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This presentation was given during the 2022 AGU Fall Meeting in Chicago, IL. Abstract: Modern water supply networks are complex 'systems of systems' in which hydrologic, engineered, and institutional systems interact across a range of spatiotemporal scales. Advances in watershed process representation, data assimilation, and distributed computing have improved hydrologic modeling in recent years, but it remains a challenge to account for human factors such as water demand, reservoir operations, regulatory institutions, infrastructure investment, and risk management. Human systems emerge through dynamic, adaptive, and distributed decision-making processes subject to conflicting management objectives and high levels of uncertainty. Water management activities often bridge spatiotemporal scales; e.g., assessing the value of groundwater recharge facilities requires modeling the fast dynamics (daily timestep or less) of high-flow events and infrastructure capacity constraints as well as the slow dynamics (multidecadal) of persistent extreme droughts, water supply/demand trends, and water users’ financial health. Water management networks are increasingly interconnected, so that decisions by individual water suppliers, users, or governing bodies can have complex effects that propagate through the network. Better representation of these factors provides a major opportunity to improve the relevance of models and results for decision-makers, but also a significant conceptual and computational challenge. This presentation will highlight efforts to address these challenges by combining detailed hydrologic-engineered-institutional system simulation models with ensemble-based exploratory modeling workflows that facilitate the discovery of high-performing and robust management policies, multi-objective tradeoffs, and consequential uncertainties. The presentation will draw first from recent research on water supply portfolios and infrastructure planning in the Central Valley of California, using the open-source California Food-Energy-Water System (CALFEWS) simulation model. We will then demonstrate how these lessons are being applied to an ongoing translational research collaboration with the USGS to understand how hydrologic and human uncertainties could impact future water availability and drought vulnerability in the Delaware River Basin., This work was funded in part by the US National Science Foundation (NSF) INFEWS/T2 program, Award #1639268. Computing resources were provided by the University of North Carolina at Chapel Hill Research Computing Group and the Cornell Center for Advanced Computing.

This presentation was given during the 2022 EWRI Conference, Atlanta GA. Abstract:River basin managers are increasingly relying on modeling and simulation to manage the resources available to them. Water availability modeling efforts in recent decades have produced numerous models that attempt to capture how hydroclimatic and human operations move and consume water. These efforts have generally been divided in two: large-scale modeling prioritizing theoretical soundness and the consistency of hydro-climatological processes across regional and global scales, and basin-scale system modelers placing focus on the environmental, infrastructural, and institutional features that shape water scarcity at the local level. Both rely on dynamics at different scales and have been increasingly converging toward one another. Basin-scale models increasing their efforts to better incorporate climatic processes through the use of synthetic generators and other tools, and global- and regional-scale hydrologic models improving their representation of how human operation and management, by increasing their use of data-driven methods to characterize processes. This study assesses whether the insights drawn from two state-of-the-art models from each of these communities are also converging, specifically with regard to water scarcity vulnerability. We employ MOSART-WM (large-scale hydrological model) and StateMod (basin-scale systems model) and focus on the Upper Colorado Basin within the state of Colorado. Our results suggest that the large-scale model can capture the aggregate effect of all water operations in the basin, in terms of regulated flow, but is limited in representing processes in the sub-basin scale. The basin-scale model suggests a larger variance of scarcity across the basin’s water users, primarily due to its more detailed representation of human elements in the basin, specifically reservoir capacity and operations, and the institutional mechanisms of allocation. These outcomes can be used to inform how the two scales of analysis can be bridged to maintain both large-scale theoretical soundness and regional consistency, as well as relevance to basin-scale decision making.

This presentation was given during the 2022 ASCE EWRI Conference in Atlanta GA. Abstract: Water providers in California are working to develop integrated and diverse portfolios of water supply infrastructure that bridge scales from local to statewide. Investments such as canals and groundwater recharge facilities can increase the capture of water during peak flow events and bolster reliability during drought, potentially improving the robustness of water supplies to uncertainties such as climate change and environmental regulation. However, expensive regional infrastructure often requires joint investment involving a coalition of interdependent water providers (e.g., water utilities, irrigation districts) to achieve economies of scale. Traditional planning approaches have focused on total expected benefits and costs, but new frameworks are needed that account for complex interactions between the partners and are able to disaggregate benefits, costs, and risks to ensure that joint investments meet the individual objectives of each partner. The present work addresses this need in the context of the Central Valley of California, using the California Food-Energy-Water System (CALFEWS) model, which simulates daily water storage and conveyance in the state’s major reservoirs, rivers, and canals, along with water contract allocations, deliveries, and banking at the level of individual irrigation districts and water utilities. The Borg Multi-Objective Evolutionary Algorithm (MOEA) is used to search for water supply investment partnerships that represent the optimal tradeoffs between objectives such as total water yield for the partnership, water cost for the worst-off partner, and regional impacts outside the partnership. Candidate solutions are then subjected to a broader range of potential states of the world under deep uncertainties such as climate change and environmental regulation in order to identify investment partnerships that are effective at the project level, fair to all partners, and robust to future uncertainties., This work was funded in part by the US National Science Foundation (NSF) INFEWS/T2 program, Award #1639268. Computing resources were provided by the Texas Advanced Computing Center (TACC) under the NSF Extreme Science and Engineering Discovery Environment (XSEDE) program, Award #TG-EAR090013, as well as the University of North Carolina at Chapel Hill Research Computing Group and the Cornell Center for Advanced Computing.

Ebook: Addressing Uncertainty in MultiSector Dynamics Research Access the ebook here:https://immm-sfa.github.io/msd_uncertainty_ebook/

This report outlines a vision for MultiSector Dynamics (MSD) as an emerging transdisciplinary field that seeks to advance our understanding of how human-Earth systems interactions shape the resources, goods, and services on which society depends. The core objective of this MSD Vision Report is to clarify core definitions, share research questions, highlight scientific opportunities, and provide steps for improving the MSD community’s capacity to support needed scientific progress. The report has several technical audiences in mind. These include current MSD researchers, scientists working in complementary fields who wish to learn more about opportunities for engagement, and research program managers at the US Department of Energy (DOE). Additionally, the research-to-operations (R2O2R) and community building elements of the report hold value for a broad array of US federal agencies as well as other governments and international organizations. As a transdisciplinary endeavor, the vision presented here should have elements that directly interest sectoral analysts engaged in energy, water, agriculture, transportation, health, etc. We hope these audiences will find the report a helpful reference and a source of opportunities for shaping the future of MSD science. The report incorporates ideas and insights from the members of the recently established MSD Community of Practice (CoP). MSD finds its roots in a number of research fields and communities, including integrated assessment; impacts, adaptation, and vulnerability; Earth system science; and complex adaptive systems. However, the MSD CoP draws its conceptual basis from a 2016 workshop sponsored and led by the DOE, "Understanding Dynamics and Resilience in Complex Interdependent Systems: Prospects for a Multi-Model Framework and Community of Practice," organized with other federal agencies and hosted by the US Global Change Research Program. The rationale for the CoP is that research on understanding risks and opportunities arising from tightly connected human and natural systems is fragmented across several fields, requiring improved collaboration and synthesis to accelerate needed scientific advances. A CoP Facilitation Team and a Scientific Steering Group (SSG) were launched in 2019 to advance the needed collaborations and scientific synthesis. Since that time, an initial core group of projects supported by DOE’s MSD research program has provided input to the development of the CoP through activities including a community questionnaire to identify current tools and research interests, regular meetings of technical working groups (WGs), MSD community briefings, research workshops, and the MSD CoP website. The members of the MSD SSG and Facilitation Team are responsible for drafting this report, based on the above community inputs as well as a formal review of recent research within related fields such as Earth system science, integrated assessment modeling, economics, decision science, socio-ecological systems, socio-environmental systems, complexity science, systems engineering, energy transitions, urban systems, and coastal dynamics. Members of the major projects in the DOE MSD research program provided extensive comments on a first draft of the report (see Chapter 2.2 for descriptions and links to projects' websites for additional information). Robert Vallario, program manager for the DOE Earth and Environmental Systems Modeling MSD research program area, has provided insights, perspectives, and comments that have been critically important throughout the process. The SSG and the Facilitation Team thank these individuals for their many contributions and ongoing support. In addition, the Facilitation Team thanks the DOE Office of Science, Earth and Environmental System Modeling program for financial support of its activities through the Integrated Multisector Multiscale Modeling (IM3) project. In the supplemental material folder you will find: All figures andimages used in the report. Figures created by the report's authors also include editable vector file formats(.ai) and may be reused with attribution. Figures and images reused from other sources should be reused with original source permission and/or citation. Sample powerpoint presentation of main concepts from the report A copy of the report with tracked changes, resulting from an internal review and comment process withthe major projects in the DOE MSD research program.&nbsp

This poster has been presented at the AGU Fall Meeting 2021 Globally increasing demand for water services and risks of water scarcity are causing river basin managers to struggle with how to best manage their water resources. These challenges have motivated rapid growth in model development and simulation to aid evaluations of the performance of alternative management policies and project future conditions. In recent efforts focused on modeling water availability, a divide has emerged between the research community of large-scale hydrologic modelers emphasizing hydro-climatological processes and that of watershed-system modelers emphasizing the environmental, infrastructural, and institutional features that shape water scarcity at the local basin level. These two research foci each rely on dynamics at different scales but have been increasingly converging towards one another, with basin-scale models directing efforts toward improved incorporation of climatic processes, and global- and regional-scale hydrologic models directing efforts toward improving their representation of how humans convey, store, use, and govern water. This study assesses if convergent insights on water scarcity assessment can be drawn from two representative state-of-the-art models from each of these communities. The comparison is focused on the Upper Colorado Basin within the state of Colorado and evaluates whether the conclusions one would draw about scarcity for water users in the basin would be consistent between the two models. Results suggest that the regional-scale model (MOSART-WM) can overestimate basin-scale water scarcity vulnerability while underestimating its sub-basin scale variability. The basin-scale model (StateMod) suggests a larger variance of scarcity across the basin’s water users. This could be due to several factors, including the simplified reservoir operations and the coarse representation of human elements in the basin by MOSART-WM, as well as the simplified institutional mechanisms of allocation. These outcomes can be used to inform the interpretation of large-scale studies on water scarcity, as well as how the two scales of analysis can be bridged to maintain both large-scale theoretical soundness and decision-scale relevance.

This poster has been presented at the AGU Fall Meeting 2021 Water resources planning has long been challenged by the presence of deep uncertainty in how hydroclimatic and societal factors will evolve. Deep uncertainty is especially present in how individual and collective human preference and action are represented in water resources systems models. Modeling human action is challenging enough when considering historical conditions but becomes most confounding when envisioning human response to previously unexperienced conditions, such as longer droughts or higher temperatures. Bottom-up planning frameworks attempt to overcome this challenge by employing exploratory modeling, which assesses a system under a broad range of plausible states of the world. In this study, we expand on prior work in the Upper Colorado River Basin within the state of Colorado by applying such a bottom-up framework to the individual irrigation demands of hundreds of agricultural water users. The basin supports water supply for several sectors, cities, towns and individuals who vie for water through the doctrine of prior appropriation. Water users in the basin have been adapting to increasingly stressed and uncertain conditions by applying conservation measures, and committing to formal or informal water right trading agreements. Through this exploratory modeling approach, we are able to represent hundreds of adaptive demand decisions for irrigation users in this basin, that vary by their hydrologic condition triggers, demand adjustment levels and the number of users that employ them. These adaptive demands are unique to each user and dynamically change under a large ensemble of hydroclimatic conditions, creating a total of 600,000 so-called “states of the world” for this basin. Through this experiment we explore the capacity (and the limits) of adaptive irrigation demand management through informal water transfers to modulate the effects of drought conditions on the basin’s multisectoral water users both individually and collectively. Our findings can inform water conservation policy, as well as support the establishment of more formal trading mechanisms in the basin and across the state of Colorado.