Embedding co-production and addressing uncertainty in watershed modeling decision-support tools: successes and challenges

The EPA Ecosystem Services Tool Selection Portal

The dynamics of an environmental decision-making context can be complicated. The use of decision support tools can help better facilitate restoring and maintaining ecosystems that provide environmental benefits (ecosystem services) to people. Although an ecosystem services assessment tool is designed for specific purposes, having access to a comprehensive suite of tools offers the user additional insight and resources to help in decision making. A range of approaches exist to connect ecosystem services to a given decision context ranging from less to more complex: using the best professional judgment; applying examples from other efforts; testing individual tool applications; and using a systematic, decision-tree approach to navigate among relevant tools and frameworks. The U.S. Environmental Protection Agency developed a decision-tree approach for a user to navigate the question of how to choose among a suite of ecosystem services assessment tools for three decision contexts: (1) ecological risk assessments; (2) cleanup of contaminated sites; (3) and generic structured decision-making processes. This tool selection navigator was developed with/for the intended user, including developing crosswalks between tool functionality and the user's language for what they require in a tool. To navigate the tool, the user first chooses one of three decision contexts. Second, the user selects among the different phases of the decision process. Third, the user selects among a few ecosystem-services related tasks relevant to the decision context chosen to identify potential tools. The tool uses simple language to navigate the decision pathways and provides the user with a suite of potential ES resources and tools for their given decision context.

Decision support tools for invasive alien species management should better consider principles of robust decision making

Invasive alien species (IAS) pose global threat to economies and biodiversity. With rising number of species and limited resources, IAS management must be prioritised; yet agreed tools to assist decision-making and their application are currently inadequate. There is need for simple decision support tools (DST) that guide stakeholders to optimise investment based on objective and quantifiable criteria. This paper reviews DSTs for IAS management to assess their availability and application of principles of robust decision-making. The aim is to provide guidance towards adopting the principles of robust decision-making to improve applicability and practical use of DST. A literature search conducted to identify relevant studies that report on DST in biological invasion. Results indicate an increase in availability of DST; however, available studies are largely biased in geographical, habitat and taxonomic focus. The results also show challenges in practical use of existing tools as most of them do not apply principles of robust decision-making. Application of these principles has the potential to overcome weakness of the current decision-making process and as such, enable decision-makers to efficiently allocate resources towards IAS management. A call is made for more consideration and adoption of principles of robust decision-making when developing DST for IAS invasions.

Advancing Watershed Legacy Nitrogen Modeling to Improve Global Water Quality

Despite widespread implementation of watershed nitrogen reduction programs across the globe, nitrogen levels in many surface waters remain high. Watershed legacy nitrogen storage, i.e., the long-term retention of nitrogen in soils and groundwater, is one of several explanations for this lack of progress. However scientists and water managers are ill-equipped to estimate how legacy nitrogen moderates in-stream nitrogen responses to land conservation practices, largely because modeling tools and associated long-term monitoring approaches to answering these questions remain inadequate. We demonstrate the need for improved watershed models to simulate legacy nitrogen processes and offer modeling solutions to support long-term nitrogen-based sustainable land management across the globe.

A review of regulatory modeling frameworks supporting numeric water quality criteria development in the United States

The US Environmental Protection Agency (USEPA) has a long history of leveraging environmental models and integrated modeling frameworks to support the regulatory development of numeric ambient water quality criteria for the protection of aquatic life and human health. Primary modeling types include conceptual, mechanistic, and data-driven empirical models; Bayesian and probabilistic models; and risk-based modeling frameworks. These models and modeling frameworks differ in their applicability to and suitability for various water quality criteria objectives. They require varying knowledge of system processes and stressor-response relationships, data availability, and expertise of stakeholders. In addition, models can be distinguished by their ability to characterize variability and uncertainty. In this work, we review USEPA recommendations for model use in existing regulatory frameworks, technical support documents, and peer-reviewed literature. We characterize key attributes, identify knowledge gaps and opportunities for future research, and highlight where renewed USEPA guidance is needed to promote the development and use of models in numeric criteria derivation. These outcomes then inform a decision-based framework for determining model suitability under particular scenarios of available knowledge, data, and access to technical resources. Integr Environ Assess Manag 2023;19:191-201. © 2022 SETAC.

Towards a Better Understanding of Social-Ecological Systems for Basin Governance: A Case Study from the Weihe River Basin, China

Promoting sustainable development of the river basin ecosystem is important for improving human ecological environment. Thus, prior knowledge of natural and social sciences on the integration of natural, economic, and social factors related to rivers should be assimilated to improve river basin governance. This study uses a social-ecological systems (SES) framework to diagnose key factors affecting the governance of the Weihe River Basin, ranging from the social, economic, and political context to related ecosystems, watershed resource systems, watershed management system, and watershed governance actors’ five subsystems. Further, corresponding countermeasures are proposed for the problems found during our diagnosis. The results of this study show that applying an SES framework to the diagnosis and analysis of river basin governance integrates the research results of different disciplines and fields. Thus, this study is helpful in identifying and proposing the key impact variables related to river basin management to establish a comprehensive management counterplan.

Data- and Model-Based Discharge Hindcasting over a Subtropical River Basin

This study aims to evaluate the performance of the Soil and Water Assessment Tool (SWAT), a simple Auto-Regressive with eXogenous input (ARX) model, and a gene expression programming (GEP)-based model in one-day-ahead discharge prediction for the upper Kentucky River Basin. Calibration of the models were carried out for the period of 2002–2005 using daily flow at a stream gauging station unaffected by the flow regulation. Validation of the calibrated models were executed for the period of 2008–2010 at the same gauging station along with another station 88 km downstream. GEP provided the best calibration (coefficient of determination (R) value 0.94 and Nash-Sutcliffe Efficiency (NSE) value of 0.88) and validation (R values of 0.93 and 0.93, NSE values of 0.87 and 0.87, respectively) results at the two gauging stations. While SWAT performed reasonably well in calibration (R value 0.85 and NSE value 0.72), its performance somewhat degraded in validation (R values of 0.85 and 0.82, NSE values of 0.65 and 0.65, for the two stations). ARX performed very well in calibration (R value 0.92, NSE value 0.82) and reasonably well in validation (R values of 0.88 and 0.92, NSE values of 0.76 and 0.85) at the two stations. Research results suggest that sophisticated hydrological models could be outperformed by simple data-driven models and GEP has the advantage to generate functional relationships that allows investigation of the complex nonlinear interrelationships among the input variables.

Engaging Multiple Worldviews With Quantitative Decision Support: A Robust Decision-Making Demonstration Using the Lake Model

Many of today's most pressing policy challenges are usefully characterized as wicked problems. With contested framings parties to a decision disagree not only on potential solutions, but on the nature of the problem they are trying to solve. The quantitative tools of risk and policy analysis, commonly designed to develop and compare choices within a single decision framing, are poorly designed to bring quantitative information into debates with contested framings. This study aims to build on recent advances in decision making under deep uncertainty (DMDU) to demonstrate methods and tools that may help resolve the tension between quantitative decision support and multiworldview approaches for addressing wicked problems. The study employs robust decision making (RDM), one common DMDU method, and a new version of the lake model, a simple and widely used model of a coupled human and natural system, to conduct a stylized analysis that reflects three different worldviews. The RDM analysis solves the decision challenge independently for each worldview and then compares each set of solutions from the vantage of the other worldviews. The resulting utopia-dystopia matrix informs problem reframing that seeks robust, adaptive strategies independently consistent with each worldview and thus provides a locus for agreement. The study describes how stakeholder engagements might use such analytic tools and their information products to provide overlapping but alternative entry points for groups with fundamentally different worldviews to engage with each other in deliberative processes appropriate for wicked problems.

Modeling Water Quality in Watersheds: From Here to the Next Generation

In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds. We first discuss areas of potential improvement in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in-stream water quality and process interactions, soil health and land management, and (peri-)urban areas. In addition, we provide insights into the contemporary challenges in the practices of watershed water quality modeling, including quality control of monitoring data, model parameterization and calibration, uncertainty management, scale mismatches, and provisioning of modeling tools. Finally, we make three recommendations to provide a path forward for improving watershed water quality modeling science, infrastructure, and practices. These include building stronger collaborations between experimentalists and modelers, bridging gaps between modelers and stakeholders, and cultivating and applying procedural knowledge to better govern and support water quality modeling processes within organizations.

Scenario processes for socio-environmental systems analysis of futures: A review of recent efforts and a salient research agenda for supporting decision making

This paper reviews the latest research on scenarios including the processes and products for socio-environmental systems (SES) analysis, modeling and decision making. A group of scenario researchers and practitioners participated in a workshop to discuss consolidation of existing research on the development and use of scenario analysis in exploring and understanding the interplay between human and environmental systems. This paper presents an extended overview of the workshop discussions and follow-up review work. It is structured around the essential challenges that are crucial to progress support of decision making and learning with respect to our highly uncertain socio-environmental futures. It identifies a practical research agenda where challenges are grouped according to the process stage at which they are most significant: before, during, and after the creation of the scenarios as products. These challenges for SES include: enhancing the role of stakeholder and public engagement in the co-development of scenarios, linking scenarios across multiple geographical, sectoral and temporal scales, improving the links between the qualitative and quantitative aspects of scenario analysis, addressing uncertainties especially surprise, addressing scenario diversity and their consistency together, communicating scenarios including visualization methods, and linking scenarios to decision making.

Making 'Chemical Cocktails' - Evolution of Urban Geochemical Processes across the Periodic Table of Elements

Urbanization contributes to the formation of novel elemental combinations and signatures in terrestrial and aquatic watersheds, also known as 'chemical cocktails.' The composition of chemical cocktails evolves across space and time due to: (1) elevated concentrations from anthropogenic sources, (2) accelerated weathering and corrosion of the built environment, (3) increased drainage density and intensification of urban water conveyance systems, and (4) enhanced rates of geochemical transformations due to changes in temperature, ionic strength, pH, and redox potentials. Characterizing chemical cocktails and underlying geochemical processes is necessary for: (1) tracking pollution sources using complex chemical mixtures instead of individual elements or compounds; (2) developing new strategies for co-managing groups of contaminants; (3) identifying proxies for predicting transport of chemical mixtures using continuous sensor data; and (4) determining whether interactive effects of chemical cocktails produce ecosystem-scale impacts greater than the sum of individual chemical stressors. First, we discuss some unique urban geochemical processes which form chemical cocktails, such as urban soil formation, human-accelerated weathering, urban acidification-alkalinization, and freshwater salinization syndrome. Second, we review and synthesize global patterns in concentrations of major ions, carbon and nutrients, and trace elements in urban streams across different world regions and make comparisons with reference conditions. In addition to our global analysis, we highlight examples from some watersheds in the Baltimore-Washington DC region, which show increased transport of major ions, trace metals, and nutrients across streams draining a well-defined land-use gradient. Urbanization increased the concentrations of multiple major and trace elements in streams draining human-dominated watersheds compared to reference conditions. Chemical cocktails of major and trace elements were formed over diurnal cycles coinciding with changes in streamflow, dissolved oxygen, pH, and other variables measured by high-frequency sensors. Some chemical cocktails of major and trace elements were also significantly related to specific conductance (p<0.05), which can be measured by sensors. Concentrations of major and trace elements increased, peaked, or decreased longitudinally along streams as watershed urbanization increased, which is consistent with distinct shifts in chemical mixtures upstream and downstream of other major cities in the world. Our global analysis of urban streams shows that concentrations of multiple elements along the Periodic Table significantly increase when compared with reference conditions. Furthermore, similar biogeochemical patterns and processes can be grouped among distinct mixtures of elements of major ions, dissolved organic matter, nutrients, and trace elements as chemical cocktails. Chemical cocktails form in urban waters over diurnal cycles, decades, and throughout drainage basins. We conclude our global review and synthesis by proposing strategies for monitoring and managing chemical cocktails using source control, ecosystem restoration, and green infrastructure. We discuss future research directions applying the watershed chemical cocktail approach to diagnose and manage environmental problems. Ultimately, a chemical cocktail approach targeting sources, transport, and transformations of different and distinct elemental combinations is necessary to more holistically monitor and manage the emerging impacts of chemical mixtures in the world's fresh waters.

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.

Non-floodplain Wetlands Affect Watershed Nutrient Dynamics: A Critical Review

Wetlands have the capacity to retain nitrogen and phosphorus and are thereby often considered a viable option for improving water quality at local scales. However, little is known about the cumulative influence of wetlands outside of floodplains, i.e., non-floodplain wetlands (NFWs), on surface water quality at watershed scales. Such evidence is important to meet global, national, regional, and local water quality goals effectively and comprehensively. In this critical review, we synthesize the state of the science about the watershed-scale effects of NFWs on nutrient-based (nitrogen, phosphorus) water quality. We further highlight where knowledge is limited in this research area and the challenges of garnering this information. On the basis of previous wetland literature, we develop emerging concepts that assist in advancing the science linking NFWs to watershed-scale nutrient conditions. Finally, we ask, "Where do we go from here?" We address this question using a 2-fold approach. First, we demonstrate, via example model simulations, how explicitly considering NFWs in watershed nutrient modeling changes predicted nutrient yields to receiving waters-and how this may potentially affect future water quality management decisions. Second, we outline research recommendations that will improve our scientific understanding of how NFWs affect downstream water quality.