- Principal investigator: J. David Moulton
- Use case leads: Xingyuan Chen, Laura Condon, Reed Maxwell, Sergi Molins, Scott Painter, Steven Smith
- Use cases: ideas-productivity.org/ideasclassic/use-cases/
- Better Scientific Software community portal: bssw.io
Water resources are critically important for energy production, drinking water, agriculture, and ecosystem health, and they are under increasing pressure from growing demand, land-use change, and Earth system change. These stresses on the water supply are largely transmitted through the nation’s watersheds. To enable a robust, predictive understanding of how watersheds function and respond to perturbations as integrated hydro-biogeochemical systems, challenges in multiscale and multiphysics modeling must be overcome. At the same time, disruptive changes in computer architectures are creating significant uncertainty in programming models. This confluence of interdisciplinary challenges drives the Interoperable Design of Extreme-scale Application Software (IDEAS) family of projects to provide community-based approaches to software development. Within this family, the IDEAS–Watersheds project seeks to enhance scientific productivity through an agile approach centered on adapting modern software engineering tools, practices, and processes to build a flexible scientific software ecosystem. By tightly integrating modeling with observations and experiments, the Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) advances systems-level under-standing of how watersheds function and translates that understanding into advanced, science-based models of watershed systems.
The IDEAS–Watersheds project is organized around six research activities to address important scientific challenges and advance software development methodologies and engagement in the growing community-driven software ecosystem. The first three of these research activities encompass partnership activities, each undertaken jointly with one of SBR’s interdisciplinary Science Focus Areas (SFAs) at Lawrence Berkeley National Laboratory (LBNL), Oak Ridge National Laboratory (ORNL), and Pacific Northwest National Laboratory (PNNL). They address biogeochemical cycling in streams across a wide range of stream orders in disparate climates and land-use conditions.
LBNL Watershed Function SFA. Perturbations to mountainous watersheds (e.g., floods, drought, and early snowmelt) impact the downstream delivery of water, nutrients, carbon, and trace metals. Currently, no single model can capture all the relevant processes across this domain at fine resolution. The partnership activity with the LBNL SFA aims to develop a multiscale modeling framework that enables consideration of processes at different resolutions within the watershed, including the software tools and workflows required for this framework.
ORNL Critical Interfaces SFA. Metabolically active transient storage zones (MATSZs), regions surrounding stream channels where the downstream movement of water is delayed, are responsible for a significant portion of carbon, nutrient, and trace metal processing, thus affecting stream biogeochemistry and, ultimately, downstream water quality. The partnership activity with the ORNL SFA is developing a stream corridor modeling framework that allows laboratory-derived understanding of biogeochemical processes occurring in slow-flowing biogeochemical hotspots known as MATSZs to be combined with reach-scale observations. The partnership supports the overarching strategy of a multiscale river network modeling system to represent how MATSZs influence downstream water quality by processing carbon, nutrients, and trace metals.
PNNL River Corridor SFA. River corridor science is conducted in the context of larger watershed processes that define boundary fluxes and exert other controls on hydrological exchange, including interactions among variable river surface elevation (“stage”), hydromorphic setting, and hydrogeological heterogeneity to determine how those interactions influence river corridor hydro-biogeochemical function. Models must include land-surface and groundwater processes over domains much larger than the river corridor itself. The partnership activity with the PNNL SFA aims to enable fundamental understanding of the hydro-biogeochemical function of dynamic river corridor eco-systems and translate that understanding into predictive, interoperable models across watersheds.In addition to these three partnership activities, the IDEAS–Watersheds project encompasses three crosscutting research activities.
Continental United States (CONUS) Activity. Simulating integrated flow over continental scales at so-called hyper-resolution is an identified grand challenge in computational hydrology. To adequately capture feedbacks among deeper subsurface flow, the land energy budget, and the lower atmosphere, explicit connections must be made between these systems in large-scale models. The CONUS activity supports the development of an integrated hydrological modeling platform of CONUS using the ParFlow-Community Land Model (PF-CLM). The CONUS model bridges across IDEAS–Watersheds study areas and provides a scaling framework from the reach scale up to watershed and regional systems.
Reaction Network Activity. Reaction networks to describe biogeochemical transformations are a central component of SBR research. This activity bridges across the SFAs and develops process-explicit reaction models for aqueous complexation, surface complexation, mineral dissolution-precipitation, microbially mediated reactions, microbial dynamics, and similar processes.
Shared Infrastructure Activity. This activity coordinates development of the shared computational infrastructure by creating and advancing existing, multiscale workflow tools and software interfaces for transferring information across scales, customized meshing, and model-data integration, as well as interfaces to couple multiple process-based codes and support code interoperability.
Scientific and Community Impact
The IDEAS–Watersheds project has made significant progress in developing a flexible scientific software ecosystem to accelerate scientific discovery and understanding in environmental systems, including completion of open-source licensing and open access to source code repositories. In addition, code teams are adopting agile methodologies and developer workflows, improving sustainability while enhancing capabilities.