatial units, primarily focused on surface water and groundwater interaction with a shallow unconfined aquifer. Analytic Element Method (AEM) based GW models seem to be ideal for coupling with SWAT due to their innate character to consider the HRU, sub-basin, River, and lake boundaries as individual analytic elements directly without the need for any further discretization or modeling units. This study explores the spatio-temporal patterns of groundwater (GW) discharge rates to a river system in a moist-sub humid region with SWAT-AEM applied to the San Jacinto River basin (SJRB) in Texas. The SW-GW interactions are explored throughout the watershed from 2000–2017 using the integrated SWAT-AEM model, which is tested against stream flow and GW levels. The integrated SWAT-AEM model results show good improvement in predicting the stream flow (R2 = 0.65–0.80) and GW levels as compared to the standalone SWAT model. Further, the integrated model predicted the low flows better compared to the standalone SWAT model, thus accounting for the SW-GW interactions. Almost 80% of the stream network experiences an increase in groundwater discharge rate between 2000 and 2017 with an annual average GW discharge rate of 1853 Mm3/year. The result from the study seems promising for potential applications of SWAT-AEM coupling in regions with considerable SW-GW interactions. 

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