Identification of integrated models is still hindered by submodels’ uncertainty propagation. In this article, a novel identifiability and identification framework is applied to screen and establish reasonable hypotheses of an integrated instream (WASP) and catchment water quality (VENSIM) model. Using the framework, the models were linked, and critical parameters and processes identified. First, an ensemble of catchment nutrient loads was simulated with randomized parameter settings of the catchment processes (e.g. nutrient decay rates). A second Monte Carlo analysis was then staged with randomized loadings and parameter values mimicking insteam processes (e.g. algae growth). The most significant parameters and their processes were identified. This coupling of models for a two-step global sensitivity analysis is a novel approach to integrated catchment-scale water quality model identification. Catchment processes were, overall, more significant to the river’s water quality than the instream processes of this Prairie river system investigated (Qu’Appelle River).

Abstract Nutrient export from agricultural areas is among the main contributors to water pollution in various watersheds. Agricultural Beneficial Management Practices (BMPs) are commonly used to reduce excessive nutrient runoff and improve water quality. The successful uptake of BMPs not only depends on their effectiveness but also on their costs of implementation. This study conducts a set of cost-effectiveness analyses to help stakeholders identify their preferred combinations of BMPs in the Qu’Appelle River Basin, a typical watershed in the Canadian Prairies. The considered BMPs are related to cattle and cropping farms and are initially selected by agricultural producers in this region. The analyses use a water quality model to estimate the impact of implementing BMPs on nutrient export, and the cost estimation model to approximate the cost of implementing BMPs at tributary and watershed scales. Our results show that BMPs' effectiveness, total costs of implementation and costs per kilogram of nutrient abatement vary between tributaries. However, wetland conservation is among the optimal practices to improve water quality across the watershed. It is also found that the rates of BMP adoption by stakeholders can influence the effectiveness of practices in a large watershed scale, which highlights the importance of stakeholder engagement in water quality management. This type of analyses can help stakeholders choose single or a combination of BMPs according to their available budget and acceptable levels of reduction in nutrients.

There is growing interest to develop processes for creating user-informed watershed scale models of hydrology and water quality and to assist in decision-making for balanced policies for managing watersheds. Watershed models can be enhanced with the incorporation of social dimensions of watershed management as brought forward by participants such as the perspectives, values, and norms of people that depend on the land, water, and ecosystems for sustenance, economies, and overall wellbeing. In this work, we explore the value of combining both qualitative and quantitative methods and social science data to enhance salience and legitimacy of watershed models so that end-users are more engaged. We discuss pilot testing and engagement workshops for building and testing a systems dynamics model of the Qu'Appelle Valley to gather insights from local farmers and understand their perceptions of Beneficial Management Practices (BMPs). Mixed-method workshops with agricultural producers in the Qu'Appelle Watershed gathered feedback on the developing model and the incorporation of social determinants affecting decision-making. Analysis of focus groups and factor analysis of Q-sorts were used to identify the desired components of the model, and whether it supported farmers' understanding of the potential effects of BMPs on water quality. We explored farmers' engagement with models testing BMPs and the potential of incorporating their decision processes within the model itself. Finally, we discuss the reception of the process and the practicality of the approach in providing legitimate and credible decision support tools for a community of farmers.

Water quality is increasingly at risk due to nutrient pollution entering river systems from cities, industrial zones and agricultural areas. Agricultural activities are typically the largest non-point source of water pollution. The dynamics of agricultural impacts on water quality are complex and stem from the decisions and activities of multiple stakeholders, often with diverse business plans, values, and attitudes towards practices that can improve water quality. This study proposes a framework to understand and incorporate stakeholders' viewpoints into water quality modeling and management. The framework was applied to the Qu'Appelle River Basin, Saskatchewan, Canada. Q-methodology was used to understand viewpoints of stakeholders, namely agricultural producers (annual croppers, cattle producers, mixed farmers) and cottage owners, regarding a range of agricultural Beneficial Management Practices (BMPs) that can improve water quality, and to identify their preferred BMPs. A System Dynamics (SD) approach was employed to develop a transparent and user-friendly water quality model, SD-Qu'Appelle, to simulate nutrient loads in the region before and after implementation of stakeholder identified BMPs. The SD-Qu'Appelle was used in real-time engagement of stakeholders in model simulations to demonstrate and explore the potential effects of different BMPs in mitigating water pollution. Stakeholder perspectives were explored to understand the functionality and value of the SD-Qu'Appelle, preferred policies and potential barriers to BMP implementation on their land. Results show that although there are differences between viewpoints of stakeholders, they identified wetland restoration/retention, flow and erosion control, and relocation of corrals near creeks to sites more distant from waterways as the most effective BMPs for improving water quality. Economics was identified as a primary factor that causes agricultural producers to either accept or refuse the implementation of BMPs. Agricultural producers believe that incentives rather than regulations are the best policies for increasing the adoption of BMPs. Overall, stakeholders indicated the SD-Qu'Appelle had considerable value for water quality management and provided a set of recommendations to improve the model.