In response to degraded water quality, federal policy makers in the US and Canada called for a 40% reduction in phosphorus (P) loads to Lake Erie, and state and provincial policy makers in the Great Lakes region set a load‐reduction target for the year 2025. Here, we configured five separate SWAT (US Department of Agriculture's Soil and Water Assessment Tool) models to assess load reduction strategies for the agriculturally dominated Maumee River watershed, the largest P source contributing to toxic algal blooms in Lake Erie. Although several potential pathways may achieve the target loads, our results show that any successful pathway will require large‐scale implementation of multiple practices. For example, one successful pathway involved targeting 50% of row cropland that has the highest P loss in the watershed with a combination of three practices: subsurface application of P fertilizers, planting cereal rye as a winter cover crop, and installing buffer strips. Achieving these levels of implementation will require local, state/provincial, and federal agencies to collaborate with the private sector to set shared implementation goals and to demand innovation and honest assessments of water quality‐related programs, policies, and partnerships.
Watershed models typically are evaluated solely through comparison of in-stream water and nutrient fluxes with measured data using established performance criteria, whereas processes and responses within the interior of the watershed that govern these global fluxes often are neglected. Due to the large number of parameters at the disposal of these models, circumstances may arise in which excellent global results are achieved using inaccurate magnitudes of these "intra-watershed" responses. When used for scenario analysis, a given model hence may inaccurately predict the global, in-stream effect of implementing land-use practices at the interior of the watershed. In this study, data regarding internal watershed behavior are used to constrain parameter estimation to maintain realistic intra-watershed responses while also matching available in-stream monitoring data. The methodology is demonstrated for the Eagle Creek Watershed in central Indiana. Streamflow and nitrate (NO) loading are used as global in-stream comparisons, with two process responses, the annual mass of denitrification and the ratio of NO losses from subsurface and surface flow, used to constrain parameter estimation. Results show that imposing these constraints not only yields realistic internal watershed behavior but also provides good in-stream comparisons. Results further demonstrate that in the absence of incorporating intra-watershed constraints, evaluation of nutrient abatement strategies could be misleading, even though typical performance criteria are satisfied. Incorporating intra-watershed responses yields a watershed model that more accurately represents the observed behavior of the system and hence a tool that can be used with confidence in scenario evaluation.
Abstract:Watershed simulation models are used extensively to investigate hydrologic processes, landuse and climate change impacts, pollutant load assessments and best management practices (BMPs). Developing, calibrating and validating these models require a number of critical decisions that will influence the ability of the model to represent real world conditions. Understanding how these decisions influence model performance is crucial, especially when making science-based policy decisions. This study used the Soil and Water Assessment Tool (SWAT) model in West Lake Erie Basin (WLEB) to examine the influence of several of these decisions on hydrological processes and streamflow simulations. Specifically, this study addressed the following objectives (1) demonstrate the importance of considering intra-watershed processes during model development, (2) compare and evaluated spatial calibration versus calibration at outlet and (3) evaluate parameter transfers across temporal and spatial scales. A coarser resolution (HUC-12) model and a finer resolution model (NHDPlus model) were used to support the objectives. Results showed that knowledge of watershed characteristics and intra-watershed processes are critical to produced accurate and realistic hydrologic simulations. The spatial calibration strategy produced better results compared to outlet calibration strategy and provided more confidence. Transferring parameter values across spatial scales (i.e. from coarser resolution model to finer resolution model) needs additional fine tuning to produce realistic results. Transferring parameters across temporal scales (i.e. from monthly to yearly and daily time-steps) performed well with a similar spatial resolution model. Furthermore, this study shows that relying solely on quantitative statistics without considering additional information can produce good but unrealistic simulations.
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