Advancing the Cyberinfrastructure for Integrated Water Resources Modeling

Like other scientists, hydrologists encode mathematical formulations that simulate various hydrologic processes as computer programs so that problems with water resource management that would otherwise be manually intractable can be solved efficiently. These computer models are typically developed to answer specific questions within a specific study domain. For example, one computer model may be developed to solve for magnitudes of water flow and water levels in an aquifer while another may be developed to solve for magnitudes of water flow through a water distribution network of pipes and reservoirs. Interactions between different processes are often ignored or are approximated using overly simplistic assumptions. The increasing complexity of the water resources challenges society faces, including stresses from variable climate and land use change, means that some of these models need to be stitched together so that these challenges are not evaluated myopically from the perspective of a single research discipline or study domain. The research in this dissertation presents an investigation of the various approaches and technologies that can be used to support model integration. The research delves into some of the computational challenges associated with model integration and suggests approaches for dealing with these challenges. Finally, it advances new software that provides data structures that water resources modelers are more accustomed to and allows them to take advantage of advanced computing resources for efficient simulations

Advancing the Open Modeling Interface (OpenMI) for Integrated Water Resources Modeling

The use of existing component-based modeling frameworks for integrated water resources modeling is currently hampered for some important use cases because they lack support for commonly used, topology-aware, spatiotemporal data structures. Additionally, existing frameworks are often accompanied by large software stacks with steep learning curves. Others lack specifications for deploying them on high performance, heterogeneous computing (HPC) infrastructure. This puts their use beyond the reach of many water resources modelers. In this paper, we describe new advances in component-based modeling using a framework called HydroCouple. This framework largely adopts the Open Modeling Interface (OpenMI) 2.0 interface definitions but demonstrates important advances for water resources modeling. HydroCouple explicitly defines standard and widely used geospatial data formats and provides interface definitions to support simulations on HPC infrastructure. In this paper, we illustrate how these advances can be used to develop efficient model components through a coupled urban stormwater modeling exercise

iSAW: Integrating Structure, Actors, and Water to Study Socio-Hydro-Ecological Systems

Urbanization, climate, and ecosystem change represent major challenges for managing water resources. Although water systems are complex, a need exists for a generalized representation of these systems to identify important components and linkages to guide scientific inquiry and aid water management. We developed an integrated Structure-Actor-Water framework (iSAW) to facilitate the understanding of and transitions to sustainable water systems. Our goal was to produce an interdisciplinary framework for water resources research that could address management challenges across scales (e.g., plot to region) and domains (e.g., water supply and quality, transitioning, and urban landscapes). The framework was designed to be generalizable across all human–environment systems, yet with sufficient detail and flexibility to be customized to specific cases. iSAW includes three major components: structure (natural, built, and social), actors (individual and organizational), and water (quality and quantity). Key linkages among these components include: (1) ecological/hydrologic processes, (2) ecosystem/geomorphic feedbacks, (3) planning, design, and policy, (4) perceptions, information, and experience, (5) resource access and risk, and (6) operational water use and management. We illustrate the flexibility and utility of the iSAW framework by applying it to two research and management problems: understanding urban water supply and demand in a changing climate and expanding use of green storm water infrastructure in a semi-arid environment. The applications demonstrate that a generalized conceptual model can identify important components and linkages in complex and diverse water systems and facilitate communication about those systems among researchers from diverse disciplines

Computational Penalties of Component Based Models: An Urban Stormwater Component-Based Modeling Application Using Open MI

Component-based environmental modeling, or loose model coupling, has been proposed as an alternative to traditional tight model coupling, which is characterized by inflexible and often large model codes with highly interdependent functions compiled into a single execution unit. Loosely coupling model components developed by decomposing complex systems into smaller or less complex independent units promises earth systems modelers: (1) an approach to better explore feedbacks between domains of different disciplines that are typically modeled independently, and (2) a way to experiment with different process formulations to select those that are most appropriate for a particular application. The additional function calls, data transformations, and discontinuity at the connection points between model components resulting from the use of component-based modeling may, however, give rise to computational penalties, including increased simulation time and mass balance error. In the study presented here, we sought to investigate these computational penalties as the number of coupled model components increases using the Open Modeling Interface (OpenMI), which is component-based modeling interface specification. A Stormwater Management Model (SWMM) application developed for the City of Logan, Utah, USA and run in its standard, tightly coupled configuration served as a reference against which several configurations of coupled OpenMI-compliant SWMM model components were compared. The various configurations of coupled OpenMI SWMM model components were derived by decomposing the reference SWMM model first by process (i.e., runoff coupled to routing) and then by space (i.e., catchments or groups of catchments coupled together). Results showed that simulation times increased linearly as the number of connections between model components increased. The results also showed that changes in total mass balance error introduced through coupling were dependent on how well each model component was able to resolve the time series data it received. This study also demonstrates and proposes some strategies to address these computational penalties in component-based modeling frameworks

Evaluating the simulation times and mass balance errors of component-based models: An application of OpenMI 2.0 to an urban stormwater system

In making the decision whether to use component-based modeling, its benefits must be balanced against computational costs. Studies evaluating these costs using the Open Modeling Interface (OpenMI) have largely used models with simplified formulations, small spatial and temporal domains, or a limited number of components. We evaluate these costs by applying OpenMI to a relatively complex Stormwater Management Model (SWMM) for the City of Logan, Utah, USA. Configurations of coupled OpenMI components resulting from decomposing the stormwater model by process (i.e., runoff coupled to routing) and then by space (i.e., groups of catchments coupled together) were compared to a reference model executed in the standard SWMM configuration. Simulation times increased linearly with the number of connections between components, and mass balance error was a function of the degree to which a component resolved time series data received. This study also examines and proposes some strategies to address these computational costs